2024-03-11 23:34:29,688 INFO [train.py:805] (2/6) Training started
2024-03-11 23:34:29,689 INFO [train.py:815] (2/6) Device: cuda:2
2024-03-11 23:34:29,689 INFO [tts_datamodule.py:322] (2/6) About to get train cuts
2024-03-11 23:34:29,693 INFO [tts_datamodule.py:337] (2/6) About to get speakers
2024-03-11 23:34:29,694 INFO [train.py:827] (2/6) {'best_train_loss': inf, 'best_valid_loss': inf, 'best_train_epoch': -1, 'best_valid_epoch': -1, 'batch_idx_train': -1, 'log_interval': 50, 'valid_interval': 200, 'env_info': {'k2-version': '1.24.4', 'k2-build-type': 'Release', 'k2-with-cuda': True, 'k2-git-sha1': '2989b0b1186fa6022932804f5b39fbb2781ebf42', 'k2-git-date': 'Fri Nov 24 11:34:10 2023', 'lhotse-version': '1.22.0.dev+git.d8ed1bbb.dirty', 'torch-version': '1.11.0+cu102', 'torch-cuda-available': True, 'torch-cuda-version': '10.2', 'python-version': '3.9', 'icefall-git-branch': 'dev/tts/vctk/tokenizer', 'icefall-git-sha1': 'e69b60e5-clean', 'icefall-git-date': 'Mon Mar 11 23:14:14 2024', 'icefall-path': '/star-home/jinzengrui/lib/miniconda3/envs/dev39/lib/python3.9/site-packages/icefall-1.0-py3.9.egg', 'k2-path': '/star-home/jinzengrui/lib/miniconda3/envs/dev39/lib/python3.9/site-packages/k2-1.24.4.dev20231207+cuda10.2.torch1.11.0-py3.9-linux-x86_64.egg/k2/__init__.py', 'lhotse-path': '/star-home/jinzengrui/lib/miniconda3/envs/dev39/lib/python3.9/site-packages/lhotse-1.22.0.dev0+git.d8ed1bbb.dirty-py3.9.egg/lhotse/__init__.py', 'hostname': 'de-74279-k2-train-9-0208143539-7dbf569d4f-r7nrb', 'IP address': '10.177.13.150'}, 'sampling_rate': 22050, 'frame_shift': 256, 'frame_length': 1024, 'feature_dim': 513, 'n_mels': 80, 'lambda_adv': 1.0, 'lambda_mel': 45.0, 'lambda_feat_match': 2.0, 'lambda_dur': 1.0, 'lambda_kl': 1.0, 'world_size': 6, 'master_port': 12354, 'tensorboard': True, 'num_epochs': 1000, 'start_epoch': 1, 'exp_dir': PosixPath('vits/exp_fp32'), 'tokens': 'data/tokens.txt', 'lr': 0.0002, 'seed': 42, 'print_diagnostics': False, 'inf_check': False, 'save_every_n': 20, 'use_fp16': False, 'manifest_dir': PosixPath('data/spectrogram'), 'speakers': PosixPath('data/speakers.txt'), 'max_duration': 200, 'bucketing_sampler': True, 'num_buckets': 30, 'on_the_fly_feats': False, 'shuffle': True, 'drop_last': True, 'return_cuts': False, 'num_workers': 8, 'input_strategy': 'PrecomputedFeatures', 'blank_id': 0, 'vocab_size': 159, 'num_spks': 108}
2024-03-11 23:34:29,694 INFO [train.py:829] (2/6) About to create model
2024-03-11 23:34:32,707 INFO [train.py:835] (2/6) Number of parameters in generator: 39004210
2024-03-11 23:34:32,708 INFO [train.py:837] (2/6) Number of parameters in discriminator: 50974956
2024-03-11 23:34:32,709 INFO [train.py:838] (2/6) Total number of parameters: 89979166
2024-03-11 23:34:40,019 INFO [train.py:845] (2/6) Using DDP
2024-03-11 23:34:41,291 INFO [tts_datamodule.py:175] (2/6) About to create train dataset
2024-03-11 23:34:41,291 INFO [tts_datamodule.py:201] (2/6) Using DynamicBucketingSampler.
2024-03-11 23:34:42,543 INFO [tts_datamodule.py:218] (2/6) About to create train dataloader
2024-03-11 23:34:42,543 INFO [tts_datamodule.py:327] (2/6) About to get validation cuts
2024-03-11 23:34:42,545 INFO [tts_datamodule.py:241] (2/6) About to create dev dataset
2024-03-11 23:34:42,558 INFO [tts_datamodule.py:270] (2/6) About to create valid dataloader
2024-03-11 23:34:42,559 INFO [train.py:725] (2/6) Sanity check -- see if any of the batches in epoch 1 would cause OOM.
2024-03-11 23:35:04,648 INFO [train.py:780] (2/6) Maximum memory allocated so far is 11595MB
2024-03-11 23:35:06,681 INFO [train.py:780] (2/6) Maximum memory allocated so far is 11943MB
2024-03-11 23:35:10,802 INFO [train.py:780] (2/6) Maximum memory allocated so far is 19063MB
2024-03-11 23:35:13,714 INFO [train.py:780] (2/6) Maximum memory allocated so far is 19073MB
2024-03-11 23:35:18,922 INFO [train.py:780] (2/6) Maximum memory allocated so far is 27594MB
2024-03-11 23:35:22,790 INFO [train.py:780] (2/6) Maximum memory allocated so far is 27594MB
2024-03-11 23:35:22,802 INFO [train.py:919] (2/6) Start epoch 1
2024-03-11 23:35:44,652 INFO [train.py:527] (2/6) Epoch 1, batch 0, global_batch_idx: 0, batch size: 68, loss[discriminator_loss=6.107, discriminator_real_loss=6.106, discriminator_fake_loss=0.001034, generator_loss=1701, generator_mel_loss=107.1, generator_kl_loss=1587, generator_dur_loss=1.761, generator_adv_loss=4.809, generator_feat_match_loss=0.1753, over 68.00 samples.], tot_loss[discriminator_loss=6.107, discriminator_real_loss=6.106, discriminator_fake_loss=0.001034, generator_loss=1701, generator_mel_loss=107.1, generator_kl_loss=1587, generator_dur_loss=1.761, generator_adv_loss=4.809, generator_feat_match_loss=0.1753, over 68.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-11 23:35:44,654 INFO [train.py:581] (2/6) Computing validation loss
2024-03-11 23:35:53,001 INFO [train.py:591] (2/6) Epoch 1, validation: discriminator_loss=4.882, discriminator_real_loss=4.807, discriminator_fake_loss=0.07482, generator_loss=763.5, generator_mel_loss=112.9, generator_kl_loss=643.8, generator_dur_loss=1.851, generator_adv_loss=4.809, generator_feat_match_loss=0.1531, over 100.00 samples.
2024-03-11 23:35:53,003 INFO [train.py:592] (2/6) Maximum memory allocated so far is 27594MB
2024-03-11 23:38:13,684 INFO [train.py:527] (2/6) Epoch 1, batch 50, global_batch_idx: 50, batch size: 56, loss[discriminator_loss=2.758, discriminator_real_loss=1.451, discriminator_fake_loss=1.306, generator_loss=119.3, generator_mel_loss=50.2, generator_kl_loss=63.98, generator_dur_loss=1.677, generator_adv_loss=1.824, generator_feat_match_loss=1.596, over 56.00 samples.], tot_loss[discriminator_loss=3.146, discriminator_real_loss=1.812, discriminator_fake_loss=1.333, generator_loss=232.9, generator_mel_loss=63.89, generator_kl_loss=165, generator_dur_loss=1.666, generator_adv_loss=1.816, generator_feat_match_loss=0.5115, over 2958.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-11 23:40:30,896 INFO [train.py:527] (2/6) Epoch 1, batch 100, global_batch_idx: 100, batch size: 50, loss[discriminator_loss=2.603, discriminator_real_loss=1.464, discriminator_fake_loss=1.139, generator_loss=89.04, generator_mel_loss=50.11, generator_kl_loss=33.67, generator_dur_loss=1.727, generator_adv_loss=1.825, generator_feat_match_loss=1.715, over 50.00 samples.], tot_loss[discriminator_loss=2.934, discriminator_real_loss=1.654, discriminator_fake_loss=1.279, generator_loss=167, generator_mel_loss=55.96, generator_kl_loss=106.4, generator_dur_loss=1.684, generator_adv_loss=1.854, generator_feat_match_loss=1.055, over 5920.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-11 23:41:35,218 INFO [train.py:919] (2/6) Start epoch 2
2024-03-11 23:43:11,632 INFO [train.py:527] (2/6) Epoch 2, batch 26, global_batch_idx: 150, batch size: 39, loss[discriminator_loss=2.786, discriminator_real_loss=1.293, discriminator_fake_loss=1.493, generator_loss=76.38, generator_mel_loss=47.25, generator_kl_loss=24.19, generator_dur_loss=1.816, generator_adv_loss=1.719, generator_feat_match_loss=1.406, over 39.00 samples.], tot_loss[discriminator_loss=2.809, discriminator_real_loss=1.508, discriminator_fake_loss=1.301, generator_loss=75.41, generator_mel_loss=43.7, generator_kl_loss=26.37, generator_dur_loss=1.83, generator_adv_loss=1.925, generator_feat_match_loss=1.581, over 1686.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-11 23:45:31,879 INFO [train.py:527] (2/6) Epoch 2, batch 76, global_batch_idx: 200, batch size: 64, loss[discriminator_loss=2.891, discriminator_real_loss=1.593, discriminator_fake_loss=1.298, generator_loss=61.48, generator_mel_loss=40.76, generator_kl_loss=15.87, generator_dur_loss=1.919, generator_adv_loss=1.77, generator_feat_match_loss=1.166, over 64.00 samples.], tot_loss[discriminator_loss=2.82, discriminator_real_loss=1.521, discriminator_fake_loss=1.299, generator_loss=70.25, generator_mel_loss=42.74, generator_kl_loss=22.23, generator_dur_loss=1.853, generator_adv_loss=1.901, generator_feat_match_loss=1.522, over 4723.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-11 23:45:31,881 INFO [train.py:581] (2/6) Computing validation loss
2024-03-11 23:45:39,717 INFO [train.py:591] (2/6) Epoch 2, validation: discriminator_loss=2.887, discriminator_real_loss=1.544, discriminator_fake_loss=1.343, generator_loss=55.76, generator_mel_loss=38.74, generator_kl_loss=12.24, generator_dur_loss=2.086, generator_adv_loss=1.775, generator_feat_match_loss=0.9245, over 100.00 samples.
2024-03-11 23:45:39,718 INFO [train.py:592] (2/6) Maximum memory allocated so far is 28618MB
2024-03-11 23:47:45,223 INFO [train.py:919] (2/6) Start epoch 3
2024-03-11 23:48:14,650 INFO [train.py:527] (2/6) Epoch 3, batch 2, global_batch_idx: 250, batch size: 68, loss[discriminator_loss=2.96, discriminator_real_loss=1.635, discriminator_fake_loss=1.325, generator_loss=53.63, generator_mel_loss=35.39, generator_kl_loss=13.89, generator_dur_loss=1.949, generator_adv_loss=1.733, generator_feat_match_loss=0.6746, over 68.00 samples.], tot_loss[discriminator_loss=2.897, discriminator_real_loss=1.518, discriminator_fake_loss=1.379, generator_loss=55.71, generator_mel_loss=37.15, generator_kl_loss=14.09, generator_dur_loss=1.919, generator_adv_loss=1.767, generator_feat_match_loss=0.7744, over 184.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-11 23:50:34,598 INFO [train.py:527] (2/6) Epoch 3, batch 52, global_batch_idx: 300, batch size: 36, loss[discriminator_loss=3.025, discriminator_real_loss=1.535, discriminator_fake_loss=1.491, generator_loss=50.89, generator_mel_loss=36.2, generator_kl_loss=9.953, generator_dur_loss=1.906, generator_adv_loss=1.808, generator_feat_match_loss=1.017, over 36.00 samples.], tot_loss[discriminator_loss=2.88, discriminator_real_loss=1.465, discriminator_fake_loss=1.416, generator_loss=53.59, generator_mel_loss=36.82, generator_kl_loss=12.24, generator_dur_loss=1.92, generator_adv_loss=1.689, generator_feat_match_loss=0.9208, over 3014.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-11 23:52:54,841 INFO [train.py:527] (2/6) Epoch 3, batch 102, global_batch_idx: 350, batch size: 52, loss[discriminator_loss=2.899, discriminator_real_loss=1.687, discriminator_fake_loss=1.211, generator_loss=47.41, generator_mel_loss=33.79, generator_kl_loss=8.922, generator_dur_loss=1.911, generator_adv_loss=1.769, generator_feat_match_loss=1.017, over 52.00 samples.], tot_loss[discriminator_loss=2.865, discriminator_real_loss=1.471, discriminator_fake_loss=1.395, generator_loss=51.99, generator_mel_loss=36.31, generator_kl_loss=11.01, generator_dur_loss=1.923, generator_adv_loss=1.727, generator_feat_match_loss=1.023, over 5772.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-11 23:53:55,511 INFO [train.py:919] (2/6) Start epoch 4
2024-03-11 23:55:37,836 INFO [train.py:527] (2/6) Epoch 4, batch 28, global_batch_idx: 400, batch size: 70, loss[discriminator_loss=2.605, discriminator_real_loss=1.336, discriminator_fake_loss=1.269, generator_loss=46.45, generator_mel_loss=33.33, generator_kl_loss=7.548, generator_dur_loss=1.933, generator_adv_loss=1.853, generator_feat_match_loss=1.784, over 70.00 samples.], tot_loss[discriminator_loss=2.762, discriminator_real_loss=1.475, discriminator_fake_loss=1.287, generator_loss=46.6, generator_mel_loss=33.4, generator_kl_loss=7.917, generator_dur_loss=1.947, generator_adv_loss=1.863, generator_feat_match_loss=1.47, over 1704.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-11 23:55:37,837 INFO [train.py:581] (2/6) Computing validation loss
2024-03-11 23:55:46,452 INFO [train.py:591] (2/6) Epoch 4, validation: discriminator_loss=2.851, discriminator_real_loss=1.361, discriminator_fake_loss=1.49, generator_loss=43.7, generator_mel_loss=32.79, generator_kl_loss=5.991, generator_dur_loss=2.147, generator_adv_loss=1.682, generator_feat_match_loss=1.097, over 100.00 samples.
2024-03-11 23:55:46,454 INFO [train.py:592] (2/6) Maximum memory allocated so far is 28618MB
2024-03-11 23:58:04,894 INFO [train.py:527] (2/6) Epoch 4, batch 78, global_batch_idx: 450, batch size: 96, loss[discriminator_loss=2.638, discriminator_real_loss=1.272, discriminator_fake_loss=1.366, generator_loss=43.82, generator_mel_loss=31.9, generator_kl_loss=6.052, generator_dur_loss=2.064, generator_adv_loss=1.93, generator_feat_match_loss=1.87, over 96.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.432, discriminator_fake_loss=1.294, generator_loss=45.62, generator_mel_loss=33.03, generator_kl_loss=7.148, generator_dur_loss=1.946, generator_adv_loss=1.878, generator_feat_match_loss=1.625, over 4530.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 00:00:09,413 INFO [train.py:919] (2/6) Start epoch 5
2024-03-12 00:00:45,104 INFO [train.py:527] (2/6) Epoch 5, batch 4, global_batch_idx: 500, batch size: 96, loss[discriminator_loss=2.735, discriminator_real_loss=1.417, discriminator_fake_loss=1.318, generator_loss=43.54, generator_mel_loss=32.18, generator_kl_loss=5.769, generator_dur_loss=1.976, generator_adv_loss=1.874, generator_feat_match_loss=1.743, over 96.00 samples.], tot_loss[discriminator_loss=2.753, discriminator_real_loss=1.447, discriminator_fake_loss=1.307, generator_loss=43.21, generator_mel_loss=31.98, generator_kl_loss=5.833, generator_dur_loss=1.976, generator_adv_loss=1.833, generator_feat_match_loss=1.595, over 366.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 00:03:05,358 INFO [train.py:527] (2/6) Epoch 5, batch 54, global_batch_idx: 550, batch size: 58, loss[discriminator_loss=2.769, discriminator_real_loss=1.513, discriminator_fake_loss=1.257, generator_loss=40.1, generator_mel_loss=30.47, generator_kl_loss=4.143, generator_dur_loss=1.993, generator_adv_loss=2.032, generator_feat_match_loss=1.459, over 58.00 samples.], tot_loss[discriminator_loss=2.751, discriminator_real_loss=1.415, discriminator_fake_loss=1.335, generator_loss=41.55, generator_mel_loss=30.96, generator_kl_loss=5.179, generator_dur_loss=1.959, generator_adv_loss=1.832, generator_feat_match_loss=1.62, over 3233.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 00:05:22,098 INFO [train.py:527] (2/6) Epoch 5, batch 104, global_batch_idx: 600, batch size: 70, loss[discriminator_loss=2.777, discriminator_real_loss=1.602, discriminator_fake_loss=1.175, generator_loss=39.7, generator_mel_loss=30.08, generator_kl_loss=4.228, generator_dur_loss=1.967, generator_adv_loss=1.892, generator_feat_match_loss=1.534, over 70.00 samples.], tot_loss[discriminator_loss=2.736, discriminator_real_loss=1.426, discriminator_fake_loss=1.31, generator_loss=40.66, generator_mel_loss=30.36, generator_kl_loss=4.808, generator_dur_loss=1.955, generator_adv_loss=1.863, generator_feat_match_loss=1.681, over 6038.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 00:05:22,100 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 00:05:31,118 INFO [train.py:591] (2/6) Epoch 5, validation: discriminator_loss=2.816, discriminator_real_loss=1.506, discriminator_fake_loss=1.31, generator_loss=36.96, generator_mel_loss=28.4, generator_kl_loss=3.509, generator_dur_loss=2.138, generator_adv_loss=1.789, generator_feat_match_loss=1.124, over 100.00 samples.
2024-03-12 00:05:31,118 INFO [train.py:592] (2/6) Maximum memory allocated so far is 28876MB
2024-03-12 00:06:23,943 INFO [train.py:919] (2/6) Start epoch 6
2024-03-12 00:08:08,935 INFO [train.py:527] (2/6) Epoch 6, batch 30, global_batch_idx: 650, batch size: 59, loss[discriminator_loss=2.877, discriminator_real_loss=1.384, discriminator_fake_loss=1.493, generator_loss=38.12, generator_mel_loss=29.01, generator_kl_loss=3.731, generator_dur_loss=1.915, generator_adv_loss=1.668, generator_feat_match_loss=1.793, over 59.00 samples.], tot_loss[discriminator_loss=2.788, discriminator_real_loss=1.472, discriminator_fake_loss=1.316, generator_loss=38.28, generator_mel_loss=28.91, generator_kl_loss=3.822, generator_dur_loss=1.945, generator_adv_loss=1.893, generator_feat_match_loss=1.708, over 1796.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 00:10:28,031 INFO [train.py:527] (2/6) Epoch 6, batch 80, global_batch_idx: 700, batch size: 55, loss[discriminator_loss=2.847, discriminator_real_loss=1.321, discriminator_fake_loss=1.526, generator_loss=37.39, generator_mel_loss=28.23, generator_kl_loss=3.489, generator_dur_loss=1.914, generator_adv_loss=2.109, generator_feat_match_loss=1.644, over 55.00 samples.], tot_loss[discriminator_loss=2.739, discriminator_real_loss=1.431, discriminator_fake_loss=1.308, generator_loss=37.82, generator_mel_loss=28.56, generator_kl_loss=3.641, generator_dur_loss=1.959, generator_adv_loss=1.891, generator_feat_match_loss=1.769, over 4809.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 00:12:30,178 INFO [train.py:919] (2/6) Start epoch 7
2024-03-12 00:13:11,136 INFO [train.py:527] (2/6) Epoch 7, batch 6, global_batch_idx: 750, batch size: 44, loss[discriminator_loss=2.667, discriminator_real_loss=1.277, discriminator_fake_loss=1.39, generator_loss=36.86, generator_mel_loss=28.01, generator_kl_loss=2.979, generator_dur_loss=1.924, generator_adv_loss=2.012, generator_feat_match_loss=1.931, over 44.00 samples.], tot_loss[discriminator_loss=2.76, discriminator_real_loss=1.381, discriminator_fake_loss=1.379, generator_loss=36.65, generator_mel_loss=27.95, generator_kl_loss=3.059, generator_dur_loss=1.924, generator_adv_loss=1.907, generator_feat_match_loss=1.81, over 311.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 00:15:30,277 INFO [train.py:527] (2/6) Epoch 7, batch 56, global_batch_idx: 800, batch size: 70, loss[discriminator_loss=2.845, discriminator_real_loss=1.567, discriminator_fake_loss=1.279, generator_loss=34.71, generator_mel_loss=26.72, generator_kl_loss=2.747, generator_dur_loss=1.954, generator_adv_loss=1.969, generator_feat_match_loss=1.326, over 70.00 samples.], tot_loss[discriminator_loss=2.765, discriminator_real_loss=1.445, discriminator_fake_loss=1.32, generator_loss=36.1, generator_mel_loss=27.53, generator_kl_loss=2.922, generator_dur_loss=1.955, generator_adv_loss=1.916, generator_feat_match_loss=1.783, over 3145.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 00:15:30,278 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 00:15:38,549 INFO [train.py:591] (2/6) Epoch 7, validation: discriminator_loss=2.831, discriminator_real_loss=1.662, discriminator_fake_loss=1.168, generator_loss=33.21, generator_mel_loss=25.58, generator_kl_loss=2.468, generator_dur_loss=2.112, generator_adv_loss=1.932, generator_feat_match_loss=1.119, over 100.00 samples.
2024-03-12 00:15:38,550 INFO [train.py:592] (2/6) Maximum memory allocated so far is 28876MB
2024-03-12 00:17:56,799 INFO [train.py:527] (2/6) Epoch 7, batch 106, global_batch_idx: 850, batch size: 15, loss[discriminator_loss=2.43, discriminator_real_loss=1.295, discriminator_fake_loss=1.134, generator_loss=40.58, generator_mel_loss=30.84, generator_kl_loss=2.961, generator_dur_loss=1.85, generator_adv_loss=2.075, generator_feat_match_loss=2.848, over 15.00 samples.], tot_loss[discriminator_loss=2.759, discriminator_real_loss=1.446, discriminator_fake_loss=1.314, generator_loss=35.64, generator_mel_loss=27.23, generator_kl_loss=2.803, generator_dur_loss=1.957, generator_adv_loss=1.894, generator_feat_match_loss=1.754, over 5914.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 00:18:47,284 INFO [train.py:919] (2/6) Start epoch 8
2024-03-12 00:20:42,551 INFO [train.py:527] (2/6) Epoch 8, batch 32, global_batch_idx: 900, batch size: 74, loss[discriminator_loss=2.773, discriminator_real_loss=1.43, discriminator_fake_loss=1.342, generator_loss=33.5, generator_mel_loss=25.7, generator_kl_loss=2.42, generator_dur_loss=2.019, generator_adv_loss=1.739, generator_feat_match_loss=1.627, over 74.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.429, discriminator_fake_loss=1.291, generator_loss=34.99, generator_mel_loss=26.77, generator_kl_loss=2.479, generator_dur_loss=1.955, generator_adv_loss=1.904, generator_feat_match_loss=1.878, over 1767.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 00:23:05,280 INFO [train.py:527] (2/6) Epoch 8, batch 82, global_batch_idx: 950, batch size: 53, loss[discriminator_loss=2.768, discriminator_real_loss=1.507, discriminator_fake_loss=1.261, generator_loss=33.02, generator_mel_loss=25.33, generator_kl_loss=2.303, generator_dur_loss=1.945, generator_adv_loss=1.851, generator_feat_match_loss=1.599, over 53.00 samples.], tot_loss[discriminator_loss=2.729, discriminator_real_loss=1.432, discriminator_fake_loss=1.297, generator_loss=34.95, generator_mel_loss=26.75, generator_kl_loss=2.394, generator_dur_loss=1.948, generator_adv_loss=1.919, generator_feat_match_loss=1.935, over 4493.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 00:24:59,524 INFO [train.py:919] (2/6) Start epoch 9
2024-03-12 00:25:44,816 INFO [train.py:527] (2/6) Epoch 9, batch 8, global_batch_idx: 1000, batch size: 39, loss[discriminator_loss=2.727, discriminator_real_loss=1.517, discriminator_fake_loss=1.21, generator_loss=32.14, generator_mel_loss=24.45, generator_kl_loss=2.061, generator_dur_loss=1.955, generator_adv_loss=1.911, generator_feat_match_loss=1.767, over 39.00 samples.], tot_loss[discriminator_loss=2.711, discriminator_real_loss=1.385, discriminator_fake_loss=1.326, generator_loss=33.75, generator_mel_loss=25.88, generator_kl_loss=2.188, generator_dur_loss=1.977, generator_adv_loss=1.852, generator_feat_match_loss=1.852, over 494.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 00:25:44,819 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 00:25:52,726 INFO [train.py:591] (2/6) Epoch 9, validation: discriminator_loss=2.716, discriminator_real_loss=1.498, discriminator_fake_loss=1.218, generator_loss=34.19, generator_mel_loss=26.16, generator_kl_loss=2.238, generator_dur_loss=2.052, generator_adv_loss=1.915, generator_feat_match_loss=1.823, over 100.00 samples.
2024-03-12 00:25:52,728 INFO [train.py:592] (2/6) Maximum memory allocated so far is 28876MB
2024-03-12 00:28:16,629 INFO [train.py:527] (2/6) Epoch 9, batch 58, global_batch_idx: 1050, batch size: 59, loss[discriminator_loss=2.67, discriminator_real_loss=1.294, discriminator_fake_loss=1.375, generator_loss=35.67, generator_mel_loss=27.12, generator_kl_loss=2.171, generator_dur_loss=1.913, generator_adv_loss=2.199, generator_feat_match_loss=2.269, over 59.00 samples.], tot_loss[discriminator_loss=2.69, discriminator_real_loss=1.401, discriminator_fake_loss=1.289, generator_loss=34.14, generator_mel_loss=26.1, generator_kl_loss=2.172, generator_dur_loss=1.959, generator_adv_loss=1.911, generator_feat_match_loss=1.999, over 3212.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 00:30:36,565 INFO [train.py:527] (2/6) Epoch 9, batch 108, global_batch_idx: 1100, batch size: 58, loss[discriminator_loss=2.79, discriminator_real_loss=1.479, discriminator_fake_loss=1.311, generator_loss=33.23, generator_mel_loss=25.1, generator_kl_loss=2.101, generator_dur_loss=1.943, generator_adv_loss=2.244, generator_feat_match_loss=1.839, over 58.00 samples.], tot_loss[discriminator_loss=2.696, discriminator_real_loss=1.402, discriminator_fake_loss=1.294, generator_loss=33.99, generator_mel_loss=25.99, generator_kl_loss=2.126, generator_dur_loss=1.953, generator_adv_loss=1.913, generator_feat_match_loss=2.014, over 6022.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 00:31:17,559 INFO [train.py:919] (2/6) Start epoch 10
2024-03-12 00:33:17,575 INFO [train.py:527] (2/6) Epoch 10, batch 34, global_batch_idx: 1150, batch size: 44, loss[discriminator_loss=2.677, discriminator_real_loss=1.373, discriminator_fake_loss=1.305, generator_loss=32.5, generator_mel_loss=24.48, generator_kl_loss=1.877, generator_dur_loss=1.935, generator_adv_loss=2.198, generator_feat_match_loss=2.014, over 44.00 samples.], tot_loss[discriminator_loss=2.674, discriminator_real_loss=1.395, discriminator_fake_loss=1.28, generator_loss=33.62, generator_mel_loss=25.7, generator_kl_loss=1.933, generator_dur_loss=1.918, generator_adv_loss=1.948, generator_feat_match_loss=2.121, over 1931.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 00:35:38,769 INFO [train.py:527] (2/6) Epoch 10, batch 84, global_batch_idx: 1200, batch size: 25, loss[discriminator_loss=2.667, discriminator_real_loss=1.475, discriminator_fake_loss=1.192, generator_loss=34.9, generator_mel_loss=27.33, generator_kl_loss=1.892, generator_dur_loss=1.849, generator_adv_loss=1.7, generator_feat_match_loss=2.133, over 25.00 samples.], tot_loss[discriminator_loss=2.682, discriminator_real_loss=1.402, discriminator_fake_loss=1.28, generator_loss=33.57, generator_mel_loss=25.71, generator_kl_loss=1.856, generator_dur_loss=1.918, generator_adv_loss=1.95, generator_feat_match_loss=2.133, over 4624.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 00:35:38,770 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 00:35:47,142 INFO [train.py:591] (2/6) Epoch 10, validation: discriminator_loss=2.786, discriminator_real_loss=1.171, discriminator_fake_loss=1.615, generator_loss=31.34, generator_mel_loss=24.62, generator_kl_loss=1.472, generator_dur_loss=2.13, generator_adv_loss=1.501, generator_feat_match_loss=1.612, over 100.00 samples.
2024-03-12 00:35:47,143 INFO [train.py:592] (2/6) Maximum memory allocated so far is 28876MB
2024-03-12 00:37:36,240 INFO [train.py:919] (2/6) Start epoch 11
2024-03-12 00:38:30,466 INFO [train.py:527] (2/6) Epoch 11, batch 10, global_batch_idx: 1250, batch size: 68, loss[discriminator_loss=2.66, discriminator_real_loss=1.459, discriminator_fake_loss=1.201, generator_loss=33.99, generator_mel_loss=26.1, generator_kl_loss=1.753, generator_dur_loss=1.996, generator_adv_loss=1.97, generator_feat_match_loss=2.167, over 68.00 samples.], tot_loss[discriminator_loss=2.672, discriminator_real_loss=1.404, discriminator_fake_loss=1.268, generator_loss=33.47, generator_mel_loss=25.75, generator_kl_loss=1.699, generator_dur_loss=1.923, generator_adv_loss=1.943, generator_feat_match_loss=2.147, over 593.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 00:40:53,322 INFO [train.py:527] (2/6) Epoch 11, batch 60, global_batch_idx: 1300, batch size: 36, loss[discriminator_loss=2.732, discriminator_real_loss=1.424, discriminator_fake_loss=1.308, generator_loss=33.01, generator_mel_loss=25.15, generator_kl_loss=1.674, generator_dur_loss=1.909, generator_adv_loss=2.05, generator_feat_match_loss=2.234, over 36.00 samples.], tot_loss[discriminator_loss=2.696, discriminator_real_loss=1.413, discriminator_fake_loss=1.283, generator_loss=32.87, generator_mel_loss=25.21, generator_kl_loss=1.654, generator_dur_loss=1.955, generator_adv_loss=1.936, generator_feat_match_loss=2.122, over 3289.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 00:43:12,125 INFO [train.py:527] (2/6) Epoch 11, batch 110, global_batch_idx: 1350, batch size: 66, loss[discriminator_loss=2.512, discriminator_real_loss=1.254, discriminator_fake_loss=1.257, generator_loss=33.51, generator_mel_loss=25.35, generator_kl_loss=1.46, generator_dur_loss=1.992, generator_adv_loss=2.086, generator_feat_match_loss=2.627, over 66.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.401, discriminator_fake_loss=1.284, generator_loss=32.83, generator_mel_loss=25.13, generator_kl_loss=1.617, generator_dur_loss=1.967, generator_adv_loss=1.952, generator_feat_match_loss=2.17, over 6355.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 00:43:49,494 INFO [train.py:919] (2/6) Start epoch 12
2024-03-12 00:45:56,714 INFO [train.py:527] (2/6) Epoch 12, batch 36, global_batch_idx: 1400, batch size: 44, loss[discriminator_loss=2.838, discriminator_real_loss=1.551, discriminator_fake_loss=1.286, generator_loss=32.64, generator_mel_loss=25.48, generator_kl_loss=1.538, generator_dur_loss=1.927, generator_adv_loss=1.676, generator_feat_match_loss=2.012, over 44.00 samples.], tot_loss[discriminator_loss=2.739, discriminator_real_loss=1.424, discriminator_fake_loss=1.315, generator_loss=32.89, generator_mel_loss=25.16, generator_kl_loss=1.519, generator_dur_loss=1.974, generator_adv_loss=1.991, generator_feat_match_loss=2.247, over 2124.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 00:45:56,715 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 00:46:04,726 INFO [train.py:591] (2/6) Epoch 12, validation: discriminator_loss=2.896, discriminator_real_loss=1.381, discriminator_fake_loss=1.515, generator_loss=31.16, generator_mel_loss=24.6, generator_kl_loss=1.302, generator_dur_loss=2.125, generator_adv_loss=1.658, generator_feat_match_loss=1.471, over 100.00 samples.
2024-03-12 00:46:04,727 INFO [train.py:592] (2/6) Maximum memory allocated so far is 28876MB
2024-03-12 00:48:26,162 INFO [train.py:527] (2/6) Epoch 12, batch 86, global_batch_idx: 1450, batch size: 17, loss[discriminator_loss=2.797, discriminator_real_loss=1.535, discriminator_fake_loss=1.261, generator_loss=31.26, generator_mel_loss=24.56, generator_kl_loss=1.62, generator_dur_loss=1.739, generator_adv_loss=1.792, generator_feat_match_loss=1.544, over 17.00 samples.], tot_loss[discriminator_loss=2.731, discriminator_real_loss=1.419, discriminator_fake_loss=1.312, generator_loss=32.53, generator_mel_loss=25.03, generator_kl_loss=1.514, generator_dur_loss=1.969, generator_adv_loss=1.928, generator_feat_match_loss=2.093, over 4974.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 00:50:11,950 INFO [train.py:919] (2/6) Start epoch 13
2024-03-12 00:51:09,430 INFO [train.py:527] (2/6) Epoch 13, batch 12, global_batch_idx: 1500, batch size: 31, loss[discriminator_loss=2.679, discriminator_real_loss=1.405, discriminator_fake_loss=1.274, generator_loss=33.44, generator_mel_loss=25.58, generator_kl_loss=1.568, generator_dur_loss=1.84, generator_adv_loss=1.913, generator_feat_match_loss=2.538, over 31.00 samples.], tot_loss[discriminator_loss=2.704, discriminator_real_loss=1.414, discriminator_fake_loss=1.29, generator_loss=32.54, generator_mel_loss=24.93, generator_kl_loss=1.46, generator_dur_loss=1.974, generator_adv_loss=1.979, generator_feat_match_loss=2.196, over 722.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 00:53:26,366 INFO [train.py:527] (2/6) Epoch 13, batch 62, global_batch_idx: 1550, batch size: 58, loss[discriminator_loss=2.801, discriminator_real_loss=1.75, discriminator_fake_loss=1.051, generator_loss=32.3, generator_mel_loss=24.95, generator_kl_loss=1.381, generator_dur_loss=1.989, generator_adv_loss=1.949, generator_feat_match_loss=2.031, over 58.00 samples.], tot_loss[discriminator_loss=2.734, discriminator_real_loss=1.426, discriminator_fake_loss=1.309, generator_loss=32.03, generator_mel_loss=24.61, generator_kl_loss=1.436, generator_dur_loss=1.974, generator_adv_loss=1.919, generator_feat_match_loss=2.092, over 3812.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 00:55:42,373 INFO [train.py:527] (2/6) Epoch 13, batch 112, global_batch_idx: 1600, batch size: 77, loss[discriminator_loss=2.629, discriminator_real_loss=1.234, discriminator_fake_loss=1.395, generator_loss=33.84, generator_mel_loss=25.84, generator_kl_loss=1.618, generator_dur_loss=2.059, generator_adv_loss=1.962, generator_feat_match_loss=2.364, over 77.00 samples.], tot_loss[discriminator_loss=2.737, discriminator_real_loss=1.424, discriminator_fake_loss=1.313, generator_loss=31.98, generator_mel_loss=24.58, generator_kl_loss=1.445, generator_dur_loss=1.976, generator_adv_loss=1.901, generator_feat_match_loss=2.069, over 6819.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 00:55:42,374 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 00:55:51,189 INFO [train.py:591] (2/6) Epoch 13, validation: discriminator_loss=2.687, discriminator_real_loss=1.474, discriminator_fake_loss=1.213, generator_loss=31.94, generator_mel_loss=25.06, generator_kl_loss=1.229, generator_dur_loss=2.103, generator_adv_loss=1.918, generator_feat_match_loss=1.634, over 100.00 samples.
2024-03-12 00:55:51,190 INFO [train.py:592] (2/6) Maximum memory allocated so far is 28876MB
2024-03-12 00:56:23,071 INFO [train.py:919] (2/6) Start epoch 14
2024-03-12 00:58:32,800 INFO [train.py:527] (2/6) Epoch 14, batch 38, global_batch_idx: 1650, batch size: 72, loss[discriminator_loss=2.799, discriminator_real_loss=1.459, discriminator_fake_loss=1.339, generator_loss=31.15, generator_mel_loss=23.94, generator_kl_loss=1.283, generator_dur_loss=2.023, generator_adv_loss=1.977, generator_feat_match_loss=1.928, over 72.00 samples.], tot_loss[discriminator_loss=2.729, discriminator_real_loss=1.405, discriminator_fake_loss=1.324, generator_loss=32.28, generator_mel_loss=24.84, generator_kl_loss=1.386, generator_dur_loss=1.967, generator_adv_loss=1.923, generator_feat_match_loss=2.159, over 2113.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 01:00:50,087 INFO [train.py:527] (2/6) Epoch 14, batch 88, global_batch_idx: 1700, batch size: 42, loss[discriminator_loss=2.767, discriminator_real_loss=1.401, discriminator_fake_loss=1.366, generator_loss=31.72, generator_mel_loss=24.45, generator_kl_loss=1.319, generator_dur_loss=1.98, generator_adv_loss=1.9, generator_feat_match_loss=2.068, over 42.00 samples.], tot_loss[discriminator_loss=2.735, discriminator_real_loss=1.409, discriminator_fake_loss=1.326, generator_loss=31.96, generator_mel_loss=24.57, generator_kl_loss=1.375, generator_dur_loss=1.966, generator_adv_loss=1.917, generator_feat_match_loss=2.136, over 4749.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 01:02:30,058 INFO [train.py:919] (2/6) Start epoch 15
2024-03-12 01:03:32,312 INFO [train.py:527] (2/6) Epoch 15, batch 14, global_batch_idx: 1750, batch size: 53, loss[discriminator_loss=2.782, discriminator_real_loss=1.371, discriminator_fake_loss=1.411, generator_loss=30.13, generator_mel_loss=23.31, generator_kl_loss=1.326, generator_dur_loss=1.906, generator_adv_loss=1.885, generator_feat_match_loss=1.698, over 53.00 samples.], tot_loss[discriminator_loss=2.766, discriminator_real_loss=1.406, discriminator_fake_loss=1.36, generator_loss=30.87, generator_mel_loss=23.77, generator_kl_loss=1.332, generator_dur_loss=1.984, generator_adv_loss=1.846, generator_feat_match_loss=1.936, over 889.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 01:05:50,162 INFO [train.py:527] (2/6) Epoch 15, batch 64, global_batch_idx: 1800, batch size: 55, loss[discriminator_loss=2.748, discriminator_real_loss=1.453, discriminator_fake_loss=1.295, generator_loss=31.58, generator_mel_loss=24.3, generator_kl_loss=1.42, generator_dur_loss=1.937, generator_adv_loss=1.948, generator_feat_match_loss=1.972, over 55.00 samples.], tot_loss[discriminator_loss=2.762, discriminator_real_loss=1.417, discriminator_fake_loss=1.344, generator_loss=31.29, generator_mel_loss=24.12, generator_kl_loss=1.328, generator_dur_loss=1.979, generator_adv_loss=1.86, generator_feat_match_loss=2.003, over 3804.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 01:05:50,164 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 01:05:57,891 INFO [train.py:591] (2/6) Epoch 15, validation: discriminator_loss=2.818, discriminator_real_loss=1.518, discriminator_fake_loss=1.3, generator_loss=31.04, generator_mel_loss=24.12, generator_kl_loss=1.255, generator_dur_loss=2.117, generator_adv_loss=1.833, generator_feat_match_loss=1.711, over 100.00 samples.
2024-03-12 01:05:57,892 INFO [train.py:592] (2/6) Maximum memory allocated so far is 28876MB
2024-03-12 01:08:15,700 INFO [train.py:527] (2/6) Epoch 15, batch 114, global_batch_idx: 1850, batch size: 88, loss[discriminator_loss=2.825, discriminator_real_loss=1.631, discriminator_fake_loss=1.194, generator_loss=30.98, generator_mel_loss=24.24, generator_kl_loss=1.17, generator_dur_loss=2.077, generator_adv_loss=1.673, generator_feat_match_loss=1.814, over 88.00 samples.], tot_loss[discriminator_loss=2.762, discriminator_real_loss=1.426, discriminator_fake_loss=1.336, generator_loss=31.27, generator_mel_loss=24.09, generator_kl_loss=1.321, generator_dur_loss=1.98, generator_adv_loss=1.872, generator_feat_match_loss=2.006, over 6736.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 01:08:41,765 INFO [train.py:919] (2/6) Start epoch 16
2024-03-12 01:10:58,075 INFO [train.py:527] (2/6) Epoch 16, batch 40, global_batch_idx: 1900, batch size: 45, loss[discriminator_loss=2.776, discriminator_real_loss=1.57, discriminator_fake_loss=1.206, generator_loss=32.4, generator_mel_loss=25.47, generator_kl_loss=1.368, generator_dur_loss=1.87, generator_adv_loss=1.632, generator_feat_match_loss=2.064, over 45.00 samples.], tot_loss[discriminator_loss=2.742, discriminator_real_loss=1.408, discriminator_fake_loss=1.334, generator_loss=31.41, generator_mel_loss=24.23, generator_kl_loss=1.295, generator_dur_loss=1.985, generator_adv_loss=1.868, generator_feat_match_loss=2.037, over 2496.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 01:13:14,058 INFO [train.py:527] (2/6) Epoch 16, batch 90, global_batch_idx: 1950, batch size: 58, loss[discriminator_loss=2.683, discriminator_real_loss=1.287, discriminator_fake_loss=1.396, generator_loss=31.91, generator_mel_loss=24.54, generator_kl_loss=1.222, generator_dur_loss=2.016, generator_adv_loss=1.841, generator_feat_match_loss=2.287, over 58.00 samples.], tot_loss[discriminator_loss=2.754, discriminator_real_loss=1.416, discriminator_fake_loss=1.338, generator_loss=31.43, generator_mel_loss=24.23, generator_kl_loss=1.304, generator_dur_loss=1.98, generator_adv_loss=1.873, generator_feat_match_loss=2.043, over 5368.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 01:14:46,779 INFO [train.py:919] (2/6) Start epoch 17
2024-03-12 01:15:55,086 INFO [train.py:527] (2/6) Epoch 17, batch 16, global_batch_idx: 2000, batch size: 45, loss[discriminator_loss=2.67, discriminator_real_loss=1.327, discriminator_fake_loss=1.342, generator_loss=33.6, generator_mel_loss=26.21, generator_kl_loss=1.339, generator_dur_loss=1.937, generator_adv_loss=1.856, generator_feat_match_loss=2.256, over 45.00 samples.], tot_loss[discriminator_loss=2.888, discriminator_real_loss=1.485, discriminator_fake_loss=1.403, generator_loss=30.34, generator_mel_loss=23.42, generator_kl_loss=1.254, generator_dur_loss=1.997, generator_adv_loss=1.889, generator_feat_match_loss=1.774, over 1013.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 01:15:55,087 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 01:16:02,946 INFO [train.py:591] (2/6) Epoch 17, validation: discriminator_loss=2.88, discriminator_real_loss=1.485, discriminator_fake_loss=1.395, generator_loss=29.27, generator_mel_loss=23.01, generator_kl_loss=1.108, generator_dur_loss=2.102, generator_adv_loss=1.687, generator_feat_match_loss=1.358, over 100.00 samples.
2024-03-12 01:16:02,947 INFO [train.py:592] (2/6) Maximum memory allocated so far is 28876MB
2024-03-12 01:18:23,040 INFO [train.py:527] (2/6) Epoch 17, batch 66, global_batch_idx: 2050, batch size: 96, loss[discriminator_loss=2.897, discriminator_real_loss=1.654, discriminator_fake_loss=1.243, generator_loss=31, generator_mel_loss=23.7, generator_kl_loss=1.38, generator_dur_loss=2.026, generator_adv_loss=2.085, generator_feat_match_loss=1.805, over 96.00 samples.], tot_loss[discriminator_loss=2.8, discriminator_real_loss=1.443, discriminator_fake_loss=1.356, generator_loss=30.6, generator_mel_loss=23.65, generator_kl_loss=1.257, generator_dur_loss=1.988, generator_adv_loss=1.841, generator_feat_match_loss=1.868, over 4256.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 01:20:38,076 INFO [train.py:527] (2/6) Epoch 17, batch 116, global_batch_idx: 2100, batch size: 48, loss[discriminator_loss=2.766, discriminator_real_loss=1.4, discriminator_fake_loss=1.366, generator_loss=30.71, generator_mel_loss=23.54, generator_kl_loss=1.333, generator_dur_loss=1.886, generator_adv_loss=1.808, generator_feat_match_loss=2.144, over 48.00 samples.], tot_loss[discriminator_loss=2.788, discriminator_real_loss=1.438, discriminator_fake_loss=1.35, generator_loss=30.72, generator_mel_loss=23.7, generator_kl_loss=1.262, generator_dur_loss=1.983, generator_adv_loss=1.849, generator_feat_match_loss=1.929, over 7238.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 01:20:57,403 INFO [train.py:919] (2/6) Start epoch 18
2024-03-12 01:23:20,740 INFO [train.py:527] (2/6) Epoch 18, batch 42, global_batch_idx: 2150, batch size: 70, loss[discriminator_loss=2.924, discriminator_real_loss=1.616, discriminator_fake_loss=1.308, generator_loss=31.27, generator_mel_loss=24.32, generator_kl_loss=1.185, generator_dur_loss=1.982, generator_adv_loss=1.751, generator_feat_match_loss=2.028, over 70.00 samples.], tot_loss[discriminator_loss=2.76, discriminator_real_loss=1.421, discriminator_fake_loss=1.339, generator_loss=31.31, generator_mel_loss=24, generator_kl_loss=1.265, generator_dur_loss=1.99, generator_adv_loss=1.905, generator_feat_match_loss=2.159, over 2725.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 01:25:39,861 INFO [train.py:527] (2/6) Epoch 18, batch 92, global_batch_idx: 2200, batch size: 48, loss[discriminator_loss=2.798, discriminator_real_loss=1.265, discriminator_fake_loss=1.534, generator_loss=31.43, generator_mel_loss=23.96, generator_kl_loss=1.317, generator_dur_loss=1.939, generator_adv_loss=2.021, generator_feat_match_loss=2.192, over 48.00 samples.], tot_loss[discriminator_loss=2.767, discriminator_real_loss=1.425, discriminator_fake_loss=1.342, generator_loss=31.12, generator_mel_loss=23.88, generator_kl_loss=1.268, generator_dur_loss=1.976, generator_adv_loss=1.89, generator_feat_match_loss=2.107, over 5276.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 01:25:39,863 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 01:25:48,601 INFO [train.py:591] (2/6) Epoch 18, validation: discriminator_loss=2.828, discriminator_real_loss=1.563, discriminator_fake_loss=1.265, generator_loss=31.05, generator_mel_loss=24.18, generator_kl_loss=1.084, generator_dur_loss=2.103, generator_adv_loss=1.899, generator_feat_match_loss=1.786, over 100.00 samples.
2024-03-12 01:25:48,601 INFO [train.py:592] (2/6) Maximum memory allocated so far is 28876MB
2024-03-12 01:27:10,500 INFO [train.py:919] (2/6) Start epoch 19
2024-03-12 01:28:25,368 INFO [train.py:527] (2/6) Epoch 19, batch 18, global_batch_idx: 2250, batch size: 88, loss[discriminator_loss=2.791, discriminator_real_loss=1.417, discriminator_fake_loss=1.373, generator_loss=28.14, generator_mel_loss=21.38, generator_kl_loss=1.207, generator_dur_loss=2.031, generator_adv_loss=1.672, generator_feat_match_loss=1.852, over 88.00 samples.], tot_loss[discriminator_loss=2.796, discriminator_real_loss=1.434, discriminator_fake_loss=1.361, generator_loss=30.66, generator_mel_loss=23.6, generator_kl_loss=1.21, generator_dur_loss=1.986, generator_adv_loss=1.879, generator_feat_match_loss=1.986, over 1244.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 01:30:45,092 INFO [train.py:527] (2/6) Epoch 19, batch 68, global_batch_idx: 2300, batch size: 42, loss[discriminator_loss=2.799, discriminator_real_loss=1.656, discriminator_fake_loss=1.143, generator_loss=30.93, generator_mel_loss=23.18, generator_kl_loss=1.319, generator_dur_loss=1.919, generator_adv_loss=2.406, generator_feat_match_loss=2.107, over 42.00 samples.], tot_loss[discriminator_loss=2.757, discriminator_real_loss=1.412, discriminator_fake_loss=1.345, generator_loss=30.86, generator_mel_loss=23.57, generator_kl_loss=1.248, generator_dur_loss=1.976, generator_adv_loss=1.909, generator_feat_match_loss=2.153, over 3986.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 01:33:04,893 INFO [train.py:527] (2/6) Epoch 19, batch 118, global_batch_idx: 2350, batch size: 48, loss[discriminator_loss=2.754, discriminator_real_loss=1.409, discriminator_fake_loss=1.346, generator_loss=31.43, generator_mel_loss=24.17, generator_kl_loss=1.397, generator_dur_loss=1.863, generator_adv_loss=1.872, generator_feat_match_loss=2.129, over 48.00 samples.], tot_loss[discriminator_loss=2.766, discriminator_real_loss=1.424, discriminator_fake_loss=1.342, generator_loss=31.03, generator_mel_loss=23.67, generator_kl_loss=1.258, generator_dur_loss=1.973, generator_adv_loss=1.932, generator_feat_match_loss=2.196, over 6763.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 01:33:20,765 INFO [train.py:919] (2/6) Start epoch 20
2024-03-12 01:35:47,061 INFO [train.py:527] (2/6) Epoch 20, batch 44, global_batch_idx: 2400, batch size: 56, loss[discriminator_loss=2.694, discriminator_real_loss=1.353, discriminator_fake_loss=1.34, generator_loss=32.26, generator_mel_loss=24.85, generator_kl_loss=1.258, generator_dur_loss=1.937, generator_adv_loss=1.884, generator_feat_match_loss=2.331, over 56.00 samples.], tot_loss[discriminator_loss=2.736, discriminator_real_loss=1.396, discriminator_fake_loss=1.34, generator_loss=30.86, generator_mel_loss=23.55, generator_kl_loss=1.301, generator_dur_loss=1.97, generator_adv_loss=1.884, generator_feat_match_loss=2.161, over 2524.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 01:35:47,063 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 01:35:54,747 INFO [train.py:591] (2/6) Epoch 20, validation: discriminator_loss=2.762, discriminator_real_loss=1.446, discriminator_fake_loss=1.316, generator_loss=29.25, generator_mel_loss=22.69, generator_kl_loss=1.153, generator_dur_loss=2.09, generator_adv_loss=1.794, generator_feat_match_loss=1.518, over 100.00 samples.
2024-03-12 01:35:54,748 INFO [train.py:592] (2/6) Maximum memory allocated so far is 28876MB
2024-03-12 01:38:14,686 INFO [train.py:527] (2/6) Epoch 20, batch 94, global_batch_idx: 2450, batch size: 88, loss[discriminator_loss=2.751, discriminator_real_loss=1.341, discriminator_fake_loss=1.41, generator_loss=28.93, generator_mel_loss=21.72, generator_kl_loss=1.363, generator_dur_loss=2.071, generator_adv_loss=1.876, generator_feat_match_loss=1.898, over 88.00 samples.], tot_loss[discriminator_loss=2.733, discriminator_real_loss=1.404, discriminator_fake_loss=1.329, generator_loss=30.75, generator_mel_loss=23.4, generator_kl_loss=1.29, generator_dur_loss=1.976, generator_adv_loss=1.894, generator_feat_match_loss=2.195, over 5496.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 01:39:35,033 INFO [train.py:919] (2/6) Start epoch 21
2024-03-12 01:41:48,435 INFO [train.py:527] (2/6) Epoch 21, batch 20, global_batch_idx: 2500, batch size: 56, loss[discriminator_loss=2.769, discriminator_real_loss=1.588, discriminator_fake_loss=1.181, generator_loss=30.01, generator_mel_loss=22.47, generator_kl_loss=1.439, generator_dur_loss=1.938, generator_adv_loss=1.933, generator_feat_match_loss=2.232, over 56.00 samples.], tot_loss[discriminator_loss=2.733, discriminator_real_loss=1.415, discriminator_fake_loss=1.318, generator_loss=31.16, generator_mel_loss=23.68, generator_kl_loss=1.372, generator_dur_loss=1.936, generator_adv_loss=1.928, generator_feat_match_loss=2.24, over 1033.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 01:44:07,468 INFO [train.py:527] (2/6) Epoch 21, batch 70, global_batch_idx: 2550, batch size: 39, loss[discriminator_loss=2.82, discriminator_real_loss=1.575, discriminator_fake_loss=1.245, generator_loss=29.63, generator_mel_loss=22.82, generator_kl_loss=1.251, generator_dur_loss=1.942, generator_adv_loss=1.781, generator_feat_match_loss=1.838, over 39.00 samples.], tot_loss[discriminator_loss=2.73, discriminator_real_loss=1.4, discriminator_fake_loss=1.33, generator_loss=30.76, generator_mel_loss=23.32, generator_kl_loss=1.307, generator_dur_loss=1.96, generator_adv_loss=1.916, generator_feat_match_loss=2.26, over 3907.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 01:46:24,431 INFO [train.py:527] (2/6) Epoch 21, batch 120, global_batch_idx: 2600, batch size: 80, loss[discriminator_loss=2.771, discriminator_real_loss=1.419, discriminator_fake_loss=1.352, generator_loss=29.16, generator_mel_loss=21.88, generator_kl_loss=1.295, generator_dur_loss=2.016, generator_adv_loss=1.907, generator_feat_match_loss=2.064, over 80.00 samples.], tot_loss[discriminator_loss=2.74, discriminator_real_loss=1.404, discriminator_fake_loss=1.335, generator_loss=30.75, generator_mel_loss=23.29, generator_kl_loss=1.305, generator_dur_loss=1.96, generator_adv_loss=1.921, generator_feat_match_loss=2.275, over 6512.00 samples.], cur_lr_g: 2.00e-04, cur_lr_d: 2.00e-04, 
2024-03-12 01:46:24,433 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 01:46:33,223 INFO [train.py:591] (2/6) Epoch 21, validation: discriminator_loss=2.716, discriminator_real_loss=1.447, discriminator_fake_loss=1.27, generator_loss=30.54, generator_mel_loss=23.51, generator_kl_loss=1.136, generator_dur_loss=2.084, generator_adv_loss=1.928, generator_feat_match_loss=1.873, over 100.00 samples.
2024-03-12 01:46:33,224 INFO [train.py:592] (2/6) Maximum memory allocated so far is 28876MB
2024-03-12 01:46:43,490 INFO [train.py:919] (2/6) Start epoch 22
2024-03-12 01:49:19,674 INFO [train.py:527] (2/6) Epoch 22, batch 46, global_batch_idx: 2650, batch size: 44, loss[discriminator_loss=2.708, discriminator_real_loss=1.376, discriminator_fake_loss=1.332, generator_loss=30.34, generator_mel_loss=22.83, generator_kl_loss=1.382, generator_dur_loss=1.919, generator_adv_loss=1.992, generator_feat_match_loss=2.218, over 44.00 samples.], tot_loss[discriminator_loss=2.735, discriminator_real_loss=1.409, discriminator_fake_loss=1.327, generator_loss=30.62, generator_mel_loss=23.16, generator_kl_loss=1.267, generator_dur_loss=1.983, generator_adv_loss=1.928, generator_feat_match_loss=2.28, over 2860.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 01:51:39,032 INFO [train.py:527] (2/6) Epoch 22, batch 96, global_batch_idx: 2700, batch size: 55, loss[discriminator_loss=2.771, discriminator_real_loss=1.332, discriminator_fake_loss=1.439, generator_loss=30.22, generator_mel_loss=23.16, generator_kl_loss=1.113, generator_dur_loss=1.87, generator_adv_loss=2.02, generator_feat_match_loss=2.062, over 55.00 samples.], tot_loss[discriminator_loss=2.74, discriminator_real_loss=1.405, discriminator_fake_loss=1.335, generator_loss=30.49, generator_mel_loss=23.06, generator_kl_loss=1.262, generator_dur_loss=1.98, generator_adv_loss=1.924, generator_feat_match_loss=2.263, over 5718.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 01:52:50,074 INFO [train.py:919] (2/6) Start epoch 23
2024-03-12 01:54:13,249 INFO [train.py:527] (2/6) Epoch 23, batch 22, global_batch_idx: 2750, batch size: 61, loss[discriminator_loss=2.711, discriminator_real_loss=1.394, discriminator_fake_loss=1.317, generator_loss=30.45, generator_mel_loss=23.08, generator_kl_loss=1.316, generator_dur_loss=1.937, generator_adv_loss=1.779, generator_feat_match_loss=2.345, over 61.00 samples.], tot_loss[discriminator_loss=2.735, discriminator_real_loss=1.401, discriminator_fake_loss=1.334, generator_loss=30.68, generator_mel_loss=23.22, generator_kl_loss=1.343, generator_dur_loss=1.948, generator_adv_loss=1.897, generator_feat_match_loss=2.267, over 1093.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 01:56:31,438 INFO [train.py:527] (2/6) Epoch 23, batch 72, global_batch_idx: 2800, batch size: 70, loss[discriminator_loss=2.754, discriminator_real_loss=1.369, discriminator_fake_loss=1.385, generator_loss=29.08, generator_mel_loss=21.65, generator_kl_loss=1.298, generator_dur_loss=2.053, generator_adv_loss=2.088, generator_feat_match_loss=1.985, over 70.00 samples.], tot_loss[discriminator_loss=2.753, discriminator_real_loss=1.424, discriminator_fake_loss=1.329, generator_loss=30.75, generator_mel_loss=23.2, generator_kl_loss=1.288, generator_dur_loss=1.961, generator_adv_loss=1.963, generator_feat_match_loss=2.342, over 3923.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 01:56:31,440 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 01:56:39,134 INFO [train.py:591] (2/6) Epoch 23, validation: discriminator_loss=2.76, discriminator_real_loss=1.551, discriminator_fake_loss=1.209, generator_loss=29.39, generator_mel_loss=22.55, generator_kl_loss=1.05, generator_dur_loss=2.078, generator_adv_loss=2.038, generator_feat_match_loss=1.676, over 100.00 samples.
2024-03-12 01:56:39,135 INFO [train.py:592] (2/6) Maximum memory allocated so far is 28876MB
2024-03-12 01:58:56,573 INFO [train.py:527] (2/6) Epoch 23, batch 122, global_batch_idx: 2850, batch size: 31, loss[discriminator_loss=2.705, discriminator_real_loss=1.4, discriminator_fake_loss=1.305, generator_loss=30.49, generator_mel_loss=23.35, generator_kl_loss=1.162, generator_dur_loss=1.919, generator_adv_loss=1.938, generator_feat_match_loss=2.123, over 31.00 samples.], tot_loss[discriminator_loss=2.741, discriminator_real_loss=1.417, discriminator_fake_loss=1.324, generator_loss=30.66, generator_mel_loss=23.17, generator_kl_loss=1.272, generator_dur_loss=1.964, generator_adv_loss=1.938, generator_feat_match_loss=2.32, over 6620.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 01:59:02,374 INFO [train.py:919] (2/6) Start epoch 24
2024-03-12 02:01:38,295 INFO [train.py:527] (2/6) Epoch 24, batch 48, global_batch_idx: 2900, batch size: 50, loss[discriminator_loss=2.583, discriminator_real_loss=1.193, discriminator_fake_loss=1.39, generator_loss=31.65, generator_mel_loss=23.53, generator_kl_loss=1.307, generator_dur_loss=1.896, generator_adv_loss=2.074, generator_feat_match_loss=2.839, over 50.00 samples.], tot_loss[discriminator_loss=2.746, discriminator_real_loss=1.41, discriminator_fake_loss=1.336, generator_loss=30.25, generator_mel_loss=22.9, generator_kl_loss=1.249, generator_dur_loss=1.967, generator_adv_loss=1.879, generator_feat_match_loss=2.257, over 2829.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 02:03:56,279 INFO [train.py:527] (2/6) Epoch 24, batch 98, global_batch_idx: 2950, batch size: 59, loss[discriminator_loss=2.695, discriminator_real_loss=1.419, discriminator_fake_loss=1.276, generator_loss=31.18, generator_mel_loss=23.68, generator_kl_loss=1.353, generator_dur_loss=1.959, generator_adv_loss=2.011, generator_feat_match_loss=2.181, over 59.00 samples.], tot_loss[discriminator_loss=2.745, discriminator_real_loss=1.408, discriminator_fake_loss=1.337, generator_loss=30.39, generator_mel_loss=22.92, generator_kl_loss=1.259, generator_dur_loss=1.966, generator_adv_loss=1.914, generator_feat_match_loss=2.33, over 5535.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 02:05:07,552 INFO [train.py:919] (2/6) Start epoch 25
2024-03-12 02:06:39,775 INFO [train.py:527] (2/6) Epoch 25, batch 24, global_batch_idx: 3000, batch size: 64, loss[discriminator_loss=2.905, discriminator_real_loss=1.729, discriminator_fake_loss=1.177, generator_loss=30.19, generator_mel_loss=22.51, generator_kl_loss=1.365, generator_dur_loss=2.022, generator_adv_loss=2.074, generator_feat_match_loss=2.217, over 64.00 samples.], tot_loss[discriminator_loss=2.754, discriminator_real_loss=1.417, discriminator_fake_loss=1.337, generator_loss=30.34, generator_mel_loss=22.76, generator_kl_loss=1.259, generator_dur_loss=1.973, generator_adv_loss=1.973, generator_feat_match_loss=2.384, over 1550.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 02:06:39,776 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 02:06:47,849 INFO [train.py:591] (2/6) Epoch 25, validation: discriminator_loss=2.911, discriminator_real_loss=1.657, discriminator_fake_loss=1.254, generator_loss=29.63, generator_mel_loss=22.44, generator_kl_loss=1.237, generator_dur_loss=2.038, generator_adv_loss=2.074, generator_feat_match_loss=1.843, over 100.00 samples.
2024-03-12 02:06:47,850 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 02:09:03,795 INFO [train.py:527] (2/6) Epoch 25, batch 74, global_batch_idx: 3050, batch size: 25, loss[discriminator_loss=2.837, discriminator_real_loss=1.293, discriminator_fake_loss=1.544, generator_loss=32.1, generator_mel_loss=23.84, generator_kl_loss=1.664, generator_dur_loss=1.735, generator_adv_loss=2.331, generator_feat_match_loss=2.53, over 25.00 samples.], tot_loss[discriminator_loss=2.742, discriminator_real_loss=1.408, discriminator_fake_loss=1.334, generator_loss=30.22, generator_mel_loss=22.73, generator_kl_loss=1.272, generator_dur_loss=1.97, generator_adv_loss=1.933, generator_feat_match_loss=2.315, over 4447.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 02:11:21,732 INFO [train.py:919] (2/6) Start epoch 26
2024-03-12 02:11:45,881 INFO [train.py:527] (2/6) Epoch 26, batch 0, global_batch_idx: 3100, batch size: 72, loss[discriminator_loss=2.785, discriminator_real_loss=1.329, discriminator_fake_loss=1.456, generator_loss=27.98, generator_mel_loss=21.02, generator_kl_loss=1.189, generator_dur_loss=1.968, generator_adv_loss=1.775, generator_feat_match_loss=2.024, over 72.00 samples.], tot_loss[discriminator_loss=2.785, discriminator_real_loss=1.329, discriminator_fake_loss=1.456, generator_loss=27.98, generator_mel_loss=21.02, generator_kl_loss=1.189, generator_dur_loss=1.968, generator_adv_loss=1.775, generator_feat_match_loss=2.024, over 72.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 02:14:06,930 INFO [train.py:527] (2/6) Epoch 26, batch 50, global_batch_idx: 3150, batch size: 53, loss[discriminator_loss=2.675, discriminator_real_loss=1.32, discriminator_fake_loss=1.355, generator_loss=31.08, generator_mel_loss=23.54, generator_kl_loss=1.282, generator_dur_loss=1.897, generator_adv_loss=1.978, generator_feat_match_loss=2.378, over 53.00 samples.], tot_loss[discriminator_loss=2.733, discriminator_real_loss=1.391, discriminator_fake_loss=1.342, generator_loss=30.34, generator_mel_loss=22.8, generator_kl_loss=1.252, generator_dur_loss=1.963, generator_adv_loss=1.936, generator_feat_match_loss=2.384, over 3031.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 02:16:25,919 INFO [train.py:527] (2/6) Epoch 26, batch 100, global_batch_idx: 3200, batch size: 83, loss[discriminator_loss=2.792, discriminator_real_loss=1.525, discriminator_fake_loss=1.267, generator_loss=28.75, generator_mel_loss=21.71, generator_kl_loss=1.206, generator_dur_loss=2.054, generator_adv_loss=1.784, generator_feat_match_loss=1.995, over 83.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.391, discriminator_fake_loss=1.335, generator_loss=30.2, generator_mel_loss=22.68, generator_kl_loss=1.26, generator_dur_loss=1.97, generator_adv_loss=1.927, generator_feat_match_loss=2.37, over 5977.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 02:16:25,921 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 02:16:34,499 INFO [train.py:591] (2/6) Epoch 26, validation: discriminator_loss=2.733, discriminator_real_loss=1.372, discriminator_fake_loss=1.361, generator_loss=28.89, generator_mel_loss=22.07, generator_kl_loss=1.013, generator_dur_loss=2.064, generator_adv_loss=1.783, generator_feat_match_loss=1.959, over 100.00 samples.
2024-03-12 02:16:34,500 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 02:17:37,580 INFO [train.py:919] (2/6) Start epoch 27
2024-03-12 02:19:15,671 INFO [train.py:527] (2/6) Epoch 27, batch 26, global_batch_idx: 3250, batch size: 44, loss[discriminator_loss=2.755, discriminator_real_loss=1.367, discriminator_fake_loss=1.388, generator_loss=30.13, generator_mel_loss=22.7, generator_kl_loss=1.351, generator_dur_loss=1.894, generator_adv_loss=1.782, generator_feat_match_loss=2.404, over 44.00 samples.], tot_loss[discriminator_loss=2.741, discriminator_real_loss=1.418, discriminator_fake_loss=1.323, generator_loss=30.53, generator_mel_loss=22.78, generator_kl_loss=1.279, generator_dur_loss=1.959, generator_adv_loss=2.01, generator_feat_match_loss=2.503, over 1466.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 02:21:36,367 INFO [train.py:527] (2/6) Epoch 27, batch 76, global_batch_idx: 3300, batch size: 48, loss[discriminator_loss=2.701, discriminator_real_loss=1.306, discriminator_fake_loss=1.395, generator_loss=31.47, generator_mel_loss=23.59, generator_kl_loss=1.181, generator_dur_loss=1.951, generator_adv_loss=2.195, generator_feat_match_loss=2.556, over 48.00 samples.], tot_loss[discriminator_loss=2.746, discriminator_real_loss=1.416, discriminator_fake_loss=1.33, generator_loss=30.32, generator_mel_loss=22.65, generator_kl_loss=1.261, generator_dur_loss=1.964, generator_adv_loss=1.993, generator_feat_match_loss=2.454, over 4345.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 02:23:48,065 INFO [train.py:919] (2/6) Start epoch 28
2024-03-12 02:24:17,389 INFO [train.py:527] (2/6) Epoch 28, batch 2, global_batch_idx: 3350, batch size: 61, loss[discriminator_loss=2.879, discriminator_real_loss=1.413, discriminator_fake_loss=1.466, generator_loss=29.27, generator_mel_loss=22.22, generator_kl_loss=1.195, generator_dur_loss=1.896, generator_adv_loss=1.814, generator_feat_match_loss=2.145, over 61.00 samples.], tot_loss[discriminator_loss=2.757, discriminator_real_loss=1.38, discriminator_fake_loss=1.378, generator_loss=30.78, generator_mel_loss=23.01, generator_kl_loss=1.306, generator_dur_loss=1.893, generator_adv_loss=2.017, generator_feat_match_loss=2.55, over 144.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 02:26:35,485 INFO [train.py:527] (2/6) Epoch 28, batch 52, global_batch_idx: 3400, batch size: 42, loss[discriminator_loss=2.824, discriminator_real_loss=1.316, discriminator_fake_loss=1.508, generator_loss=29.5, generator_mel_loss=22.64, generator_kl_loss=1.209, generator_dur_loss=1.89, generator_adv_loss=1.815, generator_feat_match_loss=1.949, over 42.00 samples.], tot_loss[discriminator_loss=2.768, discriminator_real_loss=1.425, discriminator_fake_loss=1.343, generator_loss=29.95, generator_mel_loss=22.47, generator_kl_loss=1.256, generator_dur_loss=1.957, generator_adv_loss=1.931, generator_feat_match_loss=2.338, over 3072.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 02:26:35,486 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 02:26:43,331 INFO [train.py:591] (2/6) Epoch 28, validation: discriminator_loss=2.762, discriminator_real_loss=1.354, discriminator_fake_loss=1.408, generator_loss=30.33, generator_mel_loss=23.31, generator_kl_loss=1.208, generator_dur_loss=2.058, generator_adv_loss=1.726, generator_feat_match_loss=2.028, over 100.00 samples.
2024-03-12 02:26:43,332 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 02:29:00,658 INFO [train.py:527] (2/6) Epoch 28, batch 102, global_batch_idx: 3450, batch size: 70, loss[discriminator_loss=2.7, discriminator_real_loss=1.457, discriminator_fake_loss=1.244, generator_loss=30.79, generator_mel_loss=22.74, generator_kl_loss=1.179, generator_dur_loss=1.986, generator_adv_loss=2.14, generator_feat_match_loss=2.744, over 70.00 samples.], tot_loss[discriminator_loss=2.748, discriminator_real_loss=1.411, discriminator_fake_loss=1.337, generator_loss=29.91, generator_mel_loss=22.44, generator_kl_loss=1.264, generator_dur_loss=1.956, generator_adv_loss=1.925, generator_feat_match_loss=2.32, over 5847.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 02:30:01,492 INFO [train.py:919] (2/6) Start epoch 29
2024-03-12 02:31:42,454 INFO [train.py:527] (2/6) Epoch 29, batch 28, global_batch_idx: 3500, batch size: 66, loss[discriminator_loss=2.692, discriminator_real_loss=1.297, discriminator_fake_loss=1.395, generator_loss=30.56, generator_mel_loss=22.87, generator_kl_loss=1.326, generator_dur_loss=1.907, generator_adv_loss=1.866, generator_feat_match_loss=2.591, over 66.00 samples.], tot_loss[discriminator_loss=2.737, discriminator_real_loss=1.392, discriminator_fake_loss=1.345, generator_loss=29.51, generator_mel_loss=22.18, generator_kl_loss=1.232, generator_dur_loss=1.978, generator_adv_loss=1.876, generator_feat_match_loss=2.243, over 1774.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 02:34:01,820 INFO [train.py:527] (2/6) Epoch 29, batch 78, global_batch_idx: 3550, batch size: 66, loss[discriminator_loss=2.745, discriminator_real_loss=1.414, discriminator_fake_loss=1.33, generator_loss=29.97, generator_mel_loss=22.4, generator_kl_loss=1.19, generator_dur_loss=1.951, generator_adv_loss=2.102, generator_feat_match_loss=2.32, over 66.00 samples.], tot_loss[discriminator_loss=2.741, discriminator_real_loss=1.404, discriminator_fake_loss=1.336, generator_loss=29.81, generator_mel_loss=22.33, generator_kl_loss=1.239, generator_dur_loss=1.967, generator_adv_loss=1.928, generator_feat_match_loss=2.341, over 4611.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 02:36:07,336 INFO [train.py:919] (2/6) Start epoch 30
2024-03-12 02:36:42,543 INFO [train.py:527] (2/6) Epoch 30, batch 4, global_batch_idx: 3600, batch size: 52, loss[discriminator_loss=2.554, discriminator_real_loss=1.421, discriminator_fake_loss=1.133, generator_loss=31.85, generator_mel_loss=23.63, generator_kl_loss=1.328, generator_dur_loss=1.915, generator_adv_loss=1.833, generator_feat_match_loss=3.141, over 52.00 samples.], tot_loss[discriminator_loss=2.642, discriminator_real_loss=1.407, discriminator_fake_loss=1.234, generator_loss=30.48, generator_mel_loss=22.67, generator_kl_loss=1.292, generator_dur_loss=1.896, generator_adv_loss=2.034, generator_feat_match_loss=2.587, over 254.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 02:36:42,546 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 02:36:50,361 INFO [train.py:591] (2/6) Epoch 30, validation: discriminator_loss=2.709, discriminator_real_loss=1.298, discriminator_fake_loss=1.41, generator_loss=28.39, generator_mel_loss=21.72, generator_kl_loss=1.022, generator_dur_loss=2.038, generator_adv_loss=1.708, generator_feat_match_loss=1.903, over 100.00 samples.
2024-03-12 02:36:50,364 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 02:39:06,970 INFO [train.py:527] (2/6) Epoch 30, batch 54, global_batch_idx: 3650, batch size: 56, loss[discriminator_loss=2.696, discriminator_real_loss=1.379, discriminator_fake_loss=1.317, generator_loss=29.95, generator_mel_loss=22.27, generator_kl_loss=1.332, generator_dur_loss=1.925, generator_adv_loss=1.977, generator_feat_match_loss=2.443, over 56.00 samples.], tot_loss[discriminator_loss=2.725, discriminator_real_loss=1.395, discriminator_fake_loss=1.33, generator_loss=30.15, generator_mel_loss=22.52, generator_kl_loss=1.238, generator_dur_loss=1.941, generator_adv_loss=1.955, generator_feat_match_loss=2.493, over 3117.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 02:41:24,082 INFO [train.py:527] (2/6) Epoch 30, batch 104, global_batch_idx: 3700, batch size: 74, loss[discriminator_loss=2.704, discriminator_real_loss=1.442, discriminator_fake_loss=1.263, generator_loss=29.5, generator_mel_loss=21.8, generator_kl_loss=1.154, generator_dur_loss=2.047, generator_adv_loss=1.846, generator_feat_match_loss=2.65, over 74.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.396, discriminator_fake_loss=1.33, generator_loss=29.97, generator_mel_loss=22.39, generator_kl_loss=1.239, generator_dur_loss=1.946, generator_adv_loss=1.937, generator_feat_match_loss=2.463, over 6007.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 02:42:19,571 INFO [train.py:919] (2/6) Start epoch 31
2024-03-12 02:44:05,419 INFO [train.py:527] (2/6) Epoch 31, batch 30, global_batch_idx: 3750, batch size: 88, loss[discriminator_loss=2.826, discriminator_real_loss=1.455, discriminator_fake_loss=1.37, generator_loss=29.82, generator_mel_loss=21.81, generator_kl_loss=1.149, generator_dur_loss=2.038, generator_adv_loss=1.989, generator_feat_match_loss=2.834, over 88.00 samples.], tot_loss[discriminator_loss=2.745, discriminator_real_loss=1.412, discriminator_fake_loss=1.333, generator_loss=29.9, generator_mel_loss=22.16, generator_kl_loss=1.234, generator_dur_loss=1.944, generator_adv_loss=1.994, generator_feat_match_loss=2.564, over 1709.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 02:46:25,064 INFO [train.py:527] (2/6) Epoch 31, batch 80, global_batch_idx: 3800, batch size: 66, loss[discriminator_loss=2.743, discriminator_real_loss=1.276, discriminator_fake_loss=1.467, generator_loss=28.56, generator_mel_loss=21.65, generator_kl_loss=1.25, generator_dur_loss=1.946, generator_adv_loss=1.648, generator_feat_match_loss=2.063, over 66.00 samples.], tot_loss[discriminator_loss=2.757, discriminator_real_loss=1.414, discriminator_fake_loss=1.343, generator_loss=29.51, generator_mel_loss=21.99, generator_kl_loss=1.241, generator_dur_loss=1.951, generator_adv_loss=1.945, generator_feat_match_loss=2.386, over 4676.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 02:46:25,065 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 02:46:33,133 INFO [train.py:591] (2/6) Epoch 31, validation: discriminator_loss=2.739, discriminator_real_loss=1.32, discriminator_fake_loss=1.419, generator_loss=27.75, generator_mel_loss=21.26, generator_kl_loss=1.047, generator_dur_loss=2.012, generator_adv_loss=1.689, generator_feat_match_loss=1.744, over 100.00 samples.
2024-03-12 02:46:33,134 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 02:48:32,074 INFO [train.py:919] (2/6) Start epoch 32
2024-03-12 02:49:14,961 INFO [train.py:527] (2/6) Epoch 32, batch 6, global_batch_idx: 3850, batch size: 50, loss[discriminator_loss=2.706, discriminator_real_loss=1.394, discriminator_fake_loss=1.312, generator_loss=29.81, generator_mel_loss=22.58, generator_kl_loss=1.304, generator_dur_loss=1.891, generator_adv_loss=1.851, generator_feat_match_loss=2.185, over 50.00 samples.], tot_loss[discriminator_loss=2.737, discriminator_real_loss=1.374, discriminator_fake_loss=1.363, generator_loss=29.54, generator_mel_loss=22.14, generator_kl_loss=1.221, generator_dur_loss=1.948, generator_adv_loss=1.882, generator_feat_match_loss=2.35, over 398.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 02:51:36,065 INFO [train.py:527] (2/6) Epoch 32, batch 56, global_batch_idx: 3900, batch size: 83, loss[discriminator_loss=2.7, discriminator_real_loss=1.371, discriminator_fake_loss=1.329, generator_loss=29.29, generator_mel_loss=21.84, generator_kl_loss=1.13, generator_dur_loss=2.032, generator_adv_loss=1.875, generator_feat_match_loss=2.413, over 83.00 samples.], tot_loss[discriminator_loss=2.753, discriminator_real_loss=1.412, discriminator_fake_loss=1.341, generator_loss=29.39, generator_mel_loss=21.94, generator_kl_loss=1.216, generator_dur_loss=1.95, generator_adv_loss=1.929, generator_feat_match_loss=2.363, over 3396.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 02:53:54,764 INFO [train.py:527] (2/6) Epoch 32, batch 106, global_batch_idx: 3950, batch size: 47, loss[discriminator_loss=2.771, discriminator_real_loss=1.428, discriminator_fake_loss=1.342, generator_loss=29.75, generator_mel_loss=22.18, generator_kl_loss=1.41, generator_dur_loss=1.851, generator_adv_loss=1.897, generator_feat_match_loss=2.417, over 47.00 samples.], tot_loss[discriminator_loss=2.745, discriminator_real_loss=1.405, discriminator_fake_loss=1.34, generator_loss=29.5, generator_mel_loss=22.01, generator_kl_loss=1.227, generator_dur_loss=1.943, generator_adv_loss=1.932, generator_feat_match_loss=2.381, over 6109.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 02:54:42,027 INFO [train.py:919] (2/6) Start epoch 33
2024-03-12 02:56:35,260 INFO [train.py:527] (2/6) Epoch 33, batch 32, global_batch_idx: 4000, batch size: 55, loss[discriminator_loss=2.765, discriminator_real_loss=1.481, discriminator_fake_loss=1.283, generator_loss=29.59, generator_mel_loss=22.03, generator_kl_loss=1.242, generator_dur_loss=1.897, generator_adv_loss=1.779, generator_feat_match_loss=2.635, over 55.00 samples.], tot_loss[discriminator_loss=2.739, discriminator_real_loss=1.419, discriminator_fake_loss=1.32, generator_loss=29.87, generator_mel_loss=22.21, generator_kl_loss=1.227, generator_dur_loss=1.918, generator_adv_loss=1.988, generator_feat_match_loss=2.535, over 1821.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 02:56:35,262 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 02:56:43,046 INFO [train.py:591] (2/6) Epoch 33, validation: discriminator_loss=2.715, discriminator_real_loss=1.291, discriminator_fake_loss=1.424, generator_loss=28.62, generator_mel_loss=21.9, generator_kl_loss=1.076, generator_dur_loss=2.005, generator_adv_loss=1.742, generator_feat_match_loss=1.901, over 100.00 samples.
2024-03-12 02:56:43,047 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 02:59:01,994 INFO [train.py:527] (2/6) Epoch 33, batch 82, global_batch_idx: 4050, batch size: 96, loss[discriminator_loss=2.884, discriminator_real_loss=1.377, discriminator_fake_loss=1.507, generator_loss=28.77, generator_mel_loss=21.47, generator_kl_loss=1.191, generator_dur_loss=2.086, generator_adv_loss=1.952, generator_feat_match_loss=2.076, over 96.00 samples.], tot_loss[discriminator_loss=2.758, discriminator_real_loss=1.421, discriminator_fake_loss=1.337, generator_loss=29.68, generator_mel_loss=22.02, generator_kl_loss=1.245, generator_dur_loss=1.922, generator_adv_loss=1.995, generator_feat_match_loss=2.498, over 4712.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 03:00:56,976 INFO [train.py:919] (2/6) Start epoch 34
2024-03-12 03:01:42,836 INFO [train.py:527] (2/6) Epoch 34, batch 8, global_batch_idx: 4100, batch size: 83, loss[discriminator_loss=2.671, discriminator_real_loss=1.25, discriminator_fake_loss=1.421, generator_loss=28.92, generator_mel_loss=21.48, generator_kl_loss=1.197, generator_dur_loss=1.992, generator_adv_loss=1.954, generator_feat_match_loss=2.3, over 83.00 samples.], tot_loss[discriminator_loss=2.693, discriminator_real_loss=1.381, discriminator_fake_loss=1.312, generator_loss=28.94, generator_mel_loss=21.54, generator_kl_loss=1.208, generator_dur_loss=1.927, generator_adv_loss=1.92, generator_feat_match_loss=2.339, over 514.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 03:04:02,945 INFO [train.py:527] (2/6) Epoch 34, batch 58, global_batch_idx: 4150, batch size: 64, loss[discriminator_loss=2.774, discriminator_real_loss=1.312, discriminator_fake_loss=1.462, generator_loss=29.75, generator_mel_loss=22.21, generator_kl_loss=1.262, generator_dur_loss=1.965, generator_adv_loss=1.846, generator_feat_match_loss=2.468, over 64.00 samples.], tot_loss[discriminator_loss=2.743, discriminator_real_loss=1.404, discriminator_fake_loss=1.339, generator_loss=29.41, generator_mel_loss=21.96, generator_kl_loss=1.241, generator_dur_loss=1.919, generator_adv_loss=1.915, generator_feat_match_loss=2.376, over 3335.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 03:06:21,458 INFO [train.py:527] (2/6) Epoch 34, batch 108, global_batch_idx: 4200, batch size: 50, loss[discriminator_loss=2.693, discriminator_real_loss=1.32, discriminator_fake_loss=1.373, generator_loss=29.63, generator_mel_loss=22.22, generator_kl_loss=1.287, generator_dur_loss=1.822, generator_adv_loss=2.01, generator_feat_match_loss=2.288, over 50.00 samples.], tot_loss[discriminator_loss=2.738, discriminator_real_loss=1.404, discriminator_fake_loss=1.334, generator_loss=29.59, generator_mel_loss=22.04, generator_kl_loss=1.238, generator_dur_loss=1.926, generator_adv_loss=1.947, generator_feat_match_loss=2.434, over 6277.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 03:06:21,459 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 03:06:30,178 INFO [train.py:591] (2/6) Epoch 34, validation: discriminator_loss=2.732, discriminator_real_loss=1.566, discriminator_fake_loss=1.165, generator_loss=28.72, generator_mel_loss=21.75, generator_kl_loss=1.073, generator_dur_loss=1.998, generator_adv_loss=1.98, generator_feat_match_loss=1.921, over 100.00 samples.
2024-03-12 03:06:30,179 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 03:07:11,539 INFO [train.py:919] (2/6) Start epoch 35
2024-03-12 03:09:10,553 INFO [train.py:527] (2/6) Epoch 35, batch 34, global_batch_idx: 4250, batch size: 66, loss[discriminator_loss=2.716, discriminator_real_loss=1.305, discriminator_fake_loss=1.411, generator_loss=29.66, generator_mel_loss=21.93, generator_kl_loss=1.154, generator_dur_loss=1.961, generator_adv_loss=2.077, generator_feat_match_loss=2.544, over 66.00 samples.], tot_loss[discriminator_loss=2.717, discriminator_real_loss=1.379, discriminator_fake_loss=1.339, generator_loss=29.78, generator_mel_loss=22.28, generator_kl_loss=1.231, generator_dur_loss=1.899, generator_adv_loss=1.91, generator_feat_match_loss=2.454, over 1860.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 03:11:30,598 INFO [train.py:527] (2/6) Epoch 35, batch 84, global_batch_idx: 4300, batch size: 83, loss[discriminator_loss=2.866, discriminator_real_loss=1.328, discriminator_fake_loss=1.538, generator_loss=30.47, generator_mel_loss=22.53, generator_kl_loss=1.344, generator_dur_loss=2.068, generator_adv_loss=2.129, generator_feat_match_loss=2.4, over 83.00 samples.], tot_loss[discriminator_loss=2.74, discriminator_real_loss=1.399, discriminator_fake_loss=1.34, generator_loss=29.68, generator_mel_loss=22.11, generator_kl_loss=1.244, generator_dur_loss=1.912, generator_adv_loss=1.941, generator_feat_match_loss=2.467, over 4740.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 03:13:17,857 INFO [train.py:919] (2/6) Start epoch 36
2024-03-12 03:14:10,449 INFO [train.py:527] (2/6) Epoch 36, batch 10, global_batch_idx: 4350, batch size: 55, loss[discriminator_loss=2.743, discriminator_real_loss=1.467, discriminator_fake_loss=1.276, generator_loss=29.18, generator_mel_loss=21.99, generator_kl_loss=1.186, generator_dur_loss=1.845, generator_adv_loss=1.79, generator_feat_match_loss=2.376, over 55.00 samples.], tot_loss[discriminator_loss=2.752, discriminator_real_loss=1.424, discriminator_fake_loss=1.328, generator_loss=29.22, generator_mel_loss=21.81, generator_kl_loss=1.244, generator_dur_loss=1.916, generator_adv_loss=1.918, generator_feat_match_loss=2.328, over 689.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 03:16:31,639 INFO [train.py:527] (2/6) Epoch 36, batch 60, global_batch_idx: 4400, batch size: 52, loss[discriminator_loss=2.586, discriminator_real_loss=1.24, discriminator_fake_loss=1.345, generator_loss=30.95, generator_mel_loss=22.81, generator_kl_loss=1.434, generator_dur_loss=1.833, generator_adv_loss=2.031, generator_feat_match_loss=2.841, over 52.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.396, discriminator_fake_loss=1.323, generator_loss=29.55, generator_mel_loss=21.99, generator_kl_loss=1.288, generator_dur_loss=1.893, generator_adv_loss=1.942, generator_feat_match_loss=2.444, over 3094.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 03:16:31,640 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 03:16:39,666 INFO [train.py:591] (2/6) Epoch 36, validation: discriminator_loss=2.713, discriminator_real_loss=1.416, discriminator_fake_loss=1.297, generator_loss=28.13, generator_mel_loss=21.35, generator_kl_loss=1.097, generator_dur_loss=1.984, generator_adv_loss=1.838, generator_feat_match_loss=1.856, over 100.00 samples.
2024-03-12 03:16:39,667 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 03:18:56,451 INFO [train.py:527] (2/6) Epoch 36, batch 110, global_batch_idx: 4450, batch size: 52, loss[discriminator_loss=2.717, discriminator_real_loss=1.461, discriminator_fake_loss=1.256, generator_loss=28.91, generator_mel_loss=21.68, generator_kl_loss=1.228, generator_dur_loss=1.799, generator_adv_loss=1.843, generator_feat_match_loss=2.362, over 52.00 samples.], tot_loss[discriminator_loss=2.728, discriminator_real_loss=1.398, discriminator_fake_loss=1.33, generator_loss=29.45, generator_mel_loss=21.92, generator_kl_loss=1.278, generator_dur_loss=1.898, generator_adv_loss=1.936, generator_feat_match_loss=2.421, over 5973.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 03:19:32,789 INFO [train.py:919] (2/6) Start epoch 37
2024-03-12 03:21:34,203 INFO [train.py:527] (2/6) Epoch 37, batch 36, global_batch_idx: 4500, batch size: 36, loss[discriminator_loss=2.815, discriminator_real_loss=1.307, discriminator_fake_loss=1.508, generator_loss=28.56, generator_mel_loss=21.58, generator_kl_loss=1.238, generator_dur_loss=1.835, generator_adv_loss=1.766, generator_feat_match_loss=2.142, over 36.00 samples.], tot_loss[discriminator_loss=2.76, discriminator_real_loss=1.403, discriminator_fake_loss=1.358, generator_loss=29.32, generator_mel_loss=21.76, generator_kl_loss=1.286, generator_dur_loss=1.875, generator_adv_loss=1.947, generator_feat_match_loss=2.448, over 1941.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 03:23:54,431 INFO [train.py:527] (2/6) Epoch 37, batch 86, global_batch_idx: 4550, batch size: 96, loss[discriminator_loss=2.717, discriminator_real_loss=1.29, discriminator_fake_loss=1.427, generator_loss=27.95, generator_mel_loss=20.47, generator_kl_loss=1.28, generator_dur_loss=2.063, generator_adv_loss=1.874, generator_feat_match_loss=2.27, over 96.00 samples.], tot_loss[discriminator_loss=2.744, discriminator_real_loss=1.398, discriminator_fake_loss=1.346, generator_loss=29.19, generator_mel_loss=21.68, generator_kl_loss=1.264, generator_dur_loss=1.885, generator_adv_loss=1.94, generator_feat_match_loss=2.422, over 4736.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 03:25:40,955 INFO [train.py:919] (2/6) Start epoch 38
2024-03-12 03:26:39,468 INFO [train.py:527] (2/6) Epoch 38, batch 12, global_batch_idx: 4600, batch size: 58, loss[discriminator_loss=2.735, discriminator_real_loss=1.491, discriminator_fake_loss=1.244, generator_loss=28.38, generator_mel_loss=21.25, generator_kl_loss=1.121, generator_dur_loss=1.924, generator_adv_loss=1.831, generator_feat_match_loss=2.245, over 58.00 samples.], tot_loss[discriminator_loss=2.761, discriminator_real_loss=1.413, discriminator_fake_loss=1.348, generator_loss=28.95, generator_mel_loss=21.51, generator_kl_loss=1.256, generator_dur_loss=1.883, generator_adv_loss=1.907, generator_feat_match_loss=2.386, over 718.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 03:26:39,471 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 03:26:47,323 INFO [train.py:591] (2/6) Epoch 38, validation: discriminator_loss=2.736, discriminator_real_loss=1.45, discriminator_fake_loss=1.286, generator_loss=27.59, generator_mel_loss=21.01, generator_kl_loss=1.146, generator_dur_loss=1.966, generator_adv_loss=1.795, generator_feat_match_loss=1.672, over 100.00 samples.
2024-03-12 03:26:47,323 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 03:29:05,392 INFO [train.py:527] (2/6) Epoch 38, batch 62, global_batch_idx: 4650, batch size: 56, loss[discriminator_loss=2.725, discriminator_real_loss=1.413, discriminator_fake_loss=1.312, generator_loss=28.82, generator_mel_loss=21.27, generator_kl_loss=1.326, generator_dur_loss=1.871, generator_adv_loss=2.066, generator_feat_match_loss=2.29, over 56.00 samples.], tot_loss[discriminator_loss=2.736, discriminator_real_loss=1.4, discriminator_fake_loss=1.336, generator_loss=29.21, generator_mel_loss=21.74, generator_kl_loss=1.259, generator_dur_loss=1.89, generator_adv_loss=1.904, generator_feat_match_loss=2.417, over 3486.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 03:31:25,943 INFO [train.py:527] (2/6) Epoch 38, batch 112, global_batch_idx: 4700, batch size: 13, loss[discriminator_loss=2.796, discriminator_real_loss=1.557, discriminator_fake_loss=1.239, generator_loss=31.34, generator_mel_loss=24.05, generator_kl_loss=1.502, generator_dur_loss=1.789, generator_adv_loss=1.772, generator_feat_match_loss=2.227, over 13.00 samples.], tot_loss[discriminator_loss=2.743, discriminator_real_loss=1.407, discriminator_fake_loss=1.336, generator_loss=29.17, generator_mel_loss=21.7, generator_kl_loss=1.252, generator_dur_loss=1.896, generator_adv_loss=1.909, generator_feat_match_loss=2.413, over 6294.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 03:31:59,538 INFO [train.py:919] (2/6) Start epoch 39
2024-03-12 03:34:09,071 INFO [train.py:527] (2/6) Epoch 39, batch 38, global_batch_idx: 4750, batch size: 59, loss[discriminator_loss=2.707, discriminator_real_loss=1.28, discriminator_fake_loss=1.427, generator_loss=28.52, generator_mel_loss=21.19, generator_kl_loss=1.271, generator_dur_loss=1.888, generator_adv_loss=1.991, generator_feat_match_loss=2.178, over 59.00 samples.], tot_loss[discriminator_loss=2.773, discriminator_real_loss=1.437, discriminator_fake_loss=1.336, generator_loss=29.23, generator_mel_loss=21.63, generator_kl_loss=1.287, generator_dur_loss=1.902, generator_adv_loss=1.99, generator_feat_match_loss=2.423, over 2199.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 03:36:27,784 INFO [train.py:527] (2/6) Epoch 39, batch 88, global_batch_idx: 4800, batch size: 47, loss[discriminator_loss=2.703, discriminator_real_loss=1.333, discriminator_fake_loss=1.37, generator_loss=28.96, generator_mel_loss=21.43, generator_kl_loss=1.389, generator_dur_loss=1.836, generator_adv_loss=1.942, generator_feat_match_loss=2.364, over 47.00 samples.], tot_loss[discriminator_loss=2.76, discriminator_real_loss=1.423, discriminator_fake_loss=1.338, generator_loss=29.22, generator_mel_loss=21.67, generator_kl_loss=1.275, generator_dur_loss=1.901, generator_adv_loss=1.958, generator_feat_match_loss=2.424, over 5139.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 03:36:27,785 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 03:36:36,858 INFO [train.py:591] (2/6) Epoch 39, validation: discriminator_loss=2.785, discriminator_real_loss=1.46, discriminator_fake_loss=1.325, generator_loss=28.19, generator_mel_loss=21.57, generator_kl_loss=1.116, generator_dur_loss=1.951, generator_adv_loss=1.746, generator_feat_match_loss=1.807, over 100.00 samples.
2024-03-12 03:36:36,859 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 03:38:15,485 INFO [train.py:919] (2/6) Start epoch 40
2024-03-12 03:39:17,970 INFO [train.py:527] (2/6) Epoch 40, batch 14, global_batch_idx: 4850, batch size: 48, loss[discriminator_loss=2.626, discriminator_real_loss=1.449, discriminator_fake_loss=1.177, generator_loss=29.59, generator_mel_loss=21.72, generator_kl_loss=1.409, generator_dur_loss=1.779, generator_adv_loss=1.98, generator_feat_match_loss=2.698, over 48.00 samples.], tot_loss[discriminator_loss=2.725, discriminator_real_loss=1.387, discriminator_fake_loss=1.338, generator_loss=28.98, generator_mel_loss=21.44, generator_kl_loss=1.253, generator_dur_loss=1.874, generator_adv_loss=1.957, generator_feat_match_loss=2.458, over 827.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 03:41:34,705 INFO [train.py:527] (2/6) Epoch 40, batch 64, global_batch_idx: 4900, batch size: 96, loss[discriminator_loss=2.667, discriminator_real_loss=1.402, discriminator_fake_loss=1.265, generator_loss=28.88, generator_mel_loss=20.54, generator_kl_loss=1.125, generator_dur_loss=2.024, generator_adv_loss=2.281, generator_feat_match_loss=2.919, over 96.00 samples.], tot_loss[discriminator_loss=2.742, discriminator_real_loss=1.404, discriminator_fake_loss=1.338, generator_loss=29.15, generator_mel_loss=21.57, generator_kl_loss=1.254, generator_dur_loss=1.889, generator_adv_loss=1.946, generator_feat_match_loss=2.486, over 3749.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 03:43:52,654 INFO [train.py:527] (2/6) Epoch 40, batch 114, global_batch_idx: 4950, batch size: 36, loss[discriminator_loss=2.706, discriminator_real_loss=1.386, discriminator_fake_loss=1.32, generator_loss=28.85, generator_mel_loss=21.57, generator_kl_loss=1.346, generator_dur_loss=1.867, generator_adv_loss=1.796, generator_feat_match_loss=2.278, over 36.00 samples.], tot_loss[discriminator_loss=2.757, discriminator_real_loss=1.422, discriminator_fake_loss=1.335, generator_loss=29.05, generator_mel_loss=21.46, generator_kl_loss=1.264, generator_dur_loss=1.89, generator_adv_loss=1.97, generator_feat_match_loss=2.468, over 6570.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 03:44:20,313 INFO [train.py:919] (2/6) Start epoch 41
2024-03-12 03:46:42,087 INFO [train.py:527] (2/6) Epoch 41, batch 40, global_batch_idx: 5000, batch size: 48, loss[discriminator_loss=2.65, discriminator_real_loss=1.324, discriminator_fake_loss=1.326, generator_loss=28.97, generator_mel_loss=21.41, generator_kl_loss=1.297, generator_dur_loss=1.812, generator_adv_loss=1.877, generator_feat_match_loss=2.579, over 48.00 samples.], tot_loss[discriminator_loss=2.723, discriminator_real_loss=1.383, discriminator_fake_loss=1.34, generator_loss=28.81, generator_mel_loss=21.38, generator_kl_loss=1.266, generator_dur_loss=1.89, generator_adv_loss=1.874, generator_feat_match_loss=2.392, over 2364.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 03:46:42,089 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 03:46:50,132 INFO [train.py:591] (2/6) Epoch 41, validation: discriminator_loss=2.762, discriminator_real_loss=1.392, discriminator_fake_loss=1.37, generator_loss=28.57, generator_mel_loss=21.81, generator_kl_loss=1.047, generator_dur_loss=1.956, generator_adv_loss=1.772, generator_feat_match_loss=1.978, over 100.00 samples.
2024-03-12 03:46:50,133 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 03:49:08,360 INFO [train.py:527] (2/6) Epoch 41, batch 90, global_batch_idx: 5050, batch size: 18, loss[discriminator_loss=2.635, discriminator_real_loss=1.307, discriminator_fake_loss=1.328, generator_loss=31.03, generator_mel_loss=23.37, generator_kl_loss=1.546, generator_dur_loss=1.684, generator_adv_loss=1.871, generator_feat_match_loss=2.562, over 18.00 samples.], tot_loss[discriminator_loss=2.732, discriminator_real_loss=1.393, discriminator_fake_loss=1.339, generator_loss=28.98, generator_mel_loss=21.52, generator_kl_loss=1.273, generator_dur_loss=1.891, generator_adv_loss=1.892, generator_feat_match_loss=2.402, over 5279.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 03:50:41,977 INFO [train.py:919] (2/6) Start epoch 42
2024-03-12 03:51:51,537 INFO [train.py:527] (2/6) Epoch 42, batch 16, global_batch_idx: 5100, batch size: 77, loss[discriminator_loss=2.664, discriminator_real_loss=1.35, discriminator_fake_loss=1.314, generator_loss=29.12, generator_mel_loss=21.36, generator_kl_loss=1.174, generator_dur_loss=1.966, generator_adv_loss=1.836, generator_feat_match_loss=2.786, over 77.00 samples.], tot_loss[discriminator_loss=2.738, discriminator_real_loss=1.38, discriminator_fake_loss=1.358, generator_loss=28.96, generator_mel_loss=21.44, generator_kl_loss=1.245, generator_dur_loss=1.908, generator_adv_loss=1.908, generator_feat_match_loss=2.455, over 1045.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 03:54:10,667 INFO [train.py:527] (2/6) Epoch 42, batch 66, global_batch_idx: 5150, batch size: 74, loss[discriminator_loss=2.728, discriminator_real_loss=1.354, discriminator_fake_loss=1.374, generator_loss=28.52, generator_mel_loss=21.21, generator_kl_loss=1.197, generator_dur_loss=1.918, generator_adv_loss=1.825, generator_feat_match_loss=2.373, over 74.00 samples.], tot_loss[discriminator_loss=2.748, discriminator_real_loss=1.399, discriminator_fake_loss=1.348, generator_loss=28.98, generator_mel_loss=21.39, generator_kl_loss=1.264, generator_dur_loss=1.903, generator_adv_loss=1.943, generator_feat_match_loss=2.483, over 3974.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 03:56:26,610 INFO [train.py:527] (2/6) Epoch 42, batch 116, global_batch_idx: 5200, batch size: 83, loss[discriminator_loss=2.737, discriminator_real_loss=1.543, discriminator_fake_loss=1.195, generator_loss=28.72, generator_mel_loss=21.09, generator_kl_loss=1.338, generator_dur_loss=1.96, generator_adv_loss=1.857, generator_feat_match_loss=2.471, over 83.00 samples.], tot_loss[discriminator_loss=2.738, discriminator_real_loss=1.394, discriminator_fake_loss=1.344, generator_loss=29.04, generator_mel_loss=21.46, generator_kl_loss=1.271, generator_dur_loss=1.891, generator_adv_loss=1.929, generator_feat_match_loss=2.485, over 6673.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 03:56:26,612 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 03:56:35,583 INFO [train.py:591] (2/6) Epoch 42, validation: discriminator_loss=2.725, discriminator_real_loss=1.443, discriminator_fake_loss=1.282, generator_loss=27.96, generator_mel_loss=21.22, generator_kl_loss=0.9713, generator_dur_loss=1.932, generator_adv_loss=1.878, generator_feat_match_loss=1.963, over 100.00 samples.
2024-03-12 03:56:35,584 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 03:56:56,444 INFO [train.py:919] (2/6) Start epoch 43
2024-03-12 03:59:14,947 INFO [train.py:527] (2/6) Epoch 43, batch 42, global_batch_idx: 5250, batch size: 53, loss[discriminator_loss=2.818, discriminator_real_loss=1.5, discriminator_fake_loss=1.318, generator_loss=29.23, generator_mel_loss=22.11, generator_kl_loss=1.198, generator_dur_loss=1.86, generator_adv_loss=1.835, generator_feat_match_loss=2.228, over 53.00 samples.], tot_loss[discriminator_loss=2.747, discriminator_real_loss=1.405, discriminator_fake_loss=1.342, generator_loss=28.96, generator_mel_loss=21.49, generator_kl_loss=1.284, generator_dur_loss=1.861, generator_adv_loss=1.901, generator_feat_match_loss=2.423, over 2282.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 04:01:32,824 INFO [train.py:527] (2/6) Epoch 43, batch 92, global_batch_idx: 5300, batch size: 66, loss[discriminator_loss=2.859, discriminator_real_loss=1.474, discriminator_fake_loss=1.385, generator_loss=27.46, generator_mel_loss=20.67, generator_kl_loss=1.253, generator_dur_loss=1.908, generator_adv_loss=1.809, generator_feat_match_loss=1.825, over 66.00 samples.], tot_loss[discriminator_loss=2.754, discriminator_real_loss=1.41, discriminator_fake_loss=1.344, generator_loss=29.01, generator_mel_loss=21.42, generator_kl_loss=1.282, generator_dur_loss=1.873, generator_adv_loss=1.956, generator_feat_match_loss=2.485, over 5142.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 04:03:01,629 INFO [train.py:919] (2/6) Start epoch 44
2024-03-12 04:04:18,507 INFO [train.py:527] (2/6) Epoch 44, batch 18, global_batch_idx: 5350, batch size: 17, loss[discriminator_loss=2.727, discriminator_real_loss=1.471, discriminator_fake_loss=1.256, generator_loss=32.96, generator_mel_loss=24.12, generator_kl_loss=1.598, generator_dur_loss=1.637, generator_adv_loss=2.005, generator_feat_match_loss=3.595, over 17.00 samples.], tot_loss[discriminator_loss=2.717, discriminator_real_loss=1.397, discriminator_fake_loss=1.32, generator_loss=29.47, generator_mel_loss=21.94, generator_kl_loss=1.33, generator_dur_loss=1.819, generator_adv_loss=1.924, generator_feat_match_loss=2.459, over 868.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 04:06:38,354 INFO [train.py:527] (2/6) Epoch 44, batch 68, global_batch_idx: 5400, batch size: 31, loss[discriminator_loss=2.739, discriminator_real_loss=1.49, discriminator_fake_loss=1.249, generator_loss=28.8, generator_mel_loss=21.45, generator_kl_loss=1.323, generator_dur_loss=1.752, generator_adv_loss=2.017, generator_feat_match_loss=2.259, over 31.00 samples.], tot_loss[discriminator_loss=2.747, discriminator_real_loss=1.398, discriminator_fake_loss=1.349, generator_loss=28.76, generator_mel_loss=21.34, generator_kl_loss=1.274, generator_dur_loss=1.872, generator_adv_loss=1.879, generator_feat_match_loss=2.392, over 3901.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 04:06:38,355 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 04:06:46,212 INFO [train.py:591] (2/6) Epoch 44, validation: discriminator_loss=2.79, discriminator_real_loss=1.573, discriminator_fake_loss=1.217, generator_loss=27.42, generator_mel_loss=20.68, generator_kl_loss=1.082, generator_dur_loss=1.954, generator_adv_loss=1.905, generator_feat_match_loss=1.804, over 100.00 samples.
2024-03-12 04:06:46,213 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 04:09:04,560 INFO [train.py:527] (2/6) Epoch 44, batch 118, global_batch_idx: 5450, batch size: 66, loss[discriminator_loss=2.653, discriminator_real_loss=1.419, discriminator_fake_loss=1.234, generator_loss=28.89, generator_mel_loss=20.86, generator_kl_loss=1.2, generator_dur_loss=1.929, generator_adv_loss=2.32, generator_feat_match_loss=2.579, over 66.00 samples.], tot_loss[discriminator_loss=2.748, discriminator_real_loss=1.398, discriminator_fake_loss=1.35, generator_loss=28.84, generator_mel_loss=21.31, generator_kl_loss=1.279, generator_dur_loss=1.873, generator_adv_loss=1.919, generator_feat_match_loss=2.455, over 6700.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 04:09:19,162 INFO [train.py:919] (2/6) Start epoch 45
2024-03-12 04:11:43,234 INFO [train.py:527] (2/6) Epoch 45, batch 44, global_batch_idx: 5500, batch size: 55, loss[discriminator_loss=2.729, discriminator_real_loss=1.404, discriminator_fake_loss=1.325, generator_loss=29.87, generator_mel_loss=22.22, generator_kl_loss=1.19, generator_dur_loss=1.841, generator_adv_loss=1.91, generator_feat_match_loss=2.717, over 55.00 samples.], tot_loss[discriminator_loss=2.736, discriminator_real_loss=1.398, discriminator_fake_loss=1.338, generator_loss=28.63, generator_mel_loss=21.23, generator_kl_loss=1.28, generator_dur_loss=1.853, generator_adv_loss=1.891, generator_feat_match_loss=2.384, over 2504.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 04:14:03,103 INFO [train.py:527] (2/6) Epoch 45, batch 94, global_batch_idx: 5550, batch size: 96, loss[discriminator_loss=2.747, discriminator_real_loss=1.343, discriminator_fake_loss=1.404, generator_loss=29.1, generator_mel_loss=21.3, generator_kl_loss=1.239, generator_dur_loss=1.995, generator_adv_loss=2.088, generator_feat_match_loss=2.474, over 96.00 samples.], tot_loss[discriminator_loss=2.736, discriminator_real_loss=1.393, discriminator_fake_loss=1.343, generator_loss=28.75, generator_mel_loss=21.22, generator_kl_loss=1.294, generator_dur_loss=1.876, generator_adv_loss=1.907, generator_feat_match_loss=2.457, over 5553.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 04:15:26,420 INFO [train.py:919] (2/6) Start epoch 46
2024-03-12 04:16:45,580 INFO [train.py:527] (2/6) Epoch 46, batch 20, global_batch_idx: 5600, batch size: 72, loss[discriminator_loss=2.733, discriminator_real_loss=1.446, discriminator_fake_loss=1.288, generator_loss=29.36, generator_mel_loss=21.93, generator_kl_loss=1.236, generator_dur_loss=1.919, generator_adv_loss=1.791, generator_feat_match_loss=2.487, over 72.00 samples.], tot_loss[discriminator_loss=2.737, discriminator_real_loss=1.407, discriminator_fake_loss=1.33, generator_loss=28.74, generator_mel_loss=21.21, generator_kl_loss=1.256, generator_dur_loss=1.879, generator_adv_loss=1.921, generator_feat_match_loss=2.468, over 1304.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 04:16:45,582 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 04:16:53,514 INFO [train.py:591] (2/6) Epoch 46, validation: discriminator_loss=2.71, discriminator_real_loss=1.41, discriminator_fake_loss=1.301, generator_loss=27.62, generator_mel_loss=20.81, generator_kl_loss=1.172, generator_dur_loss=1.926, generator_adv_loss=1.793, generator_feat_match_loss=1.917, over 100.00 samples.
2024-03-12 04:16:53,515 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 04:19:10,762 INFO [train.py:527] (2/6) Epoch 46, batch 70, global_batch_idx: 5650, batch size: 42, loss[discriminator_loss=2.749, discriminator_real_loss=1.343, discriminator_fake_loss=1.406, generator_loss=27.84, generator_mel_loss=20.52, generator_kl_loss=1.298, generator_dur_loss=1.815, generator_adv_loss=1.898, generator_feat_match_loss=2.305, over 42.00 samples.], tot_loss[discriminator_loss=2.74, discriminator_real_loss=1.407, discriminator_fake_loss=1.333, generator_loss=28.71, generator_mel_loss=21.2, generator_kl_loss=1.293, generator_dur_loss=1.856, generator_adv_loss=1.903, generator_feat_match_loss=2.458, over 3890.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 04:21:29,305 INFO [train.py:527] (2/6) Epoch 46, batch 120, global_batch_idx: 5700, batch size: 58, loss[discriminator_loss=2.779, discriminator_real_loss=1.43, discriminator_fake_loss=1.348, generator_loss=27.82, generator_mel_loss=20.66, generator_kl_loss=1.324, generator_dur_loss=1.812, generator_adv_loss=1.715, generator_feat_match_loss=2.309, over 58.00 samples.], tot_loss[discriminator_loss=2.732, discriminator_real_loss=1.4, discriminator_fake_loss=1.332, generator_loss=28.74, generator_mel_loss=21.19, generator_kl_loss=1.301, generator_dur_loss=1.854, generator_adv_loss=1.899, generator_feat_match_loss=2.496, over 6803.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 04:21:39,912 INFO [train.py:919] (2/6) Start epoch 47
2024-03-12 04:24:10,994 INFO [train.py:527] (2/6) Epoch 47, batch 46, global_batch_idx: 5750, batch size: 66, loss[discriminator_loss=2.805, discriminator_real_loss=1.495, discriminator_fake_loss=1.31, generator_loss=28.3, generator_mel_loss=21.02, generator_kl_loss=1.133, generator_dur_loss=1.835, generator_adv_loss=1.977, generator_feat_match_loss=2.338, over 66.00 samples.], tot_loss[discriminator_loss=2.753, discriminator_real_loss=1.412, discriminator_fake_loss=1.341, generator_loss=28.73, generator_mel_loss=21.12, generator_kl_loss=1.302, generator_dur_loss=1.861, generator_adv_loss=1.946, generator_feat_match_loss=2.505, over 2769.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 04:26:28,680 INFO [train.py:527] (2/6) Epoch 47, batch 96, global_batch_idx: 5800, batch size: 31, loss[discriminator_loss=2.7, discriminator_real_loss=1.455, discriminator_fake_loss=1.245, generator_loss=28.37, generator_mel_loss=21.13, generator_kl_loss=1.191, generator_dur_loss=1.768, generator_adv_loss=1.846, generator_feat_match_loss=2.44, over 31.00 samples.], tot_loss[discriminator_loss=2.749, discriminator_real_loss=1.407, discriminator_fake_loss=1.342, generator_loss=28.49, generator_mel_loss=20.97, generator_kl_loss=1.304, generator_dur_loss=1.854, generator_adv_loss=1.918, generator_feat_match_loss=2.442, over 5521.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 04:26:28,681 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 04:26:37,447 INFO [train.py:591] (2/6) Epoch 47, validation: discriminator_loss=2.724, discriminator_real_loss=1.397, discriminator_fake_loss=1.327, generator_loss=27.83, generator_mel_loss=20.92, generator_kl_loss=1.124, generator_dur_loss=1.896, generator_adv_loss=1.839, generator_feat_match_loss=2.052, over 100.00 samples.
2024-03-12 04:26:37,448 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 04:27:54,755 INFO [train.py:919] (2/6) Start epoch 48
2024-03-12 04:29:21,038 INFO [train.py:527] (2/6) Epoch 48, batch 22, global_batch_idx: 5850, batch size: 62, loss[discriminator_loss=2.729, discriminator_real_loss=1.355, discriminator_fake_loss=1.375, generator_loss=29.86, generator_mel_loss=21.88, generator_kl_loss=1.334, generator_dur_loss=1.808, generator_adv_loss=1.992, generator_feat_match_loss=2.845, over 62.00 samples.], tot_loss[discriminator_loss=2.756, discriminator_real_loss=1.449, discriminator_fake_loss=1.307, generator_loss=29.09, generator_mel_loss=21.11, generator_kl_loss=1.297, generator_dur_loss=1.843, generator_adv_loss=2.07, generator_feat_match_loss=2.774, over 1306.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 04:31:38,654 INFO [train.py:527] (2/6) Epoch 48, batch 72, global_batch_idx: 5900, batch size: 48, loss[discriminator_loss=2.832, discriminator_real_loss=1.478, discriminator_fake_loss=1.353, generator_loss=28.47, generator_mel_loss=21.05, generator_kl_loss=1.421, generator_dur_loss=1.818, generator_adv_loss=1.948, generator_feat_match_loss=2.234, over 48.00 samples.], tot_loss[discriminator_loss=2.763, discriminator_real_loss=1.423, discriminator_fake_loss=1.34, generator_loss=28.65, generator_mel_loss=20.97, generator_kl_loss=1.316, generator_dur_loss=1.845, generator_adv_loss=1.983, generator_feat_match_loss=2.54, over 4059.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 04:33:57,412 INFO [train.py:527] (2/6) Epoch 48, batch 122, global_batch_idx: 5950, batch size: 31, loss[discriminator_loss=2.845, discriminator_real_loss=1.343, discriminator_fake_loss=1.501, generator_loss=28.63, generator_mel_loss=21.38, generator_kl_loss=1.358, generator_dur_loss=1.709, generator_adv_loss=1.743, generator_feat_match_loss=2.432, over 31.00 samples.], tot_loss[discriminator_loss=2.756, discriminator_real_loss=1.413, discriminator_fake_loss=1.343, generator_loss=28.47, generator_mel_loss=20.91, generator_kl_loss=1.3, generator_dur_loss=1.857, generator_adv_loss=1.928, generator_feat_match_loss=2.472, over 7140.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 04:34:02,840 INFO [train.py:919] (2/6) Start epoch 49
2024-03-12 04:36:36,718 INFO [train.py:527] (2/6) Epoch 49, batch 48, global_batch_idx: 6000, batch size: 55, loss[discriminator_loss=2.724, discriminator_real_loss=1.372, discriminator_fake_loss=1.352, generator_loss=29.97, generator_mel_loss=22.13, generator_kl_loss=1.319, generator_dur_loss=1.753, generator_adv_loss=2.07, generator_feat_match_loss=2.689, over 55.00 samples.], tot_loss[discriminator_loss=2.744, discriminator_real_loss=1.401, discriminator_fake_loss=1.343, generator_loss=28.52, generator_mel_loss=21.02, generator_kl_loss=1.308, generator_dur_loss=1.838, generator_adv_loss=1.881, generator_feat_match_loss=2.469, over 2726.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 04:36:36,719 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 04:36:44,771 INFO [train.py:591] (2/6) Epoch 49, validation: discriminator_loss=2.812, discriminator_real_loss=1.581, discriminator_fake_loss=1.231, generator_loss=27.72, generator_mel_loss=20.69, generator_kl_loss=1.054, generator_dur_loss=1.903, generator_adv_loss=2.012, generator_feat_match_loss=2.069, over 100.00 samples.
2024-03-12 04:36:44,772 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 04:39:03,189 INFO [train.py:527] (2/6) Epoch 49, batch 98, global_batch_idx: 6050, batch size: 58, loss[discriminator_loss=2.843, discriminator_real_loss=1.348, discriminator_fake_loss=1.495, generator_loss=28.01, generator_mel_loss=20.54, generator_kl_loss=1.412, generator_dur_loss=1.848, generator_adv_loss=2.02, generator_feat_match_loss=2.193, over 58.00 samples.], tot_loss[discriminator_loss=2.744, discriminator_real_loss=1.396, discriminator_fake_loss=1.347, generator_loss=28.5, generator_mel_loss=20.97, generator_kl_loss=1.311, generator_dur_loss=1.851, generator_adv_loss=1.88, generator_feat_match_loss=2.48, over 5652.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 04:40:16,145 INFO [train.py:919] (2/6) Start epoch 50
2024-03-12 04:41:46,350 INFO [train.py:527] (2/6) Epoch 50, batch 24, global_batch_idx: 6100, batch size: 55, loss[discriminator_loss=2.688, discriminator_real_loss=1.407, discriminator_fake_loss=1.281, generator_loss=29.89, generator_mel_loss=21.85, generator_kl_loss=1.413, generator_dur_loss=1.807, generator_adv_loss=1.926, generator_feat_match_loss=2.891, over 55.00 samples.], tot_loss[discriminator_loss=2.734, discriminator_real_loss=1.393, discriminator_fake_loss=1.341, generator_loss=28.84, generator_mel_loss=21.14, generator_kl_loss=1.349, generator_dur_loss=1.815, generator_adv_loss=1.911, generator_feat_match_loss=2.624, over 1359.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 04:44:05,991 INFO [train.py:527] (2/6) Epoch 50, batch 74, global_batch_idx: 6150, batch size: 80, loss[discriminator_loss=2.59, discriminator_real_loss=1.17, discriminator_fake_loss=1.42, generator_loss=29.42, generator_mel_loss=21.17, generator_kl_loss=1.262, generator_dur_loss=1.903, generator_adv_loss=2.25, generator_feat_match_loss=2.843, over 80.00 samples.], tot_loss[discriminator_loss=2.741, discriminator_real_loss=1.399, discriminator_fake_loss=1.342, generator_loss=28.6, generator_mel_loss=20.96, generator_kl_loss=1.328, generator_dur_loss=1.837, generator_adv_loss=1.926, generator_feat_match_loss=2.548, over 4302.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 04:46:23,957 INFO [train.py:919] (2/6) Start epoch 51
2024-03-12 04:46:48,867 INFO [train.py:527] (2/6) Epoch 51, batch 0, global_batch_idx: 6200, batch size: 31, loss[discriminator_loss=2.672, discriminator_real_loss=1.298, discriminator_fake_loss=1.374, generator_loss=28.99, generator_mel_loss=21.53, generator_kl_loss=1.492, generator_dur_loss=1.722, generator_adv_loss=1.856, generator_feat_match_loss=2.381, over 31.00 samples.], tot_loss[discriminator_loss=2.672, discriminator_real_loss=1.298, discriminator_fake_loss=1.374, generator_loss=28.99, generator_mel_loss=21.53, generator_kl_loss=1.492, generator_dur_loss=1.722, generator_adv_loss=1.856, generator_feat_match_loss=2.381, over 31.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 04:46:48,869 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 04:46:56,728 INFO [train.py:591] (2/6) Epoch 51, validation: discriminator_loss=2.728, discriminator_real_loss=1.345, discriminator_fake_loss=1.383, generator_loss=27.59, generator_mel_loss=20.65, generator_kl_loss=1.177, generator_dur_loss=1.902, generator_adv_loss=1.782, generator_feat_match_loss=2.077, over 100.00 samples.
2024-03-12 04:46:56,777 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 04:49:14,960 INFO [train.py:527] (2/6) Epoch 51, batch 50, global_batch_idx: 6250, batch size: 70, loss[discriminator_loss=2.665, discriminator_real_loss=1.252, discriminator_fake_loss=1.413, generator_loss=29.25, generator_mel_loss=21.35, generator_kl_loss=1.147, generator_dur_loss=1.897, generator_adv_loss=1.904, generator_feat_match_loss=2.955, over 70.00 samples.], tot_loss[discriminator_loss=2.724, discriminator_real_loss=1.379, discriminator_fake_loss=1.344, generator_loss=28.33, generator_mel_loss=20.76, generator_kl_loss=1.328, generator_dur_loss=1.823, generator_adv_loss=1.882, generator_feat_match_loss=2.535, over 2524.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 04:51:35,335 INFO [train.py:527] (2/6) Epoch 51, batch 100, global_batch_idx: 6300, batch size: 53, loss[discriminator_loss=2.73, discriminator_real_loss=1.367, discriminator_fake_loss=1.362, generator_loss=28.58, generator_mel_loss=21, generator_kl_loss=1.365, generator_dur_loss=1.806, generator_adv_loss=1.91, generator_feat_match_loss=2.494, over 53.00 samples.], tot_loss[discriminator_loss=2.749, discriminator_real_loss=1.4, discriminator_fake_loss=1.349, generator_loss=28.38, generator_mel_loss=20.78, generator_kl_loss=1.317, generator_dur_loss=1.84, generator_adv_loss=1.91, generator_feat_match_loss=2.529, over 5466.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 04:52:40,266 INFO [train.py:919] (2/6) Start epoch 52
2024-03-12 04:54:18,861 INFO [train.py:527] (2/6) Epoch 52, batch 26, global_batch_idx: 6350, batch size: 77, loss[discriminator_loss=2.683, discriminator_real_loss=1.257, discriminator_fake_loss=1.426, generator_loss=28.28, generator_mel_loss=20.4, generator_kl_loss=1.305, generator_dur_loss=1.914, generator_adv_loss=1.977, generator_feat_match_loss=2.677, over 77.00 samples.], tot_loss[discriminator_loss=2.773, discriminator_real_loss=1.439, discriminator_fake_loss=1.334, generator_loss=28.58, generator_mel_loss=20.67, generator_kl_loss=1.318, generator_dur_loss=1.84, generator_adv_loss=2.048, generator_feat_match_loss=2.703, over 1535.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 04:56:38,060 INFO [train.py:527] (2/6) Epoch 52, batch 76, global_batch_idx: 6400, batch size: 77, loss[discriminator_loss=2.694, discriminator_real_loss=1.345, discriminator_fake_loss=1.35, generator_loss=29.03, generator_mel_loss=21, generator_kl_loss=1.323, generator_dur_loss=1.921, generator_adv_loss=2.031, generator_feat_match_loss=2.749, over 77.00 samples.], tot_loss[discriminator_loss=2.754, discriminator_real_loss=1.414, discriminator_fake_loss=1.34, generator_loss=28.41, generator_mel_loss=20.71, generator_kl_loss=1.315, generator_dur_loss=1.84, generator_adv_loss=1.972, generator_feat_match_loss=2.579, over 4477.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 04:56:38,062 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 04:56:46,043 INFO [train.py:591] (2/6) Epoch 52, validation: discriminator_loss=2.773, discriminator_real_loss=1.574, discriminator_fake_loss=1.199, generator_loss=26.39, generator_mel_loss=19.74, generator_kl_loss=1.16, generator_dur_loss=1.911, generator_adv_loss=1.953, generator_feat_match_loss=1.628, over 100.00 samples.
2024-03-12 04:56:46,044 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 04:58:55,996 INFO [train.py:919] (2/6) Start epoch 53
2024-03-12 04:59:25,794 INFO [train.py:527] (2/6) Epoch 53, batch 2, global_batch_idx: 6450, batch size: 42, loss[discriminator_loss=2.804, discriminator_real_loss=1.412, discriminator_fake_loss=1.392, generator_loss=27.7, generator_mel_loss=20.22, generator_kl_loss=1.498, generator_dur_loss=1.767, generator_adv_loss=1.989, generator_feat_match_loss=2.226, over 42.00 samples.], tot_loss[discriminator_loss=2.769, discriminator_real_loss=1.491, discriminator_fake_loss=1.277, generator_loss=28.27, generator_mel_loss=20.71, generator_kl_loss=1.424, generator_dur_loss=1.787, generator_adv_loss=1.92, generator_feat_match_loss=2.426, over 126.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 05:01:44,714 INFO [train.py:527] (2/6) Epoch 53, batch 52, global_batch_idx: 6500, batch size: 61, loss[discriminator_loss=2.726, discriminator_real_loss=1.372, discriminator_fake_loss=1.355, generator_loss=28.89, generator_mel_loss=21.19, generator_kl_loss=1.355, generator_dur_loss=1.777, generator_adv_loss=1.885, generator_feat_match_loss=2.684, over 61.00 samples.], tot_loss[discriminator_loss=2.745, discriminator_real_loss=1.397, discriminator_fake_loss=1.348, generator_loss=28.17, generator_mel_loss=20.63, generator_kl_loss=1.308, generator_dur_loss=1.854, generator_adv_loss=1.891, generator_feat_match_loss=2.479, over 3026.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 05:04:04,407 INFO [train.py:527] (2/6) Epoch 53, batch 102, global_batch_idx: 6550, batch size: 66, loss[discriminator_loss=2.758, discriminator_real_loss=1.395, discriminator_fake_loss=1.363, generator_loss=27.01, generator_mel_loss=19.93, generator_kl_loss=1.337, generator_dur_loss=1.916, generator_adv_loss=1.734, generator_feat_match_loss=2.091, over 66.00 samples.], tot_loss[discriminator_loss=2.749, discriminator_real_loss=1.399, discriminator_fake_loss=1.351, generator_loss=28.15, generator_mel_loss=20.62, generator_kl_loss=1.319, generator_dur_loss=1.846, generator_adv_loss=1.882, generator_feat_match_loss=2.481, over 5783.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 05:05:04,008 INFO [train.py:919] (2/6) Start epoch 54
2024-03-12 05:06:44,473 INFO [train.py:527] (2/6) Epoch 54, batch 28, global_batch_idx: 6600, batch size: 39, loss[discriminator_loss=2.753, discriminator_real_loss=1.304, discriminator_fake_loss=1.449, generator_loss=25.77, generator_mel_loss=18.6, generator_kl_loss=1.51, generator_dur_loss=1.767, generator_adv_loss=1.819, generator_feat_match_loss=2.065, over 39.00 samples.], tot_loss[discriminator_loss=2.753, discriminator_real_loss=1.41, discriminator_fake_loss=1.342, generator_loss=28.11, generator_mel_loss=20.58, generator_kl_loss=1.335, generator_dur_loss=1.828, generator_adv_loss=1.873, generator_feat_match_loss=2.491, over 1533.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 05:06:44,475 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 05:06:52,267 INFO [train.py:591] (2/6) Epoch 54, validation: discriminator_loss=2.733, discriminator_real_loss=1.331, discriminator_fake_loss=1.402, generator_loss=27.36, generator_mel_loss=20.51, generator_kl_loss=1.199, generator_dur_loss=1.892, generator_adv_loss=1.785, generator_feat_match_loss=1.97, over 100.00 samples.
2024-03-12 05:06:52,268 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 05:09:08,090 INFO [train.py:527] (2/6) Epoch 54, batch 78, global_batch_idx: 6650, batch size: 80, loss[discriminator_loss=2.757, discriminator_real_loss=1.366, discriminator_fake_loss=1.391, generator_loss=28.49, generator_mel_loss=20.92, generator_kl_loss=1.375, generator_dur_loss=1.824, generator_adv_loss=1.934, generator_feat_match_loss=2.437, over 80.00 samples.], tot_loss[discriminator_loss=2.744, discriminator_real_loss=1.405, discriminator_fake_loss=1.339, generator_loss=28.13, generator_mel_loss=20.54, generator_kl_loss=1.335, generator_dur_loss=1.83, generator_adv_loss=1.913, generator_feat_match_loss=2.509, over 4383.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 05:11:16,345 INFO [train.py:919] (2/6) Start epoch 55
2024-03-12 05:11:50,267 INFO [train.py:527] (2/6) Epoch 55, batch 4, global_batch_idx: 6700, batch size: 25, loss[discriminator_loss=2.715, discriminator_real_loss=1.474, discriminator_fake_loss=1.241, generator_loss=28.63, generator_mel_loss=21.1, generator_kl_loss=1.391, generator_dur_loss=1.721, generator_adv_loss=1.751, generator_feat_match_loss=2.663, over 25.00 samples.], tot_loss[discriminator_loss=2.773, discriminator_real_loss=1.341, discriminator_fake_loss=1.432, generator_loss=28.07, generator_mel_loss=20.31, generator_kl_loss=1.328, generator_dur_loss=1.899, generator_adv_loss=1.958, generator_feat_match_loss=2.572, over 256.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 05:14:11,428 INFO [train.py:527] (2/6) Epoch 55, batch 54, global_batch_idx: 6750, batch size: 36, loss[discriminator_loss=2.847, discriminator_real_loss=1.41, discriminator_fake_loss=1.437, generator_loss=27.44, generator_mel_loss=20.12, generator_kl_loss=1.462, generator_dur_loss=1.758, generator_adv_loss=1.871, generator_feat_match_loss=2.225, over 36.00 samples.], tot_loss[discriminator_loss=2.747, discriminator_real_loss=1.399, discriminator_fake_loss=1.348, generator_loss=28.39, generator_mel_loss=20.65, generator_kl_loss=1.334, generator_dur_loss=1.854, generator_adv_loss=1.947, generator_feat_match_loss=2.602, over 3269.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 05:16:32,168 INFO [train.py:527] (2/6) Epoch 55, batch 104, global_batch_idx: 6800, batch size: 64, loss[discriminator_loss=2.698, discriminator_real_loss=1.251, discriminator_fake_loss=1.447, generator_loss=28.4, generator_mel_loss=20.79, generator_kl_loss=1.384, generator_dur_loss=1.846, generator_adv_loss=1.804, generator_feat_match_loss=2.567, over 64.00 samples.], tot_loss[discriminator_loss=2.747, discriminator_real_loss=1.401, discriminator_fake_loss=1.346, generator_loss=28.22, generator_mel_loss=20.54, generator_kl_loss=1.321, generator_dur_loss=1.849, generator_adv_loss=1.926, generator_feat_match_loss=2.579, over 6265.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 05:16:32,170 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 05:16:41,182 INFO [train.py:591] (2/6) Epoch 55, validation: discriminator_loss=2.695, discriminator_real_loss=1.381, discriminator_fake_loss=1.314, generator_loss=28.01, generator_mel_loss=20.84, generator_kl_loss=1.443, generator_dur_loss=1.868, generator_adv_loss=1.822, generator_feat_match_loss=2.032, over 100.00 samples.
2024-03-12 05:16:41,183 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 05:17:33,124 INFO [train.py:919] (2/6) Start epoch 56
2024-03-12 05:19:21,128 INFO [train.py:527] (2/6) Epoch 56, batch 30, global_batch_idx: 6850, batch size: 58, loss[discriminator_loss=2.789, discriminator_real_loss=1.479, discriminator_fake_loss=1.31, generator_loss=27.59, generator_mel_loss=20.47, generator_kl_loss=1.333, generator_dur_loss=1.85, generator_adv_loss=1.975, generator_feat_match_loss=1.957, over 58.00 samples.], tot_loss[discriminator_loss=2.757, discriminator_real_loss=1.409, discriminator_fake_loss=1.348, generator_loss=28.22, generator_mel_loss=20.68, generator_kl_loss=1.32, generator_dur_loss=1.835, generator_adv_loss=1.877, generator_feat_match_loss=2.509, over 1831.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 05:21:42,295 INFO [train.py:527] (2/6) Epoch 56, batch 80, global_batch_idx: 6900, batch size: 56, loss[discriminator_loss=2.789, discriminator_real_loss=1.54, discriminator_fake_loss=1.249, generator_loss=28.11, generator_mel_loss=20.84, generator_kl_loss=1.275, generator_dur_loss=1.775, generator_adv_loss=1.816, generator_feat_match_loss=2.412, over 56.00 samples.], tot_loss[discriminator_loss=2.751, discriminator_real_loss=1.407, discriminator_fake_loss=1.344, generator_loss=28.18, generator_mel_loss=20.62, generator_kl_loss=1.319, generator_dur_loss=1.829, generator_adv_loss=1.884, generator_feat_match_loss=2.525, over 4661.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 05:23:44,908 INFO [train.py:919] (2/6) Start epoch 57
2024-03-12 05:24:26,604 INFO [train.py:527] (2/6) Epoch 57, batch 6, global_batch_idx: 6950, batch size: 80, loss[discriminator_loss=2.731, discriminator_real_loss=1.293, discriminator_fake_loss=1.438, generator_loss=28.16, generator_mel_loss=20.32, generator_kl_loss=1.337, generator_dur_loss=1.931, generator_adv_loss=1.918, generator_feat_match_loss=2.649, over 80.00 samples.], tot_loss[discriminator_loss=2.732, discriminator_real_loss=1.394, discriminator_fake_loss=1.337, generator_loss=28.71, generator_mel_loss=20.78, generator_kl_loss=1.424, generator_dur_loss=1.826, generator_adv_loss=1.935, generator_feat_match_loss=2.749, over 401.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 05:26:47,942 INFO [train.py:527] (2/6) Epoch 57, batch 56, global_batch_idx: 7000, batch size: 64, loss[discriminator_loss=2.798, discriminator_real_loss=1.397, discriminator_fake_loss=1.401, generator_loss=27.44, generator_mel_loss=19.92, generator_kl_loss=1.456, generator_dur_loss=1.792, generator_adv_loss=1.904, generator_feat_match_loss=2.36, over 64.00 samples.], tot_loss[discriminator_loss=2.752, discriminator_real_loss=1.408, discriminator_fake_loss=1.344, generator_loss=28.21, generator_mel_loss=20.52, generator_kl_loss=1.337, generator_dur_loss=1.831, generator_adv_loss=1.92, generator_feat_match_loss=2.599, over 3203.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 05:26:47,943 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 05:26:56,060 INFO [train.py:591] (2/6) Epoch 57, validation: discriminator_loss=2.915, discriminator_real_loss=1.59, discriminator_fake_loss=1.324, generator_loss=27.21, generator_mel_loss=20.49, generator_kl_loss=1.026, generator_dur_loss=1.886, generator_adv_loss=1.882, generator_feat_match_loss=1.929, over 100.00 samples.
2024-03-12 05:26:56,061 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 05:29:16,444 INFO [train.py:527] (2/6) Epoch 57, batch 106, global_batch_idx: 7050, batch size: 70, loss[discriminator_loss=2.762, discriminator_real_loss=1.35, discriminator_fake_loss=1.412, generator_loss=28.31, generator_mel_loss=20.39, generator_kl_loss=1.271, generator_dur_loss=1.878, generator_adv_loss=1.985, generator_feat_match_loss=2.78, over 70.00 samples.], tot_loss[discriminator_loss=2.753, discriminator_real_loss=1.404, discriminator_fake_loss=1.349, generator_loss=28.1, generator_mel_loss=20.48, generator_kl_loss=1.331, generator_dur_loss=1.83, generator_adv_loss=1.908, generator_feat_match_loss=2.557, over 5890.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 05:30:06,386 INFO [train.py:919] (2/6) Start epoch 58
2024-03-12 05:32:02,586 INFO [train.py:527] (2/6) Epoch 58, batch 32, global_batch_idx: 7100, batch size: 42, loss[discriminator_loss=2.806, discriminator_real_loss=1.474, discriminator_fake_loss=1.331, generator_loss=27.69, generator_mel_loss=20.49, generator_kl_loss=1.336, generator_dur_loss=1.748, generator_adv_loss=1.843, generator_feat_match_loss=2.271, over 42.00 samples.], tot_loss[discriminator_loss=2.746, discriminator_real_loss=1.392, discriminator_fake_loss=1.354, generator_loss=28.19, generator_mel_loss=20.52, generator_kl_loss=1.344, generator_dur_loss=1.836, generator_adv_loss=1.902, generator_feat_match_loss=2.591, over 1838.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 05:34:24,750 INFO [train.py:527] (2/6) Epoch 58, batch 82, global_batch_idx: 7150, batch size: 61, loss[discriminator_loss=2.717, discriminator_real_loss=1.494, discriminator_fake_loss=1.222, generator_loss=27.52, generator_mel_loss=20.09, generator_kl_loss=1.226, generator_dur_loss=1.816, generator_adv_loss=1.898, generator_feat_match_loss=2.488, over 61.00 samples.], tot_loss[discriminator_loss=2.762, discriminator_real_loss=1.413, discriminator_fake_loss=1.35, generator_loss=27.98, generator_mel_loss=20.43, generator_kl_loss=1.34, generator_dur_loss=1.827, generator_adv_loss=1.884, generator_feat_match_loss=2.499, over 4447.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 05:36:22,675 INFO [train.py:919] (2/6) Start epoch 59
2024-03-12 05:37:09,840 INFO [train.py:527] (2/6) Epoch 59, batch 8, global_batch_idx: 7200, batch size: 66, loss[discriminator_loss=2.667, discriminator_real_loss=1.391, discriminator_fake_loss=1.276, generator_loss=28.75, generator_mel_loss=20.63, generator_kl_loss=1.262, generator_dur_loss=1.833, generator_adv_loss=2.168, generator_feat_match_loss=2.861, over 66.00 samples.], tot_loss[discriminator_loss=2.708, discriminator_real_loss=1.375, discriminator_fake_loss=1.333, generator_loss=28.25, generator_mel_loss=20.51, generator_kl_loss=1.294, generator_dur_loss=1.815, generator_adv_loss=1.996, generator_feat_match_loss=2.628, over 471.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 05:37:09,843 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 05:37:17,482 INFO [train.py:591] (2/6) Epoch 59, validation: discriminator_loss=2.651, discriminator_real_loss=1.434, discriminator_fake_loss=1.216, generator_loss=28.18, generator_mel_loss=20.64, generator_kl_loss=1.036, generator_dur_loss=1.874, generator_adv_loss=2.041, generator_feat_match_loss=2.591, over 100.00 samples.
2024-03-12 05:37:17,484 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 05:39:37,569 INFO [train.py:527] (2/6) Epoch 59, batch 58, global_batch_idx: 7250, batch size: 72, loss[discriminator_loss=2.73, discriminator_real_loss=1.444, discriminator_fake_loss=1.286, generator_loss=27.66, generator_mel_loss=19.99, generator_kl_loss=1.287, generator_dur_loss=1.866, generator_adv_loss=1.961, generator_feat_match_loss=2.565, over 72.00 samples.], tot_loss[discriminator_loss=2.746, discriminator_real_loss=1.404, discriminator_fake_loss=1.342, generator_loss=28.08, generator_mel_loss=20.45, generator_kl_loss=1.32, generator_dur_loss=1.82, generator_adv_loss=1.926, generator_feat_match_loss=2.572, over 3181.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 05:42:00,698 INFO [train.py:527] (2/6) Epoch 59, batch 108, global_batch_idx: 7300, batch size: 70, loss[discriminator_loss=2.728, discriminator_real_loss=1.404, discriminator_fake_loss=1.324, generator_loss=27.57, generator_mel_loss=20.16, generator_kl_loss=1.254, generator_dur_loss=1.865, generator_adv_loss=1.771, generator_feat_match_loss=2.523, over 70.00 samples.], tot_loss[discriminator_loss=2.746, discriminator_real_loss=1.402, discriminator_fake_loss=1.344, generator_loss=28.02, generator_mel_loss=20.42, generator_kl_loss=1.318, generator_dur_loss=1.822, generator_adv_loss=1.906, generator_feat_match_loss=2.558, over 6048.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 05:42:44,795 INFO [train.py:919] (2/6) Start epoch 60
2024-03-12 05:44:46,001 INFO [train.py:527] (2/6) Epoch 60, batch 34, global_batch_idx: 7350, batch size: 39, loss[discriminator_loss=2.796, discriminator_real_loss=1.43, discriminator_fake_loss=1.366, generator_loss=28.13, generator_mel_loss=20.78, generator_kl_loss=1.429, generator_dur_loss=1.763, generator_adv_loss=1.757, generator_feat_match_loss=2.399, over 39.00 samples.], tot_loss[discriminator_loss=2.755, discriminator_real_loss=1.392, discriminator_fake_loss=1.363, generator_loss=27.88, generator_mel_loss=20.32, generator_kl_loss=1.324, generator_dur_loss=1.853, generator_adv_loss=1.868, generator_feat_match_loss=2.509, over 2091.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 05:47:06,777 INFO [train.py:527] (2/6) Epoch 60, batch 84, global_batch_idx: 7400, batch size: 77, loss[discriminator_loss=2.796, discriminator_real_loss=1.5, discriminator_fake_loss=1.296, generator_loss=27.46, generator_mel_loss=20.25, generator_kl_loss=1.209, generator_dur_loss=1.893, generator_adv_loss=1.766, generator_feat_match_loss=2.347, over 77.00 samples.], tot_loss[discriminator_loss=2.762, discriminator_real_loss=1.402, discriminator_fake_loss=1.36, generator_loss=28, generator_mel_loss=20.38, generator_kl_loss=1.318, generator_dur_loss=1.839, generator_adv_loss=1.899, generator_feat_match_loss=2.561, over 5097.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 05:47:06,779 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 05:47:15,706 INFO [train.py:591] (2/6) Epoch 60, validation: discriminator_loss=2.809, discriminator_real_loss=1.414, discriminator_fake_loss=1.395, generator_loss=25.96, generator_mel_loss=19.55, generator_kl_loss=1.112, generator_dur_loss=1.884, generator_adv_loss=1.7, generator_feat_match_loss=1.717, over 100.00 samples.
2024-03-12 05:47:15,707 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 05:49:05,297 INFO [train.py:919] (2/6) Start epoch 61
2024-03-12 05:50:53,551 INFO [train.py:527] (2/6) Epoch 61, batch 10, global_batch_idx: 7450, batch size: 56, loss[discriminator_loss=2.772, discriminator_real_loss=1.366, discriminator_fake_loss=1.406, generator_loss=28.18, generator_mel_loss=20.22, generator_kl_loss=1.473, generator_dur_loss=1.798, generator_adv_loss=1.813, generator_feat_match_loss=2.874, over 56.00 samples.], tot_loss[discriminator_loss=2.741, discriminator_real_loss=1.398, discriminator_fake_loss=1.342, generator_loss=28.12, generator_mel_loss=20.4, generator_kl_loss=1.374, generator_dur_loss=1.819, generator_adv_loss=1.89, generator_feat_match_loss=2.637, over 567.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 05:53:16,108 INFO [train.py:527] (2/6) Epoch 61, batch 60, global_batch_idx: 7500, batch size: 55, loss[discriminator_loss=2.734, discriminator_real_loss=1.347, discriminator_fake_loss=1.387, generator_loss=28.98, generator_mel_loss=21.46, generator_kl_loss=1.332, generator_dur_loss=1.799, generator_adv_loss=1.772, generator_feat_match_loss=2.613, over 55.00 samples.], tot_loss[discriminator_loss=2.749, discriminator_real_loss=1.399, discriminator_fake_loss=1.351, generator_loss=27.96, generator_mel_loss=20.26, generator_kl_loss=1.338, generator_dur_loss=1.833, generator_adv_loss=1.92, generator_feat_match_loss=2.61, over 3468.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 05:55:36,981 INFO [train.py:527] (2/6) Epoch 61, batch 110, global_batch_idx: 7550, batch size: 36, loss[discriminator_loss=2.672, discriminator_real_loss=1.377, discriminator_fake_loss=1.295, generator_loss=30.06, generator_mel_loss=21.86, generator_kl_loss=1.518, generator_dur_loss=1.884, generator_adv_loss=1.839, generator_feat_match_loss=2.964, over 36.00 samples.], tot_loss[discriminator_loss=2.743, discriminator_real_loss=1.394, discriminator_fake_loss=1.349, generator_loss=28.03, generator_mel_loss=20.33, generator_kl_loss=1.338, generator_dur_loss=1.828, generator_adv_loss=1.907, generator_feat_match_loss=2.623, over 6177.00 samples.], cur_lr_g: 1.99e-04, cur_lr_d: 1.99e-04, 
2024-03-12 05:56:16,843 INFO [train.py:919] (2/6) Start epoch 62
2024-03-12 05:58:26,336 INFO [train.py:527] (2/6) Epoch 62, batch 36, global_batch_idx: 7600, batch size: 12, loss[discriminator_loss=2.859, discriminator_real_loss=1.515, discriminator_fake_loss=1.344, generator_loss=31.19, generator_mel_loss=23.11, generator_kl_loss=1.824, generator_dur_loss=1.7, generator_adv_loss=1.715, generator_feat_match_loss=2.842, over 12.00 samples.], tot_loss[discriminator_loss=2.762, discriminator_real_loss=1.412, discriminator_fake_loss=1.351, generator_loss=28.09, generator_mel_loss=20.41, generator_kl_loss=1.375, generator_dur_loss=1.805, generator_adv_loss=1.904, generator_feat_match_loss=2.592, over 1890.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 05:58:26,338 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 05:58:34,412 INFO [train.py:591] (2/6) Epoch 62, validation: discriminator_loss=2.777, discriminator_real_loss=1.434, discriminator_fake_loss=1.344, generator_loss=26.63, generator_mel_loss=20.06, generator_kl_loss=1.08, generator_dur_loss=1.882, generator_adv_loss=1.807, generator_feat_match_loss=1.799, over 100.00 samples.
2024-03-12 05:58:34,413 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 06:00:56,855 INFO [train.py:527] (2/6) Epoch 62, batch 86, global_batch_idx: 7650, batch size: 68, loss[discriminator_loss=2.778, discriminator_real_loss=1.231, discriminator_fake_loss=1.547, generator_loss=27.51, generator_mel_loss=20.05, generator_kl_loss=1.218, generator_dur_loss=1.876, generator_adv_loss=1.764, generator_feat_match_loss=2.606, over 68.00 samples.], tot_loss[discriminator_loss=2.766, discriminator_real_loss=1.415, discriminator_fake_loss=1.351, generator_loss=28.03, generator_mel_loss=20.36, generator_kl_loss=1.338, generator_dur_loss=1.815, generator_adv_loss=1.92, generator_feat_match_loss=2.593, over 4759.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 06:02:41,154 INFO [train.py:919] (2/6) Start epoch 63
2024-03-12 06:03:38,539 INFO [train.py:527] (2/6) Epoch 63, batch 12, global_batch_idx: 7700, batch size: 88, loss[discriminator_loss=2.837, discriminator_real_loss=1.31, discriminator_fake_loss=1.527, generator_loss=28.04, generator_mel_loss=19.61, generator_kl_loss=1.499, generator_dur_loss=1.9, generator_adv_loss=2.429, generator_feat_match_loss=2.603, over 88.00 samples.], tot_loss[discriminator_loss=2.74, discriminator_real_loss=1.374, discriminator_fake_loss=1.366, generator_loss=27.87, generator_mel_loss=20.08, generator_kl_loss=1.331, generator_dur_loss=1.807, generator_adv_loss=1.931, generator_feat_match_loss=2.716, over 764.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 06:05:54,396 INFO [train.py:527] (2/6) Epoch 63, batch 62, global_batch_idx: 7750, batch size: 62, loss[discriminator_loss=2.769, discriminator_real_loss=1.377, discriminator_fake_loss=1.392, generator_loss=28.12, generator_mel_loss=20.08, generator_kl_loss=1.611, generator_dur_loss=1.782, generator_adv_loss=1.853, generator_feat_match_loss=2.792, over 62.00 samples.], tot_loss[discriminator_loss=2.757, discriminator_real_loss=1.397, discriminator_fake_loss=1.36, generator_loss=27.74, generator_mel_loss=20.09, generator_kl_loss=1.334, generator_dur_loss=1.808, generator_adv_loss=1.888, generator_feat_match_loss=2.618, over 3615.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 06:08:16,576 INFO [train.py:527] (2/6) Epoch 63, batch 112, global_batch_idx: 7800, batch size: 48, loss[discriminator_loss=2.687, discriminator_real_loss=1.464, discriminator_fake_loss=1.223, generator_loss=29.51, generator_mel_loss=21.38, generator_kl_loss=1.634, generator_dur_loss=1.669, generator_adv_loss=1.824, generator_feat_match_loss=3.006, over 48.00 samples.], tot_loss[discriminator_loss=2.76, discriminator_real_loss=1.399, discriminator_fake_loss=1.36, generator_loss=27.83, generator_mel_loss=20.2, generator_kl_loss=1.329, generator_dur_loss=1.814, generator_adv_loss=1.885, generator_feat_match_loss=2.597, over 6589.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 06:08:16,578 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 06:08:25,395 INFO [train.py:591] (2/6) Epoch 63, validation: discriminator_loss=2.713, discriminator_real_loss=1.429, discriminator_fake_loss=1.284, generator_loss=26.21, generator_mel_loss=19.45, generator_kl_loss=1.161, generator_dur_loss=1.878, generator_adv_loss=1.771, generator_feat_match_loss=1.95, over 100.00 samples.
2024-03-12 06:08:25,396 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 06:08:58,089 INFO [train.py:919] (2/6) Start epoch 64
2024-03-12 06:11:06,489 INFO [train.py:527] (2/6) Epoch 64, batch 38, global_batch_idx: 7850, batch size: 72, loss[discriminator_loss=2.785, discriminator_real_loss=1.327, discriminator_fake_loss=1.458, generator_loss=26.82, generator_mel_loss=19.36, generator_kl_loss=1.309, generator_dur_loss=1.86, generator_adv_loss=1.771, generator_feat_match_loss=2.521, over 72.00 samples.], tot_loss[discriminator_loss=2.743, discriminator_real_loss=1.406, discriminator_fake_loss=1.337, generator_loss=27.75, generator_mel_loss=20.09, generator_kl_loss=1.34, generator_dur_loss=1.81, generator_adv_loss=1.888, generator_feat_match_loss=2.622, over 2255.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 06:13:29,490 INFO [train.py:527] (2/6) Epoch 64, batch 88, global_batch_idx: 7900, batch size: 66, loss[discriminator_loss=2.786, discriminator_real_loss=1.397, discriminator_fake_loss=1.389, generator_loss=28.06, generator_mel_loss=20.19, generator_kl_loss=1.338, generator_dur_loss=1.83, generator_adv_loss=2.118, generator_feat_match_loss=2.584, over 66.00 samples.], tot_loss[discriminator_loss=2.733, discriminator_real_loss=1.394, discriminator_fake_loss=1.34, generator_loss=27.9, generator_mel_loss=20.16, generator_kl_loss=1.349, generator_dur_loss=1.805, generator_adv_loss=1.914, generator_feat_match_loss=2.675, over 4950.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 06:15:03,369 INFO [train.py:919] (2/6) Start epoch 65
2024-03-12 06:16:05,142 INFO [train.py:527] (2/6) Epoch 65, batch 14, global_batch_idx: 7950, batch size: 52, loss[discriminator_loss=2.888, discriminator_real_loss=1.692, discriminator_fake_loss=1.196, generator_loss=27.87, generator_mel_loss=20.41, generator_kl_loss=1.34, generator_dur_loss=1.77, generator_adv_loss=1.506, generator_feat_match_loss=2.845, over 52.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.405, discriminator_fake_loss=1.32, generator_loss=27.88, generator_mel_loss=20.21, generator_kl_loss=1.324, generator_dur_loss=1.806, generator_adv_loss=1.902, generator_feat_match_loss=2.639, over 822.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 06:18:22,625 INFO [train.py:527] (2/6) Epoch 65, batch 64, global_batch_idx: 8000, batch size: 52, loss[discriminator_loss=2.6, discriminator_real_loss=1.352, discriminator_fake_loss=1.248, generator_loss=29.9, generator_mel_loss=20.91, generator_kl_loss=1.559, generator_dur_loss=1.712, generator_adv_loss=2.126, generator_feat_match_loss=3.592, over 52.00 samples.], tot_loss[discriminator_loss=2.742, discriminator_real_loss=1.398, discriminator_fake_loss=1.344, generator_loss=28.14, generator_mel_loss=20.33, generator_kl_loss=1.318, generator_dur_loss=1.817, generator_adv_loss=1.936, generator_feat_match_loss=2.736, over 3628.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 06:18:22,627 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 06:18:31,351 INFO [train.py:591] (2/6) Epoch 65, validation: discriminator_loss=2.641, discriminator_real_loss=1.246, discriminator_fake_loss=1.395, generator_loss=28.02, generator_mel_loss=20.6, generator_kl_loss=1.285, generator_dur_loss=1.878, generator_adv_loss=1.843, generator_feat_match_loss=2.41, over 100.00 samples.
2024-03-12 06:18:31,351 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 06:20:51,802 INFO [train.py:527] (2/6) Epoch 65, batch 114, global_batch_idx: 8050, batch size: 44, loss[discriminator_loss=2.744, discriminator_real_loss=1.535, discriminator_fake_loss=1.209, generator_loss=28.47, generator_mel_loss=20.7, generator_kl_loss=1.343, generator_dur_loss=1.758, generator_adv_loss=1.943, generator_feat_match_loss=2.728, over 44.00 samples.], tot_loss[discriminator_loss=2.749, discriminator_real_loss=1.403, discriminator_fake_loss=1.346, generator_loss=27.99, generator_mel_loss=20.19, generator_kl_loss=1.323, generator_dur_loss=1.821, generator_adv_loss=1.942, generator_feat_match_loss=2.719, over 6574.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 06:21:19,025 INFO [train.py:919] (2/6) Start epoch 66
2024-03-12 06:23:34,301 INFO [train.py:527] (2/6) Epoch 66, batch 40, global_batch_idx: 8100, batch size: 77, loss[discriminator_loss=2.736, discriminator_real_loss=1.446, discriminator_fake_loss=1.29, generator_loss=27.49, generator_mel_loss=19.96, generator_kl_loss=1.269, generator_dur_loss=1.886, generator_adv_loss=1.735, generator_feat_match_loss=2.636, over 77.00 samples.], tot_loss[discriminator_loss=2.76, discriminator_real_loss=1.418, discriminator_fake_loss=1.342, generator_loss=27.86, generator_mel_loss=20.16, generator_kl_loss=1.35, generator_dur_loss=1.821, generator_adv_loss=1.886, generator_feat_match_loss=2.645, over 2412.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 06:25:54,612 INFO [train.py:527] (2/6) Epoch 66, batch 90, global_batch_idx: 8150, batch size: 70, loss[discriminator_loss=2.659, discriminator_real_loss=1.209, discriminator_fake_loss=1.45, generator_loss=27.77, generator_mel_loss=19.59, generator_kl_loss=1.286, generator_dur_loss=1.839, generator_adv_loss=2.108, generator_feat_match_loss=2.952, over 70.00 samples.], tot_loss[discriminator_loss=2.754, discriminator_real_loss=1.4, discriminator_fake_loss=1.354, generator_loss=27.85, generator_mel_loss=20.15, generator_kl_loss=1.328, generator_dur_loss=1.82, generator_adv_loss=1.893, generator_feat_match_loss=2.659, over 5356.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 06:27:27,350 INFO [train.py:919] (2/6) Start epoch 67
2024-03-12 06:28:32,185 INFO [train.py:527] (2/6) Epoch 67, batch 16, global_batch_idx: 8200, batch size: 44, loss[discriminator_loss=2.785, discriminator_real_loss=1.432, discriminator_fake_loss=1.353, generator_loss=28.01, generator_mel_loss=20.02, generator_kl_loss=1.434, generator_dur_loss=1.784, generator_adv_loss=2.077, generator_feat_match_loss=2.695, over 44.00 samples.], tot_loss[discriminator_loss=2.753, discriminator_real_loss=1.407, discriminator_fake_loss=1.346, generator_loss=28.04, generator_mel_loss=20.34, generator_kl_loss=1.328, generator_dur_loss=1.804, generator_adv_loss=1.908, generator_feat_match_loss=2.66, over 950.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 06:28:32,186 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 06:28:40,207 INFO [train.py:591] (2/6) Epoch 67, validation: discriminator_loss=2.852, discriminator_real_loss=1.627, discriminator_fake_loss=1.225, generator_loss=27.61, generator_mel_loss=20.41, generator_kl_loss=1.213, generator_dur_loss=1.846, generator_adv_loss=2.016, generator_feat_match_loss=2.123, over 100.00 samples.
2024-03-12 06:28:40,208 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 06:30:59,886 INFO [train.py:527] (2/6) Epoch 67, batch 66, global_batch_idx: 8250, batch size: 74, loss[discriminator_loss=2.749, discriminator_real_loss=1.57, discriminator_fake_loss=1.179, generator_loss=28.14, generator_mel_loss=20.58, generator_kl_loss=1.298, generator_dur_loss=1.882, generator_adv_loss=1.751, generator_feat_match_loss=2.628, over 74.00 samples.], tot_loss[discriminator_loss=2.756, discriminator_real_loss=1.413, discriminator_fake_loss=1.343, generator_loss=27.94, generator_mel_loss=20.25, generator_kl_loss=1.359, generator_dur_loss=1.801, generator_adv_loss=1.899, generator_feat_match_loss=2.631, over 3669.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 06:33:19,353 INFO [train.py:527] (2/6) Epoch 67, batch 116, global_batch_idx: 8300, batch size: 64, loss[discriminator_loss=2.808, discriminator_real_loss=1.315, discriminator_fake_loss=1.493, generator_loss=28.19, generator_mel_loss=19.97, generator_kl_loss=1.334, generator_dur_loss=1.784, generator_adv_loss=2.182, generator_feat_match_loss=2.922, over 64.00 samples.], tot_loss[discriminator_loss=2.763, discriminator_real_loss=1.406, discriminator_fake_loss=1.357, generator_loss=27.73, generator_mel_loss=20.09, generator_kl_loss=1.343, generator_dur_loss=1.804, generator_adv_loss=1.899, generator_feat_match_loss=2.596, over 6612.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 06:33:38,700 INFO [train.py:919] (2/6) Start epoch 68
2024-03-12 06:35:59,109 INFO [train.py:527] (2/6) Epoch 68, batch 42, global_batch_idx: 8350, batch size: 58, loss[discriminator_loss=2.708, discriminator_real_loss=1.286, discriminator_fake_loss=1.422, generator_loss=27.59, generator_mel_loss=19.97, generator_kl_loss=1.396, generator_dur_loss=1.786, generator_adv_loss=1.997, generator_feat_match_loss=2.44, over 58.00 samples.], tot_loss[discriminator_loss=2.753, discriminator_real_loss=1.4, discriminator_fake_loss=1.353, generator_loss=27.54, generator_mel_loss=19.82, generator_kl_loss=1.323, generator_dur_loss=1.808, generator_adv_loss=1.953, generator_feat_match_loss=2.641, over 2492.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 06:38:17,958 INFO [train.py:527] (2/6) Epoch 68, batch 92, global_batch_idx: 8400, batch size: 14, loss[discriminator_loss=2.733, discriminator_real_loss=1.296, discriminator_fake_loss=1.437, generator_loss=28.99, generator_mel_loss=20.6, generator_kl_loss=1.633, generator_dur_loss=1.719, generator_adv_loss=2.303, generator_feat_match_loss=2.743, over 14.00 samples.], tot_loss[discriminator_loss=2.748, discriminator_real_loss=1.403, discriminator_fake_loss=1.345, generator_loss=27.62, generator_mel_loss=19.94, generator_kl_loss=1.323, generator_dur_loss=1.812, generator_adv_loss=1.917, generator_feat_match_loss=2.623, over 5216.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 06:38:17,959 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 06:38:26,712 INFO [train.py:591] (2/6) Epoch 68, validation: discriminator_loss=2.963, discriminator_real_loss=1.622, discriminator_fake_loss=1.34, generator_loss=27.87, generator_mel_loss=20.22, generator_kl_loss=1.24, generator_dur_loss=1.867, generator_adv_loss=2.181, generator_feat_match_loss=2.365, over 100.00 samples.
2024-03-12 06:38:26,713 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 06:39:51,865 INFO [train.py:919] (2/6) Start epoch 69
2024-03-12 06:41:07,239 INFO [train.py:527] (2/6) Epoch 69, batch 18, global_batch_idx: 8450, batch size: 62, loss[discriminator_loss=2.712, discriminator_real_loss=1.417, discriminator_fake_loss=1.295, generator_loss=27.91, generator_mel_loss=19.86, generator_kl_loss=1.437, generator_dur_loss=1.809, generator_adv_loss=1.909, generator_feat_match_loss=2.9, over 62.00 samples.], tot_loss[discriminator_loss=2.76, discriminator_real_loss=1.392, discriminator_fake_loss=1.369, generator_loss=27.77, generator_mel_loss=20.04, generator_kl_loss=1.316, generator_dur_loss=1.824, generator_adv_loss=1.916, generator_feat_match_loss=2.679, over 1217.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 06:43:24,092 INFO [train.py:527] (2/6) Epoch 69, batch 68, global_batch_idx: 8500, batch size: 97, loss[discriminator_loss=2.77, discriminator_real_loss=1.442, discriminator_fake_loss=1.327, generator_loss=26.6, generator_mel_loss=19.06, generator_kl_loss=1.28, generator_dur_loss=1.893, generator_adv_loss=1.951, generator_feat_match_loss=2.414, over 97.00 samples.], tot_loss[discriminator_loss=2.748, discriminator_real_loss=1.397, discriminator_fake_loss=1.352, generator_loss=27.67, generator_mel_loss=20.01, generator_kl_loss=1.344, generator_dur_loss=1.804, generator_adv_loss=1.906, generator_feat_match_loss=2.607, over 4117.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 06:45:42,059 INFO [train.py:527] (2/6) Epoch 69, batch 118, global_batch_idx: 8550, batch size: 66, loss[discriminator_loss=2.742, discriminator_real_loss=1.405, discriminator_fake_loss=1.337, generator_loss=27.96, generator_mel_loss=20.1, generator_kl_loss=1.259, generator_dur_loss=1.801, generator_adv_loss=1.981, generator_feat_match_loss=2.811, over 66.00 samples.], tot_loss[discriminator_loss=2.753, discriminator_real_loss=1.402, discriminator_fake_loss=1.351, generator_loss=27.64, generator_mel_loss=19.99, generator_kl_loss=1.344, generator_dur_loss=1.798, generator_adv_loss=1.891, generator_feat_match_loss=2.617, over 6881.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 06:45:59,589 INFO [train.py:919] (2/6) Start epoch 70
2024-03-12 06:48:24,326 INFO [train.py:527] (2/6) Epoch 70, batch 44, global_batch_idx: 8600, batch size: 62, loss[discriminator_loss=2.837, discriminator_real_loss=1.515, discriminator_fake_loss=1.322, generator_loss=27.74, generator_mel_loss=20.23, generator_kl_loss=1.396, generator_dur_loss=1.805, generator_adv_loss=1.796, generator_feat_match_loss=2.507, over 62.00 samples.], tot_loss[discriminator_loss=2.784, discriminator_real_loss=1.429, discriminator_fake_loss=1.354, generator_loss=28.1, generator_mel_loss=20.08, generator_kl_loss=1.342, generator_dur_loss=1.804, generator_adv_loss=2.019, generator_feat_match_loss=2.853, over 2595.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 06:48:24,327 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 06:48:32,172 INFO [train.py:591] (2/6) Epoch 70, validation: discriminator_loss=2.833, discriminator_real_loss=1.384, discriminator_fake_loss=1.449, generator_loss=27.25, generator_mel_loss=20.62, generator_kl_loss=1.145, generator_dur_loss=1.861, generator_adv_loss=1.695, generator_feat_match_loss=1.926, over 100.00 samples.
2024-03-12 06:48:32,173 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 06:50:51,357 INFO [train.py:527] (2/6) Epoch 70, batch 94, global_batch_idx: 8650, batch size: 80, loss[discriminator_loss=2.749, discriminator_real_loss=1.405, discriminator_fake_loss=1.344, generator_loss=28.09, generator_mel_loss=20.35, generator_kl_loss=1.199, generator_dur_loss=1.836, generator_adv_loss=1.848, generator_feat_match_loss=2.862, over 80.00 samples.], tot_loss[discriminator_loss=2.759, discriminator_real_loss=1.41, discriminator_fake_loss=1.349, generator_loss=27.87, generator_mel_loss=20.05, generator_kl_loss=1.327, generator_dur_loss=1.807, generator_adv_loss=1.953, generator_feat_match_loss=2.742, over 5436.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 06:52:11,743 INFO [train.py:919] (2/6) Start epoch 71
2024-03-12 06:53:31,236 INFO [train.py:527] (2/6) Epoch 71, batch 20, global_batch_idx: 8700, batch size: 68, loss[discriminator_loss=2.759, discriminator_real_loss=1.498, discriminator_fake_loss=1.261, generator_loss=26.6, generator_mel_loss=19.51, generator_kl_loss=1.261, generator_dur_loss=1.825, generator_adv_loss=1.732, generator_feat_match_loss=2.272, over 68.00 samples.], tot_loss[discriminator_loss=2.737, discriminator_real_loss=1.408, discriminator_fake_loss=1.329, generator_loss=27.78, generator_mel_loss=20.02, generator_kl_loss=1.353, generator_dur_loss=1.791, generator_adv_loss=1.915, generator_feat_match_loss=2.702, over 1170.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 06:55:49,076 INFO [train.py:527] (2/6) Epoch 71, batch 70, global_batch_idx: 8750, batch size: 62, loss[discriminator_loss=2.806, discriminator_real_loss=1.407, discriminator_fake_loss=1.399, generator_loss=28.53, generator_mel_loss=20.75, generator_kl_loss=1.4, generator_dur_loss=1.795, generator_adv_loss=1.833, generator_feat_match_loss=2.756, over 62.00 samples.], tot_loss[discriminator_loss=2.749, discriminator_real_loss=1.406, discriminator_fake_loss=1.344, generator_loss=27.7, generator_mel_loss=19.97, generator_kl_loss=1.352, generator_dur_loss=1.799, generator_adv_loss=1.905, generator_feat_match_loss=2.671, over 4189.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 06:58:06,956 INFO [train.py:527] (2/6) Epoch 71, batch 120, global_batch_idx: 8800, batch size: 96, loss[discriminator_loss=2.771, discriminator_real_loss=1.574, discriminator_fake_loss=1.197, generator_loss=27.36, generator_mel_loss=19.16, generator_kl_loss=1.313, generator_dur_loss=1.864, generator_adv_loss=2.043, generator_feat_match_loss=2.976, over 96.00 samples.], tot_loss[discriminator_loss=2.756, discriminator_real_loss=1.407, discriminator_fake_loss=1.349, generator_loss=27.75, generator_mel_loss=20, generator_kl_loss=1.348, generator_dur_loss=1.795, generator_adv_loss=1.917, generator_feat_match_loss=2.699, over 6912.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 06:58:06,958 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 06:58:15,683 INFO [train.py:591] (2/6) Epoch 71, validation: discriminator_loss=2.67, discriminator_real_loss=1.398, discriminator_fake_loss=1.273, generator_loss=28.15, generator_mel_loss=20.67, generator_kl_loss=1.155, generator_dur_loss=1.83, generator_adv_loss=1.908, generator_feat_match_loss=2.588, over 100.00 samples.
2024-03-12 06:58:15,684 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 06:58:25,625 INFO [train.py:919] (2/6) Start epoch 72
2024-03-12 07:00:55,661 INFO [train.py:527] (2/6) Epoch 72, batch 46, global_batch_idx: 8850, batch size: 39, loss[discriminator_loss=2.7, discriminator_real_loss=1.286, discriminator_fake_loss=1.413, generator_loss=28.76, generator_mel_loss=20.59, generator_kl_loss=1.5, generator_dur_loss=1.751, generator_adv_loss=2.037, generator_feat_match_loss=2.882, over 39.00 samples.], tot_loss[discriminator_loss=2.763, discriminator_real_loss=1.407, discriminator_fake_loss=1.356, generator_loss=27.62, generator_mel_loss=19.9, generator_kl_loss=1.365, generator_dur_loss=1.775, generator_adv_loss=1.937, generator_feat_match_loss=2.647, over 2565.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 07:03:14,365 INFO [train.py:527] (2/6) Epoch 72, batch 96, global_batch_idx: 8900, batch size: 62, loss[discriminator_loss=2.744, discriminator_real_loss=1.488, discriminator_fake_loss=1.256, generator_loss=27.44, generator_mel_loss=20.16, generator_kl_loss=1.37, generator_dur_loss=1.78, generator_adv_loss=1.89, generator_feat_match_loss=2.246, over 62.00 samples.], tot_loss[discriminator_loss=2.749, discriminator_real_loss=1.399, discriminator_fake_loss=1.351, generator_loss=27.69, generator_mel_loss=19.96, generator_kl_loss=1.359, generator_dur_loss=1.782, generator_adv_loss=1.919, generator_feat_match_loss=2.67, over 5434.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 07:04:31,347 INFO [train.py:919] (2/6) Start epoch 73
2024-03-12 07:05:57,037 INFO [train.py:527] (2/6) Epoch 73, batch 22, global_batch_idx: 8950, batch size: 68, loss[discriminator_loss=2.958, discriminator_real_loss=1.536, discriminator_fake_loss=1.423, generator_loss=26.81, generator_mel_loss=19.51, generator_kl_loss=1.272, generator_dur_loss=1.865, generator_adv_loss=1.775, generator_feat_match_loss=2.387, over 68.00 samples.], tot_loss[discriminator_loss=2.77, discriminator_real_loss=1.421, discriminator_fake_loss=1.349, generator_loss=28.12, generator_mel_loss=19.96, generator_kl_loss=1.367, generator_dur_loss=1.792, generator_adv_loss=2.053, generator_feat_match_loss=2.947, over 1300.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 07:08:14,587 INFO [train.py:527] (2/6) Epoch 73, batch 72, global_batch_idx: 9000, batch size: 64, loss[discriminator_loss=2.771, discriminator_real_loss=1.354, discriminator_fake_loss=1.417, generator_loss=26.88, generator_mel_loss=20.01, generator_kl_loss=1.241, generator_dur_loss=1.787, generator_adv_loss=1.785, generator_feat_match_loss=2.056, over 64.00 samples.], tot_loss[discriminator_loss=2.772, discriminator_real_loss=1.426, discriminator_fake_loss=1.346, generator_loss=27.86, generator_mel_loss=19.96, generator_kl_loss=1.345, generator_dur_loss=1.801, generator_adv_loss=2.007, generator_feat_match_loss=2.756, over 4137.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 07:08:14,588 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 07:08:23,140 INFO [train.py:591] (2/6) Epoch 73, validation: discriminator_loss=2.808, discriminator_real_loss=1.416, discriminator_fake_loss=1.392, generator_loss=27.31, generator_mel_loss=20.49, generator_kl_loss=1.148, generator_dur_loss=1.855, generator_adv_loss=1.733, generator_feat_match_loss=2.082, over 100.00 samples.
2024-03-12 07:08:23,141 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 07:10:40,058 INFO [train.py:527] (2/6) Epoch 73, batch 122, global_batch_idx: 9050, batch size: 58, loss[discriminator_loss=2.769, discriminator_real_loss=1.51, discriminator_fake_loss=1.258, generator_loss=27.06, generator_mel_loss=19.6, generator_kl_loss=1.304, generator_dur_loss=1.804, generator_adv_loss=1.857, generator_feat_match_loss=2.5, over 58.00 samples.], tot_loss[discriminator_loss=2.754, discriminator_real_loss=1.414, discriminator_fake_loss=1.34, generator_loss=27.73, generator_mel_loss=19.92, generator_kl_loss=1.345, generator_dur_loss=1.797, generator_adv_loss=1.96, generator_feat_match_loss=2.712, over 6955.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 07:10:46,022 INFO [train.py:919] (2/6) Start epoch 74
2024-03-12 07:13:21,555 INFO [train.py:527] (2/6) Epoch 74, batch 48, global_batch_idx: 9100, batch size: 44, loss[discriminator_loss=2.66, discriminator_real_loss=1.474, discriminator_fake_loss=1.186, generator_loss=28.65, generator_mel_loss=20.04, generator_kl_loss=1.45, generator_dur_loss=1.748, generator_adv_loss=2.138, generator_feat_match_loss=3.274, over 44.00 samples.], tot_loss[discriminator_loss=2.767, discriminator_real_loss=1.397, discriminator_fake_loss=1.37, generator_loss=27.43, generator_mel_loss=19.77, generator_kl_loss=1.35, generator_dur_loss=1.793, generator_adv_loss=1.884, generator_feat_match_loss=2.639, over 2726.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 07:15:39,605 INFO [train.py:527] (2/6) Epoch 74, batch 98, global_batch_idx: 9150, batch size: 88, loss[discriminator_loss=2.794, discriminator_real_loss=1.334, discriminator_fake_loss=1.459, generator_loss=26.71, generator_mel_loss=19.49, generator_kl_loss=1.258, generator_dur_loss=1.894, generator_adv_loss=2.042, generator_feat_match_loss=2.028, over 88.00 samples.], tot_loss[discriminator_loss=2.763, discriminator_real_loss=1.399, discriminator_fake_loss=1.364, generator_loss=27.59, generator_mel_loss=19.9, generator_kl_loss=1.346, generator_dur_loss=1.805, generator_adv_loss=1.893, generator_feat_match_loss=2.64, over 5666.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 07:16:51,173 INFO [train.py:919] (2/6) Start epoch 75
2024-03-12 07:18:20,452 INFO [train.py:527] (2/6) Epoch 75, batch 24, global_batch_idx: 9200, batch size: 42, loss[discriminator_loss=2.706, discriminator_real_loss=1.327, discriminator_fake_loss=1.379, generator_loss=27.22, generator_mel_loss=19.22, generator_kl_loss=1.591, generator_dur_loss=1.696, generator_adv_loss=1.91, generator_feat_match_loss=2.804, over 42.00 samples.], tot_loss[discriminator_loss=2.768, discriminator_real_loss=1.416, discriminator_fake_loss=1.352, generator_loss=27.5, generator_mel_loss=19.84, generator_kl_loss=1.395, generator_dur_loss=1.762, generator_adv_loss=1.852, generator_feat_match_loss=2.65, over 1290.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 07:18:20,453 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 07:18:28,222 INFO [train.py:591] (2/6) Epoch 75, validation: discriminator_loss=2.814, discriminator_real_loss=1.479, discriminator_fake_loss=1.335, generator_loss=27.15, generator_mel_loss=20.35, generator_kl_loss=1.058, generator_dur_loss=1.861, generator_adv_loss=1.815, generator_feat_match_loss=2.065, over 100.00 samples.
2024-03-12 07:18:28,222 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 07:20:44,766 INFO [train.py:527] (2/6) Epoch 75, batch 74, global_batch_idx: 9250, batch size: 25, loss[discriminator_loss=2.71, discriminator_real_loss=1.374, discriminator_fake_loss=1.336, generator_loss=29.39, generator_mel_loss=20.87, generator_kl_loss=1.819, generator_dur_loss=1.611, generator_adv_loss=2.012, generator_feat_match_loss=3.086, over 25.00 samples.], tot_loss[discriminator_loss=2.77, discriminator_real_loss=1.412, discriminator_fake_loss=1.358, generator_loss=27.46, generator_mel_loss=19.76, generator_kl_loss=1.386, generator_dur_loss=1.801, generator_adv_loss=1.874, generator_feat_match_loss=2.638, over 4143.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 07:23:01,937 INFO [train.py:919] (2/6) Start epoch 76
2024-03-12 07:23:25,939 INFO [train.py:527] (2/6) Epoch 76, batch 0, global_batch_idx: 9300, batch size: 62, loss[discriminator_loss=2.66, discriminator_real_loss=1.256, discriminator_fake_loss=1.404, generator_loss=28.23, generator_mel_loss=20.54, generator_kl_loss=1.28, generator_dur_loss=1.794, generator_adv_loss=1.783, generator_feat_match_loss=2.837, over 62.00 samples.], tot_loss[discriminator_loss=2.66, discriminator_real_loss=1.256, discriminator_fake_loss=1.404, generator_loss=28.23, generator_mel_loss=20.54, generator_kl_loss=1.28, generator_dur_loss=1.794, generator_adv_loss=1.783, generator_feat_match_loss=2.837, over 62.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 07:25:43,616 INFO [train.py:527] (2/6) Epoch 76, batch 50, global_batch_idx: 9350, batch size: 74, loss[discriminator_loss=2.751, discriminator_real_loss=1.363, discriminator_fake_loss=1.388, generator_loss=28.21, generator_mel_loss=20.18, generator_kl_loss=1.397, generator_dur_loss=1.807, generator_adv_loss=2.048, generator_feat_match_loss=2.774, over 74.00 samples.], tot_loss[discriminator_loss=2.729, discriminator_real_loss=1.387, discriminator_fake_loss=1.342, generator_loss=27.47, generator_mel_loss=19.77, generator_kl_loss=1.314, generator_dur_loss=1.796, generator_adv_loss=1.929, generator_feat_match_loss=2.66, over 2987.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 07:28:05,338 INFO [train.py:527] (2/6) Epoch 76, batch 100, global_batch_idx: 9400, batch size: 56, loss[discriminator_loss=2.698, discriminator_real_loss=1.449, discriminator_fake_loss=1.249, generator_loss=28.28, generator_mel_loss=20.11, generator_kl_loss=1.353, generator_dur_loss=1.801, generator_adv_loss=2.133, generator_feat_match_loss=2.879, over 56.00 samples.], tot_loss[discriminator_loss=2.732, discriminator_real_loss=1.392, discriminator_fake_loss=1.34, generator_loss=27.5, generator_mel_loss=19.78, generator_kl_loss=1.329, generator_dur_loss=1.802, generator_adv_loss=1.915, generator_feat_match_loss=2.674, over 5983.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 07:28:05,339 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 07:28:14,095 INFO [train.py:591] (2/6) Epoch 76, validation: discriminator_loss=2.765, discriminator_real_loss=1.503, discriminator_fake_loss=1.262, generator_loss=26.53, generator_mel_loss=19.46, generator_kl_loss=1.181, generator_dur_loss=1.839, generator_adv_loss=1.956, generator_feat_match_loss=2.087, over 100.00 samples.
2024-03-12 07:28:14,096 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 07:29:15,312 INFO [train.py:919] (2/6) Start epoch 77
2024-03-12 07:30:53,673 INFO [train.py:527] (2/6) Epoch 77, batch 26, global_batch_idx: 9450, batch size: 13, loss[discriminator_loss=2.686, discriminator_real_loss=1.182, discriminator_fake_loss=1.504, generator_loss=29.66, generator_mel_loss=21.04, generator_kl_loss=1.643, generator_dur_loss=1.564, generator_adv_loss=1.87, generator_feat_match_loss=3.538, over 13.00 samples.], tot_loss[discriminator_loss=2.742, discriminator_real_loss=1.402, discriminator_fake_loss=1.341, generator_loss=27.56, generator_mel_loss=19.8, generator_kl_loss=1.38, generator_dur_loss=1.774, generator_adv_loss=1.899, generator_feat_match_loss=2.706, over 1348.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 07:33:12,746 INFO [train.py:527] (2/6) Epoch 77, batch 76, global_batch_idx: 9500, batch size: 66, loss[discriminator_loss=2.814, discriminator_real_loss=1.53, discriminator_fake_loss=1.284, generator_loss=25.97, generator_mel_loss=18.9, generator_kl_loss=1.283, generator_dur_loss=1.81, generator_adv_loss=1.714, generator_feat_match_loss=2.262, over 66.00 samples.], tot_loss[discriminator_loss=2.762, discriminator_real_loss=1.413, discriminator_fake_loss=1.349, generator_loss=27.53, generator_mel_loss=19.73, generator_kl_loss=1.343, generator_dur_loss=1.814, generator_adv_loss=1.939, generator_feat_match_loss=2.702, over 4629.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 07:35:22,397 INFO [train.py:919] (2/6) Start epoch 78
2024-03-12 07:35:52,846 INFO [train.py:527] (2/6) Epoch 78, batch 2, global_batch_idx: 9550, batch size: 48, loss[discriminator_loss=2.691, discriminator_real_loss=1.326, discriminator_fake_loss=1.365, generator_loss=27.28, generator_mel_loss=19.29, generator_kl_loss=1.507, generator_dur_loss=1.735, generator_adv_loss=1.887, generator_feat_match_loss=2.866, over 48.00 samples.], tot_loss[discriminator_loss=2.711, discriminator_real_loss=1.326, discriminator_fake_loss=1.385, generator_loss=27.41, generator_mel_loss=19.44, generator_kl_loss=1.426, generator_dur_loss=1.859, generator_adv_loss=1.832, generator_feat_match_loss=2.856, over 218.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 07:38:10,292 INFO [train.py:527] (2/6) Epoch 78, batch 52, global_batch_idx: 9600, batch size: 88, loss[discriminator_loss=2.764, discriminator_real_loss=1.389, discriminator_fake_loss=1.374, generator_loss=26.33, generator_mel_loss=18.82, generator_kl_loss=1.151, generator_dur_loss=1.891, generator_adv_loss=1.9, generator_feat_match_loss=2.572, over 88.00 samples.], tot_loss[discriminator_loss=2.748, discriminator_real_loss=1.389, discriminator_fake_loss=1.358, generator_loss=27.4, generator_mel_loss=19.64, generator_kl_loss=1.346, generator_dur_loss=1.819, generator_adv_loss=1.873, generator_feat_match_loss=2.72, over 3154.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 07:38:10,293 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 07:38:18,167 INFO [train.py:591] (2/6) Epoch 78, validation: discriminator_loss=2.832, discriminator_real_loss=1.553, discriminator_fake_loss=1.28, generator_loss=27.19, generator_mel_loss=19.96, generator_kl_loss=1.056, generator_dur_loss=1.858, generator_adv_loss=1.962, generator_feat_match_loss=2.352, over 100.00 samples.
2024-03-12 07:38:18,168 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 07:40:37,222 INFO [train.py:527] (2/6) Epoch 78, batch 102, global_batch_idx: 9650, batch size: 53, loss[discriminator_loss=2.723, discriminator_real_loss=1.413, discriminator_fake_loss=1.31, generator_loss=26.86, generator_mel_loss=19.34, generator_kl_loss=1.357, generator_dur_loss=1.738, generator_adv_loss=1.643, generator_feat_match_loss=2.777, over 53.00 samples.], tot_loss[discriminator_loss=2.744, discriminator_real_loss=1.389, discriminator_fake_loss=1.354, generator_loss=27.55, generator_mel_loss=19.75, generator_kl_loss=1.369, generator_dur_loss=1.804, generator_adv_loss=1.878, generator_feat_match_loss=2.748, over 5775.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 07:41:37,055 INFO [train.py:919] (2/6) Start epoch 79
2024-03-12 07:43:17,099 INFO [train.py:527] (2/6) Epoch 79, batch 28, global_batch_idx: 9700, batch size: 72, loss[discriminator_loss=2.726, discriminator_real_loss=1.44, discriminator_fake_loss=1.286, generator_loss=27.7, generator_mel_loss=19.86, generator_kl_loss=1.316, generator_dur_loss=1.844, generator_adv_loss=1.877, generator_feat_match_loss=2.805, over 72.00 samples.], tot_loss[discriminator_loss=2.764, discriminator_real_loss=1.422, discriminator_fake_loss=1.342, generator_loss=27.62, generator_mel_loss=19.79, generator_kl_loss=1.361, generator_dur_loss=1.79, generator_adv_loss=1.897, generator_feat_match_loss=2.787, over 1708.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 07:45:39,644 INFO [train.py:527] (2/6) Epoch 79, batch 78, global_batch_idx: 9750, batch size: 25, loss[discriminator_loss=2.732, discriminator_real_loss=1.336, discriminator_fake_loss=1.396, generator_loss=29.28, generator_mel_loss=21.25, generator_kl_loss=1.646, generator_dur_loss=1.614, generator_adv_loss=1.789, generator_feat_match_loss=2.985, over 25.00 samples.], tot_loss[discriminator_loss=2.77, discriminator_real_loss=1.418, discriminator_fake_loss=1.352, generator_loss=27.43, generator_mel_loss=19.67, generator_kl_loss=1.36, generator_dur_loss=1.802, generator_adv_loss=1.892, generator_feat_match_loss=2.708, over 4621.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 07:47:45,370 INFO [train.py:919] (2/6) Start epoch 80
2024-03-12 07:48:20,441 INFO [train.py:527] (2/6) Epoch 80, batch 4, global_batch_idx: 9800, batch size: 74, loss[discriminator_loss=2.778, discriminator_real_loss=1.457, discriminator_fake_loss=1.32, generator_loss=27.02, generator_mel_loss=19.66, generator_kl_loss=1.27, generator_dur_loss=1.855, generator_adv_loss=1.815, generator_feat_match_loss=2.422, over 74.00 samples.], tot_loss[discriminator_loss=2.779, discriminator_real_loss=1.422, discriminator_fake_loss=1.357, generator_loss=26.98, generator_mel_loss=19.32, generator_kl_loss=1.319, generator_dur_loss=1.854, generator_adv_loss=1.852, generator_feat_match_loss=2.635, over 339.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 07:48:20,445 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 07:48:28,384 INFO [train.py:591] (2/6) Epoch 80, validation: discriminator_loss=2.778, discriminator_real_loss=1.448, discriminator_fake_loss=1.329, generator_loss=27.23, generator_mel_loss=20.25, generator_kl_loss=1.085, generator_dur_loss=1.86, generator_adv_loss=1.811, generator_feat_match_loss=2.225, over 100.00 samples.
2024-03-12 07:48:28,387 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 07:50:45,554 INFO [train.py:527] (2/6) Epoch 80, batch 54, global_batch_idx: 9850, batch size: 15, loss[discriminator_loss=2.855, discriminator_real_loss=1.542, discriminator_fake_loss=1.313, generator_loss=27.73, generator_mel_loss=20.19, generator_kl_loss=1.723, generator_dur_loss=1.666, generator_adv_loss=1.742, generator_feat_match_loss=2.411, over 15.00 samples.], tot_loss[discriminator_loss=2.747, discriminator_real_loss=1.399, discriminator_fake_loss=1.348, generator_loss=27.62, generator_mel_loss=19.81, generator_kl_loss=1.374, generator_dur_loss=1.777, generator_adv_loss=1.885, generator_feat_match_loss=2.775, over 2952.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 07:53:04,987 INFO [train.py:527] (2/6) Epoch 80, batch 104, global_batch_idx: 9900, batch size: 83, loss[discriminator_loss=2.777, discriminator_real_loss=1.485, discriminator_fake_loss=1.292, generator_loss=27.46, generator_mel_loss=19.38, generator_kl_loss=1.366, generator_dur_loss=1.856, generator_adv_loss=1.693, generator_feat_match_loss=3.169, over 83.00 samples.], tot_loss[discriminator_loss=2.745, discriminator_real_loss=1.397, discriminator_fake_loss=1.349, generator_loss=27.58, generator_mel_loss=19.75, generator_kl_loss=1.377, generator_dur_loss=1.788, generator_adv_loss=1.882, generator_feat_match_loss=2.777, over 5973.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 07:53:59,002 INFO [train.py:919] (2/6) Start epoch 81
2024-03-12 07:56:20,632 INFO [train.py:527] (2/6) Epoch 81, batch 30, global_batch_idx: 9950, batch size: 53, loss[discriminator_loss=2.873, discriminator_real_loss=1.638, discriminator_fake_loss=1.235, generator_loss=27.42, generator_mel_loss=19.56, generator_kl_loss=1.382, generator_dur_loss=1.764, generator_adv_loss=2.037, generator_feat_match_loss=2.674, over 53.00 samples.], tot_loss[discriminator_loss=2.759, discriminator_real_loss=1.406, discriminator_fake_loss=1.352, generator_loss=27.62, generator_mel_loss=19.69, generator_kl_loss=1.353, generator_dur_loss=1.804, generator_adv_loss=1.938, generator_feat_match_loss=2.834, over 1796.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 07:58:38,431 INFO [train.py:527] (2/6) Epoch 81, batch 80, global_batch_idx: 10000, batch size: 96, loss[discriminator_loss=2.72, discriminator_real_loss=1.313, discriminator_fake_loss=1.407, generator_loss=27.77, generator_mel_loss=19.53, generator_kl_loss=1.435, generator_dur_loss=1.88, generator_adv_loss=1.898, generator_feat_match_loss=3.025, over 96.00 samples.], tot_loss[discriminator_loss=2.749, discriminator_real_loss=1.395, discriminator_fake_loss=1.353, generator_loss=27.61, generator_mel_loss=19.72, generator_kl_loss=1.353, generator_dur_loss=1.806, generator_adv_loss=1.919, generator_feat_match_loss=2.809, over 4817.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 07:58:38,432 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 07:58:46,879 INFO [train.py:591] (2/6) Epoch 81, validation: discriminator_loss=2.771, discriminator_real_loss=1.479, discriminator_fake_loss=1.292, generator_loss=27.36, generator_mel_loss=20.11, generator_kl_loss=1.106, generator_dur_loss=1.827, generator_adv_loss=1.929, generator_feat_match_loss=2.384, over 100.00 samples.
2024-03-12 07:58:46,880 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 08:00:49,053 INFO [train.py:919] (2/6) Start epoch 82
2024-03-12 08:01:27,365 INFO [train.py:527] (2/6) Epoch 82, batch 6, global_batch_idx: 10050, batch size: 12, loss[discriminator_loss=2.703, discriminator_real_loss=1.316, discriminator_fake_loss=1.388, generator_loss=29.04, generator_mel_loss=20.63, generator_kl_loss=1.604, generator_dur_loss=1.699, generator_adv_loss=1.933, generator_feat_match_loss=3.169, over 12.00 samples.], tot_loss[discriminator_loss=2.663, discriminator_real_loss=1.35, discriminator_fake_loss=1.313, generator_loss=28.14, generator_mel_loss=19.95, generator_kl_loss=1.394, generator_dur_loss=1.751, generator_adv_loss=1.966, generator_feat_match_loss=3.075, over 318.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 08:03:45,418 INFO [train.py:527] (2/6) Epoch 82, batch 56, global_batch_idx: 10100, batch size: 56, loss[discriminator_loss=2.731, discriminator_real_loss=1.349, discriminator_fake_loss=1.383, generator_loss=27.34, generator_mel_loss=19.7, generator_kl_loss=1.43, generator_dur_loss=1.804, generator_adv_loss=1.914, generator_feat_match_loss=2.491, over 56.00 samples.], tot_loss[discriminator_loss=2.696, discriminator_real_loss=1.365, discriminator_fake_loss=1.331, generator_loss=27.58, generator_mel_loss=19.55, generator_kl_loss=1.375, generator_dur_loss=1.787, generator_adv_loss=1.956, generator_feat_match_loss=2.917, over 3322.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 08:06:04,689 INFO [train.py:527] (2/6) Epoch 82, batch 106, global_batch_idx: 10150, batch size: 59, loss[discriminator_loss=2.76, discriminator_real_loss=1.476, discriminator_fake_loss=1.285, generator_loss=28.92, generator_mel_loss=20.71, generator_kl_loss=1.436, generator_dur_loss=1.78, generator_adv_loss=1.979, generator_feat_match_loss=3.018, over 59.00 samples.], tot_loss[discriminator_loss=2.721, discriminator_real_loss=1.384, discriminator_fake_loss=1.338, generator_loss=27.56, generator_mel_loss=19.62, generator_kl_loss=1.356, generator_dur_loss=1.791, generator_adv_loss=1.941, generator_feat_match_loss=2.853, over 6285.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 08:06:53,070 INFO [train.py:919] (2/6) Start epoch 83
2024-03-12 08:08:44,674 INFO [train.py:527] (2/6) Epoch 83, batch 32, global_batch_idx: 10200, batch size: 96, loss[discriminator_loss=2.76, discriminator_real_loss=1.377, discriminator_fake_loss=1.384, generator_loss=27.33, generator_mel_loss=19.34, generator_kl_loss=1.326, generator_dur_loss=1.918, generator_adv_loss=1.848, generator_feat_match_loss=2.901, over 96.00 samples.], tot_loss[discriminator_loss=2.768, discriminator_real_loss=1.395, discriminator_fake_loss=1.373, generator_loss=27.43, generator_mel_loss=19.66, generator_kl_loss=1.365, generator_dur_loss=1.799, generator_adv_loss=1.877, generator_feat_match_loss=2.734, over 1878.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 08:08:44,676 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 08:08:52,604 INFO [train.py:591] (2/6) Epoch 83, validation: discriminator_loss=2.828, discriminator_real_loss=1.457, discriminator_fake_loss=1.371, generator_loss=26.67, generator_mel_loss=19.9, generator_kl_loss=1.167, generator_dur_loss=1.845, generator_adv_loss=1.756, generator_feat_match_loss=2.008, over 100.00 samples.
2024-03-12 08:08:52,605 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 08:11:12,300 INFO [train.py:527] (2/6) Epoch 83, batch 82, global_batch_idx: 10250, batch size: 59, loss[discriminator_loss=2.673, discriminator_real_loss=1.414, discriminator_fake_loss=1.259, generator_loss=28.33, generator_mel_loss=19.83, generator_kl_loss=1.38, generator_dur_loss=1.79, generator_adv_loss=2.148, generator_feat_match_loss=3.186, over 59.00 samples.], tot_loss[discriminator_loss=2.754, discriminator_real_loss=1.397, discriminator_fake_loss=1.358, generator_loss=27.6, generator_mel_loss=19.76, generator_kl_loss=1.372, generator_dur_loss=1.794, generator_adv_loss=1.894, generator_feat_match_loss=2.782, over 4548.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 08:13:05,018 INFO [train.py:919] (2/6) Start epoch 84
2024-03-12 08:13:51,785 INFO [train.py:527] (2/6) Epoch 84, batch 8, global_batch_idx: 10300, batch size: 55, loss[discriminator_loss=2.663, discriminator_real_loss=1.438, discriminator_fake_loss=1.225, generator_loss=27.47, generator_mel_loss=19.28, generator_kl_loss=1.528, generator_dur_loss=1.708, generator_adv_loss=1.809, generator_feat_match_loss=3.147, over 55.00 samples.], tot_loss[discriminator_loss=2.702, discriminator_real_loss=1.382, discriminator_fake_loss=1.32, generator_loss=27.79, generator_mel_loss=19.81, generator_kl_loss=1.399, generator_dur_loss=1.764, generator_adv_loss=1.875, generator_feat_match_loss=2.94, over 533.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 08:16:09,568 INFO [train.py:527] (2/6) Epoch 84, batch 58, global_batch_idx: 10350, batch size: 48, loss[discriminator_loss=2.756, discriminator_real_loss=1.372, discriminator_fake_loss=1.384, generator_loss=27.98, generator_mel_loss=20.31, generator_kl_loss=1.462, generator_dur_loss=1.725, generator_adv_loss=1.93, generator_feat_match_loss=2.553, over 48.00 samples.], tot_loss[discriminator_loss=2.737, discriminator_real_loss=1.392, discriminator_fake_loss=1.345, generator_loss=27.45, generator_mel_loss=19.59, generator_kl_loss=1.368, generator_dur_loss=1.798, generator_adv_loss=1.892, generator_feat_match_loss=2.801, over 3549.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 08:18:30,347 INFO [train.py:527] (2/6) Epoch 84, batch 108, global_batch_idx: 10400, batch size: 53, loss[discriminator_loss=2.77, discriminator_real_loss=1.478, discriminator_fake_loss=1.292, generator_loss=28.1, generator_mel_loss=20.27, generator_kl_loss=1.594, generator_dur_loss=1.681, generator_adv_loss=1.569, generator_feat_match_loss=2.994, over 53.00 samples.], tot_loss[discriminator_loss=2.751, discriminator_real_loss=1.399, discriminator_fake_loss=1.352, generator_loss=27.43, generator_mel_loss=19.61, generator_kl_loss=1.373, generator_dur_loss=1.791, generator_adv_loss=1.889, generator_feat_match_loss=2.772, over 6542.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 08:18:30,348 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 08:18:39,356 INFO [train.py:591] (2/6) Epoch 84, validation: discriminator_loss=2.949, discriminator_real_loss=1.299, discriminator_fake_loss=1.649, generator_loss=26.47, generator_mel_loss=19.88, generator_kl_loss=1.111, generator_dur_loss=1.823, generator_adv_loss=1.488, generator_feat_match_loss=2.164, over 100.00 samples.
2024-03-12 08:18:39,357 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 08:19:18,145 INFO [train.py:919] (2/6) Start epoch 85
2024-03-12 08:21:17,346 INFO [train.py:527] (2/6) Epoch 85, batch 34, global_batch_idx: 10450, batch size: 44, loss[discriminator_loss=2.708, discriminator_real_loss=1.355, discriminator_fake_loss=1.353, generator_loss=26.44, generator_mel_loss=18.59, generator_kl_loss=1.438, generator_dur_loss=1.715, generator_adv_loss=1.951, generator_feat_match_loss=2.742, over 44.00 samples.], tot_loss[discriminator_loss=2.759, discriminator_real_loss=1.416, discriminator_fake_loss=1.344, generator_loss=27.45, generator_mel_loss=19.52, generator_kl_loss=1.345, generator_dur_loss=1.798, generator_adv_loss=1.959, generator_feat_match_loss=2.825, over 2104.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 08:23:35,890 INFO [train.py:527] (2/6) Epoch 85, batch 84, global_batch_idx: 10500, batch size: 50, loss[discriminator_loss=2.715, discriminator_real_loss=1.419, discriminator_fake_loss=1.296, generator_loss=28.66, generator_mel_loss=20.66, generator_kl_loss=1.513, generator_dur_loss=1.669, generator_adv_loss=1.829, generator_feat_match_loss=2.981, over 50.00 samples.], tot_loss[discriminator_loss=2.751, discriminator_real_loss=1.4, discriminator_fake_loss=1.351, generator_loss=27.4, generator_mel_loss=19.53, generator_kl_loss=1.351, generator_dur_loss=1.783, generator_adv_loss=1.925, generator_feat_match_loss=2.809, over 5022.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 08:25:24,280 INFO [train.py:919] (2/6) Start epoch 86
2024-03-12 08:26:14,422 INFO [train.py:527] (2/6) Epoch 86, batch 10, global_batch_idx: 10550, batch size: 14, loss[discriminator_loss=2.74, discriminator_real_loss=1.197, discriminator_fake_loss=1.543, generator_loss=28.86, generator_mel_loss=20.06, generator_kl_loss=1.774, generator_dur_loss=1.714, generator_adv_loss=1.731, generator_feat_match_loss=3.585, over 14.00 samples.], tot_loss[discriminator_loss=2.761, discriminator_real_loss=1.418, discriminator_fake_loss=1.344, generator_loss=27.24, generator_mel_loss=19.34, generator_kl_loss=1.406, generator_dur_loss=1.761, generator_adv_loss=1.919, generator_feat_match_loss=2.814, over 539.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 08:28:39,021 INFO [train.py:527] (2/6) Epoch 86, batch 60, global_batch_idx: 10600, batch size: 50, loss[discriminator_loss=2.663, discriminator_real_loss=1.18, discriminator_fake_loss=1.484, generator_loss=28.31, generator_mel_loss=19.82, generator_kl_loss=1.437, generator_dur_loss=1.686, generator_adv_loss=2.097, generator_feat_match_loss=3.269, over 50.00 samples.], tot_loss[discriminator_loss=2.736, discriminator_real_loss=1.392, discriminator_fake_loss=1.344, generator_loss=27.48, generator_mel_loss=19.53, generator_kl_loss=1.379, generator_dur_loss=1.769, generator_adv_loss=1.924, generator_feat_match_loss=2.88, over 3425.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 08:28:39,022 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 08:28:46,851 INFO [train.py:591] (2/6) Epoch 86, validation: discriminator_loss=2.49, discriminator_real_loss=1.263, discriminator_fake_loss=1.227, generator_loss=27, generator_mel_loss=19.12, generator_kl_loss=1.179, generator_dur_loss=1.824, generator_adv_loss=2.144, generator_feat_match_loss=2.727, over 100.00 samples.
2024-03-12 08:28:46,852 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 08:31:04,070 INFO [train.py:527] (2/6) Epoch 86, batch 110, global_batch_idx: 10650, batch size: 45, loss[discriminator_loss=2.77, discriminator_real_loss=1.425, discriminator_fake_loss=1.346, generator_loss=26.94, generator_mel_loss=19.18, generator_kl_loss=1.519, generator_dur_loss=1.711, generator_adv_loss=1.856, generator_feat_match_loss=2.674, over 45.00 samples.], tot_loss[discriminator_loss=2.736, discriminator_real_loss=1.402, discriminator_fake_loss=1.334, generator_loss=27.68, generator_mel_loss=19.5, generator_kl_loss=1.368, generator_dur_loss=1.777, generator_adv_loss=2.018, generator_feat_match_loss=3.019, over 6308.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 08:31:40,256 INFO [train.py:919] (2/6) Start epoch 87
2024-03-12 08:33:42,585 INFO [train.py:527] (2/6) Epoch 87, batch 36, global_batch_idx: 10700, batch size: 66, loss[discriminator_loss=2.722, discriminator_real_loss=1.421, discriminator_fake_loss=1.302, generator_loss=27.05, generator_mel_loss=19.27, generator_kl_loss=1.333, generator_dur_loss=1.84, generator_adv_loss=1.847, generator_feat_match_loss=2.759, over 66.00 samples.], tot_loss[discriminator_loss=2.73, discriminator_real_loss=1.396, discriminator_fake_loss=1.333, generator_loss=27.32, generator_mel_loss=19.5, generator_kl_loss=1.374, generator_dur_loss=1.792, generator_adv_loss=1.909, generator_feat_match_loss=2.744, over 2066.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 08:36:02,593 INFO [train.py:527] (2/6) Epoch 87, batch 86, global_batch_idx: 10750, batch size: 15, loss[discriminator_loss=2.752, discriminator_real_loss=1.454, discriminator_fake_loss=1.298, generator_loss=29.18, generator_mel_loss=20.93, generator_kl_loss=1.594, generator_dur_loss=1.683, generator_adv_loss=1.834, generator_feat_match_loss=3.132, over 15.00 samples.], tot_loss[discriminator_loss=2.732, discriminator_real_loss=1.393, discriminator_fake_loss=1.338, generator_loss=27.44, generator_mel_loss=19.57, generator_kl_loss=1.376, generator_dur_loss=1.794, generator_adv_loss=1.91, generator_feat_match_loss=2.783, over 5006.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 08:37:45,798 INFO [train.py:919] (2/6) Start epoch 88
2024-03-12 08:38:43,607 INFO [train.py:527] (2/6) Epoch 88, batch 12, global_batch_idx: 10800, batch size: 80, loss[discriminator_loss=2.78, discriminator_real_loss=1.373, discriminator_fake_loss=1.406, generator_loss=26.58, generator_mel_loss=18.97, generator_kl_loss=1.29, generator_dur_loss=1.827, generator_adv_loss=1.884, generator_feat_match_loss=2.606, over 80.00 samples.], tot_loss[discriminator_loss=2.762, discriminator_real_loss=1.387, discriminator_fake_loss=1.375, generator_loss=27.14, generator_mel_loss=19.31, generator_kl_loss=1.381, generator_dur_loss=1.799, generator_adv_loss=1.852, generator_feat_match_loss=2.792, over 763.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 08:38:43,610 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 08:38:51,181 INFO [train.py:591] (2/6) Epoch 88, validation: discriminator_loss=2.811, discriminator_real_loss=1.449, discriminator_fake_loss=1.362, generator_loss=27.26, generator_mel_loss=20.33, generator_kl_loss=1.1, generator_dur_loss=1.832, generator_adv_loss=1.811, generator_feat_match_loss=2.186, over 100.00 samples.
2024-03-12 08:38:51,182 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 08:41:09,906 INFO [train.py:527] (2/6) Epoch 88, batch 62, global_batch_idx: 10850, batch size: 53, loss[discriminator_loss=2.652, discriminator_real_loss=1.466, discriminator_fake_loss=1.186, generator_loss=28.24, generator_mel_loss=20.01, generator_kl_loss=1.342, generator_dur_loss=1.738, generator_adv_loss=1.867, generator_feat_match_loss=3.287, over 53.00 samples.], tot_loss[discriminator_loss=2.75, discriminator_real_loss=1.394, discriminator_fake_loss=1.357, generator_loss=27.41, generator_mel_loss=19.53, generator_kl_loss=1.383, generator_dur_loss=1.793, generator_adv_loss=1.881, generator_feat_match_loss=2.822, over 3631.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 08:43:28,405 INFO [train.py:527] (2/6) Epoch 88, batch 112, global_batch_idx: 10900, batch size: 31, loss[discriminator_loss=2.772, discriminator_real_loss=1.474, discriminator_fake_loss=1.298, generator_loss=27.68, generator_mel_loss=19.8, generator_kl_loss=1.472, generator_dur_loss=1.653, generator_adv_loss=1.879, generator_feat_match_loss=2.873, over 31.00 samples.], tot_loss[discriminator_loss=2.769, discriminator_real_loss=1.41, discriminator_fake_loss=1.36, generator_loss=27.38, generator_mel_loss=19.5, generator_kl_loss=1.369, generator_dur_loss=1.79, generator_adv_loss=1.92, generator_feat_match_loss=2.802, over 6523.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 08:44:02,185 INFO [train.py:919] (2/6) Start epoch 89
2024-03-12 08:46:13,299 INFO [train.py:527] (2/6) Epoch 89, batch 38, global_batch_idx: 10950, batch size: 25, loss[discriminator_loss=2.654, discriminator_real_loss=1.337, discriminator_fake_loss=1.317, generator_loss=29.63, generator_mel_loss=20.91, generator_kl_loss=1.717, generator_dur_loss=1.602, generator_adv_loss=2.082, generator_feat_match_loss=3.324, over 25.00 samples.], tot_loss[discriminator_loss=2.723, discriminator_real_loss=1.379, discriminator_fake_loss=1.344, generator_loss=27.55, generator_mel_loss=19.57, generator_kl_loss=1.344, generator_dur_loss=1.821, generator_adv_loss=1.913, generator_feat_match_loss=2.904, over 2346.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 08:48:28,971 INFO [train.py:527] (2/6) Epoch 89, batch 88, global_batch_idx: 11000, batch size: 70, loss[discriminator_loss=2.753, discriminator_real_loss=1.467, discriminator_fake_loss=1.286, generator_loss=27.44, generator_mel_loss=19.43, generator_kl_loss=1.257, generator_dur_loss=1.846, generator_adv_loss=2.018, generator_feat_match_loss=2.896, over 70.00 samples.], tot_loss[discriminator_loss=2.743, discriminator_real_loss=1.393, discriminator_fake_loss=1.35, generator_loss=27.37, generator_mel_loss=19.48, generator_kl_loss=1.36, generator_dur_loss=1.804, generator_adv_loss=1.895, generator_feat_match_loss=2.828, over 5191.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 08:48:28,973 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 08:48:37,872 INFO [train.py:591] (2/6) Epoch 89, validation: discriminator_loss=2.752, discriminator_real_loss=1.557, discriminator_fake_loss=1.195, generator_loss=26.74, generator_mel_loss=19.27, generator_kl_loss=1.154, generator_dur_loss=1.835, generator_adv_loss=2.016, generator_feat_match_loss=2.461, over 100.00 samples.
2024-03-12 08:48:37,873 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 08:50:16,561 INFO [train.py:919] (2/6) Start epoch 90
2024-03-12 08:51:22,956 INFO [train.py:527] (2/6) Epoch 90, batch 14, global_batch_idx: 11050, batch size: 72, loss[discriminator_loss=2.689, discriminator_real_loss=1.386, discriminator_fake_loss=1.303, generator_loss=27.58, generator_mel_loss=19.17, generator_kl_loss=1.33, generator_dur_loss=1.842, generator_adv_loss=2.044, generator_feat_match_loss=3.193, over 72.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.365, discriminator_fake_loss=1.351, generator_loss=27.69, generator_mel_loss=19.55, generator_kl_loss=1.383, generator_dur_loss=1.781, generator_adv_loss=1.957, generator_feat_match_loss=3.019, over 948.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 08:53:43,268 INFO [train.py:527] (2/6) Epoch 90, batch 64, global_batch_idx: 11100, batch size: 72, loss[discriminator_loss=2.715, discriminator_real_loss=1.213, discriminator_fake_loss=1.501, generator_loss=28.15, generator_mel_loss=19.83, generator_kl_loss=1.257, generator_dur_loss=1.81, generator_adv_loss=1.94, generator_feat_match_loss=3.308, over 72.00 samples.], tot_loss[discriminator_loss=2.75, discriminator_real_loss=1.387, discriminator_fake_loss=1.362, generator_loss=27.46, generator_mel_loss=19.51, generator_kl_loss=1.358, generator_dur_loss=1.808, generator_adv_loss=1.907, generator_feat_match_loss=2.868, over 3963.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 08:56:00,687 INFO [train.py:527] (2/6) Epoch 90, batch 114, global_batch_idx: 11150, batch size: 52, loss[discriminator_loss=2.745, discriminator_real_loss=1.417, discriminator_fake_loss=1.329, generator_loss=28, generator_mel_loss=19.78, generator_kl_loss=1.484, generator_dur_loss=1.75, generator_adv_loss=1.851, generator_feat_match_loss=3.127, over 52.00 samples.], tot_loss[discriminator_loss=2.741, discriminator_real_loss=1.386, discriminator_fake_loss=1.355, generator_loss=27.46, generator_mel_loss=19.5, generator_kl_loss=1.37, generator_dur_loss=1.802, generator_adv_loss=1.907, generator_feat_match_loss=2.88, over 6873.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 08:56:24,282 INFO [train.py:919] (2/6) Start epoch 91
2024-03-12 08:58:38,260 INFO [train.py:527] (2/6) Epoch 91, batch 40, global_batch_idx: 11200, batch size: 62, loss[discriminator_loss=2.683, discriminator_real_loss=1.354, discriminator_fake_loss=1.329, generator_loss=27.97, generator_mel_loss=19.68, generator_kl_loss=1.522, generator_dur_loss=1.77, generator_adv_loss=1.908, generator_feat_match_loss=3.092, over 62.00 samples.], tot_loss[discriminator_loss=2.746, discriminator_real_loss=1.387, discriminator_fake_loss=1.358, generator_loss=27.68, generator_mel_loss=19.74, generator_kl_loss=1.381, generator_dur_loss=1.776, generator_adv_loss=1.903, generator_feat_match_loss=2.882, over 2315.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 08:58:38,262 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 08:58:46,107 INFO [train.py:591] (2/6) Epoch 91, validation: discriminator_loss=2.709, discriminator_real_loss=1.359, discriminator_fake_loss=1.35, generator_loss=27.02, generator_mel_loss=19.51, generator_kl_loss=1.237, generator_dur_loss=1.81, generator_adv_loss=1.85, generator_feat_match_loss=2.611, over 100.00 samples.
2024-03-12 08:58:46,108 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 09:01:04,262 INFO [train.py:527] (2/6) Epoch 91, batch 90, global_batch_idx: 11250, batch size: 39, loss[discriminator_loss=2.733, discriminator_real_loss=1.354, discriminator_fake_loss=1.379, generator_loss=27.33, generator_mel_loss=19.39, generator_kl_loss=1.475, generator_dur_loss=1.705, generator_adv_loss=1.788, generator_feat_match_loss=2.969, over 39.00 samples.], tot_loss[discriminator_loss=2.744, discriminator_real_loss=1.39, discriminator_fake_loss=1.354, generator_loss=27.46, generator_mel_loss=19.55, generator_kl_loss=1.379, generator_dur_loss=1.778, generator_adv_loss=1.891, generator_feat_match_loss=2.862, over 5271.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 09:02:38,022 INFO [train.py:919] (2/6) Start epoch 92
2024-03-12 09:03:48,772 INFO [train.py:527] (2/6) Epoch 92, batch 16, global_batch_idx: 11300, batch size: 74, loss[discriminator_loss=2.736, discriminator_real_loss=1.351, discriminator_fake_loss=1.385, generator_loss=27.41, generator_mel_loss=19.46, generator_kl_loss=1.266, generator_dur_loss=1.84, generator_adv_loss=2.005, generator_feat_match_loss=2.843, over 74.00 samples.], tot_loss[discriminator_loss=2.752, discriminator_real_loss=1.407, discriminator_fake_loss=1.345, generator_loss=27.21, generator_mel_loss=19.32, generator_kl_loss=1.394, generator_dur_loss=1.776, generator_adv_loss=1.942, generator_feat_match_loss=2.782, over 904.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 09:06:10,305 INFO [train.py:527] (2/6) Epoch 92, batch 66, global_batch_idx: 11350, batch size: 53, loss[discriminator_loss=2.731, discriminator_real_loss=1.305, discriminator_fake_loss=1.427, generator_loss=27.66, generator_mel_loss=19.62, generator_kl_loss=1.364, generator_dur_loss=1.759, generator_adv_loss=2.03, generator_feat_match_loss=2.886, over 53.00 samples.], tot_loss[discriminator_loss=2.737, discriminator_real_loss=1.396, discriminator_fake_loss=1.341, generator_loss=27.47, generator_mel_loss=19.54, generator_kl_loss=1.392, generator_dur_loss=1.787, generator_adv_loss=1.907, generator_feat_match_loss=2.844, over 3784.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 09:08:27,323 INFO [train.py:527] (2/6) Epoch 92, batch 116, global_batch_idx: 11400, batch size: 70, loss[discriminator_loss=2.812, discriminator_real_loss=1.46, discriminator_fake_loss=1.352, generator_loss=27.57, generator_mel_loss=19.77, generator_kl_loss=1.395, generator_dur_loss=1.782, generator_adv_loss=1.909, generator_feat_match_loss=2.717, over 70.00 samples.], tot_loss[discriminator_loss=2.736, discriminator_real_loss=1.398, discriminator_fake_loss=1.338, generator_loss=27.59, generator_mel_loss=19.6, generator_kl_loss=1.386, generator_dur_loss=1.771, generator_adv_loss=1.932, generator_feat_match_loss=2.905, over 6467.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 09:08:27,324 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 09:08:36,556 INFO [train.py:591] (2/6) Epoch 92, validation: discriminator_loss=2.79, discriminator_real_loss=1.531, discriminator_fake_loss=1.259, generator_loss=27.22, generator_mel_loss=19.99, generator_kl_loss=1.191, generator_dur_loss=1.808, generator_adv_loss=1.89, generator_feat_match_loss=2.342, over 100.00 samples.
2024-03-12 09:08:36,557 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 09:08:55,448 INFO [train.py:919] (2/6) Start epoch 93
2024-03-12 09:11:18,248 INFO [train.py:527] (2/6) Epoch 93, batch 42, global_batch_idx: 11450, batch size: 62, loss[discriminator_loss=2.695, discriminator_real_loss=1.225, discriminator_fake_loss=1.47, generator_loss=26.58, generator_mel_loss=18.95, generator_kl_loss=1.349, generator_dur_loss=1.704, generator_adv_loss=1.878, generator_feat_match_loss=2.7, over 62.00 samples.], tot_loss[discriminator_loss=2.742, discriminator_real_loss=1.39, discriminator_fake_loss=1.352, generator_loss=27.39, generator_mel_loss=19.49, generator_kl_loss=1.341, generator_dur_loss=1.772, generator_adv_loss=1.929, generator_feat_match_loss=2.86, over 2643.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 09:13:34,403 INFO [train.py:527] (2/6) Epoch 93, batch 92, global_batch_idx: 11500, batch size: 45, loss[discriminator_loss=2.714, discriminator_real_loss=1.452, discriminator_fake_loss=1.262, generator_loss=28.4, generator_mel_loss=20.23, generator_kl_loss=1.64, generator_dur_loss=1.638, generator_adv_loss=1.829, generator_feat_match_loss=3.054, over 45.00 samples.], tot_loss[discriminator_loss=2.749, discriminator_real_loss=1.398, discriminator_fake_loss=1.351, generator_loss=27.37, generator_mel_loss=19.46, generator_kl_loss=1.36, generator_dur_loss=1.755, generator_adv_loss=1.921, generator_feat_match_loss=2.871, over 5530.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 09:15:01,496 INFO [train.py:919] (2/6) Start epoch 94
2024-03-12 09:16:10,287 INFO [train.py:527] (2/6) Epoch 94, batch 18, global_batch_idx: 11550, batch size: 66, loss[discriminator_loss=2.658, discriminator_real_loss=1.375, discriminator_fake_loss=1.283, generator_loss=26.95, generator_mel_loss=18.94, generator_kl_loss=1.338, generator_dur_loss=1.778, generator_adv_loss=1.955, generator_feat_match_loss=2.944, over 66.00 samples.], tot_loss[discriminator_loss=2.713, discriminator_real_loss=1.373, discriminator_fake_loss=1.34, generator_loss=27.26, generator_mel_loss=19.3, generator_kl_loss=1.364, generator_dur_loss=1.759, generator_adv_loss=1.905, generator_feat_match_loss=2.929, over 1093.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 09:18:29,016 INFO [train.py:527] (2/6) Epoch 94, batch 68, global_batch_idx: 11600, batch size: 52, loss[discriminator_loss=2.771, discriminator_real_loss=1.372, discriminator_fake_loss=1.399, generator_loss=28.84, generator_mel_loss=20.37, generator_kl_loss=1.555, generator_dur_loss=1.651, generator_adv_loss=2.032, generator_feat_match_loss=3.231, over 52.00 samples.], tot_loss[discriminator_loss=2.733, discriminator_real_loss=1.385, discriminator_fake_loss=1.348, generator_loss=27.34, generator_mel_loss=19.39, generator_kl_loss=1.366, generator_dur_loss=1.748, generator_adv_loss=1.91, generator_feat_match_loss=2.925, over 3958.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 09:18:29,018 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 09:18:37,810 INFO [train.py:591] (2/6) Epoch 94, validation: discriminator_loss=2.789, discriminator_real_loss=1.553, discriminator_fake_loss=1.236, generator_loss=27.3, generator_mel_loss=19.89, generator_kl_loss=1.23, generator_dur_loss=1.789, generator_adv_loss=1.981, generator_feat_match_loss=2.414, over 100.00 samples.
2024-03-12 09:18:37,811 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 09:20:57,127 INFO [train.py:527] (2/6) Epoch 94, batch 118, global_batch_idx: 11650, batch size: 61, loss[discriminator_loss=2.653, discriminator_real_loss=1.334, discriminator_fake_loss=1.319, generator_loss=28.64, generator_mel_loss=19.81, generator_kl_loss=1.407, generator_dur_loss=1.676, generator_adv_loss=2.016, generator_feat_match_loss=3.732, over 61.00 samples.], tot_loss[discriminator_loss=2.725, discriminator_real_loss=1.38, discriminator_fake_loss=1.345, generator_loss=27.35, generator_mel_loss=19.35, generator_kl_loss=1.378, generator_dur_loss=1.735, generator_adv_loss=1.927, generator_feat_match_loss=2.961, over 6823.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 09:21:13,855 INFO [train.py:919] (2/6) Start epoch 95
2024-03-12 09:23:40,781 INFO [train.py:527] (2/6) Epoch 95, batch 44, global_batch_idx: 11700, batch size: 72, loss[discriminator_loss=2.776, discriminator_real_loss=1.472, discriminator_fake_loss=1.304, generator_loss=26.87, generator_mel_loss=19.22, generator_kl_loss=1.222, generator_dur_loss=1.797, generator_adv_loss=1.837, generator_feat_match_loss=2.789, over 72.00 samples.], tot_loss[discriminator_loss=2.739, discriminator_real_loss=1.391, discriminator_fake_loss=1.349, generator_loss=27.49, generator_mel_loss=19.52, generator_kl_loss=1.357, generator_dur_loss=1.745, generator_adv_loss=1.923, generator_feat_match_loss=2.951, over 2611.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 09:26:04,504 INFO [train.py:527] (2/6) Epoch 95, batch 94, global_batch_idx: 11750, batch size: 70, loss[discriminator_loss=2.784, discriminator_real_loss=1.295, discriminator_fake_loss=1.489, generator_loss=27.13, generator_mel_loss=19.11, generator_kl_loss=1.416, generator_dur_loss=1.783, generator_adv_loss=1.935, generator_feat_match_loss=2.883, over 70.00 samples.], tot_loss[discriminator_loss=2.744, discriminator_real_loss=1.393, discriminator_fake_loss=1.351, generator_loss=27.4, generator_mel_loss=19.45, generator_kl_loss=1.374, generator_dur_loss=1.749, generator_adv_loss=1.915, generator_feat_match_loss=2.908, over 5685.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 09:27:30,753 INFO [train.py:919] (2/6) Start epoch 96
2024-03-12 09:28:50,225 INFO [train.py:527] (2/6) Epoch 96, batch 20, global_batch_idx: 11800, batch size: 77, loss[discriminator_loss=2.707, discriminator_real_loss=1.368, discriminator_fake_loss=1.339, generator_loss=27.79, generator_mel_loss=19.6, generator_kl_loss=1.333, generator_dur_loss=1.788, generator_adv_loss=1.971, generator_feat_match_loss=3.102, over 77.00 samples.], tot_loss[discriminator_loss=2.744, discriminator_real_loss=1.399, discriminator_fake_loss=1.345, generator_loss=27.6, generator_mel_loss=19.57, generator_kl_loss=1.407, generator_dur_loss=1.762, generator_adv_loss=1.914, generator_feat_match_loss=2.949, over 1188.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 09:28:50,227 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 09:28:58,043 INFO [train.py:591] (2/6) Epoch 96, validation: discriminator_loss=2.716, discriminator_real_loss=1.489, discriminator_fake_loss=1.227, generator_loss=26.48, generator_mel_loss=19.32, generator_kl_loss=1.108, generator_dur_loss=1.819, generator_adv_loss=1.963, generator_feat_match_loss=2.267, over 100.00 samples.
2024-03-12 09:28:58,044 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 09:31:21,703 INFO [train.py:527] (2/6) Epoch 96, batch 70, global_batch_idx: 11850, batch size: 48, loss[discriminator_loss=2.687, discriminator_real_loss=1.284, discriminator_fake_loss=1.403, generator_loss=27.71, generator_mel_loss=19.32, generator_kl_loss=1.441, generator_dur_loss=1.747, generator_adv_loss=1.982, generator_feat_match_loss=3.218, over 48.00 samples.], tot_loss[discriminator_loss=2.763, discriminator_real_loss=1.399, discriminator_fake_loss=1.363, generator_loss=27.57, generator_mel_loss=19.46, generator_kl_loss=1.39, generator_dur_loss=1.771, generator_adv_loss=1.942, generator_feat_match_loss=3.006, over 4220.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 09:33:43,432 INFO [train.py:527] (2/6) Epoch 96, batch 120, global_batch_idx: 11900, batch size: 88, loss[discriminator_loss=2.922, discriminator_real_loss=1.196, discriminator_fake_loss=1.726, generator_loss=26.74, generator_mel_loss=18.94, generator_kl_loss=1.291, generator_dur_loss=1.81, generator_adv_loss=1.838, generator_feat_match_loss=2.863, over 88.00 samples.], tot_loss[discriminator_loss=2.755, discriminator_real_loss=1.393, discriminator_fake_loss=1.362, generator_loss=27.52, generator_mel_loss=19.45, generator_kl_loss=1.38, generator_dur_loss=1.765, generator_adv_loss=1.935, generator_feat_match_loss=2.988, over 6925.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 09:33:55,166 INFO [train.py:919] (2/6) Start epoch 97
2024-03-12 09:36:28,032 INFO [train.py:527] (2/6) Epoch 97, batch 46, global_batch_idx: 11950, batch size: 58, loss[discriminator_loss=2.767, discriminator_real_loss=1.406, discriminator_fake_loss=1.362, generator_loss=27.62, generator_mel_loss=19.27, generator_kl_loss=1.441, generator_dur_loss=1.711, generator_adv_loss=1.951, generator_feat_match_loss=3.246, over 58.00 samples.], tot_loss[discriminator_loss=2.734, discriminator_real_loss=1.384, discriminator_fake_loss=1.35, generator_loss=27.54, generator_mel_loss=19.46, generator_kl_loss=1.378, generator_dur_loss=1.769, generator_adv_loss=1.913, generator_feat_match_loss=3.02, over 2708.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 09:38:50,947 INFO [train.py:527] (2/6) Epoch 97, batch 96, global_batch_idx: 12000, batch size: 55, loss[discriminator_loss=2.779, discriminator_real_loss=1.349, discriminator_fake_loss=1.43, generator_loss=27.33, generator_mel_loss=19.2, generator_kl_loss=1.386, generator_dur_loss=1.73, generator_adv_loss=1.989, generator_feat_match_loss=3.024, over 55.00 samples.], tot_loss[discriminator_loss=2.739, discriminator_real_loss=1.389, discriminator_fake_loss=1.35, generator_loss=27.45, generator_mel_loss=19.41, generator_kl_loss=1.388, generator_dur_loss=1.783, generator_adv_loss=1.907, generator_feat_match_loss=2.964, over 5694.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 09:38:50,949 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 09:38:59,575 INFO [train.py:591] (2/6) Epoch 97, validation: discriminator_loss=2.715, discriminator_real_loss=1.468, discriminator_fake_loss=1.247, generator_loss=26.83, generator_mel_loss=19.48, generator_kl_loss=1.2, generator_dur_loss=1.834, generator_adv_loss=1.95, generator_feat_match_loss=2.361, over 100.00 samples.
2024-03-12 09:38:59,577 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 09:40:12,062 INFO [train.py:919] (2/6) Start epoch 98
2024-03-12 09:41:40,450 INFO [train.py:527] (2/6) Epoch 98, batch 22, global_batch_idx: 12050, batch size: 56, loss[discriminator_loss=2.788, discriminator_real_loss=1.542, discriminator_fake_loss=1.246, generator_loss=26.63, generator_mel_loss=19.24, generator_kl_loss=1.494, generator_dur_loss=1.731, generator_adv_loss=1.649, generator_feat_match_loss=2.515, over 56.00 samples.], tot_loss[discriminator_loss=2.744, discriminator_real_loss=1.393, discriminator_fake_loss=1.351, generator_loss=27.18, generator_mel_loss=19.22, generator_kl_loss=1.415, generator_dur_loss=1.785, generator_adv_loss=1.898, generator_feat_match_loss=2.866, over 1269.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 09:44:00,515 INFO [train.py:527] (2/6) Epoch 98, batch 72, global_batch_idx: 12100, batch size: 44, loss[discriminator_loss=2.746, discriminator_real_loss=1.448, discriminator_fake_loss=1.297, generator_loss=27.08, generator_mel_loss=19.14, generator_kl_loss=1.523, generator_dur_loss=1.745, generator_adv_loss=1.81, generator_feat_match_loss=2.865, over 44.00 samples.], tot_loss[discriminator_loss=2.761, discriminator_real_loss=1.417, discriminator_fake_loss=1.344, generator_loss=27.47, generator_mel_loss=19.32, generator_kl_loss=1.389, generator_dur_loss=1.778, generator_adv_loss=1.97, generator_feat_match_loss=3.011, over 4199.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 09:46:23,279 INFO [train.py:527] (2/6) Epoch 98, batch 122, global_batch_idx: 12150, batch size: 68, loss[discriminator_loss=2.7, discriminator_real_loss=1.337, discriminator_fake_loss=1.364, generator_loss=27.63, generator_mel_loss=19.47, generator_kl_loss=1.413, generator_dur_loss=1.74, generator_adv_loss=1.971, generator_feat_match_loss=3.035, over 68.00 samples.], tot_loss[discriminator_loss=2.751, discriminator_real_loss=1.409, discriminator_fake_loss=1.343, generator_loss=27.33, generator_mel_loss=19.25, generator_kl_loss=1.391, generator_dur_loss=1.78, generator_adv_loss=1.952, generator_feat_match_loss=2.961, over 6856.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 09:46:27,942 INFO [train.py:919] (2/6) Start epoch 99
2024-03-12 09:49:09,522 INFO [train.py:527] (2/6) Epoch 99, batch 48, global_batch_idx: 12200, batch size: 36, loss[discriminator_loss=2.771, discriminator_real_loss=1.547, discriminator_fake_loss=1.224, generator_loss=26.6, generator_mel_loss=18.74, generator_kl_loss=1.488, generator_dur_loss=1.675, generator_adv_loss=1.889, generator_feat_match_loss=2.803, over 36.00 samples.], tot_loss[discriminator_loss=2.729, discriminator_real_loss=1.385, discriminator_fake_loss=1.344, generator_loss=27.26, generator_mel_loss=19.24, generator_kl_loss=1.359, generator_dur_loss=1.792, generator_adv_loss=1.923, generator_feat_match_loss=2.947, over 2906.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 09:49:09,524 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 09:49:17,401 INFO [train.py:591] (2/6) Epoch 99, validation: discriminator_loss=2.729, discriminator_real_loss=1.43, discriminator_fake_loss=1.299, generator_loss=27.87, generator_mel_loss=20.36, generator_kl_loss=1.145, generator_dur_loss=1.836, generator_adv_loss=1.867, generator_feat_match_loss=2.665, over 100.00 samples.
2024-03-12 09:49:17,402 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 09:51:38,233 INFO [train.py:527] (2/6) Epoch 99, batch 98, global_batch_idx: 12250, batch size: 39, loss[discriminator_loss=2.676, discriminator_real_loss=1.252, discriminator_fake_loss=1.424, generator_loss=28.84, generator_mel_loss=20.19, generator_kl_loss=1.571, generator_dur_loss=1.736, generator_adv_loss=1.971, generator_feat_match_loss=3.372, over 39.00 samples.], tot_loss[discriminator_loss=2.743, discriminator_real_loss=1.397, discriminator_fake_loss=1.346, generator_loss=27.22, generator_mel_loss=19.28, generator_kl_loss=1.366, generator_dur_loss=1.791, generator_adv_loss=1.901, generator_feat_match_loss=2.881, over 5610.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 09:52:48,887 INFO [train.py:919] (2/6) Start epoch 100
2024-03-12 09:54:22,577 INFO [train.py:527] (2/6) Epoch 100, batch 24, global_batch_idx: 12300, batch size: 48, loss[discriminator_loss=2.74, discriminator_real_loss=1.389, discriminator_fake_loss=1.351, generator_loss=27.9, generator_mel_loss=19.68, generator_kl_loss=1.56, generator_dur_loss=1.686, generator_adv_loss=1.951, generator_feat_match_loss=3.026, over 48.00 samples.], tot_loss[discriminator_loss=2.763, discriminator_real_loss=1.416, discriminator_fake_loss=1.347, generator_loss=27.46, generator_mel_loss=19.41, generator_kl_loss=1.426, generator_dur_loss=1.748, generator_adv_loss=1.902, generator_feat_match_loss=2.979, over 1372.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 09:56:41,980 INFO [train.py:527] (2/6) Epoch 100, batch 74, global_batch_idx: 12350, batch size: 25, loss[discriminator_loss=2.579, discriminator_real_loss=1.319, discriminator_fake_loss=1.261, generator_loss=29.08, generator_mel_loss=19.51, generator_kl_loss=1.564, generator_dur_loss=1.592, generator_adv_loss=2.417, generator_feat_match_loss=3.999, over 25.00 samples.], tot_loss[discriminator_loss=2.751, discriminator_real_loss=1.396, discriminator_fake_loss=1.354, generator_loss=27.54, generator_mel_loss=19.4, generator_kl_loss=1.401, generator_dur_loss=1.764, generator_adv_loss=1.929, generator_feat_match_loss=3.042, over 4130.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 09:59:04,038 INFO [train.py:919] (2/6) Start epoch 101
2024-03-12 09:59:33,528 INFO [train.py:527] (2/6) Epoch 101, batch 0, global_batch_idx: 12400, batch size: 13, loss[discriminator_loss=2.633, discriminator_real_loss=1.272, discriminator_fake_loss=1.361, generator_loss=29.01, generator_mel_loss=20.58, generator_kl_loss=1.761, generator_dur_loss=1.677, generator_adv_loss=1.854, generator_feat_match_loss=3.143, over 13.00 samples.], tot_loss[discriminator_loss=2.633, discriminator_real_loss=1.272, discriminator_fake_loss=1.361, generator_loss=29.01, generator_mel_loss=20.58, generator_kl_loss=1.761, generator_dur_loss=1.677, generator_adv_loss=1.854, generator_feat_match_loss=3.143, over 13.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 09:59:33,531 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 09:59:41,317 INFO [train.py:591] (2/6) Epoch 101, validation: discriminator_loss=2.747, discriminator_real_loss=1.379, discriminator_fake_loss=1.368, generator_loss=27.1, generator_mel_loss=19.92, generator_kl_loss=1.113, generator_dur_loss=1.817, generator_adv_loss=1.748, generator_feat_match_loss=2.501, over 100.00 samples.
2024-03-12 09:59:41,319 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 10:02:00,961 INFO [train.py:527] (2/6) Epoch 101, batch 50, global_batch_idx: 12450, batch size: 61, loss[discriminator_loss=2.791, discriminator_real_loss=1.479, discriminator_fake_loss=1.312, generator_loss=27.3, generator_mel_loss=19.5, generator_kl_loss=1.311, generator_dur_loss=1.775, generator_adv_loss=1.882, generator_feat_match_loss=2.824, over 61.00 samples.], tot_loss[discriminator_loss=2.746, discriminator_real_loss=1.389, discriminator_fake_loss=1.357, generator_loss=27.46, generator_mel_loss=19.46, generator_kl_loss=1.403, generator_dur_loss=1.772, generator_adv_loss=1.897, generator_feat_match_loss=2.933, over 2851.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 10:04:20,062 INFO [train.py:527] (2/6) Epoch 101, batch 100, global_batch_idx: 12500, batch size: 53, loss[discriminator_loss=2.787, discriminator_real_loss=1.397, discriminator_fake_loss=1.39, generator_loss=27.11, generator_mel_loss=19.36, generator_kl_loss=1.498, generator_dur_loss=1.762, generator_adv_loss=1.706, generator_feat_match_loss=2.784, over 53.00 samples.], tot_loss[discriminator_loss=2.746, discriminator_real_loss=1.396, discriminator_fake_loss=1.35, generator_loss=27.38, generator_mel_loss=19.36, generator_kl_loss=1.399, generator_dur_loss=1.774, generator_adv_loss=1.911, generator_feat_match_loss=2.936, over 5603.00 samples.], cur_lr_g: 1.98e-04, cur_lr_d: 1.98e-04, 
2024-03-12 10:05:28,555 INFO [train.py:919] (2/6) Start epoch 102
2024-03-12 10:07:05,945 INFO [train.py:527] (2/6) Epoch 102, batch 26, global_batch_idx: 12550, batch size: 68, loss[discriminator_loss=2.701, discriminator_real_loss=1.466, discriminator_fake_loss=1.234, generator_loss=27.64, generator_mel_loss=19.44, generator_kl_loss=1.311, generator_dur_loss=1.786, generator_adv_loss=2.07, generator_feat_match_loss=3.032, over 68.00 samples.], tot_loss[discriminator_loss=2.751, discriminator_real_loss=1.408, discriminator_fake_loss=1.343, generator_loss=27.11, generator_mel_loss=19.18, generator_kl_loss=1.401, generator_dur_loss=1.756, generator_adv_loss=1.885, generator_feat_match_loss=2.89, over 1462.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 10:09:27,028 INFO [train.py:527] (2/6) Epoch 102, batch 76, global_batch_idx: 12600, batch size: 80, loss[discriminator_loss=2.746, discriminator_real_loss=1.387, discriminator_fake_loss=1.36, generator_loss=26.65, generator_mel_loss=18.72, generator_kl_loss=1.439, generator_dur_loss=1.791, generator_adv_loss=1.846, generator_feat_match_loss=2.847, over 80.00 samples.], tot_loss[discriminator_loss=2.749, discriminator_real_loss=1.402, discriminator_fake_loss=1.346, generator_loss=27.3, generator_mel_loss=19.26, generator_kl_loss=1.386, generator_dur_loss=1.767, generator_adv_loss=1.934, generator_feat_match_loss=2.947, over 4261.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 10:09:27,030 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 10:09:35,879 INFO [train.py:591] (2/6) Epoch 102, validation: discriminator_loss=2.726, discriminator_real_loss=1.317, discriminator_fake_loss=1.409, generator_loss=26.52, generator_mel_loss=19.64, generator_kl_loss=1.136, generator_dur_loss=1.834, generator_adv_loss=1.754, generator_feat_match_loss=2.162, over 100.00 samples.
2024-03-12 10:09:35,880 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 10:11:48,582 INFO [train.py:919] (2/6) Start epoch 103
2024-03-12 10:12:19,671 INFO [train.py:527] (2/6) Epoch 103, batch 2, global_batch_idx: 12650, batch size: 53, loss[discriminator_loss=2.679, discriminator_real_loss=1.288, discriminator_fake_loss=1.391, generator_loss=27.71, generator_mel_loss=19.2, generator_kl_loss=1.537, generator_dur_loss=1.754, generator_adv_loss=1.864, generator_feat_match_loss=3.353, over 53.00 samples.], tot_loss[discriminator_loss=2.761, discriminator_real_loss=1.429, discriminator_fake_loss=1.332, generator_loss=27.45, generator_mel_loss=19.36, generator_kl_loss=1.463, generator_dur_loss=1.774, generator_adv_loss=1.928, generator_feat_match_loss=2.922, over 166.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 10:14:41,572 INFO [train.py:527] (2/6) Epoch 103, batch 52, global_batch_idx: 12700, batch size: 83, loss[discriminator_loss=2.796, discriminator_real_loss=1.37, discriminator_fake_loss=1.426, generator_loss=25.72, generator_mel_loss=17.93, generator_kl_loss=1.349, generator_dur_loss=1.793, generator_adv_loss=1.971, generator_feat_match_loss=2.675, over 83.00 samples.], tot_loss[discriminator_loss=2.732, discriminator_real_loss=1.38, discriminator_fake_loss=1.352, generator_loss=27.41, generator_mel_loss=19.27, generator_kl_loss=1.43, generator_dur_loss=1.737, generator_adv_loss=1.918, generator_feat_match_loss=3.053, over 2758.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 10:17:01,166 INFO [train.py:527] (2/6) Epoch 103, batch 102, global_batch_idx: 12750, batch size: 88, loss[discriminator_loss=2.761, discriminator_real_loss=1.376, discriminator_fake_loss=1.384, generator_loss=26.98, generator_mel_loss=18.81, generator_kl_loss=1.362, generator_dur_loss=1.866, generator_adv_loss=1.884, generator_feat_match_loss=3.05, over 88.00 samples.], tot_loss[discriminator_loss=2.737, discriminator_real_loss=1.387, discriminator_fake_loss=1.351, generator_loss=27.41, generator_mel_loss=19.3, generator_kl_loss=1.412, generator_dur_loss=1.744, generator_adv_loss=1.923, generator_feat_match_loss=3.029, over 5613.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 10:18:03,394 INFO [train.py:919] (2/6) Start epoch 104
2024-03-12 10:19:45,650 INFO [train.py:527] (2/6) Epoch 104, batch 28, global_batch_idx: 12800, batch size: 72, loss[discriminator_loss=2.695, discriminator_real_loss=1.389, discriminator_fake_loss=1.306, generator_loss=27.62, generator_mel_loss=19.41, generator_kl_loss=1.348, generator_dur_loss=1.876, generator_adv_loss=1.832, generator_feat_match_loss=3.161, over 72.00 samples.], tot_loss[discriminator_loss=2.763, discriminator_real_loss=1.393, discriminator_fake_loss=1.37, generator_loss=27.13, generator_mel_loss=19.21, generator_kl_loss=1.388, generator_dur_loss=1.771, generator_adv_loss=1.875, generator_feat_match_loss=2.89, over 1790.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 10:19:45,651 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 10:19:53,816 INFO [train.py:591] (2/6) Epoch 104, validation: discriminator_loss=2.756, discriminator_real_loss=1.366, discriminator_fake_loss=1.39, generator_loss=26.69, generator_mel_loss=19.5, generator_kl_loss=1.266, generator_dur_loss=1.804, generator_adv_loss=1.795, generator_feat_match_loss=2.324, over 100.00 samples.
2024-03-12 10:19:53,817 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 10:22:18,515 INFO [train.py:527] (2/6) Epoch 104, batch 78, global_batch_idx: 12850, batch size: 77, loss[discriminator_loss=2.652, discriminator_real_loss=1.299, discriminator_fake_loss=1.353, generator_loss=27.41, generator_mel_loss=19.27, generator_kl_loss=1.276, generator_dur_loss=1.807, generator_adv_loss=1.887, generator_feat_match_loss=3.168, over 77.00 samples.], tot_loss[discriminator_loss=2.758, discriminator_real_loss=1.394, discriminator_fake_loss=1.364, generator_loss=27.21, generator_mel_loss=19.24, generator_kl_loss=1.371, generator_dur_loss=1.78, generator_adv_loss=1.878, generator_feat_match_loss=2.948, over 4911.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 10:24:25,337 INFO [train.py:919] (2/6) Start epoch 105
2024-03-12 10:25:02,213 INFO [train.py:527] (2/6) Epoch 105, batch 4, global_batch_idx: 12900, batch size: 45, loss[discriminator_loss=2.836, discriminator_real_loss=1.419, discriminator_fake_loss=1.417, generator_loss=26.04, generator_mel_loss=18.81, generator_kl_loss=1.463, generator_dur_loss=1.691, generator_adv_loss=1.788, generator_feat_match_loss=2.291, over 45.00 samples.], tot_loss[discriminator_loss=2.756, discriminator_real_loss=1.363, discriminator_fake_loss=1.392, generator_loss=26.89, generator_mel_loss=19.04, generator_kl_loss=1.39, generator_dur_loss=1.737, generator_adv_loss=1.863, generator_feat_match_loss=2.864, over 272.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 10:27:25,861 INFO [train.py:527] (2/6) Epoch 105, batch 54, global_batch_idx: 12950, batch size: 56, loss[discriminator_loss=2.727, discriminator_real_loss=1.407, discriminator_fake_loss=1.32, generator_loss=27.18, generator_mel_loss=19.18, generator_kl_loss=1.378, generator_dur_loss=1.681, generator_adv_loss=1.943, generator_feat_match_loss=3.001, over 56.00 samples.], tot_loss[discriminator_loss=2.753, discriminator_real_loss=1.394, discriminator_fake_loss=1.359, generator_loss=27.09, generator_mel_loss=19.1, generator_kl_loss=1.377, generator_dur_loss=1.784, generator_adv_loss=1.895, generator_feat_match_loss=2.935, over 3340.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 10:29:48,124 INFO [train.py:527] (2/6) Epoch 105, batch 104, global_batch_idx: 13000, batch size: 96, loss[discriminator_loss=2.674, discriminator_real_loss=1.275, discriminator_fake_loss=1.4, generator_loss=27.14, generator_mel_loss=18.61, generator_kl_loss=1.317, generator_dur_loss=1.928, generator_adv_loss=1.897, generator_feat_match_loss=3.385, over 96.00 samples.], tot_loss[discriminator_loss=2.752, discriminator_real_loss=1.397, discriminator_fake_loss=1.355, generator_loss=27.08, generator_mel_loss=19.08, generator_kl_loss=1.368, generator_dur_loss=1.787, generator_adv_loss=1.895, generator_feat_match_loss=2.957, over 6278.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 10:29:48,126 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 10:29:57,126 INFO [train.py:591] (2/6) Epoch 105, validation: discriminator_loss=2.617, discriminator_real_loss=1.249, discriminator_fake_loss=1.368, generator_loss=26.98, generator_mel_loss=19.23, generator_kl_loss=1.241, generator_dur_loss=1.776, generator_adv_loss=1.931, generator_feat_match_loss=2.793, over 100.00 samples.
2024-03-12 10:29:57,127 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 10:30:50,544 INFO [train.py:919] (2/6) Start epoch 106
2024-03-12 10:32:41,801 INFO [train.py:527] (2/6) Epoch 106, batch 30, global_batch_idx: 13050, batch size: 83, loss[discriminator_loss=2.698, discriminator_real_loss=1.378, discriminator_fake_loss=1.32, generator_loss=27.23, generator_mel_loss=19.06, generator_kl_loss=1.344, generator_dur_loss=1.808, generator_adv_loss=1.847, generator_feat_match_loss=3.174, over 83.00 samples.], tot_loss[discriminator_loss=2.755, discriminator_real_loss=1.399, discriminator_fake_loss=1.356, generator_loss=27.26, generator_mel_loss=19.21, generator_kl_loss=1.392, generator_dur_loss=1.776, generator_adv_loss=1.917, generator_feat_match_loss=2.971, over 1773.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 10:35:02,097 INFO [train.py:527] (2/6) Epoch 106, batch 80, global_batch_idx: 13100, batch size: 70, loss[discriminator_loss=2.818, discriminator_real_loss=1.296, discriminator_fake_loss=1.522, generator_loss=26.32, generator_mel_loss=18.66, generator_kl_loss=1.336, generator_dur_loss=1.798, generator_adv_loss=2.03, generator_feat_match_loss=2.498, over 70.00 samples.], tot_loss[discriminator_loss=2.749, discriminator_real_loss=1.391, discriminator_fake_loss=1.358, generator_loss=27.32, generator_mel_loss=19.25, generator_kl_loss=1.38, generator_dur_loss=1.775, generator_adv_loss=1.909, generator_feat_match_loss=3.013, over 4696.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 10:37:09,246 INFO [train.py:919] (2/6) Start epoch 107
2024-03-12 10:37:52,377 INFO [train.py:527] (2/6) Epoch 107, batch 6, global_batch_idx: 13150, batch size: 70, loss[discriminator_loss=2.737, discriminator_real_loss=1.406, discriminator_fake_loss=1.331, generator_loss=26.93, generator_mel_loss=19.11, generator_kl_loss=1.349, generator_dur_loss=1.84, generator_adv_loss=1.864, generator_feat_match_loss=2.769, over 70.00 samples.], tot_loss[discriminator_loss=2.734, discriminator_real_loss=1.398, discriminator_fake_loss=1.336, generator_loss=27.11, generator_mel_loss=19.19, generator_kl_loss=1.302, generator_dur_loss=1.763, generator_adv_loss=1.89, generator_feat_match_loss=2.961, over 424.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 10:40:17,665 INFO [train.py:527] (2/6) Epoch 107, batch 56, global_batch_idx: 13200, batch size: 42, loss[discriminator_loss=2.703, discriminator_real_loss=1.301, discriminator_fake_loss=1.402, generator_loss=26.98, generator_mel_loss=18.83, generator_kl_loss=1.465, generator_dur_loss=1.725, generator_adv_loss=2.012, generator_feat_match_loss=2.947, over 42.00 samples.], tot_loss[discriminator_loss=2.75, discriminator_real_loss=1.398, discriminator_fake_loss=1.352, generator_loss=27.29, generator_mel_loss=19.2, generator_kl_loss=1.358, generator_dur_loss=1.758, generator_adv_loss=1.926, generator_feat_match_loss=3.048, over 3341.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 10:40:17,667 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 10:40:25,396 INFO [train.py:591] (2/6) Epoch 107, validation: discriminator_loss=2.792, discriminator_real_loss=1.582, discriminator_fake_loss=1.21, generator_loss=26.08, generator_mel_loss=18.85, generator_kl_loss=1.137, generator_dur_loss=1.792, generator_adv_loss=1.94, generator_feat_match_loss=2.356, over 100.00 samples.
2024-03-12 10:40:25,397 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 10:42:43,108 INFO [train.py:527] (2/6) Epoch 107, batch 106, global_batch_idx: 13250, batch size: 72, loss[discriminator_loss=2.773, discriminator_real_loss=1.362, discriminator_fake_loss=1.411, generator_loss=27.24, generator_mel_loss=19.01, generator_kl_loss=1.332, generator_dur_loss=1.816, generator_adv_loss=1.91, generator_feat_match_loss=3.168, over 72.00 samples.], tot_loss[discriminator_loss=2.746, discriminator_real_loss=1.394, discriminator_fake_loss=1.352, generator_loss=27.3, generator_mel_loss=19.23, generator_kl_loss=1.37, generator_dur_loss=1.754, generator_adv_loss=1.912, generator_feat_match_loss=3.036, over 6057.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 10:43:31,577 INFO [train.py:919] (2/6) Start epoch 108
2024-03-12 10:45:23,188 INFO [train.py:527] (2/6) Epoch 108, batch 32, global_batch_idx: 13300, batch size: 83, loss[discriminator_loss=2.654, discriminator_real_loss=1.208, discriminator_fake_loss=1.446, generator_loss=26.91, generator_mel_loss=18.87, generator_kl_loss=1.289, generator_dur_loss=1.891, generator_adv_loss=1.736, generator_feat_match_loss=3.121, over 83.00 samples.], tot_loss[discriminator_loss=2.723, discriminator_real_loss=1.377, discriminator_fake_loss=1.345, generator_loss=27.57, generator_mel_loss=19.31, generator_kl_loss=1.379, generator_dur_loss=1.78, generator_adv_loss=1.952, generator_feat_match_loss=3.144, over 1796.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 10:47:44,155 INFO [train.py:527] (2/6) Epoch 108, batch 82, global_batch_idx: 13350, batch size: 72, loss[discriminator_loss=2.711, discriminator_real_loss=1.4, discriminator_fake_loss=1.312, generator_loss=27.61, generator_mel_loss=19.36, generator_kl_loss=1.372, generator_dur_loss=1.803, generator_adv_loss=1.874, generator_feat_match_loss=3.2, over 72.00 samples.], tot_loss[discriminator_loss=2.74, discriminator_real_loss=1.389, discriminator_fake_loss=1.351, generator_loss=27.42, generator_mel_loss=19.24, generator_kl_loss=1.388, generator_dur_loss=1.775, generator_adv_loss=1.926, generator_feat_match_loss=3.084, over 4652.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 10:49:43,169 INFO [train.py:919] (2/6) Start epoch 109
2024-03-12 10:50:30,710 INFO [train.py:527] (2/6) Epoch 109, batch 8, global_batch_idx: 13400, batch size: 55, loss[discriminator_loss=2.755, discriminator_real_loss=1.595, discriminator_fake_loss=1.16, generator_loss=29.28, generator_mel_loss=20.15, generator_kl_loss=1.407, generator_dur_loss=1.727, generator_adv_loss=2.446, generator_feat_match_loss=3.547, over 55.00 samples.], tot_loss[discriminator_loss=2.825, discriminator_real_loss=1.41, discriminator_fake_loss=1.415, generator_loss=27.99, generator_mel_loss=19.41, generator_kl_loss=1.347, generator_dur_loss=1.776, generator_adv_loss=2.092, generator_feat_match_loss=3.359, over 550.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 10:50:30,712 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 10:50:38,652 INFO [train.py:591] (2/6) Epoch 109, validation: discriminator_loss=2.703, discriminator_real_loss=1.603, discriminator_fake_loss=1.1, generator_loss=27.09, generator_mel_loss=19.11, generator_kl_loss=1.1, generator_dur_loss=1.82, generator_adv_loss=2.323, generator_feat_match_loss=2.736, over 100.00 samples.
2024-03-12 10:50:38,671 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 10:53:02,597 INFO [train.py:527] (2/6) Epoch 109, batch 58, global_batch_idx: 13450, batch size: 59, loss[discriminator_loss=2.755, discriminator_real_loss=1.433, discriminator_fake_loss=1.322, generator_loss=27.77, generator_mel_loss=19.37, generator_kl_loss=1.476, generator_dur_loss=1.764, generator_adv_loss=2.127, generator_feat_match_loss=3.027, over 59.00 samples.], tot_loss[discriminator_loss=2.773, discriminator_real_loss=1.407, discriminator_fake_loss=1.366, generator_loss=27.37, generator_mel_loss=19.21, generator_kl_loss=1.369, generator_dur_loss=1.778, generator_adv_loss=1.969, generator_feat_match_loss=3.044, over 3476.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 10:55:21,061 INFO [train.py:527] (2/6) Epoch 109, batch 108, global_batch_idx: 13500, batch size: 47, loss[discriminator_loss=2.749, discriminator_real_loss=1.386, discriminator_fake_loss=1.363, generator_loss=27.45, generator_mel_loss=19.6, generator_kl_loss=1.343, generator_dur_loss=1.726, generator_adv_loss=1.765, generator_feat_match_loss=3.009, over 47.00 samples.], tot_loss[discriminator_loss=2.767, discriminator_real_loss=1.407, discriminator_fake_loss=1.36, generator_loss=27.23, generator_mel_loss=19.22, generator_kl_loss=1.367, generator_dur_loss=1.761, generator_adv_loss=1.924, generator_feat_match_loss=2.958, over 6250.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 10:56:05,170 INFO [train.py:919] (2/6) Start epoch 110
2024-03-12 10:58:07,983 INFO [train.py:527] (2/6) Epoch 110, batch 34, global_batch_idx: 13550, batch size: 31, loss[discriminator_loss=2.786, discriminator_real_loss=1.345, discriminator_fake_loss=1.441, generator_loss=27.01, generator_mel_loss=19.12, generator_kl_loss=1.594, generator_dur_loss=1.688, generator_adv_loss=1.937, generator_feat_match_loss=2.679, over 31.00 samples.], tot_loss[discriminator_loss=2.748, discriminator_real_loss=1.395, discriminator_fake_loss=1.353, generator_loss=27.19, generator_mel_loss=19.17, generator_kl_loss=1.402, generator_dur_loss=1.761, generator_adv_loss=1.886, generator_feat_match_loss=2.975, over 2145.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 11:00:32,756 INFO [train.py:527] (2/6) Epoch 110, batch 84, global_batch_idx: 13600, batch size: 80, loss[discriminator_loss=2.711, discriminator_real_loss=1.385, discriminator_fake_loss=1.326, generator_loss=26.94, generator_mel_loss=18.67, generator_kl_loss=1.417, generator_dur_loss=1.861, generator_adv_loss=1.961, generator_feat_match_loss=3.038, over 80.00 samples.], tot_loss[discriminator_loss=2.751, discriminator_real_loss=1.398, discriminator_fake_loss=1.353, generator_loss=27.18, generator_mel_loss=19.15, generator_kl_loss=1.396, generator_dur_loss=1.769, generator_adv_loss=1.895, generator_feat_match_loss=2.975, over 4893.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 11:00:32,758 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 11:00:41,512 INFO [train.py:591] (2/6) Epoch 110, validation: discriminator_loss=2.734, discriminator_real_loss=1.415, discriminator_fake_loss=1.319, generator_loss=26.16, generator_mel_loss=19.01, generator_kl_loss=1.163, generator_dur_loss=1.823, generator_adv_loss=1.86, generator_feat_match_loss=2.299, over 100.00 samples.
2024-03-12 11:00:41,513 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 11:02:28,778 INFO [train.py:919] (2/6) Start epoch 111
2024-03-12 11:03:24,302 INFO [train.py:527] (2/6) Epoch 111, batch 10, global_batch_idx: 13650, batch size: 61, loss[discriminator_loss=2.714, discriminator_real_loss=1.337, discriminator_fake_loss=1.377, generator_loss=27, generator_mel_loss=18.81, generator_kl_loss=1.403, generator_dur_loss=1.703, generator_adv_loss=1.956, generator_feat_match_loss=3.126, over 61.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.37, discriminator_fake_loss=1.355, generator_loss=27.26, generator_mel_loss=19.07, generator_kl_loss=1.373, generator_dur_loss=1.78, generator_adv_loss=1.912, generator_feat_match_loss=3.126, over 748.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 11:05:46,984 INFO [train.py:527] (2/6) Epoch 111, batch 60, global_batch_idx: 13700, batch size: 48, loss[discriminator_loss=2.742, discriminator_real_loss=1.424, discriminator_fake_loss=1.318, generator_loss=27.84, generator_mel_loss=19.7, generator_kl_loss=1.468, generator_dur_loss=1.722, generator_adv_loss=1.907, generator_feat_match_loss=3.035, over 48.00 samples.], tot_loss[discriminator_loss=2.733, discriminator_real_loss=1.388, discriminator_fake_loss=1.344, generator_loss=27.44, generator_mel_loss=19.25, generator_kl_loss=1.384, generator_dur_loss=1.757, generator_adv_loss=1.915, generator_feat_match_loss=3.136, over 3758.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 11:08:05,578 INFO [train.py:527] (2/6) Epoch 111, batch 110, global_batch_idx: 13750, batch size: 58, loss[discriminator_loss=2.822, discriminator_real_loss=1.412, discriminator_fake_loss=1.411, generator_loss=26.44, generator_mel_loss=18.97, generator_kl_loss=1.358, generator_dur_loss=1.754, generator_adv_loss=1.767, generator_feat_match_loss=2.593, over 58.00 samples.], tot_loss[discriminator_loss=2.745, discriminator_real_loss=1.388, discriminator_fake_loss=1.357, generator_loss=27.43, generator_mel_loss=19.23, generator_kl_loss=1.394, generator_dur_loss=1.759, generator_adv_loss=1.926, generator_feat_match_loss=3.119, over 6349.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 11:08:44,705 INFO [train.py:919] (2/6) Start epoch 112
2024-03-12 11:10:51,417 INFO [train.py:527] (2/6) Epoch 112, batch 36, global_batch_idx: 13800, batch size: 66, loss[discriminator_loss=2.784, discriminator_real_loss=1.439, discriminator_fake_loss=1.346, generator_loss=27.15, generator_mel_loss=19.35, generator_kl_loss=1.418, generator_dur_loss=1.765, generator_adv_loss=1.841, generator_feat_match_loss=2.777, over 66.00 samples.], tot_loss[discriminator_loss=2.743, discriminator_real_loss=1.393, discriminator_fake_loss=1.35, generator_loss=27.33, generator_mel_loss=19.15, generator_kl_loss=1.387, generator_dur_loss=1.808, generator_adv_loss=1.906, generator_feat_match_loss=3.076, over 2230.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 11:10:51,419 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 11:10:59,110 INFO [train.py:591] (2/6) Epoch 112, validation: discriminator_loss=2.8, discriminator_real_loss=1.409, discriminator_fake_loss=1.391, generator_loss=26.38, generator_mel_loss=19.18, generator_kl_loss=1.216, generator_dur_loss=1.816, generator_adv_loss=1.727, generator_feat_match_loss=2.443, over 100.00 samples.
2024-03-12 11:10:59,112 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 11:13:21,190 INFO [train.py:527] (2/6) Epoch 112, batch 86, global_batch_idx: 13850, batch size: 59, loss[discriminator_loss=2.676, discriminator_real_loss=1.379, discriminator_fake_loss=1.296, generator_loss=27.8, generator_mel_loss=19.46, generator_kl_loss=1.245, generator_dur_loss=1.718, generator_adv_loss=2.057, generator_feat_match_loss=3.318, over 59.00 samples.], tot_loss[discriminator_loss=2.746, discriminator_real_loss=1.393, discriminator_fake_loss=1.354, generator_loss=27.31, generator_mel_loss=19.18, generator_kl_loss=1.375, generator_dur_loss=1.789, generator_adv_loss=1.902, generator_feat_match_loss=3.063, over 5278.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 11:15:04,563 INFO [train.py:919] (2/6) Start epoch 113
2024-03-12 11:16:04,159 INFO [train.py:527] (2/6) Epoch 113, batch 12, global_batch_idx: 13900, batch size: 95, loss[discriminator_loss=2.577, discriminator_real_loss=1.288, discriminator_fake_loss=1.289, generator_loss=27.97, generator_mel_loss=19.1, generator_kl_loss=1.298, generator_dur_loss=1.919, generator_adv_loss=2.041, generator_feat_match_loss=3.609, over 95.00 samples.], tot_loss[discriminator_loss=2.711, discriminator_real_loss=1.368, discriminator_fake_loss=1.343, generator_loss=27.82, generator_mel_loss=19.34, generator_kl_loss=1.391, generator_dur_loss=1.767, generator_adv_loss=2.008, generator_feat_match_loss=3.315, over 755.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 11:18:23,917 INFO [train.py:527] (2/6) Epoch 113, batch 62, global_batch_idx: 13950, batch size: 52, loss[discriminator_loss=2.696, discriminator_real_loss=1.408, discriminator_fake_loss=1.289, generator_loss=27.63, generator_mel_loss=19.58, generator_kl_loss=1.337, generator_dur_loss=1.675, generator_adv_loss=1.898, generator_feat_match_loss=3.144, over 52.00 samples.], tot_loss[discriminator_loss=2.75, discriminator_real_loss=1.401, discriminator_fake_loss=1.35, generator_loss=27.34, generator_mel_loss=19.16, generator_kl_loss=1.394, generator_dur_loss=1.764, generator_adv_loss=1.959, generator_feat_match_loss=3.068, over 3440.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 11:20:48,966 INFO [train.py:527] (2/6) Epoch 113, batch 112, global_batch_idx: 14000, batch size: 48, loss[discriminator_loss=2.757, discriminator_real_loss=1.398, discriminator_fake_loss=1.358, generator_loss=28, generator_mel_loss=19.4, generator_kl_loss=1.542, generator_dur_loss=1.679, generator_adv_loss=1.849, generator_feat_match_loss=3.532, over 48.00 samples.], tot_loss[discriminator_loss=2.745, discriminator_real_loss=1.396, discriminator_fake_loss=1.35, generator_loss=27.29, generator_mel_loss=19.1, generator_kl_loss=1.392, generator_dur_loss=1.776, generator_adv_loss=1.929, generator_feat_match_loss=3.09, over 6284.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 11:20:48,967 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 11:20:57,871 INFO [train.py:591] (2/6) Epoch 113, validation: discriminator_loss=2.751, discriminator_real_loss=1.385, discriminator_fake_loss=1.366, generator_loss=25.82, generator_mel_loss=18.77, generator_kl_loss=1.134, generator_dur_loss=1.803, generator_adv_loss=1.791, generator_feat_match_loss=2.326, over 100.00 samples.
2024-03-12 11:20:57,873 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 11:21:28,912 INFO [train.py:919] (2/6) Start epoch 114
2024-03-12 11:23:41,747 INFO [train.py:527] (2/6) Epoch 114, batch 38, global_batch_idx: 14050, batch size: 31, loss[discriminator_loss=2.715, discriminator_real_loss=1.312, discriminator_fake_loss=1.404, generator_loss=27.61, generator_mel_loss=19.21, generator_kl_loss=1.728, generator_dur_loss=1.583, generator_adv_loss=1.821, generator_feat_match_loss=3.275, over 31.00 samples.], tot_loss[discriminator_loss=2.727, discriminator_real_loss=1.383, discriminator_fake_loss=1.344, generator_loss=27.36, generator_mel_loss=19.21, generator_kl_loss=1.436, generator_dur_loss=1.726, generator_adv_loss=1.903, generator_feat_match_loss=3.091, over 1990.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 11:26:06,667 INFO [train.py:527] (2/6) Epoch 114, batch 88, global_batch_idx: 14100, batch size: 48, loss[discriminator_loss=2.736, discriminator_real_loss=1.383, discriminator_fake_loss=1.353, generator_loss=28.11, generator_mel_loss=19.68, generator_kl_loss=1.449, generator_dur_loss=1.718, generator_adv_loss=2.078, generator_feat_match_loss=3.187, over 48.00 samples.], tot_loss[discriminator_loss=2.736, discriminator_real_loss=1.396, discriminator_fake_loss=1.34, generator_loss=27.38, generator_mel_loss=19.2, generator_kl_loss=1.402, generator_dur_loss=1.746, generator_adv_loss=1.919, generator_feat_match_loss=3.111, over 5083.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 11:27:46,817 INFO [train.py:919] (2/6) Start epoch 115
2024-03-12 11:28:53,650 INFO [train.py:527] (2/6) Epoch 115, batch 14, global_batch_idx: 14150, batch size: 96, loss[discriminator_loss=2.756, discriminator_real_loss=1.336, discriminator_fake_loss=1.42, generator_loss=27.5, generator_mel_loss=18.82, generator_kl_loss=1.15, generator_dur_loss=1.885, generator_adv_loss=2.143, generator_feat_match_loss=3.505, over 96.00 samples.], tot_loss[discriminator_loss=2.728, discriminator_real_loss=1.366, discriminator_fake_loss=1.361, generator_loss=27.29, generator_mel_loss=19.06, generator_kl_loss=1.317, generator_dur_loss=1.832, generator_adv_loss=1.945, generator_feat_match_loss=3.138, over 1056.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 11:31:17,712 INFO [train.py:527] (2/6) Epoch 115, batch 64, global_batch_idx: 14200, batch size: 80, loss[discriminator_loss=2.765, discriminator_real_loss=1.436, discriminator_fake_loss=1.329, generator_loss=27.03, generator_mel_loss=18.89, generator_kl_loss=1.217, generator_dur_loss=1.811, generator_adv_loss=1.867, generator_feat_match_loss=3.237, over 80.00 samples.], tot_loss[discriminator_loss=2.737, discriminator_real_loss=1.388, discriminator_fake_loss=1.349, generator_loss=27.35, generator_mel_loss=19.1, generator_kl_loss=1.362, generator_dur_loss=1.79, generator_adv_loss=1.962, generator_feat_match_loss=3.136, over 3960.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 11:31:17,714 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 11:31:25,538 INFO [train.py:591] (2/6) Epoch 115, validation: discriminator_loss=2.747, discriminator_real_loss=1.47, discriminator_fake_loss=1.277, generator_loss=26.49, generator_mel_loss=19.07, generator_kl_loss=1.219, generator_dur_loss=1.805, generator_adv_loss=1.859, generator_feat_match_loss=2.54, over 100.00 samples.
2024-03-12 11:31:25,540 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 11:33:42,937 INFO [train.py:527] (2/6) Epoch 115, batch 114, global_batch_idx: 14250, batch size: 48, loss[discriminator_loss=2.737, discriminator_real_loss=1.392, discriminator_fake_loss=1.345, generator_loss=27.74, generator_mel_loss=19.7, generator_kl_loss=1.589, generator_dur_loss=1.645, generator_adv_loss=1.94, generator_feat_match_loss=2.873, over 48.00 samples.], tot_loss[discriminator_loss=2.737, discriminator_real_loss=1.388, discriminator_fake_loss=1.349, generator_loss=27.42, generator_mel_loss=19.18, generator_kl_loss=1.387, generator_dur_loss=1.784, generator_adv_loss=1.94, generator_feat_match_loss=3.129, over 6681.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 11:34:08,799 INFO [train.py:919] (2/6) Start epoch 116
2024-03-12 11:36:27,906 INFO [train.py:527] (2/6) Epoch 116, batch 40, global_batch_idx: 14300, batch size: 70, loss[discriminator_loss=2.785, discriminator_real_loss=1.393, discriminator_fake_loss=1.391, generator_loss=27.63, generator_mel_loss=19.71, generator_kl_loss=1.46, generator_dur_loss=1.8, generator_adv_loss=1.898, generator_feat_match_loss=2.756, over 70.00 samples.], tot_loss[discriminator_loss=2.739, discriminator_real_loss=1.392, discriminator_fake_loss=1.347, generator_loss=27.31, generator_mel_loss=19.17, generator_kl_loss=1.414, generator_dur_loss=1.772, generator_adv_loss=1.906, generator_feat_match_loss=3.048, over 2294.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 11:38:53,213 INFO [train.py:527] (2/6) Epoch 116, batch 90, global_batch_idx: 14350, batch size: 56, loss[discriminator_loss=2.744, discriminator_real_loss=1.396, discriminator_fake_loss=1.347, generator_loss=26.51, generator_mel_loss=18.61, generator_kl_loss=1.316, generator_dur_loss=1.736, generator_adv_loss=2.049, generator_feat_match_loss=2.794, over 56.00 samples.], tot_loss[discriminator_loss=2.748, discriminator_real_loss=1.396, discriminator_fake_loss=1.352, generator_loss=27.19, generator_mel_loss=19.11, generator_kl_loss=1.395, generator_dur_loss=1.781, generator_adv_loss=1.898, generator_feat_match_loss=3.013, over 5321.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 11:40:23,616 INFO [train.py:919] (2/6) Start epoch 117
2024-03-12 11:41:34,153 INFO [train.py:527] (2/6) Epoch 117, batch 16, global_batch_idx: 14400, batch size: 77, loss[discriminator_loss=2.709, discriminator_real_loss=1.375, discriminator_fake_loss=1.334, generator_loss=26.5, generator_mel_loss=18.54, generator_kl_loss=1.319, generator_dur_loss=1.853, generator_adv_loss=1.94, generator_feat_match_loss=2.846, over 77.00 samples.], tot_loss[discriminator_loss=2.748, discriminator_real_loss=1.399, discriminator_fake_loss=1.349, generator_loss=27.32, generator_mel_loss=19.21, generator_kl_loss=1.373, generator_dur_loss=1.776, generator_adv_loss=1.913, generator_feat_match_loss=3.048, over 901.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 11:41:34,154 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 11:41:42,045 INFO [train.py:591] (2/6) Epoch 117, validation: discriminator_loss=2.698, discriminator_real_loss=1.388, discriminator_fake_loss=1.31, generator_loss=26.84, generator_mel_loss=19.33, generator_kl_loss=1.169, generator_dur_loss=1.842, generator_adv_loss=1.867, generator_feat_match_loss=2.631, over 100.00 samples.
2024-03-12 11:41:42,046 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 11:44:05,294 INFO [train.py:527] (2/6) Epoch 117, batch 66, global_batch_idx: 14450, batch size: 45, loss[discriminator_loss=2.695, discriminator_real_loss=1.29, discriminator_fake_loss=1.405, generator_loss=27.81, generator_mel_loss=19.57, generator_kl_loss=1.407, generator_dur_loss=1.673, generator_adv_loss=1.966, generator_feat_match_loss=3.188, over 45.00 samples.], tot_loss[discriminator_loss=2.749, discriminator_real_loss=1.391, discriminator_fake_loss=1.357, generator_loss=27.3, generator_mel_loss=19.17, generator_kl_loss=1.38, generator_dur_loss=1.764, generator_adv_loss=1.907, generator_feat_match_loss=3.074, over 3893.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 11:46:21,852 INFO [train.py:527] (2/6) Epoch 117, batch 116, global_batch_idx: 14500, batch size: 36, loss[discriminator_loss=2.665, discriminator_real_loss=1.22, discriminator_fake_loss=1.445, generator_loss=29, generator_mel_loss=20.03, generator_kl_loss=1.688, generator_dur_loss=1.69, generator_adv_loss=1.921, generator_feat_match_loss=3.671, over 36.00 samples.], tot_loss[discriminator_loss=2.752, discriminator_real_loss=1.393, discriminator_fake_loss=1.359, generator_loss=27.34, generator_mel_loss=19.18, generator_kl_loss=1.402, generator_dur_loss=1.755, generator_adv_loss=1.912, generator_feat_match_loss=3.085, over 6530.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 11:46:41,399 INFO [train.py:919] (2/6) Start epoch 118
2024-03-12 11:49:04,577 INFO [train.py:527] (2/6) Epoch 118, batch 42, global_batch_idx: 14550, batch size: 74, loss[discriminator_loss=2.743, discriminator_real_loss=1.426, discriminator_fake_loss=1.317, generator_loss=27.05, generator_mel_loss=19.03, generator_kl_loss=1.518, generator_dur_loss=1.834, generator_adv_loss=1.735, generator_feat_match_loss=2.931, over 74.00 samples.], tot_loss[discriminator_loss=2.756, discriminator_real_loss=1.401, discriminator_fake_loss=1.355, generator_loss=27.18, generator_mel_loss=19.14, generator_kl_loss=1.403, generator_dur_loss=1.748, generator_adv_loss=1.879, generator_feat_match_loss=3.009, over 2305.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 11:51:25,264 INFO [train.py:527] (2/6) Epoch 118, batch 92, global_batch_idx: 14600, batch size: 39, loss[discriminator_loss=2.754, discriminator_real_loss=1.386, discriminator_fake_loss=1.368, generator_loss=27.76, generator_mel_loss=19.36, generator_kl_loss=1.579, generator_dur_loss=1.691, generator_adv_loss=1.878, generator_feat_match_loss=3.257, over 39.00 samples.], tot_loss[discriminator_loss=2.756, discriminator_real_loss=1.398, discriminator_fake_loss=1.357, generator_loss=27.16, generator_mel_loss=19.08, generator_kl_loss=1.393, generator_dur_loss=1.764, generator_adv_loss=1.889, generator_feat_match_loss=3.038, over 5211.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 11:51:25,266 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 11:51:33,693 INFO [train.py:591] (2/6) Epoch 118, validation: discriminator_loss=2.765, discriminator_real_loss=1.428, discriminator_fake_loss=1.338, generator_loss=26.6, generator_mel_loss=19.28, generator_kl_loss=1.279, generator_dur_loss=1.827, generator_adv_loss=1.81, generator_feat_match_loss=2.411, over 100.00 samples.
2024-03-12 11:51:33,694 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 11:53:02,225 INFO [train.py:919] (2/6) Start epoch 119
2024-03-12 11:54:18,550 INFO [train.py:527] (2/6) Epoch 119, batch 18, global_batch_idx: 14650, batch size: 72, loss[discriminator_loss=2.705, discriminator_real_loss=1.306, discriminator_fake_loss=1.398, generator_loss=26.53, generator_mel_loss=18.68, generator_kl_loss=1.285, generator_dur_loss=1.76, generator_adv_loss=1.815, generator_feat_match_loss=2.982, over 72.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.365, discriminator_fake_loss=1.361, generator_loss=27.07, generator_mel_loss=18.95, generator_kl_loss=1.33, generator_dur_loss=1.768, generator_adv_loss=1.91, generator_feat_match_loss=3.107, over 1156.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 11:56:42,176 INFO [train.py:527] (2/6) Epoch 119, batch 68, global_batch_idx: 14700, batch size: 42, loss[discriminator_loss=2.789, discriminator_real_loss=1.426, discriminator_fake_loss=1.362, generator_loss=27.05, generator_mel_loss=18.97, generator_kl_loss=1.481, generator_dur_loss=1.667, generator_adv_loss=1.934, generator_feat_match_loss=2.994, over 42.00 samples.], tot_loss[discriminator_loss=2.747, discriminator_real_loss=1.389, discriminator_fake_loss=1.358, generator_loss=27.17, generator_mel_loss=19.06, generator_kl_loss=1.392, generator_dur_loss=1.753, generator_adv_loss=1.909, generator_feat_match_loss=3.057, over 4048.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 11:58:56,905 INFO [train.py:527] (2/6) Epoch 119, batch 118, global_batch_idx: 14750, batch size: 74, loss[discriminator_loss=2.715, discriminator_real_loss=1.268, discriminator_fake_loss=1.447, generator_loss=27.66, generator_mel_loss=19.47, generator_kl_loss=1.329, generator_dur_loss=1.798, generator_adv_loss=1.907, generator_feat_match_loss=3.16, over 74.00 samples.], tot_loss[discriminator_loss=2.751, discriminator_real_loss=1.39, discriminator_fake_loss=1.361, generator_loss=27.18, generator_mel_loss=19.06, generator_kl_loss=1.39, generator_dur_loss=1.76, generator_adv_loss=1.897, generator_feat_match_loss=3.068, over 6883.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 11:59:12,644 INFO [train.py:919] (2/6) Start epoch 120
2024-03-12 12:01:37,977 INFO [train.py:527] (2/6) Epoch 120, batch 44, global_batch_idx: 14800, batch size: 88, loss[discriminator_loss=2.716, discriminator_real_loss=1.398, discriminator_fake_loss=1.318, generator_loss=27.1, generator_mel_loss=19.07, generator_kl_loss=1.274, generator_dur_loss=1.871, generator_adv_loss=1.899, generator_feat_match_loss=2.984, over 88.00 samples.], tot_loss[discriminator_loss=2.746, discriminator_real_loss=1.399, discriminator_fake_loss=1.347, generator_loss=27.39, generator_mel_loss=19.17, generator_kl_loss=1.415, generator_dur_loss=1.764, generator_adv_loss=1.918, generator_feat_match_loss=3.123, over 2571.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 12:01:37,978 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 12:01:45,879 INFO [train.py:591] (2/6) Epoch 120, validation: discriminator_loss=2.76, discriminator_real_loss=1.43, discriminator_fake_loss=1.33, generator_loss=26.73, generator_mel_loss=19.22, generator_kl_loss=1.226, generator_dur_loss=1.797, generator_adv_loss=1.813, generator_feat_match_loss=2.683, over 100.00 samples.
2024-03-12 12:01:45,880 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 12:04:04,611 INFO [train.py:527] (2/6) Epoch 120, batch 94, global_batch_idx: 14850, batch size: 25, loss[discriminator_loss=2.852, discriminator_real_loss=1.698, discriminator_fake_loss=1.154, generator_loss=26.63, generator_mel_loss=19.21, generator_kl_loss=1.704, generator_dur_loss=1.559, generator_adv_loss=1.56, generator_feat_match_loss=2.595, over 25.00 samples.], tot_loss[discriminator_loss=2.742, discriminator_real_loss=1.389, discriminator_fake_loss=1.354, generator_loss=27.31, generator_mel_loss=19.1, generator_kl_loss=1.412, generator_dur_loss=1.758, generator_adv_loss=1.908, generator_feat_match_loss=3.129, over 5482.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 12:05:27,257 INFO [train.py:919] (2/6) Start epoch 121
2024-03-12 12:06:45,411 INFO [train.py:527] (2/6) Epoch 121, batch 20, global_batch_idx: 14900, batch size: 15, loss[discriminator_loss=2.77, discriminator_real_loss=1.385, discriminator_fake_loss=1.385, generator_loss=28.47, generator_mel_loss=19.96, generator_kl_loss=1.798, generator_dur_loss=1.612, generator_adv_loss=1.897, generator_feat_match_loss=3.208, over 15.00 samples.], tot_loss[discriminator_loss=2.77, discriminator_real_loss=1.4, discriminator_fake_loss=1.369, generator_loss=27.14, generator_mel_loss=19, generator_kl_loss=1.449, generator_dur_loss=1.708, generator_adv_loss=1.939, generator_feat_match_loss=3.036, over 1008.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 12:09:06,772 INFO [train.py:527] (2/6) Epoch 121, batch 70, global_batch_idx: 14950, batch size: 44, loss[discriminator_loss=2.751, discriminator_real_loss=1.271, discriminator_fake_loss=1.48, generator_loss=27.98, generator_mel_loss=19.54, generator_kl_loss=1.611, generator_dur_loss=1.715, generator_adv_loss=1.803, generator_feat_match_loss=3.312, over 44.00 samples.], tot_loss[discriminator_loss=2.753, discriminator_real_loss=1.397, discriminator_fake_loss=1.357, generator_loss=27.18, generator_mel_loss=19.05, generator_kl_loss=1.423, generator_dur_loss=1.75, generator_adv_loss=1.909, generator_feat_match_loss=3.056, over 3717.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 12:11:25,476 INFO [train.py:527] (2/6) Epoch 121, batch 120, global_batch_idx: 15000, batch size: 50, loss[discriminator_loss=2.701, discriminator_real_loss=1.307, discriminator_fake_loss=1.394, generator_loss=27.86, generator_mel_loss=19.21, generator_kl_loss=1.427, generator_dur_loss=1.734, generator_adv_loss=2.005, generator_feat_match_loss=3.476, over 50.00 samples.], tot_loss[discriminator_loss=2.745, discriminator_real_loss=1.393, discriminator_fake_loss=1.352, generator_loss=27.17, generator_mel_loss=19.01, generator_kl_loss=1.406, generator_dur_loss=1.751, generator_adv_loss=1.911, generator_feat_match_loss=3.091, over 6648.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 12:11:25,478 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 12:11:34,416 INFO [train.py:591] (2/6) Epoch 121, validation: discriminator_loss=2.75, discriminator_real_loss=1.455, discriminator_fake_loss=1.294, generator_loss=26.64, generator_mel_loss=19.12, generator_kl_loss=1.093, generator_dur_loss=1.827, generator_adv_loss=1.899, generator_feat_match_loss=2.698, over 100.00 samples.
2024-03-12 12:11:34,418 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 12:11:44,136 INFO [train.py:919] (2/6) Start epoch 122
2024-03-12 12:14:17,583 INFO [train.py:527] (2/6) Epoch 122, batch 46, global_batch_idx: 15050, batch size: 31, loss[discriminator_loss=2.636, discriminator_real_loss=1.347, discriminator_fake_loss=1.289, generator_loss=28.71, generator_mel_loss=19.84, generator_kl_loss=1.443, generator_dur_loss=1.644, generator_adv_loss=2.16, generator_feat_match_loss=3.621, over 31.00 samples.], tot_loss[discriminator_loss=2.754, discriminator_real_loss=1.382, discriminator_fake_loss=1.372, generator_loss=27.19, generator_mel_loss=18.96, generator_kl_loss=1.385, generator_dur_loss=1.765, generator_adv_loss=1.924, generator_feat_match_loss=3.159, over 2894.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 12:16:36,050 INFO [train.py:527] (2/6) Epoch 122, batch 96, global_batch_idx: 15100, batch size: 14, loss[discriminator_loss=2.666, discriminator_real_loss=1.362, discriminator_fake_loss=1.303, generator_loss=27.75, generator_mel_loss=19.54, generator_kl_loss=1.583, generator_dur_loss=1.616, generator_adv_loss=1.849, generator_feat_match_loss=3.161, over 14.00 samples.], tot_loss[discriminator_loss=2.748, discriminator_real_loss=1.39, discriminator_fake_loss=1.359, generator_loss=27.2, generator_mel_loss=19, generator_kl_loss=1.387, generator_dur_loss=1.767, generator_adv_loss=1.92, generator_feat_match_loss=3.128, over 5750.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 12:17:48,314 INFO [train.py:919] (2/6) Start epoch 123
2024-03-12 12:19:14,256 INFO [train.py:527] (2/6) Epoch 123, batch 22, global_batch_idx: 15150, batch size: 44, loss[discriminator_loss=2.726, discriminator_real_loss=1.27, discriminator_fake_loss=1.456, generator_loss=29.18, generator_mel_loss=20.51, generator_kl_loss=1.519, generator_dur_loss=1.658, generator_adv_loss=2.014, generator_feat_match_loss=3.476, over 44.00 samples.], tot_loss[discriminator_loss=2.749, discriminator_real_loss=1.383, discriminator_fake_loss=1.366, generator_loss=26.85, generator_mel_loss=18.85, generator_kl_loss=1.395, generator_dur_loss=1.753, generator_adv_loss=1.874, generator_feat_match_loss=2.974, over 1259.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 12:21:34,505 INFO [train.py:527] (2/6) Epoch 123, batch 72, global_batch_idx: 15200, batch size: 16, loss[discriminator_loss=2.715, discriminator_real_loss=1.405, discriminator_fake_loss=1.31, generator_loss=28.82, generator_mel_loss=20.13, generator_kl_loss=1.694, generator_dur_loss=1.615, generator_adv_loss=1.884, generator_feat_match_loss=3.494, over 16.00 samples.], tot_loss[discriminator_loss=2.755, discriminator_real_loss=1.394, discriminator_fake_loss=1.361, generator_loss=27.13, generator_mel_loss=19, generator_kl_loss=1.383, generator_dur_loss=1.771, generator_adv_loss=1.895, generator_feat_match_loss=3.083, over 4308.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 12:21:34,507 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 12:21:42,582 INFO [train.py:591] (2/6) Epoch 123, validation: discriminator_loss=2.71, discriminator_real_loss=1.427, discriminator_fake_loss=1.282, generator_loss=26.89, generator_mel_loss=19.56, generator_kl_loss=1.188, generator_dur_loss=1.806, generator_adv_loss=1.883, generator_feat_match_loss=2.453, over 100.00 samples.
2024-03-12 12:21:42,583 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 12:24:00,644 INFO [train.py:527] (2/6) Epoch 123, batch 122, global_batch_idx: 15250, batch size: 58, loss[discriminator_loss=2.773, discriminator_real_loss=1.339, discriminator_fake_loss=1.434, generator_loss=27.34, generator_mel_loss=18.84, generator_kl_loss=1.415, generator_dur_loss=1.758, generator_adv_loss=1.873, generator_feat_match_loss=3.457, over 58.00 samples.], tot_loss[discriminator_loss=2.747, discriminator_real_loss=1.388, discriminator_fake_loss=1.359, generator_loss=27.21, generator_mel_loss=19.04, generator_kl_loss=1.399, generator_dur_loss=1.763, generator_adv_loss=1.901, generator_feat_match_loss=3.109, over 6822.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 12:24:05,513 INFO [train.py:919] (2/6) Start epoch 124
2024-03-12 12:26:41,470 INFO [train.py:527] (2/6) Epoch 124, batch 48, global_batch_idx: 15300, batch size: 56, loss[discriminator_loss=2.759, discriminator_real_loss=1.475, discriminator_fake_loss=1.285, generator_loss=26.87, generator_mel_loss=18.88, generator_kl_loss=1.26, generator_dur_loss=1.774, generator_adv_loss=2.136, generator_feat_match_loss=2.828, over 56.00 samples.], tot_loss[discriminator_loss=2.745, discriminator_real_loss=1.402, discriminator_fake_loss=1.343, generator_loss=27.5, generator_mel_loss=19.07, generator_kl_loss=1.4, generator_dur_loss=1.779, generator_adv_loss=1.979, generator_feat_match_loss=3.269, over 2699.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 12:28:58,143 INFO [train.py:527] (2/6) Epoch 124, batch 98, global_batch_idx: 15350, batch size: 77, loss[discriminator_loss=2.779, discriminator_real_loss=1.482, discriminator_fake_loss=1.297, generator_loss=26.5, generator_mel_loss=18.54, generator_kl_loss=1.265, generator_dur_loss=1.874, generator_adv_loss=1.951, generator_feat_match_loss=2.87, over 77.00 samples.], tot_loss[discriminator_loss=2.753, discriminator_real_loss=1.402, discriminator_fake_loss=1.35, generator_loss=27.29, generator_mel_loss=19.02, generator_kl_loss=1.398, generator_dur_loss=1.767, generator_adv_loss=1.944, generator_feat_match_loss=3.168, over 5265.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 12:30:10,246 INFO [train.py:919] (2/6) Start epoch 125
2024-03-12 12:31:40,996 INFO [train.py:527] (2/6) Epoch 125, batch 24, global_batch_idx: 15400, batch size: 44, loss[discriminator_loss=2.691, discriminator_real_loss=1.389, discriminator_fake_loss=1.302, generator_loss=27.3, generator_mel_loss=19.04, generator_kl_loss=1.405, generator_dur_loss=1.754, generator_adv_loss=1.776, generator_feat_match_loss=3.334, over 44.00 samples.], tot_loss[discriminator_loss=2.745, discriminator_real_loss=1.399, discriminator_fake_loss=1.346, generator_loss=27.18, generator_mel_loss=19.02, generator_kl_loss=1.396, generator_dur_loss=1.799, generator_adv_loss=1.88, generator_feat_match_loss=3.084, over 1380.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 12:31:40,998 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 12:31:49,014 INFO [train.py:591] (2/6) Epoch 125, validation: discriminator_loss=2.708, discriminator_real_loss=1.334, discriminator_fake_loss=1.374, generator_loss=25.91, generator_mel_loss=18.78, generator_kl_loss=1.215, generator_dur_loss=1.829, generator_adv_loss=1.705, generator_feat_match_loss=2.374, over 100.00 samples.
2024-03-12 12:31:49,015 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 12:34:10,603 INFO [train.py:527] (2/6) Epoch 125, batch 74, global_batch_idx: 15450, batch size: 64, loss[discriminator_loss=2.696, discriminator_real_loss=1.359, discriminator_fake_loss=1.337, generator_loss=26.85, generator_mel_loss=18.46, generator_kl_loss=1.36, generator_dur_loss=1.754, generator_adv_loss=2.094, generator_feat_match_loss=3.187, over 64.00 samples.], tot_loss[discriminator_loss=2.743, discriminator_real_loss=1.396, discriminator_fake_loss=1.346, generator_loss=27.19, generator_mel_loss=19.02, generator_kl_loss=1.4, generator_dur_loss=1.767, generator_adv_loss=1.896, generator_feat_match_loss=3.106, over 4171.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 12:36:26,751 INFO [train.py:919] (2/6) Start epoch 126
2024-03-12 12:36:50,425 INFO [train.py:527] (2/6) Epoch 126, batch 0, global_batch_idx: 15500, batch size: 56, loss[discriminator_loss=2.746, discriminator_real_loss=1.403, discriminator_fake_loss=1.343, generator_loss=28.09, generator_mel_loss=19.74, generator_kl_loss=1.5, generator_dur_loss=1.641, generator_adv_loss=1.888, generator_feat_match_loss=3.32, over 56.00 samples.], tot_loss[discriminator_loss=2.746, discriminator_real_loss=1.403, discriminator_fake_loss=1.343, generator_loss=28.09, generator_mel_loss=19.74, generator_kl_loss=1.5, generator_dur_loss=1.641, generator_adv_loss=1.888, generator_feat_match_loss=3.32, over 56.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 12:39:10,053 INFO [train.py:527] (2/6) Epoch 126, batch 50, global_batch_idx: 15550, batch size: 61, loss[discriminator_loss=2.799, discriminator_real_loss=1.418, discriminator_fake_loss=1.38, generator_loss=26.49, generator_mel_loss=18.75, generator_kl_loss=1.357, generator_dur_loss=1.746, generator_adv_loss=1.773, generator_feat_match_loss=2.863, over 61.00 samples.], tot_loss[discriminator_loss=2.754, discriminator_real_loss=1.399, discriminator_fake_loss=1.355, generator_loss=27.11, generator_mel_loss=18.96, generator_kl_loss=1.379, generator_dur_loss=1.729, generator_adv_loss=1.898, generator_feat_match_loss=3.15, over 3081.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 12:41:27,692 INFO [train.py:527] (2/6) Epoch 126, batch 100, global_batch_idx: 15600, batch size: 70, loss[discriminator_loss=2.777, discriminator_real_loss=1.275, discriminator_fake_loss=1.502, generator_loss=27.6, generator_mel_loss=19.15, generator_kl_loss=1.339, generator_dur_loss=1.836, generator_adv_loss=2.159, generator_feat_match_loss=3.115, over 70.00 samples.], tot_loss[discriminator_loss=2.75, discriminator_real_loss=1.395, discriminator_fake_loss=1.355, generator_loss=27.15, generator_mel_loss=18.97, generator_kl_loss=1.384, generator_dur_loss=1.751, generator_adv_loss=1.908, generator_feat_match_loss=3.137, over 5835.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 12:41:27,693 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 12:41:36,597 INFO [train.py:591] (2/6) Epoch 126, validation: discriminator_loss=2.815, discriminator_real_loss=1.61, discriminator_fake_loss=1.205, generator_loss=25.88, generator_mel_loss=18.47, generator_kl_loss=1.162, generator_dur_loss=1.825, generator_adv_loss=2.079, generator_feat_match_loss=2.346, over 100.00 samples.
2024-03-12 12:41:36,598 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 12:42:40,890 INFO [train.py:919] (2/6) Start epoch 127
2024-03-12 12:44:17,932 INFO [train.py:527] (2/6) Epoch 127, batch 26, global_batch_idx: 15650, batch size: 53, loss[discriminator_loss=2.771, discriminator_real_loss=1.454, discriminator_fake_loss=1.317, generator_loss=26.56, generator_mel_loss=19.06, generator_kl_loss=1.343, generator_dur_loss=1.735, generator_adv_loss=1.748, generator_feat_match_loss=2.679, over 53.00 samples.], tot_loss[discriminator_loss=2.744, discriminator_real_loss=1.396, discriminator_fake_loss=1.348, generator_loss=27.16, generator_mel_loss=18.99, generator_kl_loss=1.407, generator_dur_loss=1.742, generator_adv_loss=1.904, generator_feat_match_loss=3.11, over 1402.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 12:46:38,040 INFO [train.py:527] (2/6) Epoch 127, batch 76, global_batch_idx: 15700, batch size: 66, loss[discriminator_loss=2.706, discriminator_real_loss=1.455, discriminator_fake_loss=1.25, generator_loss=27.81, generator_mel_loss=19.32, generator_kl_loss=1.363, generator_dur_loss=1.781, generator_adv_loss=2.043, generator_feat_match_loss=3.305, over 66.00 samples.], tot_loss[discriminator_loss=2.751, discriminator_real_loss=1.396, discriminator_fake_loss=1.355, generator_loss=27.33, generator_mel_loss=19.05, generator_kl_loss=1.392, generator_dur_loss=1.753, generator_adv_loss=1.933, generator_feat_match_loss=3.198, over 4201.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 12:48:48,702 INFO [train.py:919] (2/6) Start epoch 128
2024-03-12 12:49:17,603 INFO [train.py:527] (2/6) Epoch 128, batch 2, global_batch_idx: 15750, batch size: 44, loss[discriminator_loss=2.741, discriminator_real_loss=1.244, discriminator_fake_loss=1.497, generator_loss=27.72, generator_mel_loss=18.97, generator_kl_loss=1.54, generator_dur_loss=1.732, generator_adv_loss=2.014, generator_feat_match_loss=3.465, over 44.00 samples.], tot_loss[discriminator_loss=2.757, discriminator_real_loss=1.373, discriminator_fake_loss=1.384, generator_loss=26.89, generator_mel_loss=18.76, generator_kl_loss=1.405, generator_dur_loss=1.751, generator_adv_loss=1.892, generator_feat_match_loss=3.074, over 162.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 12:51:35,863 INFO [train.py:527] (2/6) Epoch 128, batch 52, global_batch_idx: 15800, batch size: 68, loss[discriminator_loss=2.712, discriminator_real_loss=1.329, discriminator_fake_loss=1.383, generator_loss=27.83, generator_mel_loss=19.26, generator_kl_loss=1.347, generator_dur_loss=1.811, generator_adv_loss=1.938, generator_feat_match_loss=3.476, over 68.00 samples.], tot_loss[discriminator_loss=2.747, discriminator_real_loss=1.387, discriminator_fake_loss=1.361, generator_loss=27.3, generator_mel_loss=19.02, generator_kl_loss=1.39, generator_dur_loss=1.784, generator_adv_loss=1.923, generator_feat_match_loss=3.181, over 3048.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 12:51:35,864 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 12:51:44,034 INFO [train.py:591] (2/6) Epoch 128, validation: discriminator_loss=2.787, discriminator_real_loss=1.483, discriminator_fake_loss=1.303, generator_loss=26.23, generator_mel_loss=19.01, generator_kl_loss=1.189, generator_dur_loss=1.831, generator_adv_loss=1.855, generator_feat_match_loss=2.347, over 100.00 samples.
2024-03-12 12:51:44,035 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 12:54:00,543 INFO [train.py:527] (2/6) Epoch 128, batch 102, global_batch_idx: 15850, batch size: 59, loss[discriminator_loss=2.775, discriminator_real_loss=1.473, discriminator_fake_loss=1.302, generator_loss=27.22, generator_mel_loss=19.16, generator_kl_loss=1.474, generator_dur_loss=1.762, generator_adv_loss=1.857, generator_feat_match_loss=2.967, over 59.00 samples.], tot_loss[discriminator_loss=2.748, discriminator_real_loss=1.388, discriminator_fake_loss=1.36, generator_loss=27.38, generator_mel_loss=19.11, generator_kl_loss=1.386, generator_dur_loss=1.776, generator_adv_loss=1.912, generator_feat_match_loss=3.201, over 5831.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 12:55:01,863 INFO [train.py:919] (2/6) Start epoch 129
2024-03-12 12:56:44,547 INFO [train.py:527] (2/6) Epoch 129, batch 28, global_batch_idx: 15900, batch size: 45, loss[discriminator_loss=2.76, discriminator_real_loss=1.412, discriminator_fake_loss=1.348, generator_loss=27.35, generator_mel_loss=19.16, generator_kl_loss=1.541, generator_dur_loss=1.695, generator_adv_loss=1.921, generator_feat_match_loss=3.029, over 45.00 samples.], tot_loss[discriminator_loss=2.743, discriminator_real_loss=1.38, discriminator_fake_loss=1.363, generator_loss=27.36, generator_mel_loss=19.15, generator_kl_loss=1.372, generator_dur_loss=1.781, generator_adv_loss=1.88, generator_feat_match_loss=3.175, over 1801.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 12:59:02,184 INFO [train.py:527] (2/6) Epoch 129, batch 78, global_batch_idx: 15950, batch size: 64, loss[discriminator_loss=2.829, discriminator_real_loss=1.436, discriminator_fake_loss=1.393, generator_loss=27.1, generator_mel_loss=19.1, generator_kl_loss=1.249, generator_dur_loss=1.783, generator_adv_loss=1.725, generator_feat_match_loss=3.244, over 64.00 samples.], tot_loss[discriminator_loss=2.757, discriminator_real_loss=1.396, discriminator_fake_loss=1.361, generator_loss=27.25, generator_mel_loss=19.05, generator_kl_loss=1.376, generator_dur_loss=1.775, generator_adv_loss=1.892, generator_feat_match_loss=3.156, over 4626.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 13:01:07,732 INFO [train.py:919] (2/6) Start epoch 130
2024-03-12 13:01:42,822 INFO [train.py:527] (2/6) Epoch 130, batch 4, global_batch_idx: 16000, batch size: 72, loss[discriminator_loss=2.696, discriminator_real_loss=1.313, discriminator_fake_loss=1.383, generator_loss=27.49, generator_mel_loss=19.17, generator_kl_loss=1.378, generator_dur_loss=1.797, generator_adv_loss=1.873, generator_feat_match_loss=3.277, over 72.00 samples.], tot_loss[discriminator_loss=2.75, discriminator_real_loss=1.352, discriminator_fake_loss=1.398, generator_loss=27.16, generator_mel_loss=18.94, generator_kl_loss=1.375, generator_dur_loss=1.825, generator_adv_loss=1.898, generator_feat_match_loss=3.116, over 318.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 13:01:42,825 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 13:01:50,761 INFO [train.py:591] (2/6) Epoch 130, validation: discriminator_loss=2.706, discriminator_real_loss=1.423, discriminator_fake_loss=1.283, generator_loss=26.49, generator_mel_loss=19.13, generator_kl_loss=1.206, generator_dur_loss=1.832, generator_adv_loss=1.842, generator_feat_match_loss=2.484, over 100.00 samples.
2024-03-12 13:01:50,780 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 13:04:09,463 INFO [train.py:527] (2/6) Epoch 130, batch 54, global_batch_idx: 16050, batch size: 64, loss[discriminator_loss=2.758, discriminator_real_loss=1.37, discriminator_fake_loss=1.387, generator_loss=26.94, generator_mel_loss=18.93, generator_kl_loss=1.38, generator_dur_loss=1.788, generator_adv_loss=1.795, generator_feat_match_loss=3.052, over 64.00 samples.], tot_loss[discriminator_loss=2.749, discriminator_real_loss=1.386, discriminator_fake_loss=1.363, generator_loss=27.25, generator_mel_loss=19.07, generator_kl_loss=1.387, generator_dur_loss=1.779, generator_adv_loss=1.898, generator_feat_match_loss=3.116, over 3109.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 13:06:28,642 INFO [train.py:527] (2/6) Epoch 130, batch 104, global_batch_idx: 16100, batch size: 42, loss[discriminator_loss=2.69, discriminator_real_loss=1.481, discriminator_fake_loss=1.21, generator_loss=27.94, generator_mel_loss=19.83, generator_kl_loss=1.382, generator_dur_loss=1.715, generator_adv_loss=1.84, generator_feat_match_loss=3.179, over 42.00 samples.], tot_loss[discriminator_loss=2.751, discriminator_real_loss=1.391, discriminator_fake_loss=1.36, generator_loss=27.27, generator_mel_loss=19.08, generator_kl_loss=1.383, generator_dur_loss=1.774, generator_adv_loss=1.896, generator_feat_match_loss=3.137, over 5995.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 13:07:19,979 INFO [train.py:919] (2/6) Start epoch 131
2024-03-12 13:09:08,199 INFO [train.py:527] (2/6) Epoch 131, batch 30, global_batch_idx: 16150, batch size: 72, loss[discriminator_loss=2.707, discriminator_real_loss=1.347, discriminator_fake_loss=1.361, generator_loss=26.93, generator_mel_loss=18.49, generator_kl_loss=1.329, generator_dur_loss=1.834, generator_adv_loss=1.899, generator_feat_match_loss=3.376, over 72.00 samples.], tot_loss[discriminator_loss=2.728, discriminator_real_loss=1.38, discriminator_fake_loss=1.349, generator_loss=27.31, generator_mel_loss=19.03, generator_kl_loss=1.363, generator_dur_loss=1.776, generator_adv_loss=1.913, generator_feat_match_loss=3.231, over 1911.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 13:11:30,107 INFO [train.py:527] (2/6) Epoch 131, batch 80, global_batch_idx: 16200, batch size: 80, loss[discriminator_loss=2.684, discriminator_real_loss=1.39, discriminator_fake_loss=1.295, generator_loss=27.63, generator_mel_loss=19.18, generator_kl_loss=1.294, generator_dur_loss=1.814, generator_adv_loss=1.946, generator_feat_match_loss=3.4, over 80.00 samples.], tot_loss[discriminator_loss=2.732, discriminator_real_loss=1.383, discriminator_fake_loss=1.35, generator_loss=27.24, generator_mel_loss=18.98, generator_kl_loss=1.376, generator_dur_loss=1.759, generator_adv_loss=1.908, generator_feat_match_loss=3.209, over 4826.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 13:11:30,109 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 13:11:39,153 INFO [train.py:591] (2/6) Epoch 131, validation: discriminator_loss=2.756, discriminator_real_loss=1.528, discriminator_fake_loss=1.229, generator_loss=27.04, generator_mel_loss=19.35, generator_kl_loss=1.247, generator_dur_loss=1.804, generator_adv_loss=1.937, generator_feat_match_loss=2.705, over 100.00 samples.
2024-03-12 13:11:39,154 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 13:13:34,808 INFO [train.py:919] (2/6) Start epoch 132
2024-03-12 13:14:15,339 INFO [train.py:527] (2/6) Epoch 132, batch 6, global_batch_idx: 16250, batch size: 68, loss[discriminator_loss=2.9, discriminator_real_loss=1.625, discriminator_fake_loss=1.275, generator_loss=27.31, generator_mel_loss=18.96, generator_kl_loss=1.474, generator_dur_loss=1.76, generator_adv_loss=1.881, generator_feat_match_loss=3.236, over 68.00 samples.], tot_loss[discriminator_loss=2.929, discriminator_real_loss=1.608, discriminator_fake_loss=1.321, generator_loss=27.74, generator_mel_loss=19.08, generator_kl_loss=1.326, generator_dur_loss=1.773, generator_adv_loss=2.252, generator_feat_match_loss=3.309, over 451.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 13:16:32,877 INFO [train.py:527] (2/6) Epoch 132, batch 56, global_batch_idx: 16300, batch size: 80, loss[discriminator_loss=2.805, discriminator_real_loss=1.498, discriminator_fake_loss=1.307, generator_loss=26.81, generator_mel_loss=18.84, generator_kl_loss=1.331, generator_dur_loss=1.791, generator_adv_loss=1.66, generator_feat_match_loss=3.189, over 80.00 samples.], tot_loss[discriminator_loss=2.769, discriminator_real_loss=1.427, discriminator_fake_loss=1.341, generator_loss=27.45, generator_mel_loss=19.06, generator_kl_loss=1.377, generator_dur_loss=1.751, generator_adv_loss=2.015, generator_feat_match_loss=3.248, over 3261.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 13:18:53,793 INFO [train.py:527] (2/6) Epoch 132, batch 106, global_batch_idx: 16350, batch size: 80, loss[discriminator_loss=2.695, discriminator_real_loss=1.423, discriminator_fake_loss=1.272, generator_loss=27.02, generator_mel_loss=18.86, generator_kl_loss=1.263, generator_dur_loss=1.867, generator_adv_loss=1.946, generator_feat_match_loss=3.09, over 80.00 samples.], tot_loss[discriminator_loss=2.766, discriminator_real_loss=1.413, discriminator_fake_loss=1.353, generator_loss=27.38, generator_mel_loss=19.07, generator_kl_loss=1.381, generator_dur_loss=1.761, generator_adv_loss=1.964, generator_feat_match_loss=3.209, over 6222.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 13:19:43,491 INFO [train.py:919] (2/6) Start epoch 133
2024-03-12 13:21:35,317 INFO [train.py:527] (2/6) Epoch 133, batch 32, global_batch_idx: 16400, batch size: 59, loss[discriminator_loss=2.831, discriminator_real_loss=1.519, discriminator_fake_loss=1.313, generator_loss=27.12, generator_mel_loss=19.08, generator_kl_loss=1.443, generator_dur_loss=1.728, generator_adv_loss=1.682, generator_feat_match_loss=3.183, over 59.00 samples.], tot_loss[discriminator_loss=2.746, discriminator_real_loss=1.405, discriminator_fake_loss=1.342, generator_loss=27.23, generator_mel_loss=19.01, generator_kl_loss=1.4, generator_dur_loss=1.73, generator_adv_loss=1.902, generator_feat_match_loss=3.193, over 1894.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 13:21:35,319 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 13:21:43,789 INFO [train.py:591] (2/6) Epoch 133, validation: discriminator_loss=2.789, discriminator_real_loss=1.338, discriminator_fake_loss=1.45, generator_loss=25.78, generator_mel_loss=19.04, generator_kl_loss=1.105, generator_dur_loss=1.795, generator_adv_loss=1.623, generator_feat_match_loss=2.221, over 100.00 samples.
2024-03-12 13:21:43,790 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 13:24:02,138 INFO [train.py:527] (2/6) Epoch 133, batch 82, global_batch_idx: 16450, batch size: 74, loss[discriminator_loss=2.77, discriminator_real_loss=1.483, discriminator_fake_loss=1.286, generator_loss=27.71, generator_mel_loss=19, generator_kl_loss=1.404, generator_dur_loss=1.777, generator_adv_loss=2.075, generator_feat_match_loss=3.451, over 74.00 samples.], tot_loss[discriminator_loss=2.757, discriminator_real_loss=1.407, discriminator_fake_loss=1.351, generator_loss=27.1, generator_mel_loss=18.89, generator_kl_loss=1.398, generator_dur_loss=1.74, generator_adv_loss=1.913, generator_feat_match_loss=3.158, over 4694.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 13:25:57,410 INFO [train.py:919] (2/6) Start epoch 134
2024-03-12 13:26:43,193 INFO [train.py:527] (2/6) Epoch 134, batch 8, global_batch_idx: 16500, batch size: 88, loss[discriminator_loss=2.774, discriminator_real_loss=1.371, discriminator_fake_loss=1.404, generator_loss=26.38, generator_mel_loss=18.41, generator_kl_loss=1.169, generator_dur_loss=1.877, generator_adv_loss=1.901, generator_feat_match_loss=3.024, over 88.00 samples.], tot_loss[discriminator_loss=2.79, discriminator_real_loss=1.427, discriminator_fake_loss=1.363, generator_loss=27.49, generator_mel_loss=19.06, generator_kl_loss=1.355, generator_dur_loss=1.772, generator_adv_loss=1.982, generator_feat_match_loss=3.315, over 545.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 13:29:01,146 INFO [train.py:527] (2/6) Epoch 134, batch 58, global_batch_idx: 16550, batch size: 70, loss[discriminator_loss=2.729, discriminator_real_loss=1.401, discriminator_fake_loss=1.328, generator_loss=27.15, generator_mel_loss=19, generator_kl_loss=1.359, generator_dur_loss=1.794, generator_adv_loss=1.905, generator_feat_match_loss=3.092, over 70.00 samples.], tot_loss[discriminator_loss=2.756, discriminator_real_loss=1.409, discriminator_fake_loss=1.347, generator_loss=27.33, generator_mel_loss=19.06, generator_kl_loss=1.383, generator_dur_loss=1.77, generator_adv_loss=1.917, generator_feat_match_loss=3.204, over 3425.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 13:31:20,799 INFO [train.py:527] (2/6) Epoch 134, batch 108, global_batch_idx: 16600, batch size: 88, loss[discriminator_loss=2.687, discriminator_real_loss=1.306, discriminator_fake_loss=1.381, generator_loss=27.42, generator_mel_loss=18.82, generator_kl_loss=1.398, generator_dur_loss=1.842, generator_adv_loss=1.954, generator_feat_match_loss=3.411, over 88.00 samples.], tot_loss[discriminator_loss=2.745, discriminator_real_loss=1.396, discriminator_fake_loss=1.349, generator_loss=27.32, generator_mel_loss=19.01, generator_kl_loss=1.387, generator_dur_loss=1.777, generator_adv_loss=1.921, generator_feat_match_loss=3.232, over 6491.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 13:31:20,801 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 13:31:29,814 INFO [train.py:591] (2/6) Epoch 134, validation: discriminator_loss=2.726, discriminator_real_loss=1.442, discriminator_fake_loss=1.284, generator_loss=26.65, generator_mel_loss=19.52, generator_kl_loss=1.061, generator_dur_loss=1.825, generator_adv_loss=1.899, generator_feat_match_loss=2.339, over 100.00 samples.
2024-03-12 13:31:29,815 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 13:32:11,912 INFO [train.py:919] (2/6) Start epoch 135
2024-03-12 13:34:10,406 INFO [train.py:527] (2/6) Epoch 135, batch 34, global_batch_idx: 16650, batch size: 42, loss[discriminator_loss=2.674, discriminator_real_loss=1.383, discriminator_fake_loss=1.291, generator_loss=28.42, generator_mel_loss=19.47, generator_kl_loss=1.615, generator_dur_loss=1.645, generator_adv_loss=2.08, generator_feat_match_loss=3.61, over 42.00 samples.], tot_loss[discriminator_loss=2.725, discriminator_real_loss=1.385, discriminator_fake_loss=1.34, generator_loss=27.33, generator_mel_loss=18.95, generator_kl_loss=1.408, generator_dur_loss=1.751, generator_adv_loss=1.921, generator_feat_match_loss=3.293, over 2001.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 13:36:29,226 INFO [train.py:527] (2/6) Epoch 135, batch 84, global_batch_idx: 16700, batch size: 70, loss[discriminator_loss=2.755, discriminator_real_loss=1.411, discriminator_fake_loss=1.345, generator_loss=26.1, generator_mel_loss=18.47, generator_kl_loss=1.27, generator_dur_loss=1.81, generator_adv_loss=1.78, generator_feat_match_loss=2.772, over 70.00 samples.], tot_loss[discriminator_loss=2.741, discriminator_real_loss=1.39, discriminator_fake_loss=1.351, generator_loss=27.53, generator_mel_loss=19.04, generator_kl_loss=1.411, generator_dur_loss=1.742, generator_adv_loss=1.989, generator_feat_match_loss=3.355, over 4515.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 13:38:17,138 INFO [train.py:919] (2/6) Start epoch 136
2024-03-12 13:39:10,298 INFO [train.py:527] (2/6) Epoch 136, batch 10, global_batch_idx: 16750, batch size: 83, loss[discriminator_loss=2.746, discriminator_real_loss=1.343, discriminator_fake_loss=1.403, generator_loss=27.4, generator_mel_loss=18.59, generator_kl_loss=1.267, generator_dur_loss=1.81, generator_adv_loss=2.104, generator_feat_match_loss=3.631, over 83.00 samples.], tot_loss[discriminator_loss=2.699, discriminator_real_loss=1.359, discriminator_fake_loss=1.34, generator_loss=27.42, generator_mel_loss=19.03, generator_kl_loss=1.31, generator_dur_loss=1.761, generator_adv_loss=1.934, generator_feat_match_loss=3.39, over 634.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 13:41:29,470 INFO [train.py:527] (2/6) Epoch 136, batch 60, global_batch_idx: 16800, batch size: 45, loss[discriminator_loss=2.742, discriminator_real_loss=1.53, discriminator_fake_loss=1.212, generator_loss=26.18, generator_mel_loss=18.33, generator_kl_loss=1.397, generator_dur_loss=1.676, generator_adv_loss=1.812, generator_feat_match_loss=2.961, over 45.00 samples.], tot_loss[discriminator_loss=2.748, discriminator_real_loss=1.397, discriminator_fake_loss=1.351, generator_loss=27.22, generator_mel_loss=19.04, generator_kl_loss=1.363, generator_dur_loss=1.728, generator_adv_loss=1.913, generator_feat_match_loss=3.183, over 3259.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 13:41:29,471 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 13:41:37,382 INFO [train.py:591] (2/6) Epoch 136, validation: discriminator_loss=2.743, discriminator_real_loss=1.405, discriminator_fake_loss=1.338, generator_loss=26.94, generator_mel_loss=19.67, generator_kl_loss=1.201, generator_dur_loss=1.773, generator_adv_loss=1.724, generator_feat_match_loss=2.572, over 100.00 samples.
2024-03-12 13:41:37,383 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 13:43:55,357 INFO [train.py:527] (2/6) Epoch 136, batch 110, global_batch_idx: 16850, batch size: 74, loss[discriminator_loss=2.828, discriminator_real_loss=1.374, discriminator_fake_loss=1.454, generator_loss=26.92, generator_mel_loss=18.62, generator_kl_loss=1.403, generator_dur_loss=1.805, generator_adv_loss=2.05, generator_feat_match_loss=3.044, over 74.00 samples.], tot_loss[discriminator_loss=2.748, discriminator_real_loss=1.393, discriminator_fake_loss=1.354, generator_loss=27.19, generator_mel_loss=19, generator_kl_loss=1.364, generator_dur_loss=1.741, generator_adv_loss=1.903, generator_feat_match_loss=3.185, over 6196.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 13:44:31,542 INFO [train.py:919] (2/6) Start epoch 137
2024-03-12 13:46:36,253 INFO [train.py:527] (2/6) Epoch 137, batch 36, global_batch_idx: 16900, batch size: 96, loss[discriminator_loss=2.761, discriminator_real_loss=1.388, discriminator_fake_loss=1.373, generator_loss=27.26, generator_mel_loss=18.98, generator_kl_loss=1.295, generator_dur_loss=1.864, generator_adv_loss=1.977, generator_feat_match_loss=3.145, over 96.00 samples.], tot_loss[discriminator_loss=2.733, discriminator_real_loss=1.385, discriminator_fake_loss=1.348, generator_loss=27.33, generator_mel_loss=19.05, generator_kl_loss=1.38, generator_dur_loss=1.773, generator_adv_loss=1.89, generator_feat_match_loss=3.244, over 2161.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 13:48:58,053 INFO [train.py:527] (2/6) Epoch 137, batch 86, global_batch_idx: 16950, batch size: 53, loss[discriminator_loss=2.717, discriminator_real_loss=1.351, discriminator_fake_loss=1.366, generator_loss=26.13, generator_mel_loss=18.07, generator_kl_loss=1.348, generator_dur_loss=1.699, generator_adv_loss=1.904, generator_feat_match_loss=3.11, over 53.00 samples.], tot_loss[discriminator_loss=2.742, discriminator_real_loss=1.39, discriminator_fake_loss=1.352, generator_loss=27.33, generator_mel_loss=18.99, generator_kl_loss=1.378, generator_dur_loss=1.771, generator_adv_loss=1.929, generator_feat_match_loss=3.256, over 5138.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 13:50:40,080 INFO [train.py:919] (2/6) Start epoch 138
2024-03-12 13:51:34,797 INFO [train.py:527] (2/6) Epoch 138, batch 12, global_batch_idx: 17000, batch size: 66, loss[discriminator_loss=2.695, discriminator_real_loss=1.388, discriminator_fake_loss=1.307, generator_loss=27.57, generator_mel_loss=19.18, generator_kl_loss=1.437, generator_dur_loss=1.817, generator_adv_loss=1.815, generator_feat_match_loss=3.32, over 66.00 samples.], tot_loss[discriminator_loss=2.734, discriminator_real_loss=1.399, discriminator_fake_loss=1.335, generator_loss=27.22, generator_mel_loss=19.07, generator_kl_loss=1.412, generator_dur_loss=1.76, generator_adv_loss=1.885, generator_feat_match_loss=3.091, over 680.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 13:51:34,800 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 13:51:42,684 INFO [train.py:591] (2/6) Epoch 138, validation: discriminator_loss=2.777, discriminator_real_loss=1.404, discriminator_fake_loss=1.373, generator_loss=26.47, generator_mel_loss=19.28, generator_kl_loss=1.093, generator_dur_loss=1.828, generator_adv_loss=1.725, generator_feat_match_loss=2.551, over 100.00 samples.
2024-03-12 13:51:42,685 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 13:54:03,172 INFO [train.py:527] (2/6) Epoch 138, batch 62, global_batch_idx: 17050, batch size: 66, loss[discriminator_loss=2.772, discriminator_real_loss=1.43, discriminator_fake_loss=1.342, generator_loss=27.46, generator_mel_loss=19.32, generator_kl_loss=1.322, generator_dur_loss=1.753, generator_adv_loss=1.824, generator_feat_match_loss=3.246, over 66.00 samples.], tot_loss[discriminator_loss=2.733, discriminator_real_loss=1.391, discriminator_fake_loss=1.342, generator_loss=27.27, generator_mel_loss=18.96, generator_kl_loss=1.401, generator_dur_loss=1.762, generator_adv_loss=1.893, generator_feat_match_loss=3.253, over 3609.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 13:56:19,473 INFO [train.py:527] (2/6) Epoch 138, batch 112, global_batch_idx: 17100, batch size: 53, loss[discriminator_loss=2.75, discriminator_real_loss=1.383, discriminator_fake_loss=1.367, generator_loss=26.54, generator_mel_loss=18.51, generator_kl_loss=1.378, generator_dur_loss=1.691, generator_adv_loss=1.866, generator_feat_match_loss=3.101, over 53.00 samples.], tot_loss[discriminator_loss=2.738, discriminator_real_loss=1.391, discriminator_fake_loss=1.347, generator_loss=27.31, generator_mel_loss=19.02, generator_kl_loss=1.4, generator_dur_loss=1.76, generator_adv_loss=1.892, generator_feat_match_loss=3.243, over 6319.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 13:56:50,773 INFO [train.py:919] (2/6) Start epoch 139
2024-03-12 13:59:01,270 INFO [train.py:527] (2/6) Epoch 139, batch 38, global_batch_idx: 17150, batch size: 77, loss[discriminator_loss=2.79, discriminator_real_loss=1.535, discriminator_fake_loss=1.255, generator_loss=26.75, generator_mel_loss=18.68, generator_kl_loss=1.175, generator_dur_loss=1.864, generator_adv_loss=1.866, generator_feat_match_loss=3.167, over 77.00 samples.], tot_loss[discriminator_loss=2.773, discriminator_real_loss=1.408, discriminator_fake_loss=1.366, generator_loss=27.39, generator_mel_loss=18.97, generator_kl_loss=1.355, generator_dur_loss=1.788, generator_adv_loss=1.992, generator_feat_match_loss=3.286, over 2371.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 14:01:21,686 INFO [train.py:527] (2/6) Epoch 139, batch 88, global_batch_idx: 17200, batch size: 39, loss[discriminator_loss=2.73, discriminator_real_loss=1.378, discriminator_fake_loss=1.352, generator_loss=26.51, generator_mel_loss=18.6, generator_kl_loss=1.224, generator_dur_loss=1.696, generator_adv_loss=1.895, generator_feat_match_loss=3.09, over 39.00 samples.], tot_loss[discriminator_loss=2.759, discriminator_real_loss=1.404, discriminator_fake_loss=1.355, generator_loss=27.26, generator_mel_loss=18.94, generator_kl_loss=1.363, generator_dur_loss=1.779, generator_adv_loss=1.945, generator_feat_match_loss=3.228, over 5181.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 14:01:21,688 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 14:01:29,862 INFO [train.py:591] (2/6) Epoch 139, validation: discriminator_loss=2.667, discriminator_real_loss=1.392, discriminator_fake_loss=1.275, generator_loss=26.29, generator_mel_loss=18.75, generator_kl_loss=1.098, generator_dur_loss=1.795, generator_adv_loss=1.943, generator_feat_match_loss=2.702, over 100.00 samples.
2024-03-12 14:01:29,863 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 14:03:08,484 INFO [train.py:919] (2/6) Start epoch 140
2024-03-12 14:04:12,722 INFO [train.py:527] (2/6) Epoch 140, batch 14, global_batch_idx: 17250, batch size: 59, loss[discriminator_loss=2.713, discriminator_real_loss=1.383, discriminator_fake_loss=1.33, generator_loss=27.63, generator_mel_loss=19.32, generator_kl_loss=1.378, generator_dur_loss=1.735, generator_adv_loss=1.825, generator_feat_match_loss=3.367, over 59.00 samples.], tot_loss[discriminator_loss=2.751, discriminator_real_loss=1.402, discriminator_fake_loss=1.349, generator_loss=27.3, generator_mel_loss=18.99, generator_kl_loss=1.386, generator_dur_loss=1.773, generator_adv_loss=1.897, generator_feat_match_loss=3.25, over 899.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 14:06:31,489 INFO [train.py:527] (2/6) Epoch 140, batch 64, global_batch_idx: 17300, batch size: 50, loss[discriminator_loss=2.788, discriminator_real_loss=1.453, discriminator_fake_loss=1.336, generator_loss=26.53, generator_mel_loss=18.78, generator_kl_loss=1.404, generator_dur_loss=1.666, generator_adv_loss=1.793, generator_feat_match_loss=2.885, over 50.00 samples.], tot_loss[discriminator_loss=2.742, discriminator_real_loss=1.391, discriminator_fake_loss=1.351, generator_loss=27.31, generator_mel_loss=19.01, generator_kl_loss=1.378, generator_dur_loss=1.755, generator_adv_loss=1.903, generator_feat_match_loss=3.265, over 3854.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 14:08:49,291 INFO [train.py:527] (2/6) Epoch 140, batch 114, global_batch_idx: 17350, batch size: 56, loss[discriminator_loss=2.746, discriminator_real_loss=1.402, discriminator_fake_loss=1.344, generator_loss=26.98, generator_mel_loss=18.25, generator_kl_loss=1.491, generator_dur_loss=1.707, generator_adv_loss=2.128, generator_feat_match_loss=3.413, over 56.00 samples.], tot_loss[discriminator_loss=2.75, discriminator_real_loss=1.393, discriminator_fake_loss=1.357, generator_loss=27.31, generator_mel_loss=19.01, generator_kl_loss=1.392, generator_dur_loss=1.748, generator_adv_loss=1.898, generator_feat_match_loss=3.259, over 6449.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 14:09:15,466 INFO [train.py:919] (2/6) Start epoch 141
2024-03-12 14:11:31,928 INFO [train.py:527] (2/6) Epoch 141, batch 40, global_batch_idx: 17400, batch size: 56, loss[discriminator_loss=2.725, discriminator_real_loss=1.282, discriminator_fake_loss=1.442, generator_loss=27.6, generator_mel_loss=19.2, generator_kl_loss=1.509, generator_dur_loss=1.68, generator_adv_loss=1.892, generator_feat_match_loss=3.318, over 56.00 samples.], tot_loss[discriminator_loss=2.733, discriminator_real_loss=1.382, discriminator_fake_loss=1.352, generator_loss=27.39, generator_mel_loss=18.95, generator_kl_loss=1.392, generator_dur_loss=1.78, generator_adv_loss=1.929, generator_feat_match_loss=3.334, over 2528.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 14:11:31,930 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 14:11:40,077 INFO [train.py:591] (2/6) Epoch 141, validation: discriminator_loss=2.773, discriminator_real_loss=1.432, discriminator_fake_loss=1.341, generator_loss=26.01, generator_mel_loss=18.65, generator_kl_loss=1.195, generator_dur_loss=1.798, generator_adv_loss=1.86, generator_feat_match_loss=2.51, over 100.00 samples.
2024-03-12 14:11:40,078 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 14:13:59,383 INFO [train.py:527] (2/6) Epoch 141, batch 90, global_batch_idx: 17450, batch size: 66, loss[discriminator_loss=2.705, discriminator_real_loss=1.382, discriminator_fake_loss=1.323, generator_loss=27.21, generator_mel_loss=19.38, generator_kl_loss=1.353, generator_dur_loss=1.798, generator_adv_loss=1.854, generator_feat_match_loss=2.816, over 66.00 samples.], tot_loss[discriminator_loss=2.74, discriminator_real_loss=1.387, discriminator_fake_loss=1.352, generator_loss=27.36, generator_mel_loss=18.98, generator_kl_loss=1.404, generator_dur_loss=1.764, generator_adv_loss=1.919, generator_feat_match_loss=3.289, over 5387.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 14:15:33,473 INFO [train.py:919] (2/6) Start epoch 142
2024-03-12 14:16:41,586 INFO [train.py:527] (2/6) Epoch 142, batch 16, global_batch_idx: 17500, batch size: 96, loss[discriminator_loss=2.78, discriminator_real_loss=1.366, discriminator_fake_loss=1.413, generator_loss=25.99, generator_mel_loss=18.22, generator_kl_loss=1.258, generator_dur_loss=1.846, generator_adv_loss=1.846, generator_feat_match_loss=2.817, over 96.00 samples.], tot_loss[discriminator_loss=2.772, discriminator_real_loss=1.429, discriminator_fake_loss=1.344, generator_loss=27.01, generator_mel_loss=18.79, generator_kl_loss=1.397, generator_dur_loss=1.776, generator_adv_loss=1.879, generator_feat_match_loss=3.169, over 1043.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 14:19:00,025 INFO [train.py:527] (2/6) Epoch 142, batch 66, global_batch_idx: 17550, batch size: 25, loss[discriminator_loss=2.684, discriminator_real_loss=1.375, discriminator_fake_loss=1.309, generator_loss=27.84, generator_mel_loss=19.6, generator_kl_loss=1.461, generator_dur_loss=1.543, generator_adv_loss=1.875, generator_feat_match_loss=3.362, over 25.00 samples.], tot_loss[discriminator_loss=2.749, discriminator_real_loss=1.399, discriminator_fake_loss=1.35, generator_loss=27.33, generator_mel_loss=18.97, generator_kl_loss=1.421, generator_dur_loss=1.757, generator_adv_loss=1.891, generator_feat_match_loss=3.297, over 3692.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 14:21:16,247 INFO [train.py:527] (2/6) Epoch 142, batch 116, global_batch_idx: 17600, batch size: 88, loss[discriminator_loss=3.174, discriminator_real_loss=1.59, discriminator_fake_loss=1.584, generator_loss=27.68, generator_mel_loss=19.4, generator_kl_loss=1.355, generator_dur_loss=1.834, generator_adv_loss=1.842, generator_feat_match_loss=3.246, over 88.00 samples.], tot_loss[discriminator_loss=2.754, discriminator_real_loss=1.395, discriminator_fake_loss=1.36, generator_loss=27.36, generator_mel_loss=18.98, generator_kl_loss=1.423, generator_dur_loss=1.752, generator_adv_loss=1.902, generator_feat_match_loss=3.307, over 6257.00 samples.], cur_lr_g: 1.97e-04, cur_lr_d: 1.97e-04, 
2024-03-12 14:21:16,249 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 14:21:25,033 INFO [train.py:591] (2/6) Epoch 142, validation: discriminator_loss=3.002, discriminator_real_loss=1.685, discriminator_fake_loss=1.318, generator_loss=27, generator_mel_loss=19.09, generator_kl_loss=1.229, generator_dur_loss=1.787, generator_adv_loss=1.925, generator_feat_match_loss=2.968, over 100.00 samples.
2024-03-12 14:21:25,034 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 14:21:45,677 INFO [train.py:919] (2/6) Start epoch 143
2024-03-12 14:24:07,030 INFO [train.py:527] (2/6) Epoch 143, batch 42, global_batch_idx: 17650, batch size: 66, loss[discriminator_loss=2.78, discriminator_real_loss=1.498, discriminator_fake_loss=1.282, generator_loss=26.61, generator_mel_loss=18.58, generator_kl_loss=1.296, generator_dur_loss=1.772, generator_adv_loss=1.961, generator_feat_match_loss=3.007, over 66.00 samples.], tot_loss[discriminator_loss=2.745, discriminator_real_loss=1.39, discriminator_fake_loss=1.355, generator_loss=27.28, generator_mel_loss=18.93, generator_kl_loss=1.378, generator_dur_loss=1.747, generator_adv_loss=1.926, generator_feat_match_loss=3.297, over 2521.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 14:26:24,708 INFO [train.py:527] (2/6) Epoch 143, batch 92, global_batch_idx: 17700, batch size: 77, loss[discriminator_loss=2.79, discriminator_real_loss=1.437, discriminator_fake_loss=1.352, generator_loss=26.78, generator_mel_loss=18.84, generator_kl_loss=1.309, generator_dur_loss=1.756, generator_adv_loss=1.946, generator_feat_match_loss=2.932, over 77.00 samples.], tot_loss[discriminator_loss=2.748, discriminator_real_loss=1.395, discriminator_fake_loss=1.353, generator_loss=27.22, generator_mel_loss=18.89, generator_kl_loss=1.382, generator_dur_loss=1.749, generator_adv_loss=1.909, generator_feat_match_loss=3.292, over 5444.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 14:27:50,714 INFO [train.py:919] (2/6) Start epoch 144
2024-03-12 14:29:04,002 INFO [train.py:527] (2/6) Epoch 144, batch 18, global_batch_idx: 17750, batch size: 77, loss[discriminator_loss=2.941, discriminator_real_loss=1.68, discriminator_fake_loss=1.261, generator_loss=26.54, generator_mel_loss=18.94, generator_kl_loss=1.216, generator_dur_loss=1.867, generator_adv_loss=1.492, generator_feat_match_loss=3.029, over 77.00 samples.], tot_loss[discriminator_loss=2.767, discriminator_real_loss=1.406, discriminator_fake_loss=1.36, generator_loss=27.48, generator_mel_loss=19.16, generator_kl_loss=1.366, generator_dur_loss=1.779, generator_adv_loss=1.888, generator_feat_match_loss=3.286, over 1182.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 14:31:23,750 INFO [train.py:527] (2/6) Epoch 144, batch 68, global_batch_idx: 17800, batch size: 88, loss[discriminator_loss=2.756, discriminator_real_loss=1.348, discriminator_fake_loss=1.408, generator_loss=26.93, generator_mel_loss=18.6, generator_kl_loss=1.284, generator_dur_loss=1.901, generator_adv_loss=1.784, generator_feat_match_loss=3.365, over 88.00 samples.], tot_loss[discriminator_loss=2.747, discriminator_real_loss=1.389, discriminator_fake_loss=1.358, generator_loss=27.32, generator_mel_loss=18.94, generator_kl_loss=1.384, generator_dur_loss=1.776, generator_adv_loss=1.914, generator_feat_match_loss=3.312, over 4150.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 14:31:23,752 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 14:31:31,868 INFO [train.py:591] (2/6) Epoch 144, validation: discriminator_loss=2.728, discriminator_real_loss=1.3, discriminator_fake_loss=1.429, generator_loss=26.78, generator_mel_loss=19.42, generator_kl_loss=1.208, generator_dur_loss=1.821, generator_adv_loss=1.719, generator_feat_match_loss=2.614, over 100.00 samples.
2024-03-12 14:31:31,869 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 14:33:51,165 INFO [train.py:527] (2/6) Epoch 144, batch 118, global_batch_idx: 17850, batch size: 45, loss[discriminator_loss=2.756, discriminator_real_loss=1.379, discriminator_fake_loss=1.377, generator_loss=27.67, generator_mel_loss=19.3, generator_kl_loss=1.496, generator_dur_loss=1.713, generator_adv_loss=1.955, generator_feat_match_loss=3.206, over 45.00 samples.], tot_loss[discriminator_loss=2.748, discriminator_real_loss=1.391, discriminator_fake_loss=1.358, generator_loss=27.32, generator_mel_loss=18.96, generator_kl_loss=1.385, generator_dur_loss=1.78, generator_adv_loss=1.908, generator_feat_match_loss=3.28, over 6962.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 14:34:07,027 INFO [train.py:919] (2/6) Start epoch 145
2024-03-12 14:36:30,855 INFO [train.py:527] (2/6) Epoch 145, batch 44, global_batch_idx: 17900, batch size: 53, loss[discriminator_loss=2.697, discriminator_real_loss=1.389, discriminator_fake_loss=1.309, generator_loss=26.86, generator_mel_loss=18.63, generator_kl_loss=1.425, generator_dur_loss=1.71, generator_adv_loss=1.936, generator_feat_match_loss=3.153, over 53.00 samples.], tot_loss[discriminator_loss=2.748, discriminator_real_loss=1.394, discriminator_fake_loss=1.354, generator_loss=27.18, generator_mel_loss=18.86, generator_kl_loss=1.394, generator_dur_loss=1.756, generator_adv_loss=1.904, generator_feat_match_loss=3.266, over 2636.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 14:38:48,789 INFO [train.py:527] (2/6) Epoch 145, batch 94, global_batch_idx: 17950, batch size: 39, loss[discriminator_loss=2.688, discriminator_real_loss=1.425, discriminator_fake_loss=1.263, generator_loss=27.64, generator_mel_loss=18.94, generator_kl_loss=1.423, generator_dur_loss=1.715, generator_adv_loss=1.88, generator_feat_match_loss=3.676, over 39.00 samples.], tot_loss[discriminator_loss=2.754, discriminator_real_loss=1.393, discriminator_fake_loss=1.361, generator_loss=27.17, generator_mel_loss=18.84, generator_kl_loss=1.398, generator_dur_loss=1.749, generator_adv_loss=1.905, generator_feat_match_loss=3.283, over 5313.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 14:40:11,794 INFO [train.py:919] (2/6) Start epoch 146
2024-03-12 14:41:30,542 INFO [train.py:527] (2/6) Epoch 146, batch 20, global_batch_idx: 18000, batch size: 77, loss[discriminator_loss=2.791, discriminator_real_loss=1.505, discriminator_fake_loss=1.286, generator_loss=26.91, generator_mel_loss=18.96, generator_kl_loss=1.25, generator_dur_loss=1.83, generator_adv_loss=1.813, generator_feat_match_loss=3.056, over 77.00 samples.], tot_loss[discriminator_loss=2.727, discriminator_real_loss=1.394, discriminator_fake_loss=1.333, generator_loss=27.33, generator_mel_loss=19.02, generator_kl_loss=1.348, generator_dur_loss=1.769, generator_adv_loss=1.925, generator_feat_match_loss=3.265, over 1254.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 14:41:30,544 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 14:41:38,563 INFO [train.py:591] (2/6) Epoch 146, validation: discriminator_loss=2.748, discriminator_real_loss=1.38, discriminator_fake_loss=1.368, generator_loss=26.46, generator_mel_loss=19.02, generator_kl_loss=1.269, generator_dur_loss=1.793, generator_adv_loss=1.78, generator_feat_match_loss=2.597, over 100.00 samples.
2024-03-12 14:41:38,564 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 14:43:56,290 INFO [train.py:527] (2/6) Epoch 146, batch 70, global_batch_idx: 18050, batch size: 96, loss[discriminator_loss=2.739, discriminator_real_loss=1.439, discriminator_fake_loss=1.3, generator_loss=26.91, generator_mel_loss=18.64, generator_kl_loss=1.16, generator_dur_loss=1.937, generator_adv_loss=1.83, generator_feat_match_loss=3.346, over 96.00 samples.], tot_loss[discriminator_loss=2.739, discriminator_real_loss=1.395, discriminator_fake_loss=1.344, generator_loss=27.34, generator_mel_loss=18.98, generator_kl_loss=1.379, generator_dur_loss=1.773, generator_adv_loss=1.918, generator_feat_match_loss=3.287, over 4081.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 14:46:14,850 INFO [train.py:527] (2/6) Epoch 146, batch 120, global_batch_idx: 18100, batch size: 58, loss[discriminator_loss=2.741, discriminator_real_loss=1.281, discriminator_fake_loss=1.461, generator_loss=27.66, generator_mel_loss=18.9, generator_kl_loss=1.382, generator_dur_loss=1.778, generator_adv_loss=2.015, generator_feat_match_loss=3.585, over 58.00 samples.], tot_loss[discriminator_loss=2.737, discriminator_real_loss=1.387, discriminator_fake_loss=1.35, generator_loss=27.39, generator_mel_loss=19, generator_kl_loss=1.385, generator_dur_loss=1.771, generator_adv_loss=1.927, generator_feat_match_loss=3.306, over 6720.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 14:46:24,646 INFO [train.py:919] (2/6) Start epoch 147
2024-03-12 14:48:55,259 INFO [train.py:527] (2/6) Epoch 147, batch 46, global_batch_idx: 18150, batch size: 74, loss[discriminator_loss=2.708, discriminator_real_loss=1.416, discriminator_fake_loss=1.293, generator_loss=27.25, generator_mel_loss=18.64, generator_kl_loss=1.295, generator_dur_loss=1.771, generator_adv_loss=2.065, generator_feat_match_loss=3.473, over 74.00 samples.], tot_loss[discriminator_loss=2.73, discriminator_real_loss=1.386, discriminator_fake_loss=1.344, generator_loss=27.33, generator_mel_loss=18.93, generator_kl_loss=1.386, generator_dur_loss=1.772, generator_adv_loss=1.924, generator_feat_match_loss=3.314, over 2762.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 14:51:14,725 INFO [train.py:527] (2/6) Epoch 147, batch 96, global_batch_idx: 18200, batch size: 50, loss[discriminator_loss=2.774, discriminator_real_loss=1.419, discriminator_fake_loss=1.356, generator_loss=26.37, generator_mel_loss=18.56, generator_kl_loss=1.27, generator_dur_loss=1.708, generator_adv_loss=1.935, generator_feat_match_loss=2.894, over 50.00 samples.], tot_loss[discriminator_loss=2.733, discriminator_real_loss=1.386, discriminator_fake_loss=1.347, generator_loss=27.35, generator_mel_loss=18.92, generator_kl_loss=1.377, generator_dur_loss=1.773, generator_adv_loss=1.928, generator_feat_match_loss=3.35, over 5801.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 14:51:14,727 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 14:51:22,538 INFO [train.py:591] (2/6) Epoch 147, validation: discriminator_loss=2.8, discriminator_real_loss=1.475, discriminator_fake_loss=1.325, generator_loss=26.11, generator_mel_loss=18.68, generator_kl_loss=1.205, generator_dur_loss=1.791, generator_adv_loss=1.852, generator_feat_match_loss=2.585, over 100.00 samples.
2024-03-12 14:51:22,539 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 14:52:35,262 INFO [train.py:919] (2/6) Start epoch 148
2024-03-12 14:54:01,891 INFO [train.py:527] (2/6) Epoch 148, batch 22, global_batch_idx: 18250, batch size: 80, loss[discriminator_loss=2.754, discriminator_real_loss=1.347, discriminator_fake_loss=1.407, generator_loss=27.03, generator_mel_loss=18.84, generator_kl_loss=1.368, generator_dur_loss=1.842, generator_adv_loss=1.759, generator_feat_match_loss=3.225, over 80.00 samples.], tot_loss[discriminator_loss=2.758, discriminator_real_loss=1.399, discriminator_fake_loss=1.359, generator_loss=27.57, generator_mel_loss=19.13, generator_kl_loss=1.401, generator_dur_loss=1.745, generator_adv_loss=1.959, generator_feat_match_loss=3.341, over 1212.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 14:56:18,694 INFO [train.py:527] (2/6) Epoch 148, batch 72, global_batch_idx: 18300, batch size: 88, loss[discriminator_loss=2.66, discriminator_real_loss=1.34, discriminator_fake_loss=1.319, generator_loss=27.34, generator_mel_loss=18.79, generator_kl_loss=1.313, generator_dur_loss=1.788, generator_adv_loss=1.884, generator_feat_match_loss=3.568, over 88.00 samples.], tot_loss[discriminator_loss=2.741, discriminator_real_loss=1.391, discriminator_fake_loss=1.351, generator_loss=27.37, generator_mel_loss=18.97, generator_kl_loss=1.388, generator_dur_loss=1.76, generator_adv_loss=1.932, generator_feat_match_loss=3.325, over 4042.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 14:58:38,623 INFO [train.py:527] (2/6) Epoch 148, batch 122, global_batch_idx: 18350, batch size: 96, loss[discriminator_loss=2.719, discriminator_real_loss=1.435, discriminator_fake_loss=1.284, generator_loss=27.26, generator_mel_loss=18.91, generator_kl_loss=1.412, generator_dur_loss=1.788, generator_adv_loss=1.784, generator_feat_match_loss=3.361, over 96.00 samples.], tot_loss[discriminator_loss=2.741, discriminator_real_loss=1.389, discriminator_fake_loss=1.353, generator_loss=27.34, generator_mel_loss=18.93, generator_kl_loss=1.392, generator_dur_loss=1.761, generator_adv_loss=1.926, generator_feat_match_loss=3.336, over 6988.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 14:58:43,747 INFO [train.py:919] (2/6) Start epoch 149
2024-03-12 15:01:23,305 INFO [train.py:527] (2/6) Epoch 149, batch 48, global_batch_idx: 18400, batch size: 16, loss[discriminator_loss=2.671, discriminator_real_loss=1.378, discriminator_fake_loss=1.293, generator_loss=28.31, generator_mel_loss=19.79, generator_kl_loss=1.588, generator_dur_loss=1.659, generator_adv_loss=2.067, generator_feat_match_loss=3.199, over 16.00 samples.], tot_loss[discriminator_loss=2.741, discriminator_real_loss=1.39, discriminator_fake_loss=1.351, generator_loss=27.28, generator_mel_loss=18.92, generator_kl_loss=1.384, generator_dur_loss=1.757, generator_adv_loss=1.914, generator_feat_match_loss=3.304, over 2782.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 15:01:23,307 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 15:01:31,251 INFO [train.py:591] (2/6) Epoch 149, validation: discriminator_loss=2.775, discriminator_real_loss=1.531, discriminator_fake_loss=1.244, generator_loss=26.8, generator_mel_loss=19.07, generator_kl_loss=1.13, generator_dur_loss=1.803, generator_adv_loss=2.019, generator_feat_match_loss=2.784, over 100.00 samples.
2024-03-12 15:01:31,253 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 15:03:52,675 INFO [train.py:527] (2/6) Epoch 149, batch 98, global_batch_idx: 18450, batch size: 45, loss[discriminator_loss=2.786, discriminator_real_loss=1.478, discriminator_fake_loss=1.308, generator_loss=27.41, generator_mel_loss=19.2, generator_kl_loss=1.469, generator_dur_loss=1.721, generator_adv_loss=1.719, generator_feat_match_loss=3.305, over 45.00 samples.], tot_loss[discriminator_loss=2.746, discriminator_real_loss=1.394, discriminator_fake_loss=1.352, generator_loss=27.33, generator_mel_loss=18.93, generator_kl_loss=1.398, generator_dur_loss=1.76, generator_adv_loss=1.921, generator_feat_match_loss=3.321, over 5493.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 15:05:03,050 INFO [train.py:919] (2/6) Start epoch 150
2024-03-12 15:06:33,931 INFO [train.py:527] (2/6) Epoch 150, batch 24, global_batch_idx: 18500, batch size: 70, loss[discriminator_loss=2.726, discriminator_real_loss=1.459, discriminator_fake_loss=1.266, generator_loss=26.74, generator_mel_loss=18.64, generator_kl_loss=1.281, generator_dur_loss=1.815, generator_adv_loss=1.841, generator_feat_match_loss=3.166, over 70.00 samples.], tot_loss[discriminator_loss=2.723, discriminator_real_loss=1.39, discriminator_fake_loss=1.334, generator_loss=27.46, generator_mel_loss=18.89, generator_kl_loss=1.385, generator_dur_loss=1.763, generator_adv_loss=1.929, generator_feat_match_loss=3.49, over 1474.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 15:08:53,858 INFO [train.py:527] (2/6) Epoch 150, batch 74, global_batch_idx: 18550, batch size: 64, loss[discriminator_loss=2.731, discriminator_real_loss=1.26, discriminator_fake_loss=1.47, generator_loss=27.18, generator_mel_loss=18.71, generator_kl_loss=1.374, generator_dur_loss=1.792, generator_adv_loss=1.985, generator_feat_match_loss=3.315, over 64.00 samples.], tot_loss[discriminator_loss=2.744, discriminator_real_loss=1.388, discriminator_fake_loss=1.356, generator_loss=27.31, generator_mel_loss=18.85, generator_kl_loss=1.393, generator_dur_loss=1.785, generator_adv_loss=1.92, generator_feat_match_loss=3.361, over 4525.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 15:11:08,960 INFO [train.py:919] (2/6) Start epoch 151
2024-03-12 15:11:33,468 INFO [train.py:527] (2/6) Epoch 151, batch 0, global_batch_idx: 18600, batch size: 58, loss[discriminator_loss=2.746, discriminator_real_loss=1.353, discriminator_fake_loss=1.393, generator_loss=27.45, generator_mel_loss=18.93, generator_kl_loss=1.335, generator_dur_loss=1.731, generator_adv_loss=2.009, generator_feat_match_loss=3.443, over 58.00 samples.], tot_loss[discriminator_loss=2.746, discriminator_real_loss=1.353, discriminator_fake_loss=1.393, generator_loss=27.45, generator_mel_loss=18.93, generator_kl_loss=1.335, generator_dur_loss=1.731, generator_adv_loss=2.009, generator_feat_match_loss=3.443, over 58.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 15:11:33,471 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 15:11:41,536 INFO [train.py:591] (2/6) Epoch 151, validation: discriminator_loss=2.735, discriminator_real_loss=1.467, discriminator_fake_loss=1.268, generator_loss=26.89, generator_mel_loss=19.14, generator_kl_loss=1.258, generator_dur_loss=1.801, generator_adv_loss=1.948, generator_feat_match_loss=2.737, over 100.00 samples.
2024-03-12 15:11:41,545 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 15:13:59,569 INFO [train.py:527] (2/6) Epoch 151, batch 50, global_batch_idx: 18650, batch size: 31, loss[discriminator_loss=2.647, discriminator_real_loss=1.267, discriminator_fake_loss=1.38, generator_loss=29, generator_mel_loss=19.9, generator_kl_loss=1.625, generator_dur_loss=1.659, generator_adv_loss=2.085, generator_feat_match_loss=3.727, over 31.00 samples.], tot_loss[discriminator_loss=2.739, discriminator_real_loss=1.395, discriminator_fake_loss=1.344, generator_loss=27.43, generator_mel_loss=18.88, generator_kl_loss=1.413, generator_dur_loss=1.75, generator_adv_loss=1.955, generator_feat_match_loss=3.429, over 2591.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 15:16:18,482 INFO [train.py:527] (2/6) Epoch 151, batch 100, global_batch_idx: 18700, batch size: 52, loss[discriminator_loss=2.798, discriminator_real_loss=1.324, discriminator_fake_loss=1.474, generator_loss=27.16, generator_mel_loss=18.83, generator_kl_loss=1.411, generator_dur_loss=1.685, generator_adv_loss=1.887, generator_feat_match_loss=3.344, over 52.00 samples.], tot_loss[discriminator_loss=2.747, discriminator_real_loss=1.391, discriminator_fake_loss=1.356, generator_loss=27.43, generator_mel_loss=18.94, generator_kl_loss=1.4, generator_dur_loss=1.766, generator_adv_loss=1.935, generator_feat_match_loss=3.383, over 5647.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 15:17:23,860 INFO [train.py:919] (2/6) Start epoch 152
2024-03-12 15:19:01,267 INFO [train.py:527] (2/6) Epoch 152, batch 26, global_batch_idx: 18750, batch size: 59, loss[discriminator_loss=2.769, discriminator_real_loss=1.452, discriminator_fake_loss=1.317, generator_loss=27.27, generator_mel_loss=19.44, generator_kl_loss=1.459, generator_dur_loss=1.757, generator_adv_loss=1.81, generator_feat_match_loss=2.796, over 59.00 samples.], tot_loss[discriminator_loss=2.745, discriminator_real_loss=1.385, discriminator_fake_loss=1.36, generator_loss=27.47, generator_mel_loss=19.01, generator_kl_loss=1.377, generator_dur_loss=1.773, generator_adv_loss=1.891, generator_feat_match_loss=3.412, over 1656.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 15:21:20,232 INFO [train.py:527] (2/6) Epoch 152, batch 76, global_batch_idx: 18800, batch size: 55, loss[discriminator_loss=2.719, discriminator_real_loss=1.324, discriminator_fake_loss=1.395, generator_loss=28.21, generator_mel_loss=19.4, generator_kl_loss=1.479, generator_dur_loss=1.723, generator_adv_loss=2.051, generator_feat_match_loss=3.548, over 55.00 samples.], tot_loss[discriminator_loss=2.746, discriminator_real_loss=1.39, discriminator_fake_loss=1.356, generator_loss=27.4, generator_mel_loss=18.96, generator_kl_loss=1.388, generator_dur_loss=1.762, generator_adv_loss=1.908, generator_feat_match_loss=3.382, over 4600.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 15:21:20,234 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 15:21:28,347 INFO [train.py:591] (2/6) Epoch 152, validation: discriminator_loss=2.778, discriminator_real_loss=1.529, discriminator_fake_loss=1.249, generator_loss=26.45, generator_mel_loss=18.82, generator_kl_loss=1.153, generator_dur_loss=1.825, generator_adv_loss=2.006, generator_feat_match_loss=2.646, over 100.00 samples.
2024-03-12 15:21:28,349 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 15:23:37,873 INFO [train.py:919] (2/6) Start epoch 153
2024-03-12 15:24:09,061 INFO [train.py:527] (2/6) Epoch 153, batch 2, global_batch_idx: 18850, batch size: 66, loss[discriminator_loss=2.739, discriminator_real_loss=1.433, discriminator_fake_loss=1.306, generator_loss=27.42, generator_mel_loss=18.87, generator_kl_loss=1.38, generator_dur_loss=1.815, generator_adv_loss=1.932, generator_feat_match_loss=3.423, over 66.00 samples.], tot_loss[discriminator_loss=2.696, discriminator_real_loss=1.366, discriminator_fake_loss=1.329, generator_loss=27.44, generator_mel_loss=18.81, generator_kl_loss=1.345, generator_dur_loss=1.836, generator_adv_loss=2.038, generator_feat_match_loss=3.412, over 234.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 15:26:29,807 INFO [train.py:527] (2/6) Epoch 153, batch 52, global_batch_idx: 18900, batch size: 64, loss[discriminator_loss=2.684, discriminator_real_loss=1.41, discriminator_fake_loss=1.274, generator_loss=27.28, generator_mel_loss=19.13, generator_kl_loss=1.216, generator_dur_loss=1.763, generator_adv_loss=1.905, generator_feat_match_loss=3.263, over 64.00 samples.], tot_loss[discriminator_loss=2.733, discriminator_real_loss=1.382, discriminator_fake_loss=1.352, generator_loss=27.42, generator_mel_loss=18.89, generator_kl_loss=1.377, generator_dur_loss=1.77, generator_adv_loss=1.969, generator_feat_match_loss=3.417, over 3136.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 15:28:46,063 INFO [train.py:527] (2/6) Epoch 153, batch 102, global_batch_idx: 18950, batch size: 45, loss[discriminator_loss=2.679, discriminator_real_loss=1.322, discriminator_fake_loss=1.356, generator_loss=26.71, generator_mel_loss=18.74, generator_kl_loss=1.495, generator_dur_loss=1.658, generator_adv_loss=1.874, generator_feat_match_loss=2.945, over 45.00 samples.], tot_loss[discriminator_loss=2.73, discriminator_real_loss=1.384, discriminator_fake_loss=1.345, generator_loss=27.38, generator_mel_loss=18.87, generator_kl_loss=1.385, generator_dur_loss=1.768, generator_adv_loss=1.943, generator_feat_match_loss=3.406, over 6033.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 15:29:46,777 INFO [train.py:919] (2/6) Start epoch 154
2024-03-12 15:31:26,262 INFO [train.py:527] (2/6) Epoch 154, batch 28, global_batch_idx: 19000, batch size: 58, loss[discriminator_loss=2.756, discriminator_real_loss=1.45, discriminator_fake_loss=1.307, generator_loss=27.2, generator_mel_loss=19.03, generator_kl_loss=1.322, generator_dur_loss=1.66, generator_adv_loss=1.877, generator_feat_match_loss=3.308, over 58.00 samples.], tot_loss[discriminator_loss=2.729, discriminator_real_loss=1.375, discriminator_fake_loss=1.354, generator_loss=27.27, generator_mel_loss=18.93, generator_kl_loss=1.396, generator_dur_loss=1.73, generator_adv_loss=1.894, generator_feat_match_loss=3.324, over 1807.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 15:31:26,263 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 15:31:34,131 INFO [train.py:591] (2/6) Epoch 154, validation: discriminator_loss=2.717, discriminator_real_loss=1.374, discriminator_fake_loss=1.343, generator_loss=26.3, generator_mel_loss=18.72, generator_kl_loss=1.243, generator_dur_loss=1.74, generator_adv_loss=1.839, generator_feat_match_loss=2.755, over 100.00 samples.
2024-03-12 15:31:34,132 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 15:33:53,044 INFO [train.py:527] (2/6) Epoch 154, batch 78, global_batch_idx: 19050, batch size: 62, loss[discriminator_loss=2.918, discriminator_real_loss=1.663, discriminator_fake_loss=1.255, generator_loss=27.63, generator_mel_loss=19.42, generator_kl_loss=1.374, generator_dur_loss=1.761, generator_adv_loss=1.669, generator_feat_match_loss=3.4, over 62.00 samples.], tot_loss[discriminator_loss=2.739, discriminator_real_loss=1.387, discriminator_fake_loss=1.352, generator_loss=27.35, generator_mel_loss=18.95, generator_kl_loss=1.408, generator_dur_loss=1.725, generator_adv_loss=1.905, generator_feat_match_loss=3.361, over 4648.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 15:36:01,433 INFO [train.py:919] (2/6) Start epoch 155
2024-03-12 15:36:35,989 INFO [train.py:527] (2/6) Epoch 155, batch 4, global_batch_idx: 19100, batch size: 66, loss[discriminator_loss=2.714, discriminator_real_loss=1.388, discriminator_fake_loss=1.326, generator_loss=28.05, generator_mel_loss=19.36, generator_kl_loss=1.088, generator_dur_loss=1.798, generator_adv_loss=2.051, generator_feat_match_loss=3.754, over 66.00 samples.], tot_loss[discriminator_loss=2.734, discriminator_real_loss=1.393, discriminator_fake_loss=1.341, generator_loss=27.78, generator_mel_loss=19.12, generator_kl_loss=1.324, generator_dur_loss=1.752, generator_adv_loss=1.941, generator_feat_match_loss=3.641, over 303.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 15:38:53,488 INFO [train.py:527] (2/6) Epoch 155, batch 54, global_batch_idx: 19150, batch size: 74, loss[discriminator_loss=2.66, discriminator_real_loss=1.389, discriminator_fake_loss=1.271, generator_loss=28.11, generator_mel_loss=19.47, generator_kl_loss=1.254, generator_dur_loss=1.811, generator_adv_loss=1.923, generator_feat_match_loss=3.651, over 74.00 samples.], tot_loss[discriminator_loss=2.741, discriminator_real_loss=1.387, discriminator_fake_loss=1.354, generator_loss=27.5, generator_mel_loss=18.98, generator_kl_loss=1.37, generator_dur_loss=1.753, generator_adv_loss=1.928, generator_feat_match_loss=3.461, over 3167.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 15:41:13,947 INFO [train.py:527] (2/6) Epoch 155, batch 104, global_batch_idx: 19200, batch size: 50, loss[discriminator_loss=2.702, discriminator_real_loss=1.305, discriminator_fake_loss=1.397, generator_loss=27.74, generator_mel_loss=19.12, generator_kl_loss=1.533, generator_dur_loss=1.673, generator_adv_loss=1.969, generator_feat_match_loss=3.438, over 50.00 samples.], tot_loss[discriminator_loss=2.734, discriminator_real_loss=1.387, discriminator_fake_loss=1.347, generator_loss=27.48, generator_mel_loss=18.95, generator_kl_loss=1.372, generator_dur_loss=1.767, generator_adv_loss=1.942, generator_feat_match_loss=3.452, over 6064.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 15:41:13,948 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 15:41:22,941 INFO [train.py:591] (2/6) Epoch 155, validation: discriminator_loss=2.767, discriminator_real_loss=1.508, discriminator_fake_loss=1.259, generator_loss=26.42, generator_mel_loss=18.97, generator_kl_loss=1.178, generator_dur_loss=1.82, generator_adv_loss=1.914, generator_feat_match_loss=2.536, over 100.00 samples.
2024-03-12 15:41:22,941 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 15:42:17,701 INFO [train.py:919] (2/6) Start epoch 156
2024-03-12 15:44:06,872 INFO [train.py:527] (2/6) Epoch 156, batch 30, global_batch_idx: 19250, batch size: 36, loss[discriminator_loss=2.731, discriminator_real_loss=1.376, discriminator_fake_loss=1.354, generator_loss=27.34, generator_mel_loss=18.96, generator_kl_loss=1.482, generator_dur_loss=1.721, generator_adv_loss=1.973, generator_feat_match_loss=3.21, over 36.00 samples.], tot_loss[discriminator_loss=2.708, discriminator_real_loss=1.376, discriminator_fake_loss=1.332, generator_loss=27.21, generator_mel_loss=18.7, generator_kl_loss=1.387, generator_dur_loss=1.735, generator_adv_loss=1.931, generator_feat_match_loss=3.462, over 1786.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 15:46:28,114 INFO [train.py:527] (2/6) Epoch 156, batch 80, global_batch_idx: 19300, batch size: 39, loss[discriminator_loss=2.626, discriminator_real_loss=1.315, discriminator_fake_loss=1.311, generator_loss=28.83, generator_mel_loss=19.62, generator_kl_loss=1.72, generator_dur_loss=1.636, generator_adv_loss=1.868, generator_feat_match_loss=3.986, over 39.00 samples.], tot_loss[discriminator_loss=2.719, discriminator_real_loss=1.377, discriminator_fake_loss=1.341, generator_loss=27.46, generator_mel_loss=18.91, generator_kl_loss=1.377, generator_dur_loss=1.743, generator_adv_loss=1.942, generator_feat_match_loss=3.491, over 4822.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 15:48:24,567 INFO [train.py:919] (2/6) Start epoch 157
2024-03-12 15:49:07,915 INFO [train.py:527] (2/6) Epoch 157, batch 6, global_batch_idx: 19350, batch size: 68, loss[discriminator_loss=2.7, discriminator_real_loss=1.261, discriminator_fake_loss=1.44, generator_loss=27.45, generator_mel_loss=18.66, generator_kl_loss=1.224, generator_dur_loss=1.813, generator_adv_loss=2.061, generator_feat_match_loss=3.696, over 68.00 samples.], tot_loss[discriminator_loss=2.739, discriminator_real_loss=1.311, discriminator_fake_loss=1.428, generator_loss=27.47, generator_mel_loss=18.88, generator_kl_loss=1.39, generator_dur_loss=1.798, generator_adv_loss=1.888, generator_feat_match_loss=3.51, over 389.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 15:51:26,058 INFO [train.py:527] (2/6) Epoch 157, batch 56, global_batch_idx: 19400, batch size: 16, loss[discriminator_loss=2.748, discriminator_real_loss=1.433, discriminator_fake_loss=1.315, generator_loss=28.25, generator_mel_loss=19.84, generator_kl_loss=1.461, generator_dur_loss=1.686, generator_adv_loss=2.022, generator_feat_match_loss=3.245, over 16.00 samples.], tot_loss[discriminator_loss=2.736, discriminator_real_loss=1.395, discriminator_fake_loss=1.341, generator_loss=27.57, generator_mel_loss=18.95, generator_kl_loss=1.395, generator_dur_loss=1.732, generator_adv_loss=1.983, generator_feat_match_loss=3.512, over 3022.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 15:51:26,061 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 15:51:34,073 INFO [train.py:591] (2/6) Epoch 157, validation: discriminator_loss=2.749, discriminator_real_loss=1.516, discriminator_fake_loss=1.233, generator_loss=26.44, generator_mel_loss=19.06, generator_kl_loss=1.206, generator_dur_loss=1.765, generator_adv_loss=1.966, generator_feat_match_loss=2.451, over 100.00 samples.
2024-03-12 15:51:34,074 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 15:53:51,976 INFO [train.py:527] (2/6) Epoch 157, batch 106, global_batch_idx: 19450, batch size: 56, loss[discriminator_loss=2.712, discriminator_real_loss=1.417, discriminator_fake_loss=1.296, generator_loss=27.01, generator_mel_loss=18.75, generator_kl_loss=1.38, generator_dur_loss=1.721, generator_adv_loss=1.916, generator_feat_match_loss=3.244, over 56.00 samples.], tot_loss[discriminator_loss=2.753, discriminator_real_loss=1.404, discriminator_fake_loss=1.349, generator_loss=27.48, generator_mel_loss=18.93, generator_kl_loss=1.396, generator_dur_loss=1.735, generator_adv_loss=1.966, generator_feat_match_loss=3.445, over 5622.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 15:54:43,380 INFO [train.py:919] (2/6) Start epoch 158
2024-03-12 15:56:35,713 INFO [train.py:527] (2/6) Epoch 158, batch 32, global_batch_idx: 19500, batch size: 42, loss[discriminator_loss=2.754, discriminator_real_loss=1.312, discriminator_fake_loss=1.442, generator_loss=27.45, generator_mel_loss=19.11, generator_kl_loss=1.435, generator_dur_loss=1.682, generator_adv_loss=1.884, generator_feat_match_loss=3.338, over 42.00 samples.], tot_loss[discriminator_loss=2.735, discriminator_real_loss=1.386, discriminator_fake_loss=1.348, generator_loss=27.4, generator_mel_loss=18.98, generator_kl_loss=1.374, generator_dur_loss=1.749, generator_adv_loss=1.917, generator_feat_match_loss=3.387, over 1938.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 15:58:57,718 INFO [train.py:527] (2/6) Epoch 158, batch 82, global_batch_idx: 19550, batch size: 72, loss[discriminator_loss=2.786, discriminator_real_loss=1.349, discriminator_fake_loss=1.437, generator_loss=27.13, generator_mel_loss=18.57, generator_kl_loss=1.424, generator_dur_loss=1.819, generator_adv_loss=2.105, generator_feat_match_loss=3.217, over 72.00 samples.], tot_loss[discriminator_loss=2.739, discriminator_real_loss=1.388, discriminator_fake_loss=1.351, generator_loss=27.41, generator_mel_loss=18.93, generator_kl_loss=1.393, generator_dur_loss=1.767, generator_adv_loss=1.923, generator_feat_match_loss=3.4, over 4912.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 16:00:50,293 INFO [train.py:919] (2/6) Start epoch 159
2024-03-12 16:01:36,518 INFO [train.py:527] (2/6) Epoch 159, batch 8, global_batch_idx: 19600, batch size: 88, loss[discriminator_loss=2.731, discriminator_real_loss=1.469, discriminator_fake_loss=1.262, generator_loss=27.27, generator_mel_loss=18.78, generator_kl_loss=1.305, generator_dur_loss=1.829, generator_adv_loss=1.963, generator_feat_match_loss=3.391, over 88.00 samples.], tot_loss[discriminator_loss=2.708, discriminator_real_loss=1.382, discriminator_fake_loss=1.325, generator_loss=27.23, generator_mel_loss=18.71, generator_kl_loss=1.418, generator_dur_loss=1.746, generator_adv_loss=1.957, generator_feat_match_loss=3.401, over 510.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 16:01:36,521 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 16:01:44,546 INFO [train.py:591] (2/6) Epoch 159, validation: discriminator_loss=2.698, discriminator_real_loss=1.452, discriminator_fake_loss=1.247, generator_loss=27.56, generator_mel_loss=19.76, generator_kl_loss=1.168, generator_dur_loss=1.787, generator_adv_loss=1.922, generator_feat_match_loss=2.921, over 100.00 samples.
2024-03-12 16:01:44,549 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 16:04:06,499 INFO [train.py:527] (2/6) Epoch 159, batch 58, global_batch_idx: 19650, batch size: 16, loss[discriminator_loss=2.731, discriminator_real_loss=1.35, discriminator_fake_loss=1.381, generator_loss=30.67, generator_mel_loss=21.76, generator_kl_loss=1.611, generator_dur_loss=1.546, generator_adv_loss=1.884, generator_feat_match_loss=3.872, over 16.00 samples.], tot_loss[discriminator_loss=2.73, discriminator_real_loss=1.379, discriminator_fake_loss=1.351, generator_loss=27.53, generator_mel_loss=18.91, generator_kl_loss=1.413, generator_dur_loss=1.752, generator_adv_loss=1.946, generator_feat_match_loss=3.513, over 3343.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 16:06:25,392 INFO [train.py:527] (2/6) Epoch 159, batch 108, global_batch_idx: 19700, batch size: 25, loss[discriminator_loss=2.669, discriminator_real_loss=1.192, discriminator_fake_loss=1.477, generator_loss=30.09, generator_mel_loss=20.27, generator_kl_loss=1.681, generator_dur_loss=1.544, generator_adv_loss=2.271, generator_feat_match_loss=4.323, over 25.00 samples.], tot_loss[discriminator_loss=2.729, discriminator_real_loss=1.38, discriminator_fake_loss=1.349, generator_loss=27.47, generator_mel_loss=18.94, generator_kl_loss=1.392, generator_dur_loss=1.752, generator_adv_loss=1.939, generator_feat_match_loss=3.448, over 6227.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 16:07:05,335 INFO [train.py:919] (2/6) Start epoch 160
2024-03-12 16:09:05,137 INFO [train.py:527] (2/6) Epoch 160, batch 34, global_batch_idx: 19750, batch size: 50, loss[discriminator_loss=2.768, discriminator_real_loss=1.445, discriminator_fake_loss=1.324, generator_loss=27.72, generator_mel_loss=19.34, generator_kl_loss=1.52, generator_dur_loss=1.706, generator_adv_loss=1.857, generator_feat_match_loss=3.293, over 50.00 samples.], tot_loss[discriminator_loss=2.763, discriminator_real_loss=1.405, discriminator_fake_loss=1.358, generator_loss=27.24, generator_mel_loss=18.79, generator_kl_loss=1.397, generator_dur_loss=1.762, generator_adv_loss=1.913, generator_feat_match_loss=3.374, over 1987.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 16:11:24,991 INFO [train.py:527] (2/6) Epoch 160, batch 84, global_batch_idx: 19800, batch size: 59, loss[discriminator_loss=2.767, discriminator_real_loss=1.423, discriminator_fake_loss=1.344, generator_loss=27.27, generator_mel_loss=19.12, generator_kl_loss=1.443, generator_dur_loss=1.763, generator_adv_loss=1.906, generator_feat_match_loss=3.035, over 59.00 samples.], tot_loss[discriminator_loss=2.752, discriminator_real_loss=1.397, discriminator_fake_loss=1.355, generator_loss=27.29, generator_mel_loss=18.88, generator_kl_loss=1.387, generator_dur_loss=1.762, generator_adv_loss=1.908, generator_feat_match_loss=3.346, over 4810.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 16:11:24,992 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 16:11:32,896 INFO [train.py:591] (2/6) Epoch 160, validation: discriminator_loss=2.75, discriminator_real_loss=1.446, discriminator_fake_loss=1.304, generator_loss=26.95, generator_mel_loss=19.15, generator_kl_loss=1.266, generator_dur_loss=1.828, generator_adv_loss=1.832, generator_feat_match_loss=2.876, over 100.00 samples.
2024-03-12 16:11:32,897 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 16:13:23,414 INFO [train.py:919] (2/6) Start epoch 161
2024-03-12 16:14:14,998 INFO [train.py:527] (2/6) Epoch 161, batch 10, global_batch_idx: 19850, batch size: 72, loss[discriminator_loss=2.794, discriminator_real_loss=1.429, discriminator_fake_loss=1.365, generator_loss=27.69, generator_mel_loss=19.45, generator_kl_loss=1.414, generator_dur_loss=1.814, generator_adv_loss=1.837, generator_feat_match_loss=3.174, over 72.00 samples.], tot_loss[discriminator_loss=2.748, discriminator_real_loss=1.391, discriminator_fake_loss=1.357, generator_loss=27.13, generator_mel_loss=18.81, generator_kl_loss=1.38, generator_dur_loss=1.756, generator_adv_loss=1.928, generator_feat_match_loss=3.251, over 646.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 16:16:33,445 INFO [train.py:527] (2/6) Epoch 161, batch 60, global_batch_idx: 19900, batch size: 58, loss[discriminator_loss=2.713, discriminator_real_loss=1.359, discriminator_fake_loss=1.353, generator_loss=27.95, generator_mel_loss=19.24, generator_kl_loss=1.428, generator_dur_loss=1.757, generator_adv_loss=2.039, generator_feat_match_loss=3.484, over 58.00 samples.], tot_loss[discriminator_loss=2.743, discriminator_real_loss=1.394, discriminator_fake_loss=1.349, generator_loss=27.22, generator_mel_loss=18.81, generator_kl_loss=1.393, generator_dur_loss=1.75, generator_adv_loss=1.922, generator_feat_match_loss=3.345, over 3288.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 16:18:52,777 INFO [train.py:527] (2/6) Epoch 161, batch 110, global_batch_idx: 19950, batch size: 13, loss[discriminator_loss=2.779, discriminator_real_loss=1.271, discriminator_fake_loss=1.508, generator_loss=29.81, generator_mel_loss=20.73, generator_kl_loss=1.786, generator_dur_loss=1.621, generator_adv_loss=2.032, generator_feat_match_loss=3.642, over 13.00 samples.], tot_loss[discriminator_loss=2.742, discriminator_real_loss=1.389, discriminator_fake_loss=1.353, generator_loss=27.33, generator_mel_loss=18.85, generator_kl_loss=1.389, generator_dur_loss=1.759, generator_adv_loss=1.923, generator_feat_match_loss=3.404, over 6162.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 16:19:29,228 INFO [train.py:919] (2/6) Start epoch 162
2024-03-12 16:21:31,290 INFO [train.py:527] (2/6) Epoch 162, batch 36, global_batch_idx: 20000, batch size: 36, loss[discriminator_loss=2.775, discriminator_real_loss=1.429, discriminator_fake_loss=1.346, generator_loss=26.93, generator_mel_loss=18.85, generator_kl_loss=1.369, generator_dur_loss=1.672, generator_adv_loss=1.774, generator_feat_match_loss=3.268, over 36.00 samples.], tot_loss[discriminator_loss=2.74, discriminator_real_loss=1.387, discriminator_fake_loss=1.353, generator_loss=27.36, generator_mel_loss=18.89, generator_kl_loss=1.381, generator_dur_loss=1.755, generator_adv_loss=1.913, generator_feat_match_loss=3.421, over 2205.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 16:21:31,292 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 16:21:39,252 INFO [train.py:591] (2/6) Epoch 162, validation: discriminator_loss=2.779, discriminator_real_loss=1.425, discriminator_fake_loss=1.354, generator_loss=26.49, generator_mel_loss=19.13, generator_kl_loss=1.198, generator_dur_loss=1.781, generator_adv_loss=1.756, generator_feat_match_loss=2.623, over 100.00 samples.
2024-03-12 16:21:39,253 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 16:23:56,704 INFO [train.py:527] (2/6) Epoch 162, batch 86, global_batch_idx: 20050, batch size: 31, loss[discriminator_loss=2.755, discriminator_real_loss=1.313, discriminator_fake_loss=1.443, generator_loss=28.06, generator_mel_loss=19.57, generator_kl_loss=1.399, generator_dur_loss=1.64, generator_adv_loss=2.076, generator_feat_match_loss=3.369, over 31.00 samples.], tot_loss[discriminator_loss=2.741, discriminator_real_loss=1.39, discriminator_fake_loss=1.351, generator_loss=27.44, generator_mel_loss=18.94, generator_kl_loss=1.404, generator_dur_loss=1.74, generator_adv_loss=1.926, generator_feat_match_loss=3.433, over 4851.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 16:25:44,109 INFO [train.py:919] (2/6) Start epoch 163
2024-03-12 16:26:42,830 INFO [train.py:527] (2/6) Epoch 163, batch 12, global_batch_idx: 20100, batch size: 15, loss[discriminator_loss=2.649, discriminator_real_loss=1.383, discriminator_fake_loss=1.266, generator_loss=30.65, generator_mel_loss=20.95, generator_kl_loss=1.669, generator_dur_loss=1.588, generator_adv_loss=2.214, generator_feat_match_loss=4.235, over 15.00 samples.], tot_loss[discriminator_loss=2.73, discriminator_real_loss=1.394, discriminator_fake_loss=1.336, generator_loss=27.54, generator_mel_loss=18.91, generator_kl_loss=1.369, generator_dur_loss=1.734, generator_adv_loss=1.945, generator_feat_match_loss=3.583, over 658.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 16:29:01,077 INFO [train.py:527] (2/6) Epoch 163, batch 62, global_batch_idx: 20150, batch size: 44, loss[discriminator_loss=2.682, discriminator_real_loss=1.346, discriminator_fake_loss=1.336, generator_loss=27.56, generator_mel_loss=18.75, generator_kl_loss=1.415, generator_dur_loss=1.698, generator_adv_loss=2.039, generator_feat_match_loss=3.663, over 44.00 samples.], tot_loss[discriminator_loss=2.738, discriminator_real_loss=1.389, discriminator_fake_loss=1.349, generator_loss=27.42, generator_mel_loss=18.91, generator_kl_loss=1.395, generator_dur_loss=1.74, generator_adv_loss=1.908, generator_feat_match_loss=3.463, over 3427.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 16:31:20,185 INFO [train.py:527] (2/6) Epoch 163, batch 112, global_batch_idx: 20200, batch size: 58, loss[discriminator_loss=2.845, discriminator_real_loss=1.483, discriminator_fake_loss=1.362, generator_loss=28.08, generator_mel_loss=19.61, generator_kl_loss=1.43, generator_dur_loss=1.731, generator_adv_loss=2.018, generator_feat_match_loss=3.289, over 58.00 samples.], tot_loss[discriminator_loss=2.743, discriminator_real_loss=1.392, discriminator_fake_loss=1.351, generator_loss=27.46, generator_mel_loss=18.83, generator_kl_loss=1.388, generator_dur_loss=1.741, generator_adv_loss=1.967, generator_feat_match_loss=3.53, over 6414.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 16:31:20,187 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 16:31:29,124 INFO [train.py:591] (2/6) Epoch 163, validation: discriminator_loss=2.982, discriminator_real_loss=1.568, discriminator_fake_loss=1.414, generator_loss=26.57, generator_mel_loss=19.42, generator_kl_loss=1.199, generator_dur_loss=1.781, generator_adv_loss=1.785, generator_feat_match_loss=2.386, over 100.00 samples.
2024-03-12 16:31:29,125 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 16:31:59,570 INFO [train.py:919] (2/6) Start epoch 164
2024-03-12 16:34:11,308 INFO [train.py:527] (2/6) Epoch 164, batch 38, global_batch_idx: 20250, batch size: 68, loss[discriminator_loss=2.723, discriminator_real_loss=1.334, discriminator_fake_loss=1.389, generator_loss=27.62, generator_mel_loss=18.93, generator_kl_loss=1.454, generator_dur_loss=1.726, generator_adv_loss=1.76, generator_feat_match_loss=3.747, over 68.00 samples.], tot_loss[discriminator_loss=2.742, discriminator_real_loss=1.393, discriminator_fake_loss=1.349, generator_loss=27.27, generator_mel_loss=18.82, generator_kl_loss=1.362, generator_dur_loss=1.768, generator_adv_loss=1.93, generator_feat_match_loss=3.389, over 2447.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 16:36:29,713 INFO [train.py:527] (2/6) Epoch 164, batch 88, global_batch_idx: 20300, batch size: 70, loss[discriminator_loss=2.803, discriminator_real_loss=1.437, discriminator_fake_loss=1.366, generator_loss=27.65, generator_mel_loss=19.31, generator_kl_loss=1.339, generator_dur_loss=1.802, generator_adv_loss=1.78, generator_feat_match_loss=3.413, over 70.00 samples.], tot_loss[discriminator_loss=2.74, discriminator_real_loss=1.394, discriminator_fake_loss=1.345, generator_loss=27.34, generator_mel_loss=18.85, generator_kl_loss=1.384, generator_dur_loss=1.755, generator_adv_loss=1.922, generator_feat_match_loss=3.436, over 5337.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 16:38:05,644 INFO [train.py:919] (2/6) Start epoch 165
2024-03-12 16:39:10,461 INFO [train.py:527] (2/6) Epoch 165, batch 14, global_batch_idx: 20350, batch size: 55, loss[discriminator_loss=2.659, discriminator_real_loss=1.209, discriminator_fake_loss=1.45, generator_loss=27.38, generator_mel_loss=18.71, generator_kl_loss=1.499, generator_dur_loss=1.646, generator_adv_loss=1.925, generator_feat_match_loss=3.595, over 55.00 samples.], tot_loss[discriminator_loss=2.732, discriminator_real_loss=1.361, discriminator_fake_loss=1.371, generator_loss=27.48, generator_mel_loss=18.8, generator_kl_loss=1.415, generator_dur_loss=1.721, generator_adv_loss=1.942, generator_feat_match_loss=3.607, over 876.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 16:41:30,682 INFO [train.py:527] (2/6) Epoch 165, batch 64, global_batch_idx: 20400, batch size: 62, loss[discriminator_loss=2.763, discriminator_real_loss=1.39, discriminator_fake_loss=1.373, generator_loss=27.08, generator_mel_loss=18.72, generator_kl_loss=1.455, generator_dur_loss=1.743, generator_adv_loss=1.777, generator_feat_match_loss=3.386, over 62.00 samples.], tot_loss[discriminator_loss=2.745, discriminator_real_loss=1.392, discriminator_fake_loss=1.353, generator_loss=27.22, generator_mel_loss=18.75, generator_kl_loss=1.387, generator_dur_loss=1.731, generator_adv_loss=1.916, generator_feat_match_loss=3.435, over 3670.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 16:41:30,683 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 16:41:38,611 INFO [train.py:591] (2/6) Epoch 165, validation: discriminator_loss=2.729, discriminator_real_loss=1.357, discriminator_fake_loss=1.372, generator_loss=26.09, generator_mel_loss=18.77, generator_kl_loss=1.186, generator_dur_loss=1.781, generator_adv_loss=1.756, generator_feat_match_loss=2.6, over 100.00 samples.
2024-03-12 16:41:38,612 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 16:43:59,049 INFO [train.py:527] (2/6) Epoch 165, batch 114, global_batch_idx: 20450, batch size: 53, loss[discriminator_loss=2.726, discriminator_real_loss=1.426, discriminator_fake_loss=1.3, generator_loss=28.22, generator_mel_loss=19.38, generator_kl_loss=1.478, generator_dur_loss=1.651, generator_adv_loss=1.812, generator_feat_match_loss=3.9, over 53.00 samples.], tot_loss[discriminator_loss=2.748, discriminator_real_loss=1.396, discriminator_fake_loss=1.352, generator_loss=27.23, generator_mel_loss=18.77, generator_kl_loss=1.391, generator_dur_loss=1.744, generator_adv_loss=1.912, generator_feat_match_loss=3.412, over 6604.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 16:44:25,454 INFO [train.py:919] (2/6) Start epoch 166
2024-03-12 16:46:40,193 INFO [train.py:527] (2/6) Epoch 166, batch 40, global_batch_idx: 20500, batch size: 59, loss[discriminator_loss=2.77, discriminator_real_loss=1.528, discriminator_fake_loss=1.242, generator_loss=26.99, generator_mel_loss=18.76, generator_kl_loss=1.367, generator_dur_loss=1.699, generator_adv_loss=1.868, generator_feat_match_loss=3.294, over 59.00 samples.], tot_loss[discriminator_loss=2.74, discriminator_real_loss=1.39, discriminator_fake_loss=1.35, generator_loss=27.32, generator_mel_loss=18.86, generator_kl_loss=1.384, generator_dur_loss=1.763, generator_adv_loss=1.911, generator_feat_match_loss=3.4, over 2371.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 16:49:00,034 INFO [train.py:527] (2/6) Epoch 166, batch 90, global_batch_idx: 20550, batch size: 53, loss[discriminator_loss=2.778, discriminator_real_loss=1.448, discriminator_fake_loss=1.33, generator_loss=26.9, generator_mel_loss=18.69, generator_kl_loss=1.499, generator_dur_loss=1.668, generator_adv_loss=1.939, generator_feat_match_loss=3.103, over 53.00 samples.], tot_loss[discriminator_loss=2.746, discriminator_real_loss=1.398, discriminator_fake_loss=1.348, generator_loss=27.28, generator_mel_loss=18.86, generator_kl_loss=1.398, generator_dur_loss=1.723, generator_adv_loss=1.906, generator_feat_match_loss=3.384, over 5032.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 16:50:32,547 INFO [train.py:919] (2/6) Start epoch 167
2024-03-12 16:51:41,488 INFO [train.py:527] (2/6) Epoch 167, batch 16, global_batch_idx: 20600, batch size: 66, loss[discriminator_loss=2.779, discriminator_real_loss=1.469, discriminator_fake_loss=1.31, generator_loss=27.18, generator_mel_loss=19.01, generator_kl_loss=1.34, generator_dur_loss=1.717, generator_adv_loss=1.776, generator_feat_match_loss=3.337, over 66.00 samples.], tot_loss[discriminator_loss=2.729, discriminator_real_loss=1.373, discriminator_fake_loss=1.355, generator_loss=27.46, generator_mel_loss=18.88, generator_kl_loss=1.355, generator_dur_loss=1.749, generator_adv_loss=1.918, generator_feat_match_loss=3.563, over 1130.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 16:51:41,490 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 16:51:49,247 INFO [train.py:591] (2/6) Epoch 167, validation: discriminator_loss=2.73, discriminator_real_loss=1.293, discriminator_fake_loss=1.436, generator_loss=27.39, generator_mel_loss=19.63, generator_kl_loss=1.25, generator_dur_loss=1.775, generator_adv_loss=1.671, generator_feat_match_loss=3.066, over 100.00 samples.
2024-03-12 16:51:49,248 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 16:54:07,883 INFO [train.py:527] (2/6) Epoch 167, batch 66, global_batch_idx: 20650, batch size: 62, loss[discriminator_loss=2.748, discriminator_real_loss=1.473, discriminator_fake_loss=1.275, generator_loss=26.8, generator_mel_loss=18.38, generator_kl_loss=1.477, generator_dur_loss=1.731, generator_adv_loss=1.999, generator_feat_match_loss=3.206, over 62.00 samples.], tot_loss[discriminator_loss=2.741, discriminator_real_loss=1.386, discriminator_fake_loss=1.356, generator_loss=27.45, generator_mel_loss=18.89, generator_kl_loss=1.398, generator_dur_loss=1.741, generator_adv_loss=1.924, generator_feat_match_loss=3.492, over 3883.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 16:56:25,115 INFO [train.py:527] (2/6) Epoch 167, batch 116, global_batch_idx: 20700, batch size: 83, loss[discriminator_loss=2.694, discriminator_real_loss=1.433, discriminator_fake_loss=1.261, generator_loss=26.5, generator_mel_loss=18.43, generator_kl_loss=1.247, generator_dur_loss=1.821, generator_adv_loss=1.735, generator_feat_match_loss=3.268, over 83.00 samples.], tot_loss[discriminator_loss=2.74, discriminator_real_loss=1.386, discriminator_fake_loss=1.354, generator_loss=27.36, generator_mel_loss=18.85, generator_kl_loss=1.391, generator_dur_loss=1.749, generator_adv_loss=1.924, generator_feat_match_loss=3.451, over 6791.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 16:56:47,259 INFO [train.py:919] (2/6) Start epoch 168
2024-03-12 16:59:06,642 INFO [train.py:527] (2/6) Epoch 168, batch 42, global_batch_idx: 20750, batch size: 39, loss[discriminator_loss=2.792, discriminator_real_loss=1.366, discriminator_fake_loss=1.426, generator_loss=27.66, generator_mel_loss=19.01, generator_kl_loss=1.422, generator_dur_loss=1.64, generator_adv_loss=1.994, generator_feat_match_loss=3.594, over 39.00 samples.], tot_loss[discriminator_loss=2.753, discriminator_real_loss=1.397, discriminator_fake_loss=1.356, generator_loss=27.41, generator_mel_loss=18.87, generator_kl_loss=1.379, generator_dur_loss=1.751, generator_adv_loss=1.928, generator_feat_match_loss=3.484, over 2504.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 17:01:25,295 INFO [train.py:527] (2/6) Epoch 168, batch 92, global_batch_idx: 20800, batch size: 39, loss[discriminator_loss=2.731, discriminator_real_loss=1.453, discriminator_fake_loss=1.279, generator_loss=28.36, generator_mel_loss=19.81, generator_kl_loss=1.381, generator_dur_loss=1.71, generator_adv_loss=1.88, generator_feat_match_loss=3.581, over 39.00 samples.], tot_loss[discriminator_loss=2.74, discriminator_real_loss=1.388, discriminator_fake_loss=1.352, generator_loss=27.4, generator_mel_loss=18.86, generator_kl_loss=1.38, generator_dur_loss=1.743, generator_adv_loss=1.918, generator_feat_match_loss=3.496, over 5289.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 17:01:25,297 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 17:01:33,561 INFO [train.py:591] (2/6) Epoch 168, validation: discriminator_loss=2.724, discriminator_real_loss=1.436, discriminator_fake_loss=1.287, generator_loss=26.81, generator_mel_loss=19.08, generator_kl_loss=1.096, generator_dur_loss=1.803, generator_adv_loss=1.849, generator_feat_match_loss=2.988, over 100.00 samples.
2024-03-12 17:01:33,563 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 17:03:00,508 INFO [train.py:919] (2/6) Start epoch 169
2024-03-12 17:04:15,934 INFO [train.py:527] (2/6) Epoch 169, batch 18, global_batch_idx: 20850, batch size: 55, loss[discriminator_loss=2.838, discriminator_real_loss=1.394, discriminator_fake_loss=1.444, generator_loss=28.06, generator_mel_loss=19.29, generator_kl_loss=1.366, generator_dur_loss=1.709, generator_adv_loss=1.89, generator_feat_match_loss=3.809, over 55.00 samples.], tot_loss[discriminator_loss=2.735, discriminator_real_loss=1.397, discriminator_fake_loss=1.338, generator_loss=27.71, generator_mel_loss=18.8, generator_kl_loss=1.411, generator_dur_loss=1.707, generator_adv_loss=2.095, generator_feat_match_loss=3.693, over 966.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 17:06:32,666 INFO [train.py:527] (2/6) Epoch 169, batch 68, global_batch_idx: 20900, batch size: 77, loss[discriminator_loss=2.734, discriminator_real_loss=1.363, discriminator_fake_loss=1.371, generator_loss=26.47, generator_mel_loss=18.33, generator_kl_loss=1.119, generator_dur_loss=1.83, generator_adv_loss=1.83, generator_feat_match_loss=3.361, over 77.00 samples.], tot_loss[discriminator_loss=2.734, discriminator_real_loss=1.395, discriminator_fake_loss=1.339, generator_loss=27.37, generator_mel_loss=18.76, generator_kl_loss=1.389, generator_dur_loss=1.736, generator_adv_loss=1.968, generator_feat_match_loss=3.51, over 3845.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 17:08:52,755 INFO [train.py:527] (2/6) Epoch 169, batch 118, global_batch_idx: 20950, batch size: 96, loss[discriminator_loss=2.724, discriminator_real_loss=1.34, discriminator_fake_loss=1.384, generator_loss=27.18, generator_mel_loss=18.57, generator_kl_loss=1.332, generator_dur_loss=1.896, generator_adv_loss=1.712, generator_feat_match_loss=3.67, over 96.00 samples.], tot_loss[discriminator_loss=2.735, discriminator_real_loss=1.392, discriminator_fake_loss=1.344, generator_loss=27.33, generator_mel_loss=18.77, generator_kl_loss=1.38, generator_dur_loss=1.748, generator_adv_loss=1.943, generator_feat_match_loss=3.49, over 6694.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 17:09:08,753 INFO [train.py:919] (2/6) Start epoch 170
2024-03-12 17:11:33,921 INFO [train.py:527] (2/6) Epoch 170, batch 44, global_batch_idx: 21000, batch size: 53, loss[discriminator_loss=2.697, discriminator_real_loss=1.462, discriminator_fake_loss=1.235, generator_loss=27.56, generator_mel_loss=19.15, generator_kl_loss=1.377, generator_dur_loss=1.717, generator_adv_loss=1.787, generator_feat_match_loss=3.526, over 53.00 samples.], tot_loss[discriminator_loss=2.737, discriminator_real_loss=1.393, discriminator_fake_loss=1.344, generator_loss=27.34, generator_mel_loss=18.83, generator_kl_loss=1.394, generator_dur_loss=1.737, generator_adv_loss=1.91, generator_feat_match_loss=3.468, over 2514.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 17:11:33,923 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 17:11:41,705 INFO [train.py:591] (2/6) Epoch 170, validation: discriminator_loss=2.708, discriminator_real_loss=1.313, discriminator_fake_loss=1.394, generator_loss=26.42, generator_mel_loss=18.87, generator_kl_loss=1.098, generator_dur_loss=1.825, generator_adv_loss=1.715, generator_feat_match_loss=2.916, over 100.00 samples.
2024-03-12 17:11:41,706 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 17:14:00,403 INFO [train.py:527] (2/6) Epoch 170, batch 94, global_batch_idx: 21050, batch size: 64, loss[discriminator_loss=2.727, discriminator_real_loss=1.407, discriminator_fake_loss=1.32, generator_loss=27.81, generator_mel_loss=19.08, generator_kl_loss=1.384, generator_dur_loss=1.79, generator_adv_loss=1.908, generator_feat_match_loss=3.644, over 64.00 samples.], tot_loss[discriminator_loss=2.737, discriminator_real_loss=1.389, discriminator_fake_loss=1.348, generator_loss=27.34, generator_mel_loss=18.84, generator_kl_loss=1.378, generator_dur_loss=1.753, generator_adv_loss=1.915, generator_feat_match_loss=3.46, over 5376.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 17:15:20,355 INFO [train.py:919] (2/6) Start epoch 171
2024-03-12 17:16:42,708 INFO [train.py:527] (2/6) Epoch 171, batch 20, global_batch_idx: 21100, batch size: 56, loss[discriminator_loss=2.741, discriminator_real_loss=1.512, discriminator_fake_loss=1.229, generator_loss=28.07, generator_mel_loss=19.25, generator_kl_loss=1.43, generator_dur_loss=1.736, generator_adv_loss=1.963, generator_feat_match_loss=3.688, over 56.00 samples.], tot_loss[discriminator_loss=2.736, discriminator_real_loss=1.403, discriminator_fake_loss=1.332, generator_loss=27.24, generator_mel_loss=18.8, generator_kl_loss=1.367, generator_dur_loss=1.758, generator_adv_loss=1.928, generator_feat_match_loss=3.382, over 1238.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 17:19:03,282 INFO [train.py:527] (2/6) Epoch 171, batch 70, global_batch_idx: 21150, batch size: 56, loss[discriminator_loss=2.825, discriminator_real_loss=1.503, discriminator_fake_loss=1.322, generator_loss=26.53, generator_mel_loss=18.38, generator_kl_loss=1.293, generator_dur_loss=1.72, generator_adv_loss=1.991, generator_feat_match_loss=3.145, over 56.00 samples.], tot_loss[discriminator_loss=2.75, discriminator_real_loss=1.397, discriminator_fake_loss=1.353, generator_loss=27.29, generator_mel_loss=18.8, generator_kl_loss=1.385, generator_dur_loss=1.755, generator_adv_loss=1.915, generator_feat_match_loss=3.433, over 4149.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 17:21:20,427 INFO [train.py:527] (2/6) Epoch 171, batch 120, global_batch_idx: 21200, batch size: 59, loss[discriminator_loss=2.71, discriminator_real_loss=1.39, discriminator_fake_loss=1.32, generator_loss=27.17, generator_mel_loss=18.74, generator_kl_loss=1.381, generator_dur_loss=1.724, generator_adv_loss=2.004, generator_feat_match_loss=3.323, over 59.00 samples.], tot_loss[discriminator_loss=2.756, discriminator_real_loss=1.405, discriminator_fake_loss=1.351, generator_loss=27.34, generator_mel_loss=18.76, generator_kl_loss=1.388, generator_dur_loss=1.759, generator_adv_loss=1.957, generator_feat_match_loss=3.475, over 6995.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 17:21:20,428 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 17:21:29,266 INFO [train.py:591] (2/6) Epoch 171, validation: discriminator_loss=2.765, discriminator_real_loss=1.541, discriminator_fake_loss=1.224, generator_loss=26.33, generator_mel_loss=18.74, generator_kl_loss=1.2, generator_dur_loss=1.815, generator_adv_loss=1.967, generator_feat_match_loss=2.605, over 100.00 samples.
2024-03-12 17:21:29,267 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 17:21:38,849 INFO [train.py:919] (2/6) Start epoch 172
2024-03-12 17:24:09,810 INFO [train.py:527] (2/6) Epoch 172, batch 46, global_batch_idx: 21250, batch size: 48, loss[discriminator_loss=2.753, discriminator_real_loss=1.383, discriminator_fake_loss=1.371, generator_loss=27.19, generator_mel_loss=18.6, generator_kl_loss=1.384, generator_dur_loss=1.697, generator_adv_loss=1.83, generator_feat_match_loss=3.673, over 48.00 samples.], tot_loss[discriminator_loss=2.745, discriminator_real_loss=1.393, discriminator_fake_loss=1.351, generator_loss=27.26, generator_mel_loss=18.77, generator_kl_loss=1.392, generator_dur_loss=1.756, generator_adv_loss=1.902, generator_feat_match_loss=3.435, over 2677.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 17:26:25,269 INFO [train.py:527] (2/6) Epoch 172, batch 96, global_batch_idx: 21300, batch size: 13, loss[discriminator_loss=2.613, discriminator_real_loss=1.239, discriminator_fake_loss=1.375, generator_loss=27.87, generator_mel_loss=19.1, generator_kl_loss=1.841, generator_dur_loss=1.631, generator_adv_loss=2.048, generator_feat_match_loss=3.249, over 13.00 samples.], tot_loss[discriminator_loss=2.729, discriminator_real_loss=1.387, discriminator_fake_loss=1.343, generator_loss=27.38, generator_mel_loss=18.83, generator_kl_loss=1.416, generator_dur_loss=1.75, generator_adv_loss=1.91, generator_feat_match_loss=3.47, over 5236.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 17:27:43,062 INFO [train.py:919] (2/6) Start epoch 173
2024-03-12 17:29:08,009 INFO [train.py:527] (2/6) Epoch 173, batch 22, global_batch_idx: 21350, batch size: 53, loss[discriminator_loss=2.77, discriminator_real_loss=1.466, discriminator_fake_loss=1.305, generator_loss=26.66, generator_mel_loss=18.75, generator_kl_loss=1.394, generator_dur_loss=1.661, generator_adv_loss=1.805, generator_feat_match_loss=3.053, over 53.00 samples.], tot_loss[discriminator_loss=2.743, discriminator_real_loss=1.398, discriminator_fake_loss=1.345, generator_loss=27.41, generator_mel_loss=18.88, generator_kl_loss=1.39, generator_dur_loss=1.764, generator_adv_loss=1.922, generator_feat_match_loss=3.457, over 1210.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 17:31:29,537 INFO [train.py:527] (2/6) Epoch 173, batch 72, global_batch_idx: 21400, batch size: 96, loss[discriminator_loss=2.669, discriminator_real_loss=1.416, discriminator_fake_loss=1.253, generator_loss=26.5, generator_mel_loss=18.29, generator_kl_loss=1.19, generator_dur_loss=1.841, generator_adv_loss=1.79, generator_feat_match_loss=3.392, over 96.00 samples.], tot_loss[discriminator_loss=2.733, discriminator_real_loss=1.385, discriminator_fake_loss=1.348, generator_loss=27.36, generator_mel_loss=18.85, generator_kl_loss=1.374, generator_dur_loss=1.775, generator_adv_loss=1.914, generator_feat_match_loss=3.456, over 3982.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 17:31:29,538 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 17:31:37,517 INFO [train.py:591] (2/6) Epoch 173, validation: discriminator_loss=2.743, discriminator_real_loss=1.333, discriminator_fake_loss=1.41, generator_loss=26.61, generator_mel_loss=19, generator_kl_loss=1.281, generator_dur_loss=1.815, generator_adv_loss=1.698, generator_feat_match_loss=2.808, over 100.00 samples.
2024-03-12 17:31:37,518 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 17:33:54,524 INFO [train.py:527] (2/6) Epoch 173, batch 122, global_batch_idx: 21450, batch size: 58, loss[discriminator_loss=2.755, discriminator_real_loss=1.428, discriminator_fake_loss=1.326, generator_loss=27.43, generator_mel_loss=19.11, generator_kl_loss=1.439, generator_dur_loss=1.75, generator_adv_loss=1.761, generator_feat_match_loss=3.374, over 58.00 samples.], tot_loss[discriminator_loss=2.733, discriminator_real_loss=1.381, discriminator_fake_loss=1.351, generator_loss=27.41, generator_mel_loss=18.82, generator_kl_loss=1.385, generator_dur_loss=1.768, generator_adv_loss=1.928, generator_feat_match_loss=3.512, over 6668.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 17:33:59,467 INFO [train.py:919] (2/6) Start epoch 174
2024-03-12 17:36:37,021 INFO [train.py:527] (2/6) Epoch 174, batch 48, global_batch_idx: 21500, batch size: 36, loss[discriminator_loss=2.742, discriminator_real_loss=1.367, discriminator_fake_loss=1.374, generator_loss=26.92, generator_mel_loss=18.18, generator_kl_loss=1.607, generator_dur_loss=1.675, generator_adv_loss=1.867, generator_feat_match_loss=3.59, over 36.00 samples.], tot_loss[discriminator_loss=2.744, discriminator_real_loss=1.385, discriminator_fake_loss=1.359, generator_loss=27.24, generator_mel_loss=18.72, generator_kl_loss=1.388, generator_dur_loss=1.737, generator_adv_loss=1.899, generator_feat_match_loss=3.497, over 2683.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 17:38:55,035 INFO [train.py:527] (2/6) Epoch 174, batch 98, global_batch_idx: 21550, batch size: 56, loss[discriminator_loss=2.727, discriminator_real_loss=1.461, discriminator_fake_loss=1.265, generator_loss=27.77, generator_mel_loss=19.27, generator_kl_loss=1.265, generator_dur_loss=1.778, generator_adv_loss=1.884, generator_feat_match_loss=3.575, over 56.00 samples.], tot_loss[discriminator_loss=2.744, discriminator_real_loss=1.389, discriminator_fake_loss=1.355, generator_loss=27.28, generator_mel_loss=18.73, generator_kl_loss=1.383, generator_dur_loss=1.748, generator_adv_loss=1.907, generator_feat_match_loss=3.517, over 5528.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 17:40:01,665 INFO [train.py:919] (2/6) Start epoch 175
2024-03-12 17:41:32,581 INFO [train.py:527] (2/6) Epoch 175, batch 24, global_batch_idx: 21600, batch size: 52, loss[discriminator_loss=2.764, discriminator_real_loss=1.307, discriminator_fake_loss=1.458, generator_loss=28.05, generator_mel_loss=18.94, generator_kl_loss=1.536, generator_dur_loss=1.685, generator_adv_loss=2.126, generator_feat_match_loss=3.761, over 52.00 samples.], tot_loss[discriminator_loss=2.742, discriminator_real_loss=1.399, discriminator_fake_loss=1.344, generator_loss=27.38, generator_mel_loss=18.78, generator_kl_loss=1.417, generator_dur_loss=1.761, generator_adv_loss=1.918, generator_feat_match_loss=3.51, over 1233.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 17:41:32,583 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 17:41:40,573 INFO [train.py:591] (2/6) Epoch 175, validation: discriminator_loss=2.808, discriminator_real_loss=1.562, discriminator_fake_loss=1.246, generator_loss=26.82, generator_mel_loss=18.91, generator_kl_loss=1.191, generator_dur_loss=1.83, generator_adv_loss=2.054, generator_feat_match_loss=2.835, over 100.00 samples.
2024-03-12 17:41:40,574 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 17:44:02,847 INFO [train.py:527] (2/6) Epoch 175, batch 74, global_batch_idx: 21650, batch size: 45, loss[discriminator_loss=2.662, discriminator_real_loss=1.367, discriminator_fake_loss=1.295, generator_loss=28.05, generator_mel_loss=19.5, generator_kl_loss=1.463, generator_dur_loss=1.674, generator_adv_loss=1.808, generator_feat_match_loss=3.607, over 45.00 samples.], tot_loss[discriminator_loss=2.735, discriminator_real_loss=1.388, discriminator_fake_loss=1.347, generator_loss=27.3, generator_mel_loss=18.7, generator_kl_loss=1.393, generator_dur_loss=1.759, generator_adv_loss=1.918, generator_feat_match_loss=3.527, over 4132.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 17:46:18,020 INFO [train.py:919] (2/6) Start epoch 176
2024-03-12 17:46:42,003 INFO [train.py:527] (2/6) Epoch 176, batch 0, global_batch_idx: 21700, batch size: 52, loss[discriminator_loss=2.758, discriminator_real_loss=1.394, discriminator_fake_loss=1.363, generator_loss=28.27, generator_mel_loss=19.52, generator_kl_loss=1.495, generator_dur_loss=1.676, generator_adv_loss=2.173, generator_feat_match_loss=3.411, over 52.00 samples.], tot_loss[discriminator_loss=2.758, discriminator_real_loss=1.394, discriminator_fake_loss=1.363, generator_loss=28.27, generator_mel_loss=19.52, generator_kl_loss=1.495, generator_dur_loss=1.676, generator_adv_loss=2.173, generator_feat_match_loss=3.411, over 52.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 17:49:00,880 INFO [train.py:527] (2/6) Epoch 176, batch 50, global_batch_idx: 21750, batch size: 16, loss[discriminator_loss=2.78, discriminator_real_loss=1.423, discriminator_fake_loss=1.357, generator_loss=29.52, generator_mel_loss=20.25, generator_kl_loss=1.906, generator_dur_loss=1.607, generator_adv_loss=1.975, generator_feat_match_loss=3.774, over 16.00 samples.], tot_loss[discriminator_loss=2.738, discriminator_real_loss=1.38, discriminator_fake_loss=1.357, generator_loss=27.58, generator_mel_loss=18.91, generator_kl_loss=1.412, generator_dur_loss=1.749, generator_adv_loss=1.927, generator_feat_match_loss=3.581, over 2736.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 17:51:22,166 INFO [train.py:527] (2/6) Epoch 176, batch 100, global_batch_idx: 21800, batch size: 39, loss[discriminator_loss=2.939, discriminator_real_loss=1.621, discriminator_fake_loss=1.318, generator_loss=27.68, generator_mel_loss=18.69, generator_kl_loss=1.416, generator_dur_loss=1.717, generator_adv_loss=2.031, generator_feat_match_loss=3.823, over 39.00 samples.], tot_loss[discriminator_loss=2.747, discriminator_real_loss=1.389, discriminator_fake_loss=1.358, generator_loss=27.46, generator_mel_loss=18.85, generator_kl_loss=1.396, generator_dur_loss=1.767, generator_adv_loss=1.92, generator_feat_match_loss=3.532, over 5778.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 17:51:22,168 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 17:51:31,012 INFO [train.py:591] (2/6) Epoch 176, validation: discriminator_loss=2.772, discriminator_real_loss=1.518, discriminator_fake_loss=1.254, generator_loss=26.16, generator_mel_loss=18.47, generator_kl_loss=1.18, generator_dur_loss=1.799, generator_adv_loss=1.881, generator_feat_match_loss=2.832, over 100.00 samples.
2024-03-12 17:51:31,013 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 17:52:33,789 INFO [train.py:919] (2/6) Start epoch 177
2024-03-12 17:54:10,051 INFO [train.py:527] (2/6) Epoch 177, batch 26, global_batch_idx: 21850, batch size: 61, loss[discriminator_loss=2.737, discriminator_real_loss=1.334, discriminator_fake_loss=1.402, generator_loss=28.31, generator_mel_loss=19.06, generator_kl_loss=1.615, generator_dur_loss=1.759, generator_adv_loss=1.915, generator_feat_match_loss=3.96, over 61.00 samples.], tot_loss[discriminator_loss=2.743, discriminator_real_loss=1.405, discriminator_fake_loss=1.338, generator_loss=27.32, generator_mel_loss=18.7, generator_kl_loss=1.397, generator_dur_loss=1.768, generator_adv_loss=1.942, generator_feat_match_loss=3.517, over 1604.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 17:56:28,985 INFO [train.py:527] (2/6) Epoch 177, batch 76, global_batch_idx: 21900, batch size: 36, loss[discriminator_loss=2.807, discriminator_real_loss=1.4, discriminator_fake_loss=1.407, generator_loss=26.67, generator_mel_loss=18.31, generator_kl_loss=1.266, generator_dur_loss=1.797, generator_adv_loss=1.958, generator_feat_match_loss=3.344, over 36.00 samples.], tot_loss[discriminator_loss=2.74, discriminator_real_loss=1.396, discriminator_fake_loss=1.344, generator_loss=27.3, generator_mel_loss=18.7, generator_kl_loss=1.385, generator_dur_loss=1.765, generator_adv_loss=1.924, generator_feat_match_loss=3.521, over 4540.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 17:58:41,404 INFO [train.py:919] (2/6) Start epoch 178
2024-03-12 17:59:09,272 INFO [train.py:527] (2/6) Epoch 178, batch 2, global_batch_idx: 21950, batch size: 25, loss[discriminator_loss=2.75, discriminator_real_loss=1.372, discriminator_fake_loss=1.379, generator_loss=26.78, generator_mel_loss=18.63, generator_kl_loss=1.526, generator_dur_loss=1.593, generator_adv_loss=1.799, generator_feat_match_loss=3.232, over 25.00 samples.], tot_loss[discriminator_loss=2.743, discriminator_real_loss=1.407, discriminator_fake_loss=1.336, generator_loss=26.93, generator_mel_loss=18.58, generator_kl_loss=1.484, generator_dur_loss=1.71, generator_adv_loss=1.848, generator_feat_match_loss=3.307, over 112.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 18:01:30,775 INFO [train.py:527] (2/6) Epoch 178, batch 52, global_batch_idx: 22000, batch size: 72, loss[discriminator_loss=2.678, discriminator_real_loss=1.366, discriminator_fake_loss=1.312, generator_loss=26.94, generator_mel_loss=18.42, generator_kl_loss=1.31, generator_dur_loss=1.818, generator_adv_loss=1.813, generator_feat_match_loss=3.578, over 72.00 samples.], tot_loss[discriminator_loss=2.714, discriminator_real_loss=1.366, discriminator_fake_loss=1.348, generator_loss=27.46, generator_mel_loss=18.77, generator_kl_loss=1.394, generator_dur_loss=1.743, generator_adv_loss=1.923, generator_feat_match_loss=3.633, over 2903.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 18:01:30,777 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 18:01:38,782 INFO [train.py:591] (2/6) Epoch 178, validation: discriminator_loss=2.709, discriminator_real_loss=1.303, discriminator_fake_loss=1.406, generator_loss=26.32, generator_mel_loss=18.65, generator_kl_loss=1.19, generator_dur_loss=1.805, generator_adv_loss=1.767, generator_feat_match_loss=2.913, over 100.00 samples.
2024-03-12 18:01:38,783 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 18:03:57,045 INFO [train.py:527] (2/6) Epoch 178, batch 102, global_batch_idx: 22050, batch size: 64, loss[discriminator_loss=2.721, discriminator_real_loss=1.425, discriminator_fake_loss=1.296, generator_loss=27.38, generator_mel_loss=18.9, generator_kl_loss=1.344, generator_dur_loss=1.779, generator_adv_loss=1.726, generator_feat_match_loss=3.637, over 64.00 samples.], tot_loss[discriminator_loss=2.724, discriminator_real_loss=1.375, discriminator_fake_loss=1.349, generator_loss=27.4, generator_mel_loss=18.76, generator_kl_loss=1.407, generator_dur_loss=1.738, generator_adv_loss=1.917, generator_feat_match_loss=3.58, over 5620.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 18:04:55,653 INFO [train.py:919] (2/6) Start epoch 179
2024-03-12 18:06:36,860 INFO [train.py:527] (2/6) Epoch 179, batch 28, global_batch_idx: 22100, batch size: 59, loss[discriminator_loss=2.879, discriminator_real_loss=1.616, discriminator_fake_loss=1.263, generator_loss=27.41, generator_mel_loss=18.89, generator_kl_loss=1.627, generator_dur_loss=1.701, generator_adv_loss=1.75, generator_feat_match_loss=3.446, over 59.00 samples.], tot_loss[discriminator_loss=2.744, discriminator_real_loss=1.381, discriminator_fake_loss=1.363, generator_loss=27.26, generator_mel_loss=18.63, generator_kl_loss=1.385, generator_dur_loss=1.77, generator_adv_loss=1.94, generator_feat_match_loss=3.542, over 1693.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 18:08:55,011 INFO [train.py:527] (2/6) Epoch 179, batch 78, global_batch_idx: 22150, batch size: 72, loss[discriminator_loss=2.696, discriminator_real_loss=1.376, discriminator_fake_loss=1.32, generator_loss=27.22, generator_mel_loss=18.8, generator_kl_loss=1.392, generator_dur_loss=1.76, generator_adv_loss=1.837, generator_feat_match_loss=3.43, over 72.00 samples.], tot_loss[discriminator_loss=2.743, discriminator_real_loss=1.393, discriminator_fake_loss=1.351, generator_loss=27.37, generator_mel_loss=18.71, generator_kl_loss=1.396, generator_dur_loss=1.762, generator_adv_loss=1.944, generator_feat_match_loss=3.55, over 4522.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 18:11:02,001 INFO [train.py:919] (2/6) Start epoch 180
2024-03-12 18:11:35,681 INFO [train.py:527] (2/6) Epoch 180, batch 4, global_batch_idx: 22200, batch size: 83, loss[discriminator_loss=2.768, discriminator_real_loss=1.362, discriminator_fake_loss=1.406, generator_loss=25.9, generator_mel_loss=18.1, generator_kl_loss=1.267, generator_dur_loss=1.869, generator_adv_loss=1.73, generator_feat_match_loss=2.932, over 83.00 samples.], tot_loss[discriminator_loss=2.808, discriminator_real_loss=1.43, discriminator_fake_loss=1.378, generator_loss=26.78, generator_mel_loss=18.48, generator_kl_loss=1.385, generator_dur_loss=1.782, generator_adv_loss=1.84, generator_feat_match_loss=3.287, over 297.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 18:11:35,683 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 18:11:43,426 INFO [train.py:591] (2/6) Epoch 180, validation: discriminator_loss=2.791, discriminator_real_loss=1.35, discriminator_fake_loss=1.44, generator_loss=25.83, generator_mel_loss=18.47, generator_kl_loss=1.269, generator_dur_loss=1.814, generator_adv_loss=1.689, generator_feat_match_loss=2.591, over 100.00 samples.
2024-03-12 18:11:43,429 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 18:14:02,376 INFO [train.py:527] (2/6) Epoch 180, batch 54, global_batch_idx: 22250, batch size: 68, loss[discriminator_loss=2.815, discriminator_real_loss=1.386, discriminator_fake_loss=1.429, generator_loss=27.27, generator_mel_loss=18.62, generator_kl_loss=1.391, generator_dur_loss=1.755, generator_adv_loss=1.947, generator_feat_match_loss=3.555, over 68.00 samples.], tot_loss[discriminator_loss=2.748, discriminator_real_loss=1.39, discriminator_fake_loss=1.358, generator_loss=27.28, generator_mel_loss=18.73, generator_kl_loss=1.375, generator_dur_loss=1.749, generator_adv_loss=1.896, generator_feat_match_loss=3.535, over 3131.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 18:16:22,259 INFO [train.py:527] (2/6) Epoch 180, batch 104, global_batch_idx: 22300, batch size: 96, loss[discriminator_loss=2.726, discriminator_real_loss=1.348, discriminator_fake_loss=1.378, generator_loss=27.4, generator_mel_loss=18.71, generator_kl_loss=1.311, generator_dur_loss=1.853, generator_adv_loss=1.884, generator_feat_match_loss=3.647, over 96.00 samples.], tot_loss[discriminator_loss=2.742, discriminator_real_loss=1.389, discriminator_fake_loss=1.353, generator_loss=27.34, generator_mel_loss=18.73, generator_kl_loss=1.381, generator_dur_loss=1.751, generator_adv_loss=1.911, generator_feat_match_loss=3.566, over 6148.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 18:17:13,583 INFO [train.py:919] (2/6) Start epoch 181
2024-03-12 18:19:03,212 INFO [train.py:527] (2/6) Epoch 181, batch 30, global_batch_idx: 22350, batch size: 77, loss[discriminator_loss=2.729, discriminator_real_loss=1.471, discriminator_fake_loss=1.258, generator_loss=27.61, generator_mel_loss=18.57, generator_kl_loss=1.411, generator_dur_loss=1.833, generator_adv_loss=2.036, generator_feat_match_loss=3.753, over 77.00 samples.], tot_loss[discriminator_loss=2.731, discriminator_real_loss=1.373, discriminator_fake_loss=1.358, generator_loss=27.62, generator_mel_loss=18.85, generator_kl_loss=1.44, generator_dur_loss=1.762, generator_adv_loss=1.926, generator_feat_match_loss=3.634, over 1712.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 18:21:23,378 INFO [train.py:527] (2/6) Epoch 181, batch 80, global_batch_idx: 22400, batch size: 68, loss[discriminator_loss=2.812, discriminator_real_loss=1.414, discriminator_fake_loss=1.398, generator_loss=27.61, generator_mel_loss=19.23, generator_kl_loss=1.348, generator_dur_loss=1.818, generator_adv_loss=1.897, generator_feat_match_loss=3.317, over 68.00 samples.], tot_loss[discriminator_loss=2.743, discriminator_real_loss=1.389, discriminator_fake_loss=1.354, generator_loss=27.48, generator_mel_loss=18.78, generator_kl_loss=1.397, generator_dur_loss=1.768, generator_adv_loss=1.942, generator_feat_match_loss=3.596, over 4686.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 18:21:23,379 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 18:21:31,724 INFO [train.py:591] (2/6) Epoch 181, validation: discriminator_loss=2.819, discriminator_real_loss=1.557, discriminator_fake_loss=1.263, generator_loss=26.69, generator_mel_loss=18.85, generator_kl_loss=1.198, generator_dur_loss=1.781, generator_adv_loss=1.944, generator_feat_match_loss=2.917, over 100.00 samples.
2024-03-12 18:21:31,725 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 18:23:28,336 INFO [train.py:919] (2/6) Start epoch 182
2024-03-12 18:24:07,823 INFO [train.py:527] (2/6) Epoch 182, batch 6, global_batch_idx: 22450, batch size: 88, loss[discriminator_loss=2.781, discriminator_real_loss=1.471, discriminator_fake_loss=1.31, generator_loss=26.94, generator_mel_loss=18.68, generator_kl_loss=1.289, generator_dur_loss=1.889, generator_adv_loss=1.723, generator_feat_match_loss=3.366, over 88.00 samples.], tot_loss[discriminator_loss=2.77, discriminator_real_loss=1.416, discriminator_fake_loss=1.354, generator_loss=27.24, generator_mel_loss=18.81, generator_kl_loss=1.37, generator_dur_loss=1.768, generator_adv_loss=1.853, generator_feat_match_loss=3.436, over 422.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 18:26:28,687 INFO [train.py:527] (2/6) Epoch 182, batch 56, global_batch_idx: 22500, batch size: 72, loss[discriminator_loss=2.75, discriminator_real_loss=1.427, discriminator_fake_loss=1.323, generator_loss=27.74, generator_mel_loss=18.95, generator_kl_loss=1.395, generator_dur_loss=1.785, generator_adv_loss=1.865, generator_feat_match_loss=3.738, over 72.00 samples.], tot_loss[discriminator_loss=2.751, discriminator_real_loss=1.388, discriminator_fake_loss=1.363, generator_loss=27.33, generator_mel_loss=18.74, generator_kl_loss=1.38, generator_dur_loss=1.774, generator_adv_loss=1.895, generator_feat_match_loss=3.539, over 3431.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 18:28:47,528 INFO [train.py:527] (2/6) Epoch 182, batch 106, global_batch_idx: 22550, batch size: 45, loss[discriminator_loss=2.603, discriminator_real_loss=1.29, discriminator_fake_loss=1.313, generator_loss=29.01, generator_mel_loss=19.72, generator_kl_loss=1.42, generator_dur_loss=1.701, generator_adv_loss=1.848, generator_feat_match_loss=4.323, over 45.00 samples.], tot_loss[discriminator_loss=2.742, discriminator_real_loss=1.383, discriminator_fake_loss=1.358, generator_loss=27.41, generator_mel_loss=18.75, generator_kl_loss=1.393, generator_dur_loss=1.766, generator_adv_loss=1.915, generator_feat_match_loss=3.581, over 6158.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 18:29:34,519 INFO [train.py:919] (2/6) Start epoch 183
2024-03-12 18:31:27,932 INFO [train.py:527] (2/6) Epoch 183, batch 32, global_batch_idx: 22600, batch size: 25, loss[discriminator_loss=2.627, discriminator_real_loss=1.407, discriminator_fake_loss=1.22, generator_loss=28.73, generator_mel_loss=19.54, generator_kl_loss=1.772, generator_dur_loss=1.582, generator_adv_loss=1.949, generator_feat_match_loss=3.889, over 25.00 samples.], tot_loss[discriminator_loss=2.737, discriminator_real_loss=1.384, discriminator_fake_loss=1.353, generator_loss=27.19, generator_mel_loss=18.63, generator_kl_loss=1.372, generator_dur_loss=1.774, generator_adv_loss=1.931, generator_feat_match_loss=3.486, over 2043.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 18:31:27,933 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 18:31:35,883 INFO [train.py:591] (2/6) Epoch 183, validation: discriminator_loss=2.735, discriminator_real_loss=1.413, discriminator_fake_loss=1.323, generator_loss=27.1, generator_mel_loss=19, generator_kl_loss=1.172, generator_dur_loss=1.819, generator_adv_loss=1.838, generator_feat_match_loss=3.275, over 100.00 samples.
2024-03-12 18:31:35,884 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 18:33:56,371 INFO [train.py:527] (2/6) Epoch 183, batch 82, global_batch_idx: 22650, batch size: 70, loss[discriminator_loss=2.751, discriminator_real_loss=1.351, discriminator_fake_loss=1.4, generator_loss=28.24, generator_mel_loss=19.14, generator_kl_loss=1.435, generator_dur_loss=1.785, generator_adv_loss=2.004, generator_feat_match_loss=3.873, over 70.00 samples.], tot_loss[discriminator_loss=2.743, discriminator_real_loss=1.392, discriminator_fake_loss=1.351, generator_loss=27.33, generator_mel_loss=18.72, generator_kl_loss=1.383, generator_dur_loss=1.772, generator_adv_loss=1.924, generator_feat_match_loss=3.53, over 5066.00 samples.], cur_lr_g: 1.96e-04, cur_lr_d: 1.96e-04, 
2024-03-12 18:35:50,161 INFO [train.py:919] (2/6) Start epoch 184
2024-03-12 18:36:35,622 INFO [train.py:527] (2/6) Epoch 184, batch 8, global_batch_idx: 22700, batch size: 68, loss[discriminator_loss=2.774, discriminator_real_loss=1.421, discriminator_fake_loss=1.353, generator_loss=26.81, generator_mel_loss=18.31, generator_kl_loss=1.32, generator_dur_loss=1.823, generator_adv_loss=1.904, generator_feat_match_loss=3.453, over 68.00 samples.], tot_loss[discriminator_loss=2.736, discriminator_real_loss=1.412, discriminator_fake_loss=1.324, generator_loss=27.47, generator_mel_loss=18.71, generator_kl_loss=1.441, generator_dur_loss=1.758, generator_adv_loss=1.954, generator_feat_match_loss=3.601, over 483.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 18:38:51,539 INFO [train.py:527] (2/6) Epoch 184, batch 58, global_batch_idx: 22750, batch size: 68, loss[discriminator_loss=2.754, discriminator_real_loss=1.412, discriminator_fake_loss=1.342, generator_loss=26.84, generator_mel_loss=18.49, generator_kl_loss=1.363, generator_dur_loss=1.731, generator_adv_loss=2.09, generator_feat_match_loss=3.16, over 68.00 samples.], tot_loss[discriminator_loss=2.751, discriminator_real_loss=1.396, discriminator_fake_loss=1.355, generator_loss=27.42, generator_mel_loss=18.76, generator_kl_loss=1.416, generator_dur_loss=1.741, generator_adv_loss=1.942, generator_feat_match_loss=3.553, over 3325.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 18:41:09,962 INFO [train.py:527] (2/6) Epoch 184, batch 108, global_batch_idx: 22800, batch size: 59, loss[discriminator_loss=2.765, discriminator_real_loss=1.323, discriminator_fake_loss=1.442, generator_loss=28.08, generator_mel_loss=19.02, generator_kl_loss=1.446, generator_dur_loss=1.722, generator_adv_loss=2.087, generator_feat_match_loss=3.802, over 59.00 samples.], tot_loss[discriminator_loss=2.747, discriminator_real_loss=1.392, discriminator_fake_loss=1.355, generator_loss=27.33, generator_mel_loss=18.71, generator_kl_loss=1.389, generator_dur_loss=1.761, generator_adv_loss=1.924, generator_feat_match_loss=3.544, over 6394.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 18:41:09,964 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 18:41:18,937 INFO [train.py:591] (2/6) Epoch 184, validation: discriminator_loss=2.867, discriminator_real_loss=1.662, discriminator_fake_loss=1.205, generator_loss=26.73, generator_mel_loss=19.04, generator_kl_loss=1.196, generator_dur_loss=1.823, generator_adv_loss=2.106, generator_feat_match_loss=2.571, over 100.00 samples.
2024-03-12 18:41:18,937 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 18:42:02,902 INFO [train.py:919] (2/6) Start epoch 185
2024-03-12 18:44:00,278 INFO [train.py:527] (2/6) Epoch 185, batch 34, global_batch_idx: 22850, batch size: 70, loss[discriminator_loss=2.75, discriminator_real_loss=1.528, discriminator_fake_loss=1.222, generator_loss=27.13, generator_mel_loss=18.49, generator_kl_loss=1.248, generator_dur_loss=1.854, generator_adv_loss=1.994, generator_feat_match_loss=3.549, over 70.00 samples.], tot_loss[discriminator_loss=2.759, discriminator_real_loss=1.406, discriminator_fake_loss=1.354, generator_loss=27.31, generator_mel_loss=18.69, generator_kl_loss=1.401, generator_dur_loss=1.762, generator_adv_loss=1.918, generator_feat_match_loss=3.543, over 2055.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 18:46:18,236 INFO [train.py:527] (2/6) Epoch 185, batch 84, global_batch_idx: 22900, batch size: 42, loss[discriminator_loss=2.665, discriminator_real_loss=1.347, discriminator_fake_loss=1.319, generator_loss=28.18, generator_mel_loss=18.94, generator_kl_loss=1.505, generator_dur_loss=1.679, generator_adv_loss=1.712, generator_feat_match_loss=4.349, over 42.00 samples.], tot_loss[discriminator_loss=2.749, discriminator_real_loss=1.395, discriminator_fake_loss=1.354, generator_loss=27.33, generator_mel_loss=18.71, generator_kl_loss=1.409, generator_dur_loss=1.759, generator_adv_loss=1.902, generator_feat_match_loss=3.549, over 4797.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 18:48:08,509 INFO [train.py:919] (2/6) Start epoch 186
2024-03-12 18:49:00,477 INFO [train.py:527] (2/6) Epoch 186, batch 10, global_batch_idx: 22950, batch size: 68, loss[discriminator_loss=2.713, discriminator_real_loss=1.461, discriminator_fake_loss=1.252, generator_loss=27.97, generator_mel_loss=18.69, generator_kl_loss=1.465, generator_dur_loss=1.822, generator_adv_loss=2.308, generator_feat_match_loss=3.684, over 68.00 samples.], tot_loss[discriminator_loss=2.731, discriminator_real_loss=1.355, discriminator_fake_loss=1.376, generator_loss=27.41, generator_mel_loss=18.65, generator_kl_loss=1.386, generator_dur_loss=1.779, generator_adv_loss=1.972, generator_feat_match_loss=3.622, over 687.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 18:51:17,449 INFO [train.py:527] (2/6) Epoch 186, batch 60, global_batch_idx: 23000, batch size: 44, loss[discriminator_loss=2.773, discriminator_real_loss=1.443, discriminator_fake_loss=1.33, generator_loss=26.94, generator_mel_loss=18.42, generator_kl_loss=1.437, generator_dur_loss=1.712, generator_adv_loss=1.777, generator_feat_match_loss=3.597, over 44.00 samples.], tot_loss[discriminator_loss=2.738, discriminator_real_loss=1.387, discriminator_fake_loss=1.351, generator_loss=27.44, generator_mel_loss=18.75, generator_kl_loss=1.41, generator_dur_loss=1.764, generator_adv_loss=1.931, generator_feat_match_loss=3.582, over 3404.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 18:51:17,451 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 18:51:25,374 INFO [train.py:591] (2/6) Epoch 186, validation: discriminator_loss=2.794, discriminator_real_loss=1.451, discriminator_fake_loss=1.344, generator_loss=26.57, generator_mel_loss=18.9, generator_kl_loss=1.241, generator_dur_loss=1.796, generator_adv_loss=1.81, generator_feat_match_loss=2.816, over 100.00 samples.
2024-03-12 18:51:25,375 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 18:53:42,536 INFO [train.py:527] (2/6) Epoch 186, batch 110, global_batch_idx: 23050, batch size: 62, loss[discriminator_loss=2.76, discriminator_real_loss=1.416, discriminator_fake_loss=1.344, generator_loss=27.86, generator_mel_loss=19, generator_kl_loss=1.386, generator_dur_loss=1.817, generator_adv_loss=1.862, generator_feat_match_loss=3.793, over 62.00 samples.], tot_loss[discriminator_loss=2.737, discriminator_real_loss=1.388, discriminator_fake_loss=1.349, generator_loss=27.43, generator_mel_loss=18.77, generator_kl_loss=1.419, generator_dur_loss=1.756, generator_adv_loss=1.925, generator_feat_match_loss=3.56, over 6188.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 18:54:20,728 INFO [train.py:919] (2/6) Start epoch 187
2024-03-12 18:56:22,601 INFO [train.py:527] (2/6) Epoch 187, batch 36, global_batch_idx: 23100, batch size: 45, loss[discriminator_loss=2.783, discriminator_real_loss=1.354, discriminator_fake_loss=1.428, generator_loss=28.12, generator_mel_loss=19.17, generator_kl_loss=1.526, generator_dur_loss=1.663, generator_adv_loss=2.081, generator_feat_match_loss=3.683, over 45.00 samples.], tot_loss[discriminator_loss=2.735, discriminator_real_loss=1.38, discriminator_fake_loss=1.356, generator_loss=27.51, generator_mel_loss=18.81, generator_kl_loss=1.39, generator_dur_loss=1.749, generator_adv_loss=1.962, generator_feat_match_loss=3.601, over 2075.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 18:58:38,483 INFO [train.py:527] (2/6) Epoch 187, batch 86, global_batch_idx: 23150, batch size: 56, loss[discriminator_loss=2.722, discriminator_real_loss=1.383, discriminator_fake_loss=1.338, generator_loss=27.3, generator_mel_loss=18.45, generator_kl_loss=1.47, generator_dur_loss=1.711, generator_adv_loss=2.029, generator_feat_match_loss=3.639, over 56.00 samples.], tot_loss[discriminator_loss=2.73, discriminator_real_loss=1.383, discriminator_fake_loss=1.347, generator_loss=27.41, generator_mel_loss=18.74, generator_kl_loss=1.395, generator_dur_loss=1.743, generator_adv_loss=1.934, generator_feat_match_loss=3.606, over 4972.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 19:00:23,593 INFO [train.py:919] (2/6) Start epoch 188
2024-03-12 19:01:22,027 INFO [train.py:527] (2/6) Epoch 188, batch 12, global_batch_idx: 23200, batch size: 47, loss[discriminator_loss=2.753, discriminator_real_loss=1.389, discriminator_fake_loss=1.364, generator_loss=27.92, generator_mel_loss=19.14, generator_kl_loss=1.596, generator_dur_loss=1.698, generator_adv_loss=1.942, generator_feat_match_loss=3.545, over 47.00 samples.], tot_loss[discriminator_loss=2.773, discriminator_real_loss=1.411, discriminator_fake_loss=1.362, generator_loss=27.35, generator_mel_loss=18.78, generator_kl_loss=1.41, generator_dur_loss=1.719, generator_adv_loss=1.913, generator_feat_match_loss=3.525, over 687.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 19:01:22,029 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 19:01:30,005 INFO [train.py:591] (2/6) Epoch 188, validation: discriminator_loss=2.763, discriminator_real_loss=1.442, discriminator_fake_loss=1.321, generator_loss=26.05, generator_mel_loss=18.39, generator_kl_loss=1.334, generator_dur_loss=1.8, generator_adv_loss=1.876, generator_feat_match_loss=2.644, over 100.00 samples.
2024-03-12 19:01:30,006 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 19:03:48,367 INFO [train.py:527] (2/6) Epoch 188, batch 62, global_batch_idx: 23250, batch size: 52, loss[discriminator_loss=2.777, discriminator_real_loss=1.398, discriminator_fake_loss=1.379, generator_loss=26.45, generator_mel_loss=18.57, generator_kl_loss=1.397, generator_dur_loss=1.683, generator_adv_loss=1.866, generator_feat_match_loss=2.934, over 52.00 samples.], tot_loss[discriminator_loss=2.753, discriminator_real_loss=1.399, discriminator_fake_loss=1.354, generator_loss=27.31, generator_mel_loss=18.74, generator_kl_loss=1.409, generator_dur_loss=1.73, generator_adv_loss=1.907, generator_feat_match_loss=3.528, over 3481.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 19:06:09,599 INFO [train.py:527] (2/6) Epoch 188, batch 112, global_batch_idx: 23300, batch size: 44, loss[discriminator_loss=2.735, discriminator_real_loss=1.17, discriminator_fake_loss=1.565, generator_loss=27.69, generator_mel_loss=18.93, generator_kl_loss=1.414, generator_dur_loss=1.723, generator_adv_loss=1.98, generator_feat_match_loss=3.639, over 44.00 samples.], tot_loss[discriminator_loss=2.743, discriminator_real_loss=1.385, discriminator_fake_loss=1.357, generator_loss=27.35, generator_mel_loss=18.7, generator_kl_loss=1.393, generator_dur_loss=1.748, generator_adv_loss=1.914, generator_feat_match_loss=3.59, over 6535.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 19:06:41,205 INFO [train.py:919] (2/6) Start epoch 189
2024-03-12 19:08:53,189 INFO [train.py:527] (2/6) Epoch 189, batch 38, global_batch_idx: 23350, batch size: 44, loss[discriminator_loss=2.676, discriminator_real_loss=1.343, discriminator_fake_loss=1.334, generator_loss=27.88, generator_mel_loss=18.96, generator_kl_loss=1.546, generator_dur_loss=1.689, generator_adv_loss=1.825, generator_feat_match_loss=3.864, over 44.00 samples.], tot_loss[discriminator_loss=2.758, discriminator_real_loss=1.405, discriminator_fake_loss=1.353, generator_loss=27.25, generator_mel_loss=18.66, generator_kl_loss=1.416, generator_dur_loss=1.766, generator_adv_loss=1.928, generator_feat_match_loss=3.475, over 2121.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 19:11:15,674 INFO [train.py:527] (2/6) Epoch 189, batch 88, global_batch_idx: 23400, batch size: 72, loss[discriminator_loss=2.751, discriminator_real_loss=1.414, discriminator_fake_loss=1.337, generator_loss=27.36, generator_mel_loss=18.81, generator_kl_loss=1.379, generator_dur_loss=1.805, generator_adv_loss=2.006, generator_feat_match_loss=3.359, over 72.00 samples.], tot_loss[discriminator_loss=2.753, discriminator_real_loss=1.399, discriminator_fake_loss=1.354, generator_loss=27.28, generator_mel_loss=18.65, generator_kl_loss=1.397, generator_dur_loss=1.771, generator_adv_loss=1.911, generator_feat_match_loss=3.548, over 5110.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 19:11:15,675 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 19:11:23,873 INFO [train.py:591] (2/6) Epoch 189, validation: discriminator_loss=2.761, discriminator_real_loss=1.482, discriminator_fake_loss=1.279, generator_loss=27.2, generator_mel_loss=18.92, generator_kl_loss=1.165, generator_dur_loss=1.831, generator_adv_loss=1.969, generator_feat_match_loss=3.312, over 100.00 samples.
2024-03-12 19:11:23,874 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 19:12:58,414 INFO [train.py:919] (2/6) Start epoch 190
2024-03-12 19:14:01,702 INFO [train.py:527] (2/6) Epoch 190, batch 14, global_batch_idx: 23450, batch size: 68, loss[discriminator_loss=2.798, discriminator_real_loss=1.341, discriminator_fake_loss=1.457, generator_loss=27.25, generator_mel_loss=18.62, generator_kl_loss=1.311, generator_dur_loss=1.799, generator_adv_loss=1.991, generator_feat_match_loss=3.533, over 68.00 samples.], tot_loss[discriminator_loss=2.76, discriminator_real_loss=1.398, discriminator_fake_loss=1.362, generator_loss=27.52, generator_mel_loss=18.82, generator_kl_loss=1.381, generator_dur_loss=1.758, generator_adv_loss=1.982, generator_feat_match_loss=3.584, over 824.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 19:16:20,342 INFO [train.py:527] (2/6) Epoch 190, batch 64, global_batch_idx: 23500, batch size: 83, loss[discriminator_loss=2.738, discriminator_real_loss=1.361, discriminator_fake_loss=1.377, generator_loss=27.43, generator_mel_loss=18.67, generator_kl_loss=1.289, generator_dur_loss=1.832, generator_adv_loss=1.834, generator_feat_match_loss=3.813, over 83.00 samples.], tot_loss[discriminator_loss=2.73, discriminator_real_loss=1.388, discriminator_fake_loss=1.342, generator_loss=27.48, generator_mel_loss=18.78, generator_kl_loss=1.368, generator_dur_loss=1.761, generator_adv_loss=1.925, generator_feat_match_loss=3.645, over 3652.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 19:18:39,707 INFO [train.py:527] (2/6) Epoch 190, batch 114, global_batch_idx: 23550, batch size: 17, loss[discriminator_loss=2.806, discriminator_real_loss=1.465, discriminator_fake_loss=1.341, generator_loss=26.4, generator_mel_loss=17.93, generator_kl_loss=1.647, generator_dur_loss=1.63, generator_adv_loss=1.874, generator_feat_match_loss=3.321, over 17.00 samples.], tot_loss[discriminator_loss=2.739, discriminator_real_loss=1.392, discriminator_fake_loss=1.347, generator_loss=27.45, generator_mel_loss=18.78, generator_kl_loss=1.375, generator_dur_loss=1.761, generator_adv_loss=1.921, generator_feat_match_loss=3.612, over 6426.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 19:19:03,952 INFO [train.py:919] (2/6) Start epoch 191
2024-03-12 19:21:21,799 INFO [train.py:527] (2/6) Epoch 191, batch 40, global_batch_idx: 23600, batch size: 45, loss[discriminator_loss=2.755, discriminator_real_loss=1.34, discriminator_fake_loss=1.415, generator_loss=28.33, generator_mel_loss=19.35, generator_kl_loss=1.495, generator_dur_loss=1.676, generator_adv_loss=2.091, generator_feat_match_loss=3.714, over 45.00 samples.], tot_loss[discriminator_loss=2.736, discriminator_real_loss=1.389, discriminator_fake_loss=1.347, generator_loss=27.43, generator_mel_loss=18.76, generator_kl_loss=1.418, generator_dur_loss=1.694, generator_adv_loss=1.917, generator_feat_match_loss=3.641, over 2317.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 19:21:21,800 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 19:21:29,539 INFO [train.py:591] (2/6) Epoch 191, validation: discriminator_loss=2.788, discriminator_real_loss=1.5, discriminator_fake_loss=1.288, generator_loss=26.94, generator_mel_loss=18.69, generator_kl_loss=1.259, generator_dur_loss=1.796, generator_adv_loss=2.027, generator_feat_match_loss=3.167, over 100.00 samples.
2024-03-12 19:21:29,540 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 19:23:48,615 INFO [train.py:527] (2/6) Epoch 191, batch 90, global_batch_idx: 23650, batch size: 77, loss[discriminator_loss=2.783, discriminator_real_loss=1.472, discriminator_fake_loss=1.311, generator_loss=26.56, generator_mel_loss=18.2, generator_kl_loss=1.308, generator_dur_loss=1.83, generator_adv_loss=1.864, generator_feat_match_loss=3.36, over 77.00 samples.], tot_loss[discriminator_loss=2.746, discriminator_real_loss=1.393, discriminator_fake_loss=1.353, generator_loss=27.34, generator_mel_loss=18.69, generator_kl_loss=1.393, generator_dur_loss=1.728, generator_adv_loss=1.918, generator_feat_match_loss=3.605, over 5269.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 19:25:17,560 INFO [train.py:919] (2/6) Start epoch 192
2024-03-12 19:26:26,509 INFO [train.py:527] (2/6) Epoch 192, batch 16, global_batch_idx: 23700, batch size: 45, loss[discriminator_loss=2.741, discriminator_real_loss=1.378, discriminator_fake_loss=1.362, generator_loss=27.32, generator_mel_loss=18.13, generator_kl_loss=1.646, generator_dur_loss=1.681, generator_adv_loss=2.023, generator_feat_match_loss=3.842, over 45.00 samples.], tot_loss[discriminator_loss=2.728, discriminator_real_loss=1.381, discriminator_fake_loss=1.347, generator_loss=27.29, generator_mel_loss=18.6, generator_kl_loss=1.392, generator_dur_loss=1.769, generator_adv_loss=1.933, generator_feat_match_loss=3.591, over 1054.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 19:28:41,799 INFO [train.py:527] (2/6) Epoch 192, batch 66, global_batch_idx: 23750, batch size: 64, loss[discriminator_loss=2.758, discriminator_real_loss=1.415, discriminator_fake_loss=1.343, generator_loss=27.04, generator_mel_loss=18.9, generator_kl_loss=1.293, generator_dur_loss=1.776, generator_adv_loss=1.807, generator_feat_match_loss=3.263, over 64.00 samples.], tot_loss[discriminator_loss=2.742, discriminator_real_loss=1.391, discriminator_fake_loss=1.35, generator_loss=27.28, generator_mel_loss=18.68, generator_kl_loss=1.401, generator_dur_loss=1.762, generator_adv_loss=1.906, generator_feat_match_loss=3.533, over 3769.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 19:31:01,602 INFO [train.py:527] (2/6) Epoch 192, batch 116, global_batch_idx: 23800, batch size: 88, loss[discriminator_loss=2.758, discriminator_real_loss=1.436, discriminator_fake_loss=1.323, generator_loss=27.34, generator_mel_loss=18.44, generator_kl_loss=1.298, generator_dur_loss=1.84, generator_adv_loss=1.805, generator_feat_match_loss=3.948, over 88.00 samples.], tot_loss[discriminator_loss=2.739, discriminator_real_loss=1.387, discriminator_fake_loss=1.352, generator_loss=27.33, generator_mel_loss=18.65, generator_kl_loss=1.401, generator_dur_loss=1.768, generator_adv_loss=1.911, generator_feat_match_loss=3.595, over 6654.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 19:31:01,604 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 19:31:10,676 INFO [train.py:591] (2/6) Epoch 192, validation: discriminator_loss=2.816, discriminator_real_loss=1.43, discriminator_fake_loss=1.386, generator_loss=25.78, generator_mel_loss=18.34, generator_kl_loss=1.284, generator_dur_loss=1.825, generator_adv_loss=1.748, generator_feat_match_loss=2.581, over 100.00 samples.
2024-03-12 19:31:10,677 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 19:31:32,710 INFO [train.py:919] (2/6) Start epoch 193
2024-03-12 19:33:52,772 INFO [train.py:527] (2/6) Epoch 193, batch 42, global_batch_idx: 23850, batch size: 36, loss[discriminator_loss=2.67, discriminator_real_loss=1.39, discriminator_fake_loss=1.28, generator_loss=28.24, generator_mel_loss=19.02, generator_kl_loss=1.52, generator_dur_loss=1.753, generator_adv_loss=1.851, generator_feat_match_loss=4.101, over 36.00 samples.], tot_loss[discriminator_loss=2.736, discriminator_real_loss=1.391, discriminator_fake_loss=1.345, generator_loss=27.38, generator_mel_loss=18.69, generator_kl_loss=1.367, generator_dur_loss=1.76, generator_adv_loss=1.943, generator_feat_match_loss=3.629, over 2464.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 19:36:10,095 INFO [train.py:527] (2/6) Epoch 193, batch 92, global_batch_idx: 23900, batch size: 88, loss[discriminator_loss=2.752, discriminator_real_loss=1.284, discriminator_fake_loss=1.467, generator_loss=27.54, generator_mel_loss=19.04, generator_kl_loss=1.126, generator_dur_loss=1.834, generator_adv_loss=1.778, generator_feat_match_loss=3.759, over 88.00 samples.], tot_loss[discriminator_loss=2.737, discriminator_real_loss=1.389, discriminator_fake_loss=1.349, generator_loss=27.39, generator_mel_loss=18.69, generator_kl_loss=1.391, generator_dur_loss=1.75, generator_adv_loss=1.932, generator_feat_match_loss=3.622, over 5169.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 19:37:38,312 INFO [train.py:919] (2/6) Start epoch 194
2024-03-12 19:38:53,574 INFO [train.py:527] (2/6) Epoch 194, batch 18, global_batch_idx: 23950, batch size: 14, loss[discriminator_loss=2.768, discriminator_real_loss=1.299, discriminator_fake_loss=1.469, generator_loss=28.78, generator_mel_loss=19.65, generator_kl_loss=1.799, generator_dur_loss=1.59, generator_adv_loss=2.081, generator_feat_match_loss=3.656, over 14.00 samples.], tot_loss[discriminator_loss=2.738, discriminator_real_loss=1.381, discriminator_fake_loss=1.357, generator_loss=27.51, generator_mel_loss=18.68, generator_kl_loss=1.445, generator_dur_loss=1.709, generator_adv_loss=1.936, generator_feat_match_loss=3.737, over 932.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 19:41:16,332 INFO [train.py:527] (2/6) Epoch 194, batch 68, global_batch_idx: 24000, batch size: 45, loss[discriminator_loss=2.832, discriminator_real_loss=1.308, discriminator_fake_loss=1.524, generator_loss=28.61, generator_mel_loss=19.46, generator_kl_loss=1.488, generator_dur_loss=1.7, generator_adv_loss=1.903, generator_feat_match_loss=4.05, over 45.00 samples.], tot_loss[discriminator_loss=2.738, discriminator_real_loss=1.382, discriminator_fake_loss=1.356, generator_loss=27.47, generator_mel_loss=18.73, generator_kl_loss=1.392, generator_dur_loss=1.731, generator_adv_loss=1.935, generator_feat_match_loss=3.677, over 3767.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 19:41:16,334 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 19:41:24,225 INFO [train.py:591] (2/6) Epoch 194, validation: discriminator_loss=2.733, discriminator_real_loss=1.463, discriminator_fake_loss=1.27, generator_loss=26.68, generator_mel_loss=18.65, generator_kl_loss=1.177, generator_dur_loss=1.78, generator_adv_loss=2.005, generator_feat_match_loss=3.069, over 100.00 samples.
2024-03-12 19:41:24,226 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 19:43:40,354 INFO [train.py:527] (2/6) Epoch 194, batch 118, global_batch_idx: 24050, batch size: 70, loss[discriminator_loss=2.778, discriminator_real_loss=1.489, discriminator_fake_loss=1.29, generator_loss=26.46, generator_mel_loss=18.27, generator_kl_loss=1.312, generator_dur_loss=1.827, generator_adv_loss=1.897, generator_feat_match_loss=3.149, over 70.00 samples.], tot_loss[discriminator_loss=2.736, discriminator_real_loss=1.385, discriminator_fake_loss=1.351, generator_loss=27.38, generator_mel_loss=18.7, generator_kl_loss=1.385, generator_dur_loss=1.727, generator_adv_loss=1.927, generator_feat_match_loss=3.646, over 6535.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 19:43:56,389 INFO [train.py:919] (2/6) Start epoch 195
2024-03-12 19:46:20,748 INFO [train.py:527] (2/6) Epoch 195, batch 44, global_batch_idx: 24100, batch size: 77, loss[discriminator_loss=2.79, discriminator_real_loss=1.392, discriminator_fake_loss=1.398, generator_loss=27.01, generator_mel_loss=18.83, generator_kl_loss=1.326, generator_dur_loss=1.803, generator_adv_loss=1.81, generator_feat_match_loss=3.244, over 77.00 samples.], tot_loss[discriminator_loss=2.756, discriminator_real_loss=1.409, discriminator_fake_loss=1.347, generator_loss=27.32, generator_mel_loss=18.57, generator_kl_loss=1.378, generator_dur_loss=1.741, generator_adv_loss=2.006, generator_feat_match_loss=3.624, over 2536.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 19:48:39,007 INFO [train.py:527] (2/6) Epoch 195, batch 94, global_batch_idx: 24150, batch size: 55, loss[discriminator_loss=2.749, discriminator_real_loss=1.416, discriminator_fake_loss=1.333, generator_loss=27.24, generator_mel_loss=18.81, generator_kl_loss=1.47, generator_dur_loss=1.723, generator_adv_loss=1.915, generator_feat_match_loss=3.32, over 55.00 samples.], tot_loss[discriminator_loss=2.741, discriminator_real_loss=1.4, discriminator_fake_loss=1.341, generator_loss=27.33, generator_mel_loss=18.62, generator_kl_loss=1.388, generator_dur_loss=1.749, generator_adv_loss=1.965, generator_feat_match_loss=3.61, over 5461.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 19:50:03,423 INFO [train.py:919] (2/6) Start epoch 196
2024-03-12 19:51:22,219 INFO [train.py:527] (2/6) Epoch 196, batch 20, global_batch_idx: 24200, batch size: 56, loss[discriminator_loss=2.76, discriminator_real_loss=1.415, discriminator_fake_loss=1.346, generator_loss=27.01, generator_mel_loss=18.49, generator_kl_loss=1.344, generator_dur_loss=1.723, generator_adv_loss=1.933, generator_feat_match_loss=3.516, over 56.00 samples.], tot_loss[discriminator_loss=2.742, discriminator_real_loss=1.404, discriminator_fake_loss=1.338, generator_loss=27.22, generator_mel_loss=18.6, generator_kl_loss=1.336, generator_dur_loss=1.789, generator_adv_loss=1.912, generator_feat_match_loss=3.577, over 1397.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 19:51:22,220 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 19:51:30,420 INFO [train.py:591] (2/6) Epoch 196, validation: discriminator_loss=2.765, discriminator_real_loss=1.547, discriminator_fake_loss=1.218, generator_loss=26.23, generator_mel_loss=18.75, generator_kl_loss=1.178, generator_dur_loss=1.825, generator_adv_loss=1.943, generator_feat_match_loss=2.539, over 100.00 samples.
2024-03-12 19:51:30,421 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 19:53:49,957 INFO [train.py:527] (2/6) Epoch 196, batch 70, global_batch_idx: 24250, batch size: 77, loss[discriminator_loss=2.728, discriminator_real_loss=1.351, discriminator_fake_loss=1.377, generator_loss=26.87, generator_mel_loss=18.37, generator_kl_loss=1.321, generator_dur_loss=1.846, generator_adv_loss=1.991, generator_feat_match_loss=3.343, over 77.00 samples.], tot_loss[discriminator_loss=2.743, discriminator_real_loss=1.395, discriminator_fake_loss=1.348, generator_loss=27.24, generator_mel_loss=18.61, generator_kl_loss=1.373, generator_dur_loss=1.781, generator_adv_loss=1.904, generator_feat_match_loss=3.577, over 4399.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 19:56:06,098 INFO [train.py:527] (2/6) Epoch 196, batch 120, global_batch_idx: 24300, batch size: 31, loss[discriminator_loss=2.673, discriminator_real_loss=1.372, discriminator_fake_loss=1.302, generator_loss=27.85, generator_mel_loss=19.04, generator_kl_loss=1.487, generator_dur_loss=1.705, generator_adv_loss=2.071, generator_feat_match_loss=3.546, over 31.00 samples.], tot_loss[discriminator_loss=2.744, discriminator_real_loss=1.393, discriminator_fake_loss=1.351, generator_loss=27.24, generator_mel_loss=18.6, generator_kl_loss=1.38, generator_dur_loss=1.776, generator_adv_loss=1.901, generator_feat_match_loss=3.589, over 7161.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 19:56:15,288 INFO [train.py:919] (2/6) Start epoch 197
2024-03-12 19:58:46,782 INFO [train.py:527] (2/6) Epoch 197, batch 46, global_batch_idx: 24350, batch size: 77, loss[discriminator_loss=2.738, discriminator_real_loss=1.439, discriminator_fake_loss=1.299, generator_loss=27.54, generator_mel_loss=19.14, generator_kl_loss=1.184, generator_dur_loss=1.803, generator_adv_loss=1.947, generator_feat_match_loss=3.465, over 77.00 samples.], tot_loss[discriminator_loss=2.752, discriminator_real_loss=1.394, discriminator_fake_loss=1.358, generator_loss=27.51, generator_mel_loss=18.77, generator_kl_loss=1.386, generator_dur_loss=1.748, generator_adv_loss=1.941, generator_feat_match_loss=3.663, over 2713.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 20:01:06,584 INFO [train.py:527] (2/6) Epoch 197, batch 96, global_batch_idx: 24400, batch size: 52, loss[discriminator_loss=2.816, discriminator_real_loss=1.364, discriminator_fake_loss=1.452, generator_loss=26.71, generator_mel_loss=18.29, generator_kl_loss=1.427, generator_dur_loss=1.663, generator_adv_loss=1.939, generator_feat_match_loss=3.392, over 52.00 samples.], tot_loss[discriminator_loss=2.743, discriminator_real_loss=1.39, discriminator_fake_loss=1.353, generator_loss=27.47, generator_mel_loss=18.76, generator_kl_loss=1.393, generator_dur_loss=1.74, generator_adv_loss=1.926, generator_feat_match_loss=3.654, over 5324.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 20:01:06,586 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 20:01:15,297 INFO [train.py:591] (2/6) Epoch 197, validation: discriminator_loss=2.775, discriminator_real_loss=1.452, discriminator_fake_loss=1.324, generator_loss=25.87, generator_mel_loss=18.32, generator_kl_loss=1.216, generator_dur_loss=1.813, generator_adv_loss=1.908, generator_feat_match_loss=2.619, over 100.00 samples.
2024-03-12 20:01:15,298 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 20:02:32,651 INFO [train.py:919] (2/6) Start epoch 198
2024-03-12 20:03:57,302 INFO [train.py:527] (2/6) Epoch 198, batch 22, global_batch_idx: 24450, batch size: 47, loss[discriminator_loss=2.692, discriminator_real_loss=1.222, discriminator_fake_loss=1.47, generator_loss=27.24, generator_mel_loss=18.33, generator_kl_loss=1.543, generator_dur_loss=1.61, generator_adv_loss=1.994, generator_feat_match_loss=3.762, over 47.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.37, discriminator_fake_loss=1.349, generator_loss=27.38, generator_mel_loss=18.63, generator_kl_loss=1.374, generator_dur_loss=1.749, generator_adv_loss=1.916, generator_feat_match_loss=3.715, over 1388.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 20:06:18,111 INFO [train.py:527] (2/6) Epoch 198, batch 72, global_batch_idx: 24500, batch size: 96, loss[discriminator_loss=2.826, discriminator_real_loss=1.381, discriminator_fake_loss=1.445, generator_loss=25.84, generator_mel_loss=17.71, generator_kl_loss=1.241, generator_dur_loss=1.824, generator_adv_loss=1.801, generator_feat_match_loss=3.258, over 96.00 samples.], tot_loss[discriminator_loss=2.736, discriminator_real_loss=1.38, discriminator_fake_loss=1.356, generator_loss=27.36, generator_mel_loss=18.61, generator_kl_loss=1.387, generator_dur_loss=1.746, generator_adv_loss=1.923, generator_feat_match_loss=3.688, over 4187.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 20:08:36,542 INFO [train.py:527] (2/6) Epoch 198, batch 122, global_batch_idx: 24550, batch size: 83, loss[discriminator_loss=2.808, discriminator_real_loss=1.299, discriminator_fake_loss=1.509, generator_loss=28.2, generator_mel_loss=19.44, generator_kl_loss=1.493, generator_dur_loss=1.838, generator_adv_loss=1.919, generator_feat_match_loss=3.504, over 83.00 samples.], tot_loss[discriminator_loss=2.74, discriminator_real_loss=1.384, discriminator_fake_loss=1.356, generator_loss=27.42, generator_mel_loss=18.67, generator_kl_loss=1.396, generator_dur_loss=1.747, generator_adv_loss=1.924, generator_feat_match_loss=3.68, over 7067.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 20:08:41,600 INFO [train.py:919] (2/6) Start epoch 199
2024-03-12 20:11:17,805 INFO [train.py:527] (2/6) Epoch 199, batch 48, global_batch_idx: 24600, batch size: 48, loss[discriminator_loss=2.699, discriminator_real_loss=1.289, discriminator_fake_loss=1.41, generator_loss=27.07, generator_mel_loss=18.27, generator_kl_loss=1.581, generator_dur_loss=1.703, generator_adv_loss=1.769, generator_feat_match_loss=3.743, over 48.00 samples.], tot_loss[discriminator_loss=2.738, discriminator_real_loss=1.379, discriminator_fake_loss=1.359, generator_loss=27.41, generator_mel_loss=18.62, generator_kl_loss=1.404, generator_dur_loss=1.758, generator_adv_loss=1.901, generator_feat_match_loss=3.717, over 2733.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 20:11:17,807 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 20:11:25,594 INFO [train.py:591] (2/6) Epoch 199, validation: discriminator_loss=2.783, discriminator_real_loss=1.337, discriminator_fake_loss=1.447, generator_loss=26.96, generator_mel_loss=19, generator_kl_loss=1.197, generator_dur_loss=1.821, generator_adv_loss=1.71, generator_feat_match_loss=3.232, over 100.00 samples.
2024-03-12 20:11:25,595 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 20:13:45,130 INFO [train.py:527] (2/6) Epoch 199, batch 98, global_batch_idx: 24650, batch size: 59, loss[discriminator_loss=2.712, discriminator_real_loss=1.434, discriminator_fake_loss=1.278, generator_loss=26.79, generator_mel_loss=18.36, generator_kl_loss=1.348, generator_dur_loss=1.745, generator_adv_loss=1.836, generator_feat_match_loss=3.497, over 59.00 samples.], tot_loss[discriminator_loss=2.735, discriminator_real_loss=1.385, discriminator_fake_loss=1.35, generator_loss=27.36, generator_mel_loss=18.62, generator_kl_loss=1.389, generator_dur_loss=1.769, generator_adv_loss=1.909, generator_feat_match_loss=3.672, over 5736.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 20:14:55,963 INFO [train.py:919] (2/6) Start epoch 200
2024-03-12 20:16:26,062 INFO [train.py:527] (2/6) Epoch 200, batch 24, global_batch_idx: 24700, batch size: 45, loss[discriminator_loss=2.792, discriminator_real_loss=1.292, discriminator_fake_loss=1.5, generator_loss=28.08, generator_mel_loss=19.21, generator_kl_loss=1.591, generator_dur_loss=1.654, generator_adv_loss=1.907, generator_feat_match_loss=3.722, over 45.00 samples.], tot_loss[discriminator_loss=2.74, discriminator_real_loss=1.386, discriminator_fake_loss=1.354, generator_loss=27.41, generator_mel_loss=18.69, generator_kl_loss=1.413, generator_dur_loss=1.724, generator_adv_loss=1.894, generator_feat_match_loss=3.683, over 1387.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 20:18:45,095 INFO [train.py:527] (2/6) Epoch 200, batch 74, global_batch_idx: 24750, batch size: 66, loss[discriminator_loss=2.746, discriminator_real_loss=1.421, discriminator_fake_loss=1.325, generator_loss=26.54, generator_mel_loss=18.45, generator_kl_loss=1.154, generator_dur_loss=1.774, generator_adv_loss=1.737, generator_feat_match_loss=3.423, over 66.00 samples.], tot_loss[discriminator_loss=2.749, discriminator_real_loss=1.394, discriminator_fake_loss=1.355, generator_loss=27.28, generator_mel_loss=18.63, generator_kl_loss=1.397, generator_dur_loss=1.73, generator_adv_loss=1.897, generator_feat_match_loss=3.633, over 4280.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 20:21:02,480 INFO [train.py:919] (2/6) Start epoch 201
2024-03-12 20:21:28,019 INFO [train.py:527] (2/6) Epoch 201, batch 0, global_batch_idx: 24800, batch size: 80, loss[discriminator_loss=2.698, discriminator_real_loss=1.354, discriminator_fake_loss=1.344, generator_loss=26.67, generator_mel_loss=18.3, generator_kl_loss=1.263, generator_dur_loss=1.783, generator_adv_loss=1.883, generator_feat_match_loss=3.449, over 80.00 samples.], tot_loss[discriminator_loss=2.698, discriminator_real_loss=1.354, discriminator_fake_loss=1.344, generator_loss=26.67, generator_mel_loss=18.3, generator_kl_loss=1.263, generator_dur_loss=1.783, generator_adv_loss=1.883, generator_feat_match_loss=3.449, over 80.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 20:21:28,021 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 20:21:35,806 INFO [train.py:591] (2/6) Epoch 201, validation: discriminator_loss=2.747, discriminator_real_loss=1.414, discriminator_fake_loss=1.333, generator_loss=26.54, generator_mel_loss=19.03, generator_kl_loss=1.132, generator_dur_loss=1.801, generator_adv_loss=1.8, generator_feat_match_loss=2.77, over 100.00 samples.
2024-03-12 20:21:35,808 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 20:23:53,774 INFO [train.py:527] (2/6) Epoch 201, batch 50, global_batch_idx: 24850, batch size: 44, loss[discriminator_loss=2.75, discriminator_real_loss=1.365, discriminator_fake_loss=1.386, generator_loss=27.07, generator_mel_loss=18.31, generator_kl_loss=1.497, generator_dur_loss=1.716, generator_adv_loss=1.907, generator_feat_match_loss=3.64, over 44.00 samples.], tot_loss[discriminator_loss=2.735, discriminator_real_loss=1.387, discriminator_fake_loss=1.348, generator_loss=27.36, generator_mel_loss=18.68, generator_kl_loss=1.378, generator_dur_loss=1.733, generator_adv_loss=1.921, generator_feat_match_loss=3.652, over 2846.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 20:26:11,204 INFO [train.py:527] (2/6) Epoch 201, batch 100, global_batch_idx: 24900, batch size: 48, loss[discriminator_loss=2.62, discriminator_real_loss=1.269, discriminator_fake_loss=1.35, generator_loss=27.85, generator_mel_loss=18.36, generator_kl_loss=1.55, generator_dur_loss=1.734, generator_adv_loss=2.05, generator_feat_match_loss=4.157, over 48.00 samples.], tot_loss[discriminator_loss=2.733, discriminator_real_loss=1.385, discriminator_fake_loss=1.347, generator_loss=27.39, generator_mel_loss=18.64, generator_kl_loss=1.396, generator_dur_loss=1.731, generator_adv_loss=1.94, generator_feat_match_loss=3.68, over 5327.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 20:27:18,197 INFO [train.py:919] (2/6) Start epoch 202
2024-03-12 20:28:54,310 INFO [train.py:527] (2/6) Epoch 202, batch 26, global_batch_idx: 24950, batch size: 47, loss[discriminator_loss=2.729, discriminator_real_loss=1.449, discriminator_fake_loss=1.28, generator_loss=27.88, generator_mel_loss=19.13, generator_kl_loss=1.547, generator_dur_loss=1.692, generator_adv_loss=1.768, generator_feat_match_loss=3.738, over 47.00 samples.], tot_loss[discriminator_loss=2.745, discriminator_real_loss=1.401, discriminator_fake_loss=1.344, generator_loss=27.33, generator_mel_loss=18.6, generator_kl_loss=1.407, generator_dur_loss=1.724, generator_adv_loss=1.921, generator_feat_match_loss=3.674, over 1476.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 20:31:15,304 INFO [train.py:527] (2/6) Epoch 202, batch 76, global_batch_idx: 25000, batch size: 45, loss[discriminator_loss=2.776, discriminator_real_loss=1.31, discriminator_fake_loss=1.467, generator_loss=27.95, generator_mel_loss=18.88, generator_kl_loss=1.457, generator_dur_loss=1.653, generator_adv_loss=1.944, generator_feat_match_loss=4.024, over 45.00 samples.], tot_loss[discriminator_loss=2.738, discriminator_real_loss=1.39, discriminator_fake_loss=1.348, generator_loss=27.36, generator_mel_loss=18.61, generator_kl_loss=1.418, generator_dur_loss=1.755, generator_adv_loss=1.91, generator_feat_match_loss=3.669, over 4420.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 20:31:15,306 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 20:31:23,179 INFO [train.py:591] (2/6) Epoch 202, validation: discriminator_loss=2.801, discriminator_real_loss=1.557, discriminator_fake_loss=1.244, generator_loss=26.27, generator_mel_loss=18.44, generator_kl_loss=1.31, generator_dur_loss=1.826, generator_adv_loss=1.946, generator_feat_match_loss=2.748, over 100.00 samples.
2024-03-12 20:31:23,180 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 20:33:34,401 INFO [train.py:919] (2/6) Start epoch 203
2024-03-12 20:34:05,544 INFO [train.py:527] (2/6) Epoch 203, batch 2, global_batch_idx: 25050, batch size: 96, loss[discriminator_loss=2.716, discriminator_real_loss=1.225, discriminator_fake_loss=1.491, generator_loss=27.16, generator_mel_loss=18.19, generator_kl_loss=1.354, generator_dur_loss=1.819, generator_adv_loss=2.043, generator_feat_match_loss=3.747, over 96.00 samples.], tot_loss[discriminator_loss=2.742, discriminator_real_loss=1.355, discriminator_fake_loss=1.387, generator_loss=27.43, generator_mel_loss=18.7, generator_kl_loss=1.293, generator_dur_loss=1.813, generator_adv_loss=1.942, generator_feat_match_loss=3.685, over 250.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 20:36:24,692 INFO [train.py:527] (2/6) Epoch 203, batch 52, global_batch_idx: 25100, batch size: 55, loss[discriminator_loss=2.683, discriminator_real_loss=1.36, discriminator_fake_loss=1.323, generator_loss=28.93, generator_mel_loss=19.58, generator_kl_loss=1.438, generator_dur_loss=1.707, generator_adv_loss=2.132, generator_feat_match_loss=4.075, over 55.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.372, discriminator_fake_loss=1.348, generator_loss=27.44, generator_mel_loss=18.67, generator_kl_loss=1.36, generator_dur_loss=1.772, generator_adv_loss=1.919, generator_feat_match_loss=3.717, over 3356.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 20:38:42,966 INFO [train.py:527] (2/6) Epoch 203, batch 102, global_batch_idx: 25150, batch size: 47, loss[discriminator_loss=2.696, discriminator_real_loss=1.294, discriminator_fake_loss=1.403, generator_loss=27.5, generator_mel_loss=18.73, generator_kl_loss=1.391, generator_dur_loss=1.722, generator_adv_loss=1.924, generator_feat_match_loss=3.728, over 47.00 samples.], tot_loss[discriminator_loss=2.732, discriminator_real_loss=1.385, discriminator_fake_loss=1.347, generator_loss=27.48, generator_mel_loss=18.68, generator_kl_loss=1.378, generator_dur_loss=1.752, generator_adv_loss=1.941, generator_feat_match_loss=3.726, over 6173.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 20:39:43,235 INFO [train.py:919] (2/6) Start epoch 204
2024-03-12 20:41:27,024 INFO [train.py:527] (2/6) Epoch 204, batch 28, global_batch_idx: 25200, batch size: 80, loss[discriminator_loss=2.843, discriminator_real_loss=1.349, discriminator_fake_loss=1.493, generator_loss=27.22, generator_mel_loss=18.69, generator_kl_loss=1.294, generator_dur_loss=1.814, generator_adv_loss=1.925, generator_feat_match_loss=3.501, over 80.00 samples.], tot_loss[discriminator_loss=2.74, discriminator_real_loss=1.397, discriminator_fake_loss=1.343, generator_loss=27.36, generator_mel_loss=18.64, generator_kl_loss=1.397, generator_dur_loss=1.763, generator_adv_loss=1.904, generator_feat_match_loss=3.652, over 1629.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 20:41:27,026 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 20:41:34,969 INFO [train.py:591] (2/6) Epoch 204, validation: discriminator_loss=2.807, discriminator_real_loss=1.546, discriminator_fake_loss=1.261, generator_loss=26.54, generator_mel_loss=18.68, generator_kl_loss=1.063, generator_dur_loss=1.807, generator_adv_loss=1.974, generator_feat_match_loss=3.013, over 100.00 samples.
2024-03-12 20:41:34,970 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 20:43:55,157 INFO [train.py:527] (2/6) Epoch 204, batch 78, global_batch_idx: 25250, batch size: 45, loss[discriminator_loss=2.707, discriminator_real_loss=1.33, discriminator_fake_loss=1.377, generator_loss=28, generator_mel_loss=19.15, generator_kl_loss=1.331, generator_dur_loss=1.684, generator_adv_loss=1.91, generator_feat_match_loss=3.925, over 45.00 samples.], tot_loss[discriminator_loss=2.743, discriminator_real_loss=1.396, discriminator_fake_loss=1.348, generator_loss=27.25, generator_mel_loss=18.57, generator_kl_loss=1.366, generator_dur_loss=1.773, generator_adv_loss=1.906, generator_feat_match_loss=3.636, over 4850.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 20:45:59,849 INFO [train.py:919] (2/6) Start epoch 205
2024-03-12 20:46:34,530 INFO [train.py:527] (2/6) Epoch 205, batch 4, global_batch_idx: 25300, batch size: 77, loss[discriminator_loss=2.818, discriminator_real_loss=1.472, discriminator_fake_loss=1.346, generator_loss=27.1, generator_mel_loss=18.38, generator_kl_loss=1.21, generator_dur_loss=1.829, generator_adv_loss=1.854, generator_feat_match_loss=3.832, over 77.00 samples.], tot_loss[discriminator_loss=2.76, discriminator_real_loss=1.423, discriminator_fake_loss=1.338, generator_loss=27.44, generator_mel_loss=18.69, generator_kl_loss=1.348, generator_dur_loss=1.78, generator_adv_loss=1.924, generator_feat_match_loss=3.704, over 297.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 20:48:55,206 INFO [train.py:527] (2/6) Epoch 205, batch 54, global_batch_idx: 25350, batch size: 96, loss[discriminator_loss=2.758, discriminator_real_loss=1.529, discriminator_fake_loss=1.229, generator_loss=27.24, generator_mel_loss=17.98, generator_kl_loss=1.359, generator_dur_loss=1.751, generator_adv_loss=2.063, generator_feat_match_loss=4.095, over 96.00 samples.], tot_loss[discriminator_loss=2.751, discriminator_real_loss=1.401, discriminator_fake_loss=1.35, generator_loss=27.66, generator_mel_loss=18.63, generator_kl_loss=1.376, generator_dur_loss=1.749, generator_adv_loss=2.009, generator_feat_match_loss=3.891, over 3075.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 20:51:12,572 INFO [train.py:527] (2/6) Epoch 205, batch 104, global_batch_idx: 25400, batch size: 96, loss[discriminator_loss=2.745, discriminator_real_loss=1.287, discriminator_fake_loss=1.458, generator_loss=26.94, generator_mel_loss=18.32, generator_kl_loss=1.127, generator_dur_loss=1.869, generator_adv_loss=1.966, generator_feat_match_loss=3.657, over 96.00 samples.], tot_loss[discriminator_loss=2.746, discriminator_real_loss=1.397, discriminator_fake_loss=1.348, generator_loss=27.56, generator_mel_loss=18.64, generator_kl_loss=1.388, generator_dur_loss=1.752, generator_adv_loss=1.991, generator_feat_match_loss=3.795, over 5909.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 20:51:12,574 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 20:51:21,443 INFO [train.py:591] (2/6) Epoch 205, validation: discriminator_loss=2.768, discriminator_real_loss=1.479, discriminator_fake_loss=1.289, generator_loss=26.36, generator_mel_loss=18.63, generator_kl_loss=1.039, generator_dur_loss=1.821, generator_adv_loss=1.939, generator_feat_match_loss=2.932, over 100.00 samples.
2024-03-12 20:51:21,444 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 20:52:14,088 INFO [train.py:919] (2/6) Start epoch 206
2024-03-12 20:54:02,111 INFO [train.py:527] (2/6) Epoch 206, batch 30, global_batch_idx: 25450, batch size: 74, loss[discriminator_loss=2.698, discriminator_real_loss=1.355, discriminator_fake_loss=1.343, generator_loss=27.23, generator_mel_loss=18.51, generator_kl_loss=1.375, generator_dur_loss=1.819, generator_adv_loss=1.931, generator_feat_match_loss=3.598, over 74.00 samples.], tot_loss[discriminator_loss=2.747, discriminator_real_loss=1.405, discriminator_fake_loss=1.342, generator_loss=27.3, generator_mel_loss=18.63, generator_kl_loss=1.366, generator_dur_loss=1.777, generator_adv_loss=1.906, generator_feat_match_loss=3.617, over 1831.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 20:56:20,980 INFO [train.py:527] (2/6) Epoch 206, batch 80, global_batch_idx: 25500, batch size: 31, loss[discriminator_loss=2.764, discriminator_real_loss=1.525, discriminator_fake_loss=1.238, generator_loss=27.09, generator_mel_loss=18.86, generator_kl_loss=1.477, generator_dur_loss=1.649, generator_adv_loss=1.772, generator_feat_match_loss=3.328, over 31.00 samples.], tot_loss[discriminator_loss=2.732, discriminator_real_loss=1.392, discriminator_fake_loss=1.34, generator_loss=27.34, generator_mel_loss=18.61, generator_kl_loss=1.385, generator_dur_loss=1.771, generator_adv_loss=1.911, generator_feat_match_loss=3.661, over 4749.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 20:58:19,430 INFO [train.py:919] (2/6) Start epoch 207
2024-03-12 20:58:57,483 INFO [train.py:527] (2/6) Epoch 207, batch 6, global_batch_idx: 25550, batch size: 55, loss[discriminator_loss=2.811, discriminator_real_loss=1.513, discriminator_fake_loss=1.298, generator_loss=27.39, generator_mel_loss=18.72, generator_kl_loss=1.28, generator_dur_loss=1.726, generator_adv_loss=1.859, generator_feat_match_loss=3.81, over 55.00 samples.], tot_loss[discriminator_loss=2.745, discriminator_real_loss=1.358, discriminator_fake_loss=1.387, generator_loss=27.7, generator_mel_loss=18.83, generator_kl_loss=1.386, generator_dur_loss=1.774, generator_adv_loss=1.958, generator_feat_match_loss=3.758, over 393.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 21:01:18,366 INFO [train.py:527] (2/6) Epoch 207, batch 56, global_batch_idx: 25600, batch size: 44, loss[discriminator_loss=2.894, discriminator_real_loss=1.335, discriminator_fake_loss=1.559, generator_loss=28.08, generator_mel_loss=18.82, generator_kl_loss=1.485, generator_dur_loss=1.722, generator_adv_loss=2.032, generator_feat_match_loss=4.02, over 44.00 samples.], tot_loss[discriminator_loss=2.735, discriminator_real_loss=1.376, discriminator_fake_loss=1.359, generator_loss=27.45, generator_mel_loss=18.66, generator_kl_loss=1.388, generator_dur_loss=1.768, generator_adv_loss=1.938, generator_feat_match_loss=3.702, over 3190.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 21:01:18,367 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 21:01:26,534 INFO [train.py:591] (2/6) Epoch 207, validation: discriminator_loss=2.717, discriminator_real_loss=1.586, discriminator_fake_loss=1.131, generator_loss=27.03, generator_mel_loss=18.54, generator_kl_loss=1.148, generator_dur_loss=1.846, generator_adv_loss=2.142, generator_feat_match_loss=3.347, over 100.00 samples.
2024-03-12 21:01:26,535 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 21:03:49,607 INFO [train.py:527] (2/6) Epoch 207, batch 106, global_batch_idx: 25650, batch size: 25, loss[discriminator_loss=2.805, discriminator_real_loss=1.595, discriminator_fake_loss=1.21, generator_loss=27.85, generator_mel_loss=18.93, generator_kl_loss=1.566, generator_dur_loss=1.591, generator_adv_loss=1.711, generator_feat_match_loss=4.059, over 25.00 samples.], tot_loss[discriminator_loss=2.734, discriminator_real_loss=1.383, discriminator_fake_loss=1.351, generator_loss=27.42, generator_mel_loss=18.66, generator_kl_loss=1.373, generator_dur_loss=1.766, generator_adv_loss=1.941, generator_feat_match_loss=3.681, over 6157.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 21:04:34,127 INFO [train.py:919] (2/6) Start epoch 208
2024-03-12 21:06:25,028 INFO [train.py:527] (2/6) Epoch 208, batch 32, global_batch_idx: 25700, batch size: 80, loss[discriminator_loss=2.75, discriminator_real_loss=1.386, discriminator_fake_loss=1.364, generator_loss=27.02, generator_mel_loss=18.46, generator_kl_loss=1.399, generator_dur_loss=1.83, generator_adv_loss=1.875, generator_feat_match_loss=3.459, over 80.00 samples.], tot_loss[discriminator_loss=2.722, discriminator_real_loss=1.385, discriminator_fake_loss=1.337, generator_loss=27.46, generator_mel_loss=18.64, generator_kl_loss=1.399, generator_dur_loss=1.752, generator_adv_loss=1.929, generator_feat_match_loss=3.741, over 1761.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 21:08:44,952 INFO [train.py:527] (2/6) Epoch 208, batch 82, global_batch_idx: 25750, batch size: 59, loss[discriminator_loss=2.717, discriminator_real_loss=1.342, discriminator_fake_loss=1.375, generator_loss=26.63, generator_mel_loss=18.24, generator_kl_loss=1.362, generator_dur_loss=1.757, generator_adv_loss=1.747, generator_feat_match_loss=3.524, over 59.00 samples.], tot_loss[discriminator_loss=2.73, discriminator_real_loss=1.382, discriminator_fake_loss=1.348, generator_loss=27.36, generator_mel_loss=18.58, generator_kl_loss=1.383, generator_dur_loss=1.775, generator_adv_loss=1.916, generator_feat_match_loss=3.711, over 4793.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 21:10:40,241 INFO [train.py:919] (2/6) Start epoch 209
2024-03-12 21:11:24,741 INFO [train.py:527] (2/6) Epoch 209, batch 8, global_batch_idx: 25800, batch size: 56, loss[discriminator_loss=2.759, discriminator_real_loss=1.501, discriminator_fake_loss=1.258, generator_loss=27.28, generator_mel_loss=18.37, generator_kl_loss=1.245, generator_dur_loss=1.697, generator_adv_loss=1.924, generator_feat_match_loss=4.041, over 56.00 samples.], tot_loss[discriminator_loss=2.777, discriminator_real_loss=1.42, discriminator_fake_loss=1.357, generator_loss=27.17, generator_mel_loss=18.51, generator_kl_loss=1.383, generator_dur_loss=1.764, generator_adv_loss=1.895, generator_feat_match_loss=3.622, over 604.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 21:11:24,746 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 21:11:32,763 INFO [train.py:591] (2/6) Epoch 209, validation: discriminator_loss=2.782, discriminator_real_loss=1.439, discriminator_fake_loss=1.343, generator_loss=26, generator_mel_loss=18.5, generator_kl_loss=1.201, generator_dur_loss=1.815, generator_adv_loss=1.769, generator_feat_match_loss=2.715, over 100.00 samples.
2024-03-12 21:11:32,765 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 21:13:50,557 INFO [train.py:527] (2/6) Epoch 209, batch 58, global_batch_idx: 25850, batch size: 52, loss[discriminator_loss=2.712, discriminator_real_loss=1.237, discriminator_fake_loss=1.475, generator_loss=27.45, generator_mel_loss=18.31, generator_kl_loss=1.455, generator_dur_loss=1.658, generator_adv_loss=2.078, generator_feat_match_loss=3.945, over 52.00 samples.], tot_loss[discriminator_loss=2.744, discriminator_real_loss=1.383, discriminator_fake_loss=1.361, generator_loss=27.36, generator_mel_loss=18.59, generator_kl_loss=1.373, generator_dur_loss=1.758, generator_adv_loss=1.906, generator_feat_match_loss=3.734, over 3498.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 21:16:09,420 INFO [train.py:527] (2/6) Epoch 209, batch 108, global_batch_idx: 25900, batch size: 25, loss[discriminator_loss=2.724, discriminator_real_loss=1.425, discriminator_fake_loss=1.3, generator_loss=27.6, generator_mel_loss=18.56, generator_kl_loss=1.603, generator_dur_loss=1.551, generator_adv_loss=1.969, generator_feat_match_loss=3.912, over 25.00 samples.], tot_loss[discriminator_loss=2.737, discriminator_real_loss=1.382, discriminator_fake_loss=1.355, generator_loss=27.36, generator_mel_loss=18.61, generator_kl_loss=1.386, generator_dur_loss=1.738, generator_adv_loss=1.918, generator_feat_match_loss=3.712, over 6272.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 21:16:51,398 INFO [train.py:919] (2/6) Start epoch 210
2024-03-12 21:18:49,292 INFO [train.py:527] (2/6) Epoch 210, batch 34, global_batch_idx: 25950, batch size: 88, loss[discriminator_loss=2.668, discriminator_real_loss=1.326, discriminator_fake_loss=1.343, generator_loss=26.79, generator_mel_loss=18.34, generator_kl_loss=1.192, generator_dur_loss=1.814, generator_adv_loss=2.002, generator_feat_match_loss=3.439, over 88.00 samples.], tot_loss[discriminator_loss=2.733, discriminator_real_loss=1.371, discriminator_fake_loss=1.362, generator_loss=27.45, generator_mel_loss=18.64, generator_kl_loss=1.378, generator_dur_loss=1.752, generator_adv_loss=1.925, generator_feat_match_loss=3.752, over 2037.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 21:21:09,228 INFO [train.py:527] (2/6) Epoch 210, batch 84, global_batch_idx: 26000, batch size: 25, loss[discriminator_loss=2.626, discriminator_real_loss=1.344, discriminator_fake_loss=1.282, generator_loss=29.73, generator_mel_loss=19.64, generator_kl_loss=1.599, generator_dur_loss=1.593, generator_adv_loss=1.882, generator_feat_match_loss=5.019, over 25.00 samples.], tot_loss[discriminator_loss=2.725, discriminator_real_loss=1.375, discriminator_fake_loss=1.351, generator_loss=27.48, generator_mel_loss=18.67, generator_kl_loss=1.384, generator_dur_loss=1.757, generator_adv_loss=1.92, generator_feat_match_loss=3.749, over 4969.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 21:21:09,230 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 21:21:17,006 INFO [train.py:591] (2/6) Epoch 210, validation: discriminator_loss=2.839, discriminator_real_loss=1.406, discriminator_fake_loss=1.433, generator_loss=26.29, generator_mel_loss=18.73, generator_kl_loss=1.079, generator_dur_loss=1.807, generator_adv_loss=1.765, generator_feat_match_loss=2.917, over 100.00 samples.
2024-03-12 21:21:17,007 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 21:23:06,352 INFO [train.py:919] (2/6) Start epoch 211
2024-03-12 21:23:58,831 INFO [train.py:527] (2/6) Epoch 211, batch 10, global_batch_idx: 26050, batch size: 72, loss[discriminator_loss=2.749, discriminator_real_loss=1.429, discriminator_fake_loss=1.32, generator_loss=27.25, generator_mel_loss=18.39, generator_kl_loss=1.407, generator_dur_loss=1.769, generator_adv_loss=1.786, generator_feat_match_loss=3.89, over 72.00 samples.], tot_loss[discriminator_loss=2.755, discriminator_real_loss=1.398, discriminator_fake_loss=1.357, generator_loss=27.56, generator_mel_loss=18.76, generator_kl_loss=1.394, generator_dur_loss=1.722, generator_adv_loss=1.925, generator_feat_match_loss=3.76, over 638.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 21:26:18,181 INFO [train.py:527] (2/6) Epoch 211, batch 60, global_batch_idx: 26100, batch size: 36, loss[discriminator_loss=2.775, discriminator_real_loss=1.471, discriminator_fake_loss=1.304, generator_loss=26.67, generator_mel_loss=17.96, generator_kl_loss=1.519, generator_dur_loss=1.636, generator_adv_loss=1.893, generator_feat_match_loss=3.66, over 36.00 samples.], tot_loss[discriminator_loss=2.732, discriminator_real_loss=1.385, discriminator_fake_loss=1.347, generator_loss=27.48, generator_mel_loss=18.67, generator_kl_loss=1.409, generator_dur_loss=1.715, generator_adv_loss=1.927, generator_feat_match_loss=3.759, over 3204.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 21:28:36,089 INFO [train.py:527] (2/6) Epoch 211, batch 110, global_batch_idx: 26150, batch size: 53, loss[discriminator_loss=2.673, discriminator_real_loss=1.371, discriminator_fake_loss=1.302, generator_loss=27.91, generator_mel_loss=18.67, generator_kl_loss=1.409, generator_dur_loss=1.668, generator_adv_loss=1.928, generator_feat_match_loss=4.234, over 53.00 samples.], tot_loss[discriminator_loss=2.741, discriminator_real_loss=1.387, discriminator_fake_loss=1.354, generator_loss=27.41, generator_mel_loss=18.64, generator_kl_loss=1.389, generator_dur_loss=1.73, generator_adv_loss=1.92, generator_feat_match_loss=3.732, over 5972.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 21:29:13,602 INFO [train.py:919] (2/6) Start epoch 212
2024-03-12 21:31:21,584 INFO [train.py:527] (2/6) Epoch 212, batch 36, global_batch_idx: 26200, batch size: 61, loss[discriminator_loss=2.778, discriminator_real_loss=1.238, discriminator_fake_loss=1.54, generator_loss=26.79, generator_mel_loss=18.45, generator_kl_loss=1.389, generator_dur_loss=1.729, generator_adv_loss=1.983, generator_feat_match_loss=3.238, over 61.00 samples.], tot_loss[discriminator_loss=2.721, discriminator_real_loss=1.365, discriminator_fake_loss=1.357, generator_loss=27.44, generator_mel_loss=18.54, generator_kl_loss=1.369, generator_dur_loss=1.773, generator_adv_loss=1.953, generator_feat_match_loss=3.802, over 2193.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 21:31:21,585 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 21:31:29,922 INFO [train.py:591] (2/6) Epoch 212, validation: discriminator_loss=2.765, discriminator_real_loss=1.38, discriminator_fake_loss=1.384, generator_loss=26.31, generator_mel_loss=18.38, generator_kl_loss=1.243, generator_dur_loss=1.806, generator_adv_loss=1.88, generator_feat_match_loss=3.006, over 100.00 samples.
2024-03-12 21:31:29,923 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 21:33:49,157 INFO [train.py:527] (2/6) Epoch 212, batch 86, global_batch_idx: 26250, batch size: 61, loss[discriminator_loss=2.745, discriminator_real_loss=1.339, discriminator_fake_loss=1.406, generator_loss=27.35, generator_mel_loss=18.62, generator_kl_loss=1.358, generator_dur_loss=1.74, generator_adv_loss=1.963, generator_feat_match_loss=3.662, over 61.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.379, discriminator_fake_loss=1.341, generator_loss=27.43, generator_mel_loss=18.55, generator_kl_loss=1.364, generator_dur_loss=1.762, generator_adv_loss=1.959, generator_feat_match_loss=3.796, over 4982.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 21:35:33,508 INFO [train.py:919] (2/6) Start epoch 213
2024-03-12 21:36:29,181 INFO [train.py:527] (2/6) Epoch 213, batch 12, global_batch_idx: 26300, batch size: 70, loss[discriminator_loss=2.803, discriminator_real_loss=1.483, discriminator_fake_loss=1.32, generator_loss=27.33, generator_mel_loss=18.52, generator_kl_loss=1.487, generator_dur_loss=1.81, generator_adv_loss=1.908, generator_feat_match_loss=3.605, over 70.00 samples.], tot_loss[discriminator_loss=2.781, discriminator_real_loss=1.417, discriminator_fake_loss=1.364, generator_loss=27.39, generator_mel_loss=18.52, generator_kl_loss=1.415, generator_dur_loss=1.786, generator_adv_loss=1.892, generator_feat_match_loss=3.771, over 812.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 21:38:49,993 INFO [train.py:527] (2/6) Epoch 213, batch 62, global_batch_idx: 26350, batch size: 53, loss[discriminator_loss=2.697, discriminator_real_loss=1.409, discriminator_fake_loss=1.288, generator_loss=26.47, generator_mel_loss=18.32, generator_kl_loss=1.452, generator_dur_loss=1.696, generator_adv_loss=1.849, generator_feat_match_loss=3.154, over 53.00 samples.], tot_loss[discriminator_loss=2.756, discriminator_real_loss=1.404, discriminator_fake_loss=1.352, generator_loss=27.41, generator_mel_loss=18.65, generator_kl_loss=1.37, generator_dur_loss=1.765, generator_adv_loss=1.921, generator_feat_match_loss=3.704, over 3678.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 21:41:08,800 INFO [train.py:527] (2/6) Epoch 213, batch 112, global_batch_idx: 26400, batch size: 48, loss[discriminator_loss=2.753, discriminator_real_loss=1.506, discriminator_fake_loss=1.247, generator_loss=27.6, generator_mel_loss=18.81, generator_kl_loss=1.341, generator_dur_loss=1.726, generator_adv_loss=1.913, generator_feat_match_loss=3.805, over 48.00 samples.], tot_loss[discriminator_loss=2.743, discriminator_real_loss=1.392, discriminator_fake_loss=1.351, generator_loss=27.42, generator_mel_loss=18.62, generator_kl_loss=1.381, generator_dur_loss=1.767, generator_adv_loss=1.922, generator_feat_match_loss=3.73, over 6532.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 21:41:08,801 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 21:41:17,870 INFO [train.py:591] (2/6) Epoch 213, validation: discriminator_loss=2.801, discriminator_real_loss=1.44, discriminator_fake_loss=1.36, generator_loss=26.31, generator_mel_loss=18.64, generator_kl_loss=1.191, generator_dur_loss=1.82, generator_adv_loss=1.78, generator_feat_match_loss=2.883, over 100.00 samples.
2024-03-12 21:41:17,871 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 21:41:48,853 INFO [train.py:919] (2/6) Start epoch 214
2024-03-12 21:43:55,447 INFO [train.py:527] (2/6) Epoch 214, batch 38, global_batch_idx: 26450, batch size: 44, loss[discriminator_loss=2.688, discriminator_real_loss=1.485, discriminator_fake_loss=1.204, generator_loss=27.92, generator_mel_loss=18.85, generator_kl_loss=1.49, generator_dur_loss=1.694, generator_adv_loss=1.659, generator_feat_match_loss=4.229, over 44.00 samples.], tot_loss[discriminator_loss=2.75, discriminator_real_loss=1.396, discriminator_fake_loss=1.354, generator_loss=27.51, generator_mel_loss=18.71, generator_kl_loss=1.396, generator_dur_loss=1.754, generator_adv_loss=1.913, generator_feat_match_loss=3.736, over 2095.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 21:46:16,900 INFO [train.py:527] (2/6) Epoch 214, batch 88, global_batch_idx: 26500, batch size: 42, loss[discriminator_loss=2.634, discriminator_real_loss=1.402, discriminator_fake_loss=1.231, generator_loss=28.4, generator_mel_loss=18.98, generator_kl_loss=1.629, generator_dur_loss=1.689, generator_adv_loss=1.851, generator_feat_match_loss=4.259, over 42.00 samples.], tot_loss[discriminator_loss=2.743, discriminator_real_loss=1.389, discriminator_fake_loss=1.354, generator_loss=27.44, generator_mel_loss=18.64, generator_kl_loss=1.405, generator_dur_loss=1.753, generator_adv_loss=1.916, generator_feat_match_loss=3.719, over 4914.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 21:47:54,578 INFO [train.py:919] (2/6) Start epoch 215
2024-03-12 21:48:58,716 INFO [train.py:527] (2/6) Epoch 215, batch 14, global_batch_idx: 26550, batch size: 42, loss[discriminator_loss=2.758, discriminator_real_loss=1.32, discriminator_fake_loss=1.438, generator_loss=27.4, generator_mel_loss=18.88, generator_kl_loss=1.559, generator_dur_loss=1.73, generator_adv_loss=2.051, generator_feat_match_loss=3.181, over 42.00 samples.], tot_loss[discriminator_loss=2.762, discriminator_real_loss=1.391, discriminator_fake_loss=1.371, generator_loss=27.69, generator_mel_loss=18.82, generator_kl_loss=1.415, generator_dur_loss=1.761, generator_adv_loss=1.899, generator_feat_match_loss=3.793, over 802.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 21:51:17,896 INFO [train.py:527] (2/6) Epoch 215, batch 64, global_batch_idx: 26600, batch size: 15, loss[discriminator_loss=2.714, discriminator_real_loss=1.359, discriminator_fake_loss=1.355, generator_loss=30.3, generator_mel_loss=20.38, generator_kl_loss=1.798, generator_dur_loss=1.596, generator_adv_loss=1.853, generator_feat_match_loss=4.681, over 15.00 samples.], tot_loss[discriminator_loss=2.732, discriminator_real_loss=1.383, discriminator_fake_loss=1.35, generator_loss=27.59, generator_mel_loss=18.66, generator_kl_loss=1.409, generator_dur_loss=1.766, generator_adv_loss=1.943, generator_feat_match_loss=3.812, over 3719.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 21:51:17,898 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 21:51:25,980 INFO [train.py:591] (2/6) Epoch 215, validation: discriminator_loss=2.771, discriminator_real_loss=1.38, discriminator_fake_loss=1.391, generator_loss=26, generator_mel_loss=18.38, generator_kl_loss=1.159, generator_dur_loss=1.825, generator_adv_loss=1.779, generator_feat_match_loss=2.863, over 100.00 samples.
2024-03-12 21:51:25,982 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 21:53:43,265 INFO [train.py:527] (2/6) Epoch 215, batch 114, global_batch_idx: 26650, batch size: 53, loss[discriminator_loss=2.703, discriminator_real_loss=1.444, discriminator_fake_loss=1.258, generator_loss=26.68, generator_mel_loss=18.37, generator_kl_loss=1.356, generator_dur_loss=1.686, generator_adv_loss=1.936, generator_feat_match_loss=3.336, over 53.00 samples.], tot_loss[discriminator_loss=2.734, discriminator_real_loss=1.387, discriminator_fake_loss=1.347, generator_loss=27.44, generator_mel_loss=18.58, generator_kl_loss=1.395, generator_dur_loss=1.76, generator_adv_loss=1.926, generator_feat_match_loss=3.771, over 6711.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 21:54:09,116 INFO [train.py:919] (2/6) Start epoch 216
2024-03-12 21:56:25,377 INFO [train.py:527] (2/6) Epoch 216, batch 40, global_batch_idx: 26700, batch size: 88, loss[discriminator_loss=2.771, discriminator_real_loss=1.437, discriminator_fake_loss=1.333, generator_loss=26.36, generator_mel_loss=17.98, generator_kl_loss=1.299, generator_dur_loss=1.834, generator_adv_loss=1.817, generator_feat_match_loss=3.425, over 88.00 samples.], tot_loss[discriminator_loss=2.744, discriminator_real_loss=1.4, discriminator_fake_loss=1.344, generator_loss=27.29, generator_mel_loss=18.57, generator_kl_loss=1.354, generator_dur_loss=1.758, generator_adv_loss=1.915, generator_feat_match_loss=3.7, over 2480.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 21:58:46,858 INFO [train.py:527] (2/6) Epoch 216, batch 90, global_batch_idx: 26750, batch size: 53, loss[discriminator_loss=2.735, discriminator_real_loss=1.391, discriminator_fake_loss=1.344, generator_loss=27.17, generator_mel_loss=18.36, generator_kl_loss=1.349, generator_dur_loss=1.638, generator_adv_loss=1.954, generator_feat_match_loss=3.866, over 53.00 samples.], tot_loss[discriminator_loss=2.739, discriminator_real_loss=1.391, discriminator_fake_loss=1.347, generator_loss=27.42, generator_mel_loss=18.59, generator_kl_loss=1.379, generator_dur_loss=1.748, generator_adv_loss=1.938, generator_feat_match_loss=3.766, over 5158.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 22:00:15,475 INFO [train.py:919] (2/6) Start epoch 217
2024-03-12 22:01:21,234 INFO [train.py:527] (2/6) Epoch 217, batch 16, global_batch_idx: 26800, batch size: 58, loss[discriminator_loss=2.842, discriminator_real_loss=1.351, discriminator_fake_loss=1.491, generator_loss=28.07, generator_mel_loss=18.88, generator_kl_loss=1.331, generator_dur_loss=1.749, generator_adv_loss=2.072, generator_feat_match_loss=4.044, over 58.00 samples.], tot_loss[discriminator_loss=2.758, discriminator_real_loss=1.405, discriminator_fake_loss=1.353, generator_loss=27.37, generator_mel_loss=18.58, generator_kl_loss=1.378, generator_dur_loss=1.761, generator_adv_loss=1.917, generator_feat_match_loss=3.733, over 955.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 22:01:21,236 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 22:01:29,068 INFO [train.py:591] (2/6) Epoch 217, validation: discriminator_loss=2.836, discriminator_real_loss=1.53, discriminator_fake_loss=1.306, generator_loss=26.29, generator_mel_loss=18.49, generator_kl_loss=1.131, generator_dur_loss=1.814, generator_adv_loss=1.997, generator_feat_match_loss=2.857, over 100.00 samples.
2024-03-12 22:01:29,069 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 22:03:48,065 INFO [train.py:527] (2/6) Epoch 217, batch 66, global_batch_idx: 26850, batch size: 59, loss[discriminator_loss=2.748, discriminator_real_loss=1.337, discriminator_fake_loss=1.411, generator_loss=27.79, generator_mel_loss=18.89, generator_kl_loss=1.326, generator_dur_loss=1.723, generator_adv_loss=1.832, generator_feat_match_loss=4.024, over 59.00 samples.], tot_loss[discriminator_loss=2.746, discriminator_real_loss=1.395, discriminator_fake_loss=1.351, generator_loss=27.33, generator_mel_loss=18.55, generator_kl_loss=1.375, generator_dur_loss=1.758, generator_adv_loss=1.91, generator_feat_match_loss=3.73, over 3799.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 22:06:09,852 INFO [train.py:527] (2/6) Epoch 217, batch 116, global_batch_idx: 26900, batch size: 68, loss[discriminator_loss=2.718, discriminator_real_loss=1.423, discriminator_fake_loss=1.295, generator_loss=27.6, generator_mel_loss=18.96, generator_kl_loss=1.349, generator_dur_loss=1.77, generator_adv_loss=1.838, generator_feat_match_loss=3.686, over 68.00 samples.], tot_loss[discriminator_loss=2.749, discriminator_real_loss=1.394, discriminator_fake_loss=1.354, generator_loss=27.3, generator_mel_loss=18.54, generator_kl_loss=1.374, generator_dur_loss=1.757, generator_adv_loss=1.91, generator_feat_match_loss=3.72, over 6894.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 22:06:33,232 INFO [train.py:919] (2/6) Start epoch 218
2024-03-12 22:08:55,538 INFO [train.py:527] (2/6) Epoch 218, batch 42, global_batch_idx: 26950, batch size: 47, loss[discriminator_loss=2.755, discriminator_real_loss=1.415, discriminator_fake_loss=1.34, generator_loss=28.72, generator_mel_loss=19.01, generator_kl_loss=1.529, generator_dur_loss=1.685, generator_adv_loss=2.045, generator_feat_match_loss=4.458, over 47.00 samples.], tot_loss[discriminator_loss=2.729, discriminator_real_loss=1.382, discriminator_fake_loss=1.348, generator_loss=27.57, generator_mel_loss=18.65, generator_kl_loss=1.431, generator_dur_loss=1.73, generator_adv_loss=1.919, generator_feat_match_loss=3.838, over 2242.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 22:11:14,151 INFO [train.py:527] (2/6) Epoch 218, batch 92, global_batch_idx: 27000, batch size: 58, loss[discriminator_loss=2.814, discriminator_real_loss=1.541, discriminator_fake_loss=1.273, generator_loss=26.35, generator_mel_loss=18.19, generator_kl_loss=1.444, generator_dur_loss=1.725, generator_adv_loss=1.76, generator_feat_match_loss=3.226, over 58.00 samples.], tot_loss[discriminator_loss=2.736, discriminator_real_loss=1.386, discriminator_fake_loss=1.35, generator_loss=27.55, generator_mel_loss=18.65, generator_kl_loss=1.418, generator_dur_loss=1.737, generator_adv_loss=1.915, generator_feat_match_loss=3.828, over 5049.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 22:11:14,153 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 22:11:22,206 INFO [train.py:591] (2/6) Epoch 218, validation: discriminator_loss=2.822, discriminator_real_loss=1.38, discriminator_fake_loss=1.442, generator_loss=26.12, generator_mel_loss=18.68, generator_kl_loss=1.194, generator_dur_loss=1.799, generator_adv_loss=1.661, generator_feat_match_loss=2.793, over 100.00 samples.
2024-03-12 22:11:22,207 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 22:12:47,033 INFO [train.py:919] (2/6) Start epoch 219
2024-03-12 22:14:00,069 INFO [train.py:527] (2/6) Epoch 219, batch 18, global_batch_idx: 27050, batch size: 55, loss[discriminator_loss=2.763, discriminator_real_loss=1.541, discriminator_fake_loss=1.222, generator_loss=27.35, generator_mel_loss=18.58, generator_kl_loss=1.395, generator_dur_loss=1.77, generator_adv_loss=1.994, generator_feat_match_loss=3.611, over 55.00 samples.], tot_loss[discriminator_loss=2.75, discriminator_real_loss=1.392, discriminator_fake_loss=1.358, generator_loss=28.24, generator_mel_loss=18.63, generator_kl_loss=1.38, generator_dur_loss=1.787, generator_adv_loss=2.164, generator_feat_match_loss=4.283, over 1219.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 22:16:19,131 INFO [train.py:527] (2/6) Epoch 219, batch 68, global_batch_idx: 27100, batch size: 64, loss[discriminator_loss=2.609, discriminator_real_loss=1.32, discriminator_fake_loss=1.289, generator_loss=27.75, generator_mel_loss=18.43, generator_kl_loss=1.418, generator_dur_loss=1.751, generator_adv_loss=1.923, generator_feat_match_loss=4.235, over 64.00 samples.], tot_loss[discriminator_loss=2.733, discriminator_real_loss=1.393, discriminator_fake_loss=1.339, generator_loss=27.52, generator_mel_loss=18.53, generator_kl_loss=1.379, generator_dur_loss=1.775, generator_adv_loss=1.992, generator_feat_match_loss=3.847, over 4225.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 22:18:34,756 INFO [train.py:527] (2/6) Epoch 219, batch 118, global_batch_idx: 27150, batch size: 80, loss[discriminator_loss=2.724, discriminator_real_loss=1.377, discriminator_fake_loss=1.347, generator_loss=27.72, generator_mel_loss=18.63, generator_kl_loss=1.387, generator_dur_loss=1.83, generator_adv_loss=1.953, generator_feat_match_loss=3.916, over 80.00 samples.], tot_loss[discriminator_loss=2.735, discriminator_real_loss=1.392, discriminator_fake_loss=1.343, generator_loss=27.44, generator_mel_loss=18.53, generator_kl_loss=1.386, generator_dur_loss=1.771, generator_adv_loss=1.957, generator_feat_match_loss=3.787, over 7122.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 22:18:49,872 INFO [train.py:919] (2/6) Start epoch 220
2024-03-12 22:21:10,727 INFO [train.py:527] (2/6) Epoch 220, batch 44, global_batch_idx: 27200, batch size: 31, loss[discriminator_loss=2.827, discriminator_real_loss=1.565, discriminator_fake_loss=1.261, generator_loss=28.18, generator_mel_loss=18.95, generator_kl_loss=1.642, generator_dur_loss=1.617, generator_adv_loss=2.04, generator_feat_match_loss=3.936, over 31.00 samples.], tot_loss[discriminator_loss=2.732, discriminator_real_loss=1.378, discriminator_fake_loss=1.354, generator_loss=27.39, generator_mel_loss=18.54, generator_kl_loss=1.402, generator_dur_loss=1.736, generator_adv_loss=1.943, generator_feat_match_loss=3.774, over 2406.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 22:21:10,729 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 22:21:18,866 INFO [train.py:591] (2/6) Epoch 220, validation: discriminator_loss=2.776, discriminator_real_loss=1.508, discriminator_fake_loss=1.268, generator_loss=26.93, generator_mel_loss=18.91, generator_kl_loss=1.249, generator_dur_loss=1.824, generator_adv_loss=1.972, generator_feat_match_loss=2.972, over 100.00 samples.
2024-03-12 22:21:18,867 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 22:23:37,497 INFO [train.py:527] (2/6) Epoch 220, batch 94, global_batch_idx: 27250, batch size: 77, loss[discriminator_loss=2.733, discriminator_real_loss=1.291, discriminator_fake_loss=1.442, generator_loss=27.28, generator_mel_loss=18.45, generator_kl_loss=1.512, generator_dur_loss=1.811, generator_adv_loss=1.96, generator_feat_match_loss=3.548, over 77.00 samples.], tot_loss[discriminator_loss=2.727, discriminator_real_loss=1.375, discriminator_fake_loss=1.351, generator_loss=27.46, generator_mel_loss=18.58, generator_kl_loss=1.403, generator_dur_loss=1.744, generator_adv_loss=1.924, generator_feat_match_loss=3.808, over 5281.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 22:25:02,315 INFO [train.py:919] (2/6) Start epoch 221
2024-03-12 22:26:20,695 INFO [train.py:527] (2/6) Epoch 221, batch 20, global_batch_idx: 27300, batch size: 58, loss[discriminator_loss=2.795, discriminator_real_loss=1.42, discriminator_fake_loss=1.375, generator_loss=27.32, generator_mel_loss=18.63, generator_kl_loss=1.445, generator_dur_loss=1.725, generator_adv_loss=1.752, generator_feat_match_loss=3.771, over 58.00 samples.], tot_loss[discriminator_loss=2.747, discriminator_real_loss=1.388, discriminator_fake_loss=1.36, generator_loss=27.4, generator_mel_loss=18.69, generator_kl_loss=1.428, generator_dur_loss=1.724, generator_adv_loss=1.893, generator_feat_match_loss=3.669, over 1060.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 22:28:38,536 INFO [train.py:527] (2/6) Epoch 221, batch 70, global_batch_idx: 27350, batch size: 31, loss[discriminator_loss=2.786, discriminator_real_loss=1.409, discriminator_fake_loss=1.377, generator_loss=27.21, generator_mel_loss=18.95, generator_kl_loss=1.328, generator_dur_loss=1.612, generator_adv_loss=2.067, generator_feat_match_loss=3.249, over 31.00 samples.], tot_loss[discriminator_loss=2.74, discriminator_real_loss=1.384, discriminator_fake_loss=1.355, generator_loss=27.44, generator_mel_loss=18.63, generator_kl_loss=1.397, generator_dur_loss=1.754, generator_adv_loss=1.922, generator_feat_match_loss=3.735, over 3901.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 22:30:57,898 INFO [train.py:527] (2/6) Epoch 221, batch 120, global_batch_idx: 27400, batch size: 58, loss[discriminator_loss=2.68, discriminator_real_loss=1.315, discriminator_fake_loss=1.365, generator_loss=28.01, generator_mel_loss=18.95, generator_kl_loss=1.348, generator_dur_loss=1.723, generator_adv_loss=1.949, generator_feat_match_loss=4.034, over 58.00 samples.], tot_loss[discriminator_loss=2.743, discriminator_real_loss=1.39, discriminator_fake_loss=1.353, generator_loss=27.4, generator_mel_loss=18.58, generator_kl_loss=1.379, generator_dur_loss=1.773, generator_adv_loss=1.916, generator_feat_match_loss=3.756, over 7086.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 22:30:57,900 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 22:31:06,763 INFO [train.py:591] (2/6) Epoch 221, validation: discriminator_loss=2.749, discriminator_real_loss=1.474, discriminator_fake_loss=1.275, generator_loss=26.81, generator_mel_loss=18.73, generator_kl_loss=1.234, generator_dur_loss=1.804, generator_adv_loss=1.867, generator_feat_match_loss=3.184, over 100.00 samples.
2024-03-12 22:31:06,765 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 22:31:18,033 INFO [train.py:919] (2/6) Start epoch 222
2024-03-12 22:33:52,124 INFO [train.py:527] (2/6) Epoch 222, batch 46, global_batch_idx: 27450, batch size: 52, loss[discriminator_loss=2.742, discriminator_real_loss=1.386, discriminator_fake_loss=1.356, generator_loss=28.65, generator_mel_loss=19.3, generator_kl_loss=1.452, generator_dur_loss=1.727, generator_adv_loss=2.109, generator_feat_match_loss=4.065, over 52.00 samples.], tot_loss[discriminator_loss=2.725, discriminator_real_loss=1.381, discriminator_fake_loss=1.344, generator_loss=27.4, generator_mel_loss=18.53, generator_kl_loss=1.36, generator_dur_loss=1.768, generator_adv_loss=1.926, generator_feat_match_loss=3.817, over 3020.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 22:36:11,926 INFO [train.py:527] (2/6) Epoch 222, batch 96, global_batch_idx: 27500, batch size: 68, loss[discriminator_loss=2.71, discriminator_real_loss=1.405, discriminator_fake_loss=1.306, generator_loss=27.65, generator_mel_loss=18.9, generator_kl_loss=1.32, generator_dur_loss=1.787, generator_adv_loss=2.01, generator_feat_match_loss=3.63, over 68.00 samples.], tot_loss[discriminator_loss=2.734, discriminator_real_loss=1.38, discriminator_fake_loss=1.354, generator_loss=27.44, generator_mel_loss=18.57, generator_kl_loss=1.375, generator_dur_loss=1.767, generator_adv_loss=1.921, generator_feat_match_loss=3.806, over 5923.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 22:37:23,677 INFO [train.py:919] (2/6) Start epoch 223
2024-03-12 22:38:48,890 INFO [train.py:527] (2/6) Epoch 223, batch 22, global_batch_idx: 27550, batch size: 56, loss[discriminator_loss=2.836, discriminator_real_loss=1.468, discriminator_fake_loss=1.368, generator_loss=27.44, generator_mel_loss=18.51, generator_kl_loss=1.364, generator_dur_loss=1.707, generator_adv_loss=1.927, generator_feat_match_loss=3.929, over 56.00 samples.], tot_loss[discriminator_loss=2.724, discriminator_real_loss=1.37, discriminator_fake_loss=1.354, generator_loss=27.63, generator_mel_loss=18.7, generator_kl_loss=1.4, generator_dur_loss=1.75, generator_adv_loss=1.925, generator_feat_match_loss=3.861, over 1455.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 22:41:08,929 INFO [train.py:527] (2/6) Epoch 223, batch 72, global_batch_idx: 27600, batch size: 66, loss[discriminator_loss=2.737, discriminator_real_loss=1.399, discriminator_fake_loss=1.339, generator_loss=28.08, generator_mel_loss=19.19, generator_kl_loss=1.238, generator_dur_loss=1.823, generator_adv_loss=1.874, generator_feat_match_loss=3.957, over 66.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.374, discriminator_fake_loss=1.346, generator_loss=27.52, generator_mel_loss=18.62, generator_kl_loss=1.389, generator_dur_loss=1.746, generator_adv_loss=1.928, generator_feat_match_loss=3.839, over 4148.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 22:41:08,930 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 22:41:16,882 INFO [train.py:591] (2/6) Epoch 223, validation: discriminator_loss=2.848, discriminator_real_loss=1.505, discriminator_fake_loss=1.342, generator_loss=27.03, generator_mel_loss=19.04, generator_kl_loss=1.2, generator_dur_loss=1.809, generator_adv_loss=1.849, generator_feat_match_loss=3.136, over 100.00 samples.
2024-03-12 22:41:16,883 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 22:43:34,976 INFO [train.py:527] (2/6) Epoch 223, batch 122, global_batch_idx: 27650, batch size: 53, loss[discriminator_loss=2.787, discriminator_real_loss=1.49, discriminator_fake_loss=1.297, generator_loss=27.18, generator_mel_loss=18.53, generator_kl_loss=1.413, generator_dur_loss=1.664, generator_adv_loss=1.95, generator_feat_match_loss=3.625, over 53.00 samples.], tot_loss[discriminator_loss=2.727, discriminator_real_loss=1.38, discriminator_fake_loss=1.348, generator_loss=27.48, generator_mel_loss=18.58, generator_kl_loss=1.396, generator_dur_loss=1.737, generator_adv_loss=1.925, generator_feat_match_loss=3.851, over 6901.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 22:43:40,498 INFO [train.py:919] (2/6) Start epoch 224
2024-03-12 22:46:18,910 INFO [train.py:527] (2/6) Epoch 224, batch 48, global_batch_idx: 27700, batch size: 61, loss[discriminator_loss=2.754, discriminator_real_loss=1.471, discriminator_fake_loss=1.283, generator_loss=27.18, generator_mel_loss=18.43, generator_kl_loss=1.471, generator_dur_loss=1.756, generator_adv_loss=1.914, generator_feat_match_loss=3.609, over 61.00 samples.], tot_loss[discriminator_loss=2.737, discriminator_real_loss=1.394, discriminator_fake_loss=1.342, generator_loss=27.5, generator_mel_loss=18.59, generator_kl_loss=1.406, generator_dur_loss=1.758, generator_adv_loss=1.943, generator_feat_match_loss=3.81, over 2749.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 22:48:42,025 INFO [train.py:527] (2/6) Epoch 224, batch 98, global_batch_idx: 27750, batch size: 70, loss[discriminator_loss=2.756, discriminator_real_loss=1.336, discriminator_fake_loss=1.42, generator_loss=27.27, generator_mel_loss=18.4, generator_kl_loss=1.206, generator_dur_loss=1.763, generator_adv_loss=2.013, generator_feat_match_loss=3.888, over 70.00 samples.], tot_loss[discriminator_loss=2.735, discriminator_real_loss=1.389, discriminator_fake_loss=1.346, generator_loss=27.47, generator_mel_loss=18.58, generator_kl_loss=1.38, generator_dur_loss=1.762, generator_adv_loss=1.932, generator_feat_match_loss=3.813, over 5803.00 samples.], cur_lr_g: 1.95e-04, cur_lr_d: 1.95e-04, 
2024-03-12 22:49:49,705 INFO [train.py:919] (2/6) Start epoch 225
2024-03-12 22:51:18,670 INFO [train.py:527] (2/6) Epoch 225, batch 24, global_batch_idx: 27800, batch size: 31, loss[discriminator_loss=2.687, discriminator_real_loss=1.335, discriminator_fake_loss=1.352, generator_loss=27.66, generator_mel_loss=18.78, generator_kl_loss=1.414, generator_dur_loss=1.656, generator_adv_loss=1.876, generator_feat_match_loss=3.939, over 31.00 samples.], tot_loss[discriminator_loss=2.725, discriminator_real_loss=1.382, discriminator_fake_loss=1.343, generator_loss=27.62, generator_mel_loss=18.62, generator_kl_loss=1.431, generator_dur_loss=1.73, generator_adv_loss=1.958, generator_feat_match_loss=3.879, over 1324.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-12 22:51:18,672 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 22:51:26,435 INFO [train.py:591] (2/6) Epoch 225, validation: discriminator_loss=2.695, discriminator_real_loss=1.385, discriminator_fake_loss=1.31, generator_loss=26.14, generator_mel_loss=18.37, generator_kl_loss=1.122, generator_dur_loss=1.82, generator_adv_loss=1.82, generator_feat_match_loss=3.004, over 100.00 samples.
2024-03-12 22:51:26,436 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 22:53:48,670 INFO [train.py:527] (2/6) Epoch 225, batch 74, global_batch_idx: 27850, batch size: 96, loss[discriminator_loss=3.019, discriminator_real_loss=1.479, discriminator_fake_loss=1.54, generator_loss=26.3, generator_mel_loss=18.31, generator_kl_loss=1.23, generator_dur_loss=1.879, generator_adv_loss=1.868, generator_feat_match_loss=3.012, over 96.00 samples.], tot_loss[discriminator_loss=2.748, discriminator_real_loss=1.393, discriminator_fake_loss=1.355, generator_loss=27.61, generator_mel_loss=18.59, generator_kl_loss=1.399, generator_dur_loss=1.749, generator_adv_loss=1.983, generator_feat_match_loss=3.893, over 4430.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-12 22:56:01,203 INFO [train.py:919] (2/6) Start epoch 226
2024-03-12 22:56:23,985 INFO [train.py:527] (2/6) Epoch 226, batch 0, global_batch_idx: 27900, batch size: 25, loss[discriminator_loss=2.73, discriminator_real_loss=1.431, discriminator_fake_loss=1.3, generator_loss=27.77, generator_mel_loss=19.15, generator_kl_loss=1.498, generator_dur_loss=1.613, generator_adv_loss=1.864, generator_feat_match_loss=3.638, over 25.00 samples.], tot_loss[discriminator_loss=2.73, discriminator_real_loss=1.431, discriminator_fake_loss=1.3, generator_loss=27.77, generator_mel_loss=19.15, generator_kl_loss=1.498, generator_dur_loss=1.613, generator_adv_loss=1.864, generator_feat_match_loss=3.638, over 25.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-12 22:58:40,658 INFO [train.py:527] (2/6) Epoch 226, batch 50, global_batch_idx: 27950, batch size: 83, loss[discriminator_loss=2.752, discriminator_real_loss=1.429, discriminator_fake_loss=1.323, generator_loss=27.38, generator_mel_loss=18.63, generator_kl_loss=1.312, generator_dur_loss=1.859, generator_adv_loss=1.85, generator_feat_match_loss=3.727, over 83.00 samples.], tot_loss[discriminator_loss=2.73, discriminator_real_loss=1.378, discriminator_fake_loss=1.351, generator_loss=27.55, generator_mel_loss=18.63, generator_kl_loss=1.399, generator_dur_loss=1.76, generator_adv_loss=1.905, generator_feat_match_loss=3.853, over 2909.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-12 23:00:58,244 INFO [train.py:527] (2/6) Epoch 226, batch 100, global_batch_idx: 28000, batch size: 52, loss[discriminator_loss=2.752, discriminator_real_loss=1.351, discriminator_fake_loss=1.401, generator_loss=27.25, generator_mel_loss=18.17, generator_kl_loss=1.389, generator_dur_loss=1.706, generator_adv_loss=1.976, generator_feat_match_loss=4.002, over 52.00 samples.], tot_loss[discriminator_loss=2.735, discriminator_real_loss=1.381, discriminator_fake_loss=1.354, generator_loss=27.51, generator_mel_loss=18.59, generator_kl_loss=1.398, generator_dur_loss=1.76, generator_adv_loss=1.909, generator_feat_match_loss=3.86, over 5689.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-12 23:00:58,246 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 23:01:07,117 INFO [train.py:591] (2/6) Epoch 226, validation: discriminator_loss=2.759, discriminator_real_loss=1.512, discriminator_fake_loss=1.247, generator_loss=26.25, generator_mel_loss=18.5, generator_kl_loss=1.084, generator_dur_loss=1.847, generator_adv_loss=1.931, generator_feat_match_loss=2.893, over 100.00 samples.
2024-03-12 23:01:07,118 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 23:02:12,581 INFO [train.py:919] (2/6) Start epoch 227
2024-03-12 23:03:46,723 INFO [train.py:527] (2/6) Epoch 227, batch 26, global_batch_idx: 28050, batch size: 70, loss[discriminator_loss=2.755, discriminator_real_loss=1.455, discriminator_fake_loss=1.3, generator_loss=26.75, generator_mel_loss=18.32, generator_kl_loss=1.453, generator_dur_loss=1.867, generator_adv_loss=1.767, generator_feat_match_loss=3.34, over 70.00 samples.], tot_loss[discriminator_loss=2.732, discriminator_real_loss=1.39, discriminator_fake_loss=1.341, generator_loss=27.4, generator_mel_loss=18.54, generator_kl_loss=1.406, generator_dur_loss=1.783, generator_adv_loss=1.911, generator_feat_match_loss=3.759, over 1560.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-12 23:06:09,280 INFO [train.py:527] (2/6) Epoch 227, batch 76, global_batch_idx: 28100, batch size: 44, loss[discriminator_loss=2.79, discriminator_real_loss=1.329, discriminator_fake_loss=1.461, generator_loss=28.22, generator_mel_loss=19.03, generator_kl_loss=1.497, generator_dur_loss=1.689, generator_adv_loss=1.945, generator_feat_match_loss=4.058, over 44.00 samples.], tot_loss[discriminator_loss=2.739, discriminator_real_loss=1.388, discriminator_fake_loss=1.351, generator_loss=27.31, generator_mel_loss=18.47, generator_kl_loss=1.381, generator_dur_loss=1.788, generator_adv_loss=1.914, generator_feat_match_loss=3.754, over 4559.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-12 23:08:18,197 INFO [train.py:919] (2/6) Start epoch 228
2024-03-12 23:08:47,064 INFO [train.py:527] (2/6) Epoch 228, batch 2, global_batch_idx: 28150, batch size: 88, loss[discriminator_loss=2.672, discriminator_real_loss=1.375, discriminator_fake_loss=1.297, generator_loss=27.03, generator_mel_loss=18.22, generator_kl_loss=1.199, generator_dur_loss=1.833, generator_adv_loss=1.927, generator_feat_match_loss=3.847, over 88.00 samples.], tot_loss[discriminator_loss=2.695, discriminator_real_loss=1.396, discriminator_fake_loss=1.299, generator_loss=27.06, generator_mel_loss=18.29, generator_kl_loss=1.356, generator_dur_loss=1.749, generator_adv_loss=1.946, generator_feat_match_loss=3.724, over 196.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-12 23:11:05,123 INFO [train.py:527] (2/6) Epoch 228, batch 52, global_batch_idx: 28200, batch size: 66, loss[discriminator_loss=2.736, discriminator_real_loss=1.356, discriminator_fake_loss=1.38, generator_loss=27.47, generator_mel_loss=18.5, generator_kl_loss=1.325, generator_dur_loss=1.821, generator_adv_loss=2.03, generator_feat_match_loss=3.795, over 66.00 samples.], tot_loss[discriminator_loss=2.734, discriminator_real_loss=1.386, discriminator_fake_loss=1.348, generator_loss=27.52, generator_mel_loss=18.56, generator_kl_loss=1.424, generator_dur_loss=1.748, generator_adv_loss=1.914, generator_feat_match_loss=3.865, over 2903.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-12 23:11:05,125 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 23:11:13,162 INFO [train.py:591] (2/6) Epoch 228, validation: discriminator_loss=2.724, discriminator_real_loss=1.485, discriminator_fake_loss=1.239, generator_loss=27.09, generator_mel_loss=19.16, generator_kl_loss=1.311, generator_dur_loss=1.835, generator_adv_loss=1.944, generator_feat_match_loss=2.845, over 100.00 samples.
2024-03-12 23:11:13,163 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 23:13:35,305 INFO [train.py:527] (2/6) Epoch 228, batch 102, global_batch_idx: 28250, batch size: 50, loss[discriminator_loss=2.834, discriminator_real_loss=1.343, discriminator_fake_loss=1.491, generator_loss=26.86, generator_mel_loss=18.31, generator_kl_loss=1.33, generator_dur_loss=1.712, generator_adv_loss=1.867, generator_feat_match_loss=3.643, over 50.00 samples.], tot_loss[discriminator_loss=2.742, discriminator_real_loss=1.39, discriminator_fake_loss=1.352, generator_loss=27.4, generator_mel_loss=18.53, generator_kl_loss=1.389, generator_dur_loss=1.765, generator_adv_loss=1.915, generator_feat_match_loss=3.797, over 5848.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-12 23:14:38,625 INFO [train.py:919] (2/6) Start epoch 229
2024-03-12 23:16:23,500 INFO [train.py:527] (2/6) Epoch 229, batch 28, global_batch_idx: 28300, batch size: 83, loss[discriminator_loss=2.659, discriminator_real_loss=1.267, discriminator_fake_loss=1.392, generator_loss=28.03, generator_mel_loss=18.41, generator_kl_loss=1.183, generator_dur_loss=1.874, generator_adv_loss=2.15, generator_feat_match_loss=4.41, over 83.00 samples.], tot_loss[discriminator_loss=2.73, discriminator_real_loss=1.37, discriminator_fake_loss=1.36, generator_loss=27.44, generator_mel_loss=18.55, generator_kl_loss=1.353, generator_dur_loss=1.777, generator_adv_loss=1.916, generator_feat_match_loss=3.842, over 1766.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-12 23:18:44,451 INFO [train.py:527] (2/6) Epoch 229, batch 78, global_batch_idx: 28350, batch size: 52, loss[discriminator_loss=2.749, discriminator_real_loss=1.462, discriminator_fake_loss=1.287, generator_loss=27.42, generator_mel_loss=18.61, generator_kl_loss=1.415, generator_dur_loss=1.705, generator_adv_loss=1.933, generator_feat_match_loss=3.76, over 52.00 samples.], tot_loss[discriminator_loss=2.722, discriminator_real_loss=1.374, discriminator_fake_loss=1.348, generator_loss=27.48, generator_mel_loss=18.54, generator_kl_loss=1.382, generator_dur_loss=1.759, generator_adv_loss=1.941, generator_feat_match_loss=3.86, over 4587.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-12 23:20:53,669 INFO [train.py:919] (2/6) Start epoch 230
2024-03-12 23:21:31,256 INFO [train.py:527] (2/6) Epoch 230, batch 4, global_batch_idx: 28400, batch size: 36, loss[discriminator_loss=2.703, discriminator_real_loss=1.41, discriminator_fake_loss=1.293, generator_loss=27.49, generator_mel_loss=18.22, generator_kl_loss=1.555, generator_dur_loss=1.732, generator_adv_loss=1.906, generator_feat_match_loss=4.08, over 36.00 samples.], tot_loss[discriminator_loss=2.769, discriminator_real_loss=1.421, discriminator_fake_loss=1.349, generator_loss=26.97, generator_mel_loss=18.35, generator_kl_loss=1.376, generator_dur_loss=1.792, generator_adv_loss=1.905, generator_feat_match_loss=3.546, over 309.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-12 23:21:31,259 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 23:21:39,257 INFO [train.py:591] (2/6) Epoch 230, validation: discriminator_loss=2.768, discriminator_real_loss=1.443, discriminator_fake_loss=1.324, generator_loss=25.82, generator_mel_loss=18.11, generator_kl_loss=1.236, generator_dur_loss=1.816, generator_adv_loss=1.875, generator_feat_match_loss=2.781, over 100.00 samples.
2024-03-12 23:21:39,262 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 23:24:02,487 INFO [train.py:527] (2/6) Epoch 230, batch 54, global_batch_idx: 28450, batch size: 45, loss[discriminator_loss=2.706, discriminator_real_loss=1.361, discriminator_fake_loss=1.345, generator_loss=27.81, generator_mel_loss=18.46, generator_kl_loss=1.412, generator_dur_loss=1.69, generator_adv_loss=1.883, generator_feat_match_loss=4.373, over 45.00 samples.], tot_loss[discriminator_loss=2.736, discriminator_real_loss=1.386, discriminator_fake_loss=1.349, generator_loss=27.36, generator_mel_loss=18.5, generator_kl_loss=1.397, generator_dur_loss=1.756, generator_adv_loss=1.903, generator_feat_match_loss=3.805, over 3291.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-12 23:26:23,621 INFO [train.py:527] (2/6) Epoch 230, batch 104, global_batch_idx: 28500, batch size: 83, loss[discriminator_loss=2.734, discriminator_real_loss=1.404, discriminator_fake_loss=1.33, generator_loss=27.56, generator_mel_loss=18.52, generator_kl_loss=1.508, generator_dur_loss=1.817, generator_adv_loss=1.787, generator_feat_match_loss=3.93, over 83.00 samples.], tot_loss[discriminator_loss=2.733, discriminator_real_loss=1.385, discriminator_fake_loss=1.348, generator_loss=27.39, generator_mel_loss=18.51, generator_kl_loss=1.41, generator_dur_loss=1.745, generator_adv_loss=1.907, generator_feat_match_loss=3.82, over 5981.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-12 23:27:17,379 INFO [train.py:919] (2/6) Start epoch 231
2024-03-12 23:29:07,624 INFO [train.py:527] (2/6) Epoch 231, batch 30, global_batch_idx: 28550, batch size: 96, loss[discriminator_loss=2.707, discriminator_real_loss=1.296, discriminator_fake_loss=1.412, generator_loss=27.4, generator_mel_loss=18.55, generator_kl_loss=1.243, generator_dur_loss=1.855, generator_adv_loss=1.887, generator_feat_match_loss=3.856, over 96.00 samples.], tot_loss[discriminator_loss=2.717, discriminator_real_loss=1.368, discriminator_fake_loss=1.349, generator_loss=27.46, generator_mel_loss=18.53, generator_kl_loss=1.386, generator_dur_loss=1.749, generator_adv_loss=1.929, generator_feat_match_loss=3.864, over 1766.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-12 23:31:26,559 INFO [train.py:527] (2/6) Epoch 231, batch 80, global_batch_idx: 28600, batch size: 77, loss[discriminator_loss=2.718, discriminator_real_loss=1.452, discriminator_fake_loss=1.266, generator_loss=27.01, generator_mel_loss=17.96, generator_kl_loss=1.328, generator_dur_loss=1.759, generator_adv_loss=1.932, generator_feat_match_loss=4.03, over 77.00 samples.], tot_loss[discriminator_loss=2.731, discriminator_real_loss=1.382, discriminator_fake_loss=1.349, generator_loss=27.46, generator_mel_loss=18.54, generator_kl_loss=1.393, generator_dur_loss=1.746, generator_adv_loss=1.911, generator_feat_match_loss=3.872, over 4573.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-12 23:31:26,561 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 23:31:34,637 INFO [train.py:591] (2/6) Epoch 231, validation: discriminator_loss=2.722, discriminator_real_loss=1.423, discriminator_fake_loss=1.299, generator_loss=26.46, generator_mel_loss=18.53, generator_kl_loss=1.149, generator_dur_loss=1.8, generator_adv_loss=1.853, generator_feat_match_loss=3.125, over 100.00 samples.
2024-03-12 23:31:34,638 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 23:33:36,978 INFO [train.py:919] (2/6) Start epoch 232
2024-03-12 23:34:17,980 INFO [train.py:527] (2/6) Epoch 232, batch 6, global_batch_idx: 28650, batch size: 47, loss[discriminator_loss=2.665, discriminator_real_loss=1.273, discriminator_fake_loss=1.391, generator_loss=27.72, generator_mel_loss=18.51, generator_kl_loss=1.521, generator_dur_loss=1.731, generator_adv_loss=1.983, generator_feat_match_loss=3.974, over 47.00 samples.], tot_loss[discriminator_loss=2.689, discriminator_real_loss=1.341, discriminator_fake_loss=1.348, generator_loss=27.42, generator_mel_loss=18.46, generator_kl_loss=1.425, generator_dur_loss=1.752, generator_adv_loss=1.947, generator_feat_match_loss=3.836, over 332.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-12 23:36:36,762 INFO [train.py:527] (2/6) Epoch 232, batch 56, global_batch_idx: 28700, batch size: 74, loss[discriminator_loss=2.683, discriminator_real_loss=1.323, discriminator_fake_loss=1.36, generator_loss=27.82, generator_mel_loss=18.64, generator_kl_loss=1.355, generator_dur_loss=1.76, generator_adv_loss=1.974, generator_feat_match_loss=4.099, over 74.00 samples.], tot_loss[discriminator_loss=2.727, discriminator_real_loss=1.376, discriminator_fake_loss=1.35, generator_loss=27.55, generator_mel_loss=18.53, generator_kl_loss=1.398, generator_dur_loss=1.757, generator_adv_loss=1.934, generator_feat_match_loss=3.932, over 3269.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-12 23:38:58,035 INFO [train.py:527] (2/6) Epoch 232, batch 106, global_batch_idx: 28750, batch size: 50, loss[discriminator_loss=2.723, discriminator_real_loss=1.315, discriminator_fake_loss=1.408, generator_loss=27.92, generator_mel_loss=18.9, generator_kl_loss=1.494, generator_dur_loss=1.665, generator_adv_loss=1.911, generator_feat_match_loss=3.946, over 50.00 samples.], tot_loss[discriminator_loss=2.733, discriminator_real_loss=1.383, discriminator_fake_loss=1.35, generator_loss=27.46, generator_mel_loss=18.5, generator_kl_loss=1.403, generator_dur_loss=1.738, generator_adv_loss=1.924, generator_feat_match_loss=3.891, over 6019.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-12 23:39:48,011 INFO [train.py:919] (2/6) Start epoch 233
2024-03-12 23:41:41,850 INFO [train.py:527] (2/6) Epoch 233, batch 32, global_batch_idx: 28800, batch size: 48, loss[discriminator_loss=2.762, discriminator_real_loss=1.486, discriminator_fake_loss=1.276, generator_loss=26.88, generator_mel_loss=18.14, generator_kl_loss=1.476, generator_dur_loss=1.643, generator_adv_loss=1.87, generator_feat_match_loss=3.752, over 48.00 samples.], tot_loss[discriminator_loss=2.732, discriminator_real_loss=1.391, discriminator_fake_loss=1.341, generator_loss=27.44, generator_mel_loss=18.5, generator_kl_loss=1.422, generator_dur_loss=1.709, generator_adv_loss=1.93, generator_feat_match_loss=3.879, over 1600.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-12 23:41:41,852 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 23:41:49,973 INFO [train.py:591] (2/6) Epoch 233, validation: discriminator_loss=2.74, discriminator_real_loss=1.359, discriminator_fake_loss=1.382, generator_loss=26.48, generator_mel_loss=18.5, generator_kl_loss=1.116, generator_dur_loss=1.783, generator_adv_loss=1.798, generator_feat_match_loss=3.277, over 100.00 samples.
2024-03-12 23:41:49,974 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 23:44:12,450 INFO [train.py:527] (2/6) Epoch 233, batch 82, global_batch_idx: 28850, batch size: 66, loss[discriminator_loss=2.67, discriminator_real_loss=1.37, discriminator_fake_loss=1.301, generator_loss=27.34, generator_mel_loss=18.43, generator_kl_loss=1.445, generator_dur_loss=1.719, generator_adv_loss=2.025, generator_feat_match_loss=3.728, over 66.00 samples.], tot_loss[discriminator_loss=2.741, discriminator_real_loss=1.392, discriminator_fake_loss=1.349, generator_loss=27.26, generator_mel_loss=18.43, generator_kl_loss=1.402, generator_dur_loss=1.727, generator_adv_loss=1.922, generator_feat_match_loss=3.783, over 4536.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-12 23:46:10,028 INFO [train.py:919] (2/6) Start epoch 234
2024-03-12 23:46:57,768 INFO [train.py:527] (2/6) Epoch 234, batch 8, global_batch_idx: 28900, batch size: 14, loss[discriminator_loss=2.763, discriminator_real_loss=1.445, discriminator_fake_loss=1.318, generator_loss=28.15, generator_mel_loss=19.95, generator_kl_loss=1.573, generator_dur_loss=1.642, generator_adv_loss=1.725, generator_feat_match_loss=3.261, over 14.00 samples.], tot_loss[discriminator_loss=2.708, discriminator_real_loss=1.378, discriminator_fake_loss=1.33, generator_loss=27.99, generator_mel_loss=18.61, generator_kl_loss=1.455, generator_dur_loss=1.69, generator_adv_loss=1.974, generator_feat_match_loss=4.258, over 380.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-12 23:49:18,831 INFO [train.py:527] (2/6) Epoch 234, batch 58, global_batch_idx: 28950, batch size: 48, loss[discriminator_loss=2.728, discriminator_real_loss=1.376, discriminator_fake_loss=1.352, generator_loss=27.21, generator_mel_loss=18.64, generator_kl_loss=1.507, generator_dur_loss=1.698, generator_adv_loss=1.997, generator_feat_match_loss=3.366, over 48.00 samples.], tot_loss[discriminator_loss=2.74, discriminator_real_loss=1.388, discriminator_fake_loss=1.352, generator_loss=27.48, generator_mel_loss=18.5, generator_kl_loss=1.403, generator_dur_loss=1.753, generator_adv_loss=1.938, generator_feat_match_loss=3.884, over 3314.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-12 23:51:40,511 INFO [train.py:527] (2/6) Epoch 234, batch 108, global_batch_idx: 29000, batch size: 72, loss[discriminator_loss=2.76, discriminator_real_loss=1.432, discriminator_fake_loss=1.328, generator_loss=26.68, generator_mel_loss=17.91, generator_kl_loss=1.24, generator_dur_loss=1.829, generator_adv_loss=1.904, generator_feat_match_loss=3.796, over 72.00 samples.], tot_loss[discriminator_loss=2.739, discriminator_real_loss=1.387, discriminator_fake_loss=1.352, generator_loss=27.43, generator_mel_loss=18.49, generator_kl_loss=1.393, generator_dur_loss=1.762, generator_adv_loss=1.928, generator_feat_match_loss=3.855, over 6212.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-12 23:51:40,512 INFO [train.py:581] (2/6) Computing validation loss
2024-03-12 23:51:49,175 INFO [train.py:591] (2/6) Epoch 234, validation: discriminator_loss=2.773, discriminator_real_loss=1.465, discriminator_fake_loss=1.308, generator_loss=26.51, generator_mel_loss=18.66, generator_kl_loss=1.164, generator_dur_loss=1.825, generator_adv_loss=1.845, generator_feat_match_loss=3.016, over 100.00 samples.
2024-03-12 23:51:49,191 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-12 23:52:33,295 INFO [train.py:919] (2/6) Start epoch 235
2024-03-12 23:54:37,328 INFO [train.py:527] (2/6) Epoch 235, batch 34, global_batch_idx: 29050, batch size: 83, loss[discriminator_loss=2.727, discriminator_real_loss=1.362, discriminator_fake_loss=1.365, generator_loss=27.25, generator_mel_loss=18.46, generator_kl_loss=1.322, generator_dur_loss=1.87, generator_adv_loss=2.027, generator_feat_match_loss=3.573, over 83.00 samples.], tot_loss[discriminator_loss=2.737, discriminator_real_loss=1.39, discriminator_fake_loss=1.346, generator_loss=27.38, generator_mel_loss=18.49, generator_kl_loss=1.398, generator_dur_loss=1.745, generator_adv_loss=1.928, generator_feat_match_loss=3.817, over 1942.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-12 23:57:01,716 INFO [train.py:527] (2/6) Epoch 235, batch 84, global_batch_idx: 29100, batch size: 25, loss[discriminator_loss=2.714, discriminator_real_loss=1.263, discriminator_fake_loss=1.45, generator_loss=27.93, generator_mel_loss=18.98, generator_kl_loss=1.816, generator_dur_loss=1.579, generator_adv_loss=1.773, generator_feat_match_loss=3.779, over 25.00 samples.], tot_loss[discriminator_loss=2.739, discriminator_real_loss=1.385, discriminator_fake_loss=1.354, generator_loss=27.47, generator_mel_loss=18.55, generator_kl_loss=1.407, generator_dur_loss=1.752, generator_adv_loss=1.917, generator_feat_match_loss=3.842, over 4599.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-12 23:58:51,260 INFO [train.py:919] (2/6) Start epoch 236
2024-03-12 23:59:45,942 INFO [train.py:527] (2/6) Epoch 236, batch 10, global_batch_idx: 29150, batch size: 70, loss[discriminator_loss=2.698, discriminator_real_loss=1.348, discriminator_fake_loss=1.35, generator_loss=27.87, generator_mel_loss=18.81, generator_kl_loss=1.397, generator_dur_loss=1.806, generator_adv_loss=1.932, generator_feat_match_loss=3.931, over 70.00 samples.], tot_loss[discriminator_loss=2.729, discriminator_real_loss=1.367, discriminator_fake_loss=1.363, generator_loss=27.6, generator_mel_loss=18.65, generator_kl_loss=1.372, generator_dur_loss=1.76, generator_adv_loss=1.879, generator_feat_match_loss=3.934, over 601.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 00:02:09,689 INFO [train.py:527] (2/6) Epoch 236, batch 60, global_batch_idx: 29200, batch size: 50, loss[discriminator_loss=2.699, discriminator_real_loss=1.21, discriminator_fake_loss=1.489, generator_loss=27.9, generator_mel_loss=18.72, generator_kl_loss=1.542, generator_dur_loss=1.72, generator_adv_loss=1.987, generator_feat_match_loss=3.928, over 50.00 samples.], tot_loss[discriminator_loss=2.731, discriminator_real_loss=1.378, discriminator_fake_loss=1.353, generator_loss=27.51, generator_mel_loss=18.49, generator_kl_loss=1.39, generator_dur_loss=1.786, generator_adv_loss=1.918, generator_feat_match_loss=3.919, over 3640.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 00:02:09,690 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 00:02:17,718 INFO [train.py:591] (2/6) Epoch 236, validation: discriminator_loss=2.744, discriminator_real_loss=1.492, discriminator_fake_loss=1.252, generator_loss=26.21, generator_mel_loss=18.1, generator_kl_loss=1.199, generator_dur_loss=1.843, generator_adv_loss=1.976, generator_feat_match_loss=3.094, over 100.00 samples.
2024-03-13 00:02:17,719 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 00:04:37,628 INFO [train.py:527] (2/6) Epoch 236, batch 110, global_batch_idx: 29250, batch size: 64, loss[discriminator_loss=2.775, discriminator_real_loss=1.311, discriminator_fake_loss=1.464, generator_loss=27.93, generator_mel_loss=18.65, generator_kl_loss=1.305, generator_dur_loss=1.745, generator_adv_loss=1.988, generator_feat_match_loss=4.241, over 64.00 samples.], tot_loss[discriminator_loss=2.732, discriminator_real_loss=1.381, discriminator_fake_loss=1.351, generator_loss=27.52, generator_mel_loss=18.52, generator_kl_loss=1.399, generator_dur_loss=1.776, generator_adv_loss=1.919, generator_feat_match_loss=3.912, over 6533.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 00:05:15,939 INFO [train.py:919] (2/6) Start epoch 237
2024-03-13 00:07:22,827 INFO [train.py:527] (2/6) Epoch 237, batch 36, global_batch_idx: 29300, batch size: 68, loss[discriminator_loss=2.721, discriminator_real_loss=1.385, discriminator_fake_loss=1.336, generator_loss=26.97, generator_mel_loss=18.22, generator_kl_loss=1.322, generator_dur_loss=1.782, generator_adv_loss=1.854, generator_feat_match_loss=3.793, over 68.00 samples.], tot_loss[discriminator_loss=2.732, discriminator_real_loss=1.379, discriminator_fake_loss=1.353, generator_loss=27.44, generator_mel_loss=18.51, generator_kl_loss=1.442, generator_dur_loss=1.759, generator_adv_loss=1.915, generator_feat_match_loss=3.813, over 2059.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 00:09:43,818 INFO [train.py:527] (2/6) Epoch 237, batch 86, global_batch_idx: 29350, batch size: 25, loss[discriminator_loss=2.699, discriminator_real_loss=1.35, discriminator_fake_loss=1.349, generator_loss=28.51, generator_mel_loss=19.07, generator_kl_loss=1.828, generator_dur_loss=1.605, generator_adv_loss=1.886, generator_feat_match_loss=4.12, over 25.00 samples.], tot_loss[discriminator_loss=2.746, discriminator_real_loss=1.394, discriminator_fake_loss=1.352, generator_loss=27.38, generator_mel_loss=18.51, generator_kl_loss=1.429, generator_dur_loss=1.758, generator_adv_loss=1.915, generator_feat_match_loss=3.772, over 4665.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 00:11:31,548 INFO [train.py:919] (2/6) Start epoch 238
2024-03-13 00:12:28,659 INFO [train.py:527] (2/6) Epoch 238, batch 12, global_batch_idx: 29400, batch size: 72, loss[discriminator_loss=2.746, discriminator_real_loss=1.435, discriminator_fake_loss=1.311, generator_loss=27.06, generator_mel_loss=18.11, generator_kl_loss=1.449, generator_dur_loss=1.834, generator_adv_loss=1.906, generator_feat_match_loss=3.758, over 72.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.369, discriminator_fake_loss=1.352, generator_loss=27.38, generator_mel_loss=18.41, generator_kl_loss=1.401, generator_dur_loss=1.801, generator_adv_loss=1.909, generator_feat_match_loss=3.858, over 744.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 00:12:28,663 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 00:12:36,533 INFO [train.py:591] (2/6) Epoch 238, validation: discriminator_loss=2.752, discriminator_real_loss=1.42, discriminator_fake_loss=1.332, generator_loss=26.55, generator_mel_loss=18.81, generator_kl_loss=1.148, generator_dur_loss=1.852, generator_adv_loss=1.926, generator_feat_match_loss=2.812, over 100.00 samples.
2024-03-13 00:12:36,534 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 00:14:57,994 INFO [train.py:527] (2/6) Epoch 238, batch 62, global_batch_idx: 29450, batch size: 60, loss[discriminator_loss=2.699, discriminator_real_loss=1.336, discriminator_fake_loss=1.363, generator_loss=29.45, generator_mel_loss=19.06, generator_kl_loss=1.422, generator_dur_loss=1.771, generator_adv_loss=2.032, generator_feat_match_loss=5.164, over 60.00 samples.], tot_loss[discriminator_loss=2.728, discriminator_real_loss=1.371, discriminator_fake_loss=1.357, generator_loss=27.53, generator_mel_loss=18.49, generator_kl_loss=1.407, generator_dur_loss=1.771, generator_adv_loss=1.946, generator_feat_match_loss=3.91, over 3407.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 00:17:20,345 INFO [train.py:527] (2/6) Epoch 238, batch 112, global_batch_idx: 29500, batch size: 48, loss[discriminator_loss=2.733, discriminator_real_loss=1.458, discriminator_fake_loss=1.275, generator_loss=27.14, generator_mel_loss=18.21, generator_kl_loss=1.62, generator_dur_loss=1.649, generator_adv_loss=1.915, generator_feat_match_loss=3.747, over 48.00 samples.], tot_loss[discriminator_loss=2.734, discriminator_real_loss=1.376, discriminator_fake_loss=1.358, generator_loss=27.5, generator_mel_loss=18.49, generator_kl_loss=1.4, generator_dur_loss=1.775, generator_adv_loss=1.944, generator_feat_match_loss=3.893, over 6283.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 00:17:51,106 INFO [train.py:919] (2/6) Start epoch 239
2024-03-13 00:20:03,213 INFO [train.py:527] (2/6) Epoch 239, batch 38, global_batch_idx: 29550, batch size: 15, loss[discriminator_loss=2.734, discriminator_real_loss=1.279, discriminator_fake_loss=1.455, generator_loss=28.55, generator_mel_loss=18.92, generator_kl_loss=1.602, generator_dur_loss=1.601, generator_adv_loss=2.086, generator_feat_match_loss=4.345, over 15.00 samples.], tot_loss[discriminator_loss=2.754, discriminator_real_loss=1.4, discriminator_fake_loss=1.353, generator_loss=27.29, generator_mel_loss=18.43, generator_kl_loss=1.377, generator_dur_loss=1.78, generator_adv_loss=1.917, generator_feat_match_loss=3.791, over 2222.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 00:22:24,338 INFO [train.py:527] (2/6) Epoch 239, batch 88, global_batch_idx: 29600, batch size: 53, loss[discriminator_loss=2.686, discriminator_real_loss=1.335, discriminator_fake_loss=1.351, generator_loss=28.23, generator_mel_loss=19.14, generator_kl_loss=1.527, generator_dur_loss=1.743, generator_adv_loss=1.993, generator_feat_match_loss=3.82, over 53.00 samples.], tot_loss[discriminator_loss=2.74, discriminator_real_loss=1.393, discriminator_fake_loss=1.347, generator_loss=27.35, generator_mel_loss=18.42, generator_kl_loss=1.395, generator_dur_loss=1.778, generator_adv_loss=1.917, generator_feat_match_loss=3.837, over 5011.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 00:22:24,340 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 00:22:33,354 INFO [train.py:591] (2/6) Epoch 239, validation: discriminator_loss=2.695, discriminator_real_loss=1.44, discriminator_fake_loss=1.255, generator_loss=26.48, generator_mel_loss=18.34, generator_kl_loss=1.229, generator_dur_loss=1.854, generator_adv_loss=1.96, generator_feat_match_loss=3.105, over 100.00 samples.
2024-03-13 00:22:33,354 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 00:24:15,163 INFO [train.py:919] (2/6) Start epoch 240
2024-03-13 00:25:20,322 INFO [train.py:527] (2/6) Epoch 240, batch 14, global_batch_idx: 29650, batch size: 47, loss[discriminator_loss=2.695, discriminator_real_loss=1.308, discriminator_fake_loss=1.387, generator_loss=27.89, generator_mel_loss=18.84, generator_kl_loss=1.53, generator_dur_loss=1.668, generator_adv_loss=1.987, generator_feat_match_loss=3.867, over 47.00 samples.], tot_loss[discriminator_loss=2.717, discriminator_real_loss=1.388, discriminator_fake_loss=1.329, generator_loss=27.45, generator_mel_loss=18.49, generator_kl_loss=1.354, generator_dur_loss=1.784, generator_adv_loss=1.936, generator_feat_match_loss=3.89, over 1008.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 00:27:41,185 INFO [train.py:527] (2/6) Epoch 240, batch 64, global_batch_idx: 29700, batch size: 80, loss[discriminator_loss=2.732, discriminator_real_loss=1.303, discriminator_fake_loss=1.428, generator_loss=27.79, generator_mel_loss=18.56, generator_kl_loss=1.361, generator_dur_loss=1.905, generator_adv_loss=1.952, generator_feat_match_loss=4.017, over 80.00 samples.], tot_loss[discriminator_loss=2.722, discriminator_real_loss=1.381, discriminator_fake_loss=1.341, generator_loss=27.39, generator_mel_loss=18.47, generator_kl_loss=1.375, generator_dur_loss=1.771, generator_adv_loss=1.922, generator_feat_match_loss=3.847, over 4050.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 00:30:00,484 INFO [train.py:527] (2/6) Epoch 240, batch 114, global_batch_idx: 29750, batch size: 64, loss[discriminator_loss=2.729, discriminator_real_loss=1.338, discriminator_fake_loss=1.391, generator_loss=26.85, generator_mel_loss=18.05, generator_kl_loss=1.327, generator_dur_loss=1.776, generator_adv_loss=2.087, generator_feat_match_loss=3.608, over 64.00 samples.], tot_loss[discriminator_loss=2.728, discriminator_real_loss=1.385, discriminator_fake_loss=1.343, generator_loss=27.41, generator_mel_loss=18.47, generator_kl_loss=1.382, generator_dur_loss=1.77, generator_adv_loss=1.923, generator_feat_match_loss=3.864, over 6979.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 00:30:28,297 INFO [train.py:919] (2/6) Start epoch 241
2024-03-13 00:32:44,560 INFO [train.py:527] (2/6) Epoch 241, batch 40, global_batch_idx: 29800, batch size: 74, loss[discriminator_loss=2.661, discriminator_real_loss=1.298, discriminator_fake_loss=1.363, generator_loss=28.46, generator_mel_loss=19.03, generator_kl_loss=1.332, generator_dur_loss=1.81, generator_adv_loss=2.104, generator_feat_match_loss=4.181, over 74.00 samples.], tot_loss[discriminator_loss=2.729, discriminator_real_loss=1.379, discriminator_fake_loss=1.35, generator_loss=27.46, generator_mel_loss=18.43, generator_kl_loss=1.375, generator_dur_loss=1.783, generator_adv_loss=1.954, generator_feat_match_loss=3.92, over 2316.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 00:32:44,562 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 00:32:52,458 INFO [train.py:591] (2/6) Epoch 241, validation: discriminator_loss=2.611, discriminator_real_loss=1.419, discriminator_fake_loss=1.192, generator_loss=26.98, generator_mel_loss=18.69, generator_kl_loss=1.14, generator_dur_loss=1.838, generator_adv_loss=2.076, generator_feat_match_loss=3.241, over 100.00 samples.
2024-03-13 00:32:52,459 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 00:35:13,501 INFO [train.py:527] (2/6) Epoch 241, batch 90, global_batch_idx: 29850, batch size: 36, loss[discriminator_loss=2.637, discriminator_real_loss=1.36, discriminator_fake_loss=1.277, generator_loss=29.53, generator_mel_loss=19.65, generator_kl_loss=1.536, generator_dur_loss=1.694, generator_adv_loss=1.87, generator_feat_match_loss=4.779, over 36.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.383, discriminator_fake_loss=1.343, generator_loss=27.55, generator_mel_loss=18.51, generator_kl_loss=1.382, generator_dur_loss=1.779, generator_adv_loss=1.942, generator_feat_match_loss=3.938, over 5201.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 00:36:43,396 INFO [train.py:919] (2/6) Start epoch 242
2024-03-13 00:37:54,122 INFO [train.py:527] (2/6) Epoch 242, batch 16, global_batch_idx: 29900, batch size: 77, loss[discriminator_loss=2.707, discriminator_real_loss=1.304, discriminator_fake_loss=1.403, generator_loss=27.68, generator_mel_loss=18.41, generator_kl_loss=1.213, generator_dur_loss=1.854, generator_adv_loss=1.942, generator_feat_match_loss=4.261, over 77.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.361, discriminator_fake_loss=1.354, generator_loss=27.38, generator_mel_loss=18.41, generator_kl_loss=1.352, generator_dur_loss=1.813, generator_adv_loss=1.927, generator_feat_match_loss=3.875, over 1076.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 00:40:15,149 INFO [train.py:527] (2/6) Epoch 242, batch 66, global_batch_idx: 29950, batch size: 42, loss[discriminator_loss=2.727, discriminator_real_loss=1.376, discriminator_fake_loss=1.352, generator_loss=27.92, generator_mel_loss=18.28, generator_kl_loss=1.646, generator_dur_loss=1.702, generator_adv_loss=2.202, generator_feat_match_loss=4.084, over 42.00 samples.], tot_loss[discriminator_loss=2.733, discriminator_real_loss=1.375, discriminator_fake_loss=1.358, generator_loss=27.43, generator_mel_loss=18.47, generator_kl_loss=1.37, generator_dur_loss=1.793, generator_adv_loss=1.933, generator_feat_match_loss=3.863, over 4170.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 00:42:32,714 INFO [train.py:527] (2/6) Epoch 242, batch 116, global_batch_idx: 30000, batch size: 70, loss[discriminator_loss=2.753, discriminator_real_loss=1.36, discriminator_fake_loss=1.393, generator_loss=27.18, generator_mel_loss=18.1, generator_kl_loss=1.29, generator_dur_loss=1.806, generator_adv_loss=2.024, generator_feat_match_loss=3.958, over 70.00 samples.], tot_loss[discriminator_loss=2.731, discriminator_real_loss=1.377, discriminator_fake_loss=1.355, generator_loss=27.42, generator_mel_loss=18.44, generator_kl_loss=1.383, generator_dur_loss=1.78, generator_adv_loss=1.924, generator_feat_match_loss=3.889, over 7122.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 00:42:32,716 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 00:42:41,231 INFO [train.py:591] (2/6) Epoch 242, validation: discriminator_loss=2.756, discriminator_real_loss=1.482, discriminator_fake_loss=1.275, generator_loss=27.11, generator_mel_loss=18.56, generator_kl_loss=1.247, generator_dur_loss=1.811, generator_adv_loss=1.991, generator_feat_match_loss=3.501, over 100.00 samples.
2024-03-13 00:42:41,232 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 00:43:01,528 INFO [train.py:919] (2/6) Start epoch 243
2024-03-13 00:45:22,703 INFO [train.py:527] (2/6) Epoch 243, batch 42, global_batch_idx: 30050, batch size: 52, loss[discriminator_loss=2.721, discriminator_real_loss=1.494, discriminator_fake_loss=1.228, generator_loss=27.47, generator_mel_loss=18.29, generator_kl_loss=1.548, generator_dur_loss=1.736, generator_adv_loss=1.869, generator_feat_match_loss=4.026, over 52.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.377, discriminator_fake_loss=1.343, generator_loss=27.6, generator_mel_loss=18.55, generator_kl_loss=1.396, generator_dur_loss=1.756, generator_adv_loss=1.924, generator_feat_match_loss=3.969, over 2428.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 00:47:41,929 INFO [train.py:527] (2/6) Epoch 243, batch 92, global_batch_idx: 30100, batch size: 96, loss[discriminator_loss=2.759, discriminator_real_loss=1.415, discriminator_fake_loss=1.344, generator_loss=26.64, generator_mel_loss=18.24, generator_kl_loss=1.176, generator_dur_loss=1.873, generator_adv_loss=1.836, generator_feat_match_loss=3.51, over 96.00 samples.], tot_loss[discriminator_loss=2.724, discriminator_real_loss=1.376, discriminator_fake_loss=1.348, generator_loss=27.55, generator_mel_loss=18.49, generator_kl_loss=1.377, generator_dur_loss=1.762, generator_adv_loss=1.939, generator_feat_match_loss=3.98, over 5517.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 00:49:07,973 INFO [train.py:919] (2/6) Start epoch 244
2024-03-13 00:50:23,893 INFO [train.py:527] (2/6) Epoch 244, batch 18, global_batch_idx: 30150, batch size: 62, loss[discriminator_loss=2.723, discriminator_real_loss=1.266, discriminator_fake_loss=1.457, generator_loss=27.58, generator_mel_loss=18.64, generator_kl_loss=1.208, generator_dur_loss=1.76, generator_adv_loss=2.052, generator_feat_match_loss=3.913, over 62.00 samples.], tot_loss[discriminator_loss=2.735, discriminator_real_loss=1.387, discriminator_fake_loss=1.348, generator_loss=27.4, generator_mel_loss=18.54, generator_kl_loss=1.394, generator_dur_loss=1.772, generator_adv_loss=1.896, generator_feat_match_loss=3.795, over 1022.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 00:52:43,015 INFO [train.py:527] (2/6) Epoch 244, batch 68, global_batch_idx: 30200, batch size: 61, loss[discriminator_loss=2.73, discriminator_real_loss=1.364, discriminator_fake_loss=1.367, generator_loss=27.07, generator_mel_loss=17.83, generator_kl_loss=1.485, generator_dur_loss=1.724, generator_adv_loss=1.956, generator_feat_match_loss=4.074, over 61.00 samples.], tot_loss[discriminator_loss=2.735, discriminator_real_loss=1.391, discriminator_fake_loss=1.344, generator_loss=27.5, generator_mel_loss=18.52, generator_kl_loss=1.39, generator_dur_loss=1.775, generator_adv_loss=1.913, generator_feat_match_loss=3.901, over 3848.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 00:52:43,016 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 00:52:50,820 INFO [train.py:591] (2/6) Epoch 244, validation: discriminator_loss=2.754, discriminator_real_loss=1.48, discriminator_fake_loss=1.274, generator_loss=25.97, generator_mel_loss=18.17, generator_kl_loss=1.073, generator_dur_loss=1.844, generator_adv_loss=1.922, generator_feat_match_loss=2.962, over 100.00 samples.
2024-03-13 00:52:50,821 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 00:55:09,624 INFO [train.py:527] (2/6) Epoch 244, batch 118, global_batch_idx: 30250, batch size: 83, loss[discriminator_loss=2.763, discriminator_real_loss=1.305, discriminator_fake_loss=1.458, generator_loss=26.14, generator_mel_loss=17.95, generator_kl_loss=1.188, generator_dur_loss=1.877, generator_adv_loss=1.902, generator_feat_match_loss=3.218, over 83.00 samples.], tot_loss[discriminator_loss=2.735, discriminator_real_loss=1.388, discriminator_fake_loss=1.348, generator_loss=27.57, generator_mel_loss=18.53, generator_kl_loss=1.386, generator_dur_loss=1.786, generator_adv_loss=1.922, generator_feat_match_loss=3.943, over 6878.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 00:55:24,428 INFO [train.py:919] (2/6) Start epoch 245
2024-03-13 00:57:48,110 INFO [train.py:527] (2/6) Epoch 245, batch 44, global_batch_idx: 30300, batch size: 80, loss[discriminator_loss=2.745, discriminator_real_loss=1.43, discriminator_fake_loss=1.315, generator_loss=27.54, generator_mel_loss=18.84, generator_kl_loss=1.168, generator_dur_loss=1.834, generator_adv_loss=1.943, generator_feat_match_loss=3.763, over 80.00 samples.], tot_loss[discriminator_loss=2.744, discriminator_real_loss=1.394, discriminator_fake_loss=1.35, generator_loss=27.51, generator_mel_loss=18.56, generator_kl_loss=1.402, generator_dur_loss=1.759, generator_adv_loss=1.91, generator_feat_match_loss=3.882, over 2525.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 01:00:05,251 INFO [train.py:527] (2/6) Epoch 245, batch 94, global_batch_idx: 30350, batch size: 55, loss[discriminator_loss=2.813, discriminator_real_loss=1.387, discriminator_fake_loss=1.426, generator_loss=26.82, generator_mel_loss=18.26, generator_kl_loss=1.389, generator_dur_loss=1.733, generator_adv_loss=2.02, generator_feat_match_loss=3.423, over 55.00 samples.], tot_loss[discriminator_loss=2.737, discriminator_real_loss=1.391, discriminator_fake_loss=1.346, generator_loss=27.42, generator_mel_loss=18.47, generator_kl_loss=1.397, generator_dur_loss=1.762, generator_adv_loss=1.914, generator_feat_match_loss=3.876, over 5462.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 01:01:29,224 INFO [train.py:919] (2/6) Start epoch 246
2024-03-13 01:02:46,364 INFO [train.py:527] (2/6) Epoch 246, batch 20, global_batch_idx: 30400, batch size: 15, loss[discriminator_loss=2.84, discriminator_real_loss=1.581, discriminator_fake_loss=1.259, generator_loss=28.87, generator_mel_loss=19.25, generator_kl_loss=1.749, generator_dur_loss=1.647, generator_adv_loss=1.954, generator_feat_match_loss=4.268, over 15.00 samples.], tot_loss[discriminator_loss=2.762, discriminator_real_loss=1.404, discriminator_fake_loss=1.358, generator_loss=27.65, generator_mel_loss=18.61, generator_kl_loss=1.409, generator_dur_loss=1.786, generator_adv_loss=1.925, generator_feat_match_loss=3.912, over 1071.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 01:02:46,366 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 01:02:54,161 INFO [train.py:591] (2/6) Epoch 246, validation: discriminator_loss=2.815, discriminator_real_loss=1.444, discriminator_fake_loss=1.371, generator_loss=26.77, generator_mel_loss=18.83, generator_kl_loss=1.235, generator_dur_loss=1.858, generator_adv_loss=1.815, generator_feat_match_loss=3.026, over 100.00 samples.
2024-03-13 01:02:54,162 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 01:05:15,245 INFO [train.py:527] (2/6) Epoch 246, batch 70, global_batch_idx: 30450, batch size: 31, loss[discriminator_loss=2.669, discriminator_real_loss=1.379, discriminator_fake_loss=1.289, generator_loss=27.78, generator_mel_loss=18.34, generator_kl_loss=1.627, generator_dur_loss=1.652, generator_adv_loss=2.029, generator_feat_match_loss=4.132, over 31.00 samples.], tot_loss[discriminator_loss=2.745, discriminator_real_loss=1.389, discriminator_fake_loss=1.356, generator_loss=27.51, generator_mel_loss=18.49, generator_kl_loss=1.406, generator_dur_loss=1.782, generator_adv_loss=1.915, generator_feat_match_loss=3.917, over 3923.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 01:07:31,701 INFO [train.py:527] (2/6) Epoch 246, batch 120, global_batch_idx: 30500, batch size: 31, loss[discriminator_loss=2.674, discriminator_real_loss=1.359, discriminator_fake_loss=1.315, generator_loss=28.92, generator_mel_loss=19.13, generator_kl_loss=1.629, generator_dur_loss=1.629, generator_adv_loss=1.959, generator_feat_match_loss=4.571, over 31.00 samples.], tot_loss[discriminator_loss=2.735, discriminator_real_loss=1.382, discriminator_fake_loss=1.353, generator_loss=27.54, generator_mel_loss=18.51, generator_kl_loss=1.401, generator_dur_loss=1.773, generator_adv_loss=1.915, generator_feat_match_loss=3.936, over 6743.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 01:07:42,075 INFO [train.py:919] (2/6) Start epoch 247
2024-03-13 01:10:17,066 INFO [train.py:527] (2/6) Epoch 247, batch 46, global_batch_idx: 30550, batch size: 80, loss[discriminator_loss=2.771, discriminator_real_loss=1.364, discriminator_fake_loss=1.407, generator_loss=27.81, generator_mel_loss=18.52, generator_kl_loss=1.411, generator_dur_loss=1.817, generator_adv_loss=1.931, generator_feat_match_loss=4.135, over 80.00 samples.], tot_loss[discriminator_loss=2.748, discriminator_real_loss=1.393, discriminator_fake_loss=1.355, generator_loss=27.53, generator_mel_loss=18.61, generator_kl_loss=1.409, generator_dur_loss=1.778, generator_adv_loss=1.916, generator_feat_match_loss=3.822, over 2554.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 01:12:34,191 INFO [train.py:527] (2/6) Epoch 247, batch 96, global_batch_idx: 30600, batch size: 56, loss[discriminator_loss=2.746, discriminator_real_loss=1.395, discriminator_fake_loss=1.352, generator_loss=26.9, generator_mel_loss=18.13, generator_kl_loss=1.398, generator_dur_loss=1.766, generator_adv_loss=1.699, generator_feat_match_loss=3.907, over 56.00 samples.], tot_loss[discriminator_loss=2.744, discriminator_real_loss=1.391, discriminator_fake_loss=1.354, generator_loss=27.52, generator_mel_loss=18.55, generator_kl_loss=1.397, generator_dur_loss=1.781, generator_adv_loss=1.924, generator_feat_match_loss=3.873, over 5425.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 01:12:34,192 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 01:12:43,017 INFO [train.py:591] (2/6) Epoch 247, validation: discriminator_loss=2.79, discriminator_real_loss=1.374, discriminator_fake_loss=1.416, generator_loss=25.86, generator_mel_loss=18.28, generator_kl_loss=1.187, generator_dur_loss=1.851, generator_adv_loss=1.691, generator_feat_match_loss=2.855, over 100.00 samples.
2024-03-13 01:12:43,018 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 01:13:59,480 INFO [train.py:919] (2/6) Start epoch 248
2024-03-13 01:15:24,457 INFO [train.py:527] (2/6) Epoch 248, batch 22, global_batch_idx: 30650, batch size: 31, loss[discriminator_loss=2.685, discriminator_real_loss=1.317, discriminator_fake_loss=1.368, generator_loss=27.53, generator_mel_loss=18.61, generator_kl_loss=1.55, generator_dur_loss=1.643, generator_adv_loss=1.857, generator_feat_match_loss=3.872, over 31.00 samples.], tot_loss[discriminator_loss=2.738, discriminator_real_loss=1.393, discriminator_fake_loss=1.345, generator_loss=27.48, generator_mel_loss=18.41, generator_kl_loss=1.391, generator_dur_loss=1.774, generator_adv_loss=1.923, generator_feat_match_loss=3.986, over 1480.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 01:17:42,689 INFO [train.py:527] (2/6) Epoch 248, batch 72, global_batch_idx: 30700, batch size: 62, loss[discriminator_loss=2.705, discriminator_real_loss=1.43, discriminator_fake_loss=1.274, generator_loss=27.07, generator_mel_loss=18.24, generator_kl_loss=1.325, generator_dur_loss=1.762, generator_adv_loss=1.955, generator_feat_match_loss=3.79, over 62.00 samples.], tot_loss[discriminator_loss=2.728, discriminator_real_loss=1.38, discriminator_fake_loss=1.348, generator_loss=27.55, generator_mel_loss=18.51, generator_kl_loss=1.387, generator_dur_loss=1.77, generator_adv_loss=1.924, generator_feat_match_loss=3.954, over 4417.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 01:20:00,097 INFO [train.py:527] (2/6) Epoch 248, batch 122, global_batch_idx: 30750, batch size: 96, loss[discriminator_loss=2.721, discriminator_real_loss=1.379, discriminator_fake_loss=1.342, generator_loss=27.47, generator_mel_loss=18.4, generator_kl_loss=1.388, generator_dur_loss=1.818, generator_adv_loss=1.989, generator_feat_match_loss=3.871, over 96.00 samples.], tot_loss[discriminator_loss=2.729, discriminator_real_loss=1.384, discriminator_fake_loss=1.346, generator_loss=27.48, generator_mel_loss=18.47, generator_kl_loss=1.396, generator_dur_loss=1.766, generator_adv_loss=1.922, generator_feat_match_loss=3.922, over 7110.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 01:20:05,828 INFO [train.py:919] (2/6) Start epoch 249
2024-03-13 01:22:42,440 INFO [train.py:527] (2/6) Epoch 249, batch 48, global_batch_idx: 30800, batch size: 48, loss[discriminator_loss=2.741, discriminator_real_loss=1.361, discriminator_fake_loss=1.379, generator_loss=27.61, generator_mel_loss=18.5, generator_kl_loss=1.424, generator_dur_loss=1.684, generator_adv_loss=1.957, generator_feat_match_loss=4.047, over 48.00 samples.], tot_loss[discriminator_loss=2.748, discriminator_real_loss=1.391, discriminator_fake_loss=1.357, generator_loss=27.51, generator_mel_loss=18.5, generator_kl_loss=1.424, generator_dur_loss=1.746, generator_adv_loss=1.908, generator_feat_match_loss=3.924, over 2670.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 01:22:42,442 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 01:22:50,509 INFO [train.py:591] (2/6) Epoch 249, validation: discriminator_loss=2.733, discriminator_real_loss=1.498, discriminator_fake_loss=1.234, generator_loss=26.64, generator_mel_loss=18.71, generator_kl_loss=1.198, generator_dur_loss=1.834, generator_adv_loss=1.961, generator_feat_match_loss=2.934, over 100.00 samples.
2024-03-13 01:22:50,510 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 01:25:08,809 INFO [train.py:527] (2/6) Epoch 249, batch 98, global_batch_idx: 30850, batch size: 53, loss[discriminator_loss=2.716, discriminator_real_loss=1.393, discriminator_fake_loss=1.324, generator_loss=27.46, generator_mel_loss=18.33, generator_kl_loss=1.412, generator_dur_loss=1.717, generator_adv_loss=1.99, generator_feat_match_loss=4.012, over 53.00 samples.], tot_loss[discriminator_loss=2.738, discriminator_real_loss=1.386, discriminator_fake_loss=1.352, generator_loss=27.51, generator_mel_loss=18.49, generator_kl_loss=1.398, generator_dur_loss=1.763, generator_adv_loss=1.915, generator_feat_match_loss=3.941, over 5754.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 01:26:20,094 INFO [train.py:919] (2/6) Start epoch 250
2024-03-13 01:27:49,283 INFO [train.py:527] (2/6) Epoch 250, batch 24, global_batch_idx: 30900, batch size: 47, loss[discriminator_loss=2.69, discriminator_real_loss=1.42, discriminator_fake_loss=1.27, generator_loss=27.74, generator_mel_loss=18.69, generator_kl_loss=1.519, generator_dur_loss=1.661, generator_adv_loss=1.864, generator_feat_match_loss=4.008, over 47.00 samples.], tot_loss[discriminator_loss=2.731, discriminator_real_loss=1.383, discriminator_fake_loss=1.348, generator_loss=27.59, generator_mel_loss=18.54, generator_kl_loss=1.39, generator_dur_loss=1.746, generator_adv_loss=1.922, generator_feat_match_loss=3.984, over 1329.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 01:30:07,451 INFO [train.py:527] (2/6) Epoch 250, batch 74, global_batch_idx: 30950, batch size: 64, loss[discriminator_loss=2.721, discriminator_real_loss=1.461, discriminator_fake_loss=1.26, generator_loss=27.78, generator_mel_loss=18.66, generator_kl_loss=1.342, generator_dur_loss=1.804, generator_adv_loss=1.952, generator_feat_match_loss=4.03, over 64.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.382, discriminator_fake_loss=1.344, generator_loss=27.55, generator_mel_loss=18.48, generator_kl_loss=1.405, generator_dur_loss=1.742, generator_adv_loss=1.923, generator_feat_match_loss=3.998, over 4098.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 01:32:28,202 INFO [train.py:919] (2/6) Start epoch 251
2024-03-13 01:32:48,893 INFO [train.py:527] (2/6) Epoch 251, batch 0, global_batch_idx: 31000, batch size: 31, loss[discriminator_loss=2.809, discriminator_real_loss=1.507, discriminator_fake_loss=1.302, generator_loss=26.13, generator_mel_loss=18.25, generator_kl_loss=1.573, generator_dur_loss=1.666, generator_adv_loss=1.849, generator_feat_match_loss=2.789, over 31.00 samples.], tot_loss[discriminator_loss=2.809, discriminator_real_loss=1.507, discriminator_fake_loss=1.302, generator_loss=26.13, generator_mel_loss=18.25, generator_kl_loss=1.573, generator_dur_loss=1.666, generator_adv_loss=1.849, generator_feat_match_loss=2.789, over 31.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 01:32:48,897 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 01:32:56,661 INFO [train.py:591] (2/6) Epoch 251, validation: discriminator_loss=2.724, discriminator_real_loss=1.416, discriminator_fake_loss=1.308, generator_loss=26.43, generator_mel_loss=18.63, generator_kl_loss=1.232, generator_dur_loss=1.815, generator_adv_loss=1.85, generator_feat_match_loss=2.905, over 100.00 samples.
2024-03-13 01:32:56,663 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 01:35:15,909 INFO [train.py:527] (2/6) Epoch 251, batch 50, global_batch_idx: 31050, batch size: 70, loss[discriminator_loss=2.72, discriminator_real_loss=1.394, discriminator_fake_loss=1.326, generator_loss=27.58, generator_mel_loss=18.29, generator_kl_loss=1.149, generator_dur_loss=1.798, generator_adv_loss=1.879, generator_feat_match_loss=4.469, over 70.00 samples.], tot_loss[discriminator_loss=2.729, discriminator_real_loss=1.393, discriminator_fake_loss=1.337, generator_loss=27.38, generator_mel_loss=18.42, generator_kl_loss=1.395, generator_dur_loss=1.733, generator_adv_loss=1.915, generator_feat_match_loss=3.916, over 2759.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 01:37:37,607 INFO [train.py:527] (2/6) Epoch 251, batch 100, global_batch_idx: 31100, batch size: 66, loss[discriminator_loss=2.748, discriminator_real_loss=1.301, discriminator_fake_loss=1.447, generator_loss=28.23, generator_mel_loss=18.97, generator_kl_loss=1.262, generator_dur_loss=1.775, generator_adv_loss=1.909, generator_feat_match_loss=4.314, over 66.00 samples.], tot_loss[discriminator_loss=2.732, discriminator_real_loss=1.388, discriminator_fake_loss=1.343, generator_loss=27.41, generator_mel_loss=18.45, generator_kl_loss=1.391, generator_dur_loss=1.748, generator_adv_loss=1.916, generator_feat_match_loss=3.907, over 5646.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 01:38:39,238 INFO [train.py:919] (2/6) Start epoch 252
2024-03-13 01:40:17,971 INFO [train.py:527] (2/6) Epoch 252, batch 26, global_batch_idx: 31150, batch size: 55, loss[discriminator_loss=2.738, discriminator_real_loss=1.36, discriminator_fake_loss=1.378, generator_loss=27.48, generator_mel_loss=18.62, generator_kl_loss=1.326, generator_dur_loss=1.726, generator_adv_loss=1.964, generator_feat_match_loss=3.851, over 55.00 samples.], tot_loss[discriminator_loss=2.723, discriminator_real_loss=1.376, discriminator_fake_loss=1.347, generator_loss=27.62, generator_mel_loss=18.53, generator_kl_loss=1.377, generator_dur_loss=1.763, generator_adv_loss=1.91, generator_feat_match_loss=4.043, over 1593.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 01:42:36,527 INFO [train.py:527] (2/6) Epoch 252, batch 76, global_batch_idx: 31200, batch size: 47, loss[discriminator_loss=2.778, discriminator_real_loss=1.33, discriminator_fake_loss=1.448, generator_loss=27.67, generator_mel_loss=18.42, generator_kl_loss=1.477, generator_dur_loss=1.705, generator_adv_loss=1.969, generator_feat_match_loss=4.094, over 47.00 samples.], tot_loss[discriminator_loss=2.736, discriminator_real_loss=1.387, discriminator_fake_loss=1.35, generator_loss=27.4, generator_mel_loss=18.42, generator_kl_loss=1.378, generator_dur_loss=1.759, generator_adv_loss=1.912, generator_feat_match_loss=3.938, over 4539.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 01:42:36,528 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 01:42:44,417 INFO [train.py:591] (2/6) Epoch 252, validation: discriminator_loss=2.785, discriminator_real_loss=1.56, discriminator_fake_loss=1.224, generator_loss=26.5, generator_mel_loss=18.6, generator_kl_loss=1.167, generator_dur_loss=1.826, generator_adv_loss=1.996, generator_feat_match_loss=2.911, over 100.00 samples.
2024-03-13 01:42:44,418 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 01:44:54,007 INFO [train.py:919] (2/6) Start epoch 253
2024-03-13 01:45:20,456 INFO [train.py:527] (2/6) Epoch 253, batch 2, global_batch_idx: 31250, batch size: 47, loss[discriminator_loss=2.709, discriminator_real_loss=1.387, discriminator_fake_loss=1.322, generator_loss=28.08, generator_mel_loss=19.23, generator_kl_loss=1.44, generator_dur_loss=1.761, generator_adv_loss=1.934, generator_feat_match_loss=3.718, over 47.00 samples.], tot_loss[discriminator_loss=2.738, discriminator_real_loss=1.374, discriminator_fake_loss=1.364, generator_loss=27.19, generator_mel_loss=18.55, generator_kl_loss=1.272, generator_dur_loss=1.781, generator_adv_loss=1.854, generator_feat_match_loss=3.728, over 194.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 01:47:37,749 INFO [train.py:527] (2/6) Epoch 253, batch 52, global_batch_idx: 31300, batch size: 64, loss[discriminator_loss=2.715, discriminator_real_loss=1.465, discriminator_fake_loss=1.25, generator_loss=26.62, generator_mel_loss=17.93, generator_kl_loss=1.173, generator_dur_loss=1.814, generator_adv_loss=2.13, generator_feat_match_loss=3.566, over 64.00 samples.], tot_loss[discriminator_loss=2.737, discriminator_real_loss=1.388, discriminator_fake_loss=1.35, generator_loss=27.59, generator_mel_loss=18.46, generator_kl_loss=1.38, generator_dur_loss=1.755, generator_adv_loss=1.996, generator_feat_match_loss=3.992, over 3201.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 01:49:55,111 INFO [train.py:527] (2/6) Epoch 253, batch 102, global_batch_idx: 31350, batch size: 56, loss[discriminator_loss=2.809, discriminator_real_loss=1.482, discriminator_fake_loss=1.328, generator_loss=26.74, generator_mel_loss=18.04, generator_kl_loss=1.414, generator_dur_loss=1.729, generator_adv_loss=1.907, generator_feat_match_loss=3.655, over 56.00 samples.], tot_loss[discriminator_loss=2.73, discriminator_real_loss=1.388, discriminator_fake_loss=1.342, generator_loss=27.51, generator_mel_loss=18.46, generator_kl_loss=1.397, generator_dur_loss=1.751, generator_adv_loss=1.962, generator_feat_match_loss=3.935, over 5902.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 01:50:56,585 INFO [train.py:919] (2/6) Start epoch 254
2024-03-13 01:52:38,376 INFO [train.py:527] (2/6) Epoch 254, batch 28, global_batch_idx: 31400, batch size: 74, loss[discriminator_loss=2.737, discriminator_real_loss=1.261, discriminator_fake_loss=1.476, generator_loss=27.64, generator_mel_loss=18.48, generator_kl_loss=1.296, generator_dur_loss=1.816, generator_adv_loss=2.004, generator_feat_match_loss=4.039, over 74.00 samples.], tot_loss[discriminator_loss=2.735, discriminator_real_loss=1.372, discriminator_fake_loss=1.363, generator_loss=27.47, generator_mel_loss=18.48, generator_kl_loss=1.398, generator_dur_loss=1.764, generator_adv_loss=1.926, generator_feat_match_loss=3.898, over 1484.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 01:52:38,378 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 01:52:46,336 INFO [train.py:591] (2/6) Epoch 254, validation: discriminator_loss=2.75, discriminator_real_loss=1.459, discriminator_fake_loss=1.292, generator_loss=26.99, generator_mel_loss=18.55, generator_kl_loss=1.213, generator_dur_loss=1.832, generator_adv_loss=1.963, generator_feat_match_loss=3.434, over 100.00 samples.
2024-03-13 01:52:46,337 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 01:55:03,441 INFO [train.py:527] (2/6) Epoch 254, batch 78, global_batch_idx: 31450, batch size: 45, loss[discriminator_loss=2.734, discriminator_real_loss=1.354, discriminator_fake_loss=1.38, generator_loss=27.15, generator_mel_loss=18.38, generator_kl_loss=1.38, generator_dur_loss=1.681, generator_adv_loss=1.861, generator_feat_match_loss=3.85, over 45.00 samples.], tot_loss[discriminator_loss=2.734, discriminator_real_loss=1.383, discriminator_fake_loss=1.351, generator_loss=27.42, generator_mel_loss=18.46, generator_kl_loss=1.388, generator_dur_loss=1.761, generator_adv_loss=1.92, generator_feat_match_loss=3.894, over 4355.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 01:57:12,744 INFO [train.py:919] (2/6) Start epoch 255
2024-03-13 01:57:47,723 INFO [train.py:527] (2/6) Epoch 255, batch 4, global_batch_idx: 31500, batch size: 62, loss[discriminator_loss=2.621, discriminator_real_loss=1.314, discriminator_fake_loss=1.307, generator_loss=29.18, generator_mel_loss=19.12, generator_kl_loss=1.403, generator_dur_loss=1.727, generator_adv_loss=1.991, generator_feat_match_loss=4.935, over 62.00 samples.], tot_loss[discriminator_loss=2.687, discriminator_real_loss=1.372, discriminator_fake_loss=1.315, generator_loss=28.03, generator_mel_loss=18.72, generator_kl_loss=1.407, generator_dur_loss=1.732, generator_adv_loss=1.961, generator_feat_match_loss=4.209, over 289.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 02:00:05,953 INFO [train.py:527] (2/6) Epoch 255, batch 54, global_batch_idx: 31550, batch size: 59, loss[discriminator_loss=2.707, discriminator_real_loss=1.408, discriminator_fake_loss=1.299, generator_loss=27.42, generator_mel_loss=18.47, generator_kl_loss=1.412, generator_dur_loss=1.734, generator_adv_loss=1.784, generator_feat_match_loss=4.022, over 59.00 samples.], tot_loss[discriminator_loss=2.717, discriminator_real_loss=1.38, discriminator_fake_loss=1.337, generator_loss=27.57, generator_mel_loss=18.51, generator_kl_loss=1.389, generator_dur_loss=1.752, generator_adv_loss=1.923, generator_feat_match_loss=3.999, over 3203.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 02:02:24,274 INFO [train.py:527] (2/6) Epoch 255, batch 104, global_batch_idx: 31600, batch size: 39, loss[discriminator_loss=2.838, discriminator_real_loss=1.524, discriminator_fake_loss=1.314, generator_loss=27.07, generator_mel_loss=18.36, generator_kl_loss=1.51, generator_dur_loss=1.678, generator_adv_loss=1.898, generator_feat_match_loss=3.621, over 39.00 samples.], tot_loss[discriminator_loss=2.714, discriminator_real_loss=1.373, discriminator_fake_loss=1.341, generator_loss=27.65, generator_mel_loss=18.47, generator_kl_loss=1.398, generator_dur_loss=1.755, generator_adv_loss=1.963, generator_feat_match_loss=4.064, over 6085.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 02:02:24,275 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 02:02:33,144 INFO [train.py:591] (2/6) Epoch 255, validation: discriminator_loss=2.723, discriminator_real_loss=1.394, discriminator_fake_loss=1.329, generator_loss=26.85, generator_mel_loss=18.73, generator_kl_loss=1.242, generator_dur_loss=1.828, generator_adv_loss=1.886, generator_feat_match_loss=3.165, over 100.00 samples.
2024-03-13 02:02:33,145 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 02:03:26,552 INFO [train.py:919] (2/6) Start epoch 256
2024-03-13 02:05:13,813 INFO [train.py:527] (2/6) Epoch 256, batch 30, global_batch_idx: 31650, batch size: 74, loss[discriminator_loss=2.805, discriminator_real_loss=1.585, discriminator_fake_loss=1.221, generator_loss=26.73, generator_mel_loss=18.08, generator_kl_loss=1.237, generator_dur_loss=1.802, generator_adv_loss=1.78, generator_feat_match_loss=3.828, over 74.00 samples.], tot_loss[discriminator_loss=2.745, discriminator_real_loss=1.397, discriminator_fake_loss=1.347, generator_loss=27.38, generator_mel_loss=18.37, generator_kl_loss=1.355, generator_dur_loss=1.752, generator_adv_loss=1.923, generator_feat_match_loss=3.983, over 1661.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 02:07:33,009 INFO [train.py:527] (2/6) Epoch 256, batch 80, global_batch_idx: 31700, batch size: 62, loss[discriminator_loss=2.646, discriminator_real_loss=1.407, discriminator_fake_loss=1.239, generator_loss=27.73, generator_mel_loss=18.66, generator_kl_loss=1.391, generator_dur_loss=1.783, generator_adv_loss=1.9, generator_feat_match_loss=3.995, over 62.00 samples.], tot_loss[discriminator_loss=2.734, discriminator_real_loss=1.387, discriminator_fake_loss=1.347, generator_loss=27.4, generator_mel_loss=18.4, generator_kl_loss=1.386, generator_dur_loss=1.755, generator_adv_loss=1.909, generator_feat_match_loss=3.956, over 4401.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 02:09:31,310 INFO [train.py:919] (2/6) Start epoch 257
2024-03-13 02:10:12,052 INFO [train.py:527] (2/6) Epoch 257, batch 6, global_batch_idx: 31750, batch size: 80, loss[discriminator_loss=2.762, discriminator_real_loss=1.44, discriminator_fake_loss=1.322, generator_loss=27.23, generator_mel_loss=18.21, generator_kl_loss=1.323, generator_dur_loss=1.823, generator_adv_loss=1.872, generator_feat_match_loss=3.999, over 80.00 samples.], tot_loss[discriminator_loss=2.768, discriminator_real_loss=1.405, discriminator_fake_loss=1.363, generator_loss=27.79, generator_mel_loss=18.72, generator_kl_loss=1.421, generator_dur_loss=1.751, generator_adv_loss=1.901, generator_feat_match_loss=3.992, over 375.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 02:12:30,466 INFO [train.py:527] (2/6) Epoch 257, batch 56, global_batch_idx: 31800, batch size: 61, loss[discriminator_loss=2.647, discriminator_real_loss=1.353, discriminator_fake_loss=1.293, generator_loss=27.33, generator_mel_loss=17.9, generator_kl_loss=1.378, generator_dur_loss=1.723, generator_adv_loss=2.074, generator_feat_match_loss=4.255, over 61.00 samples.], tot_loss[discriminator_loss=2.746, discriminator_real_loss=1.391, discriminator_fake_loss=1.355, generator_loss=27.4, generator_mel_loss=18.43, generator_kl_loss=1.398, generator_dur_loss=1.752, generator_adv_loss=1.916, generator_feat_match_loss=3.903, over 3115.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 02:12:30,468 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 02:12:38,373 INFO [train.py:591] (2/6) Epoch 257, validation: discriminator_loss=2.759, discriminator_real_loss=1.537, discriminator_fake_loss=1.221, generator_loss=26.49, generator_mel_loss=18.51, generator_kl_loss=1.253, generator_dur_loss=1.822, generator_adv_loss=1.931, generator_feat_match_loss=2.969, over 100.00 samples.
2024-03-13 02:12:38,374 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 02:14:57,209 INFO [train.py:527] (2/6) Epoch 257, batch 106, global_batch_idx: 31850, batch size: 70, loss[discriminator_loss=2.741, discriminator_real_loss=1.319, discriminator_fake_loss=1.422, generator_loss=26.86, generator_mel_loss=18.21, generator_kl_loss=1.318, generator_dur_loss=1.782, generator_adv_loss=1.894, generator_feat_match_loss=3.661, over 70.00 samples.], tot_loss[discriminator_loss=2.737, discriminator_real_loss=1.388, discriminator_fake_loss=1.349, generator_loss=27.43, generator_mel_loss=18.44, generator_kl_loss=1.402, generator_dur_loss=1.748, generator_adv_loss=1.912, generator_feat_match_loss=3.922, over 5809.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 02:15:44,481 INFO [train.py:919] (2/6) Start epoch 258
2024-03-13 02:17:39,472 INFO [train.py:527] (2/6) Epoch 258, batch 32, global_batch_idx: 31900, batch size: 61, loss[discriminator_loss=2.659, discriminator_real_loss=1.37, discriminator_fake_loss=1.288, generator_loss=28.06, generator_mel_loss=18.58, generator_kl_loss=1.493, generator_dur_loss=1.774, generator_adv_loss=1.908, generator_feat_match_loss=4.301, over 61.00 samples.], tot_loss[discriminator_loss=2.736, discriminator_real_loss=1.387, discriminator_fake_loss=1.349, generator_loss=27.55, generator_mel_loss=18.51, generator_kl_loss=1.407, generator_dur_loss=1.75, generator_adv_loss=1.889, generator_feat_match_loss=3.988, over 1883.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 02:19:57,433 INFO [train.py:527] (2/6) Epoch 258, batch 82, global_batch_idx: 31950, batch size: 68, loss[discriminator_loss=2.75, discriminator_real_loss=1.393, discriminator_fake_loss=1.357, generator_loss=27.79, generator_mel_loss=18.43, generator_kl_loss=1.342, generator_dur_loss=1.839, generator_adv_loss=1.941, generator_feat_match_loss=4.23, over 68.00 samples.], tot_loss[discriminator_loss=2.731, discriminator_real_loss=1.381, discriminator_fake_loss=1.35, generator_loss=27.55, generator_mel_loss=18.47, generator_kl_loss=1.408, generator_dur_loss=1.762, generator_adv_loss=1.93, generator_feat_match_loss=3.986, over 4828.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 02:21:52,123 INFO [train.py:919] (2/6) Start epoch 259
2024-03-13 02:22:39,513 INFO [train.py:527] (2/6) Epoch 259, batch 8, global_batch_idx: 32000, batch size: 58, loss[discriminator_loss=2.774, discriminator_real_loss=1.442, discriminator_fake_loss=1.332, generator_loss=28.29, generator_mel_loss=18.66, generator_kl_loss=1.541, generator_dur_loss=1.726, generator_adv_loss=1.813, generator_feat_match_loss=4.554, over 58.00 samples.], tot_loss[discriminator_loss=2.718, discriminator_real_loss=1.381, discriminator_fake_loss=1.337, generator_loss=27.78, generator_mel_loss=18.46, generator_kl_loss=1.369, generator_dur_loss=1.779, generator_adv_loss=1.917, generator_feat_match_loss=4.256, over 472.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 02:22:39,516 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 02:22:47,456 INFO [train.py:591] (2/6) Epoch 259, validation: discriminator_loss=2.777, discriminator_real_loss=1.429, discriminator_fake_loss=1.348, generator_loss=26.66, generator_mel_loss=18.57, generator_kl_loss=1.241, generator_dur_loss=1.835, generator_adv_loss=1.784, generator_feat_match_loss=3.231, over 100.00 samples.
2024-03-13 02:22:47,459 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 02:25:08,184 INFO [train.py:527] (2/6) Epoch 259, batch 58, global_batch_idx: 32050, batch size: 50, loss[discriminator_loss=2.712, discriminator_real_loss=1.421, discriminator_fake_loss=1.292, generator_loss=26.99, generator_mel_loss=18.17, generator_kl_loss=1.526, generator_dur_loss=1.726, generator_adv_loss=1.857, generator_feat_match_loss=3.717, over 50.00 samples.], tot_loss[discriminator_loss=2.733, discriminator_real_loss=1.382, discriminator_fake_loss=1.351, generator_loss=27.5, generator_mel_loss=18.41, generator_kl_loss=1.39, generator_dur_loss=1.77, generator_adv_loss=1.921, generator_feat_match_loss=4.009, over 3273.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 02:27:26,618 INFO [train.py:527] (2/6) Epoch 259, batch 108, global_batch_idx: 32100, batch size: 74, loss[discriminator_loss=2.708, discriminator_real_loss=1.382, discriminator_fake_loss=1.326, generator_loss=27.64, generator_mel_loss=18.43, generator_kl_loss=1.367, generator_dur_loss=1.861, generator_adv_loss=1.926, generator_feat_match_loss=4.05, over 74.00 samples.], tot_loss[discriminator_loss=2.734, discriminator_real_loss=1.381, discriminator_fake_loss=1.354, generator_loss=27.48, generator_mel_loss=18.41, generator_kl_loss=1.382, generator_dur_loss=1.784, generator_adv_loss=1.917, generator_feat_match_loss=3.987, over 6235.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 02:28:09,799 INFO [train.py:919] (2/6) Start epoch 260
2024-03-13 02:30:09,162 INFO [train.py:527] (2/6) Epoch 260, batch 34, global_batch_idx: 32150, batch size: 88, loss[discriminator_loss=2.682, discriminator_real_loss=1.378, discriminator_fake_loss=1.304, generator_loss=26.55, generator_mel_loss=17.8, generator_kl_loss=1.38, generator_dur_loss=1.9, generator_adv_loss=1.873, generator_feat_match_loss=3.6, over 88.00 samples.], tot_loss[discriminator_loss=2.727, discriminator_real_loss=1.383, discriminator_fake_loss=1.345, generator_loss=27.45, generator_mel_loss=18.42, generator_kl_loss=1.384, generator_dur_loss=1.78, generator_adv_loss=1.918, generator_feat_match_loss=3.955, over 2057.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 02:32:29,176 INFO [train.py:527] (2/6) Epoch 260, batch 84, global_batch_idx: 32200, batch size: 58, loss[discriminator_loss=2.757, discriminator_real_loss=1.365, discriminator_fake_loss=1.392, generator_loss=27.4, generator_mel_loss=18.47, generator_kl_loss=1.282, generator_dur_loss=1.711, generator_adv_loss=2.09, generator_feat_match_loss=3.848, over 58.00 samples.], tot_loss[discriminator_loss=2.734, discriminator_real_loss=1.388, discriminator_fake_loss=1.347, generator_loss=27.52, generator_mel_loss=18.44, generator_kl_loss=1.401, generator_dur_loss=1.769, generator_adv_loss=1.925, generator_feat_match_loss=3.991, over 4830.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 02:32:29,178 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 02:32:37,975 INFO [train.py:591] (2/6) Epoch 260, validation: discriminator_loss=2.713, discriminator_real_loss=1.453, discriminator_fake_loss=1.26, generator_loss=27.27, generator_mel_loss=18.88, generator_kl_loss=1.229, generator_dur_loss=1.83, generator_adv_loss=2.043, generator_feat_match_loss=3.287, over 100.00 samples.
2024-03-13 02:32:37,976 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 02:34:26,937 INFO [train.py:919] (2/6) Start epoch 261
2024-03-13 02:35:21,374 INFO [train.py:527] (2/6) Epoch 261, batch 10, global_batch_idx: 32250, batch size: 14, loss[discriminator_loss=2.843, discriminator_real_loss=1.437, discriminator_fake_loss=1.406, generator_loss=30.08, generator_mel_loss=20.57, generator_kl_loss=1.71, generator_dur_loss=1.51, generator_adv_loss=2.022, generator_feat_match_loss=4.27, over 14.00 samples.], tot_loss[discriminator_loss=2.761, discriminator_real_loss=1.402, discriminator_fake_loss=1.359, generator_loss=27.43, generator_mel_loss=18.48, generator_kl_loss=1.354, generator_dur_loss=1.772, generator_adv_loss=1.889, generator_feat_match_loss=3.938, over 672.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 02:37:37,277 INFO [train.py:527] (2/6) Epoch 261, batch 60, global_batch_idx: 32300, batch size: 39, loss[discriminator_loss=2.747, discriminator_real_loss=1.445, discriminator_fake_loss=1.302, generator_loss=27.4, generator_mel_loss=18.66, generator_kl_loss=1.426, generator_dur_loss=1.701, generator_adv_loss=2.015, generator_feat_match_loss=3.596, over 39.00 samples.], tot_loss[discriminator_loss=2.749, discriminator_real_loss=1.389, discriminator_fake_loss=1.36, generator_loss=27.36, generator_mel_loss=18.39, generator_kl_loss=1.369, generator_dur_loss=1.762, generator_adv_loss=1.913, generator_feat_match_loss=3.925, over 3602.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 02:39:54,469 INFO [train.py:527] (2/6) Epoch 261, batch 110, global_batch_idx: 32350, batch size: 31, loss[discriminator_loss=2.794, discriminator_real_loss=1.36, discriminator_fake_loss=1.435, generator_loss=27.48, generator_mel_loss=18.54, generator_kl_loss=1.454, generator_dur_loss=1.644, generator_adv_loss=1.898, generator_feat_match_loss=3.945, over 31.00 samples.], tot_loss[discriminator_loss=2.745, discriminator_real_loss=1.386, discriminator_fake_loss=1.359, generator_loss=27.46, generator_mel_loss=18.47, generator_kl_loss=1.384, generator_dur_loss=1.754, generator_adv_loss=1.91, generator_feat_match_loss=3.949, over 6241.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 02:40:31,287 INFO [train.py:919] (2/6) Start epoch 262
2024-03-13 02:42:32,853 INFO [train.py:527] (2/6) Epoch 262, batch 36, global_batch_idx: 32400, batch size: 55, loss[discriminator_loss=2.636, discriminator_real_loss=1.392, discriminator_fake_loss=1.243, generator_loss=27.82, generator_mel_loss=18.53, generator_kl_loss=1.348, generator_dur_loss=1.721, generator_adv_loss=1.984, generator_feat_match_loss=4.243, over 55.00 samples.], tot_loss[discriminator_loss=2.74, discriminator_real_loss=1.394, discriminator_fake_loss=1.346, generator_loss=27.59, generator_mel_loss=18.45, generator_kl_loss=1.421, generator_dur_loss=1.749, generator_adv_loss=1.922, generator_feat_match_loss=4.043, over 1967.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 02:42:32,855 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 02:42:41,014 INFO [train.py:591] (2/6) Epoch 262, validation: discriminator_loss=2.761, discriminator_real_loss=1.36, discriminator_fake_loss=1.401, generator_loss=26.68, generator_mel_loss=18.58, generator_kl_loss=1.141, generator_dur_loss=1.828, generator_adv_loss=1.766, generator_feat_match_loss=3.362, over 100.00 samples.
2024-03-13 02:42:41,014 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 02:45:03,109 INFO [train.py:527] (2/6) Epoch 262, batch 86, global_batch_idx: 32450, batch size: 44, loss[discriminator_loss=2.687, discriminator_real_loss=1.329, discriminator_fake_loss=1.357, generator_loss=28.44, generator_mel_loss=18.8, generator_kl_loss=1.545, generator_dur_loss=1.656, generator_adv_loss=2.071, generator_feat_match_loss=4.369, over 44.00 samples.], tot_loss[discriminator_loss=2.727, discriminator_real_loss=1.383, discriminator_fake_loss=1.345, generator_loss=27.56, generator_mel_loss=18.4, generator_kl_loss=1.41, generator_dur_loss=1.757, generator_adv_loss=1.942, generator_feat_match_loss=4.054, over 4953.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 02:46:48,128 INFO [train.py:919] (2/6) Start epoch 263
2024-03-13 02:47:44,477 INFO [train.py:527] (2/6) Epoch 263, batch 12, global_batch_idx: 32500, batch size: 70, loss[discriminator_loss=2.778, discriminator_real_loss=1.411, discriminator_fake_loss=1.367, generator_loss=27.65, generator_mel_loss=18.61, generator_kl_loss=1.313, generator_dur_loss=1.816, generator_adv_loss=1.822, generator_feat_match_loss=4.096, over 70.00 samples.], tot_loss[discriminator_loss=2.708, discriminator_real_loss=1.365, discriminator_fake_loss=1.343, generator_loss=27.81, generator_mel_loss=18.62, generator_kl_loss=1.396, generator_dur_loss=1.729, generator_adv_loss=1.921, generator_feat_match_loss=4.147, over 625.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 02:50:03,533 INFO [train.py:527] (2/6) Epoch 263, batch 62, global_batch_idx: 32550, batch size: 44, loss[discriminator_loss=2.724, discriminator_real_loss=1.455, discriminator_fake_loss=1.269, generator_loss=27.85, generator_mel_loss=18.81, generator_kl_loss=1.551, generator_dur_loss=1.686, generator_adv_loss=1.736, generator_feat_match_loss=4.071, over 44.00 samples.], tot_loss[discriminator_loss=2.735, discriminator_real_loss=1.384, discriminator_fake_loss=1.351, generator_loss=27.51, generator_mel_loss=18.46, generator_kl_loss=1.394, generator_dur_loss=1.752, generator_adv_loss=1.93, generator_feat_match_loss=3.971, over 3462.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 02:52:22,925 INFO [train.py:527] (2/6) Epoch 263, batch 112, global_batch_idx: 32600, batch size: 47, loss[discriminator_loss=2.822, discriminator_real_loss=1.513, discriminator_fake_loss=1.31, generator_loss=27.12, generator_mel_loss=18.43, generator_kl_loss=1.481, generator_dur_loss=1.703, generator_adv_loss=1.837, generator_feat_match_loss=3.668, over 47.00 samples.], tot_loss[discriminator_loss=2.737, discriminator_real_loss=1.387, discriminator_fake_loss=1.35, generator_loss=27.45, generator_mel_loss=18.44, generator_kl_loss=1.393, generator_dur_loss=1.75, generator_adv_loss=1.925, generator_feat_match_loss=3.943, over 6067.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 02:52:22,927 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 02:52:31,660 INFO [train.py:591] (2/6) Epoch 263, validation: discriminator_loss=2.759, discriminator_real_loss=1.445, discriminator_fake_loss=1.314, generator_loss=26.63, generator_mel_loss=18.66, generator_kl_loss=1.182, generator_dur_loss=1.837, generator_adv_loss=1.862, generator_feat_match_loss=3.083, over 100.00 samples.
2024-03-13 02:52:31,661 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 02:53:04,173 INFO [train.py:919] (2/6) Start epoch 264
2024-03-13 02:55:15,639 INFO [train.py:527] (2/6) Epoch 264, batch 38, global_batch_idx: 32650, batch size: 59, loss[discriminator_loss=2.769, discriminator_real_loss=1.436, discriminator_fake_loss=1.333, generator_loss=26.56, generator_mel_loss=18.1, generator_kl_loss=1.359, generator_dur_loss=1.736, generator_adv_loss=2.005, generator_feat_match_loss=3.367, over 59.00 samples.], tot_loss[discriminator_loss=2.747, discriminator_real_loss=1.391, discriminator_fake_loss=1.356, generator_loss=27.29, generator_mel_loss=18.3, generator_kl_loss=1.363, generator_dur_loss=1.809, generator_adv_loss=1.932, generator_feat_match_loss=3.88, over 2513.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 02:57:36,721 INFO [train.py:527] (2/6) Epoch 264, batch 88, global_batch_idx: 32700, batch size: 45, loss[discriminator_loss=2.734, discriminator_real_loss=1.409, discriminator_fake_loss=1.324, generator_loss=27.55, generator_mel_loss=18.62, generator_kl_loss=1.615, generator_dur_loss=1.623, generator_adv_loss=1.785, generator_feat_match_loss=3.912, over 45.00 samples.], tot_loss[discriminator_loss=2.741, discriminator_real_loss=1.387, discriminator_fake_loss=1.354, generator_loss=27.39, generator_mel_loss=18.36, generator_kl_loss=1.381, generator_dur_loss=1.783, generator_adv_loss=1.93, generator_feat_match_loss=3.93, over 5314.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 02:59:13,625 INFO [train.py:919] (2/6) Start epoch 265
2024-03-13 03:00:17,374 INFO [train.py:527] (2/6) Epoch 265, batch 14, global_batch_idx: 32750, batch size: 74, loss[discriminator_loss=2.712, discriminator_real_loss=1.372, discriminator_fake_loss=1.34, generator_loss=27.49, generator_mel_loss=18.53, generator_kl_loss=1.237, generator_dur_loss=1.821, generator_adv_loss=1.876, generator_feat_match_loss=4.019, over 74.00 samples.], tot_loss[discriminator_loss=2.738, discriminator_real_loss=1.385, discriminator_fake_loss=1.353, generator_loss=27.52, generator_mel_loss=18.52, generator_kl_loss=1.382, generator_dur_loss=1.738, generator_adv_loss=1.887, generator_feat_match_loss=3.994, over 859.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 03:02:39,919 INFO [train.py:527] (2/6) Epoch 265, batch 64, global_batch_idx: 32800, batch size: 83, loss[discriminator_loss=2.733, discriminator_real_loss=1.351, discriminator_fake_loss=1.382, generator_loss=27.2, generator_mel_loss=18.5, generator_kl_loss=1.374, generator_dur_loss=1.858, generator_adv_loss=1.886, generator_feat_match_loss=3.582, over 83.00 samples.], tot_loss[discriminator_loss=2.734, discriminator_real_loss=1.381, discriminator_fake_loss=1.353, generator_loss=27.41, generator_mel_loss=18.39, generator_kl_loss=1.375, generator_dur_loss=1.761, generator_adv_loss=1.917, generator_feat_match_loss=3.968, over 3984.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 03:02:39,921 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 03:02:48,051 INFO [train.py:591] (2/6) Epoch 265, validation: discriminator_loss=2.754, discriminator_real_loss=1.464, discriminator_fake_loss=1.291, generator_loss=26.78, generator_mel_loss=18.76, generator_kl_loss=1.124, generator_dur_loss=1.824, generator_adv_loss=1.835, generator_feat_match_loss=3.235, over 100.00 samples.
2024-03-13 03:02:48,052 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 03:05:03,303 INFO [train.py:527] (2/6) Epoch 265, batch 114, global_batch_idx: 32850, batch size: 55, loss[discriminator_loss=2.647, discriminator_real_loss=1.386, discriminator_fake_loss=1.261, generator_loss=27.49, generator_mel_loss=18.3, generator_kl_loss=1.482, generator_dur_loss=1.7, generator_adv_loss=1.941, generator_feat_match_loss=4.067, over 55.00 samples.], tot_loss[discriminator_loss=2.732, discriminator_real_loss=1.383, discriminator_fake_loss=1.349, generator_loss=27.36, generator_mel_loss=18.36, generator_kl_loss=1.384, generator_dur_loss=1.757, generator_adv_loss=1.917, generator_feat_match_loss=3.945, over 6695.00 samples.], cur_lr_g: 1.94e-04, cur_lr_d: 1.94e-04, 
2024-03-13 03:05:29,500 INFO [train.py:919] (2/6) Start epoch 266
2024-03-13 03:07:43,990 INFO [train.py:527] (2/6) Epoch 266, batch 40, global_batch_idx: 32900, batch size: 61, loss[discriminator_loss=2.741, discriminator_real_loss=1.452, discriminator_fake_loss=1.289, generator_loss=27.28, generator_mel_loss=18.39, generator_kl_loss=1.463, generator_dur_loss=1.722, generator_adv_loss=1.891, generator_feat_match_loss=3.816, over 61.00 samples.], tot_loss[discriminator_loss=2.724, discriminator_real_loss=1.384, discriminator_fake_loss=1.34, generator_loss=27.45, generator_mel_loss=18.4, generator_kl_loss=1.385, generator_dur_loss=1.748, generator_adv_loss=1.926, generator_feat_match_loss=3.998, over 2260.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 03:10:05,541 INFO [train.py:527] (2/6) Epoch 266, batch 90, global_batch_idx: 32950, batch size: 58, loss[discriminator_loss=2.683, discriminator_real_loss=1.395, discriminator_fake_loss=1.288, generator_loss=28.18, generator_mel_loss=18.58, generator_kl_loss=1.443, generator_dur_loss=1.75, generator_adv_loss=2.081, generator_feat_match_loss=4.326, over 58.00 samples.], tot_loss[discriminator_loss=2.731, discriminator_real_loss=1.379, discriminator_fake_loss=1.352, generator_loss=27.45, generator_mel_loss=18.34, generator_kl_loss=1.391, generator_dur_loss=1.759, generator_adv_loss=1.933, generator_feat_match_loss=4.022, over 5108.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 03:11:36,044 INFO [train.py:919] (2/6) Start epoch 267
2024-03-13 03:12:46,561 INFO [train.py:527] (2/6) Epoch 267, batch 16, global_batch_idx: 33000, batch size: 74, loss[discriminator_loss=2.716, discriminator_real_loss=1.36, discriminator_fake_loss=1.356, generator_loss=27.09, generator_mel_loss=18.22, generator_kl_loss=1.304, generator_dur_loss=1.784, generator_adv_loss=1.915, generator_feat_match_loss=3.859, over 74.00 samples.], tot_loss[discriminator_loss=2.731, discriminator_real_loss=1.383, discriminator_fake_loss=1.348, generator_loss=27.39, generator_mel_loss=18.35, generator_kl_loss=1.376, generator_dur_loss=1.782, generator_adv_loss=1.927, generator_feat_match_loss=3.956, over 1024.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 03:12:46,563 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 03:12:54,395 INFO [train.py:591] (2/6) Epoch 267, validation: discriminator_loss=2.75, discriminator_real_loss=1.458, discriminator_fake_loss=1.292, generator_loss=26.14, generator_mel_loss=18.44, generator_kl_loss=1.151, generator_dur_loss=1.833, generator_adv_loss=1.903, generator_feat_match_loss=2.817, over 100.00 samples.
2024-03-13 03:12:54,396 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 03:15:11,676 INFO [train.py:527] (2/6) Epoch 267, batch 66, global_batch_idx: 33050, batch size: 68, loss[discriminator_loss=2.764, discriminator_real_loss=1.355, discriminator_fake_loss=1.409, generator_loss=27.1, generator_mel_loss=18.28, generator_kl_loss=1.268, generator_dur_loss=1.78, generator_adv_loss=1.902, generator_feat_match_loss=3.866, over 68.00 samples.], tot_loss[discriminator_loss=2.723, discriminator_real_loss=1.376, discriminator_fake_loss=1.347, generator_loss=27.44, generator_mel_loss=18.34, generator_kl_loss=1.365, generator_dur_loss=1.775, generator_adv_loss=1.928, generator_feat_match_loss=4.033, over 3986.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 03:17:28,123 INFO [train.py:527] (2/6) Epoch 267, batch 116, global_batch_idx: 33100, batch size: 88, loss[discriminator_loss=2.703, discriminator_real_loss=1.364, discriminator_fake_loss=1.339, generator_loss=27.53, generator_mel_loss=18.38, generator_kl_loss=1.289, generator_dur_loss=1.875, generator_adv_loss=1.886, generator_feat_match_loss=4.1, over 88.00 samples.], tot_loss[discriminator_loss=2.725, discriminator_real_loss=1.376, discriminator_fake_loss=1.349, generator_loss=27.47, generator_mel_loss=18.36, generator_kl_loss=1.379, generator_dur_loss=1.767, generator_adv_loss=1.924, generator_feat_match_loss=4.045, over 6940.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 03:17:51,064 INFO [train.py:919] (2/6) Start epoch 268
2024-03-13 03:20:12,542 INFO [train.py:527] (2/6) Epoch 268, batch 42, global_batch_idx: 33150, batch size: 77, loss[discriminator_loss=2.715, discriminator_real_loss=1.262, discriminator_fake_loss=1.453, generator_loss=27.65, generator_mel_loss=18.57, generator_kl_loss=1.285, generator_dur_loss=1.871, generator_adv_loss=2.047, generator_feat_match_loss=3.873, over 77.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.379, discriminator_fake_loss=1.336, generator_loss=27.62, generator_mel_loss=18.43, generator_kl_loss=1.401, generator_dur_loss=1.753, generator_adv_loss=1.975, generator_feat_match_loss=4.071, over 2219.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 03:22:32,498 INFO [train.py:527] (2/6) Epoch 268, batch 92, global_batch_idx: 33200, batch size: 64, loss[discriminator_loss=2.686, discriminator_real_loss=1.428, discriminator_fake_loss=1.258, generator_loss=27.32, generator_mel_loss=18.03, generator_kl_loss=1.371, generator_dur_loss=1.78, generator_adv_loss=1.946, generator_feat_match_loss=4.199, over 64.00 samples.], tot_loss[discriminator_loss=2.717, discriminator_real_loss=1.382, discriminator_fake_loss=1.336, generator_loss=27.61, generator_mel_loss=18.44, generator_kl_loss=1.405, generator_dur_loss=1.753, generator_adv_loss=1.949, generator_feat_match_loss=4.062, over 4890.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 03:22:32,500 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 03:22:40,302 INFO [train.py:591] (2/6) Epoch 268, validation: discriminator_loss=2.728, discriminator_real_loss=1.388, discriminator_fake_loss=1.34, generator_loss=26.18, generator_mel_loss=18.21, generator_kl_loss=1.207, generator_dur_loss=1.82, generator_adv_loss=1.833, generator_feat_match_loss=3.11, over 100.00 samples.
2024-03-13 03:22:40,303 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 03:24:07,800 INFO [train.py:919] (2/6) Start epoch 269
2024-03-13 03:25:22,505 INFO [train.py:527] (2/6) Epoch 269, batch 18, global_batch_idx: 33250, batch size: 25, loss[discriminator_loss=2.676, discriminator_real_loss=1.309, discriminator_fake_loss=1.366, generator_loss=28.8, generator_mel_loss=19.41, generator_kl_loss=1.48, generator_dur_loss=1.529, generator_adv_loss=1.949, generator_feat_match_loss=4.439, over 25.00 samples.], tot_loss[discriminator_loss=2.736, discriminator_real_loss=1.369, discriminator_fake_loss=1.368, generator_loss=27.56, generator_mel_loss=18.42, generator_kl_loss=1.409, generator_dur_loss=1.758, generator_adv_loss=1.899, generator_feat_match_loss=4.079, over 1063.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 03:27:42,956 INFO [train.py:527] (2/6) Epoch 269, batch 68, global_batch_idx: 33300, batch size: 44, loss[discriminator_loss=2.733, discriminator_real_loss=1.391, discriminator_fake_loss=1.342, generator_loss=28.09, generator_mel_loss=18.64, generator_kl_loss=1.611, generator_dur_loss=1.655, generator_adv_loss=1.945, generator_feat_match_loss=4.242, over 44.00 samples.], tot_loss[discriminator_loss=2.741, discriminator_real_loss=1.387, discriminator_fake_loss=1.354, generator_loss=27.47, generator_mel_loss=18.38, generator_kl_loss=1.391, generator_dur_loss=1.762, generator_adv_loss=1.924, generator_feat_match_loss=4.013, over 3846.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 03:30:02,487 INFO [train.py:527] (2/6) Epoch 269, batch 118, global_batch_idx: 33350, batch size: 15, loss[discriminator_loss=2.669, discriminator_real_loss=1.391, discriminator_fake_loss=1.278, generator_loss=28.38, generator_mel_loss=19.28, generator_kl_loss=1.69, generator_dur_loss=1.638, generator_adv_loss=1.906, generator_feat_match_loss=3.86, over 15.00 samples.], tot_loss[discriminator_loss=2.74, discriminator_real_loss=1.389, discriminator_fake_loss=1.351, generator_loss=27.49, generator_mel_loss=18.4, generator_kl_loss=1.387, generator_dur_loss=1.765, generator_adv_loss=1.928, generator_feat_match_loss=4.01, over 6733.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 03:30:19,081 INFO [train.py:919] (2/6) Start epoch 270
2024-03-13 03:32:45,212 INFO [train.py:527] (2/6) Epoch 270, batch 44, global_batch_idx: 33400, batch size: 64, loss[discriminator_loss=2.656, discriminator_real_loss=1.373, discriminator_fake_loss=1.283, generator_loss=27.12, generator_mel_loss=18.03, generator_kl_loss=1.424, generator_dur_loss=1.711, generator_adv_loss=2.022, generator_feat_match_loss=3.933, over 64.00 samples.], tot_loss[discriminator_loss=2.732, discriminator_real_loss=1.386, discriminator_fake_loss=1.346, generator_loss=27.57, generator_mel_loss=18.48, generator_kl_loss=1.425, generator_dur_loss=1.714, generator_adv_loss=1.928, generator_feat_match_loss=4.021, over 2382.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 03:32:45,213 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 03:32:53,133 INFO [train.py:591] (2/6) Epoch 270, validation: discriminator_loss=2.652, discriminator_real_loss=1.411, discriminator_fake_loss=1.241, generator_loss=26.71, generator_mel_loss=18.7, generator_kl_loss=1.252, generator_dur_loss=1.777, generator_adv_loss=1.922, generator_feat_match_loss=3.056, over 100.00 samples.
2024-03-13 03:32:53,135 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 03:35:15,418 INFO [train.py:527] (2/6) Epoch 270, batch 94, global_batch_idx: 33450, batch size: 31, loss[discriminator_loss=2.683, discriminator_real_loss=1.421, discriminator_fake_loss=1.262, generator_loss=27.88, generator_mel_loss=18.47, generator_kl_loss=1.587, generator_dur_loss=1.65, generator_adv_loss=2.053, generator_feat_match_loss=4.125, over 31.00 samples.], tot_loss[discriminator_loss=2.727, discriminator_real_loss=1.382, discriminator_fake_loss=1.345, generator_loss=27.53, generator_mel_loss=18.4, generator_kl_loss=1.384, generator_dur_loss=1.738, generator_adv_loss=1.946, generator_feat_match_loss=4.061, over 5481.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 03:36:34,419 INFO [train.py:919] (2/6) Start epoch 271
2024-03-13 03:37:54,947 INFO [train.py:527] (2/6) Epoch 271, batch 20, global_batch_idx: 33500, batch size: 48, loss[discriminator_loss=2.716, discriminator_real_loss=1.442, discriminator_fake_loss=1.274, generator_loss=27.01, generator_mel_loss=18.53, generator_kl_loss=1.365, generator_dur_loss=1.701, generator_adv_loss=1.906, generator_feat_match_loss=3.512, over 48.00 samples.], tot_loss[discriminator_loss=2.735, discriminator_real_loss=1.397, discriminator_fake_loss=1.338, generator_loss=27.35, generator_mel_loss=18.35, generator_kl_loss=1.372, generator_dur_loss=1.735, generator_adv_loss=1.942, generator_feat_match_loss=3.947, over 1221.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 03:40:09,474 INFO [train.py:527] (2/6) Epoch 271, batch 70, global_batch_idx: 33550, batch size: 74, loss[discriminator_loss=2.666, discriminator_real_loss=1.259, discriminator_fake_loss=1.407, generator_loss=28.17, generator_mel_loss=18.62, generator_kl_loss=1.379, generator_dur_loss=1.728, generator_adv_loss=2.067, generator_feat_match_loss=4.374, over 74.00 samples.], tot_loss[discriminator_loss=2.737, discriminator_real_loss=1.395, discriminator_fake_loss=1.342, generator_loss=27.37, generator_mel_loss=18.38, generator_kl_loss=1.375, generator_dur_loss=1.75, generator_adv_loss=1.917, generator_feat_match_loss=3.95, over 4037.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 03:42:31,184 INFO [train.py:527] (2/6) Epoch 271, batch 120, global_batch_idx: 33600, batch size: 96, loss[discriminator_loss=2.788, discriminator_real_loss=1.315, discriminator_fake_loss=1.474, generator_loss=27.98, generator_mel_loss=18.37, generator_kl_loss=1.33, generator_dur_loss=1.865, generator_adv_loss=2.079, generator_feat_match_loss=4.334, over 96.00 samples.], tot_loss[discriminator_loss=2.739, discriminator_real_loss=1.393, discriminator_fake_loss=1.345, generator_loss=27.39, generator_mel_loss=18.36, generator_kl_loss=1.376, generator_dur_loss=1.752, generator_adv_loss=1.916, generator_feat_match_loss=3.989, over 7049.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 03:42:31,185 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 03:42:40,082 INFO [train.py:591] (2/6) Epoch 271, validation: discriminator_loss=2.862, discriminator_real_loss=1.643, discriminator_fake_loss=1.219, generator_loss=26.49, generator_mel_loss=18.31, generator_kl_loss=1.227, generator_dur_loss=1.8, generator_adv_loss=2.089, generator_feat_match_loss=3.065, over 100.00 samples.
2024-03-13 03:42:40,084 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 03:42:49,669 INFO [train.py:919] (2/6) Start epoch 272
2024-03-13 03:45:20,035 INFO [train.py:527] (2/6) Epoch 272, batch 46, global_batch_idx: 33650, batch size: 48, loss[discriminator_loss=2.729, discriminator_real_loss=1.46, discriminator_fake_loss=1.269, generator_loss=26.87, generator_mel_loss=18.06, generator_kl_loss=1.578, generator_dur_loss=1.713, generator_adv_loss=1.794, generator_feat_match_loss=3.73, over 48.00 samples.], tot_loss[discriminator_loss=2.731, discriminator_real_loss=1.387, discriminator_fake_loss=1.344, generator_loss=27.5, generator_mel_loss=18.36, generator_kl_loss=1.398, generator_dur_loss=1.776, generator_adv_loss=1.914, generator_feat_match_loss=4.054, over 2767.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 03:47:40,106 INFO [train.py:527] (2/6) Epoch 272, batch 96, global_batch_idx: 33700, batch size: 59, loss[discriminator_loss=2.758, discriminator_real_loss=1.372, discriminator_fake_loss=1.386, generator_loss=27.3, generator_mel_loss=18.57, generator_kl_loss=1.57, generator_dur_loss=1.732, generator_adv_loss=1.99, generator_feat_match_loss=3.44, over 59.00 samples.], tot_loss[discriminator_loss=2.731, discriminator_real_loss=1.387, discriminator_fake_loss=1.344, generator_loss=27.46, generator_mel_loss=18.34, generator_kl_loss=1.401, generator_dur_loss=1.784, generator_adv_loss=1.92, generator_feat_match_loss=4.013, over 5725.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 03:48:57,173 INFO [train.py:919] (2/6) Start epoch 273
2024-03-13 03:50:21,943 INFO [train.py:527] (2/6) Epoch 273, batch 22, global_batch_idx: 33750, batch size: 42, loss[discriminator_loss=2.73, discriminator_real_loss=1.361, discriminator_fake_loss=1.368, generator_loss=28.44, generator_mel_loss=19.2, generator_kl_loss=1.623, generator_dur_loss=1.699, generator_adv_loss=1.798, generator_feat_match_loss=4.115, over 42.00 samples.], tot_loss[discriminator_loss=2.729, discriminator_real_loss=1.378, discriminator_fake_loss=1.351, generator_loss=27.75, generator_mel_loss=18.48, generator_kl_loss=1.418, generator_dur_loss=1.776, generator_adv_loss=1.929, generator_feat_match_loss=4.147, over 1196.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 03:52:43,518 INFO [train.py:527] (2/6) Epoch 273, batch 72, global_batch_idx: 33800, batch size: 70, loss[discriminator_loss=2.81, discriminator_real_loss=1.43, discriminator_fake_loss=1.38, generator_loss=26.9, generator_mel_loss=18.04, generator_kl_loss=1.382, generator_dur_loss=1.834, generator_adv_loss=1.732, generator_feat_match_loss=3.905, over 70.00 samples.], tot_loss[discriminator_loss=2.729, discriminator_real_loss=1.376, discriminator_fake_loss=1.352, generator_loss=27.57, generator_mel_loss=18.39, generator_kl_loss=1.371, generator_dur_loss=1.804, generator_adv_loss=1.924, generator_feat_match_loss=4.078, over 4313.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 03:52:43,520 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 03:52:51,232 INFO [train.py:591] (2/6) Epoch 273, validation: discriminator_loss=2.808, discriminator_real_loss=1.398, discriminator_fake_loss=1.41, generator_loss=26.31, generator_mel_loss=18.41, generator_kl_loss=1.102, generator_dur_loss=1.851, generator_adv_loss=1.741, generator_feat_match_loss=3.2, over 100.00 samples.
2024-03-13 03:52:51,233 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 03:55:07,339 INFO [train.py:527] (2/6) Epoch 273, batch 122, global_batch_idx: 33850, batch size: 45, loss[discriminator_loss=2.729, discriminator_real_loss=1.398, discriminator_fake_loss=1.33, generator_loss=27.45, generator_mel_loss=18.56, generator_kl_loss=1.482, generator_dur_loss=1.748, generator_adv_loss=1.899, generator_feat_match_loss=3.766, over 45.00 samples.], tot_loss[discriminator_loss=2.727, discriminator_real_loss=1.378, discriminator_fake_loss=1.349, generator_loss=27.56, generator_mel_loss=18.41, generator_kl_loss=1.382, generator_dur_loss=1.793, generator_adv_loss=1.922, generator_feat_match_loss=4.054, over 7101.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 03:55:12,377 INFO [train.py:919] (2/6) Start epoch 274
2024-03-13 03:57:46,981 INFO [train.py:527] (2/6) Epoch 274, batch 48, global_batch_idx: 33900, batch size: 25, loss[discriminator_loss=2.667, discriminator_real_loss=1.349, discriminator_fake_loss=1.318, generator_loss=29.01, generator_mel_loss=19.33, generator_kl_loss=1.684, generator_dur_loss=1.608, generator_adv_loss=2.062, generator_feat_match_loss=4.326, over 25.00 samples.], tot_loss[discriminator_loss=2.727, discriminator_real_loss=1.381, discriminator_fake_loss=1.345, generator_loss=27.56, generator_mel_loss=18.36, generator_kl_loss=1.41, generator_dur_loss=1.777, generator_adv_loss=1.931, generator_feat_match_loss=4.088, over 2778.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 04:00:05,847 INFO [train.py:527] (2/6) Epoch 274, batch 98, global_batch_idx: 33950, batch size: 77, loss[discriminator_loss=2.744, discriminator_real_loss=1.386, discriminator_fake_loss=1.358, generator_loss=27.71, generator_mel_loss=18.36, generator_kl_loss=1.42, generator_dur_loss=1.855, generator_adv_loss=1.901, generator_feat_match_loss=4.176, over 77.00 samples.], tot_loss[discriminator_loss=2.728, discriminator_real_loss=1.381, discriminator_fake_loss=1.347, generator_loss=27.56, generator_mel_loss=18.36, generator_kl_loss=1.389, generator_dur_loss=1.786, generator_adv_loss=1.93, generator_feat_match_loss=4.091, over 5789.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 04:01:18,502 INFO [train.py:919] (2/6) Start epoch 275
2024-03-13 04:02:49,756 INFO [train.py:527] (2/6) Epoch 275, batch 24, global_batch_idx: 34000, batch size: 50, loss[discriminator_loss=2.787, discriminator_real_loss=1.339, discriminator_fake_loss=1.448, generator_loss=27.47, generator_mel_loss=18.47, generator_kl_loss=1.462, generator_dur_loss=1.663, generator_adv_loss=1.952, generator_feat_match_loss=3.914, over 50.00 samples.], tot_loss[discriminator_loss=2.717, discriminator_real_loss=1.364, discriminator_fake_loss=1.353, generator_loss=27.52, generator_mel_loss=18.4, generator_kl_loss=1.423, generator_dur_loss=1.778, generator_adv_loss=1.903, generator_feat_match_loss=4.01, over 1434.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 04:02:49,758 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 04:02:57,799 INFO [train.py:591] (2/6) Epoch 275, validation: discriminator_loss=2.829, discriminator_real_loss=1.515, discriminator_fake_loss=1.314, generator_loss=26.55, generator_mel_loss=18.36, generator_kl_loss=1.205, generator_dur_loss=1.815, generator_adv_loss=1.905, generator_feat_match_loss=3.262, over 100.00 samples.
2024-03-13 04:02:57,816 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 04:05:15,994 INFO [train.py:527] (2/6) Epoch 275, batch 74, global_batch_idx: 34050, batch size: 83, loss[discriminator_loss=2.673, discriminator_real_loss=1.413, discriminator_fake_loss=1.26, generator_loss=27.93, generator_mel_loss=18.7, generator_kl_loss=1.245, generator_dur_loss=1.89, generator_adv_loss=1.863, generator_feat_match_loss=4.24, over 83.00 samples.], tot_loss[discriminator_loss=2.747, discriminator_real_loss=1.382, discriminator_fake_loss=1.365, generator_loss=27.64, generator_mel_loss=18.41, generator_kl_loss=1.414, generator_dur_loss=1.766, generator_adv_loss=1.964, generator_feat_match_loss=4.085, over 4191.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 04:07:32,235 INFO [train.py:919] (2/6) Start epoch 276
2024-03-13 04:07:54,845 INFO [train.py:527] (2/6) Epoch 276, batch 0, global_batch_idx: 34100, batch size: 44, loss[discriminator_loss=2.684, discriminator_real_loss=1.382, discriminator_fake_loss=1.302, generator_loss=27.71, generator_mel_loss=18.73, generator_kl_loss=1.526, generator_dur_loss=1.745, generator_adv_loss=1.708, generator_feat_match_loss=4.002, over 44.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.382, discriminator_fake_loss=1.302, generator_loss=27.71, generator_mel_loss=18.73, generator_kl_loss=1.526, generator_dur_loss=1.745, generator_adv_loss=1.708, generator_feat_match_loss=4.002, over 44.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 04:10:12,704 INFO [train.py:527] (2/6) Epoch 276, batch 50, global_batch_idx: 34150, batch size: 74, loss[discriminator_loss=2.706, discriminator_real_loss=1.359, discriminator_fake_loss=1.348, generator_loss=27.93, generator_mel_loss=18.66, generator_kl_loss=1.272, generator_dur_loss=1.809, generator_adv_loss=1.724, generator_feat_match_loss=4.466, over 74.00 samples.], tot_loss[discriminator_loss=2.738, discriminator_real_loss=1.393, discriminator_fake_loss=1.344, generator_loss=27.49, generator_mel_loss=18.48, generator_kl_loss=1.375, generator_dur_loss=1.773, generator_adv_loss=1.9, generator_feat_match_loss=3.963, over 2905.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 04:12:31,986 INFO [train.py:527] (2/6) Epoch 276, batch 100, global_batch_idx: 34200, batch size: 72, loss[discriminator_loss=2.669, discriminator_real_loss=1.406, discriminator_fake_loss=1.263, generator_loss=27.02, generator_mel_loss=17.99, generator_kl_loss=1.358, generator_dur_loss=1.839, generator_adv_loss=1.975, generator_feat_match_loss=3.861, over 72.00 samples.], tot_loss[discriminator_loss=2.734, discriminator_real_loss=1.387, discriminator_fake_loss=1.347, generator_loss=27.48, generator_mel_loss=18.42, generator_kl_loss=1.383, generator_dur_loss=1.775, generator_adv_loss=1.912, generator_feat_match_loss=3.988, over 5806.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 04:12:31,987 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 04:12:41,116 INFO [train.py:591] (2/6) Epoch 276, validation: discriminator_loss=2.776, discriminator_real_loss=1.46, discriminator_fake_loss=1.316, generator_loss=26.89, generator_mel_loss=18.73, generator_kl_loss=1.25, generator_dur_loss=1.828, generator_adv_loss=1.894, generator_feat_match_loss=3.185, over 100.00 samples.
2024-03-13 04:12:41,117 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 04:13:46,253 INFO [train.py:919] (2/6) Start epoch 277
2024-03-13 04:15:22,375 INFO [train.py:527] (2/6) Epoch 277, batch 26, global_batch_idx: 34250, batch size: 56, loss[discriminator_loss=2.726, discriminator_real_loss=1.391, discriminator_fake_loss=1.335, generator_loss=29.01, generator_mel_loss=18.82, generator_kl_loss=1.439, generator_dur_loss=1.737, generator_adv_loss=2.045, generator_feat_match_loss=4.977, over 56.00 samples.], tot_loss[discriminator_loss=2.728, discriminator_real_loss=1.382, discriminator_fake_loss=1.346, generator_loss=27.4, generator_mel_loss=18.27, generator_kl_loss=1.403, generator_dur_loss=1.75, generator_adv_loss=1.922, generator_feat_match_loss=4.056, over 1446.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 04:17:41,465 INFO [train.py:527] (2/6) Epoch 277, batch 76, global_batch_idx: 34300, batch size: 96, loss[discriminator_loss=2.726, discriminator_real_loss=1.418, discriminator_fake_loss=1.308, generator_loss=28.05, generator_mel_loss=18.5, generator_kl_loss=1.427, generator_dur_loss=1.848, generator_adv_loss=1.822, generator_feat_match_loss=4.449, over 96.00 samples.], tot_loss[discriminator_loss=2.732, discriminator_real_loss=1.386, discriminator_fake_loss=1.346, generator_loss=27.51, generator_mel_loss=18.37, generator_kl_loss=1.408, generator_dur_loss=1.759, generator_adv_loss=1.921, generator_feat_match_loss=4.056, over 4262.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 04:19:55,824 INFO [train.py:919] (2/6) Start epoch 278
2024-03-13 04:20:25,109 INFO [train.py:527] (2/6) Epoch 278, batch 2, global_batch_idx: 34350, batch size: 40, loss[discriminator_loss=2.734, discriminator_real_loss=1.356, discriminator_fake_loss=1.377, generator_loss=28, generator_mel_loss=18.6, generator_kl_loss=1.476, generator_dur_loss=1.705, generator_adv_loss=2.071, generator_feat_match_loss=4.144, over 40.00 samples.], tot_loss[discriminator_loss=2.749, discriminator_real_loss=1.43, discriminator_fake_loss=1.319, generator_loss=28.22, generator_mel_loss=19.01, generator_kl_loss=1.443, generator_dur_loss=1.755, generator_adv_loss=1.988, generator_feat_match_loss=4.031, over 121.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 04:22:44,506 INFO [train.py:527] (2/6) Epoch 278, batch 52, global_batch_idx: 34400, batch size: 70, loss[discriminator_loss=2.701, discriminator_real_loss=1.354, discriminator_fake_loss=1.346, generator_loss=27.18, generator_mel_loss=18.18, generator_kl_loss=1.206, generator_dur_loss=1.832, generator_adv_loss=1.914, generator_feat_match_loss=4.053, over 70.00 samples.], tot_loss[discriminator_loss=2.738, discriminator_real_loss=1.389, discriminator_fake_loss=1.349, generator_loss=27.57, generator_mel_loss=18.41, generator_kl_loss=1.401, generator_dur_loss=1.763, generator_adv_loss=1.962, generator_feat_match_loss=4.038, over 2919.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 04:22:44,508 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 04:22:52,579 INFO [train.py:591] (2/6) Epoch 278, validation: discriminator_loss=2.754, discriminator_real_loss=1.362, discriminator_fake_loss=1.392, generator_loss=26.71, generator_mel_loss=18.73, generator_kl_loss=1.163, generator_dur_loss=1.848, generator_adv_loss=1.733, generator_feat_match_loss=3.236, over 100.00 samples.
2024-03-13 04:22:52,581 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 04:25:11,189 INFO [train.py:527] (2/6) Epoch 278, batch 102, global_batch_idx: 34450, batch size: 45, loss[discriminator_loss=2.723, discriminator_real_loss=1.31, discriminator_fake_loss=1.413, generator_loss=27.55, generator_mel_loss=18.35, generator_kl_loss=1.375, generator_dur_loss=1.667, generator_adv_loss=2.021, generator_feat_match_loss=4.133, over 45.00 samples.], tot_loss[discriminator_loss=2.735, discriminator_real_loss=1.391, discriminator_fake_loss=1.344, generator_loss=27.5, generator_mel_loss=18.37, generator_kl_loss=1.391, generator_dur_loss=1.768, generator_adv_loss=1.953, generator_feat_match_loss=4.019, over 5720.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 04:26:11,514 INFO [train.py:919] (2/6) Start epoch 279
2024-03-13 04:27:52,057 INFO [train.py:527] (2/6) Epoch 279, batch 28, global_batch_idx: 34500, batch size: 42, loss[discriminator_loss=2.763, discriminator_real_loss=1.528, discriminator_fake_loss=1.236, generator_loss=28.68, generator_mel_loss=19.43, generator_kl_loss=1.588, generator_dur_loss=1.667, generator_adv_loss=2.077, generator_feat_match_loss=3.915, over 42.00 samples.], tot_loss[discriminator_loss=2.732, discriminator_real_loss=1.377, discriminator_fake_loss=1.355, generator_loss=27.47, generator_mel_loss=18.34, generator_kl_loss=1.36, generator_dur_loss=1.787, generator_adv_loss=1.935, generator_feat_match_loss=4.047, over 1793.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 04:30:10,993 INFO [train.py:527] (2/6) Epoch 279, batch 78, global_batch_idx: 34550, batch size: 74, loss[discriminator_loss=2.745, discriminator_real_loss=1.392, discriminator_fake_loss=1.354, generator_loss=27.3, generator_mel_loss=18.18, generator_kl_loss=1.487, generator_dur_loss=1.832, generator_adv_loss=1.908, generator_feat_match_loss=3.885, over 74.00 samples.], tot_loss[discriminator_loss=2.727, discriminator_real_loss=1.382, discriminator_fake_loss=1.345, generator_loss=27.51, generator_mel_loss=18.36, generator_kl_loss=1.368, generator_dur_loss=1.773, generator_adv_loss=1.937, generator_feat_match_loss=4.071, over 4698.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 04:32:16,735 INFO [train.py:919] (2/6) Start epoch 280
2024-03-13 04:32:52,465 INFO [train.py:527] (2/6) Epoch 280, batch 4, global_batch_idx: 34600, batch size: 80, loss[discriminator_loss=2.723, discriminator_real_loss=1.354, discriminator_fake_loss=1.369, generator_loss=27.72, generator_mel_loss=18.64, generator_kl_loss=1.452, generator_dur_loss=1.845, generator_adv_loss=1.822, generator_feat_match_loss=3.957, over 80.00 samples.], tot_loss[discriminator_loss=2.722, discriminator_real_loss=1.371, discriminator_fake_loss=1.351, generator_loss=27.4, generator_mel_loss=18.4, generator_kl_loss=1.431, generator_dur_loss=1.81, generator_adv_loss=1.887, generator_feat_match_loss=3.867, over 351.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 04:32:52,468 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 04:33:00,125 INFO [train.py:591] (2/6) Epoch 280, validation: discriminator_loss=2.782, discriminator_real_loss=1.365, discriminator_fake_loss=1.417, generator_loss=26.63, generator_mel_loss=18.46, generator_kl_loss=1.26, generator_dur_loss=1.827, generator_adv_loss=1.759, generator_feat_match_loss=3.332, over 100.00 samples.
2024-03-13 04:33:00,210 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 04:35:18,198 INFO [train.py:527] (2/6) Epoch 280, batch 54, global_batch_idx: 34650, batch size: 52, loss[discriminator_loss=2.768, discriminator_real_loss=1.403, discriminator_fake_loss=1.365, generator_loss=27.13, generator_mel_loss=18.16, generator_kl_loss=1.406, generator_dur_loss=1.708, generator_adv_loss=1.991, generator_feat_match_loss=3.869, over 52.00 samples.], tot_loss[discriminator_loss=2.73, discriminator_real_loss=1.382, discriminator_fake_loss=1.348, generator_loss=27.51, generator_mel_loss=18.37, generator_kl_loss=1.39, generator_dur_loss=1.769, generator_adv_loss=1.915, generator_feat_match_loss=4.063, over 3219.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 04:37:37,890 INFO [train.py:527] (2/6) Epoch 280, batch 104, global_batch_idx: 34700, batch size: 62, loss[discriminator_loss=2.764, discriminator_real_loss=1.404, discriminator_fake_loss=1.36, generator_loss=27.5, generator_mel_loss=18.8, generator_kl_loss=1.418, generator_dur_loss=1.725, generator_adv_loss=1.849, generator_feat_match_loss=3.708, over 62.00 samples.], tot_loss[discriminator_loss=2.728, discriminator_real_loss=1.38, discriminator_fake_loss=1.348, generator_loss=27.61, generator_mel_loss=18.42, generator_kl_loss=1.389, generator_dur_loss=1.777, generator_adv_loss=1.917, generator_feat_match_loss=4.106, over 6303.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 04:38:30,911 INFO [train.py:919] (2/6) Start epoch 281
2024-03-13 04:40:20,051 INFO [train.py:527] (2/6) Epoch 281, batch 30, global_batch_idx: 34750, batch size: 61, loss[discriminator_loss=2.751, discriminator_real_loss=1.462, discriminator_fake_loss=1.289, generator_loss=27.78, generator_mel_loss=18.65, generator_kl_loss=1.342, generator_dur_loss=1.714, generator_adv_loss=1.863, generator_feat_match_loss=4.211, over 61.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.38, discriminator_fake_loss=1.34, generator_loss=27.52, generator_mel_loss=18.35, generator_kl_loss=1.358, generator_dur_loss=1.792, generator_adv_loss=1.919, generator_feat_match_loss=4.094, over 2037.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 04:42:40,562 INFO [train.py:527] (2/6) Epoch 281, batch 80, global_batch_idx: 34800, batch size: 83, loss[discriminator_loss=2.734, discriminator_real_loss=1.439, discriminator_fake_loss=1.295, generator_loss=27.91, generator_mel_loss=18.95, generator_kl_loss=1.36, generator_dur_loss=1.881, generator_adv_loss=1.935, generator_feat_match_loss=3.783, over 83.00 samples.], tot_loss[discriminator_loss=2.727, discriminator_real_loss=1.384, discriminator_fake_loss=1.343, generator_loss=27.48, generator_mel_loss=18.32, generator_kl_loss=1.38, generator_dur_loss=1.784, generator_adv_loss=1.924, generator_feat_match_loss=4.079, over 5026.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 04:42:40,564 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 04:42:48,869 INFO [train.py:591] (2/6) Epoch 281, validation: discriminator_loss=2.807, discriminator_real_loss=1.512, discriminator_fake_loss=1.295, generator_loss=26.8, generator_mel_loss=18.6, generator_kl_loss=1.13, generator_dur_loss=1.832, generator_adv_loss=1.896, generator_feat_match_loss=3.337, over 100.00 samples.
2024-03-13 04:42:48,869 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 04:44:47,622 INFO [train.py:919] (2/6) Start epoch 282
2024-03-13 04:45:27,878 INFO [train.py:527] (2/6) Epoch 282, batch 6, global_batch_idx: 34850, batch size: 88, loss[discriminator_loss=2.713, discriminator_real_loss=1.327, discriminator_fake_loss=1.386, generator_loss=27.52, generator_mel_loss=18.42, generator_kl_loss=1.215, generator_dur_loss=1.913, generator_adv_loss=1.952, generator_feat_match_loss=4.019, over 88.00 samples.], tot_loss[discriminator_loss=2.709, discriminator_real_loss=1.355, discriminator_fake_loss=1.355, generator_loss=28.05, generator_mel_loss=18.7, generator_kl_loss=1.391, generator_dur_loss=1.77, generator_adv_loss=1.935, generator_feat_match_loss=4.254, over 399.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 04:47:45,431 INFO [train.py:527] (2/6) Epoch 282, batch 56, global_batch_idx: 34900, batch size: 45, loss[discriminator_loss=2.66, discriminator_real_loss=1.34, discriminator_fake_loss=1.32, generator_loss=28.04, generator_mel_loss=18.61, generator_kl_loss=1.606, generator_dur_loss=1.708, generator_adv_loss=1.946, generator_feat_match_loss=4.171, over 45.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.365, discriminator_fake_loss=1.351, generator_loss=27.71, generator_mel_loss=18.39, generator_kl_loss=1.419, generator_dur_loss=1.754, generator_adv_loss=1.929, generator_feat_match_loss=4.221, over 3269.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 04:50:06,624 INFO [train.py:527] (2/6) Epoch 282, batch 106, global_batch_idx: 34950, batch size: 45, loss[discriminator_loss=2.825, discriminator_real_loss=1.401, discriminator_fake_loss=1.424, generator_loss=27.97, generator_mel_loss=18.53, generator_kl_loss=1.588, generator_dur_loss=1.63, generator_adv_loss=1.763, generator_feat_match_loss=4.458, over 45.00 samples.], tot_loss[discriminator_loss=2.723, discriminator_real_loss=1.368, discriminator_fake_loss=1.355, generator_loss=27.69, generator_mel_loss=18.4, generator_kl_loss=1.416, generator_dur_loss=1.753, generator_adv_loss=1.932, generator_feat_match_loss=4.187, over 5890.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 04:50:54,480 INFO [train.py:919] (2/6) Start epoch 283
2024-03-13 04:52:47,955 INFO [train.py:527] (2/6) Epoch 283, batch 32, global_batch_idx: 35000, batch size: 64, loss[discriminator_loss=2.753, discriminator_real_loss=1.367, discriminator_fake_loss=1.385, generator_loss=27.49, generator_mel_loss=18.06, generator_kl_loss=1.612, generator_dur_loss=1.778, generator_adv_loss=1.864, generator_feat_match_loss=4.18, over 64.00 samples.], tot_loss[discriminator_loss=2.749, discriminator_real_loss=1.401, discriminator_fake_loss=1.348, generator_loss=27.53, generator_mel_loss=18.35, generator_kl_loss=1.388, generator_dur_loss=1.774, generator_adv_loss=1.926, generator_feat_match_loss=4.096, over 2063.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 04:52:47,957 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 04:52:56,062 INFO [train.py:591] (2/6) Epoch 283, validation: discriminator_loss=2.796, discriminator_real_loss=1.416, discriminator_fake_loss=1.38, generator_loss=26.57, generator_mel_loss=18.39, generator_kl_loss=1.123, generator_dur_loss=1.821, generator_adv_loss=1.839, generator_feat_match_loss=3.391, over 100.00 samples.
2024-03-13 04:52:56,063 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 04:55:17,657 INFO [train.py:527] (2/6) Epoch 283, batch 82, global_batch_idx: 35050, batch size: 96, loss[discriminator_loss=2.682, discriminator_real_loss=1.407, discriminator_fake_loss=1.274, generator_loss=27.04, generator_mel_loss=17.69, generator_kl_loss=1.361, generator_dur_loss=1.848, generator_adv_loss=1.958, generator_feat_match_loss=4.188, over 96.00 samples.], tot_loss[discriminator_loss=2.736, discriminator_real_loss=1.387, discriminator_fake_loss=1.349, generator_loss=27.54, generator_mel_loss=18.34, generator_kl_loss=1.381, generator_dur_loss=1.779, generator_adv_loss=1.922, generator_feat_match_loss=4.124, over 5039.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 04:57:08,636 INFO [train.py:919] (2/6) Start epoch 284
2024-03-13 04:57:56,636 INFO [train.py:527] (2/6) Epoch 284, batch 8, global_batch_idx: 35100, batch size: 25, loss[discriminator_loss=2.612, discriminator_real_loss=1.265, discriminator_fake_loss=1.347, generator_loss=29.34, generator_mel_loss=19.13, generator_kl_loss=1.733, generator_dur_loss=1.546, generator_adv_loss=2.16, generator_feat_match_loss=4.77, over 25.00 samples.], tot_loss[discriminator_loss=2.727, discriminator_real_loss=1.391, discriminator_fake_loss=1.337, generator_loss=27.93, generator_mel_loss=18.6, generator_kl_loss=1.397, generator_dur_loss=1.751, generator_adv_loss=1.928, generator_feat_match_loss=4.251, over 502.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 05:00:13,739 INFO [train.py:527] (2/6) Epoch 284, batch 58, global_batch_idx: 35150, batch size: 55, loss[discriminator_loss=2.45, discriminator_real_loss=1.154, discriminator_fake_loss=1.295, generator_loss=29.59, generator_mel_loss=18.66, generator_kl_loss=1.465, generator_dur_loss=1.706, generator_adv_loss=2.429, generator_feat_match_loss=5.328, over 55.00 samples.], tot_loss[discriminator_loss=2.729, discriminator_real_loss=1.376, discriminator_fake_loss=1.353, generator_loss=27.89, generator_mel_loss=18.49, generator_kl_loss=1.404, generator_dur_loss=1.764, generator_adv_loss=1.962, generator_feat_match_loss=4.275, over 3307.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 05:02:32,517 INFO [train.py:527] (2/6) Epoch 284, batch 108, global_batch_idx: 35200, batch size: 96, loss[discriminator_loss=2.711, discriminator_real_loss=1.277, discriminator_fake_loss=1.434, generator_loss=27.74, generator_mel_loss=18.36, generator_kl_loss=1.148, generator_dur_loss=1.823, generator_adv_loss=1.963, generator_feat_match_loss=4.44, over 96.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.38, discriminator_fake_loss=1.347, generator_loss=27.78, generator_mel_loss=18.43, generator_kl_loss=1.403, generator_dur_loss=1.757, generator_adv_loss=1.974, generator_feat_match_loss=4.22, over 6147.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 05:02:32,518 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 05:02:41,050 INFO [train.py:591] (2/6) Epoch 284, validation: discriminator_loss=2.771, discriminator_real_loss=1.492, discriminator_fake_loss=1.28, generator_loss=25.9, generator_mel_loss=17.74, generator_kl_loss=1.18, generator_dur_loss=1.807, generator_adv_loss=1.92, generator_feat_match_loss=3.253, over 100.00 samples.
2024-03-13 05:02:41,051 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 05:03:23,843 INFO [train.py:919] (2/6) Start epoch 285
2024-03-13 05:05:22,036 INFO [train.py:527] (2/6) Epoch 285, batch 34, global_batch_idx: 35250, batch size: 47, loss[discriminator_loss=2.722, discriminator_real_loss=1.407, discriminator_fake_loss=1.314, generator_loss=28.39, generator_mel_loss=18.78, generator_kl_loss=1.512, generator_dur_loss=1.678, generator_adv_loss=1.891, generator_feat_match_loss=4.527, over 47.00 samples.], tot_loss[discriminator_loss=2.747, discriminator_real_loss=1.396, discriminator_fake_loss=1.351, generator_loss=27.35, generator_mel_loss=18.25, generator_kl_loss=1.393, generator_dur_loss=1.758, generator_adv_loss=1.905, generator_feat_match_loss=4.04, over 2048.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 05:07:39,961 INFO [train.py:527] (2/6) Epoch 285, batch 84, global_batch_idx: 35300, batch size: 50, loss[discriminator_loss=2.71, discriminator_real_loss=1.366, discriminator_fake_loss=1.343, generator_loss=27.74, generator_mel_loss=18.45, generator_kl_loss=1.347, generator_dur_loss=1.678, generator_adv_loss=1.97, generator_feat_match_loss=4.296, over 50.00 samples.], tot_loss[discriminator_loss=2.742, discriminator_real_loss=1.397, discriminator_fake_loss=1.345, generator_loss=27.38, generator_mel_loss=18.28, generator_kl_loss=1.388, generator_dur_loss=1.759, generator_adv_loss=1.914, generator_feat_match_loss=4.038, over 4974.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 05:09:32,421 INFO [train.py:919] (2/6) Start epoch 286
2024-03-13 05:10:24,790 INFO [train.py:527] (2/6) Epoch 286, batch 10, global_batch_idx: 35350, batch size: 88, loss[discriminator_loss=2.772, discriminator_real_loss=1.457, discriminator_fake_loss=1.315, generator_loss=27.05, generator_mel_loss=18.23, generator_kl_loss=1.232, generator_dur_loss=1.893, generator_adv_loss=1.722, generator_feat_match_loss=3.97, over 88.00 samples.], tot_loss[discriminator_loss=2.735, discriminator_real_loss=1.392, discriminator_fake_loss=1.343, generator_loss=27.42, generator_mel_loss=18.34, generator_kl_loss=1.35, generator_dur_loss=1.789, generator_adv_loss=1.881, generator_feat_match_loss=4.067, over 636.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 05:12:44,996 INFO [train.py:527] (2/6) Epoch 286, batch 60, global_batch_idx: 35400, batch size: 45, loss[discriminator_loss=2.783, discriminator_real_loss=1.322, discriminator_fake_loss=1.462, generator_loss=28.17, generator_mel_loss=18.7, generator_kl_loss=1.577, generator_dur_loss=1.707, generator_adv_loss=1.867, generator_feat_match_loss=4.314, over 45.00 samples.], tot_loss[discriminator_loss=2.74, discriminator_real_loss=1.388, discriminator_fake_loss=1.352, generator_loss=27.5, generator_mel_loss=18.34, generator_kl_loss=1.392, generator_dur_loss=1.774, generator_adv_loss=1.916, generator_feat_match_loss=4.072, over 3473.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 05:12:44,997 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 05:12:52,912 INFO [train.py:591] (2/6) Epoch 286, validation: discriminator_loss=2.799, discriminator_real_loss=1.48, discriminator_fake_loss=1.319, generator_loss=26.04, generator_mel_loss=18.04, generator_kl_loss=1.163, generator_dur_loss=1.825, generator_adv_loss=1.883, generator_feat_match_loss=3.125, over 100.00 samples.
2024-03-13 05:12:52,913 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 05:15:11,531 INFO [train.py:527] (2/6) Epoch 286, batch 110, global_batch_idx: 35450, batch size: 47, loss[discriminator_loss=2.728, discriminator_real_loss=1.359, discriminator_fake_loss=1.37, generator_loss=27.09, generator_mel_loss=17.83, generator_kl_loss=1.524, generator_dur_loss=1.716, generator_adv_loss=1.837, generator_feat_match_loss=4.19, over 47.00 samples.], tot_loss[discriminator_loss=2.739, discriminator_real_loss=1.391, discriminator_fake_loss=1.348, generator_loss=27.49, generator_mel_loss=18.34, generator_kl_loss=1.4, generator_dur_loss=1.762, generator_adv_loss=1.917, generator_feat_match_loss=4.07, over 6205.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 05:15:50,014 INFO [train.py:919] (2/6) Start epoch 287
2024-03-13 05:17:54,336 INFO [train.py:527] (2/6) Epoch 287, batch 36, global_batch_idx: 35500, batch size: 80, loss[discriminator_loss=2.703, discriminator_real_loss=1.343, discriminator_fake_loss=1.36, generator_loss=27.44, generator_mel_loss=18.14, generator_kl_loss=1.391, generator_dur_loss=1.851, generator_adv_loss=1.844, generator_feat_match_loss=4.208, over 80.00 samples.], tot_loss[discriminator_loss=2.734, discriminator_real_loss=1.38, discriminator_fake_loss=1.354, generator_loss=27.45, generator_mel_loss=18.23, generator_kl_loss=1.423, generator_dur_loss=1.754, generator_adv_loss=1.907, generator_feat_match_loss=4.136, over 2327.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 05:20:15,433 INFO [train.py:527] (2/6) Epoch 287, batch 86, global_batch_idx: 35550, batch size: 83, loss[discriminator_loss=2.715, discriminator_real_loss=1.368, discriminator_fake_loss=1.346, generator_loss=28.28, generator_mel_loss=18.67, generator_kl_loss=1.35, generator_dur_loss=1.86, generator_adv_loss=1.931, generator_feat_match_loss=4.476, over 83.00 samples.], tot_loss[discriminator_loss=2.729, discriminator_real_loss=1.375, discriminator_fake_loss=1.354, generator_loss=27.53, generator_mel_loss=18.31, generator_kl_loss=1.407, generator_dur_loss=1.759, generator_adv_loss=1.921, generator_feat_match_loss=4.142, over 5256.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 05:21:57,031 INFO [train.py:919] (2/6) Start epoch 288
2024-03-13 05:22:55,044 INFO [train.py:527] (2/6) Epoch 288, batch 12, global_batch_idx: 35600, batch size: 72, loss[discriminator_loss=2.697, discriminator_real_loss=1.341, discriminator_fake_loss=1.355, generator_loss=27.93, generator_mel_loss=18.49, generator_kl_loss=1.247, generator_dur_loss=1.841, generator_adv_loss=2.068, generator_feat_match_loss=4.294, over 72.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.378, discriminator_fake_loss=1.342, generator_loss=27.72, generator_mel_loss=18.4, generator_kl_loss=1.394, generator_dur_loss=1.782, generator_adv_loss=1.935, generator_feat_match_loss=4.209, over 859.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 05:22:55,083 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 05:23:03,117 INFO [train.py:591] (2/6) Epoch 288, validation: discriminator_loss=2.768, discriminator_real_loss=1.54, discriminator_fake_loss=1.228, generator_loss=27.05, generator_mel_loss=18.75, generator_kl_loss=1.322, generator_dur_loss=1.823, generator_adv_loss=2, generator_feat_match_loss=3.158, over 100.00 samples.
2024-03-13 05:23:03,118 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 05:25:20,681 INFO [train.py:527] (2/6) Epoch 288, batch 62, global_batch_idx: 35650, batch size: 44, loss[discriminator_loss=2.711, discriminator_real_loss=1.451, discriminator_fake_loss=1.259, generator_loss=27.64, generator_mel_loss=18.8, generator_kl_loss=1.406, generator_dur_loss=1.751, generator_adv_loss=1.831, generator_feat_match_loss=3.857, over 44.00 samples.], tot_loss[discriminator_loss=2.727, discriminator_real_loss=1.381, discriminator_fake_loss=1.346, generator_loss=27.56, generator_mel_loss=18.35, generator_kl_loss=1.397, generator_dur_loss=1.761, generator_adv_loss=1.918, generator_feat_match_loss=4.134, over 3822.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 05:27:39,559 INFO [train.py:527] (2/6) Epoch 288, batch 112, global_batch_idx: 35700, batch size: 61, loss[discriminator_loss=2.727, discriminator_real_loss=1.418, discriminator_fake_loss=1.309, generator_loss=26.98, generator_mel_loss=18.22, generator_kl_loss=1.515, generator_dur_loss=1.758, generator_adv_loss=1.921, generator_feat_match_loss=3.571, over 61.00 samples.], tot_loss[discriminator_loss=2.723, discriminator_real_loss=1.376, discriminator_fake_loss=1.347, generator_loss=27.64, generator_mel_loss=18.37, generator_kl_loss=1.398, generator_dur_loss=1.764, generator_adv_loss=1.934, generator_feat_match_loss=4.175, over 6808.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 05:28:10,629 INFO [train.py:919] (2/6) Start epoch 289
2024-03-13 05:30:22,435 INFO [train.py:527] (2/6) Epoch 289, batch 38, global_batch_idx: 35750, batch size: 64, loss[discriminator_loss=2.82, discriminator_real_loss=1.508, discriminator_fake_loss=1.312, generator_loss=27.24, generator_mel_loss=18.53, generator_kl_loss=1.248, generator_dur_loss=1.796, generator_adv_loss=1.83, generator_feat_match_loss=3.829, over 64.00 samples.], tot_loss[discriminator_loss=2.731, discriminator_real_loss=1.391, discriminator_fake_loss=1.341, generator_loss=27.46, generator_mel_loss=18.29, generator_kl_loss=1.355, generator_dur_loss=1.779, generator_adv_loss=1.925, generator_feat_match_loss=4.112, over 2452.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 05:32:42,132 INFO [train.py:527] (2/6) Epoch 289, batch 88, global_batch_idx: 35800, batch size: 58, loss[discriminator_loss=2.688, discriminator_real_loss=1.343, discriminator_fake_loss=1.344, generator_loss=27.96, generator_mel_loss=18.29, generator_kl_loss=1.422, generator_dur_loss=1.802, generator_adv_loss=2.048, generator_feat_match_loss=4.4, over 58.00 samples.], tot_loss[discriminator_loss=2.732, discriminator_real_loss=1.387, discriminator_fake_loss=1.345, generator_loss=27.56, generator_mel_loss=18.34, generator_kl_loss=1.378, generator_dur_loss=1.782, generator_adv_loss=1.923, generator_feat_match_loss=4.132, over 5360.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 05:32:42,133 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 05:32:50,894 INFO [train.py:591] (2/6) Epoch 289, validation: discriminator_loss=2.816, discriminator_real_loss=1.512, discriminator_fake_loss=1.304, generator_loss=25.95, generator_mel_loss=18.07, generator_kl_loss=1.23, generator_dur_loss=1.839, generator_adv_loss=1.954, generator_feat_match_loss=2.858, over 100.00 samples.
2024-03-13 05:32:50,895 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 05:34:27,347 INFO [train.py:919] (2/6) Start epoch 290
2024-03-13 05:35:31,925 INFO [train.py:527] (2/6) Epoch 290, batch 14, global_batch_idx: 35850, batch size: 53, loss[discriminator_loss=2.732, discriminator_real_loss=1.441, discriminator_fake_loss=1.291, generator_loss=27.14, generator_mel_loss=18.27, generator_kl_loss=1.402, generator_dur_loss=1.724, generator_adv_loss=1.869, generator_feat_match_loss=3.865, over 53.00 samples.], tot_loss[discriminator_loss=2.746, discriminator_real_loss=1.399, discriminator_fake_loss=1.347, generator_loss=27.5, generator_mel_loss=18.43, generator_kl_loss=1.376, generator_dur_loss=1.781, generator_adv_loss=1.899, generator_feat_match_loss=4.01, over 870.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 05:37:53,291 INFO [train.py:527] (2/6) Epoch 290, batch 64, global_batch_idx: 35900, batch size: 44, loss[discriminator_loss=2.719, discriminator_real_loss=1.358, discriminator_fake_loss=1.361, generator_loss=27.91, generator_mel_loss=18.51, generator_kl_loss=1.667, generator_dur_loss=1.677, generator_adv_loss=1.762, generator_feat_match_loss=4.296, over 44.00 samples.], tot_loss[discriminator_loss=2.731, discriminator_real_loss=1.385, discriminator_fake_loss=1.347, generator_loss=27.5, generator_mel_loss=18.28, generator_kl_loss=1.409, generator_dur_loss=1.768, generator_adv_loss=1.93, generator_feat_match_loss=4.115, over 3986.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 05:40:10,183 INFO [train.py:527] (2/6) Epoch 290, batch 114, global_batch_idx: 35950, batch size: 55, loss[discriminator_loss=2.733, discriminator_real_loss=1.576, discriminator_fake_loss=1.157, generator_loss=27.74, generator_mel_loss=18.82, generator_kl_loss=1.515, generator_dur_loss=1.669, generator_adv_loss=1.846, generator_feat_match_loss=3.888, over 55.00 samples.], tot_loss[discriminator_loss=2.727, discriminator_real_loss=1.381, discriminator_fake_loss=1.345, generator_loss=27.55, generator_mel_loss=18.3, generator_kl_loss=1.415, generator_dur_loss=1.761, generator_adv_loss=1.93, generator_feat_match_loss=4.143, over 6776.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 05:40:36,181 INFO [train.py:919] (2/6) Start epoch 291
2024-03-13 05:42:51,863 INFO [train.py:527] (2/6) Epoch 291, batch 40, global_batch_idx: 36000, batch size: 70, loss[discriminator_loss=2.703, discriminator_real_loss=1.361, discriminator_fake_loss=1.343, generator_loss=27.92, generator_mel_loss=18.68, generator_kl_loss=1.346, generator_dur_loss=1.793, generator_adv_loss=1.887, generator_feat_match_loss=4.212, over 70.00 samples.], tot_loss[discriminator_loss=2.728, discriminator_real_loss=1.393, discriminator_fake_loss=1.335, generator_loss=27.45, generator_mel_loss=18.31, generator_kl_loss=1.411, generator_dur_loss=1.754, generator_adv_loss=1.922, generator_feat_match_loss=4.049, over 2374.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 05:42:51,864 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 05:42:59,896 INFO [train.py:591] (2/6) Epoch 291, validation: discriminator_loss=2.702, discriminator_real_loss=1.352, discriminator_fake_loss=1.351, generator_loss=26.77, generator_mel_loss=18.71, generator_kl_loss=1.263, generator_dur_loss=1.81, generator_adv_loss=1.784, generator_feat_match_loss=3.208, over 100.00 samples.
2024-03-13 05:42:59,903 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 05:45:19,167 INFO [train.py:527] (2/6) Epoch 291, batch 90, global_batch_idx: 36050, batch size: 25, loss[discriminator_loss=2.814, discriminator_real_loss=1.36, discriminator_fake_loss=1.453, generator_loss=29.16, generator_mel_loss=19.59, generator_kl_loss=1.676, generator_dur_loss=1.605, generator_adv_loss=1.864, generator_feat_match_loss=4.424, over 25.00 samples.], tot_loss[discriminator_loss=2.728, discriminator_real_loss=1.384, discriminator_fake_loss=1.344, generator_loss=27.52, generator_mel_loss=18.37, generator_kl_loss=1.414, generator_dur_loss=1.747, generator_adv_loss=1.919, generator_feat_match_loss=4.07, over 5112.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 05:46:50,806 INFO [train.py:919] (2/6) Start epoch 292
2024-03-13 05:47:55,708 INFO [train.py:527] (2/6) Epoch 292, batch 16, global_batch_idx: 36100, batch size: 62, loss[discriminator_loss=2.76, discriminator_real_loss=1.337, discriminator_fake_loss=1.423, generator_loss=27.18, generator_mel_loss=18.47, generator_kl_loss=1.339, generator_dur_loss=1.742, generator_adv_loss=1.879, generator_feat_match_loss=3.75, over 62.00 samples.], tot_loss[discriminator_loss=2.731, discriminator_real_loss=1.361, discriminator_fake_loss=1.369, generator_loss=27.61, generator_mel_loss=18.32, generator_kl_loss=1.433, generator_dur_loss=1.747, generator_adv_loss=1.937, generator_feat_match_loss=4.172, over 926.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 05:50:13,902 INFO [train.py:527] (2/6) Epoch 292, batch 66, global_batch_idx: 36150, batch size: 58, loss[discriminator_loss=2.717, discriminator_real_loss=1.369, discriminator_fake_loss=1.349, generator_loss=27.83, generator_mel_loss=18.55, generator_kl_loss=1.396, generator_dur_loss=1.749, generator_adv_loss=1.898, generator_feat_match_loss=4.239, over 58.00 samples.], tot_loss[discriminator_loss=2.721, discriminator_real_loss=1.376, discriminator_fake_loss=1.345, generator_loss=27.66, generator_mel_loss=18.36, generator_kl_loss=1.425, generator_dur_loss=1.757, generator_adv_loss=1.955, generator_feat_match_loss=4.158, over 3534.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 05:52:35,055 INFO [train.py:527] (2/6) Epoch 292, batch 116, global_batch_idx: 36200, batch size: 88, loss[discriminator_loss=2.694, discriminator_real_loss=1.316, discriminator_fake_loss=1.378, generator_loss=27.27, generator_mel_loss=18.25, generator_kl_loss=1.312, generator_dur_loss=1.849, generator_adv_loss=1.825, generator_feat_match_loss=4.035, over 88.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.372, discriminator_fake_loss=1.344, generator_loss=27.63, generator_mel_loss=18.34, generator_kl_loss=1.407, generator_dur_loss=1.767, generator_adv_loss=1.945, generator_feat_match_loss=4.176, over 6515.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 05:52:35,057 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 05:52:43,683 INFO [train.py:591] (2/6) Epoch 292, validation: discriminator_loss=2.741, discriminator_real_loss=1.413, discriminator_fake_loss=1.328, generator_loss=26.7, generator_mel_loss=18.29, generator_kl_loss=1.206, generator_dur_loss=1.825, generator_adv_loss=1.835, generator_feat_match_loss=3.55, over 100.00 samples.
2024-03-13 05:52:43,683 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 05:53:04,592 INFO [train.py:919] (2/6) Start epoch 293
2024-03-13 05:55:21,907 INFO [train.py:527] (2/6) Epoch 293, batch 42, global_batch_idx: 36250, batch size: 58, loss[discriminator_loss=2.734, discriminator_real_loss=1.322, discriminator_fake_loss=1.411, generator_loss=27.74, generator_mel_loss=18.69, generator_kl_loss=1.337, generator_dur_loss=1.744, generator_adv_loss=1.98, generator_feat_match_loss=3.983, over 58.00 samples.], tot_loss[discriminator_loss=2.721, discriminator_real_loss=1.38, discriminator_fake_loss=1.341, generator_loss=27.58, generator_mel_loss=18.36, generator_kl_loss=1.399, generator_dur_loss=1.757, generator_adv_loss=1.931, generator_feat_match_loss=4.138, over 2492.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 05:57:42,457 INFO [train.py:527] (2/6) Epoch 293, batch 92, global_batch_idx: 36300, batch size: 68, loss[discriminator_loss=2.764, discriminator_real_loss=1.386, discriminator_fake_loss=1.378, generator_loss=27.81, generator_mel_loss=18.53, generator_kl_loss=1.488, generator_dur_loss=1.754, generator_adv_loss=1.959, generator_feat_match_loss=4.075, over 68.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.385, discriminator_fake_loss=1.341, generator_loss=27.52, generator_mel_loss=18.31, generator_kl_loss=1.392, generator_dur_loss=1.761, generator_adv_loss=1.924, generator_feat_match_loss=4.128, over 5457.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 05:59:11,890 INFO [train.py:919] (2/6) Start epoch 294
2024-03-13 06:00:24,442 INFO [train.py:527] (2/6) Epoch 294, batch 18, global_batch_idx: 36350, batch size: 96, loss[discriminator_loss=2.74, discriminator_real_loss=1.328, discriminator_fake_loss=1.412, generator_loss=27.56, generator_mel_loss=18.3, generator_kl_loss=1.315, generator_dur_loss=1.855, generator_adv_loss=1.926, generator_feat_match_loss=4.165, over 96.00 samples.], tot_loss[discriminator_loss=2.745, discriminator_real_loss=1.382, discriminator_fake_loss=1.362, generator_loss=27.09, generator_mel_loss=18.08, generator_kl_loss=1.372, generator_dur_loss=1.765, generator_adv_loss=1.912, generator_feat_match_loss=3.957, over 1194.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 06:02:44,297 INFO [train.py:527] (2/6) Epoch 294, batch 68, global_batch_idx: 36400, batch size: 39, loss[discriminator_loss=2.788, discriminator_real_loss=1.507, discriminator_fake_loss=1.281, generator_loss=26.76, generator_mel_loss=18.31, generator_kl_loss=1.487, generator_dur_loss=1.735, generator_adv_loss=1.883, generator_feat_match_loss=3.349, over 39.00 samples.], tot_loss[discriminator_loss=2.731, discriminator_real_loss=1.381, discriminator_fake_loss=1.35, generator_loss=27.54, generator_mel_loss=18.27, generator_kl_loss=1.39, generator_dur_loss=1.758, generator_adv_loss=1.959, generator_feat_match_loss=4.16, over 4035.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 06:02:44,299 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 06:02:52,556 INFO [train.py:591] (2/6) Epoch 294, validation: discriminator_loss=2.832, discriminator_real_loss=1.44, discriminator_fake_loss=1.392, generator_loss=27.03, generator_mel_loss=18.63, generator_kl_loss=1.28, generator_dur_loss=1.816, generator_adv_loss=1.795, generator_feat_match_loss=3.515, over 100.00 samples.
2024-03-13 06:02:52,557 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 06:05:11,261 INFO [train.py:527] (2/6) Epoch 294, batch 118, global_batch_idx: 36450, batch size: 72, loss[discriminator_loss=2.768, discriminator_real_loss=1.477, discriminator_fake_loss=1.291, generator_loss=26.81, generator_mel_loss=18.23, generator_kl_loss=1.257, generator_dur_loss=1.868, generator_adv_loss=1.89, generator_feat_match_loss=3.559, over 72.00 samples.], tot_loss[discriminator_loss=2.728, discriminator_real_loss=1.381, discriminator_fake_loss=1.347, generator_loss=27.5, generator_mel_loss=18.29, generator_kl_loss=1.392, generator_dur_loss=1.765, generator_adv_loss=1.941, generator_feat_match_loss=4.114, over 6966.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 06:05:24,638 INFO [train.py:919] (2/6) Start epoch 295
2024-03-13 06:07:52,735 INFO [train.py:527] (2/6) Epoch 295, batch 44, global_batch_idx: 36500, batch size: 61, loss[discriminator_loss=2.705, discriminator_real_loss=1.365, discriminator_fake_loss=1.34, generator_loss=27.49, generator_mel_loss=18.33, generator_kl_loss=1.328, generator_dur_loss=1.814, generator_adv_loss=2.053, generator_feat_match_loss=3.963, over 61.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.378, discriminator_fake_loss=1.337, generator_loss=27.6, generator_mel_loss=18.31, generator_kl_loss=1.4, generator_dur_loss=1.769, generator_adv_loss=1.932, generator_feat_match_loss=4.195, over 2652.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 06:10:12,754 INFO [train.py:527] (2/6) Epoch 295, batch 94, global_batch_idx: 36550, batch size: 80, loss[discriminator_loss=2.766, discriminator_real_loss=1.391, discriminator_fake_loss=1.375, generator_loss=28.14, generator_mel_loss=18.66, generator_kl_loss=1.33, generator_dur_loss=1.814, generator_adv_loss=1.886, generator_feat_match_loss=4.448, over 80.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.382, discriminator_fake_loss=1.343, generator_loss=27.61, generator_mel_loss=18.32, generator_kl_loss=1.396, generator_dur_loss=1.772, generator_adv_loss=1.923, generator_feat_match_loss=4.2, over 5601.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 06:11:31,720 INFO [train.py:919] (2/6) Start epoch 296
2024-03-13 06:12:52,837 INFO [train.py:527] (2/6) Epoch 296, batch 20, global_batch_idx: 36600, batch size: 31, loss[discriminator_loss=2.706, discriminator_real_loss=1.287, discriminator_fake_loss=1.419, generator_loss=26.83, generator_mel_loss=17.79, generator_kl_loss=1.389, generator_dur_loss=1.648, generator_adv_loss=1.845, generator_feat_match_loss=4.158, over 31.00 samples.], tot_loss[discriminator_loss=2.741, discriminator_real_loss=1.398, discriminator_fake_loss=1.343, generator_loss=27.71, generator_mel_loss=18.42, generator_kl_loss=1.431, generator_dur_loss=1.746, generator_adv_loss=1.921, generator_feat_match_loss=4.187, over 1132.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 06:12:52,838 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 06:13:00,870 INFO [train.py:591] (2/6) Epoch 296, validation: discriminator_loss=2.754, discriminator_real_loss=1.435, discriminator_fake_loss=1.319, generator_loss=26.94, generator_mel_loss=18.58, generator_kl_loss=1.185, generator_dur_loss=1.837, generator_adv_loss=1.825, generator_feat_match_loss=3.513, over 100.00 samples.
2024-03-13 06:13:00,872 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 06:15:21,450 INFO [train.py:527] (2/6) Epoch 296, batch 70, global_batch_idx: 36650, batch size: 36, loss[discriminator_loss=2.77, discriminator_real_loss=1.483, discriminator_fake_loss=1.287, generator_loss=26.79, generator_mel_loss=18.08, generator_kl_loss=1.509, generator_dur_loss=1.674, generator_adv_loss=1.798, generator_feat_match_loss=3.73, over 36.00 samples.], tot_loss[discriminator_loss=2.731, discriminator_real_loss=1.385, discriminator_fake_loss=1.346, generator_loss=27.61, generator_mel_loss=18.36, generator_kl_loss=1.404, generator_dur_loss=1.773, generator_adv_loss=1.928, generator_feat_match_loss=4.146, over 4104.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 06:17:34,805 INFO [train.py:527] (2/6) Epoch 296, batch 120, global_batch_idx: 36700, batch size: 45, loss[discriminator_loss=2.719, discriminator_real_loss=1.325, discriminator_fake_loss=1.394, generator_loss=28.06, generator_mel_loss=18.3, generator_kl_loss=1.569, generator_dur_loss=1.665, generator_adv_loss=1.905, generator_feat_match_loss=4.62, over 45.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.382, discriminator_fake_loss=1.344, generator_loss=27.65, generator_mel_loss=18.37, generator_kl_loss=1.406, generator_dur_loss=1.77, generator_adv_loss=1.927, generator_feat_match_loss=4.176, over 6804.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 06:17:45,278 INFO [train.py:919] (2/6) Start epoch 297
2024-03-13 06:20:16,539 INFO [train.py:527] (2/6) Epoch 297, batch 46, global_batch_idx: 36750, batch size: 58, loss[discriminator_loss=2.723, discriminator_real_loss=1.451, discriminator_fake_loss=1.273, generator_loss=27.25, generator_mel_loss=18.37, generator_kl_loss=1.349, generator_dur_loss=1.755, generator_adv_loss=1.902, generator_feat_match_loss=3.87, over 58.00 samples.], tot_loss[discriminator_loss=2.744, discriminator_real_loss=1.394, discriminator_fake_loss=1.35, generator_loss=27.45, generator_mel_loss=18.31, generator_kl_loss=1.362, generator_dur_loss=1.777, generator_adv_loss=1.927, generator_feat_match_loss=4.075, over 2816.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 06:22:36,396 INFO [train.py:527] (2/6) Epoch 297, batch 96, global_batch_idx: 36800, batch size: 56, loss[discriminator_loss=2.723, discriminator_real_loss=1.416, discriminator_fake_loss=1.307, generator_loss=27.35, generator_mel_loss=18.18, generator_kl_loss=1.474, generator_dur_loss=1.723, generator_adv_loss=2.015, generator_feat_match_loss=3.965, over 56.00 samples.], tot_loss[discriminator_loss=2.737, discriminator_real_loss=1.389, discriminator_fake_loss=1.348, generator_loss=27.54, generator_mel_loss=18.31, generator_kl_loss=1.38, generator_dur_loss=1.782, generator_adv_loss=1.945, generator_feat_match_loss=4.123, over 5671.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 06:22:36,397 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 06:22:45,239 INFO [train.py:591] (2/6) Epoch 297, validation: discriminator_loss=2.785, discriminator_real_loss=1.471, discriminator_fake_loss=1.315, generator_loss=26.04, generator_mel_loss=18.26, generator_kl_loss=1.083, generator_dur_loss=1.846, generator_adv_loss=1.844, generator_feat_match_loss=3.012, over 100.00 samples.
2024-03-13 06:22:45,240 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 06:24:00,826 INFO [train.py:919] (2/6) Start epoch 298
2024-03-13 06:25:24,677 INFO [train.py:527] (2/6) Epoch 298, batch 22, global_batch_idx: 36850, batch size: 56, loss[discriminator_loss=2.773, discriminator_real_loss=1.412, discriminator_fake_loss=1.361, generator_loss=27.22, generator_mel_loss=18.65, generator_kl_loss=1.533, generator_dur_loss=1.733, generator_adv_loss=1.882, generator_feat_match_loss=3.422, over 56.00 samples.], tot_loss[discriminator_loss=2.727, discriminator_real_loss=1.372, discriminator_fake_loss=1.354, generator_loss=27.63, generator_mel_loss=18.35, generator_kl_loss=1.411, generator_dur_loss=1.746, generator_adv_loss=1.942, generator_feat_match_loss=4.178, over 1222.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 06:27:44,427 INFO [train.py:527] (2/6) Epoch 298, batch 72, global_batch_idx: 36900, batch size: 62, loss[discriminator_loss=2.766, discriminator_real_loss=1.459, discriminator_fake_loss=1.307, generator_loss=27.56, generator_mel_loss=18.47, generator_kl_loss=1.342, generator_dur_loss=1.761, generator_adv_loss=1.822, generator_feat_match_loss=4.167, over 62.00 samples.], tot_loss[discriminator_loss=2.724, discriminator_real_loss=1.376, discriminator_fake_loss=1.348, generator_loss=27.67, generator_mel_loss=18.35, generator_kl_loss=1.396, generator_dur_loss=1.751, generator_adv_loss=1.936, generator_feat_match_loss=4.241, over 3908.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 06:30:01,624 INFO [train.py:527] (2/6) Epoch 298, batch 122, global_batch_idx: 36950, batch size: 42, loss[discriminator_loss=2.752, discriminator_real_loss=1.434, discriminator_fake_loss=1.318, generator_loss=27.5, generator_mel_loss=18.36, generator_kl_loss=1.555, generator_dur_loss=1.731, generator_adv_loss=1.917, generator_feat_match_loss=3.944, over 42.00 samples.], tot_loss[discriminator_loss=2.727, discriminator_real_loss=1.378, discriminator_fake_loss=1.349, generator_loss=27.64, generator_mel_loss=18.34, generator_kl_loss=1.395, generator_dur_loss=1.757, generator_adv_loss=1.934, generator_feat_match_loss=4.22, over 6583.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 06:30:07,336 INFO [train.py:919] (2/6) Start epoch 299
2024-03-13 06:32:45,622 INFO [train.py:527] (2/6) Epoch 299, batch 48, global_batch_idx: 37000, batch size: 88, loss[discriminator_loss=2.687, discriminator_real_loss=1.349, discriminator_fake_loss=1.338, generator_loss=27.66, generator_mel_loss=18.25, generator_kl_loss=1.331, generator_dur_loss=1.85, generator_adv_loss=1.879, generator_feat_match_loss=4.353, over 88.00 samples.], tot_loss[discriminator_loss=2.725, discriminator_real_loss=1.379, discriminator_fake_loss=1.346, generator_loss=27.56, generator_mel_loss=18.29, generator_kl_loss=1.4, generator_dur_loss=1.764, generator_adv_loss=1.923, generator_feat_match_loss=4.187, over 2814.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 06:32:45,624 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 06:32:53,800 INFO [train.py:591] (2/6) Epoch 299, validation: discriminator_loss=2.772, discriminator_real_loss=1.425, discriminator_fake_loss=1.347, generator_loss=26.89, generator_mel_loss=18.68, generator_kl_loss=1.164, generator_dur_loss=1.826, generator_adv_loss=1.825, generator_feat_match_loss=3.392, over 100.00 samples.
2024-03-13 06:32:53,801 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 06:35:15,131 INFO [train.py:527] (2/6) Epoch 299, batch 98, global_batch_idx: 37050, batch size: 36, loss[discriminator_loss=2.709, discriminator_real_loss=1.352, discriminator_fake_loss=1.357, generator_loss=29.14, generator_mel_loss=19.28, generator_kl_loss=1.471, generator_dur_loss=1.669, generator_adv_loss=1.809, generator_feat_match_loss=4.916, over 36.00 samples.], tot_loss[discriminator_loss=2.729, discriminator_real_loss=1.381, discriminator_fake_loss=1.348, generator_loss=27.53, generator_mel_loss=18.29, generator_kl_loss=1.395, generator_dur_loss=1.764, generator_adv_loss=1.917, generator_feat_match_loss=4.158, over 5714.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 06:36:23,886 INFO [train.py:919] (2/6) Start epoch 300
2024-03-13 06:37:53,657 INFO [train.py:527] (2/6) Epoch 300, batch 24, global_batch_idx: 37100, batch size: 77, loss[discriminator_loss=2.716, discriminator_real_loss=1.397, discriminator_fake_loss=1.319, generator_loss=27.37, generator_mel_loss=18.28, generator_kl_loss=1.218, generator_dur_loss=1.827, generator_adv_loss=1.96, generator_feat_match_loss=4.085, over 77.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.379, discriminator_fake_loss=1.337, generator_loss=27.8, generator_mel_loss=18.37, generator_kl_loss=1.394, generator_dur_loss=1.767, generator_adv_loss=1.997, generator_feat_match_loss=4.273, over 1468.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 06:40:10,445 INFO [train.py:527] (2/6) Epoch 300, batch 74, global_batch_idx: 37150, batch size: 72, loss[discriminator_loss=2.782, discriminator_real_loss=1.514, discriminator_fake_loss=1.269, generator_loss=27.4, generator_mel_loss=18.44, generator_kl_loss=1.425, generator_dur_loss=1.81, generator_adv_loss=1.707, generator_feat_match_loss=4.022, over 72.00 samples.], tot_loss[discriminator_loss=2.725, discriminator_real_loss=1.386, discriminator_fake_loss=1.34, generator_loss=27.55, generator_mel_loss=18.29, generator_kl_loss=1.39, generator_dur_loss=1.752, generator_adv_loss=1.95, generator_feat_match_loss=4.171, over 4231.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 06:42:27,979 INFO [train.py:919] (2/6) Start epoch 301
2024-03-13 06:42:51,390 INFO [train.py:527] (2/6) Epoch 301, batch 0, global_batch_idx: 37200, batch size: 52, loss[discriminator_loss=2.68, discriminator_real_loss=1.407, discriminator_fake_loss=1.273, generator_loss=27.58, generator_mel_loss=18.21, generator_kl_loss=1.311, generator_dur_loss=1.685, generator_adv_loss=2.055, generator_feat_match_loss=4.322, over 52.00 samples.], tot_loss[discriminator_loss=2.68, discriminator_real_loss=1.407, discriminator_fake_loss=1.273, generator_loss=27.58, generator_mel_loss=18.21, generator_kl_loss=1.311, generator_dur_loss=1.685, generator_adv_loss=2.055, generator_feat_match_loss=4.322, over 52.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 06:42:51,394 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 06:42:59,304 INFO [train.py:591] (2/6) Epoch 301, validation: discriminator_loss=2.769, discriminator_real_loss=1.55, discriminator_fake_loss=1.219, generator_loss=26.62, generator_mel_loss=18.4, generator_kl_loss=1.283, generator_dur_loss=1.834, generator_adv_loss=1.981, generator_feat_match_loss=3.116, over 100.00 samples.
2024-03-13 06:42:59,306 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 06:45:19,211 INFO [train.py:527] (2/6) Epoch 301, batch 50, global_batch_idx: 37250, batch size: 66, loss[discriminator_loss=2.763, discriminator_real_loss=1.421, discriminator_fake_loss=1.342, generator_loss=26.46, generator_mel_loss=17.83, generator_kl_loss=1.284, generator_dur_loss=1.749, generator_adv_loss=1.899, generator_feat_match_loss=3.698, over 66.00 samples.], tot_loss[discriminator_loss=2.728, discriminator_real_loss=1.383, discriminator_fake_loss=1.345, generator_loss=27.61, generator_mel_loss=18.29, generator_kl_loss=1.386, generator_dur_loss=1.78, generator_adv_loss=1.932, generator_feat_match_loss=4.225, over 2942.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 06:47:38,487 INFO [train.py:527] (2/6) Epoch 301, batch 100, global_batch_idx: 37300, batch size: 56, loss[discriminator_loss=2.737, discriminator_real_loss=1.347, discriminator_fake_loss=1.389, generator_loss=28.09, generator_mel_loss=18.29, generator_kl_loss=1.458, generator_dur_loss=1.751, generator_adv_loss=1.965, generator_feat_match_loss=4.619, over 56.00 samples.], tot_loss[discriminator_loss=2.73, discriminator_real_loss=1.385, discriminator_fake_loss=1.345, generator_loss=27.58, generator_mel_loss=18.28, generator_kl_loss=1.388, generator_dur_loss=1.769, generator_adv_loss=1.928, generator_feat_match_loss=4.214, over 5794.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 06:48:41,576 INFO [train.py:919] (2/6) Start epoch 302
2024-03-13 06:50:16,555 INFO [train.py:527] (2/6) Epoch 302, batch 26, global_batch_idx: 37350, batch size: 77, loss[discriminator_loss=2.725, discriminator_real_loss=1.419, discriminator_fake_loss=1.306, generator_loss=27, generator_mel_loss=17.96, generator_kl_loss=1.299, generator_dur_loss=1.816, generator_adv_loss=1.876, generator_feat_match_loss=4.046, over 77.00 samples.], tot_loss[discriminator_loss=2.728, discriminator_real_loss=1.382, discriminator_fake_loss=1.346, generator_loss=27.66, generator_mel_loss=18.3, generator_kl_loss=1.4, generator_dur_loss=1.758, generator_adv_loss=1.935, generator_feat_match_loss=4.265, over 1499.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 06:52:36,095 INFO [train.py:527] (2/6) Epoch 302, batch 76, global_batch_idx: 37400, batch size: 42, loss[discriminator_loss=2.715, discriminator_real_loss=1.398, discriminator_fake_loss=1.317, generator_loss=28.19, generator_mel_loss=18.61, generator_kl_loss=1.609, generator_dur_loss=1.667, generator_adv_loss=1.735, generator_feat_match_loss=4.562, over 42.00 samples.], tot_loss[discriminator_loss=2.736, discriminator_real_loss=1.385, discriminator_fake_loss=1.351, generator_loss=27.66, generator_mel_loss=18.32, generator_kl_loss=1.401, generator_dur_loss=1.769, generator_adv_loss=1.922, generator_feat_match_loss=4.25, over 4445.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 06:52:36,096 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 06:52:44,011 INFO [train.py:591] (2/6) Epoch 302, validation: discriminator_loss=2.744, discriminator_real_loss=1.354, discriminator_fake_loss=1.39, generator_loss=26.66, generator_mel_loss=18.47, generator_kl_loss=1.251, generator_dur_loss=1.85, generator_adv_loss=1.778, generator_feat_match_loss=3.304, over 100.00 samples.
2024-03-13 06:52:44,012 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 06:54:55,224 INFO [train.py:919] (2/6) Start epoch 303
2024-03-13 06:55:25,351 INFO [train.py:527] (2/6) Epoch 303, batch 2, global_batch_idx: 37450, batch size: 66, loss[discriminator_loss=3.076, discriminator_real_loss=1.244, discriminator_fake_loss=1.832, generator_loss=26.52, generator_mel_loss=17.79, generator_kl_loss=1.517, generator_dur_loss=1.8, generator_adv_loss=1.767, generator_feat_match_loss=3.65, over 66.00 samples.], tot_loss[discriminator_loss=2.94, discriminator_real_loss=1.432, discriminator_fake_loss=1.507, generator_loss=27.54, generator_mel_loss=18.19, generator_kl_loss=1.399, generator_dur_loss=1.834, generator_adv_loss=1.965, generator_feat_match_loss=4.152, over 226.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 06:57:42,812 INFO [train.py:527] (2/6) Epoch 303, batch 52, global_batch_idx: 37500, batch size: 31, loss[discriminator_loss=2.776, discriminator_real_loss=1.42, discriminator_fake_loss=1.356, generator_loss=27.5, generator_mel_loss=17.75, generator_kl_loss=1.694, generator_dur_loss=1.618, generator_adv_loss=2.209, generator_feat_match_loss=4.227, over 31.00 samples.], tot_loss[discriminator_loss=2.742, discriminator_real_loss=1.382, discriminator_fake_loss=1.36, generator_loss=27.46, generator_mel_loss=18.16, generator_kl_loss=1.406, generator_dur_loss=1.761, generator_adv_loss=1.93, generator_feat_match_loss=4.206, over 3114.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 07:00:01,208 INFO [train.py:527] (2/6) Epoch 303, batch 102, global_batch_idx: 37550, batch size: 55, loss[discriminator_loss=2.783, discriminator_real_loss=1.488, discriminator_fake_loss=1.296, generator_loss=26.66, generator_mel_loss=18.31, generator_kl_loss=1.308, generator_dur_loss=1.745, generator_adv_loss=1.813, generator_feat_match_loss=3.488, over 55.00 samples.], tot_loss[discriminator_loss=2.739, discriminator_real_loss=1.388, discriminator_fake_loss=1.352, generator_loss=27.53, generator_mel_loss=18.26, generator_kl_loss=1.405, generator_dur_loss=1.767, generator_adv_loss=1.945, generator_feat_match_loss=4.157, over 6039.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 07:01:00,855 INFO [train.py:919] (2/6) Start epoch 304
2024-03-13 07:02:43,421 INFO [train.py:527] (2/6) Epoch 304, batch 28, global_batch_idx: 37600, batch size: 70, loss[discriminator_loss=2.763, discriminator_real_loss=1.336, discriminator_fake_loss=1.426, generator_loss=27.63, generator_mel_loss=18.02, generator_kl_loss=1.42, generator_dur_loss=1.818, generator_adv_loss=2.167, generator_feat_match_loss=4.206, over 70.00 samples.], tot_loss[discriminator_loss=2.718, discriminator_real_loss=1.379, discriminator_fake_loss=1.339, generator_loss=27.57, generator_mel_loss=18.25, generator_kl_loss=1.37, generator_dur_loss=1.793, generator_adv_loss=1.947, generator_feat_match_loss=4.203, over 1758.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 07:02:43,423 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 07:02:51,457 INFO [train.py:591] (2/6) Epoch 304, validation: discriminator_loss=2.808, discriminator_real_loss=1.577, discriminator_fake_loss=1.231, generator_loss=27.06, generator_mel_loss=18.74, generator_kl_loss=1.14, generator_dur_loss=1.848, generator_adv_loss=2.087, generator_feat_match_loss=3.25, over 100.00 samples.
2024-03-13 07:02:51,458 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 07:05:09,879 INFO [train.py:527] (2/6) Epoch 304, batch 78, global_batch_idx: 37650, batch size: 50, loss[discriminator_loss=2.761, discriminator_real_loss=1.547, discriminator_fake_loss=1.214, generator_loss=26.81, generator_mel_loss=17.74, generator_kl_loss=1.49, generator_dur_loss=1.678, generator_adv_loss=1.884, generator_feat_match_loss=4.016, over 50.00 samples.], tot_loss[discriminator_loss=2.724, discriminator_real_loss=1.381, discriminator_fake_loss=1.343, generator_loss=27.63, generator_mel_loss=18.3, generator_kl_loss=1.392, generator_dur_loss=1.779, generator_adv_loss=1.924, generator_feat_match_loss=4.234, over 4644.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 07:07:12,012 INFO [train.py:919] (2/6) Start epoch 305
2024-03-13 07:07:47,463 INFO [train.py:527] (2/6) Epoch 305, batch 4, global_batch_idx: 37700, batch size: 70, loss[discriminator_loss=2.705, discriminator_real_loss=1.284, discriminator_fake_loss=1.422, generator_loss=28.01, generator_mel_loss=18.53, generator_kl_loss=1.424, generator_dur_loss=1.832, generator_adv_loss=1.85, generator_feat_match_loss=4.373, over 70.00 samples.], tot_loss[discriminator_loss=2.746, discriminator_real_loss=1.397, discriminator_fake_loss=1.349, generator_loss=27.36, generator_mel_loss=18.26, generator_kl_loss=1.392, generator_dur_loss=1.822, generator_adv_loss=1.896, generator_feat_match_loss=3.991, over 336.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 07:10:05,711 INFO [train.py:527] (2/6) Epoch 305, batch 54, global_batch_idx: 37750, batch size: 62, loss[discriminator_loss=2.776, discriminator_real_loss=1.492, discriminator_fake_loss=1.285, generator_loss=26.87, generator_mel_loss=18.4, generator_kl_loss=1.371, generator_dur_loss=1.795, generator_adv_loss=1.675, generator_feat_match_loss=3.627, over 62.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.378, discriminator_fake_loss=1.348, generator_loss=27.71, generator_mel_loss=18.32, generator_kl_loss=1.412, generator_dur_loss=1.787, generator_adv_loss=1.926, generator_feat_match_loss=4.267, over 3301.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 07:12:24,880 INFO [train.py:527] (2/6) Epoch 305, batch 104, global_batch_idx: 37800, batch size: 62, loss[discriminator_loss=2.777, discriminator_real_loss=1.415, discriminator_fake_loss=1.361, generator_loss=27.12, generator_mel_loss=18.21, generator_kl_loss=1.352, generator_dur_loss=1.711, generator_adv_loss=1.903, generator_feat_match_loss=3.946, over 62.00 samples.], tot_loss[discriminator_loss=2.73, discriminator_real_loss=1.382, discriminator_fake_loss=1.348, generator_loss=27.65, generator_mel_loss=18.32, generator_kl_loss=1.395, generator_dur_loss=1.788, generator_adv_loss=1.927, generator_feat_match_loss=4.215, over 6302.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 07:12:24,881 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 07:12:33,608 INFO [train.py:591] (2/6) Epoch 305, validation: discriminator_loss=2.747, discriminator_real_loss=1.47, discriminator_fake_loss=1.277, generator_loss=26.84, generator_mel_loss=18.33, generator_kl_loss=1.252, generator_dur_loss=1.839, generator_adv_loss=1.93, generator_feat_match_loss=3.486, over 100.00 samples.
2024-03-13 07:12:33,609 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 07:13:27,738 INFO [train.py:919] (2/6) Start epoch 306
2024-03-13 07:15:14,965 INFO [train.py:527] (2/6) Epoch 306, batch 30, global_batch_idx: 37850, batch size: 62, loss[discriminator_loss=2.739, discriminator_real_loss=1.28, discriminator_fake_loss=1.46, generator_loss=26.89, generator_mel_loss=17.91, generator_kl_loss=1.265, generator_dur_loss=1.801, generator_adv_loss=1.969, generator_feat_match_loss=3.951, over 62.00 samples.], tot_loss[discriminator_loss=2.74, discriminator_real_loss=1.393, discriminator_fake_loss=1.347, generator_loss=27.43, generator_mel_loss=18.22, generator_kl_loss=1.384, generator_dur_loss=1.781, generator_adv_loss=1.922, generator_feat_match_loss=4.123, over 1819.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 07:17:33,462 INFO [train.py:527] (2/6) Epoch 306, batch 80, global_batch_idx: 37900, batch size: 59, loss[discriminator_loss=2.764, discriminator_real_loss=1.357, discriminator_fake_loss=1.408, generator_loss=27.46, generator_mel_loss=18.01, generator_kl_loss=1.344, generator_dur_loss=1.77, generator_adv_loss=1.97, generator_feat_match_loss=4.368, over 59.00 samples.], tot_loss[discriminator_loss=2.733, discriminator_real_loss=1.39, discriminator_fake_loss=1.342, generator_loss=27.54, generator_mel_loss=18.24, generator_kl_loss=1.387, generator_dur_loss=1.773, generator_adv_loss=1.964, generator_feat_match_loss=4.174, over 4578.00 samples.], cur_lr_g: 1.93e-04, cur_lr_d: 1.93e-04, 
2024-03-13 07:19:33,424 INFO [train.py:919] (2/6) Start epoch 307
2024-03-13 07:20:14,595 INFO [train.py:527] (2/6) Epoch 307, batch 6, global_batch_idx: 37950, batch size: 45, loss[discriminator_loss=2.802, discriminator_real_loss=1.408, discriminator_fake_loss=1.393, generator_loss=27.19, generator_mel_loss=17.96, generator_kl_loss=1.49, generator_dur_loss=1.71, generator_adv_loss=1.925, generator_feat_match_loss=4.11, over 45.00 samples.], tot_loss[discriminator_loss=2.77, discriminator_real_loss=1.408, discriminator_fake_loss=1.363, generator_loss=27.62, generator_mel_loss=18.46, generator_kl_loss=1.4, generator_dur_loss=1.809, generator_adv_loss=1.875, generator_feat_match_loss=4.083, over 480.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 07:22:34,418 INFO [train.py:527] (2/6) Epoch 307, batch 56, global_batch_idx: 38000, batch size: 58, loss[discriminator_loss=2.74, discriminator_real_loss=1.418, discriminator_fake_loss=1.323, generator_loss=25.6, generator_mel_loss=17.54, generator_kl_loss=1.304, generator_dur_loss=1.792, generator_adv_loss=1.771, generator_feat_match_loss=3.197, over 58.00 samples.], tot_loss[discriminator_loss=2.731, discriminator_real_loss=1.388, discriminator_fake_loss=1.343, generator_loss=27.47, generator_mel_loss=18.26, generator_kl_loss=1.368, generator_dur_loss=1.793, generator_adv_loss=1.924, generator_feat_match_loss=4.125, over 3339.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 07:22:34,420 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 07:22:42,560 INFO [train.py:591] (2/6) Epoch 307, validation: discriminator_loss=2.697, discriminator_real_loss=1.295, discriminator_fake_loss=1.402, generator_loss=26.5, generator_mel_loss=18.36, generator_kl_loss=1.187, generator_dur_loss=1.84, generator_adv_loss=1.76, generator_feat_match_loss=3.359, over 100.00 samples.
2024-03-13 07:22:42,561 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 07:25:00,916 INFO [train.py:527] (2/6) Epoch 307, batch 106, global_batch_idx: 38050, batch size: 48, loss[discriminator_loss=2.723, discriminator_real_loss=1.281, discriminator_fake_loss=1.442, generator_loss=27.59, generator_mel_loss=18.11, generator_kl_loss=1.412, generator_dur_loss=1.706, generator_adv_loss=2, generator_feat_match_loss=4.367, over 48.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.382, discriminator_fake_loss=1.344, generator_loss=27.57, generator_mel_loss=18.26, generator_kl_loss=1.385, generator_dur_loss=1.782, generator_adv_loss=1.93, generator_feat_match_loss=4.221, over 6144.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 07:25:48,071 INFO [train.py:919] (2/6) Start epoch 308
2024-03-13 07:27:39,177 INFO [train.py:527] (2/6) Epoch 308, batch 32, global_batch_idx: 38100, batch size: 25, loss[discriminator_loss=2.696, discriminator_real_loss=1.376, discriminator_fake_loss=1.32, generator_loss=29.22, generator_mel_loss=18.98, generator_kl_loss=1.729, generator_dur_loss=1.548, generator_adv_loss=1.85, generator_feat_match_loss=5.11, over 25.00 samples.], tot_loss[discriminator_loss=2.739, discriminator_real_loss=1.389, discriminator_fake_loss=1.35, generator_loss=27.79, generator_mel_loss=18.35, generator_kl_loss=1.419, generator_dur_loss=1.745, generator_adv_loss=1.927, generator_feat_match_loss=4.355, over 1845.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 07:29:59,270 INFO [train.py:527] (2/6) Epoch 308, batch 82, global_batch_idx: 38150, batch size: 61, loss[discriminator_loss=2.702, discriminator_real_loss=1.354, discriminator_fake_loss=1.348, generator_loss=29.16, generator_mel_loss=19.25, generator_kl_loss=1.45, generator_dur_loss=1.767, generator_adv_loss=1.955, generator_feat_match_loss=4.743, over 61.00 samples.], tot_loss[discriminator_loss=2.727, discriminator_real_loss=1.375, discriminator_fake_loss=1.352, generator_loss=27.71, generator_mel_loss=18.33, generator_kl_loss=1.386, generator_dur_loss=1.767, generator_adv_loss=1.925, generator_feat_match_loss=4.303, over 4764.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 07:31:53,241 INFO [train.py:919] (2/6) Start epoch 309
2024-03-13 07:32:39,919 INFO [train.py:527] (2/6) Epoch 309, batch 8, global_batch_idx: 38200, batch size: 66, loss[discriminator_loss=2.74, discriminator_real_loss=1.4, discriminator_fake_loss=1.339, generator_loss=27.97, generator_mel_loss=18.3, generator_kl_loss=1.545, generator_dur_loss=1.756, generator_adv_loss=2.035, generator_feat_match_loss=4.341, over 66.00 samples.], tot_loss[discriminator_loss=2.739, discriminator_real_loss=1.369, discriminator_fake_loss=1.369, generator_loss=27.55, generator_mel_loss=18.17, generator_kl_loss=1.385, generator_dur_loss=1.816, generator_adv_loss=1.943, generator_feat_match_loss=4.243, over 647.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 07:32:39,922 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 07:32:47,771 INFO [train.py:591] (2/6) Epoch 309, validation: discriminator_loss=2.804, discriminator_real_loss=1.554, discriminator_fake_loss=1.251, generator_loss=26.52, generator_mel_loss=18.44, generator_kl_loss=1.251, generator_dur_loss=1.822, generator_adv_loss=1.96, generator_feat_match_loss=3.042, over 100.00 samples.
2024-03-13 07:32:47,773 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 07:35:05,266 INFO [train.py:527] (2/6) Epoch 309, batch 58, global_batch_idx: 38250, batch size: 61, loss[discriminator_loss=2.698, discriminator_real_loss=1.414, discriminator_fake_loss=1.284, generator_loss=27.45, generator_mel_loss=18.45, generator_kl_loss=1.267, generator_dur_loss=1.734, generator_adv_loss=1.934, generator_feat_match_loss=4.066, over 61.00 samples.], tot_loss[discriminator_loss=2.731, discriminator_real_loss=1.38, discriminator_fake_loss=1.351, generator_loss=27.65, generator_mel_loss=18.31, generator_kl_loss=1.412, generator_dur_loss=1.772, generator_adv_loss=1.96, generator_feat_match_loss=4.201, over 3455.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 07:37:22,825 INFO [train.py:527] (2/6) Epoch 309, batch 108, global_batch_idx: 38300, batch size: 83, loss[discriminator_loss=2.661, discriminator_real_loss=1.259, discriminator_fake_loss=1.402, generator_loss=28.22, generator_mel_loss=18.43, generator_kl_loss=1.247, generator_dur_loss=1.865, generator_adv_loss=1.994, generator_feat_match_loss=4.677, over 83.00 samples.], tot_loss[discriminator_loss=2.727, discriminator_real_loss=1.382, discriminator_fake_loss=1.345, generator_loss=27.63, generator_mel_loss=18.3, generator_kl_loss=1.409, generator_dur_loss=1.768, generator_adv_loss=1.95, generator_feat_match_loss=4.202, over 6336.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 07:38:08,150 INFO [train.py:919] (2/6) Start epoch 310
2024-03-13 07:40:05,833 INFO [train.py:527] (2/6) Epoch 310, batch 34, global_batch_idx: 38350, batch size: 45, loss[discriminator_loss=2.753, discriminator_real_loss=1.324, discriminator_fake_loss=1.429, generator_loss=26.84, generator_mel_loss=17.87, generator_kl_loss=1.44, generator_dur_loss=1.701, generator_adv_loss=2.103, generator_feat_match_loss=3.726, over 45.00 samples.], tot_loss[discriminator_loss=2.725, discriminator_real_loss=1.383, discriminator_fake_loss=1.342, generator_loss=27.73, generator_mel_loss=18.35, generator_kl_loss=1.364, generator_dur_loss=1.786, generator_adv_loss=1.937, generator_feat_match_loss=4.292, over 2021.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 07:42:24,882 INFO [train.py:527] (2/6) Epoch 310, batch 84, global_batch_idx: 38400, batch size: 56, loss[discriminator_loss=2.69, discriminator_real_loss=1.336, discriminator_fake_loss=1.353, generator_loss=27.84, generator_mel_loss=18.31, generator_kl_loss=1.454, generator_dur_loss=1.708, generator_adv_loss=1.936, generator_feat_match_loss=4.435, over 56.00 samples.], tot_loss[discriminator_loss=2.727, discriminator_real_loss=1.381, discriminator_fake_loss=1.345, generator_loss=27.64, generator_mel_loss=18.34, generator_kl_loss=1.381, generator_dur_loss=1.779, generator_adv_loss=1.93, generator_feat_match_loss=4.209, over 4923.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 07:42:24,883 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 07:42:33,709 INFO [train.py:591] (2/6) Epoch 310, validation: discriminator_loss=2.728, discriminator_real_loss=1.448, discriminator_fake_loss=1.28, generator_loss=26.99, generator_mel_loss=18.42, generator_kl_loss=1.213, generator_dur_loss=1.819, generator_adv_loss=1.958, generator_feat_match_loss=3.579, over 100.00 samples.
2024-03-13 07:42:33,710 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 07:44:23,336 INFO [train.py:919] (2/6) Start epoch 311
2024-03-13 07:45:16,126 INFO [train.py:527] (2/6) Epoch 311, batch 10, global_batch_idx: 38450, batch size: 80, loss[discriminator_loss=2.75, discriminator_real_loss=1.49, discriminator_fake_loss=1.26, generator_loss=26.69, generator_mel_loss=17.76, generator_kl_loss=1.364, generator_dur_loss=1.834, generator_adv_loss=1.923, generator_feat_match_loss=3.802, over 80.00 samples.], tot_loss[discriminator_loss=2.756, discriminator_real_loss=1.396, discriminator_fake_loss=1.36, generator_loss=27.13, generator_mel_loss=18.13, generator_kl_loss=1.353, generator_dur_loss=1.756, generator_adv_loss=1.924, generator_feat_match_loss=3.975, over 598.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 07:47:35,335 INFO [train.py:527] (2/6) Epoch 311, batch 60, global_batch_idx: 38500, batch size: 77, loss[discriminator_loss=2.641, discriminator_real_loss=1.373, discriminator_fake_loss=1.269, generator_loss=28.08, generator_mel_loss=18.29, generator_kl_loss=1.315, generator_dur_loss=1.807, generator_adv_loss=1.909, generator_feat_match_loss=4.759, over 77.00 samples.], tot_loss[discriminator_loss=2.732, discriminator_real_loss=1.382, discriminator_fake_loss=1.35, generator_loss=27.47, generator_mel_loss=18.24, generator_kl_loss=1.392, generator_dur_loss=1.761, generator_adv_loss=1.925, generator_feat_match_loss=4.154, over 3532.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 07:49:52,811 INFO [train.py:527] (2/6) Epoch 311, batch 110, global_batch_idx: 38550, batch size: 83, loss[discriminator_loss=2.755, discriminator_real_loss=1.43, discriminator_fake_loss=1.325, generator_loss=26.75, generator_mel_loss=17.97, generator_kl_loss=1.343, generator_dur_loss=1.878, generator_adv_loss=1.849, generator_feat_match_loss=3.703, over 83.00 samples.], tot_loss[discriminator_loss=2.731, discriminator_real_loss=1.385, discriminator_fake_loss=1.346, generator_loss=27.54, generator_mel_loss=18.27, generator_kl_loss=1.402, generator_dur_loss=1.762, generator_adv_loss=1.924, generator_feat_match_loss=4.176, over 6339.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 07:50:29,212 INFO [train.py:919] (2/6) Start epoch 312
2024-03-13 07:52:36,919 INFO [train.py:527] (2/6) Epoch 312, batch 36, global_batch_idx: 38600, batch size: 80, loss[discriminator_loss=2.832, discriminator_real_loss=1.331, discriminator_fake_loss=1.501, generator_loss=27.45, generator_mel_loss=18.23, generator_kl_loss=1.428, generator_dur_loss=1.855, generator_adv_loss=1.959, generator_feat_match_loss=3.985, over 80.00 samples.], tot_loss[discriminator_loss=2.743, discriminator_real_loss=1.379, discriminator_fake_loss=1.364, generator_loss=27.57, generator_mel_loss=18.34, generator_kl_loss=1.426, generator_dur_loss=1.755, generator_adv_loss=1.904, generator_feat_match_loss=4.146, over 2083.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 07:52:36,921 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 07:52:44,818 INFO [train.py:591] (2/6) Epoch 312, validation: discriminator_loss=2.855, discriminator_real_loss=1.551, discriminator_fake_loss=1.303, generator_loss=26.99, generator_mel_loss=18.56, generator_kl_loss=1.204, generator_dur_loss=1.823, generator_adv_loss=1.996, generator_feat_match_loss=3.411, over 100.00 samples.
2024-03-13 07:52:44,819 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 07:55:03,801 INFO [train.py:527] (2/6) Epoch 312, batch 86, global_batch_idx: 38650, batch size: 88, loss[discriminator_loss=2.704, discriminator_real_loss=1.321, discriminator_fake_loss=1.383, generator_loss=27.19, generator_mel_loss=18.12, generator_kl_loss=1.367, generator_dur_loss=1.866, generator_adv_loss=1.926, generator_feat_match_loss=3.917, over 88.00 samples.], tot_loss[discriminator_loss=2.734, discriminator_real_loss=1.378, discriminator_fake_loss=1.356, generator_loss=27.6, generator_mel_loss=18.33, generator_kl_loss=1.402, generator_dur_loss=1.764, generator_adv_loss=1.907, generator_feat_match_loss=4.194, over 4992.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 07:56:43,576 INFO [train.py:919] (2/6) Start epoch 313
2024-03-13 07:57:41,563 INFO [train.py:527] (2/6) Epoch 313, batch 12, global_batch_idx: 38700, batch size: 96, loss[discriminator_loss=2.739, discriminator_real_loss=1.345, discriminator_fake_loss=1.395, generator_loss=26.05, generator_mel_loss=17.65, generator_kl_loss=1.147, generator_dur_loss=1.899, generator_adv_loss=2.032, generator_feat_match_loss=3.327, over 96.00 samples.], tot_loss[discriminator_loss=2.751, discriminator_real_loss=1.392, discriminator_fake_loss=1.359, generator_loss=27.72, generator_mel_loss=18.5, generator_kl_loss=1.418, generator_dur_loss=1.745, generator_adv_loss=1.941, generator_feat_match_loss=4.123, over 693.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 08:00:02,065 INFO [train.py:527] (2/6) Epoch 313, batch 62, global_batch_idx: 38750, batch size: 68, loss[discriminator_loss=2.701, discriminator_real_loss=1.298, discriminator_fake_loss=1.403, generator_loss=27.9, generator_mel_loss=18.45, generator_kl_loss=1.34, generator_dur_loss=1.81, generator_adv_loss=1.952, generator_feat_match_loss=4.338, over 68.00 samples.], tot_loss[discriminator_loss=2.729, discriminator_real_loss=1.379, discriminator_fake_loss=1.35, generator_loss=27.63, generator_mel_loss=18.33, generator_kl_loss=1.385, generator_dur_loss=1.756, generator_adv_loss=1.932, generator_feat_match_loss=4.23, over 3532.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 08:02:21,414 INFO [train.py:527] (2/6) Epoch 313, batch 112, global_batch_idx: 38800, batch size: 83, loss[discriminator_loss=2.715, discriminator_real_loss=1.325, discriminator_fake_loss=1.39, generator_loss=27.54, generator_mel_loss=18.22, generator_kl_loss=1.255, generator_dur_loss=1.838, generator_adv_loss=1.871, generator_feat_match_loss=4.355, over 83.00 samples.], tot_loss[discriminator_loss=2.724, discriminator_real_loss=1.376, discriminator_fake_loss=1.348, generator_loss=27.67, generator_mel_loss=18.32, generator_kl_loss=1.396, generator_dur_loss=1.767, generator_adv_loss=1.93, generator_feat_match_loss=4.261, over 6405.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 08:02:21,416 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 08:02:30,294 INFO [train.py:591] (2/6) Epoch 313, validation: discriminator_loss=2.775, discriminator_real_loss=1.461, discriminator_fake_loss=1.314, generator_loss=26.44, generator_mel_loss=18.39, generator_kl_loss=1.12, generator_dur_loss=1.834, generator_adv_loss=1.867, generator_feat_match_loss=3.229, over 100.00 samples.
2024-03-13 08:02:30,294 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 08:03:00,411 INFO [train.py:919] (2/6) Start epoch 314
2024-03-13 08:05:10,063 INFO [train.py:527] (2/6) Epoch 314, batch 38, global_batch_idx: 38850, batch size: 53, loss[discriminator_loss=2.786, discriminator_real_loss=1.296, discriminator_fake_loss=1.49, generator_loss=27.5, generator_mel_loss=18.32, generator_kl_loss=1.512, generator_dur_loss=1.758, generator_adv_loss=2.027, generator_feat_match_loss=3.882, over 53.00 samples.], tot_loss[discriminator_loss=2.733, discriminator_real_loss=1.372, discriminator_fake_loss=1.361, generator_loss=27.42, generator_mel_loss=18.18, generator_kl_loss=1.387, generator_dur_loss=1.774, generator_adv_loss=1.915, generator_feat_match_loss=4.17, over 2337.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 08:07:30,809 INFO [train.py:527] (2/6) Epoch 314, batch 88, global_batch_idx: 38900, batch size: 47, loss[discriminator_loss=2.664, discriminator_real_loss=1.244, discriminator_fake_loss=1.42, generator_loss=29.12, generator_mel_loss=19.44, generator_kl_loss=1.552, generator_dur_loss=1.649, generator_adv_loss=1.841, generator_feat_match_loss=4.637, over 47.00 samples.], tot_loss[discriminator_loss=2.733, discriminator_real_loss=1.377, discriminator_fake_loss=1.356, generator_loss=27.44, generator_mel_loss=18.2, generator_kl_loss=1.387, generator_dur_loss=1.768, generator_adv_loss=1.909, generator_feat_match_loss=4.178, over 5319.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 08:09:07,978 INFO [train.py:919] (2/6) Start epoch 315
2024-03-13 08:10:09,783 INFO [train.py:527] (2/6) Epoch 315, batch 14, global_batch_idx: 38950, batch size: 58, loss[discriminator_loss=2.735, discriminator_real_loss=1.387, discriminator_fake_loss=1.348, generator_loss=27.4, generator_mel_loss=18.09, generator_kl_loss=1.411, generator_dur_loss=1.753, generator_adv_loss=1.934, generator_feat_match_loss=4.211, over 58.00 samples.], tot_loss[discriminator_loss=2.732, discriminator_real_loss=1.381, discriminator_fake_loss=1.351, generator_loss=27.77, generator_mel_loss=18.41, generator_kl_loss=1.419, generator_dur_loss=1.768, generator_adv_loss=1.902, generator_feat_match_loss=4.276, over 831.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 08:12:31,527 INFO [train.py:527] (2/6) Epoch 315, batch 64, global_batch_idx: 39000, batch size: 39, loss[discriminator_loss=2.697, discriminator_real_loss=1.354, discriminator_fake_loss=1.343, generator_loss=28.42, generator_mel_loss=18.38, generator_kl_loss=1.538, generator_dur_loss=1.753, generator_adv_loss=1.849, generator_feat_match_loss=4.897, over 39.00 samples.], tot_loss[discriminator_loss=2.729, discriminator_real_loss=1.385, discriminator_fake_loss=1.344, generator_loss=27.66, generator_mel_loss=18.29, generator_kl_loss=1.378, generator_dur_loss=1.774, generator_adv_loss=1.947, generator_feat_match_loss=4.272, over 3763.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 08:12:31,529 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 08:12:39,669 INFO [train.py:591] (2/6) Epoch 315, validation: discriminator_loss=2.758, discriminator_real_loss=1.362, discriminator_fake_loss=1.396, generator_loss=25.86, generator_mel_loss=17.96, generator_kl_loss=1.163, generator_dur_loss=1.846, generator_adv_loss=1.792, generator_feat_match_loss=3.098, over 100.00 samples.
2024-03-13 08:12:39,670 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 08:14:57,139 INFO [train.py:527] (2/6) Epoch 315, batch 114, global_batch_idx: 39050, batch size: 96, loss[discriminator_loss=2.747, discriminator_real_loss=1.376, discriminator_fake_loss=1.372, generator_loss=27.14, generator_mel_loss=17.81, generator_kl_loss=1.304, generator_dur_loss=1.862, generator_adv_loss=2.036, generator_feat_match_loss=4.128, over 96.00 samples.], tot_loss[discriminator_loss=2.731, discriminator_real_loss=1.385, discriminator_fake_loss=1.346, generator_loss=27.56, generator_mel_loss=18.24, generator_kl_loss=1.374, generator_dur_loss=1.785, generator_adv_loss=1.938, generator_feat_match_loss=4.226, over 6853.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 08:15:23,883 INFO [train.py:919] (2/6) Start epoch 316
2024-03-13 08:17:41,140 INFO [train.py:527] (2/6) Epoch 316, batch 40, global_batch_idx: 39100, batch size: 49, loss[discriminator_loss=2.649, discriminator_real_loss=1.37, discriminator_fake_loss=1.279, generator_loss=28.34, generator_mel_loss=18.25, generator_kl_loss=1.507, generator_dur_loss=1.675, generator_adv_loss=1.916, generator_feat_match_loss=4.994, over 49.00 samples.], tot_loss[discriminator_loss=2.727, discriminator_real_loss=1.38, discriminator_fake_loss=1.347, generator_loss=27.78, generator_mel_loss=18.37, generator_kl_loss=1.403, generator_dur_loss=1.776, generator_adv_loss=1.923, generator_feat_match_loss=4.313, over 2363.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 08:19:58,117 INFO [train.py:527] (2/6) Epoch 316, batch 90, global_batch_idx: 39150, batch size: 96, loss[discriminator_loss=2.736, discriminator_real_loss=1.39, discriminator_fake_loss=1.347, generator_loss=27.09, generator_mel_loss=18.01, generator_kl_loss=1.206, generator_dur_loss=1.789, generator_adv_loss=1.889, generator_feat_match_loss=4.196, over 96.00 samples.], tot_loss[discriminator_loss=2.723, discriminator_real_loss=1.38, discriminator_fake_loss=1.343, generator_loss=27.7, generator_mel_loss=18.31, generator_kl_loss=1.403, generator_dur_loss=1.763, generator_adv_loss=1.926, generator_feat_match_loss=4.293, over 5076.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 08:21:30,077 INFO [train.py:919] (2/6) Start epoch 317
2024-03-13 08:22:39,683 INFO [train.py:527] (2/6) Epoch 317, batch 16, global_batch_idx: 39200, batch size: 70, loss[discriminator_loss=2.726, discriminator_real_loss=1.447, discriminator_fake_loss=1.279, generator_loss=28.36, generator_mel_loss=18.53, generator_kl_loss=1.459, generator_dur_loss=1.781, generator_adv_loss=1.854, generator_feat_match_loss=4.734, over 70.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.382, discriminator_fake_loss=1.338, generator_loss=27.95, generator_mel_loss=18.46, generator_kl_loss=1.385, generator_dur_loss=1.763, generator_adv_loss=1.968, generator_feat_match_loss=4.375, over 1052.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 08:22:39,684 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 08:22:47,860 INFO [train.py:591] (2/6) Epoch 317, validation: discriminator_loss=2.8, discriminator_real_loss=1.399, discriminator_fake_loss=1.401, generator_loss=25.76, generator_mel_loss=18.18, generator_kl_loss=1.179, generator_dur_loss=1.814, generator_adv_loss=1.727, generator_feat_match_loss=2.859, over 100.00 samples.
2024-03-13 08:22:47,862 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 08:25:08,314 INFO [train.py:527] (2/6) Epoch 317, batch 66, global_batch_idx: 39250, batch size: 64, loss[discriminator_loss=2.737, discriminator_real_loss=1.418, discriminator_fake_loss=1.319, generator_loss=27.3, generator_mel_loss=18.25, generator_kl_loss=1.415, generator_dur_loss=1.768, generator_adv_loss=1.744, generator_feat_match_loss=4.122, over 64.00 samples.], tot_loss[discriminator_loss=2.735, discriminator_real_loss=1.391, discriminator_fake_loss=1.344, generator_loss=27.63, generator_mel_loss=18.29, generator_kl_loss=1.388, generator_dur_loss=1.759, generator_adv_loss=1.943, generator_feat_match_loss=4.249, over 3971.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 08:27:27,168 INFO [train.py:527] (2/6) Epoch 317, batch 116, global_batch_idx: 39300, batch size: 58, loss[discriminator_loss=2.713, discriminator_real_loss=1.342, discriminator_fake_loss=1.371, generator_loss=27.58, generator_mel_loss=17.9, generator_kl_loss=1.443, generator_dur_loss=1.749, generator_adv_loss=2.015, generator_feat_match_loss=4.479, over 58.00 samples.], tot_loss[discriminator_loss=2.733, discriminator_real_loss=1.386, discriminator_fake_loss=1.346, generator_loss=27.61, generator_mel_loss=18.28, generator_kl_loss=1.388, generator_dur_loss=1.765, generator_adv_loss=1.935, generator_feat_match_loss=4.239, over 6874.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 08:27:47,760 INFO [train.py:919] (2/6) Start epoch 318
2024-03-13 08:30:05,595 INFO [train.py:527] (2/6) Epoch 318, batch 42, global_batch_idx: 39350, batch size: 88, loss[discriminator_loss=2.69, discriminator_real_loss=1.359, discriminator_fake_loss=1.331, generator_loss=28.2, generator_mel_loss=18.33, generator_kl_loss=1.476, generator_dur_loss=1.876, generator_adv_loss=2.157, generator_feat_match_loss=4.356, over 88.00 samples.], tot_loss[discriminator_loss=2.723, discriminator_real_loss=1.383, discriminator_fake_loss=1.34, generator_loss=27.75, generator_mel_loss=18.3, generator_kl_loss=1.428, generator_dur_loss=1.761, generator_adv_loss=1.985, generator_feat_match_loss=4.275, over 2432.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 08:32:24,897 INFO [train.py:527] (2/6) Epoch 318, batch 92, global_batch_idx: 39400, batch size: 55, loss[discriminator_loss=2.761, discriminator_real_loss=1.455, discriminator_fake_loss=1.306, generator_loss=27.01, generator_mel_loss=18.41, generator_kl_loss=1.423, generator_dur_loss=1.73, generator_adv_loss=1.969, generator_feat_match_loss=3.481, over 55.00 samples.], tot_loss[discriminator_loss=2.727, discriminator_real_loss=1.381, discriminator_fake_loss=1.346, generator_loss=27.66, generator_mel_loss=18.26, generator_kl_loss=1.419, generator_dur_loss=1.766, generator_adv_loss=1.953, generator_feat_match_loss=4.26, over 5497.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 08:32:24,898 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 08:32:33,728 INFO [train.py:591] (2/6) Epoch 318, validation: discriminator_loss=2.765, discriminator_real_loss=1.53, discriminator_fake_loss=1.235, generator_loss=27.36, generator_mel_loss=18.41, generator_kl_loss=1.17, generator_dur_loss=1.838, generator_adv_loss=2.086, generator_feat_match_loss=3.85, over 100.00 samples.
2024-03-13 08:32:33,729 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 08:34:00,814 INFO [train.py:919] (2/6) Start epoch 319
2024-03-13 08:35:17,683 INFO [train.py:527] (2/6) Epoch 319, batch 18, global_batch_idx: 39450, batch size: 25, loss[discriminator_loss=2.661, discriminator_real_loss=1.235, discriminator_fake_loss=1.426, generator_loss=30.12, generator_mel_loss=19.55, generator_kl_loss=1.92, generator_dur_loss=1.591, generator_adv_loss=1.936, generator_feat_match_loss=5.114, over 25.00 samples.], tot_loss[discriminator_loss=2.734, discriminator_real_loss=1.388, discriminator_fake_loss=1.346, generator_loss=27.7, generator_mel_loss=18.33, generator_kl_loss=1.401, generator_dur_loss=1.78, generator_adv_loss=1.926, generator_feat_match_loss=4.266, over 1143.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 08:37:36,122 INFO [train.py:527] (2/6) Epoch 319, batch 68, global_batch_idx: 39500, batch size: 55, loss[discriminator_loss=2.731, discriminator_real_loss=1.382, discriminator_fake_loss=1.348, generator_loss=27.96, generator_mel_loss=18.68, generator_kl_loss=1.366, generator_dur_loss=1.698, generator_adv_loss=1.898, generator_feat_match_loss=4.323, over 55.00 samples.], tot_loss[discriminator_loss=2.733, discriminator_real_loss=1.385, discriminator_fake_loss=1.348, generator_loss=27.64, generator_mel_loss=18.28, generator_kl_loss=1.421, generator_dur_loss=1.766, generator_adv_loss=1.932, generator_feat_match_loss=4.243, over 3731.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 08:39:52,988 INFO [train.py:527] (2/6) Epoch 319, batch 118, global_batch_idx: 39550, batch size: 56, loss[discriminator_loss=2.733, discriminator_real_loss=1.287, discriminator_fake_loss=1.446, generator_loss=28.91, generator_mel_loss=18.47, generator_kl_loss=1.426, generator_dur_loss=1.715, generator_adv_loss=2.359, generator_feat_match_loss=4.937, over 56.00 samples.], tot_loss[discriminator_loss=2.73, discriminator_real_loss=1.384, discriminator_fake_loss=1.347, generator_loss=27.68, generator_mel_loss=18.31, generator_kl_loss=1.411, generator_dur_loss=1.77, generator_adv_loss=1.944, generator_feat_match_loss=4.249, over 6547.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 08:40:09,226 INFO [train.py:919] (2/6) Start epoch 320
2024-03-13 08:42:30,550 INFO [train.py:527] (2/6) Epoch 320, batch 44, global_batch_idx: 39600, batch size: 83, loss[discriminator_loss=2.778, discriminator_real_loss=1.368, discriminator_fake_loss=1.41, generator_loss=27.19, generator_mel_loss=18.01, generator_kl_loss=1.338, generator_dur_loss=1.872, generator_adv_loss=1.955, generator_feat_match_loss=4.013, over 83.00 samples.], tot_loss[discriminator_loss=2.723, discriminator_real_loss=1.364, discriminator_fake_loss=1.359, generator_loss=27.57, generator_mel_loss=18.22, generator_kl_loss=1.425, generator_dur_loss=1.766, generator_adv_loss=1.92, generator_feat_match_loss=4.242, over 2613.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 08:42:30,552 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 08:42:38,339 INFO [train.py:591] (2/6) Epoch 320, validation: discriminator_loss=2.767, discriminator_real_loss=1.523, discriminator_fake_loss=1.243, generator_loss=26.73, generator_mel_loss=18.11, generator_kl_loss=1.136, generator_dur_loss=1.827, generator_adv_loss=1.956, generator_feat_match_loss=3.705, over 100.00 samples.
2024-03-13 08:42:38,340 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 08:44:58,567 INFO [train.py:527] (2/6) Epoch 320, batch 94, global_batch_idx: 39650, batch size: 68, loss[discriminator_loss=2.631, discriminator_real_loss=1.337, discriminator_fake_loss=1.293, generator_loss=28.44, generator_mel_loss=18.13, generator_kl_loss=1.437, generator_dur_loss=1.77, generator_adv_loss=2.145, generator_feat_match_loss=4.961, over 68.00 samples.], tot_loss[discriminator_loss=2.725, discriminator_real_loss=1.37, discriminator_fake_loss=1.355, generator_loss=27.58, generator_mel_loss=18.19, generator_kl_loss=1.414, generator_dur_loss=1.78, generator_adv_loss=1.93, generator_feat_match_loss=4.26, over 5745.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 08:46:19,921 INFO [train.py:919] (2/6) Start epoch 321
2024-03-13 08:47:37,924 INFO [train.py:527] (2/6) Epoch 321, batch 20, global_batch_idx: 39700, batch size: 96, loss[discriminator_loss=2.719, discriminator_real_loss=1.372, discriminator_fake_loss=1.347, generator_loss=26.46, generator_mel_loss=17.65, generator_kl_loss=1.346, generator_dur_loss=1.855, generator_adv_loss=1.8, generator_feat_match_loss=3.809, over 96.00 samples.], tot_loss[discriminator_loss=2.728, discriminator_real_loss=1.375, discriminator_fake_loss=1.353, generator_loss=27.54, generator_mel_loss=18.28, generator_kl_loss=1.398, generator_dur_loss=1.764, generator_adv_loss=1.907, generator_feat_match_loss=4.184, over 1248.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 08:49:55,682 INFO [train.py:527] (2/6) Epoch 321, batch 70, global_batch_idx: 39750, batch size: 31, loss[discriminator_loss=2.68, discriminator_real_loss=1.265, discriminator_fake_loss=1.415, generator_loss=29.11, generator_mel_loss=18.61, generator_kl_loss=1.695, generator_dur_loss=1.556, generator_adv_loss=1.911, generator_feat_match_loss=5.339, over 31.00 samples.], tot_loss[discriminator_loss=2.729, discriminator_real_loss=1.379, discriminator_fake_loss=1.35, generator_loss=27.71, generator_mel_loss=18.32, generator_kl_loss=1.41, generator_dur_loss=1.756, generator_adv_loss=1.926, generator_feat_match_loss=4.29, over 3974.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 08:52:15,307 INFO [train.py:527] (2/6) Epoch 321, batch 120, global_batch_idx: 39800, batch size: 52, loss[discriminator_loss=2.752, discriminator_real_loss=1.529, discriminator_fake_loss=1.224, generator_loss=26.73, generator_mel_loss=17.99, generator_kl_loss=1.294, generator_dur_loss=1.708, generator_adv_loss=1.904, generator_feat_match_loss=3.833, over 52.00 samples.], tot_loss[discriminator_loss=2.729, discriminator_real_loss=1.381, discriminator_fake_loss=1.348, generator_loss=27.63, generator_mel_loss=18.27, generator_kl_loss=1.417, generator_dur_loss=1.765, generator_adv_loss=1.926, generator_feat_match_loss=4.257, over 6811.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 08:52:15,311 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 08:52:24,263 INFO [train.py:591] (2/6) Epoch 321, validation: discriminator_loss=2.749, discriminator_real_loss=1.382, discriminator_fake_loss=1.367, generator_loss=27.2, generator_mel_loss=18.48, generator_kl_loss=1.231, generator_dur_loss=1.847, generator_adv_loss=1.814, generator_feat_match_loss=3.827, over 100.00 samples.
2024-03-13 08:52:24,264 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 08:52:35,306 INFO [train.py:919] (2/6) Start epoch 322
2024-03-13 08:55:05,024 INFO [train.py:527] (2/6) Epoch 322, batch 46, global_batch_idx: 39850, batch size: 45, loss[discriminator_loss=2.681, discriminator_real_loss=1.294, discriminator_fake_loss=1.386, generator_loss=28.01, generator_mel_loss=18.48, generator_kl_loss=1.526, generator_dur_loss=1.736, generator_adv_loss=2.015, generator_feat_match_loss=4.262, over 45.00 samples.], tot_loss[discriminator_loss=2.721, discriminator_real_loss=1.377, discriminator_fake_loss=1.344, generator_loss=27.66, generator_mel_loss=18.26, generator_kl_loss=1.41, generator_dur_loss=1.77, generator_adv_loss=1.935, generator_feat_match_loss=4.289, over 2604.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 08:57:20,913 INFO [train.py:527] (2/6) Epoch 322, batch 96, global_batch_idx: 39900, batch size: 80, loss[discriminator_loss=2.728, discriminator_real_loss=1.305, discriminator_fake_loss=1.423, generator_loss=27.15, generator_mel_loss=18.18, generator_kl_loss=1.348, generator_dur_loss=1.849, generator_adv_loss=1.991, generator_feat_match_loss=3.785, over 80.00 samples.], tot_loss[discriminator_loss=2.729, discriminator_real_loss=1.381, discriminator_fake_loss=1.348, generator_loss=27.63, generator_mel_loss=18.28, generator_kl_loss=1.418, generator_dur_loss=1.767, generator_adv_loss=1.931, generator_feat_match_loss=4.24, over 5436.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 08:58:37,411 INFO [train.py:919] (2/6) Start epoch 323
2024-03-13 09:00:00,595 INFO [train.py:527] (2/6) Epoch 323, batch 22, global_batch_idx: 39950, batch size: 31, loss[discriminator_loss=2.82, discriminator_real_loss=1.51, discriminator_fake_loss=1.31, generator_loss=25.63, generator_mel_loss=17.49, generator_kl_loss=1.414, generator_dur_loss=1.692, generator_adv_loss=1.831, generator_feat_match_loss=3.206, over 31.00 samples.], tot_loss[discriminator_loss=2.719, discriminator_real_loss=1.393, discriminator_fake_loss=1.326, generator_loss=27.53, generator_mel_loss=18.25, generator_kl_loss=1.426, generator_dur_loss=1.708, generator_adv_loss=1.934, generator_feat_match_loss=4.205, over 1102.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 09:02:19,758 INFO [train.py:527] (2/6) Epoch 323, batch 72, global_batch_idx: 40000, batch size: 66, loss[discriminator_loss=2.715, discriminator_real_loss=1.36, discriminator_fake_loss=1.355, generator_loss=28.36, generator_mel_loss=18.49, generator_kl_loss=1.408, generator_dur_loss=1.787, generator_adv_loss=1.877, generator_feat_match_loss=4.804, over 66.00 samples.], tot_loss[discriminator_loss=2.727, discriminator_real_loss=1.383, discriminator_fake_loss=1.345, generator_loss=27.69, generator_mel_loss=18.3, generator_kl_loss=1.438, generator_dur_loss=1.726, generator_adv_loss=1.928, generator_feat_match_loss=4.293, over 3857.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 09:02:19,760 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 09:02:27,811 INFO [train.py:591] (2/6) Epoch 323, validation: discriminator_loss=2.763, discriminator_real_loss=1.41, discriminator_fake_loss=1.353, generator_loss=27.02, generator_mel_loss=18.64, generator_kl_loss=1.197, generator_dur_loss=1.831, generator_adv_loss=1.786, generator_feat_match_loss=3.572, over 100.00 samples.
2024-03-13 09:02:27,812 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 09:04:45,708 INFO [train.py:527] (2/6) Epoch 323, batch 122, global_batch_idx: 40050, batch size: 58, loss[discriminator_loss=2.725, discriminator_real_loss=1.398, discriminator_fake_loss=1.327, generator_loss=26.78, generator_mel_loss=17.62, generator_kl_loss=1.417, generator_dur_loss=1.725, generator_adv_loss=1.987, generator_feat_match_loss=4.027, over 58.00 samples.], tot_loss[discriminator_loss=2.73, discriminator_real_loss=1.385, discriminator_fake_loss=1.345, generator_loss=27.63, generator_mel_loss=18.28, generator_kl_loss=1.412, generator_dur_loss=1.743, generator_adv_loss=1.927, generator_feat_match_loss=4.271, over 6832.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 09:04:51,019 INFO [train.py:919] (2/6) Start epoch 324
2024-03-13 09:07:28,063 INFO [train.py:527] (2/6) Epoch 324, batch 48, global_batch_idx: 40100, batch size: 96, loss[discriminator_loss=2.737, discriminator_real_loss=1.227, discriminator_fake_loss=1.51, generator_loss=27.68, generator_mel_loss=18.24, generator_kl_loss=1.329, generator_dur_loss=1.86, generator_adv_loss=1.999, generator_feat_match_loss=4.255, over 96.00 samples.], tot_loss[discriminator_loss=2.719, discriminator_real_loss=1.365, discriminator_fake_loss=1.354, generator_loss=27.78, generator_mel_loss=18.37, generator_kl_loss=1.399, generator_dur_loss=1.767, generator_adv_loss=1.935, generator_feat_match_loss=4.315, over 2702.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 09:09:47,724 INFO [train.py:527] (2/6) Epoch 324, batch 98, global_batch_idx: 40150, batch size: 56, loss[discriminator_loss=2.717, discriminator_real_loss=1.41, discriminator_fake_loss=1.306, generator_loss=27.67, generator_mel_loss=18.38, generator_kl_loss=1.268, generator_dur_loss=1.746, generator_adv_loss=1.966, generator_feat_match_loss=4.312, over 56.00 samples.], tot_loss[discriminator_loss=2.723, discriminator_real_loss=1.376, discriminator_fake_loss=1.347, generator_loss=27.68, generator_mel_loss=18.3, generator_kl_loss=1.411, generator_dur_loss=1.756, generator_adv_loss=1.931, generator_feat_match_loss=4.279, over 5413.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 09:10:57,032 INFO [train.py:919] (2/6) Start epoch 325
2024-03-13 09:12:27,311 INFO [train.py:527] (2/6) Epoch 325, batch 24, global_batch_idx: 40200, batch size: 83, loss[discriminator_loss=2.716, discriminator_real_loss=1.357, discriminator_fake_loss=1.359, generator_loss=27.74, generator_mel_loss=18.35, generator_kl_loss=1.506, generator_dur_loss=1.866, generator_adv_loss=1.825, generator_feat_match_loss=4.192, over 83.00 samples.], tot_loss[discriminator_loss=2.723, discriminator_real_loss=1.371, discriminator_fake_loss=1.352, generator_loss=27.7, generator_mel_loss=18.27, generator_kl_loss=1.433, generator_dur_loss=1.776, generator_adv_loss=1.935, generator_feat_match_loss=4.289, over 1435.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 09:12:27,313 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 09:12:35,416 INFO [train.py:591] (2/6) Epoch 325, validation: discriminator_loss=2.748, discriminator_real_loss=1.363, discriminator_fake_loss=1.385, generator_loss=25.94, generator_mel_loss=18.11, generator_kl_loss=1.265, generator_dur_loss=1.831, generator_adv_loss=1.778, generator_feat_match_loss=2.957, over 100.00 samples.
2024-03-13 09:12:35,417 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 09:14:54,098 INFO [train.py:527] (2/6) Epoch 325, batch 74, global_batch_idx: 40250, batch size: 77, loss[discriminator_loss=2.775, discriminator_real_loss=1.31, discriminator_fake_loss=1.465, generator_loss=27.68, generator_mel_loss=18.31, generator_kl_loss=1.268, generator_dur_loss=1.765, generator_adv_loss=1.878, generator_feat_match_loss=4.453, over 77.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.374, discriminator_fake_loss=1.352, generator_loss=27.71, generator_mel_loss=18.29, generator_kl_loss=1.409, generator_dur_loss=1.766, generator_adv_loss=1.927, generator_feat_match_loss=4.322, over 4495.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 09:17:11,711 INFO [train.py:919] (2/6) Start epoch 326
2024-03-13 09:17:34,933 INFO [train.py:527] (2/6) Epoch 326, batch 0, global_batch_idx: 40300, batch size: 88, loss[discriminator_loss=2.637, discriminator_real_loss=1.303, discriminator_fake_loss=1.335, generator_loss=28.19, generator_mel_loss=18.12, generator_kl_loss=1.359, generator_dur_loss=1.877, generator_adv_loss=2.087, generator_feat_match_loss=4.751, over 88.00 samples.], tot_loss[discriminator_loss=2.637, discriminator_real_loss=1.303, discriminator_fake_loss=1.335, generator_loss=28.19, generator_mel_loss=18.12, generator_kl_loss=1.359, generator_dur_loss=1.877, generator_adv_loss=2.087, generator_feat_match_loss=4.751, over 88.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 09:19:53,518 INFO [train.py:527] (2/6) Epoch 326, batch 50, global_batch_idx: 40350, batch size: 39, loss[discriminator_loss=2.72, discriminator_real_loss=1.432, discriminator_fake_loss=1.288, generator_loss=27.72, generator_mel_loss=18.13, generator_kl_loss=1.449, generator_dur_loss=1.702, generator_adv_loss=1.823, generator_feat_match_loss=4.61, over 39.00 samples.], tot_loss[discriminator_loss=2.706, discriminator_real_loss=1.366, discriminator_fake_loss=1.339, generator_loss=27.95, generator_mel_loss=18.31, generator_kl_loss=1.419, generator_dur_loss=1.763, generator_adv_loss=1.963, generator_feat_match_loss=4.486, over 2781.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 09:22:12,747 INFO [train.py:527] (2/6) Epoch 326, batch 100, global_batch_idx: 40400, batch size: 74, loss[discriminator_loss=2.744, discriminator_real_loss=1.484, discriminator_fake_loss=1.26, generator_loss=26.69, generator_mel_loss=18.04, generator_kl_loss=1.346, generator_dur_loss=1.755, generator_adv_loss=1.78, generator_feat_match_loss=3.762, over 74.00 samples.], tot_loss[discriminator_loss=2.712, discriminator_real_loss=1.373, discriminator_fake_loss=1.339, generator_loss=27.88, generator_mel_loss=18.33, generator_kl_loss=1.438, generator_dur_loss=1.747, generator_adv_loss=1.945, generator_feat_match_loss=4.422, over 5422.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 09:22:12,749 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 09:22:21,416 INFO [train.py:591] (2/6) Epoch 326, validation: discriminator_loss=2.746, discriminator_real_loss=1.398, discriminator_fake_loss=1.347, generator_loss=26.39, generator_mel_loss=18.21, generator_kl_loss=1.223, generator_dur_loss=1.815, generator_adv_loss=1.736, generator_feat_match_loss=3.409, over 100.00 samples.
2024-03-13 09:22:21,417 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 09:23:27,273 INFO [train.py:919] (2/6) Start epoch 327
2024-03-13 09:25:03,142 INFO [train.py:527] (2/6) Epoch 327, batch 26, global_batch_idx: 40450, batch size: 80, loss[discriminator_loss=2.713, discriminator_real_loss=1.296, discriminator_fake_loss=1.416, generator_loss=27.6, generator_mel_loss=18.14, generator_kl_loss=1.361, generator_dur_loss=1.765, generator_adv_loss=2.071, generator_feat_match_loss=4.265, over 80.00 samples.], tot_loss[discriminator_loss=2.703, discriminator_real_loss=1.364, discriminator_fake_loss=1.339, generator_loss=28.05, generator_mel_loss=18.35, generator_kl_loss=1.424, generator_dur_loss=1.746, generator_adv_loss=1.96, generator_feat_match_loss=4.565, over 1494.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 09:27:22,160 INFO [train.py:527] (2/6) Epoch 327, batch 76, global_batch_idx: 40500, batch size: 12, loss[discriminator_loss=2.691, discriminator_real_loss=1.325, discriminator_fake_loss=1.365, generator_loss=29.48, generator_mel_loss=19.12, generator_kl_loss=1.809, generator_dur_loss=1.654, generator_adv_loss=2.217, generator_feat_match_loss=4.684, over 12.00 samples.], tot_loss[discriminator_loss=2.714, discriminator_real_loss=1.37, discriminator_fake_loss=1.344, generator_loss=27.83, generator_mel_loss=18.3, generator_kl_loss=1.407, generator_dur_loss=1.745, generator_adv_loss=1.929, generator_feat_match_loss=4.442, over 4064.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 09:29:33,965 INFO [train.py:919] (2/6) Start epoch 328
2024-03-13 09:30:05,272 INFO [train.py:527] (2/6) Epoch 328, batch 2, global_batch_idx: 40550, batch size: 61, loss[discriminator_loss=2.722, discriminator_real_loss=1.383, discriminator_fake_loss=1.339, generator_loss=28.3, generator_mel_loss=18.53, generator_kl_loss=1.418, generator_dur_loss=1.745, generator_adv_loss=1.998, generator_feat_match_loss=4.607, over 61.00 samples.], tot_loss[discriminator_loss=2.765, discriminator_real_loss=1.397, discriminator_fake_loss=1.369, generator_loss=27.91, generator_mel_loss=18.38, generator_kl_loss=1.416, generator_dur_loss=1.817, generator_adv_loss=1.941, generator_feat_match_loss=4.355, over 192.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 09:32:23,480 INFO [train.py:527] (2/6) Epoch 328, batch 52, global_batch_idx: 40600, batch size: 88, loss[discriminator_loss=2.753, discriminator_real_loss=1.398, discriminator_fake_loss=1.355, generator_loss=27.72, generator_mel_loss=18.27, generator_kl_loss=1.274, generator_dur_loss=1.855, generator_adv_loss=1.882, generator_feat_match_loss=4.439, over 88.00 samples.], tot_loss[discriminator_loss=2.743, discriminator_real_loss=1.391, discriminator_fake_loss=1.352, generator_loss=27.65, generator_mel_loss=18.25, generator_kl_loss=1.396, generator_dur_loss=1.779, generator_adv_loss=1.934, generator_feat_match_loss=4.285, over 3064.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 09:32:23,481 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 09:32:31,661 INFO [train.py:591] (2/6) Epoch 328, validation: discriminator_loss=2.788, discriminator_real_loss=1.456, discriminator_fake_loss=1.332, generator_loss=27.04, generator_mel_loss=18.69, generator_kl_loss=1.18, generator_dur_loss=1.834, generator_adv_loss=1.859, generator_feat_match_loss=3.474, over 100.00 samples.
2024-03-13 09:32:31,662 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 09:34:49,904 INFO [train.py:527] (2/6) Epoch 328, batch 102, global_batch_idx: 40650, batch size: 62, loss[discriminator_loss=2.753, discriminator_real_loss=1.417, discriminator_fake_loss=1.336, generator_loss=27.51, generator_mel_loss=18.28, generator_kl_loss=1.472, generator_dur_loss=1.762, generator_adv_loss=1.916, generator_feat_match_loss=4.086, over 62.00 samples.], tot_loss[discriminator_loss=2.733, discriminator_real_loss=1.382, discriminator_fake_loss=1.351, generator_loss=27.66, generator_mel_loss=18.24, generator_kl_loss=1.401, generator_dur_loss=1.786, generator_adv_loss=1.929, generator_feat_match_loss=4.308, over 6172.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 09:35:48,984 INFO [train.py:919] (2/6) Start epoch 329
2024-03-13 09:37:29,852 INFO [train.py:527] (2/6) Epoch 329, batch 28, global_batch_idx: 40700, batch size: 68, loss[discriminator_loss=2.789, discriminator_real_loss=1.562, discriminator_fake_loss=1.227, generator_loss=26.46, generator_mel_loss=17.57, generator_kl_loss=1.347, generator_dur_loss=1.793, generator_adv_loss=1.766, generator_feat_match_loss=3.984, over 68.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.37, discriminator_fake_loss=1.349, generator_loss=27.45, generator_mel_loss=18.1, generator_kl_loss=1.393, generator_dur_loss=1.775, generator_adv_loss=1.927, generator_feat_match_loss=4.255, over 1686.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 09:39:49,130 INFO [train.py:527] (2/6) Epoch 329, batch 78, global_batch_idx: 40750, batch size: 72, loss[discriminator_loss=2.707, discriminator_real_loss=1.429, discriminator_fake_loss=1.277, generator_loss=27.59, generator_mel_loss=18.57, generator_kl_loss=1.31, generator_dur_loss=1.832, generator_adv_loss=1.77, generator_feat_match_loss=4.106, over 72.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.373, discriminator_fake_loss=1.347, generator_loss=27.5, generator_mel_loss=18.15, generator_kl_loss=1.38, generator_dur_loss=1.77, generator_adv_loss=1.933, generator_feat_match_loss=4.265, over 4597.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 09:41:52,287 INFO [train.py:919] (2/6) Start epoch 330
2024-03-13 09:42:27,550 INFO [train.py:527] (2/6) Epoch 330, batch 4, global_batch_idx: 40800, batch size: 52, loss[discriminator_loss=2.767, discriminator_real_loss=1.289, discriminator_fake_loss=1.478, generator_loss=28.45, generator_mel_loss=18.73, generator_kl_loss=1.58, generator_dur_loss=1.746, generator_adv_loss=1.93, generator_feat_match_loss=4.462, over 52.00 samples.], tot_loss[discriminator_loss=2.732, discriminator_real_loss=1.39, discriminator_fake_loss=1.342, generator_loss=28.2, generator_mel_loss=18.64, generator_kl_loss=1.488, generator_dur_loss=1.737, generator_adv_loss=1.901, generator_feat_match_loss=4.433, over 242.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 09:42:27,553 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 09:42:35,303 INFO [train.py:591] (2/6) Epoch 330, validation: discriminator_loss=2.748, discriminator_real_loss=1.445, discriminator_fake_loss=1.304, generator_loss=26.97, generator_mel_loss=18.55, generator_kl_loss=1.265, generator_dur_loss=1.82, generator_adv_loss=1.899, generator_feat_match_loss=3.435, over 100.00 samples.
2024-03-13 09:42:35,306 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 09:44:59,988 INFO [train.py:527] (2/6) Epoch 330, batch 54, global_batch_idx: 40850, batch size: 48, loss[discriminator_loss=2.748, discriminator_real_loss=1.294, discriminator_fake_loss=1.454, generator_loss=27.88, generator_mel_loss=18.49, generator_kl_loss=1.421, generator_dur_loss=1.642, generator_adv_loss=2.016, generator_feat_match_loss=4.305, over 48.00 samples.], tot_loss[discriminator_loss=2.711, discriminator_real_loss=1.367, discriminator_fake_loss=1.344, generator_loss=27.74, generator_mel_loss=18.29, generator_kl_loss=1.399, generator_dur_loss=1.763, generator_adv_loss=1.933, generator_feat_match_loss=4.354, over 3281.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 09:47:18,904 INFO [train.py:527] (2/6) Epoch 330, batch 104, global_batch_idx: 40900, batch size: 83, loss[discriminator_loss=2.717, discriminator_real_loss=1.355, discriminator_fake_loss=1.362, generator_loss=27.39, generator_mel_loss=18.01, generator_kl_loss=1.263, generator_dur_loss=1.801, generator_adv_loss=1.942, generator_feat_match_loss=4.369, over 83.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.367, discriminator_fake_loss=1.349, generator_loss=27.73, generator_mel_loss=18.28, generator_kl_loss=1.4, generator_dur_loss=1.768, generator_adv_loss=1.936, generator_feat_match_loss=4.347, over 6237.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 09:48:11,121 INFO [train.py:919] (2/6) Start epoch 331
2024-03-13 09:49:59,675 INFO [train.py:527] (2/6) Epoch 331, batch 30, global_batch_idx: 40950, batch size: 58, loss[discriminator_loss=2.697, discriminator_real_loss=1.358, discriminator_fake_loss=1.339, generator_loss=27.45, generator_mel_loss=17.87, generator_kl_loss=1.466, generator_dur_loss=1.76, generator_adv_loss=1.957, generator_feat_match_loss=4.398, over 58.00 samples.], tot_loss[discriminator_loss=2.733, discriminator_real_loss=1.375, discriminator_fake_loss=1.359, generator_loss=27.62, generator_mel_loss=18.21, generator_kl_loss=1.41, generator_dur_loss=1.765, generator_adv_loss=1.916, generator_feat_match_loss=4.313, over 1713.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 09:52:17,442 INFO [train.py:527] (2/6) Epoch 331, batch 80, global_batch_idx: 41000, batch size: 53, loss[discriminator_loss=2.69, discriminator_real_loss=1.245, discriminator_fake_loss=1.445, generator_loss=27.05, generator_mel_loss=17.85, generator_kl_loss=1.37, generator_dur_loss=1.706, generator_adv_loss=1.917, generator_feat_match_loss=4.205, over 53.00 samples.], tot_loss[discriminator_loss=2.73, discriminator_real_loss=1.385, discriminator_fake_loss=1.345, generator_loss=27.62, generator_mel_loss=18.22, generator_kl_loss=1.416, generator_dur_loss=1.76, generator_adv_loss=1.932, generator_feat_match_loss=4.3, over 4578.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 09:52:17,445 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 09:52:26,154 INFO [train.py:591] (2/6) Epoch 331, validation: discriminator_loss=2.744, discriminator_real_loss=1.409, discriminator_fake_loss=1.336, generator_loss=26.9, generator_mel_loss=18.54, generator_kl_loss=1.258, generator_dur_loss=1.821, generator_adv_loss=1.844, generator_feat_match_loss=3.44, over 100.00 samples.
2024-03-13 09:52:26,155 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 09:54:27,016 INFO [train.py:919] (2/6) Start epoch 332
2024-03-13 09:55:07,469 INFO [train.py:527] (2/6) Epoch 332, batch 6, global_batch_idx: 41050, batch size: 55, loss[discriminator_loss=2.713, discriminator_real_loss=1.404, discriminator_fake_loss=1.309, generator_loss=27.7, generator_mel_loss=18.57, generator_kl_loss=1.284, generator_dur_loss=1.726, generator_adv_loss=1.945, generator_feat_match_loss=4.176, over 55.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.358, discriminator_fake_loss=1.357, generator_loss=27.75, generator_mel_loss=18.27, generator_kl_loss=1.401, generator_dur_loss=1.759, generator_adv_loss=1.94, generator_feat_match_loss=4.373, over 417.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 09:57:25,741 INFO [train.py:527] (2/6) Epoch 332, batch 56, global_batch_idx: 41100, batch size: 55, loss[discriminator_loss=2.75, discriminator_real_loss=1.352, discriminator_fake_loss=1.397, generator_loss=27.74, generator_mel_loss=18.33, generator_kl_loss=1.419, generator_dur_loss=1.752, generator_adv_loss=1.84, generator_feat_match_loss=4.395, over 55.00 samples.], tot_loss[discriminator_loss=2.729, discriminator_real_loss=1.378, discriminator_fake_loss=1.351, generator_loss=27.6, generator_mel_loss=18.2, generator_kl_loss=1.402, generator_dur_loss=1.762, generator_adv_loss=1.928, generator_feat_match_loss=4.305, over 3326.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 09:59:44,642 INFO [train.py:527] (2/6) Epoch 332, batch 106, global_batch_idx: 41150, batch size: 36, loss[discriminator_loss=2.653, discriminator_real_loss=1.321, discriminator_fake_loss=1.332, generator_loss=27.69, generator_mel_loss=18.45, generator_kl_loss=1.451, generator_dur_loss=1.775, generator_adv_loss=1.958, generator_feat_match_loss=4.062, over 36.00 samples.], tot_loss[discriminator_loss=2.725, discriminator_real_loss=1.378, discriminator_fake_loss=1.347, generator_loss=27.62, generator_mel_loss=18.2, generator_kl_loss=1.399, generator_dur_loss=1.756, generator_adv_loss=1.934, generator_feat_match_loss=4.33, over 6125.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 10:00:34,038 INFO [train.py:919] (2/6) Start epoch 333
2024-03-13 10:02:27,510 INFO [train.py:527] (2/6) Epoch 333, batch 32, global_batch_idx: 41200, batch size: 58, loss[discriminator_loss=2.724, discriminator_real_loss=1.33, discriminator_fake_loss=1.394, generator_loss=27.49, generator_mel_loss=18.12, generator_kl_loss=1.5, generator_dur_loss=1.737, generator_adv_loss=2.011, generator_feat_match_loss=4.122, over 58.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.388, discriminator_fake_loss=1.338, generator_loss=27.55, generator_mel_loss=18.19, generator_kl_loss=1.395, generator_dur_loss=1.762, generator_adv_loss=1.942, generator_feat_match_loss=4.262, over 1893.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 10:02:27,511 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 10:02:35,684 INFO [train.py:591] (2/6) Epoch 333, validation: discriminator_loss=2.759, discriminator_real_loss=1.473, discriminator_fake_loss=1.286, generator_loss=26.73, generator_mel_loss=18.49, generator_kl_loss=1.272, generator_dur_loss=1.809, generator_adv_loss=1.928, generator_feat_match_loss=3.235, over 100.00 samples.
2024-03-13 10:02:35,685 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 10:04:55,385 INFO [train.py:527] (2/6) Epoch 333, batch 82, global_batch_idx: 41250, batch size: 66, loss[discriminator_loss=2.735, discriminator_real_loss=1.439, discriminator_fake_loss=1.296, generator_loss=27.24, generator_mel_loss=18.3, generator_kl_loss=1.193, generator_dur_loss=1.791, generator_adv_loss=1.762, generator_feat_match_loss=4.2, over 66.00 samples.], tot_loss[discriminator_loss=2.732, discriminator_real_loss=1.389, discriminator_fake_loss=1.343, generator_loss=27.53, generator_mel_loss=18.21, generator_kl_loss=1.398, generator_dur_loss=1.76, generator_adv_loss=1.927, generator_feat_match_loss=4.234, over 4786.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 10:06:51,711 INFO [train.py:919] (2/6) Start epoch 334
2024-03-13 10:07:38,903 INFO [train.py:527] (2/6) Epoch 334, batch 8, global_batch_idx: 41300, batch size: 74, loss[discriminator_loss=2.732, discriminator_real_loss=1.363, discriminator_fake_loss=1.369, generator_loss=27.42, generator_mel_loss=18.14, generator_kl_loss=1.434, generator_dur_loss=1.783, generator_adv_loss=1.76, generator_feat_match_loss=4.304, over 74.00 samples.], tot_loss[discriminator_loss=2.722, discriminator_real_loss=1.39, discriminator_fake_loss=1.332, generator_loss=27.88, generator_mel_loss=18.41, generator_kl_loss=1.366, generator_dur_loss=1.784, generator_adv_loss=1.962, generator_feat_match_loss=4.364, over 573.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 10:09:55,679 INFO [train.py:527] (2/6) Epoch 334, batch 58, global_batch_idx: 41350, batch size: 74, loss[discriminator_loss=2.711, discriminator_real_loss=1.336, discriminator_fake_loss=1.375, generator_loss=27.37, generator_mel_loss=17.89, generator_kl_loss=1.464, generator_dur_loss=1.844, generator_adv_loss=1.738, generator_feat_match_loss=4.43, over 74.00 samples.], tot_loss[discriminator_loss=2.724, discriminator_real_loss=1.379, discriminator_fake_loss=1.345, generator_loss=27.64, generator_mel_loss=18.21, generator_kl_loss=1.404, generator_dur_loss=1.777, generator_adv_loss=1.931, generator_feat_match_loss=4.319, over 3430.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 10:12:16,011 INFO [train.py:527] (2/6) Epoch 334, batch 108, global_batch_idx: 41400, batch size: 45, loss[discriminator_loss=2.753, discriminator_real_loss=1.466, discriminator_fake_loss=1.288, generator_loss=27.05, generator_mel_loss=17.94, generator_kl_loss=1.539, generator_dur_loss=1.667, generator_adv_loss=1.716, generator_feat_match_loss=4.181, over 45.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.376, discriminator_fake_loss=1.344, generator_loss=27.65, generator_mel_loss=18.2, generator_kl_loss=1.406, generator_dur_loss=1.777, generator_adv_loss=1.933, generator_feat_match_loss=4.333, over 6316.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 10:12:16,013 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 10:12:24,661 INFO [train.py:591] (2/6) Epoch 334, validation: discriminator_loss=2.834, discriminator_real_loss=1.331, discriminator_fake_loss=1.503, generator_loss=27.15, generator_mel_loss=18.92, generator_kl_loss=1.164, generator_dur_loss=1.829, generator_adv_loss=1.652, generator_feat_match_loss=3.582, over 100.00 samples.
2024-03-13 10:12:24,662 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 10:13:08,362 INFO [train.py:919] (2/6) Start epoch 335
2024-03-13 10:15:06,121 INFO [train.py:527] (2/6) Epoch 335, batch 34, global_batch_idx: 41450, batch size: 74, loss[discriminator_loss=2.745, discriminator_real_loss=1.446, discriminator_fake_loss=1.298, generator_loss=27.57, generator_mel_loss=18.05, generator_kl_loss=1.356, generator_dur_loss=1.845, generator_adv_loss=2.147, generator_feat_match_loss=4.17, over 74.00 samples.], tot_loss[discriminator_loss=2.727, discriminator_real_loss=1.378, discriminator_fake_loss=1.349, generator_loss=27.72, generator_mel_loss=18.21, generator_kl_loss=1.388, generator_dur_loss=1.784, generator_adv_loss=1.956, generator_feat_match_loss=4.39, over 2103.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 10:17:24,591 INFO [train.py:527] (2/6) Epoch 335, batch 84, global_batch_idx: 41500, batch size: 80, loss[discriminator_loss=2.766, discriminator_real_loss=1.375, discriminator_fake_loss=1.39, generator_loss=27.46, generator_mel_loss=18.3, generator_kl_loss=1.213, generator_dur_loss=1.779, generator_adv_loss=1.912, generator_feat_match_loss=4.258, over 80.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.376, discriminator_fake_loss=1.349, generator_loss=27.67, generator_mel_loss=18.19, generator_kl_loss=1.39, generator_dur_loss=1.777, generator_adv_loss=1.959, generator_feat_match_loss=4.351, over 5010.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 10:19:14,872 INFO [train.py:919] (2/6) Start epoch 336
2024-03-13 10:20:06,620 INFO [train.py:527] (2/6) Epoch 336, batch 10, global_batch_idx: 41550, batch size: 13, loss[discriminator_loss=2.692, discriminator_real_loss=1.344, discriminator_fake_loss=1.348, generator_loss=26.57, generator_mel_loss=17.41, generator_kl_loss=1.61, generator_dur_loss=1.705, generator_adv_loss=2, generator_feat_match_loss=3.841, over 13.00 samples.], tot_loss[discriminator_loss=2.739, discriminator_real_loss=1.381, discriminator_fake_loss=1.358, generator_loss=27.45, generator_mel_loss=18.04, generator_kl_loss=1.455, generator_dur_loss=1.772, generator_adv_loss=1.896, generator_feat_match_loss=4.278, over 563.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 10:22:24,007 INFO [train.py:527] (2/6) Epoch 336, batch 60, global_batch_idx: 41600, batch size: 72, loss[discriminator_loss=2.708, discriminator_real_loss=1.297, discriminator_fake_loss=1.411, generator_loss=27.97, generator_mel_loss=17.59, generator_kl_loss=1.404, generator_dur_loss=1.857, generator_adv_loss=2.063, generator_feat_match_loss=5.057, over 72.00 samples.], tot_loss[discriminator_loss=2.721, discriminator_real_loss=1.376, discriminator_fake_loss=1.345, generator_loss=27.76, generator_mel_loss=18.2, generator_kl_loss=1.453, generator_dur_loss=1.761, generator_adv_loss=1.93, generator_feat_match_loss=4.416, over 3222.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 10:22:24,009 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 10:22:32,327 INFO [train.py:591] (2/6) Epoch 336, validation: discriminator_loss=2.743, discriminator_real_loss=1.444, discriminator_fake_loss=1.299, generator_loss=26.76, generator_mel_loss=18.56, generator_kl_loss=1.235, generator_dur_loss=1.829, generator_adv_loss=1.946, generator_feat_match_loss=3.193, over 100.00 samples.
2024-03-13 10:22:32,328 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 10:24:50,783 INFO [train.py:527] (2/6) Epoch 336, batch 110, global_batch_idx: 41650, batch size: 39, loss[discriminator_loss=2.661, discriminator_real_loss=1.35, discriminator_fake_loss=1.311, generator_loss=27.96, generator_mel_loss=18.23, generator_kl_loss=1.566, generator_dur_loss=1.678, generator_adv_loss=1.909, generator_feat_match_loss=4.577, over 39.00 samples.], tot_loss[discriminator_loss=2.719, discriminator_real_loss=1.376, discriminator_fake_loss=1.343, generator_loss=27.85, generator_mel_loss=18.27, generator_kl_loss=1.434, generator_dur_loss=1.771, generator_adv_loss=1.951, generator_feat_match_loss=4.421, over 6128.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 10:25:28,638 INFO [train.py:919] (2/6) Start epoch 337
2024-03-13 10:27:32,916 INFO [train.py:527] (2/6) Epoch 337, batch 36, global_batch_idx: 41700, batch size: 55, loss[discriminator_loss=2.736, discriminator_real_loss=1.373, discriminator_fake_loss=1.363, generator_loss=27.43, generator_mel_loss=18.34, generator_kl_loss=1.481, generator_dur_loss=1.75, generator_adv_loss=1.92, generator_feat_match_loss=3.946, over 55.00 samples.], tot_loss[discriminator_loss=2.722, discriminator_real_loss=1.385, discriminator_fake_loss=1.337, generator_loss=27.65, generator_mel_loss=18.15, generator_kl_loss=1.395, generator_dur_loss=1.771, generator_adv_loss=1.933, generator_feat_match_loss=4.397, over 2230.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 10:29:48,347 INFO [train.py:527] (2/6) Epoch 337, batch 86, global_batch_idx: 41750, batch size: 80, loss[discriminator_loss=2.738, discriminator_real_loss=1.349, discriminator_fake_loss=1.389, generator_loss=27.97, generator_mel_loss=18.55, generator_kl_loss=1.347, generator_dur_loss=1.816, generator_adv_loss=1.914, generator_feat_match_loss=4.348, over 80.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.378, discriminator_fake_loss=1.342, generator_loss=27.68, generator_mel_loss=18.2, generator_kl_loss=1.408, generator_dur_loss=1.766, generator_adv_loss=1.929, generator_feat_match_loss=4.381, over 4894.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 10:31:33,189 INFO [train.py:919] (2/6) Start epoch 338
2024-03-13 10:32:32,798 INFO [train.py:527] (2/6) Epoch 338, batch 12, global_batch_idx: 41800, batch size: 96, loss[discriminator_loss=2.703, discriminator_real_loss=1.359, discriminator_fake_loss=1.343, generator_loss=27.64, generator_mel_loss=18.14, generator_kl_loss=1.291, generator_dur_loss=1.871, generator_adv_loss=1.971, generator_feat_match_loss=4.369, over 96.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.384, discriminator_fake_loss=1.33, generator_loss=27.69, generator_mel_loss=18.14, generator_kl_loss=1.435, generator_dur_loss=1.786, generator_adv_loss=1.967, generator_feat_match_loss=4.363, over 797.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 10:32:32,801 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 10:32:40,993 INFO [train.py:591] (2/6) Epoch 338, validation: discriminator_loss=2.734, discriminator_real_loss=1.466, discriminator_fake_loss=1.268, generator_loss=26.89, generator_mel_loss=18.59, generator_kl_loss=1.281, generator_dur_loss=1.832, generator_adv_loss=1.936, generator_feat_match_loss=3.255, over 100.00 samples.
2024-03-13 10:32:40,994 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 10:34:58,348 INFO [train.py:527] (2/6) Epoch 338, batch 62, global_batch_idx: 41850, batch size: 36, loss[discriminator_loss=2.674, discriminator_real_loss=1.381, discriminator_fake_loss=1.293, generator_loss=27.65, generator_mel_loss=17.83, generator_kl_loss=1.591, generator_dur_loss=1.691, generator_adv_loss=1.95, generator_feat_match_loss=4.591, over 36.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.375, discriminator_fake_loss=1.344, generator_loss=27.68, generator_mel_loss=18.19, generator_kl_loss=1.417, generator_dur_loss=1.779, generator_adv_loss=1.937, generator_feat_match_loss=4.357, over 3717.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 10:37:18,488 INFO [train.py:527] (2/6) Epoch 338, batch 112, global_batch_idx: 41900, batch size: 53, loss[discriminator_loss=2.653, discriminator_real_loss=1.322, discriminator_fake_loss=1.331, generator_loss=28.36, generator_mel_loss=18.39, generator_kl_loss=1.556, generator_dur_loss=1.65, generator_adv_loss=2.117, generator_feat_match_loss=4.646, over 53.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.377, discriminator_fake_loss=1.343, generator_loss=27.65, generator_mel_loss=18.17, generator_kl_loss=1.403, generator_dur_loss=1.779, generator_adv_loss=1.944, generator_feat_match_loss=4.357, over 6593.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 10:37:47,432 INFO [train.py:919] (2/6) Start epoch 339
2024-03-13 10:39:58,049 INFO [train.py:527] (2/6) Epoch 339, batch 38, global_batch_idx: 41950, batch size: 64, loss[discriminator_loss=2.698, discriminator_real_loss=1.353, discriminator_fake_loss=1.345, generator_loss=27.92, generator_mel_loss=18.2, generator_kl_loss=1.445, generator_dur_loss=1.813, generator_adv_loss=1.875, generator_feat_match_loss=4.592, over 64.00 samples.], tot_loss[discriminator_loss=2.711, discriminator_real_loss=1.375, discriminator_fake_loss=1.336, generator_loss=27.88, generator_mel_loss=18.26, generator_kl_loss=1.414, generator_dur_loss=1.769, generator_adv_loss=1.933, generator_feat_match_loss=4.512, over 2114.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 10:42:14,517 INFO [train.py:527] (2/6) Epoch 339, batch 88, global_batch_idx: 42000, batch size: 58, loss[discriminator_loss=2.723, discriminator_real_loss=1.404, discriminator_fake_loss=1.318, generator_loss=27.76, generator_mel_loss=18.06, generator_kl_loss=1.444, generator_dur_loss=1.747, generator_adv_loss=2.09, generator_feat_match_loss=4.417, over 58.00 samples.], tot_loss[discriminator_loss=2.721, discriminator_real_loss=1.379, discriminator_fake_loss=1.342, generator_loss=27.77, generator_mel_loss=18.23, generator_kl_loss=1.409, generator_dur_loss=1.771, generator_adv_loss=1.943, generator_feat_match_loss=4.415, over 4831.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 10:42:14,518 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 10:42:23,426 INFO [train.py:591] (2/6) Epoch 339, validation: discriminator_loss=2.779, discriminator_real_loss=1.482, discriminator_fake_loss=1.298, generator_loss=27.57, generator_mel_loss=18.6, generator_kl_loss=1.219, generator_dur_loss=1.837, generator_adv_loss=2.026, generator_feat_match_loss=3.893, over 100.00 samples.
2024-03-13 10:42:23,427 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 10:44:02,790 INFO [train.py:919] (2/6) Start epoch 340
2024-03-13 10:45:05,880 INFO [train.py:527] (2/6) Epoch 340, batch 14, global_batch_idx: 42050, batch size: 77, loss[discriminator_loss=2.686, discriminator_real_loss=1.346, discriminator_fake_loss=1.34, generator_loss=27.77, generator_mel_loss=18.12, generator_kl_loss=1.463, generator_dur_loss=1.83, generator_adv_loss=1.923, generator_feat_match_loss=4.437, over 77.00 samples.], tot_loss[discriminator_loss=2.708, discriminator_real_loss=1.373, discriminator_fake_loss=1.335, generator_loss=27.45, generator_mel_loss=17.98, generator_kl_loss=1.415, generator_dur_loss=1.787, generator_adv_loss=1.923, generator_feat_match_loss=4.346, over 873.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 10:47:26,178 INFO [train.py:527] (2/6) Epoch 340, batch 64, global_batch_idx: 42100, batch size: 62, loss[discriminator_loss=2.666, discriminator_real_loss=1.287, discriminator_fake_loss=1.379, generator_loss=27.55, generator_mel_loss=18.27, generator_kl_loss=1.457, generator_dur_loss=1.789, generator_adv_loss=1.917, generator_feat_match_loss=4.113, over 62.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.378, discriminator_fake_loss=1.338, generator_loss=27.62, generator_mel_loss=18.18, generator_kl_loss=1.401, generator_dur_loss=1.77, generator_adv_loss=1.925, generator_feat_match_loss=4.343, over 3655.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 10:49:42,755 INFO [train.py:527] (2/6) Epoch 340, batch 114, global_batch_idx: 42150, batch size: 74, loss[discriminator_loss=2.707, discriminator_real_loss=1.339, discriminator_fake_loss=1.367, generator_loss=26.89, generator_mel_loss=17.85, generator_kl_loss=1.286, generator_dur_loss=1.831, generator_adv_loss=1.805, generator_feat_match_loss=4.118, over 74.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.384, discriminator_fake_loss=1.342, generator_loss=27.74, generator_mel_loss=18.25, generator_kl_loss=1.392, generator_dur_loss=1.763, generator_adv_loss=1.955, generator_feat_match_loss=4.374, over 6357.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 10:50:09,082 INFO [train.py:919] (2/6) Start epoch 341
2024-03-13 10:52:27,803 INFO [train.py:527] (2/6) Epoch 341, batch 40, global_batch_idx: 42200, batch size: 83, loss[discriminator_loss=2.725, discriminator_real_loss=1.374, discriminator_fake_loss=1.351, generator_loss=26.93, generator_mel_loss=18, generator_kl_loss=1.232, generator_dur_loss=1.838, generator_adv_loss=1.883, generator_feat_match_loss=3.976, over 83.00 samples.], tot_loss[discriminator_loss=2.722, discriminator_real_loss=1.38, discriminator_fake_loss=1.342, generator_loss=27.7, generator_mel_loss=18.18, generator_kl_loss=1.396, generator_dur_loss=1.753, generator_adv_loss=1.93, generator_feat_match_loss=4.441, over 2422.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 10:52:27,804 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 10:52:35,859 INFO [train.py:591] (2/6) Epoch 341, validation: discriminator_loss=2.714, discriminator_real_loss=1.35, discriminator_fake_loss=1.364, generator_loss=26.04, generator_mel_loss=18.07, generator_kl_loss=1.259, generator_dur_loss=1.82, generator_adv_loss=1.815, generator_feat_match_loss=3.073, over 100.00 samples.
2024-03-13 10:52:35,860 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 10:54:54,152 INFO [train.py:527] (2/6) Epoch 341, batch 90, global_batch_idx: 42250, batch size: 52, loss[discriminator_loss=2.669, discriminator_real_loss=1.355, discriminator_fake_loss=1.314, generator_loss=29.01, generator_mel_loss=18.54, generator_kl_loss=1.557, generator_dur_loss=1.708, generator_adv_loss=2.102, generator_feat_match_loss=5.103, over 52.00 samples.], tot_loss[discriminator_loss=2.722, discriminator_real_loss=1.379, discriminator_fake_loss=1.343, generator_loss=27.69, generator_mel_loss=18.19, generator_kl_loss=1.398, generator_dur_loss=1.761, generator_adv_loss=1.936, generator_feat_match_loss=4.404, over 5296.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 10:56:24,054 INFO [train.py:919] (2/6) Start epoch 342
2024-03-13 10:57:33,209 INFO [train.py:527] (2/6) Epoch 342, batch 16, global_batch_idx: 42300, batch size: 39, loss[discriminator_loss=2.749, discriminator_real_loss=1.532, discriminator_fake_loss=1.217, generator_loss=27.32, generator_mel_loss=18.11, generator_kl_loss=1.523, generator_dur_loss=1.675, generator_adv_loss=1.852, generator_feat_match_loss=4.161, over 39.00 samples.], tot_loss[discriminator_loss=2.711, discriminator_real_loss=1.373, discriminator_fake_loss=1.338, generator_loss=27.72, generator_mel_loss=18.19, generator_kl_loss=1.413, generator_dur_loss=1.756, generator_adv_loss=1.947, generator_feat_match_loss=4.412, over 948.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 10:59:51,281 INFO [train.py:527] (2/6) Epoch 342, batch 66, global_batch_idx: 42350, batch size: 25, loss[discriminator_loss=2.721, discriminator_real_loss=1.436, discriminator_fake_loss=1.285, generator_loss=26.85, generator_mel_loss=17.57, generator_kl_loss=1.558, generator_dur_loss=1.604, generator_adv_loss=2.046, generator_feat_match_loss=4.078, over 25.00 samples.], tot_loss[discriminator_loss=2.709, discriminator_real_loss=1.366, discriminator_fake_loss=1.343, generator_loss=27.77, generator_mel_loss=18.23, generator_kl_loss=1.412, generator_dur_loss=1.752, generator_adv_loss=1.944, generator_feat_match_loss=4.43, over 3820.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 11:02:09,683 INFO [train.py:527] (2/6) Epoch 342, batch 116, global_batch_idx: 42400, batch size: 47, loss[discriminator_loss=2.671, discriminator_real_loss=1.364, discriminator_fake_loss=1.308, generator_loss=28.59, generator_mel_loss=18.35, generator_kl_loss=1.299, generator_dur_loss=1.705, generator_adv_loss=2.031, generator_feat_match_loss=5.208, over 47.00 samples.], tot_loss[discriminator_loss=2.713, discriminator_real_loss=1.366, discriminator_fake_loss=1.347, generator_loss=27.73, generator_mel_loss=18.21, generator_kl_loss=1.419, generator_dur_loss=1.753, generator_adv_loss=1.933, generator_feat_match_loss=4.422, over 6489.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 11:02:09,685 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 11:02:18,384 INFO [train.py:591] (2/6) Epoch 342, validation: discriminator_loss=2.732, discriminator_real_loss=1.465, discriminator_fake_loss=1.266, generator_loss=27.05, generator_mel_loss=18.36, generator_kl_loss=1.188, generator_dur_loss=1.828, generator_adv_loss=1.955, generator_feat_match_loss=3.718, over 100.00 samples.
2024-03-13 11:02:18,385 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 11:02:39,394 INFO [train.py:919] (2/6) Start epoch 343
2024-03-13 11:05:00,117 INFO [train.py:527] (2/6) Epoch 343, batch 42, global_batch_idx: 42450, batch size: 88, loss[discriminator_loss=2.728, discriminator_real_loss=1.389, discriminator_fake_loss=1.339, generator_loss=27.19, generator_mel_loss=17.9, generator_kl_loss=1.287, generator_dur_loss=1.911, generator_adv_loss=1.989, generator_feat_match_loss=4.104, over 88.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.37, discriminator_fake_loss=1.345, generator_loss=27.73, generator_mel_loss=18.16, generator_kl_loss=1.4, generator_dur_loss=1.766, generator_adv_loss=1.94, generator_feat_match_loss=4.458, over 2366.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 11:07:19,476 INFO [train.py:527] (2/6) Epoch 343, batch 92, global_batch_idx: 42500, batch size: 68, loss[discriminator_loss=2.759, discriminator_real_loss=1.37, discriminator_fake_loss=1.39, generator_loss=28.15, generator_mel_loss=18.25, generator_kl_loss=1.297, generator_dur_loss=1.865, generator_adv_loss=1.967, generator_feat_match_loss=4.767, over 68.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.375, discriminator_fake_loss=1.34, generator_loss=27.71, generator_mel_loss=18.16, generator_kl_loss=1.403, generator_dur_loss=1.775, generator_adv_loss=1.942, generator_feat_match_loss=4.429, over 5371.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 11:08:48,361 INFO [train.py:919] (2/6) Start epoch 344
2024-03-13 11:10:02,092 INFO [train.py:527] (2/6) Epoch 344, batch 18, global_batch_idx: 42550, batch size: 52, loss[discriminator_loss=2.695, discriminator_real_loss=1.447, discriminator_fake_loss=1.248, generator_loss=27.77, generator_mel_loss=18.27, generator_kl_loss=1.455, generator_dur_loss=1.682, generator_adv_loss=1.815, generator_feat_match_loss=4.541, over 52.00 samples.], tot_loss[discriminator_loss=2.711, discriminator_real_loss=1.378, discriminator_fake_loss=1.334, generator_loss=27.89, generator_mel_loss=18.32, generator_kl_loss=1.43, generator_dur_loss=1.767, generator_adv_loss=1.928, generator_feat_match_loss=4.437, over 1118.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 11:12:19,952 INFO [train.py:527] (2/6) Epoch 344, batch 68, global_batch_idx: 42600, batch size: 42, loss[discriminator_loss=2.727, discriminator_real_loss=1.397, discriminator_fake_loss=1.331, generator_loss=27.38, generator_mel_loss=18.2, generator_kl_loss=1.387, generator_dur_loss=1.689, generator_adv_loss=1.867, generator_feat_match_loss=4.239, over 42.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.383, discriminator_fake_loss=1.342, generator_loss=27.68, generator_mel_loss=18.22, generator_kl_loss=1.45, generator_dur_loss=1.741, generator_adv_loss=1.937, generator_feat_match_loss=4.334, over 3614.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 11:12:19,954 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 11:12:27,978 INFO [train.py:591] (2/6) Epoch 344, validation: discriminator_loss=2.744, discriminator_real_loss=1.406, discriminator_fake_loss=1.338, generator_loss=26.36, generator_mel_loss=18.54, generator_kl_loss=1.174, generator_dur_loss=1.827, generator_adv_loss=1.746, generator_feat_match_loss=3.079, over 100.00 samples.
2024-03-13 11:12:27,979 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 11:14:44,671 INFO [train.py:527] (2/6) Epoch 344, batch 118, global_batch_idx: 42650, batch size: 95, loss[discriminator_loss=2.695, discriminator_real_loss=1.437, discriminator_fake_loss=1.258, generator_loss=26.62, generator_mel_loss=17.68, generator_kl_loss=1.11, generator_dur_loss=1.878, generator_adv_loss=1.788, generator_feat_match_loss=4.172, over 95.00 samples.], tot_loss[discriminator_loss=2.732, discriminator_real_loss=1.386, discriminator_fake_loss=1.346, generator_loss=27.78, generator_mel_loss=18.24, generator_kl_loss=1.436, generator_dur_loss=1.758, generator_adv_loss=1.949, generator_feat_match_loss=4.398, over 6482.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 11:15:01,200 INFO [train.py:919] (2/6) Start epoch 345
2024-03-13 11:17:24,181 INFO [train.py:527] (2/6) Epoch 345, batch 44, global_batch_idx: 42700, batch size: 47, loss[discriminator_loss=2.683, discriminator_real_loss=1.397, discriminator_fake_loss=1.286, generator_loss=27.66, generator_mel_loss=17.97, generator_kl_loss=1.452, generator_dur_loss=1.72, generator_adv_loss=1.845, generator_feat_match_loss=4.675, over 47.00 samples.], tot_loss[discriminator_loss=2.722, discriminator_real_loss=1.381, discriminator_fake_loss=1.341, generator_loss=27.53, generator_mel_loss=18.13, generator_kl_loss=1.402, generator_dur_loss=1.767, generator_adv_loss=1.923, generator_feat_match_loss=4.305, over 2475.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 11:19:44,557 INFO [train.py:527] (2/6) Epoch 345, batch 94, global_batch_idx: 42750, batch size: 56, loss[discriminator_loss=2.721, discriminator_real_loss=1.407, discriminator_fake_loss=1.314, generator_loss=27.7, generator_mel_loss=18.47, generator_kl_loss=1.286, generator_dur_loss=1.752, generator_adv_loss=2.047, generator_feat_match_loss=4.154, over 56.00 samples.], tot_loss[discriminator_loss=2.724, discriminator_real_loss=1.376, discriminator_fake_loss=1.349, generator_loss=27.62, generator_mel_loss=18.16, generator_kl_loss=1.406, generator_dur_loss=1.78, generator_adv_loss=1.933, generator_feat_match_loss=4.337, over 5634.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 11:21:04,181 INFO [train.py:919] (2/6) Start epoch 346
2024-03-13 11:22:25,993 INFO [train.py:527] (2/6) Epoch 346, batch 20, global_batch_idx: 42800, batch size: 44, loss[discriminator_loss=2.652, discriminator_real_loss=1.248, discriminator_fake_loss=1.404, generator_loss=28.87, generator_mel_loss=18.62, generator_kl_loss=1.537, generator_dur_loss=1.692, generator_adv_loss=2.044, generator_feat_match_loss=4.973, over 44.00 samples.], tot_loss[discriminator_loss=2.734, discriminator_real_loss=1.383, discriminator_fake_loss=1.351, generator_loss=27.87, generator_mel_loss=18.33, generator_kl_loss=1.437, generator_dur_loss=1.763, generator_adv_loss=1.946, generator_feat_match_loss=4.388, over 1202.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 11:22:25,995 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 11:22:34,314 INFO [train.py:591] (2/6) Epoch 346, validation: discriminator_loss=2.746, discriminator_real_loss=1.451, discriminator_fake_loss=1.295, generator_loss=26.76, generator_mel_loss=18.2, generator_kl_loss=1.215, generator_dur_loss=1.834, generator_adv_loss=1.972, generator_feat_match_loss=3.542, over 100.00 samples.
2024-03-13 11:22:34,331 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 11:24:53,449 INFO [train.py:527] (2/6) Epoch 346, batch 70, global_batch_idx: 42850, batch size: 61, loss[discriminator_loss=2.83, discriminator_real_loss=1.329, discriminator_fake_loss=1.501, generator_loss=27.03, generator_mel_loss=17.93, generator_kl_loss=1.379, generator_dur_loss=1.749, generator_adv_loss=2.031, generator_feat_match_loss=3.949, over 61.00 samples.], tot_loss[discriminator_loss=2.732, discriminator_real_loss=1.382, discriminator_fake_loss=1.351, generator_loss=27.72, generator_mel_loss=18.25, generator_kl_loss=1.402, generator_dur_loss=1.759, generator_adv_loss=1.942, generator_feat_match_loss=4.365, over 4008.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 11:27:09,944 INFO [train.py:527] (2/6) Epoch 346, batch 120, global_batch_idx: 42900, batch size: 96, loss[discriminator_loss=2.748, discriminator_real_loss=1.403, discriminator_fake_loss=1.345, generator_loss=27.71, generator_mel_loss=18.22, generator_kl_loss=1.296, generator_dur_loss=1.867, generator_adv_loss=1.916, generator_feat_match_loss=4.414, over 96.00 samples.], tot_loss[discriminator_loss=2.731, discriminator_real_loss=1.385, discriminator_fake_loss=1.346, generator_loss=27.71, generator_mel_loss=18.23, generator_kl_loss=1.398, generator_dur_loss=1.763, generator_adv_loss=1.935, generator_feat_match_loss=4.383, over 6894.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 11:27:21,140 INFO [train.py:919] (2/6) Start epoch 347
2024-03-13 11:29:52,484 INFO [train.py:527] (2/6) Epoch 347, batch 46, global_batch_idx: 42950, batch size: 70, loss[discriminator_loss=2.869, discriminator_real_loss=1.322, discriminator_fake_loss=1.547, generator_loss=27.29, generator_mel_loss=17.92, generator_kl_loss=1.291, generator_dur_loss=1.828, generator_adv_loss=2.113, generator_feat_match_loss=4.142, over 70.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.383, discriminator_fake_loss=1.343, generator_loss=27.61, generator_mel_loss=18.13, generator_kl_loss=1.413, generator_dur_loss=1.737, generator_adv_loss=1.942, generator_feat_match_loss=4.393, over 2820.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 11:32:12,672 INFO [train.py:527] (2/6) Epoch 347, batch 96, global_batch_idx: 43000, batch size: 48, loss[discriminator_loss=2.815, discriminator_real_loss=1.481, discriminator_fake_loss=1.333, generator_loss=27.72, generator_mel_loss=17.72, generator_kl_loss=1.484, generator_dur_loss=1.688, generator_adv_loss=2.252, generator_feat_match_loss=4.568, over 48.00 samples.], tot_loss[discriminator_loss=2.734, discriminator_real_loss=1.386, discriminator_fake_loss=1.348, generator_loss=27.68, generator_mel_loss=18.19, generator_kl_loss=1.418, generator_dur_loss=1.747, generator_adv_loss=1.937, generator_feat_match_loss=4.386, over 5717.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 11:32:12,674 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 11:32:21,589 INFO [train.py:591] (2/6) Epoch 347, validation: discriminator_loss=2.924, discriminator_real_loss=1.778, discriminator_fake_loss=1.146, generator_loss=26.77, generator_mel_loss=18.36, generator_kl_loss=1.268, generator_dur_loss=1.8, generator_adv_loss=2.294, generator_feat_match_loss=3.051, over 100.00 samples.
2024-03-13 11:32:21,590 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 11:33:37,250 INFO [train.py:919] (2/6) Start epoch 348
2024-03-13 11:35:02,268 INFO [train.py:527] (2/6) Epoch 348, batch 22, global_batch_idx: 43050, batch size: 47, loss[discriminator_loss=2.701, discriminator_real_loss=1.322, discriminator_fake_loss=1.379, generator_loss=27.85, generator_mel_loss=18.2, generator_kl_loss=1.347, generator_dur_loss=1.731, generator_adv_loss=1.853, generator_feat_match_loss=4.722, over 47.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.364, discriminator_fake_loss=1.35, generator_loss=27.71, generator_mel_loss=18.12, generator_kl_loss=1.387, generator_dur_loss=1.775, generator_adv_loss=1.931, generator_feat_match_loss=4.491, over 1337.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 11:37:23,124 INFO [train.py:527] (2/6) Epoch 348, batch 72, global_batch_idx: 43100, batch size: 88, loss[discriminator_loss=2.729, discriminator_real_loss=1.377, discriminator_fake_loss=1.351, generator_loss=27.9, generator_mel_loss=18.14, generator_kl_loss=1.348, generator_dur_loss=1.781, generator_adv_loss=1.887, generator_feat_match_loss=4.748, over 88.00 samples.], tot_loss[discriminator_loss=2.714, discriminator_real_loss=1.374, discriminator_fake_loss=1.34, generator_loss=27.76, generator_mel_loss=18.18, generator_kl_loss=1.4, generator_dur_loss=1.767, generator_adv_loss=1.951, generator_feat_match_loss=4.465, over 4170.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 11:39:39,551 INFO [train.py:527] (2/6) Epoch 348, batch 122, global_batch_idx: 43150, batch size: 56, loss[discriminator_loss=2.734, discriminator_real_loss=1.416, discriminator_fake_loss=1.318, generator_loss=27.61, generator_mel_loss=18.34, generator_kl_loss=1.297, generator_dur_loss=1.789, generator_adv_loss=1.835, generator_feat_match_loss=4.349, over 56.00 samples.], tot_loss[discriminator_loss=2.721, discriminator_real_loss=1.378, discriminator_fake_loss=1.342, generator_loss=27.76, generator_mel_loss=18.18, generator_kl_loss=1.408, generator_dur_loss=1.761, generator_adv_loss=1.944, generator_feat_match_loss=4.464, over 6957.00 samples.], cur_lr_g: 1.92e-04, cur_lr_d: 1.92e-04, 
2024-03-13 11:39:44,869 INFO [train.py:919] (2/6) Start epoch 349
2024-03-13 11:42:24,552 INFO [train.py:527] (2/6) Epoch 349, batch 48, global_batch_idx: 43200, batch size: 58, loss[discriminator_loss=2.727, discriminator_real_loss=1.323, discriminator_fake_loss=1.404, generator_loss=27.04, generator_mel_loss=17.51, generator_kl_loss=1.353, generator_dur_loss=1.694, generator_adv_loss=2.065, generator_feat_match_loss=4.418, over 58.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.379, discriminator_fake_loss=1.337, generator_loss=27.75, generator_mel_loss=18.17, generator_kl_loss=1.404, generator_dur_loss=1.763, generator_adv_loss=1.941, generator_feat_match_loss=4.473, over 2943.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 11:42:24,554 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 11:42:32,519 INFO [train.py:591] (2/6) Epoch 349, validation: discriminator_loss=2.758, discriminator_real_loss=1.504, discriminator_fake_loss=1.254, generator_loss=26.15, generator_mel_loss=18.04, generator_kl_loss=1.188, generator_dur_loss=1.785, generator_adv_loss=1.958, generator_feat_match_loss=3.174, over 100.00 samples.
2024-03-13 11:42:32,519 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 11:44:52,717 INFO [train.py:527] (2/6) Epoch 349, batch 98, global_batch_idx: 43250, batch size: 39, loss[discriminator_loss=2.746, discriminator_real_loss=1.445, discriminator_fake_loss=1.301, generator_loss=27.5, generator_mel_loss=18.3, generator_kl_loss=1.447, generator_dur_loss=1.684, generator_adv_loss=1.804, generator_feat_match_loss=4.266, over 39.00 samples.], tot_loss[discriminator_loss=2.722, discriminator_real_loss=1.378, discriminator_fake_loss=1.344, generator_loss=27.82, generator_mel_loss=18.21, generator_kl_loss=1.419, generator_dur_loss=1.755, generator_adv_loss=1.934, generator_feat_match_loss=4.499, over 5838.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 11:46:04,258 INFO [train.py:919] (2/6) Start epoch 350
2024-03-13 11:47:37,403 INFO [train.py:527] (2/6) Epoch 350, batch 24, global_batch_idx: 43300, batch size: 58, loss[discriminator_loss=2.781, discriminator_real_loss=1.46, discriminator_fake_loss=1.322, generator_loss=28.31, generator_mel_loss=18.77, generator_kl_loss=1.566, generator_dur_loss=1.758, generator_adv_loss=1.667, generator_feat_match_loss=4.556, over 58.00 samples.], tot_loss[discriminator_loss=2.731, discriminator_real_loss=1.401, discriminator_fake_loss=1.33, generator_loss=27.66, generator_mel_loss=18.21, generator_kl_loss=1.392, generator_dur_loss=1.753, generator_adv_loss=1.937, generator_feat_match_loss=4.367, over 1407.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 11:49:58,928 INFO [train.py:527] (2/6) Epoch 350, batch 74, global_batch_idx: 43350, batch size: 62, loss[discriminator_loss=2.747, discriminator_real_loss=1.359, discriminator_fake_loss=1.388, generator_loss=27.4, generator_mel_loss=18.19, generator_kl_loss=1.367, generator_dur_loss=1.768, generator_adv_loss=1.92, generator_feat_match_loss=4.152, over 62.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.382, discriminator_fake_loss=1.344, generator_loss=27.7, generator_mel_loss=18.21, generator_kl_loss=1.403, generator_dur_loss=1.752, generator_adv_loss=1.94, generator_feat_match_loss=4.4, over 4279.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 11:52:17,020 INFO [train.py:919] (2/6) Start epoch 351
2024-03-13 11:52:41,767 INFO [train.py:527] (2/6) Epoch 351, batch 0, global_batch_idx: 43400, batch size: 61, loss[discriminator_loss=2.72, discriminator_real_loss=1.309, discriminator_fake_loss=1.411, generator_loss=28.16, generator_mel_loss=18.13, generator_kl_loss=1.399, generator_dur_loss=1.752, generator_adv_loss=2.028, generator_feat_match_loss=4.859, over 61.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.309, discriminator_fake_loss=1.411, generator_loss=28.16, generator_mel_loss=18.13, generator_kl_loss=1.399, generator_dur_loss=1.752, generator_adv_loss=2.028, generator_feat_match_loss=4.859, over 61.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 11:52:41,770 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 11:52:49,648 INFO [train.py:591] (2/6) Epoch 351, validation: discriminator_loss=2.765, discriminator_real_loss=1.506, discriminator_fake_loss=1.26, generator_loss=26.69, generator_mel_loss=18.17, generator_kl_loss=1.219, generator_dur_loss=1.83, generator_adv_loss=1.985, generator_feat_match_loss=3.495, over 100.00 samples.
2024-03-13 11:52:49,650 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 11:55:12,262 INFO [train.py:527] (2/6) Epoch 351, batch 50, global_batch_idx: 43450, batch size: 59, loss[discriminator_loss=2.734, discriminator_real_loss=1.395, discriminator_fake_loss=1.338, generator_loss=27.27, generator_mel_loss=17.98, generator_kl_loss=1.504, generator_dur_loss=1.76, generator_adv_loss=1.919, generator_feat_match_loss=4.1, over 59.00 samples.], tot_loss[discriminator_loss=2.729, discriminator_real_loss=1.381, discriminator_fake_loss=1.348, generator_loss=27.76, generator_mel_loss=18.15, generator_kl_loss=1.439, generator_dur_loss=1.769, generator_adv_loss=1.94, generator_feat_match_loss=4.467, over 2944.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 11:57:34,592 INFO [train.py:527] (2/6) Epoch 351, batch 100, global_batch_idx: 43500, batch size: 68, loss[discriminator_loss=2.778, discriminator_real_loss=1.368, discriminator_fake_loss=1.41, generator_loss=28.21, generator_mel_loss=18.25, generator_kl_loss=1.411, generator_dur_loss=1.811, generator_adv_loss=1.96, generator_feat_match_loss=4.778, over 68.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.381, discriminator_fake_loss=1.345, generator_loss=27.71, generator_mel_loss=18.16, generator_kl_loss=1.437, generator_dur_loss=1.755, generator_adv_loss=1.938, generator_feat_match_loss=4.419, over 5709.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 11:58:40,016 INFO [train.py:919] (2/6) Start epoch 352
2024-03-13 12:00:19,357 INFO [train.py:527] (2/6) Epoch 352, batch 26, global_batch_idx: 43550, batch size: 96, loss[discriminator_loss=2.754, discriminator_real_loss=1.435, discriminator_fake_loss=1.319, generator_loss=27.73, generator_mel_loss=18.48, generator_kl_loss=1.222, generator_dur_loss=1.84, generator_adv_loss=1.791, generator_feat_match_loss=4.396, over 96.00 samples.], tot_loss[discriminator_loss=2.722, discriminator_real_loss=1.378, discriminator_fake_loss=1.344, generator_loss=27.61, generator_mel_loss=18.16, generator_kl_loss=1.384, generator_dur_loss=1.775, generator_adv_loss=1.908, generator_feat_match_loss=4.383, over 1712.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 12:02:40,173 INFO [train.py:527] (2/6) Epoch 352, batch 76, global_batch_idx: 43600, batch size: 64, loss[discriminator_loss=2.675, discriminator_real_loss=1.356, discriminator_fake_loss=1.319, generator_loss=27.87, generator_mel_loss=18.23, generator_kl_loss=1.28, generator_dur_loss=1.745, generator_adv_loss=2.007, generator_feat_match_loss=4.614, over 64.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.377, discriminator_fake_loss=1.349, generator_loss=27.64, generator_mel_loss=18.15, generator_kl_loss=1.406, generator_dur_loss=1.756, generator_adv_loss=1.923, generator_feat_match_loss=4.406, over 4506.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 12:02:40,174 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 12:02:48,186 INFO [train.py:591] (2/6) Epoch 352, validation: discriminator_loss=2.794, discriminator_real_loss=1.464, discriminator_fake_loss=1.33, generator_loss=26.55, generator_mel_loss=18.12, generator_kl_loss=1.187, generator_dur_loss=1.813, generator_adv_loss=1.878, generator_feat_match_loss=3.552, over 100.00 samples.
2024-03-13 12:02:48,186 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 12:05:04,088 INFO [train.py:919] (2/6) Start epoch 353
2024-03-13 12:05:34,570 INFO [train.py:527] (2/6) Epoch 353, batch 2, global_batch_idx: 43650, batch size: 62, loss[discriminator_loss=2.714, discriminator_real_loss=1.357, discriminator_fake_loss=1.357, generator_loss=28.27, generator_mel_loss=18.43, generator_kl_loss=1.36, generator_dur_loss=1.766, generator_adv_loss=2.036, generator_feat_match_loss=4.678, over 62.00 samples.], tot_loss[discriminator_loss=2.737, discriminator_real_loss=1.409, discriminator_fake_loss=1.328, generator_loss=27.83, generator_mel_loss=18.28, generator_kl_loss=1.476, generator_dur_loss=1.749, generator_adv_loss=1.933, generator_feat_match_loss=4.387, over 167.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 12:07:55,276 INFO [train.py:527] (2/6) Epoch 353, batch 52, global_batch_idx: 43700, batch size: 72, loss[discriminator_loss=2.669, discriminator_real_loss=1.312, discriminator_fake_loss=1.358, generator_loss=28.8, generator_mel_loss=18.36, generator_kl_loss=1.49, generator_dur_loss=1.829, generator_adv_loss=2.028, generator_feat_match_loss=5.095, over 72.00 samples.], tot_loss[discriminator_loss=2.727, discriminator_real_loss=1.381, discriminator_fake_loss=1.346, generator_loss=27.75, generator_mel_loss=18.21, generator_kl_loss=1.417, generator_dur_loss=1.775, generator_adv_loss=1.938, generator_feat_match_loss=4.415, over 2929.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 12:10:16,728 INFO [train.py:527] (2/6) Epoch 353, batch 102, global_batch_idx: 43750, batch size: 48, loss[discriminator_loss=2.635, discriminator_real_loss=1.307, discriminator_fake_loss=1.328, generator_loss=28.77, generator_mel_loss=18.9, generator_kl_loss=1.556, generator_dur_loss=1.698, generator_adv_loss=2.017, generator_feat_match_loss=4.598, over 48.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.376, discriminator_fake_loss=1.35, generator_loss=27.76, generator_mel_loss=18.19, generator_kl_loss=1.42, generator_dur_loss=1.771, generator_adv_loss=1.938, generator_feat_match_loss=4.448, over 5781.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 12:11:16,764 INFO [train.py:919] (2/6) Start epoch 354
2024-03-13 12:13:03,022 INFO [train.py:527] (2/6) Epoch 354, batch 28, global_batch_idx: 43800, batch size: 55, loss[discriminator_loss=2.709, discriminator_real_loss=1.317, discriminator_fake_loss=1.392, generator_loss=28.16, generator_mel_loss=18.49, generator_kl_loss=1.523, generator_dur_loss=1.734, generator_adv_loss=1.914, generator_feat_match_loss=4.498, over 55.00 samples.], tot_loss[discriminator_loss=2.721, discriminator_real_loss=1.377, discriminator_fake_loss=1.344, generator_loss=27.75, generator_mel_loss=18.16, generator_kl_loss=1.415, generator_dur_loss=1.774, generator_adv_loss=1.928, generator_feat_match_loss=4.473, over 1755.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 12:13:03,025 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 12:13:11,068 INFO [train.py:591] (2/6) Epoch 354, validation: discriminator_loss=2.739, discriminator_real_loss=1.403, discriminator_fake_loss=1.335, generator_loss=26.52, generator_mel_loss=18.09, generator_kl_loss=1.258, generator_dur_loss=1.833, generator_adv_loss=1.868, generator_feat_match_loss=3.472, over 100.00 samples.
2024-03-13 12:13:11,069 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 12:15:30,947 INFO [train.py:527] (2/6) Epoch 354, batch 78, global_batch_idx: 43850, batch size: 74, loss[discriminator_loss=2.711, discriminator_real_loss=1.416, discriminator_fake_loss=1.295, generator_loss=27.39, generator_mel_loss=18, generator_kl_loss=1.321, generator_dur_loss=1.836, generator_adv_loss=1.913, generator_feat_match_loss=4.319, over 74.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.377, discriminator_fake_loss=1.343, generator_loss=27.71, generator_mel_loss=18.14, generator_kl_loss=1.418, generator_dur_loss=1.772, generator_adv_loss=1.933, generator_feat_match_loss=4.444, over 4589.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 12:17:38,575 INFO [train.py:919] (2/6) Start epoch 355
2024-03-13 12:18:15,376 INFO [train.py:527] (2/6) Epoch 355, batch 4, global_batch_idx: 43900, batch size: 44, loss[discriminator_loss=2.634, discriminator_real_loss=1.224, discriminator_fake_loss=1.41, generator_loss=28.89, generator_mel_loss=18.44, generator_kl_loss=1.439, generator_dur_loss=1.679, generator_adv_loss=2.073, generator_feat_match_loss=5.256, over 44.00 samples.], tot_loss[discriminator_loss=2.683, discriminator_real_loss=1.372, discriminator_fake_loss=1.311, generator_loss=27.67, generator_mel_loss=18.03, generator_kl_loss=1.429, generator_dur_loss=1.76, generator_adv_loss=1.966, generator_feat_match_loss=4.492, over 276.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 12:20:37,083 INFO [train.py:527] (2/6) Epoch 355, batch 54, global_batch_idx: 43950, batch size: 15, loss[discriminator_loss=2.596, discriminator_real_loss=1.259, discriminator_fake_loss=1.337, generator_loss=29.53, generator_mel_loss=18.86, generator_kl_loss=1.67, generator_dur_loss=1.556, generator_adv_loss=1.943, generator_feat_match_loss=5.504, over 15.00 samples.], tot_loss[discriminator_loss=2.713, discriminator_real_loss=1.373, discriminator_fake_loss=1.34, generator_loss=27.81, generator_mel_loss=18.18, generator_kl_loss=1.419, generator_dur_loss=1.764, generator_adv_loss=1.943, generator_feat_match_loss=4.501, over 3075.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 12:23:01,865 INFO [train.py:527] (2/6) Epoch 355, batch 104, global_batch_idx: 44000, batch size: 47, loss[discriminator_loss=2.695, discriminator_real_loss=1.27, discriminator_fake_loss=1.425, generator_loss=27.57, generator_mel_loss=17.97, generator_kl_loss=1.475, generator_dur_loss=1.722, generator_adv_loss=2.084, generator_feat_match_loss=4.315, over 47.00 samples.], tot_loss[discriminator_loss=2.722, discriminator_real_loss=1.378, discriminator_fake_loss=1.344, generator_loss=27.82, generator_mel_loss=18.2, generator_kl_loss=1.421, generator_dur_loss=1.76, generator_adv_loss=1.951, generator_feat_match_loss=4.485, over 5905.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 12:23:01,867 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 12:23:10,647 INFO [train.py:591] (2/6) Epoch 355, validation: discriminator_loss=2.771, discriminator_real_loss=1.539, discriminator_fake_loss=1.233, generator_loss=26.44, generator_mel_loss=17.91, generator_kl_loss=1.252, generator_dur_loss=1.84, generator_adv_loss=2.006, generator_feat_match_loss=3.429, over 100.00 samples.
2024-03-13 12:23:10,648 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 12:24:02,377 INFO [train.py:919] (2/6) Start epoch 356
2024-03-13 12:25:51,545 INFO [train.py:527] (2/6) Epoch 356, batch 30, global_batch_idx: 44050, batch size: 53, loss[discriminator_loss=2.766, discriminator_real_loss=1.413, discriminator_fake_loss=1.352, generator_loss=27.52, generator_mel_loss=18.18, generator_kl_loss=1.506, generator_dur_loss=1.693, generator_adv_loss=1.82, generator_feat_match_loss=4.32, over 53.00 samples.], tot_loss[discriminator_loss=2.734, discriminator_real_loss=1.382, discriminator_fake_loss=1.352, generator_loss=27.63, generator_mel_loss=18.09, generator_kl_loss=1.412, generator_dur_loss=1.78, generator_adv_loss=1.915, generator_feat_match_loss=4.428, over 1754.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 12:28:09,436 INFO [train.py:527] (2/6) Epoch 356, batch 80, global_batch_idx: 44100, batch size: 59, loss[discriminator_loss=2.791, discriminator_real_loss=1.49, discriminator_fake_loss=1.301, generator_loss=26.64, generator_mel_loss=17.76, generator_kl_loss=1.426, generator_dur_loss=1.748, generator_adv_loss=1.726, generator_feat_match_loss=3.978, over 59.00 samples.], tot_loss[discriminator_loss=2.721, discriminator_real_loss=1.371, discriminator_fake_loss=1.349, generator_loss=27.61, generator_mel_loss=18.09, generator_kl_loss=1.388, generator_dur_loss=1.783, generator_adv_loss=1.915, generator_feat_match_loss=4.429, over 4883.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 12:30:10,632 INFO [train.py:919] (2/6) Start epoch 357
2024-03-13 12:30:50,313 INFO [train.py:527] (2/6) Epoch 357, batch 6, global_batch_idx: 44150, batch size: 62, loss[discriminator_loss=2.795, discriminator_real_loss=1.55, discriminator_fake_loss=1.245, generator_loss=27.51, generator_mel_loss=18.18, generator_kl_loss=1.344, generator_dur_loss=1.778, generator_adv_loss=1.878, generator_feat_match_loss=4.333, over 62.00 samples.], tot_loss[discriminator_loss=2.75, discriminator_real_loss=1.401, discriminator_fake_loss=1.349, generator_loss=27.65, generator_mel_loss=18.14, generator_kl_loss=1.468, generator_dur_loss=1.736, generator_adv_loss=1.928, generator_feat_match_loss=4.373, over 332.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 12:33:13,616 INFO [train.py:527] (2/6) Epoch 357, batch 56, global_batch_idx: 44200, batch size: 66, loss[discriminator_loss=2.727, discriminator_real_loss=1.314, discriminator_fake_loss=1.413, generator_loss=27.71, generator_mel_loss=18, generator_kl_loss=1.367, generator_dur_loss=1.766, generator_adv_loss=2.056, generator_feat_match_loss=4.521, over 66.00 samples.], tot_loss[discriminator_loss=2.73, discriminator_real_loss=1.382, discriminator_fake_loss=1.349, generator_loss=27.64, generator_mel_loss=18.17, generator_kl_loss=1.418, generator_dur_loss=1.756, generator_adv_loss=1.91, generator_feat_match_loss=4.392, over 3168.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 12:33:13,617 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 12:33:21,457 INFO [train.py:591] (2/6) Epoch 357, validation: discriminator_loss=2.821, discriminator_real_loss=1.547, discriminator_fake_loss=1.274, generator_loss=26.95, generator_mel_loss=18.57, generator_kl_loss=1.318, generator_dur_loss=1.801, generator_adv_loss=1.969, generator_feat_match_loss=3.285, over 100.00 samples.
2024-03-13 12:33:21,458 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 12:35:40,714 INFO [train.py:527] (2/6) Epoch 357, batch 106, global_batch_idx: 44250, batch size: 62, loss[discriminator_loss=2.733, discriminator_real_loss=1.305, discriminator_fake_loss=1.428, generator_loss=28.69, generator_mel_loss=18.33, generator_kl_loss=1.37, generator_dur_loss=1.786, generator_adv_loss=2.307, generator_feat_match_loss=4.896, over 62.00 samples.], tot_loss[discriminator_loss=2.732, discriminator_real_loss=1.381, discriminator_fake_loss=1.35, generator_loss=27.66, generator_mel_loss=18.18, generator_kl_loss=1.41, generator_dur_loss=1.759, generator_adv_loss=1.92, generator_feat_match_loss=4.39, over 5940.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 12:36:29,328 INFO [train.py:919] (2/6) Start epoch 358
2024-03-13 12:38:26,705 INFO [train.py:527] (2/6) Epoch 358, batch 32, global_batch_idx: 44300, batch size: 55, loss[discriminator_loss=2.696, discriminator_real_loss=1.398, discriminator_fake_loss=1.297, generator_loss=27.85, generator_mel_loss=18.32, generator_kl_loss=1.596, generator_dur_loss=1.671, generator_adv_loss=1.934, generator_feat_match_loss=4.328, over 55.00 samples.], tot_loss[discriminator_loss=2.735, discriminator_real_loss=1.389, discriminator_fake_loss=1.346, generator_loss=27.71, generator_mel_loss=18.13, generator_kl_loss=1.415, generator_dur_loss=1.759, generator_adv_loss=1.926, generator_feat_match_loss=4.485, over 1850.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 12:40:48,021 INFO [train.py:527] (2/6) Epoch 358, batch 82, global_batch_idx: 44350, batch size: 53, loss[discriminator_loss=2.779, discriminator_real_loss=1.411, discriminator_fake_loss=1.368, generator_loss=26.76, generator_mel_loss=17.82, generator_kl_loss=1.479, generator_dur_loss=1.695, generator_adv_loss=1.928, generator_feat_match_loss=3.844, over 53.00 samples.], tot_loss[discriminator_loss=2.73, discriminator_real_loss=1.382, discriminator_fake_loss=1.348, generator_loss=27.71, generator_mel_loss=18.14, generator_kl_loss=1.442, generator_dur_loss=1.746, generator_adv_loss=1.928, generator_feat_match_loss=4.453, over 4485.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 12:42:42,829 INFO [train.py:919] (2/6) Start epoch 359
2024-03-13 12:43:29,873 INFO [train.py:527] (2/6) Epoch 359, batch 8, global_batch_idx: 44400, batch size: 45, loss[discriminator_loss=2.762, discriminator_real_loss=1.35, discriminator_fake_loss=1.412, generator_loss=27.62, generator_mel_loss=18.05, generator_kl_loss=1.514, generator_dur_loss=1.677, generator_adv_loss=1.992, generator_feat_match_loss=4.391, over 45.00 samples.], tot_loss[discriminator_loss=2.744, discriminator_real_loss=1.38, discriminator_fake_loss=1.365, generator_loss=27.63, generator_mel_loss=18.21, generator_kl_loss=1.364, generator_dur_loss=1.744, generator_adv_loss=1.908, generator_feat_match_loss=4.398, over 503.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 12:43:29,876 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 12:43:37,894 INFO [train.py:591] (2/6) Epoch 359, validation: discriminator_loss=2.795, discriminator_real_loss=1.503, discriminator_fake_loss=1.292, generator_loss=27.33, generator_mel_loss=18.38, generator_kl_loss=1.276, generator_dur_loss=1.823, generator_adv_loss=1.984, generator_feat_match_loss=3.863, over 100.00 samples.
2024-03-13 12:43:37,896 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 12:45:59,830 INFO [train.py:527] (2/6) Epoch 359, batch 58, global_batch_idx: 44450, batch size: 66, loss[discriminator_loss=2.725, discriminator_real_loss=1.414, discriminator_fake_loss=1.311, generator_loss=26.69, generator_mel_loss=17.69, generator_kl_loss=1.272, generator_dur_loss=1.811, generator_adv_loss=1.88, generator_feat_match_loss=4.043, over 66.00 samples.], tot_loss[discriminator_loss=2.729, discriminator_real_loss=1.388, discriminator_fake_loss=1.341, generator_loss=27.58, generator_mel_loss=18.1, generator_kl_loss=1.414, generator_dur_loss=1.74, generator_adv_loss=1.926, generator_feat_match_loss=4.402, over 3351.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 12:48:21,901 INFO [train.py:527] (2/6) Epoch 359, batch 108, global_batch_idx: 44500, batch size: 53, loss[discriminator_loss=2.78, discriminator_real_loss=1.522, discriminator_fake_loss=1.258, generator_loss=27.31, generator_mel_loss=18.21, generator_kl_loss=1.505, generator_dur_loss=1.678, generator_adv_loss=1.918, generator_feat_match_loss=3.995, over 53.00 samples.], tot_loss[discriminator_loss=2.721, discriminator_real_loss=1.38, discriminator_fake_loss=1.341, generator_loss=27.7, generator_mel_loss=18.15, generator_kl_loss=1.413, generator_dur_loss=1.747, generator_adv_loss=1.932, generator_feat_match_loss=4.457, over 6269.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 12:49:04,215 INFO [train.py:919] (2/6) Start epoch 360
2024-03-13 12:51:04,575 INFO [train.py:527] (2/6) Epoch 360, batch 34, global_batch_idx: 44550, batch size: 48, loss[discriminator_loss=2.67, discriminator_real_loss=1.35, discriminator_fake_loss=1.32, generator_loss=27.16, generator_mel_loss=17.48, generator_kl_loss=1.423, generator_dur_loss=1.674, generator_adv_loss=1.922, generator_feat_match_loss=4.656, over 48.00 samples.], tot_loss[discriminator_loss=2.723, discriminator_real_loss=1.386, discriminator_fake_loss=1.337, generator_loss=27.54, generator_mel_loss=18.08, generator_kl_loss=1.411, generator_dur_loss=1.752, generator_adv_loss=1.941, generator_feat_match_loss=4.349, over 1974.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 12:53:25,932 INFO [train.py:527] (2/6) Epoch 360, batch 84, global_batch_idx: 44600, batch size: 70, loss[discriminator_loss=2.781, discriminator_real_loss=1.55, discriminator_fake_loss=1.231, generator_loss=26.73, generator_mel_loss=17.64, generator_kl_loss=1.208, generator_dur_loss=1.833, generator_adv_loss=1.877, generator_feat_match_loss=4.17, over 70.00 samples.], tot_loss[discriminator_loss=2.721, discriminator_real_loss=1.377, discriminator_fake_loss=1.344, generator_loss=27.66, generator_mel_loss=18.12, generator_kl_loss=1.414, generator_dur_loss=1.758, generator_adv_loss=1.937, generator_feat_match_loss=4.435, over 4951.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 12:53:25,934 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 12:53:34,615 INFO [train.py:591] (2/6) Epoch 360, validation: discriminator_loss=2.725, discriminator_real_loss=1.361, discriminator_fake_loss=1.365, generator_loss=26.64, generator_mel_loss=17.88, generator_kl_loss=1.22, generator_dur_loss=1.823, generator_adv_loss=1.872, generator_feat_match_loss=3.841, over 100.00 samples.
2024-03-13 12:53:34,616 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 12:55:25,057 INFO [train.py:919] (2/6) Start epoch 361
2024-03-13 12:56:21,985 INFO [train.py:527] (2/6) Epoch 361, batch 10, global_batch_idx: 44650, batch size: 44, loss[discriminator_loss=2.748, discriminator_real_loss=1.376, discriminator_fake_loss=1.373, generator_loss=27.59, generator_mel_loss=18.2, generator_kl_loss=1.509, generator_dur_loss=1.669, generator_adv_loss=1.977, generator_feat_match_loss=4.229, over 44.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.387, discriminator_fake_loss=1.333, generator_loss=27.71, generator_mel_loss=18.17, generator_kl_loss=1.452, generator_dur_loss=1.761, generator_adv_loss=1.939, generator_feat_match_loss=4.38, over 599.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 12:58:43,215 INFO [train.py:527] (2/6) Epoch 361, batch 60, global_batch_idx: 44700, batch size: 70, loss[discriminator_loss=2.703, discriminator_real_loss=1.347, discriminator_fake_loss=1.356, generator_loss=27.36, generator_mel_loss=17.8, generator_kl_loss=1.194, generator_dur_loss=1.803, generator_adv_loss=2.022, generator_feat_match_loss=4.541, over 70.00 samples.], tot_loss[discriminator_loss=2.722, discriminator_real_loss=1.383, discriminator_fake_loss=1.339, generator_loss=27.83, generator_mel_loss=18.18, generator_kl_loss=1.446, generator_dur_loss=1.755, generator_adv_loss=1.937, generator_feat_match_loss=4.511, over 3262.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 13:01:03,686 INFO [train.py:527] (2/6) Epoch 361, batch 110, global_batch_idx: 44750, batch size: 62, loss[discriminator_loss=2.707, discriminator_real_loss=1.473, discriminator_fake_loss=1.234, generator_loss=27.17, generator_mel_loss=17.92, generator_kl_loss=1.362, generator_dur_loss=1.782, generator_adv_loss=1.883, generator_feat_match_loss=4.22, over 62.00 samples.], tot_loss[discriminator_loss=2.719, discriminator_real_loss=1.377, discriminator_fake_loss=1.342, generator_loss=27.82, generator_mel_loss=18.19, generator_kl_loss=1.43, generator_dur_loss=1.757, generator_adv_loss=1.938, generator_feat_match_loss=4.502, over 6084.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 13:01:41,530 INFO [train.py:919] (2/6) Start epoch 362
2024-03-13 13:03:46,687 INFO [train.py:527] (2/6) Epoch 362, batch 36, global_batch_idx: 44800, batch size: 70, loss[discriminator_loss=2.698, discriminator_real_loss=1.354, discriminator_fake_loss=1.344, generator_loss=27.85, generator_mel_loss=18.3, generator_kl_loss=1.276, generator_dur_loss=1.817, generator_adv_loss=1.944, generator_feat_match_loss=4.511, over 70.00 samples.], tot_loss[discriminator_loss=2.705, discriminator_real_loss=1.373, discriminator_fake_loss=1.332, generator_loss=27.67, generator_mel_loss=18.17, generator_kl_loss=1.426, generator_dur_loss=1.736, generator_adv_loss=1.941, generator_feat_match_loss=4.405, over 1920.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 13:03:46,689 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 13:03:54,777 INFO [train.py:591] (2/6) Epoch 362, validation: discriminator_loss=2.702, discriminator_real_loss=1.446, discriminator_fake_loss=1.256, generator_loss=27.42, generator_mel_loss=18.5, generator_kl_loss=1.251, generator_dur_loss=1.811, generator_adv_loss=1.942, generator_feat_match_loss=3.917, over 100.00 samples.
2024-03-13 13:03:54,779 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 13:06:14,505 INFO [train.py:527] (2/6) Epoch 362, batch 86, global_batch_idx: 44850, batch size: 39, loss[discriminator_loss=2.728, discriminator_real_loss=1.308, discriminator_fake_loss=1.42, generator_loss=29.02, generator_mel_loss=18.38, generator_kl_loss=1.74, generator_dur_loss=1.726, generator_adv_loss=2.016, generator_feat_match_loss=5.157, over 39.00 samples.], tot_loss[discriminator_loss=2.712, discriminator_real_loss=1.375, discriminator_fake_loss=1.337, generator_loss=27.71, generator_mel_loss=18.16, generator_kl_loss=1.418, generator_dur_loss=1.731, generator_adv_loss=1.944, generator_feat_match_loss=4.456, over 4770.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 13:08:03,531 INFO [train.py:919] (2/6) Start epoch 363
2024-03-13 13:09:03,646 INFO [train.py:527] (2/6) Epoch 363, batch 12, global_batch_idx: 44900, batch size: 42, loss[discriminator_loss=2.691, discriminator_real_loss=1.324, discriminator_fake_loss=1.367, generator_loss=27.6, generator_mel_loss=17.95, generator_kl_loss=1.427, generator_dur_loss=1.65, generator_adv_loss=2.023, generator_feat_match_loss=4.549, over 42.00 samples.], tot_loss[discriminator_loss=2.744, discriminator_real_loss=1.399, discriminator_fake_loss=1.345, generator_loss=28.09, generator_mel_loss=18.35, generator_kl_loss=1.437, generator_dur_loss=1.732, generator_adv_loss=1.972, generator_feat_match_loss=4.603, over 738.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 13:11:29,973 INFO [train.py:527] (2/6) Epoch 363, batch 62, global_batch_idx: 44950, batch size: 72, loss[discriminator_loss=2.684, discriminator_real_loss=1.338, discriminator_fake_loss=1.346, generator_loss=28.63, generator_mel_loss=18.57, generator_kl_loss=1.548, generator_dur_loss=1.773, generator_adv_loss=2.005, generator_feat_match_loss=4.734, over 72.00 samples.], tot_loss[discriminator_loss=2.738, discriminator_real_loss=1.386, discriminator_fake_loss=1.352, generator_loss=27.72, generator_mel_loss=18.17, generator_kl_loss=1.411, generator_dur_loss=1.738, generator_adv_loss=1.945, generator_feat_match_loss=4.461, over 3743.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 13:13:48,459 INFO [train.py:527] (2/6) Epoch 363, batch 112, global_batch_idx: 45000, batch size: 53, loss[discriminator_loss=2.667, discriminator_real_loss=1.351, discriminator_fake_loss=1.316, generator_loss=28.05, generator_mel_loss=18.17, generator_kl_loss=1.475, generator_dur_loss=1.678, generator_adv_loss=1.951, generator_feat_match_loss=4.78, over 53.00 samples.], tot_loss[discriminator_loss=2.734, discriminator_real_loss=1.383, discriminator_fake_loss=1.351, generator_loss=27.69, generator_mel_loss=18.14, generator_kl_loss=1.41, generator_dur_loss=1.742, generator_adv_loss=1.948, generator_feat_match_loss=4.453, over 6696.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 13:13:48,461 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 13:13:57,313 INFO [train.py:591] (2/6) Epoch 363, validation: discriminator_loss=2.769, discriminator_real_loss=1.475, discriminator_fake_loss=1.294, generator_loss=27.23, generator_mel_loss=18.81, generator_kl_loss=1.246, generator_dur_loss=1.825, generator_adv_loss=1.883, generator_feat_match_loss=3.464, over 100.00 samples.
2024-03-13 13:13:57,314 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 13:14:29,056 INFO [train.py:919] (2/6) Start epoch 364
2024-03-13 13:16:41,317 INFO [train.py:527] (2/6) Epoch 364, batch 38, global_batch_idx: 45050, batch size: 39, loss[discriminator_loss=2.786, discriminator_real_loss=1.422, discriminator_fake_loss=1.364, generator_loss=27.44, generator_mel_loss=18.07, generator_kl_loss=1.621, generator_dur_loss=1.723, generator_adv_loss=1.879, generator_feat_match_loss=4.143, over 39.00 samples.], tot_loss[discriminator_loss=2.731, discriminator_real_loss=1.384, discriminator_fake_loss=1.348, generator_loss=27.73, generator_mel_loss=18.17, generator_kl_loss=1.434, generator_dur_loss=1.753, generator_adv_loss=1.942, generator_feat_match_loss=4.44, over 2177.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 13:19:04,813 INFO [train.py:527] (2/6) Epoch 364, batch 88, global_batch_idx: 45100, batch size: 64, loss[discriminator_loss=2.654, discriminator_real_loss=1.331, discriminator_fake_loss=1.322, generator_loss=28.26, generator_mel_loss=18, generator_kl_loss=1.477, generator_dur_loss=1.835, generator_adv_loss=2.019, generator_feat_match_loss=4.927, over 64.00 samples.], tot_loss[discriminator_loss=2.723, discriminator_real_loss=1.382, discriminator_fake_loss=1.341, generator_loss=27.7, generator_mel_loss=18.14, generator_kl_loss=1.408, generator_dur_loss=1.766, generator_adv_loss=1.936, generator_feat_match_loss=4.451, over 5117.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 13:20:42,584 INFO [train.py:919] (2/6) Start epoch 365
2024-03-13 13:21:47,543 INFO [train.py:527] (2/6) Epoch 365, batch 14, global_batch_idx: 45150, batch size: 66, loss[discriminator_loss=2.761, discriminator_real_loss=1.49, discriminator_fake_loss=1.271, generator_loss=27.5, generator_mel_loss=18.44, generator_kl_loss=1.58, generator_dur_loss=1.768, generator_adv_loss=2.005, generator_feat_match_loss=3.704, over 66.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.364, discriminator_fake_loss=1.351, generator_loss=27.88, generator_mel_loss=18.24, generator_kl_loss=1.467, generator_dur_loss=1.774, generator_adv_loss=1.926, generator_feat_match_loss=4.477, over 861.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 13:24:06,124 INFO [train.py:527] (2/6) Epoch 365, batch 64, global_batch_idx: 45200, batch size: 96, loss[discriminator_loss=2.71, discriminator_real_loss=1.348, discriminator_fake_loss=1.362, generator_loss=27.98, generator_mel_loss=18.04, generator_kl_loss=1.222, generator_dur_loss=1.894, generator_adv_loss=2.013, generator_feat_match_loss=4.812, over 96.00 samples.], tot_loss[discriminator_loss=2.725, discriminator_real_loss=1.377, discriminator_fake_loss=1.348, generator_loss=27.8, generator_mel_loss=18.15, generator_kl_loss=1.428, generator_dur_loss=1.766, generator_adv_loss=1.938, generator_feat_match_loss=4.519, over 3643.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 13:24:06,125 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 13:24:14,060 INFO [train.py:591] (2/6) Epoch 365, validation: discriminator_loss=2.753, discriminator_real_loss=1.471, discriminator_fake_loss=1.282, generator_loss=27.2, generator_mel_loss=18.57, generator_kl_loss=1.177, generator_dur_loss=1.815, generator_adv_loss=1.984, generator_feat_match_loss=3.647, over 100.00 samples.
2024-03-13 13:24:14,062 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 13:26:36,022 INFO [train.py:527] (2/6) Epoch 365, batch 114, global_batch_idx: 45250, batch size: 52, loss[discriminator_loss=2.766, discriminator_real_loss=1.366, discriminator_fake_loss=1.401, generator_loss=26.77, generator_mel_loss=17.62, generator_kl_loss=1.587, generator_dur_loss=1.709, generator_adv_loss=1.717, generator_feat_match_loss=4.137, over 52.00 samples.], tot_loss[discriminator_loss=2.727, discriminator_real_loss=1.379, discriminator_fake_loss=1.349, generator_loss=27.82, generator_mel_loss=18.17, generator_kl_loss=1.42, generator_dur_loss=1.767, generator_adv_loss=1.938, generator_feat_match_loss=4.523, over 6458.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 13:27:02,990 INFO [train.py:919] (2/6) Start epoch 366
2024-03-13 13:29:19,205 INFO [train.py:527] (2/6) Epoch 366, batch 40, global_batch_idx: 45300, batch size: 56, loss[discriminator_loss=2.746, discriminator_real_loss=1.435, discriminator_fake_loss=1.311, generator_loss=27.34, generator_mel_loss=18.4, generator_kl_loss=1.344, generator_dur_loss=1.736, generator_adv_loss=1.887, generator_feat_match_loss=3.978, over 56.00 samples.], tot_loss[discriminator_loss=2.721, discriminator_real_loss=1.379, discriminator_fake_loss=1.342, generator_loss=27.64, generator_mel_loss=18.07, generator_kl_loss=1.421, generator_dur_loss=1.752, generator_adv_loss=1.934, generator_feat_match_loss=4.469, over 2243.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 13:31:38,506 INFO [train.py:527] (2/6) Epoch 366, batch 90, global_batch_idx: 45350, batch size: 64, loss[discriminator_loss=2.745, discriminator_real_loss=1.393, discriminator_fake_loss=1.352, generator_loss=28.26, generator_mel_loss=18.23, generator_kl_loss=1.368, generator_dur_loss=1.762, generator_adv_loss=1.915, generator_feat_match_loss=4.986, over 64.00 samples.], tot_loss[discriminator_loss=2.713, discriminator_real_loss=1.372, discriminator_fake_loss=1.342, generator_loss=27.8, generator_mel_loss=18.13, generator_kl_loss=1.41, generator_dur_loss=1.764, generator_adv_loss=1.95, generator_feat_match_loss=4.55, over 5301.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 13:33:13,429 INFO [train.py:919] (2/6) Start epoch 367
2024-03-13 13:34:23,901 INFO [train.py:527] (2/6) Epoch 367, batch 16, global_batch_idx: 45400, batch size: 31, loss[discriminator_loss=2.716, discriminator_real_loss=1.463, discriminator_fake_loss=1.252, generator_loss=28.45, generator_mel_loss=18.2, generator_kl_loss=1.753, generator_dur_loss=1.588, generator_adv_loss=2.092, generator_feat_match_loss=4.81, over 31.00 samples.], tot_loss[discriminator_loss=2.723, discriminator_real_loss=1.37, discriminator_fake_loss=1.353, generator_loss=27.81, generator_mel_loss=18.03, generator_kl_loss=1.429, generator_dur_loss=1.764, generator_adv_loss=1.943, generator_feat_match_loss=4.637, over 999.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 13:34:23,903 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 13:34:31,915 INFO [train.py:591] (2/6) Epoch 367, validation: discriminator_loss=2.754, discriminator_real_loss=1.484, discriminator_fake_loss=1.269, generator_loss=26.96, generator_mel_loss=18.29, generator_kl_loss=1.187, generator_dur_loss=1.826, generator_adv_loss=1.993, generator_feat_match_loss=3.665, over 100.00 samples.
2024-03-13 13:34:31,916 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 13:36:53,561 INFO [train.py:527] (2/6) Epoch 367, batch 66, global_batch_idx: 45450, batch size: 42, loss[discriminator_loss=2.717, discriminator_real_loss=1.385, discriminator_fake_loss=1.332, generator_loss=27.36, generator_mel_loss=17.8, generator_kl_loss=1.419, generator_dur_loss=1.695, generator_adv_loss=1.966, generator_feat_match_loss=4.481, over 42.00 samples.], tot_loss[discriminator_loss=2.723, discriminator_real_loss=1.371, discriminator_fake_loss=1.352, generator_loss=27.87, generator_mel_loss=18.13, generator_kl_loss=1.428, generator_dur_loss=1.771, generator_adv_loss=1.949, generator_feat_match_loss=4.591, over 3919.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 13:39:09,498 INFO [train.py:527] (2/6) Epoch 367, batch 116, global_batch_idx: 45500, batch size: 70, loss[discriminator_loss=2.73, discriminator_real_loss=1.368, discriminator_fake_loss=1.362, generator_loss=27.32, generator_mel_loss=18.15, generator_kl_loss=1.296, generator_dur_loss=1.828, generator_adv_loss=1.7, generator_feat_match_loss=4.349, over 70.00 samples.], tot_loss[discriminator_loss=2.722, discriminator_real_loss=1.374, discriminator_fake_loss=1.348, generator_loss=27.83, generator_mel_loss=18.15, generator_kl_loss=1.42, generator_dur_loss=1.764, generator_adv_loss=1.944, generator_feat_match_loss=4.554, over 6539.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 13:39:32,439 INFO [train.py:919] (2/6) Start epoch 368
2024-03-13 13:41:59,561 INFO [train.py:527] (2/6) Epoch 368, batch 42, global_batch_idx: 45550, batch size: 74, loss[discriminator_loss=2.718, discriminator_real_loss=1.439, discriminator_fake_loss=1.279, generator_loss=28.21, generator_mel_loss=18.12, generator_kl_loss=1.303, generator_dur_loss=1.828, generator_adv_loss=1.897, generator_feat_match_loss=5.06, over 74.00 samples.], tot_loss[discriminator_loss=2.709, discriminator_real_loss=1.368, discriminator_fake_loss=1.341, generator_loss=27.95, generator_mel_loss=18.19, generator_kl_loss=1.412, generator_dur_loss=1.764, generator_adv_loss=1.928, generator_feat_match_loss=4.656, over 2301.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 13:44:20,809 INFO [train.py:527] (2/6) Epoch 368, batch 92, global_batch_idx: 45600, batch size: 80, loss[discriminator_loss=2.676, discriminator_real_loss=1.355, discriminator_fake_loss=1.321, generator_loss=27.63, generator_mel_loss=18.01, generator_kl_loss=1.361, generator_dur_loss=1.775, generator_adv_loss=2.017, generator_feat_match_loss=4.463, over 80.00 samples.], tot_loss[discriminator_loss=2.717, discriminator_real_loss=1.372, discriminator_fake_loss=1.346, generator_loss=27.91, generator_mel_loss=18.21, generator_kl_loss=1.396, generator_dur_loss=1.756, generator_adv_loss=1.946, generator_feat_match_loss=4.606, over 5301.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 13:44:20,811 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 13:44:29,497 INFO [train.py:591] (2/6) Epoch 368, validation: discriminator_loss=2.755, discriminator_real_loss=1.457, discriminator_fake_loss=1.298, generator_loss=26.51, generator_mel_loss=18.05, generator_kl_loss=1.227, generator_dur_loss=1.792, generator_adv_loss=1.932, generator_feat_match_loss=3.517, over 100.00 samples.
2024-03-13 13:44:29,498 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 13:45:58,097 INFO [train.py:919] (2/6) Start epoch 369
2024-03-13 13:47:12,436 INFO [train.py:527] (2/6) Epoch 369, batch 18, global_batch_idx: 45650, batch size: 36, loss[discriminator_loss=2.703, discriminator_real_loss=1.348, discriminator_fake_loss=1.356, generator_loss=27.9, generator_mel_loss=18.04, generator_kl_loss=1.699, generator_dur_loss=1.682, generator_adv_loss=2.021, generator_feat_match_loss=4.464, over 36.00 samples.], tot_loss[discriminator_loss=2.725, discriminator_real_loss=1.361, discriminator_fake_loss=1.364, generator_loss=27.96, generator_mel_loss=18.22, generator_kl_loss=1.462, generator_dur_loss=1.737, generator_adv_loss=1.928, generator_feat_match_loss=4.609, over 994.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 13:49:31,632 INFO [train.py:527] (2/6) Epoch 369, batch 68, global_batch_idx: 45700, batch size: 61, loss[discriminator_loss=2.724, discriminator_real_loss=1.418, discriminator_fake_loss=1.306, generator_loss=27.82, generator_mel_loss=18.23, generator_kl_loss=1.404, generator_dur_loss=1.764, generator_adv_loss=1.84, generator_feat_match_loss=4.589, over 61.00 samples.], tot_loss[discriminator_loss=2.724, discriminator_real_loss=1.379, discriminator_fake_loss=1.345, generator_loss=27.87, generator_mel_loss=18.19, generator_kl_loss=1.456, generator_dur_loss=1.736, generator_adv_loss=1.929, generator_feat_match_loss=4.555, over 3570.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 13:51:55,032 INFO [train.py:527] (2/6) Epoch 369, batch 118, global_batch_idx: 45750, batch size: 26, loss[discriminator_loss=2.623, discriminator_real_loss=1.264, discriminator_fake_loss=1.358, generator_loss=28.04, generator_mel_loss=18.09, generator_kl_loss=1.751, generator_dur_loss=1.48, generator_adv_loss=2.019, generator_feat_match_loss=4.696, over 26.00 samples.], tot_loss[discriminator_loss=2.724, discriminator_real_loss=1.375, discriminator_fake_loss=1.348, generator_loss=27.87, generator_mel_loss=18.21, generator_kl_loss=1.437, generator_dur_loss=1.736, generator_adv_loss=1.933, generator_feat_match_loss=4.557, over 6455.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 13:52:11,663 INFO [train.py:919] (2/6) Start epoch 370
2024-03-13 13:54:38,394 INFO [train.py:527] (2/6) Epoch 370, batch 44, global_batch_idx: 45800, batch size: 31, loss[discriminator_loss=2.73, discriminator_real_loss=1.401, discriminator_fake_loss=1.329, generator_loss=26.55, generator_mel_loss=17.48, generator_kl_loss=1.444, generator_dur_loss=1.61, generator_adv_loss=2.026, generator_feat_match_loss=3.989, over 31.00 samples.], tot_loss[discriminator_loss=2.713, discriminator_real_loss=1.371, discriminator_fake_loss=1.342, generator_loss=27.85, generator_mel_loss=18.18, generator_kl_loss=1.418, generator_dur_loss=1.74, generator_adv_loss=1.953, generator_feat_match_loss=4.562, over 2648.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 13:54:38,395 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 13:54:46,121 INFO [train.py:591] (2/6) Epoch 370, validation: discriminator_loss=2.784, discriminator_real_loss=1.52, discriminator_fake_loss=1.264, generator_loss=27.2, generator_mel_loss=18.68, generator_kl_loss=1.298, generator_dur_loss=1.818, generator_adv_loss=1.961, generator_feat_match_loss=3.441, over 100.00 samples.
2024-03-13 13:54:46,122 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 13:57:03,169 INFO [train.py:527] (2/6) Epoch 370, batch 94, global_batch_idx: 45850, batch size: 58, loss[discriminator_loss=2.743, discriminator_real_loss=1.438, discriminator_fake_loss=1.305, generator_loss=28.41, generator_mel_loss=18.85, generator_kl_loss=1.322, generator_dur_loss=1.689, generator_adv_loss=1.952, generator_feat_match_loss=4.596, over 58.00 samples.], tot_loss[discriminator_loss=2.712, discriminator_real_loss=1.37, discriminator_fake_loss=1.342, generator_loss=27.93, generator_mel_loss=18.21, generator_kl_loss=1.414, generator_dur_loss=1.743, generator_adv_loss=1.951, generator_feat_match_loss=4.613, over 5492.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 13:58:22,813 INFO [train.py:919] (2/6) Start epoch 371
2024-03-13 13:59:42,315 INFO [train.py:527] (2/6) Epoch 371, batch 20, global_batch_idx: 45900, batch size: 44, loss[discriminator_loss=2.671, discriminator_real_loss=1.259, discriminator_fake_loss=1.412, generator_loss=27.71, generator_mel_loss=18.28, generator_kl_loss=1.337, generator_dur_loss=1.713, generator_adv_loss=2.003, generator_feat_match_loss=4.382, over 44.00 samples.], tot_loss[discriminator_loss=2.732, discriminator_real_loss=1.387, discriminator_fake_loss=1.346, generator_loss=27.67, generator_mel_loss=18.08, generator_kl_loss=1.409, generator_dur_loss=1.767, generator_adv_loss=1.925, generator_feat_match_loss=4.491, over 1292.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 14:02:03,653 INFO [train.py:527] (2/6) Epoch 371, batch 70, global_batch_idx: 45950, batch size: 44, loss[discriminator_loss=2.678, discriminator_real_loss=1.383, discriminator_fake_loss=1.296, generator_loss=27.76, generator_mel_loss=18.15, generator_kl_loss=1.441, generator_dur_loss=1.671, generator_adv_loss=1.989, generator_feat_match_loss=4.509, over 44.00 samples.], tot_loss[discriminator_loss=2.731, discriminator_real_loss=1.384, discriminator_fake_loss=1.347, generator_loss=27.7, generator_mel_loss=18.09, generator_kl_loss=1.408, generator_dur_loss=1.734, generator_adv_loss=1.935, generator_feat_match_loss=4.536, over 4095.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 14:04:17,178 INFO [train.py:527] (2/6) Epoch 371, batch 120, global_batch_idx: 46000, batch size: 74, loss[discriminator_loss=2.69, discriminator_real_loss=1.338, discriminator_fake_loss=1.352, generator_loss=27.95, generator_mel_loss=18.23, generator_kl_loss=1.391, generator_dur_loss=1.77, generator_adv_loss=1.947, generator_feat_match_loss=4.611, over 74.00 samples.], tot_loss[discriminator_loss=2.724, discriminator_real_loss=1.38, discriminator_fake_loss=1.344, generator_loss=27.76, generator_mel_loss=18.13, generator_kl_loss=1.413, generator_dur_loss=1.731, generator_adv_loss=1.936, generator_feat_match_loss=4.554, over 6848.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 14:04:17,179 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 14:04:26,085 INFO [train.py:591] (2/6) Epoch 371, validation: discriminator_loss=2.727, discriminator_real_loss=1.415, discriminator_fake_loss=1.312, generator_loss=27.89, generator_mel_loss=18.8, generator_kl_loss=1.346, generator_dur_loss=1.788, generator_adv_loss=1.931, generator_feat_match_loss=4.025, over 100.00 samples.
2024-03-13 14:04:26,086 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 14:04:35,536 INFO [train.py:919] (2/6) Start epoch 372
2024-03-13 14:07:06,466 INFO [train.py:527] (2/6) Epoch 372, batch 46, global_batch_idx: 46050, batch size: 64, loss[discriminator_loss=2.674, discriminator_real_loss=1.418, discriminator_fake_loss=1.255, generator_loss=27.04, generator_mel_loss=17.9, generator_kl_loss=1.415, generator_dur_loss=1.777, generator_adv_loss=1.968, generator_feat_match_loss=3.974, over 64.00 samples.], tot_loss[discriminator_loss=2.723, discriminator_real_loss=1.376, discriminator_fake_loss=1.348, generator_loss=27.74, generator_mel_loss=18.09, generator_kl_loss=1.397, generator_dur_loss=1.752, generator_adv_loss=1.939, generator_feat_match_loss=4.569, over 2910.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 14:09:23,771 INFO [train.py:527] (2/6) Epoch 372, batch 96, global_batch_idx: 46100, batch size: 68, loss[discriminator_loss=2.737, discriminator_real_loss=1.346, discriminator_fake_loss=1.391, generator_loss=27.14, generator_mel_loss=17.87, generator_kl_loss=1.395, generator_dur_loss=1.788, generator_adv_loss=1.915, generator_feat_match_loss=4.176, over 68.00 samples.], tot_loss[discriminator_loss=2.722, discriminator_real_loss=1.378, discriminator_fake_loss=1.344, generator_loss=27.74, generator_mel_loss=18.1, generator_kl_loss=1.403, generator_dur_loss=1.755, generator_adv_loss=1.934, generator_feat_match_loss=4.543, over 5841.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 14:10:41,978 INFO [train.py:919] (2/6) Start epoch 373
2024-03-13 14:12:07,418 INFO [train.py:527] (2/6) Epoch 373, batch 22, global_batch_idx: 46150, batch size: 56, loss[discriminator_loss=2.702, discriminator_real_loss=1.413, discriminator_fake_loss=1.289, generator_loss=27.25, generator_mel_loss=17.92, generator_kl_loss=1.269, generator_dur_loss=1.774, generator_adv_loss=1.927, generator_feat_match_loss=4.357, over 56.00 samples.], tot_loss[discriminator_loss=2.75, discriminator_real_loss=1.381, discriminator_fake_loss=1.369, generator_loss=27.82, generator_mel_loss=18.32, generator_kl_loss=1.423, generator_dur_loss=1.748, generator_adv_loss=1.958, generator_feat_match_loss=4.368, over 1217.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 14:14:28,020 INFO [train.py:527] (2/6) Epoch 373, batch 72, global_batch_idx: 46200, batch size: 61, loss[discriminator_loss=2.737, discriminator_real_loss=1.401, discriminator_fake_loss=1.336, generator_loss=26.98, generator_mel_loss=17.8, generator_kl_loss=1.407, generator_dur_loss=1.706, generator_adv_loss=1.937, generator_feat_match_loss=4.135, over 61.00 samples.], tot_loss[discriminator_loss=2.729, discriminator_real_loss=1.378, discriminator_fake_loss=1.351, generator_loss=27.78, generator_mel_loss=18.2, generator_kl_loss=1.42, generator_dur_loss=1.75, generator_adv_loss=1.946, generator_feat_match_loss=4.467, over 3928.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 14:14:28,022 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 14:14:36,415 INFO [train.py:591] (2/6) Epoch 373, validation: discriminator_loss=2.779, discriminator_real_loss=1.446, discriminator_fake_loss=1.333, generator_loss=27.44, generator_mel_loss=18.47, generator_kl_loss=1.349, generator_dur_loss=1.809, generator_adv_loss=1.9, generator_feat_match_loss=3.912, over 100.00 samples.
2024-03-13 14:14:36,416 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 14:16:53,642 INFO [train.py:527] (2/6) Epoch 373, batch 122, global_batch_idx: 46250, batch size: 25, loss[discriminator_loss=2.7, discriminator_real_loss=1.313, discriminator_fake_loss=1.387, generator_loss=29.28, generator_mel_loss=18.47, generator_kl_loss=1.785, generator_dur_loss=1.535, generator_adv_loss=2.057, generator_feat_match_loss=5.43, over 25.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.377, discriminator_fake_loss=1.349, generator_loss=27.77, generator_mel_loss=18.15, generator_kl_loss=1.415, generator_dur_loss=1.753, generator_adv_loss=1.94, generator_feat_match_loss=4.504, over 6762.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 14:16:58,037 INFO [train.py:919] (2/6) Start epoch 374
2024-03-13 14:19:34,089 INFO [train.py:527] (2/6) Epoch 374, batch 48, global_batch_idx: 46300, batch size: 80, loss[discriminator_loss=2.723, discriminator_real_loss=1.391, discriminator_fake_loss=1.332, generator_loss=28.16, generator_mel_loss=18.57, generator_kl_loss=1.341, generator_dur_loss=1.837, generator_adv_loss=1.893, generator_feat_match_loss=4.523, over 80.00 samples.], tot_loss[discriminator_loss=2.729, discriminator_real_loss=1.369, discriminator_fake_loss=1.36, generator_loss=27.7, generator_mel_loss=18.11, generator_kl_loss=1.42, generator_dur_loss=1.775, generator_adv_loss=1.929, generator_feat_match_loss=4.475, over 2849.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 14:21:53,651 INFO [train.py:527] (2/6) Epoch 374, batch 98, global_batch_idx: 46350, batch size: 66, loss[discriminator_loss=2.78, discriminator_real_loss=1.399, discriminator_fake_loss=1.38, generator_loss=28.02, generator_mel_loss=18.21, generator_kl_loss=1.456, generator_dur_loss=1.816, generator_adv_loss=1.863, generator_feat_match_loss=4.681, over 66.00 samples.], tot_loss[discriminator_loss=2.724, discriminator_real_loss=1.371, discriminator_fake_loss=1.353, generator_loss=27.73, generator_mel_loss=18.13, generator_kl_loss=1.404, generator_dur_loss=1.769, generator_adv_loss=1.926, generator_feat_match_loss=4.505, over 5837.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 14:23:03,573 INFO [train.py:919] (2/6) Start epoch 375
2024-03-13 14:24:35,809 INFO [train.py:527] (2/6) Epoch 375, batch 24, global_batch_idx: 46400, batch size: 55, loss[discriminator_loss=2.676, discriminator_real_loss=1.401, discriminator_fake_loss=1.275, generator_loss=28.34, generator_mel_loss=18.43, generator_kl_loss=1.481, generator_dur_loss=1.661, generator_adv_loss=1.925, generator_feat_match_loss=4.844, over 55.00 samples.], tot_loss[discriminator_loss=2.736, discriminator_real_loss=1.383, discriminator_fake_loss=1.353, generator_loss=27.74, generator_mel_loss=18.12, generator_kl_loss=1.409, generator_dur_loss=1.737, generator_adv_loss=1.955, generator_feat_match_loss=4.518, over 1287.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 14:24:35,810 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 14:24:43,824 INFO [train.py:591] (2/6) Epoch 375, validation: discriminator_loss=2.756, discriminator_real_loss=1.434, discriminator_fake_loss=1.322, generator_loss=26.87, generator_mel_loss=18.2, generator_kl_loss=1.23, generator_dur_loss=1.825, generator_adv_loss=1.9, generator_feat_match_loss=3.715, over 100.00 samples.
2024-03-13 14:24:43,825 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 14:27:02,913 INFO [train.py:527] (2/6) Epoch 375, batch 74, global_batch_idx: 46450, batch size: 53, loss[discriminator_loss=2.662, discriminator_real_loss=1.319, discriminator_fake_loss=1.343, generator_loss=28.3, generator_mel_loss=18.25, generator_kl_loss=1.656, generator_dur_loss=1.684, generator_adv_loss=1.984, generator_feat_match_loss=4.728, over 53.00 samples.], tot_loss[discriminator_loss=2.725, discriminator_real_loss=1.372, discriminator_fake_loss=1.353, generator_loss=27.85, generator_mel_loss=18.15, generator_kl_loss=1.433, generator_dur_loss=1.765, generator_adv_loss=1.934, generator_feat_match_loss=4.57, over 4176.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 14:29:21,189 INFO [train.py:919] (2/6) Start epoch 376
2024-03-13 14:29:45,059 INFO [train.py:527] (2/6) Epoch 376, batch 0, global_batch_idx: 46500, batch size: 80, loss[discriminator_loss=2.733, discriminator_real_loss=1.473, discriminator_fake_loss=1.26, generator_loss=26.09, generator_mel_loss=17.72, generator_kl_loss=1.237, generator_dur_loss=1.812, generator_adv_loss=1.819, generator_feat_match_loss=3.5, over 80.00 samples.], tot_loss[discriminator_loss=2.733, discriminator_real_loss=1.473, discriminator_fake_loss=1.26, generator_loss=26.09, generator_mel_loss=17.72, generator_kl_loss=1.237, generator_dur_loss=1.812, generator_adv_loss=1.819, generator_feat_match_loss=3.5, over 80.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 14:32:04,774 INFO [train.py:527] (2/6) Epoch 376, batch 50, global_batch_idx: 46550, batch size: 59, loss[discriminator_loss=2.724, discriminator_real_loss=1.304, discriminator_fake_loss=1.42, generator_loss=27.39, generator_mel_loss=17.69, generator_kl_loss=1.493, generator_dur_loss=1.772, generator_adv_loss=2.029, generator_feat_match_loss=4.401, over 59.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.366, discriminator_fake_loss=1.349, generator_loss=27.78, generator_mel_loss=18.09, generator_kl_loss=1.407, generator_dur_loss=1.772, generator_adv_loss=1.926, generator_feat_match_loss=4.586, over 2953.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 14:34:24,170 INFO [train.py:527] (2/6) Epoch 376, batch 100, global_batch_idx: 46600, batch size: 62, loss[discriminator_loss=2.697, discriminator_real_loss=1.291, discriminator_fake_loss=1.406, generator_loss=28.18, generator_mel_loss=18.07, generator_kl_loss=1.293, generator_dur_loss=1.765, generator_adv_loss=2.209, generator_feat_match_loss=4.843, over 62.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.366, discriminator_fake_loss=1.353, generator_loss=27.85, generator_mel_loss=18.13, generator_kl_loss=1.411, generator_dur_loss=1.764, generator_adv_loss=1.947, generator_feat_match_loss=4.601, over 5760.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 14:34:24,172 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 14:34:32,873 INFO [train.py:591] (2/6) Epoch 376, validation: discriminator_loss=2.856, discriminator_real_loss=1.496, discriminator_fake_loss=1.36, generator_loss=26.78, generator_mel_loss=18.47, generator_kl_loss=1.237, generator_dur_loss=1.83, generator_adv_loss=1.915, generator_feat_match_loss=3.331, over 100.00 samples.
2024-03-13 14:34:32,875 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 14:35:34,430 INFO [train.py:919] (2/6) Start epoch 377
2024-03-13 14:37:11,512 INFO [train.py:527] (2/6) Epoch 377, batch 26, global_batch_idx: 46650, batch size: 18, loss[discriminator_loss=2.736, discriminator_real_loss=1.399, discriminator_fake_loss=1.338, generator_loss=28.83, generator_mel_loss=19.66, generator_kl_loss=1.366, generator_dur_loss=1.634, generator_adv_loss=1.966, generator_feat_match_loss=4.206, over 18.00 samples.], tot_loss[discriminator_loss=2.733, discriminator_real_loss=1.378, discriminator_fake_loss=1.355, generator_loss=27.79, generator_mel_loss=18.21, generator_kl_loss=1.403, generator_dur_loss=1.782, generator_adv_loss=1.92, generator_feat_match_loss=4.481, over 1525.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 14:39:32,064 INFO [train.py:527] (2/6) Epoch 377, batch 76, global_batch_idx: 46700, batch size: 61, loss[discriminator_loss=2.785, discriminator_real_loss=1.405, discriminator_fake_loss=1.38, generator_loss=26.68, generator_mel_loss=17.79, generator_kl_loss=1.331, generator_dur_loss=1.746, generator_adv_loss=2.005, generator_feat_match_loss=3.805, over 61.00 samples.], tot_loss[discriminator_loss=2.717, discriminator_real_loss=1.378, discriminator_fake_loss=1.339, generator_loss=27.74, generator_mel_loss=18.12, generator_kl_loss=1.4, generator_dur_loss=1.771, generator_adv_loss=1.932, generator_feat_match_loss=4.517, over 4484.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 14:41:41,224 INFO [train.py:919] (2/6) Start epoch 378
2024-03-13 14:42:11,545 INFO [train.py:527] (2/6) Epoch 378, batch 2, global_batch_idx: 46750, batch size: 74, loss[discriminator_loss=2.712, discriminator_real_loss=1.421, discriminator_fake_loss=1.291, generator_loss=27.47, generator_mel_loss=17.96, generator_kl_loss=1.399, generator_dur_loss=1.848, generator_adv_loss=1.862, generator_feat_match_loss=4.393, over 74.00 samples.], tot_loss[discriminator_loss=2.698, discriminator_real_loss=1.381, discriminator_fake_loss=1.317, generator_loss=27.58, generator_mel_loss=18.15, generator_kl_loss=1.458, generator_dur_loss=1.764, generator_adv_loss=1.919, generator_feat_match_loss=4.294, over 185.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 14:44:34,321 INFO [train.py:527] (2/6) Epoch 378, batch 52, global_batch_idx: 46800, batch size: 50, loss[discriminator_loss=2.792, discriminator_real_loss=1.364, discriminator_fake_loss=1.428, generator_loss=26.01, generator_mel_loss=17.1, generator_kl_loss=1.505, generator_dur_loss=1.678, generator_adv_loss=1.821, generator_feat_match_loss=3.904, over 50.00 samples.], tot_loss[discriminator_loss=2.718, discriminator_real_loss=1.367, discriminator_fake_loss=1.35, generator_loss=27.79, generator_mel_loss=18.13, generator_kl_loss=1.416, generator_dur_loss=1.775, generator_adv_loss=1.929, generator_feat_match_loss=4.536, over 3175.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 14:44:34,323 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 14:44:42,306 INFO [train.py:591] (2/6) Epoch 378, validation: discriminator_loss=2.745, discriminator_real_loss=1.341, discriminator_fake_loss=1.404, generator_loss=27.12, generator_mel_loss=18.6, generator_kl_loss=1.324, generator_dur_loss=1.814, generator_adv_loss=1.742, generator_feat_match_loss=3.636, over 100.00 samples.
2024-03-13 14:44:42,307 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 14:47:01,119 INFO [train.py:527] (2/6) Epoch 378, batch 102, global_batch_idx: 46850, batch size: 70, loss[discriminator_loss=2.711, discriminator_real_loss=1.36, discriminator_fake_loss=1.35, generator_loss=27.56, generator_mel_loss=17.93, generator_kl_loss=1.291, generator_dur_loss=1.827, generator_adv_loss=2.138, generator_feat_match_loss=4.379, over 70.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.367, discriminator_fake_loss=1.348, generator_loss=27.79, generator_mel_loss=18.12, generator_kl_loss=1.414, generator_dur_loss=1.764, generator_adv_loss=1.944, generator_feat_match_loss=4.553, over 6055.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 14:47:56,055 INFO [train.py:919] (2/6) Start epoch 379
2024-03-13 14:49:40,454 INFO [train.py:527] (2/6) Epoch 379, batch 28, global_batch_idx: 46900, batch size: 53, loss[discriminator_loss=2.696, discriminator_real_loss=1.495, discriminator_fake_loss=1.201, generator_loss=28.06, generator_mel_loss=18.45, generator_kl_loss=1.58, generator_dur_loss=1.673, generator_adv_loss=1.967, generator_feat_match_loss=4.391, over 53.00 samples.], tot_loss[discriminator_loss=2.711, discriminator_real_loss=1.38, discriminator_fake_loss=1.331, generator_loss=27.79, generator_mel_loss=18.11, generator_kl_loss=1.416, generator_dur_loss=1.751, generator_adv_loss=1.954, generator_feat_match_loss=4.556, over 1665.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 14:51:57,967 INFO [train.py:527] (2/6) Epoch 379, batch 78, global_batch_idx: 46950, batch size: 74, loss[discriminator_loss=2.707, discriminator_real_loss=1.336, discriminator_fake_loss=1.371, generator_loss=28.28, generator_mel_loss=18.31, generator_kl_loss=1.343, generator_dur_loss=1.783, generator_adv_loss=1.899, generator_feat_match_loss=4.949, over 74.00 samples.], tot_loss[discriminator_loss=2.712, discriminator_real_loss=1.375, discriminator_fake_loss=1.337, generator_loss=27.94, generator_mel_loss=18.19, generator_kl_loss=1.436, generator_dur_loss=1.733, generator_adv_loss=1.948, generator_feat_match_loss=4.639, over 4155.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 14:54:01,554 INFO [train.py:919] (2/6) Start epoch 380
2024-03-13 14:54:36,746 INFO [train.py:527] (2/6) Epoch 380, batch 4, global_batch_idx: 47000, batch size: 13, loss[discriminator_loss=2.778, discriminator_real_loss=1.347, discriminator_fake_loss=1.431, generator_loss=29.04, generator_mel_loss=18.14, generator_kl_loss=1.884, generator_dur_loss=1.592, generator_adv_loss=2.047, generator_feat_match_loss=5.382, over 13.00 samples.], tot_loss[discriminator_loss=2.723, discriminator_real_loss=1.391, discriminator_fake_loss=1.332, generator_loss=27.5, generator_mel_loss=17.87, generator_kl_loss=1.463, generator_dur_loss=1.821, generator_adv_loss=1.948, generator_feat_match_loss=4.39, over 278.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 14:54:36,749 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 14:54:44,913 INFO [train.py:591] (2/6) Epoch 380, validation: discriminator_loss=2.783, discriminator_real_loss=1.544, discriminator_fake_loss=1.239, generator_loss=27.31, generator_mel_loss=18.45, generator_kl_loss=1.266, generator_dur_loss=1.819, generator_adv_loss=2.008, generator_feat_match_loss=3.769, over 100.00 samples.
2024-03-13 14:54:44,915 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 14:57:04,657 INFO [train.py:527] (2/6) Epoch 380, batch 54, global_batch_idx: 47050, batch size: 31, loss[discriminator_loss=2.707, discriminator_real_loss=1.313, discriminator_fake_loss=1.394, generator_loss=27.68, generator_mel_loss=17.64, generator_kl_loss=1.64, generator_dur_loss=1.627, generator_adv_loss=1.988, generator_feat_match_loss=4.781, over 31.00 samples.], tot_loss[discriminator_loss=2.725, discriminator_real_loss=1.381, discriminator_fake_loss=1.344, generator_loss=27.89, generator_mel_loss=18.14, generator_kl_loss=1.402, generator_dur_loss=1.787, generator_adv_loss=1.929, generator_feat_match_loss=4.63, over 3303.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 14:59:25,703 INFO [train.py:527] (2/6) Epoch 380, batch 104, global_batch_idx: 47100, batch size: 66, loss[discriminator_loss=2.691, discriminator_real_loss=1.41, discriminator_fake_loss=1.282, generator_loss=27.29, generator_mel_loss=18.06, generator_kl_loss=1.246, generator_dur_loss=1.794, generator_adv_loss=1.912, generator_feat_match_loss=4.274, over 66.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.382, discriminator_fake_loss=1.344, generator_loss=27.83, generator_mel_loss=18.13, generator_kl_loss=1.408, generator_dur_loss=1.777, generator_adv_loss=1.932, generator_feat_match_loss=4.585, over 5881.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 15:00:16,659 INFO [train.py:919] (2/6) Start epoch 381
2024-03-13 15:02:04,299 INFO [train.py:527] (2/6) Epoch 381, batch 30, global_batch_idx: 47150, batch size: 59, loss[discriminator_loss=2.732, discriminator_real_loss=1.378, discriminator_fake_loss=1.354, generator_loss=27.32, generator_mel_loss=17.87, generator_kl_loss=1.454, generator_dur_loss=1.795, generator_adv_loss=1.856, generator_feat_match_loss=4.355, over 59.00 samples.], tot_loss[discriminator_loss=2.735, discriminator_real_loss=1.379, discriminator_fake_loss=1.356, generator_loss=27.72, generator_mel_loss=18.07, generator_kl_loss=1.408, generator_dur_loss=1.784, generator_adv_loss=1.918, generator_feat_match_loss=4.533, over 1890.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 15:04:25,814 INFO [train.py:527] (2/6) Epoch 381, batch 80, global_batch_idx: 47200, batch size: 70, loss[discriminator_loss=2.738, discriminator_real_loss=1.408, discriminator_fake_loss=1.33, generator_loss=27.58, generator_mel_loss=18.05, generator_kl_loss=1.259, generator_dur_loss=1.831, generator_adv_loss=1.917, generator_feat_match_loss=4.524, over 70.00 samples.], tot_loss[discriminator_loss=2.725, discriminator_real_loss=1.375, discriminator_fake_loss=1.35, generator_loss=27.8, generator_mel_loss=18.06, generator_kl_loss=1.41, generator_dur_loss=1.78, generator_adv_loss=1.971, generator_feat_match_loss=4.583, over 4851.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 15:04:25,815 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 15:04:34,805 INFO [train.py:591] (2/6) Epoch 381, validation: discriminator_loss=2.724, discriminator_real_loss=1.401, discriminator_fake_loss=1.323, generator_loss=26.88, generator_mel_loss=18.38, generator_kl_loss=1.162, generator_dur_loss=1.845, generator_adv_loss=1.823, generator_feat_match_loss=3.671, over 100.00 samples.
2024-03-13 15:04:34,806 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 15:06:34,829 INFO [train.py:919] (2/6) Start epoch 382
2024-03-13 15:07:16,349 INFO [train.py:527] (2/6) Epoch 382, batch 6, global_batch_idx: 47250, batch size: 25, loss[discriminator_loss=2.668, discriminator_real_loss=1.346, discriminator_fake_loss=1.322, generator_loss=27.94, generator_mel_loss=18.29, generator_kl_loss=1.615, generator_dur_loss=1.617, generator_adv_loss=1.994, generator_feat_match_loss=4.429, over 25.00 samples.], tot_loss[discriminator_loss=2.664, discriminator_real_loss=1.356, discriminator_fake_loss=1.308, generator_loss=27.49, generator_mel_loss=17.94, generator_kl_loss=1.431, generator_dur_loss=1.753, generator_adv_loss=1.946, generator_feat_match_loss=4.42, over 354.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 15:09:36,829 INFO [train.py:527] (2/6) Epoch 382, batch 56, global_batch_idx: 47300, batch size: 53, loss[discriminator_loss=2.754, discriminator_real_loss=1.507, discriminator_fake_loss=1.247, generator_loss=27.34, generator_mel_loss=18.05, generator_kl_loss=1.388, generator_dur_loss=1.741, generator_adv_loss=1.726, generator_feat_match_loss=4.432, over 53.00 samples.], tot_loss[discriminator_loss=2.71, discriminator_real_loss=1.376, discriminator_fake_loss=1.334, generator_loss=27.75, generator_mel_loss=18.08, generator_kl_loss=1.428, generator_dur_loss=1.752, generator_adv_loss=1.95, generator_feat_match_loss=4.548, over 2977.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 15:11:58,840 INFO [train.py:527] (2/6) Epoch 382, batch 106, global_batch_idx: 47350, batch size: 61, loss[discriminator_loss=2.766, discriminator_real_loss=1.484, discriminator_fake_loss=1.282, generator_loss=27.63, generator_mel_loss=18.03, generator_kl_loss=1.45, generator_dur_loss=1.79, generator_adv_loss=1.939, generator_feat_match_loss=4.42, over 61.00 samples.], tot_loss[discriminator_loss=2.713, discriminator_real_loss=1.371, discriminator_fake_loss=1.341, generator_loss=27.82, generator_mel_loss=18.09, generator_kl_loss=1.415, generator_dur_loss=1.762, generator_adv_loss=1.946, generator_feat_match_loss=4.61, over 5770.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 15:12:48,645 INFO [train.py:919] (2/6) Start epoch 383
2024-03-13 15:14:46,040 INFO [train.py:527] (2/6) Epoch 383, batch 32, global_batch_idx: 47400, batch size: 52, loss[discriminator_loss=2.737, discriminator_real_loss=1.518, discriminator_fake_loss=1.219, generator_loss=27.69, generator_mel_loss=18.1, generator_kl_loss=1.39, generator_dur_loss=1.694, generator_adv_loss=1.938, generator_feat_match_loss=4.561, over 52.00 samples.], tot_loss[discriminator_loss=2.71, discriminator_real_loss=1.374, discriminator_fake_loss=1.336, generator_loss=27.81, generator_mel_loss=18.15, generator_kl_loss=1.389, generator_dur_loss=1.772, generator_adv_loss=1.944, generator_feat_match_loss=4.558, over 1948.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 15:14:46,041 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 15:14:54,036 INFO [train.py:591] (2/6) Epoch 383, validation: discriminator_loss=2.804, discriminator_real_loss=1.39, discriminator_fake_loss=1.414, generator_loss=27.16, generator_mel_loss=18.68, generator_kl_loss=1.291, generator_dur_loss=1.826, generator_adv_loss=1.773, generator_feat_match_loss=3.595, over 100.00 samples.
2024-03-13 15:14:54,037 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 15:17:15,756 INFO [train.py:527] (2/6) Epoch 383, batch 82, global_batch_idx: 47450, batch size: 36, loss[discriminator_loss=2.795, discriminator_real_loss=1.376, discriminator_fake_loss=1.419, generator_loss=27.32, generator_mel_loss=17.78, generator_kl_loss=1.705, generator_dur_loss=1.726, generator_adv_loss=1.99, generator_feat_match_loss=4.117, over 36.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.376, discriminator_fake_loss=1.34, generator_loss=27.89, generator_mel_loss=18.18, generator_kl_loss=1.407, generator_dur_loss=1.756, generator_adv_loss=1.949, generator_feat_match_loss=4.603, over 4778.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 15:19:12,646 INFO [train.py:919] (2/6) Start epoch 384
2024-03-13 15:19:59,902 INFO [train.py:527] (2/6) Epoch 384, batch 8, global_batch_idx: 47500, batch size: 25, loss[discriminator_loss=2.832, discriminator_real_loss=1.503, discriminator_fake_loss=1.329, generator_loss=27.38, generator_mel_loss=18.38, generator_kl_loss=1.656, generator_dur_loss=1.572, generator_adv_loss=1.784, generator_feat_match_loss=3.983, over 25.00 samples.], tot_loss[discriminator_loss=2.731, discriminator_real_loss=1.379, discriminator_fake_loss=1.352, generator_loss=27.75, generator_mel_loss=18.07, generator_kl_loss=1.441, generator_dur_loss=1.694, generator_adv_loss=1.946, generator_feat_match_loss=4.594, over 466.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 15:22:23,540 INFO [train.py:527] (2/6) Epoch 384, batch 58, global_batch_idx: 47550, batch size: 52, loss[discriminator_loss=2.716, discriminator_real_loss=1.395, discriminator_fake_loss=1.321, generator_loss=27.4, generator_mel_loss=17.86, generator_kl_loss=1.451, generator_dur_loss=1.666, generator_adv_loss=1.916, generator_feat_match_loss=4.507, over 52.00 samples.], tot_loss[discriminator_loss=2.712, discriminator_real_loss=1.365, discriminator_fake_loss=1.347, generator_loss=27.92, generator_mel_loss=18.12, generator_kl_loss=1.426, generator_dur_loss=1.748, generator_adv_loss=1.944, generator_feat_match_loss=4.682, over 3442.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 15:24:42,734 INFO [train.py:527] (2/6) Epoch 384, batch 108, global_batch_idx: 47600, batch size: 39, loss[discriminator_loss=2.742, discriminator_real_loss=1.392, discriminator_fake_loss=1.349, generator_loss=27.17, generator_mel_loss=17.96, generator_kl_loss=1.616, generator_dur_loss=1.631, generator_adv_loss=1.93, generator_feat_match_loss=4.032, over 39.00 samples.], tot_loss[discriminator_loss=2.713, discriminator_real_loss=1.369, discriminator_fake_loss=1.344, generator_loss=27.87, generator_mel_loss=18.13, generator_kl_loss=1.416, generator_dur_loss=1.745, generator_adv_loss=1.946, generator_feat_match_loss=4.636, over 6281.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 15:24:42,735 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 15:24:51,610 INFO [train.py:591] (2/6) Epoch 384, validation: discriminator_loss=2.74, discriminator_real_loss=1.424, discriminator_fake_loss=1.317, generator_loss=26.79, generator_mel_loss=18.36, generator_kl_loss=1.215, generator_dur_loss=1.759, generator_adv_loss=1.913, generator_feat_match_loss=3.538, over 100.00 samples.
2024-03-13 15:24:51,611 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 15:25:32,605 INFO [train.py:919] (2/6) Start epoch 385
2024-03-13 15:27:32,038 INFO [train.py:527] (2/6) Epoch 385, batch 34, global_batch_idx: 47650, batch size: 44, loss[discriminator_loss=2.775, discriminator_real_loss=1.452, discriminator_fake_loss=1.323, generator_loss=27.43, generator_mel_loss=18.09, generator_kl_loss=1.547, generator_dur_loss=1.659, generator_adv_loss=1.978, generator_feat_match_loss=4.16, over 44.00 samples.], tot_loss[discriminator_loss=2.717, discriminator_real_loss=1.368, discriminator_fake_loss=1.349, generator_loss=27.83, generator_mel_loss=18.15, generator_kl_loss=1.427, generator_dur_loss=1.722, generator_adv_loss=1.942, generator_feat_match_loss=4.587, over 1958.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 15:29:55,483 INFO [train.py:527] (2/6) Epoch 385, batch 84, global_batch_idx: 47700, batch size: 83, loss[discriminator_loss=2.75, discriminator_real_loss=1.436, discriminator_fake_loss=1.314, generator_loss=27.87, generator_mel_loss=18.29, generator_kl_loss=1.359, generator_dur_loss=1.84, generator_adv_loss=1.86, generator_feat_match_loss=4.514, over 83.00 samples.], tot_loss[discriminator_loss=2.725, discriminator_real_loss=1.375, discriminator_fake_loss=1.35, generator_loss=27.78, generator_mel_loss=18.14, generator_kl_loss=1.423, generator_dur_loss=1.733, generator_adv_loss=1.942, generator_feat_match_loss=4.542, over 4659.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 15:31:46,360 INFO [train.py:919] (2/6) Start epoch 386
2024-03-13 15:32:38,067 INFO [train.py:527] (2/6) Epoch 386, batch 10, global_batch_idx: 47750, batch size: 58, loss[discriminator_loss=2.774, discriminator_real_loss=1.269, discriminator_fake_loss=1.505, generator_loss=28.58, generator_mel_loss=18.24, generator_kl_loss=1.378, generator_dur_loss=1.777, generator_adv_loss=2.159, generator_feat_match_loss=5.028, over 58.00 samples.], tot_loss[discriminator_loss=2.709, discriminator_real_loss=1.372, discriminator_fake_loss=1.337, generator_loss=27.93, generator_mel_loss=18.07, generator_kl_loss=1.416, generator_dur_loss=1.747, generator_adv_loss=1.983, generator_feat_match_loss=4.713, over 643.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 15:34:59,666 INFO [train.py:527] (2/6) Epoch 386, batch 60, global_batch_idx: 47800, batch size: 61, loss[discriminator_loss=2.735, discriminator_real_loss=1.351, discriminator_fake_loss=1.383, generator_loss=28.99, generator_mel_loss=18.85, generator_kl_loss=1.473, generator_dur_loss=1.747, generator_adv_loss=1.898, generator_feat_match_loss=5.024, over 61.00 samples.], tot_loss[discriminator_loss=2.728, discriminator_real_loss=1.382, discriminator_fake_loss=1.346, generator_loss=27.78, generator_mel_loss=18.12, generator_kl_loss=1.404, generator_dur_loss=1.766, generator_adv_loss=1.945, generator_feat_match_loss=4.547, over 3733.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 15:34:59,668 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 15:35:07,967 INFO [train.py:591] (2/6) Epoch 386, validation: discriminator_loss=2.777, discriminator_real_loss=1.402, discriminator_fake_loss=1.375, generator_loss=26.5, generator_mel_loss=18.08, generator_kl_loss=1.129, generator_dur_loss=1.808, generator_adv_loss=1.855, generator_feat_match_loss=3.628, over 100.00 samples.
2024-03-13 15:35:07,968 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 15:37:28,678 INFO [train.py:527] (2/6) Epoch 386, batch 110, global_batch_idx: 47850, batch size: 66, loss[discriminator_loss=2.674, discriminator_real_loss=1.351, discriminator_fake_loss=1.324, generator_loss=27.41, generator_mel_loss=18.02, generator_kl_loss=1.429, generator_dur_loss=1.761, generator_adv_loss=1.835, generator_feat_match_loss=4.363, over 66.00 samples.], tot_loss[discriminator_loss=2.73, discriminator_real_loss=1.383, discriminator_fake_loss=1.347, generator_loss=27.79, generator_mel_loss=18.13, generator_kl_loss=1.415, generator_dur_loss=1.768, generator_adv_loss=1.937, generator_feat_match_loss=4.537, over 6683.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 15:38:05,296 INFO [train.py:919] (2/6) Start epoch 387
2024-03-13 15:40:12,119 INFO [train.py:527] (2/6) Epoch 387, batch 36, global_batch_idx: 47900, batch size: 80, loss[discriminator_loss=2.698, discriminator_real_loss=1.298, discriminator_fake_loss=1.4, generator_loss=27.64, generator_mel_loss=17.83, generator_kl_loss=1.41, generator_dur_loss=1.873, generator_adv_loss=1.996, generator_feat_match_loss=4.534, over 80.00 samples.], tot_loss[discriminator_loss=2.717, discriminator_real_loss=1.366, discriminator_fake_loss=1.352, generator_loss=27.93, generator_mel_loss=18.11, generator_kl_loss=1.427, generator_dur_loss=1.752, generator_adv_loss=1.962, generator_feat_match_loss=4.681, over 2080.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 15:42:31,197 INFO [train.py:527] (2/6) Epoch 387, batch 86, global_batch_idx: 47950, batch size: 66, loss[discriminator_loss=2.723, discriminator_real_loss=1.295, discriminator_fake_loss=1.428, generator_loss=28.06, generator_mel_loss=17.97, generator_kl_loss=1.432, generator_dur_loss=1.745, generator_adv_loss=2.122, generator_feat_match_loss=4.783, over 66.00 samples.], tot_loss[discriminator_loss=2.717, discriminator_real_loss=1.366, discriminator_fake_loss=1.351, generator_loss=27.84, generator_mel_loss=18.12, generator_kl_loss=1.431, generator_dur_loss=1.741, generator_adv_loss=1.956, generator_feat_match_loss=4.601, over 4651.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 15:44:15,873 INFO [train.py:919] (2/6) Start epoch 388
2024-03-13 15:45:14,066 INFO [train.py:527] (2/6) Epoch 388, batch 12, global_batch_idx: 48000, batch size: 31, loss[discriminator_loss=2.714, discriminator_real_loss=1.298, discriminator_fake_loss=1.417, generator_loss=28.29, generator_mel_loss=18.42, generator_kl_loss=1.543, generator_dur_loss=1.628, generator_adv_loss=1.999, generator_feat_match_loss=4.708, over 31.00 samples.], tot_loss[discriminator_loss=2.73, discriminator_real_loss=1.362, discriminator_fake_loss=1.368, generator_loss=28.19, generator_mel_loss=18.39, generator_kl_loss=1.447, generator_dur_loss=1.75, generator_adv_loss=1.937, generator_feat_match_loss=4.673, over 693.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 15:45:14,068 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 15:45:21,915 INFO [train.py:591] (2/6) Epoch 388, validation: discriminator_loss=2.76, discriminator_real_loss=1.511, discriminator_fake_loss=1.249, generator_loss=26.7, generator_mel_loss=18.05, generator_kl_loss=1.114, generator_dur_loss=1.821, generator_adv_loss=2.015, generator_feat_match_loss=3.705, over 100.00 samples.
2024-03-13 15:45:21,916 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 15:47:41,656 INFO [train.py:527] (2/6) Epoch 388, batch 62, global_batch_idx: 48050, batch size: 55, loss[discriminator_loss=2.664, discriminator_real_loss=1.344, discriminator_fake_loss=1.32, generator_loss=26.46, generator_mel_loss=17.29, generator_kl_loss=1.397, generator_dur_loss=1.722, generator_adv_loss=1.876, generator_feat_match_loss=4.173, over 55.00 samples.], tot_loss[discriminator_loss=2.719, discriminator_real_loss=1.371, discriminator_fake_loss=1.348, generator_loss=27.85, generator_mel_loss=18.11, generator_kl_loss=1.429, generator_dur_loss=1.763, generator_adv_loss=1.93, generator_feat_match_loss=4.617, over 3690.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 15:50:02,450 INFO [train.py:527] (2/6) Epoch 388, batch 112, global_batch_idx: 48100, batch size: 36, loss[discriminator_loss=2.742, discriminator_real_loss=1.379, discriminator_fake_loss=1.363, generator_loss=26.13, generator_mel_loss=17.89, generator_kl_loss=1.537, generator_dur_loss=1.705, generator_adv_loss=1.802, generator_feat_match_loss=3.203, over 36.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.37, discriminator_fake_loss=1.349, generator_loss=27.9, generator_mel_loss=18.14, generator_kl_loss=1.424, generator_dur_loss=1.76, generator_adv_loss=1.938, generator_feat_match_loss=4.647, over 6476.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 15:50:35,279 INFO [train.py:919] (2/6) Start epoch 389
2024-03-13 15:52:48,456 INFO [train.py:527] (2/6) Epoch 389, batch 38, global_batch_idx: 48150, batch size: 25, loss[discriminator_loss=2.708, discriminator_real_loss=1.292, discriminator_fake_loss=1.416, generator_loss=29.31, generator_mel_loss=18.48, generator_kl_loss=1.686, generator_dur_loss=1.576, generator_adv_loss=1.973, generator_feat_match_loss=5.602, over 25.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.377, discriminator_fake_loss=1.349, generator_loss=27.9, generator_mel_loss=18.15, generator_kl_loss=1.418, generator_dur_loss=1.749, generator_adv_loss=1.955, generator_feat_match_loss=4.624, over 2170.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 15:55:12,798 INFO [train.py:527] (2/6) Epoch 389, batch 88, global_batch_idx: 48200, batch size: 56, loss[discriminator_loss=2.792, discriminator_real_loss=1.569, discriminator_fake_loss=1.223, generator_loss=27.53, generator_mel_loss=18.21, generator_kl_loss=1.273, generator_dur_loss=1.734, generator_adv_loss=1.879, generator_feat_match_loss=4.436, over 56.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.373, discriminator_fake_loss=1.353, generator_loss=27.93, generator_mel_loss=18.18, generator_kl_loss=1.413, generator_dur_loss=1.765, generator_adv_loss=1.95, generator_feat_match_loss=4.623, over 5107.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 15:55:12,800 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 15:55:21,782 INFO [train.py:591] (2/6) Epoch 389, validation: discriminator_loss=2.788, discriminator_real_loss=1.392, discriminator_fake_loss=1.397, generator_loss=27.36, generator_mel_loss=18.79, generator_kl_loss=1.243, generator_dur_loss=1.835, generator_adv_loss=1.774, generator_feat_match_loss=3.719, over 100.00 samples.
2024-03-13 15:55:21,783 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 15:56:57,768 INFO [train.py:919] (2/6) Start epoch 390
2024-03-13 15:58:02,169 INFO [train.py:527] (2/6) Epoch 390, batch 14, global_batch_idx: 48250, batch size: 70, loss[discriminator_loss=2.698, discriminator_real_loss=1.205, discriminator_fake_loss=1.493, generator_loss=28.34, generator_mel_loss=18, generator_kl_loss=1.373, generator_dur_loss=1.827, generator_adv_loss=1.967, generator_feat_match_loss=5.173, over 70.00 samples.], tot_loss[discriminator_loss=2.734, discriminator_real_loss=1.392, discriminator_fake_loss=1.342, generator_loss=27.92, generator_mel_loss=18.18, generator_kl_loss=1.358, generator_dur_loss=1.784, generator_adv_loss=1.944, generator_feat_match_loss=4.654, over 983.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 16:00:21,677 INFO [train.py:527] (2/6) Epoch 390, batch 64, global_batch_idx: 48300, batch size: 31, loss[discriminator_loss=2.76, discriminator_real_loss=1.446, discriminator_fake_loss=1.314, generator_loss=28.11, generator_mel_loss=18.28, generator_kl_loss=1.82, generator_dur_loss=1.651, generator_adv_loss=1.847, generator_feat_match_loss=4.516, over 31.00 samples.], tot_loss[discriminator_loss=2.721, discriminator_real_loss=1.383, discriminator_fake_loss=1.338, generator_loss=27.95, generator_mel_loss=18.16, generator_kl_loss=1.385, generator_dur_loss=1.763, generator_adv_loss=1.963, generator_feat_match_loss=4.673, over 3855.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 16:02:39,642 INFO [train.py:527] (2/6) Epoch 390, batch 114, global_batch_idx: 48350, batch size: 88, loss[discriminator_loss=2.735, discriminator_real_loss=1.428, discriminator_fake_loss=1.307, generator_loss=27.86, generator_mel_loss=18.36, generator_kl_loss=1.366, generator_dur_loss=1.859, generator_adv_loss=1.947, generator_feat_match_loss=4.324, over 88.00 samples.], tot_loss[discriminator_loss=2.713, discriminator_real_loss=1.378, discriminator_fake_loss=1.335, generator_loss=27.94, generator_mel_loss=18.14, generator_kl_loss=1.397, generator_dur_loss=1.768, generator_adv_loss=1.971, generator_feat_match_loss=4.67, over 6612.00 samples.], cur_lr_g: 1.91e-04, cur_lr_d: 1.91e-04, 
2024-03-13 16:03:05,861 INFO [train.py:919] (2/6) Start epoch 391
2024-03-13 16:05:21,123 INFO [train.py:527] (2/6) Epoch 391, batch 40, global_batch_idx: 48400, batch size: 25, loss[discriminator_loss=2.715, discriminator_real_loss=1.299, discriminator_fake_loss=1.416, generator_loss=29, generator_mel_loss=18.37, generator_kl_loss=1.862, generator_dur_loss=1.573, generator_adv_loss=2.085, generator_feat_match_loss=5.112, over 25.00 samples.], tot_loss[discriminator_loss=2.734, discriminator_real_loss=1.388, discriminator_fake_loss=1.346, generator_loss=27.77, generator_mel_loss=18.1, generator_kl_loss=1.413, generator_dur_loss=1.763, generator_adv_loss=1.931, generator_feat_match_loss=4.559, over 2262.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 16:05:21,125 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 16:05:28,910 INFO [train.py:591] (2/6) Epoch 391, validation: discriminator_loss=2.794, discriminator_real_loss=1.506, discriminator_fake_loss=1.288, generator_loss=27.61, generator_mel_loss=18.79, generator_kl_loss=1.207, generator_dur_loss=1.81, generator_adv_loss=1.969, generator_feat_match_loss=3.84, over 100.00 samples.
2024-03-13 16:05:28,912 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 16:07:47,805 INFO [train.py:527] (2/6) Epoch 391, batch 90, global_batch_idx: 48450, batch size: 56, loss[discriminator_loss=2.714, discriminator_real_loss=1.474, discriminator_fake_loss=1.24, generator_loss=27.37, generator_mel_loss=18.14, generator_kl_loss=1.501, generator_dur_loss=1.714, generator_adv_loss=1.786, generator_feat_match_loss=4.228, over 56.00 samples.], tot_loss[discriminator_loss=2.717, discriminator_real_loss=1.377, discriminator_fake_loss=1.34, generator_loss=27.83, generator_mel_loss=18.1, generator_kl_loss=1.403, generator_dur_loss=1.767, generator_adv_loss=1.939, generator_feat_match_loss=4.626, over 5380.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 16:09:22,920 INFO [train.py:919] (2/6) Start epoch 392
2024-03-13 16:10:32,277 INFO [train.py:527] (2/6) Epoch 392, batch 16, global_batch_idx: 48500, batch size: 96, loss[discriminator_loss=2.718, discriminator_real_loss=1.442, discriminator_fake_loss=1.276, generator_loss=27.14, generator_mel_loss=17.75, generator_kl_loss=1.308, generator_dur_loss=1.828, generator_adv_loss=1.782, generator_feat_match_loss=4.471, over 96.00 samples.], tot_loss[discriminator_loss=2.722, discriminator_real_loss=1.379, discriminator_fake_loss=1.343, generator_loss=27.68, generator_mel_loss=18.02, generator_kl_loss=1.43, generator_dur_loss=1.759, generator_adv_loss=1.93, generator_feat_match_loss=4.54, over 1021.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 16:12:50,666 INFO [train.py:527] (2/6) Epoch 392, batch 66, global_batch_idx: 48550, batch size: 59, loss[discriminator_loss=2.671, discriminator_real_loss=1.258, discriminator_fake_loss=1.414, generator_loss=28.07, generator_mel_loss=18.25, generator_kl_loss=1.307, generator_dur_loss=1.724, generator_adv_loss=2.008, generator_feat_match_loss=4.783, over 59.00 samples.], tot_loss[discriminator_loss=2.717, discriminator_real_loss=1.378, discriminator_fake_loss=1.338, generator_loss=27.72, generator_mel_loss=18.05, generator_kl_loss=1.412, generator_dur_loss=1.758, generator_adv_loss=1.931, generator_feat_match_loss=4.573, over 3966.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 16:15:11,538 INFO [train.py:527] (2/6) Epoch 392, batch 116, global_batch_idx: 48600, batch size: 77, loss[discriminator_loss=2.718, discriminator_real_loss=1.297, discriminator_fake_loss=1.421, generator_loss=27.43, generator_mel_loss=18.03, generator_kl_loss=1.28, generator_dur_loss=1.837, generator_adv_loss=1.841, generator_feat_match_loss=4.432, over 77.00 samples.], tot_loss[discriminator_loss=2.711, discriminator_real_loss=1.374, discriminator_fake_loss=1.338, generator_loss=27.83, generator_mel_loss=18.12, generator_kl_loss=1.414, generator_dur_loss=1.75, generator_adv_loss=1.933, generator_feat_match_loss=4.616, over 6771.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 16:15:11,539 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 16:15:20,602 INFO [train.py:591] (2/6) Epoch 392, validation: discriminator_loss=2.784, discriminator_real_loss=1.422, discriminator_fake_loss=1.362, generator_loss=26.41, generator_mel_loss=18.19, generator_kl_loss=1.158, generator_dur_loss=1.815, generator_adv_loss=1.784, generator_feat_match_loss=3.458, over 100.00 samples.
2024-03-13 16:15:20,603 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 16:15:41,172 INFO [train.py:919] (2/6) Start epoch 393
2024-03-13 16:18:01,794 INFO [train.py:527] (2/6) Epoch 393, batch 42, global_batch_idx: 48650, batch size: 74, loss[discriminator_loss=2.689, discriminator_real_loss=1.382, discriminator_fake_loss=1.307, generator_loss=27.66, generator_mel_loss=18.22, generator_kl_loss=1.351, generator_dur_loss=1.805, generator_adv_loss=1.957, generator_feat_match_loss=4.324, over 74.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.372, discriminator_fake_loss=1.347, generator_loss=27.94, generator_mel_loss=18.11, generator_kl_loss=1.402, generator_dur_loss=1.769, generator_adv_loss=1.966, generator_feat_match_loss=4.692, over 2490.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 16:20:18,272 INFO [train.py:527] (2/6) Epoch 393, batch 92, global_batch_idx: 48700, batch size: 45, loss[discriminator_loss=2.749, discriminator_real_loss=1.376, discriminator_fake_loss=1.374, generator_loss=27.67, generator_mel_loss=18.03, generator_kl_loss=1.49, generator_dur_loss=1.691, generator_adv_loss=1.94, generator_feat_match_loss=4.52, over 45.00 samples.], tot_loss[discriminator_loss=2.717, discriminator_real_loss=1.371, discriminator_fake_loss=1.346, generator_loss=27.86, generator_mel_loss=18.08, generator_kl_loss=1.408, generator_dur_loss=1.756, generator_adv_loss=1.958, generator_feat_match_loss=4.659, over 5277.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 16:21:48,973 INFO [train.py:919] (2/6) Start epoch 394
2024-03-13 16:23:03,812 INFO [train.py:527] (2/6) Epoch 394, batch 18, global_batch_idx: 48750, batch size: 39, loss[discriminator_loss=2.643, discriminator_real_loss=1.285, discriminator_fake_loss=1.359, generator_loss=28.3, generator_mel_loss=18.57, generator_kl_loss=1.28, generator_dur_loss=1.692, generator_adv_loss=1.832, generator_feat_match_loss=4.929, over 39.00 samples.], tot_loss[discriminator_loss=2.69, discriminator_real_loss=1.349, discriminator_fake_loss=1.34, generator_loss=27.89, generator_mel_loss=18.11, generator_kl_loss=1.389, generator_dur_loss=1.745, generator_adv_loss=1.952, generator_feat_match_loss=4.7, over 1191.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 16:25:26,135 INFO [train.py:527] (2/6) Epoch 394, batch 68, global_batch_idx: 48800, batch size: 42, loss[discriminator_loss=2.699, discriminator_real_loss=1.444, discriminator_fake_loss=1.255, generator_loss=28.59, generator_mel_loss=18.06, generator_kl_loss=1.571, generator_dur_loss=1.66, generator_adv_loss=1.908, generator_feat_match_loss=5.392, over 42.00 samples.], tot_loss[discriminator_loss=2.709, discriminator_real_loss=1.371, discriminator_fake_loss=1.338, generator_loss=27.84, generator_mel_loss=18.09, generator_kl_loss=1.395, generator_dur_loss=1.757, generator_adv_loss=1.943, generator_feat_match_loss=4.654, over 4161.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 16:25:26,137 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 16:25:34,359 INFO [train.py:591] (2/6) Epoch 394, validation: discriminator_loss=2.725, discriminator_real_loss=1.438, discriminator_fake_loss=1.287, generator_loss=26.54, generator_mel_loss=18.13, generator_kl_loss=1.228, generator_dur_loss=1.831, generator_adv_loss=1.875, generator_feat_match_loss=3.482, over 100.00 samples.
2024-03-13 16:25:34,360 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 16:27:50,237 INFO [train.py:527] (2/6) Epoch 394, batch 118, global_batch_idx: 48850, batch size: 52, loss[discriminator_loss=2.648, discriminator_real_loss=1.311, discriminator_fake_loss=1.336, generator_loss=28.45, generator_mel_loss=18.41, generator_kl_loss=1.537, generator_dur_loss=1.728, generator_adv_loss=1.912, generator_feat_match_loss=4.87, over 52.00 samples.], tot_loss[discriminator_loss=2.709, discriminator_real_loss=1.369, discriminator_fake_loss=1.339, generator_loss=27.95, generator_mel_loss=18.14, generator_kl_loss=1.408, generator_dur_loss=1.751, generator_adv_loss=1.949, generator_feat_match_loss=4.701, over 6683.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 16:28:05,133 INFO [train.py:919] (2/6) Start epoch 395
2024-03-13 16:30:31,068 INFO [train.py:527] (2/6) Epoch 395, batch 44, global_batch_idx: 48900, batch size: 58, loss[discriminator_loss=2.72, discriminator_real_loss=1.404, discriminator_fake_loss=1.316, generator_loss=27.67, generator_mel_loss=18.15, generator_kl_loss=1.376, generator_dur_loss=1.722, generator_adv_loss=2.038, generator_feat_match_loss=4.385, over 58.00 samples.], tot_loss[discriminator_loss=2.722, discriminator_real_loss=1.388, discriminator_fake_loss=1.334, generator_loss=27.8, generator_mel_loss=18.1, generator_kl_loss=1.391, generator_dur_loss=1.758, generator_adv_loss=1.945, generator_feat_match_loss=4.607, over 2452.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 16:32:51,160 INFO [train.py:527] (2/6) Epoch 395, batch 94, global_batch_idx: 48950, batch size: 64, loss[discriminator_loss=2.751, discriminator_real_loss=1.372, discriminator_fake_loss=1.379, generator_loss=27.98, generator_mel_loss=18.22, generator_kl_loss=1.495, generator_dur_loss=1.747, generator_adv_loss=2.087, generator_feat_match_loss=4.437, over 64.00 samples.], tot_loss[discriminator_loss=2.712, discriminator_real_loss=1.376, discriminator_fake_loss=1.337, generator_loss=27.87, generator_mel_loss=18.12, generator_kl_loss=1.388, generator_dur_loss=1.761, generator_adv_loss=1.95, generator_feat_match_loss=4.655, over 5398.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 16:34:12,774 INFO [train.py:919] (2/6) Start epoch 396
2024-03-13 16:35:35,009 INFO [train.py:527] (2/6) Epoch 396, batch 20, global_batch_idx: 49000, batch size: 36, loss[discriminator_loss=2.727, discriminator_real_loss=1.368, discriminator_fake_loss=1.358, generator_loss=27.78, generator_mel_loss=18.01, generator_kl_loss=1.539, generator_dur_loss=1.705, generator_adv_loss=1.889, generator_feat_match_loss=4.635, over 36.00 samples.], tot_loss[discriminator_loss=2.724, discriminator_real_loss=1.371, discriminator_fake_loss=1.353, generator_loss=27.75, generator_mel_loss=18.07, generator_kl_loss=1.419, generator_dur_loss=1.78, generator_adv_loss=1.956, generator_feat_match_loss=4.518, over 1183.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 16:35:35,011 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 16:35:43,003 INFO [train.py:591] (2/6) Epoch 396, validation: discriminator_loss=2.766, discriminator_real_loss=1.413, discriminator_fake_loss=1.353, generator_loss=27.43, generator_mel_loss=18.44, generator_kl_loss=1.212, generator_dur_loss=1.83, generator_adv_loss=1.883, generator_feat_match_loss=4.072, over 100.00 samples.
2024-03-13 16:35:43,004 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 16:37:59,754 INFO [train.py:527] (2/6) Epoch 396, batch 70, global_batch_idx: 49050, batch size: 39, loss[discriminator_loss=2.698, discriminator_real_loss=1.399, discriminator_fake_loss=1.299, generator_loss=28.46, generator_mel_loss=18.43, generator_kl_loss=1.46, generator_dur_loss=1.721, generator_adv_loss=1.88, generator_feat_match_loss=4.967, over 39.00 samples.], tot_loss[discriminator_loss=2.729, discriminator_real_loss=1.385, discriminator_fake_loss=1.344, generator_loss=27.67, generator_mel_loss=18.07, generator_kl_loss=1.414, generator_dur_loss=1.768, generator_adv_loss=1.937, generator_feat_match_loss=4.473, over 3943.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 16:40:17,413 INFO [train.py:527] (2/6) Epoch 396, batch 120, global_batch_idx: 49100, batch size: 52, loss[discriminator_loss=2.651, discriminator_real_loss=1.319, discriminator_fake_loss=1.332, generator_loss=29.28, generator_mel_loss=18.28, generator_kl_loss=1.488, generator_dur_loss=1.678, generator_adv_loss=2.236, generator_feat_match_loss=5.592, over 52.00 samples.], tot_loss[discriminator_loss=2.723, discriminator_real_loss=1.38, discriminator_fake_loss=1.343, generator_loss=27.79, generator_mel_loss=18.1, generator_kl_loss=1.42, generator_dur_loss=1.752, generator_adv_loss=1.952, generator_feat_match_loss=4.57, over 6631.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 16:40:26,465 INFO [train.py:919] (2/6) Start epoch 397
2024-03-13 16:42:57,400 INFO [train.py:527] (2/6) Epoch 397, batch 46, global_batch_idx: 49150, batch size: 83, loss[discriminator_loss=2.739, discriminator_real_loss=1.407, discriminator_fake_loss=1.332, generator_loss=26.3, generator_mel_loss=17.46, generator_kl_loss=1.232, generator_dur_loss=1.826, generator_adv_loss=1.904, generator_feat_match_loss=3.877, over 83.00 samples.], tot_loss[discriminator_loss=2.723, discriminator_real_loss=1.381, discriminator_fake_loss=1.343, generator_loss=27.78, generator_mel_loss=18.09, generator_kl_loss=1.396, generator_dur_loss=1.749, generator_adv_loss=1.948, generator_feat_match_loss=4.594, over 2867.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 16:45:16,720 INFO [train.py:527] (2/6) Epoch 397, batch 96, global_batch_idx: 49200, batch size: 36, loss[discriminator_loss=2.758, discriminator_real_loss=1.506, discriminator_fake_loss=1.252, generator_loss=27.14, generator_mel_loss=17.81, generator_kl_loss=1.646, generator_dur_loss=1.626, generator_adv_loss=1.699, generator_feat_match_loss=4.351, over 36.00 samples.], tot_loss[discriminator_loss=2.724, discriminator_real_loss=1.378, discriminator_fake_loss=1.346, generator_loss=27.77, generator_mel_loss=18.08, generator_kl_loss=1.41, generator_dur_loss=1.734, generator_adv_loss=1.94, generator_feat_match_loss=4.609, over 5570.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 16:45:16,722 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 16:45:25,874 INFO [train.py:591] (2/6) Epoch 397, validation: discriminator_loss=2.879, discriminator_real_loss=1.341, discriminator_fake_loss=1.538, generator_loss=26.4, generator_mel_loss=18.34, generator_kl_loss=1.162, generator_dur_loss=1.801, generator_adv_loss=1.615, generator_feat_match_loss=3.478, over 100.00 samples.
2024-03-13 16:45:25,875 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 16:46:39,734 INFO [train.py:919] (2/6) Start epoch 398
2024-03-13 16:48:06,587 INFO [train.py:527] (2/6) Epoch 398, batch 22, global_batch_idx: 49250, batch size: 26, loss[discriminator_loss=2.659, discriminator_real_loss=1.399, discriminator_fake_loss=1.26, generator_loss=29.41, generator_mel_loss=18.33, generator_kl_loss=1.737, generator_dur_loss=1.492, generator_adv_loss=2.153, generator_feat_match_loss=5.701, over 26.00 samples.], tot_loss[discriminator_loss=2.68, discriminator_real_loss=1.352, discriminator_fake_loss=1.328, generator_loss=28.17, generator_mel_loss=18.18, generator_kl_loss=1.409, generator_dur_loss=1.723, generator_adv_loss=1.976, generator_feat_match_loss=4.877, over 1236.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 16:50:27,800 INFO [train.py:527] (2/6) Epoch 398, batch 72, global_batch_idx: 49300, batch size: 59, loss[discriminator_loss=2.802, discriminator_real_loss=1.391, discriminator_fake_loss=1.411, generator_loss=27.54, generator_mel_loss=18.04, generator_kl_loss=1.457, generator_dur_loss=1.755, generator_adv_loss=1.872, generator_feat_match_loss=4.409, over 59.00 samples.], tot_loss[discriminator_loss=2.709, discriminator_real_loss=1.367, discriminator_fake_loss=1.342, generator_loss=27.97, generator_mel_loss=18.12, generator_kl_loss=1.413, generator_dur_loss=1.729, generator_adv_loss=1.945, generator_feat_match_loss=4.76, over 4283.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 16:52:46,069 INFO [train.py:527] (2/6) Epoch 398, batch 122, global_batch_idx: 49350, batch size: 48, loss[discriminator_loss=2.768, discriminator_real_loss=1.433, discriminator_fake_loss=1.335, generator_loss=27.11, generator_mel_loss=17.63, generator_kl_loss=1.517, generator_dur_loss=1.637, generator_adv_loss=1.915, generator_feat_match_loss=4.419, over 48.00 samples.], tot_loss[discriminator_loss=2.714, discriminator_real_loss=1.371, discriminator_fake_loss=1.343, generator_loss=27.88, generator_mel_loss=18.1, generator_kl_loss=1.412, generator_dur_loss=1.734, generator_adv_loss=1.941, generator_feat_match_loss=4.694, over 7074.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 16:52:51,466 INFO [train.py:919] (2/6) Start epoch 399
2024-03-13 16:55:32,785 INFO [train.py:527] (2/6) Epoch 399, batch 48, global_batch_idx: 49400, batch size: 52, loss[discriminator_loss=2.737, discriminator_real_loss=1.422, discriminator_fake_loss=1.315, generator_loss=28.56, generator_mel_loss=18.39, generator_kl_loss=1.537, generator_dur_loss=1.702, generator_adv_loss=1.847, generator_feat_match_loss=5.084, over 52.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.392, discriminator_fake_loss=1.334, generator_loss=27.82, generator_mel_loss=18.11, generator_kl_loss=1.428, generator_dur_loss=1.731, generator_adv_loss=1.94, generator_feat_match_loss=4.609, over 2711.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 16:55:32,787 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 16:55:40,686 INFO [train.py:591] (2/6) Epoch 399, validation: discriminator_loss=2.758, discriminator_real_loss=1.359, discriminator_fake_loss=1.399, generator_loss=26.71, generator_mel_loss=17.97, generator_kl_loss=1.191, generator_dur_loss=1.789, generator_adv_loss=1.772, generator_feat_match_loss=3.995, over 100.00 samples.
2024-03-13 16:55:40,688 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 16:58:02,448 INFO [train.py:527] (2/6) Epoch 399, batch 98, global_batch_idx: 49450, batch size: 70, loss[discriminator_loss=2.768, discriminator_real_loss=1.373, discriminator_fake_loss=1.396, generator_loss=26.22, generator_mel_loss=17.29, generator_kl_loss=1.17, generator_dur_loss=1.827, generator_adv_loss=1.922, generator_feat_match_loss=4.015, over 70.00 samples.], tot_loss[discriminator_loss=2.727, discriminator_real_loss=1.388, discriminator_fake_loss=1.34, generator_loss=27.75, generator_mel_loss=18.04, generator_kl_loss=1.408, generator_dur_loss=1.755, generator_adv_loss=1.946, generator_feat_match_loss=4.6, over 5794.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 16:59:12,879 INFO [train.py:919] (2/6) Start epoch 400
2024-03-13 17:00:45,664 INFO [train.py:527] (2/6) Epoch 400, batch 24, global_batch_idx: 49500, batch size: 31, loss[discriminator_loss=2.765, discriminator_real_loss=1.547, discriminator_fake_loss=1.218, generator_loss=28.76, generator_mel_loss=18.82, generator_kl_loss=1.54, generator_dur_loss=1.545, generator_adv_loss=1.894, generator_feat_match_loss=4.958, over 31.00 samples.], tot_loss[discriminator_loss=2.733, discriminator_real_loss=1.388, discriminator_fake_loss=1.345, generator_loss=27.82, generator_mel_loss=18.1, generator_kl_loss=1.429, generator_dur_loss=1.764, generator_adv_loss=1.929, generator_feat_match_loss=4.593, over 1407.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 17:03:05,346 INFO [train.py:527] (2/6) Epoch 400, batch 74, global_batch_idx: 49550, batch size: 64, loss[discriminator_loss=2.679, discriminator_real_loss=1.408, discriminator_fake_loss=1.271, generator_loss=27.67, generator_mel_loss=18.16, generator_kl_loss=1.436, generator_dur_loss=1.752, generator_adv_loss=2.032, generator_feat_match_loss=4.294, over 64.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.384, discriminator_fake_loss=1.342, generator_loss=27.78, generator_mel_loss=18.08, generator_kl_loss=1.439, generator_dur_loss=1.766, generator_adv_loss=1.933, generator_feat_match_loss=4.558, over 4069.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 17:05:20,409 INFO [train.py:919] (2/6) Start epoch 401
2024-03-13 17:05:44,943 INFO [train.py:527] (2/6) Epoch 401, batch 0, global_batch_idx: 49600, batch size: 44, loss[discriminator_loss=2.647, discriminator_real_loss=1.36, discriminator_fake_loss=1.288, generator_loss=27.8, generator_mel_loss=18.47, generator_kl_loss=1.45, generator_dur_loss=1.703, generator_adv_loss=1.818, generator_feat_match_loss=4.356, over 44.00 samples.], tot_loss[discriminator_loss=2.647, discriminator_real_loss=1.36, discriminator_fake_loss=1.288, generator_loss=27.8, generator_mel_loss=18.47, generator_kl_loss=1.45, generator_dur_loss=1.703, generator_adv_loss=1.818, generator_feat_match_loss=4.356, over 44.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 17:05:44,946 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 17:05:52,962 INFO [train.py:591] (2/6) Epoch 401, validation: discriminator_loss=2.752, discriminator_real_loss=1.332, discriminator_fake_loss=1.42, generator_loss=26.54, generator_mel_loss=18.37, generator_kl_loss=1.296, generator_dur_loss=1.826, generator_adv_loss=1.745, generator_feat_match_loss=3.304, over 100.00 samples.
2024-03-13 17:05:52,964 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 17:08:10,602 INFO [train.py:527] (2/6) Epoch 401, batch 50, global_batch_idx: 49650, batch size: 61, loss[discriminator_loss=2.675, discriminator_real_loss=1.315, discriminator_fake_loss=1.361, generator_loss=27.79, generator_mel_loss=17.94, generator_kl_loss=1.376, generator_dur_loss=1.754, generator_adv_loss=1.958, generator_feat_match_loss=4.759, over 61.00 samples.], tot_loss[discriminator_loss=2.714, discriminator_real_loss=1.377, discriminator_fake_loss=1.337, generator_loss=27.9, generator_mel_loss=18.12, generator_kl_loss=1.432, generator_dur_loss=1.759, generator_adv_loss=1.95, generator_feat_match_loss=4.636, over 2934.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 17:10:29,586 INFO [train.py:527] (2/6) Epoch 401, batch 100, global_batch_idx: 49700, batch size: 36, loss[discriminator_loss=2.746, discriminator_real_loss=1.405, discriminator_fake_loss=1.341, generator_loss=27.92, generator_mel_loss=18.18, generator_kl_loss=1.478, generator_dur_loss=1.655, generator_adv_loss=1.934, generator_feat_match_loss=4.676, over 36.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.38, discriminator_fake_loss=1.336, generator_loss=27.96, generator_mel_loss=18.12, generator_kl_loss=1.44, generator_dur_loss=1.754, generator_adv_loss=1.944, generator_feat_match_loss=4.701, over 5639.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 17:11:36,491 INFO [train.py:919] (2/6) Start epoch 402
2024-03-13 17:13:12,086 INFO [train.py:527] (2/6) Epoch 402, batch 26, global_batch_idx: 49750, batch size: 64, loss[discriminator_loss=2.852, discriminator_real_loss=1.591, discriminator_fake_loss=1.261, generator_loss=26.84, generator_mel_loss=17.83, generator_kl_loss=1.417, generator_dur_loss=1.771, generator_adv_loss=1.725, generator_feat_match_loss=4.095, over 64.00 samples.], tot_loss[discriminator_loss=2.718, discriminator_real_loss=1.367, discriminator_fake_loss=1.351, generator_loss=27.98, generator_mel_loss=18.05, generator_kl_loss=1.414, generator_dur_loss=1.75, generator_adv_loss=2, generator_feat_match_loss=4.765, over 1463.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 17:15:32,492 INFO [train.py:527] (2/6) Epoch 402, batch 76, global_batch_idx: 49800, batch size: 58, loss[discriminator_loss=2.677, discriminator_real_loss=1.368, discriminator_fake_loss=1.309, generator_loss=27.83, generator_mel_loss=18.34, generator_kl_loss=1.448, generator_dur_loss=1.717, generator_adv_loss=1.847, generator_feat_match_loss=4.478, over 58.00 samples.], tot_loss[discriminator_loss=2.718, discriminator_real_loss=1.378, discriminator_fake_loss=1.34, generator_loss=27.95, generator_mel_loss=18.1, generator_kl_loss=1.407, generator_dur_loss=1.76, generator_adv_loss=1.982, generator_feat_match_loss=4.704, over 4352.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 17:15:32,494 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 17:15:40,609 INFO [train.py:591] (2/6) Epoch 402, validation: discriminator_loss=2.792, discriminator_real_loss=1.35, discriminator_fake_loss=1.442, generator_loss=27.21, generator_mel_loss=18.53, generator_kl_loss=1.328, generator_dur_loss=1.833, generator_adv_loss=1.747, generator_feat_match_loss=3.771, over 100.00 samples.
2024-03-13 17:15:40,610 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 17:17:51,306 INFO [train.py:919] (2/6) Start epoch 403
2024-03-13 17:18:19,574 INFO [train.py:527] (2/6) Epoch 403, batch 2, global_batch_idx: 49850, batch size: 25, loss[discriminator_loss=2.625, discriminator_real_loss=1.337, discriminator_fake_loss=1.288, generator_loss=29.07, generator_mel_loss=18.46, generator_kl_loss=1.772, generator_dur_loss=1.542, generator_adv_loss=2.067, generator_feat_match_loss=5.237, over 25.00 samples.], tot_loss[discriminator_loss=2.651, discriminator_real_loss=1.328, discriminator_fake_loss=1.323, generator_loss=27.93, generator_mel_loss=18.04, generator_kl_loss=1.643, generator_dur_loss=1.674, generator_adv_loss=1.958, generator_feat_match_loss=4.616, over 130.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 17:20:38,887 INFO [train.py:527] (2/6) Epoch 403, batch 52, global_batch_idx: 49900, batch size: 48, loss[discriminator_loss=2.759, discriminator_real_loss=1.442, discriminator_fake_loss=1.317, generator_loss=27.18, generator_mel_loss=17.79, generator_kl_loss=1.37, generator_dur_loss=1.722, generator_adv_loss=2.041, generator_feat_match_loss=4.257, over 48.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.375, discriminator_fake_loss=1.345, generator_loss=27.74, generator_mel_loss=18.05, generator_kl_loss=1.381, generator_dur_loss=1.774, generator_adv_loss=1.939, generator_feat_match_loss=4.6, over 3262.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 17:22:55,454 INFO [train.py:527] (2/6) Epoch 403, batch 102, global_batch_idx: 49950, batch size: 52, loss[discriminator_loss=2.691, discriminator_real_loss=1.386, discriminator_fake_loss=1.305, generator_loss=27.89, generator_mel_loss=17.74, generator_kl_loss=1.612, generator_dur_loss=1.741, generator_adv_loss=1.992, generator_feat_match_loss=4.8, over 52.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.376, discriminator_fake_loss=1.341, generator_loss=27.84, generator_mel_loss=18.1, generator_kl_loss=1.395, generator_dur_loss=1.763, generator_adv_loss=1.936, generator_feat_match_loss=4.646, over 6023.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 17:23:57,035 INFO [train.py:919] (2/6) Start epoch 404
2024-03-13 17:25:39,436 INFO [train.py:527] (2/6) Epoch 404, batch 28, global_batch_idx: 50000, batch size: 66, loss[discriminator_loss=2.743, discriminator_real_loss=1.374, discriminator_fake_loss=1.369, generator_loss=27.7, generator_mel_loss=18.02, generator_kl_loss=1.244, generator_dur_loss=1.76, generator_adv_loss=1.886, generator_feat_match_loss=4.784, over 66.00 samples.], tot_loss[discriminator_loss=2.719, discriminator_real_loss=1.375, discriminator_fake_loss=1.345, generator_loss=27.85, generator_mel_loss=18.02, generator_kl_loss=1.382, generator_dur_loss=1.762, generator_adv_loss=1.929, generator_feat_match_loss=4.759, over 1826.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 17:25:39,437 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 17:25:47,417 INFO [train.py:591] (2/6) Epoch 404, validation: discriminator_loss=2.75, discriminator_real_loss=1.455, discriminator_fake_loss=1.296, generator_loss=26.89, generator_mel_loss=18.19, generator_kl_loss=1.2, generator_dur_loss=1.796, generator_adv_loss=1.865, generator_feat_match_loss=3.839, over 100.00 samples.
2024-03-13 17:25:47,418 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 17:28:05,612 INFO [train.py:527] (2/6) Epoch 404, batch 78, global_batch_idx: 50050, batch size: 39, loss[discriminator_loss=2.718, discriminator_real_loss=1.377, discriminator_fake_loss=1.341, generator_loss=28.15, generator_mel_loss=18.08, generator_kl_loss=1.452, generator_dur_loss=1.681, generator_adv_loss=1.934, generator_feat_match_loss=5.004, over 39.00 samples.], tot_loss[discriminator_loss=2.721, discriminator_real_loss=1.379, discriminator_fake_loss=1.342, generator_loss=27.78, generator_mel_loss=18.06, generator_kl_loss=1.398, generator_dur_loss=1.735, generator_adv_loss=1.938, generator_feat_match_loss=4.65, over 4374.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 17:30:10,271 INFO [train.py:919] (2/6) Start epoch 405
2024-03-13 17:30:43,964 INFO [train.py:527] (2/6) Epoch 405, batch 4, global_batch_idx: 50100, batch size: 68, loss[discriminator_loss=2.705, discriminator_real_loss=1.419, discriminator_fake_loss=1.287, generator_loss=28.33, generator_mel_loss=18.31, generator_kl_loss=1.275, generator_dur_loss=1.736, generator_adv_loss=1.963, generator_feat_match_loss=5.043, over 68.00 samples.], tot_loss[discriminator_loss=2.712, discriminator_real_loss=1.398, discriminator_fake_loss=1.314, generator_loss=27.95, generator_mel_loss=18.08, generator_kl_loss=1.424, generator_dur_loss=1.713, generator_adv_loss=1.956, generator_feat_match_loss=4.772, over 261.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 17:33:06,903 INFO [train.py:527] (2/6) Epoch 405, batch 54, global_batch_idx: 50150, batch size: 61, loss[discriminator_loss=2.729, discriminator_real_loss=1.427, discriminator_fake_loss=1.302, generator_loss=27.83, generator_mel_loss=17.99, generator_kl_loss=1.493, generator_dur_loss=1.771, generator_adv_loss=1.906, generator_feat_match_loss=4.667, over 61.00 samples.], tot_loss[discriminator_loss=2.707, discriminator_real_loss=1.367, discriminator_fake_loss=1.34, generator_loss=28.01, generator_mel_loss=18.13, generator_kl_loss=1.407, generator_dur_loss=1.761, generator_adv_loss=1.938, generator_feat_match_loss=4.768, over 3360.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 17:35:24,884 INFO [train.py:527] (2/6) Epoch 405, batch 104, global_batch_idx: 50200, batch size: 62, loss[discriminator_loss=2.718, discriminator_real_loss=1.334, discriminator_fake_loss=1.384, generator_loss=28.2, generator_mel_loss=18.29, generator_kl_loss=1.337, generator_dur_loss=1.724, generator_adv_loss=1.906, generator_feat_match_loss=4.94, over 62.00 samples.], tot_loss[discriminator_loss=2.71, discriminator_real_loss=1.37, discriminator_fake_loss=1.34, generator_loss=27.96, generator_mel_loss=18.12, generator_kl_loss=1.407, generator_dur_loss=1.758, generator_adv_loss=1.94, generator_feat_match_loss=4.738, over 6310.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 17:35:24,885 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 17:35:33,903 INFO [train.py:591] (2/6) Epoch 405, validation: discriminator_loss=2.778, discriminator_real_loss=1.448, discriminator_fake_loss=1.33, generator_loss=28.05, generator_mel_loss=18.97, generator_kl_loss=1.287, generator_dur_loss=1.812, generator_adv_loss=1.879, generator_feat_match_loss=4.106, over 100.00 samples.
2024-03-13 17:35:33,905 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 17:36:23,250 INFO [train.py:919] (2/6) Start epoch 406
2024-03-13 17:38:09,541 INFO [train.py:527] (2/6) Epoch 406, batch 30, global_batch_idx: 50250, batch size: 64, loss[discriminator_loss=2.764, discriminator_real_loss=1.47, discriminator_fake_loss=1.295, generator_loss=27.73, generator_mel_loss=17.97, generator_kl_loss=1.353, generator_dur_loss=1.783, generator_adv_loss=2.027, generator_feat_match_loss=4.599, over 64.00 samples.], tot_loss[discriminator_loss=2.71, discriminator_real_loss=1.375, discriminator_fake_loss=1.336, generator_loss=27.98, generator_mel_loss=18.17, generator_kl_loss=1.394, generator_dur_loss=1.737, generator_adv_loss=1.94, generator_feat_match_loss=4.74, over 1693.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 17:40:30,659 INFO [train.py:527] (2/6) Epoch 406, batch 80, global_batch_idx: 50300, batch size: 68, loss[discriminator_loss=2.724, discriminator_real_loss=1.403, discriminator_fake_loss=1.321, generator_loss=27.49, generator_mel_loss=18.32, generator_kl_loss=1.564, generator_dur_loss=1.735, generator_adv_loss=2.046, generator_feat_match_loss=3.83, over 68.00 samples.], tot_loss[discriminator_loss=2.714, discriminator_real_loss=1.374, discriminator_fake_loss=1.34, generator_loss=27.91, generator_mel_loss=18.13, generator_kl_loss=1.408, generator_dur_loss=1.748, generator_adv_loss=1.94, generator_feat_match_loss=4.684, over 4580.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 17:42:26,851 INFO [train.py:919] (2/6) Start epoch 407
2024-03-13 17:43:09,001 INFO [train.py:527] (2/6) Epoch 407, batch 6, global_batch_idx: 50350, batch size: 13, loss[discriminator_loss=2.62, discriminator_real_loss=1.291, discriminator_fake_loss=1.328, generator_loss=30.2, generator_mel_loss=19.22, generator_kl_loss=1.925, generator_dur_loss=1.595, generator_adv_loss=1.918, generator_feat_match_loss=5.55, over 13.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.375, discriminator_fake_loss=1.352, generator_loss=28.27, generator_mel_loss=18.41, generator_kl_loss=1.463, generator_dur_loss=1.712, generator_adv_loss=1.961, generator_feat_match_loss=4.717, over 296.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 17:45:26,354 INFO [train.py:527] (2/6) Epoch 407, batch 56, global_batch_idx: 50400, batch size: 42, loss[discriminator_loss=2.698, discriminator_real_loss=1.326, discriminator_fake_loss=1.372, generator_loss=28.95, generator_mel_loss=18.65, generator_kl_loss=1.445, generator_dur_loss=1.686, generator_adv_loss=1.947, generator_feat_match_loss=5.23, over 42.00 samples.], tot_loss[discriminator_loss=2.731, discriminator_real_loss=1.372, discriminator_fake_loss=1.359, generator_loss=28.14, generator_mel_loss=18.27, generator_kl_loss=1.444, generator_dur_loss=1.746, generator_adv_loss=1.953, generator_feat_match_loss=4.722, over 2970.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 17:45:26,355 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 17:45:34,377 INFO [train.py:591] (2/6) Epoch 407, validation: discriminator_loss=2.685, discriminator_real_loss=1.383, discriminator_fake_loss=1.302, generator_loss=27.62, generator_mel_loss=18.64, generator_kl_loss=1.114, generator_dur_loss=1.828, generator_adv_loss=1.979, generator_feat_match_loss=4.061, over 100.00 samples.
2024-03-13 17:45:34,378 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 17:47:53,243 INFO [train.py:527] (2/6) Epoch 407, batch 106, global_batch_idx: 50450, batch size: 55, loss[discriminator_loss=2.704, discriminator_real_loss=1.413, discriminator_fake_loss=1.292, generator_loss=27.46, generator_mel_loss=17.82, generator_kl_loss=1.346, generator_dur_loss=1.754, generator_adv_loss=1.92, generator_feat_match_loss=4.619, over 55.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.373, discriminator_fake_loss=1.347, generator_loss=28.03, generator_mel_loss=18.15, generator_kl_loss=1.434, generator_dur_loss=1.756, generator_adv_loss=1.953, generator_feat_match_loss=4.737, over 5890.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 17:48:41,156 INFO [train.py:919] (2/6) Start epoch 408
2024-03-13 17:50:32,336 INFO [train.py:527] (2/6) Epoch 408, batch 32, global_batch_idx: 50500, batch size: 70, loss[discriminator_loss=2.736, discriminator_real_loss=1.409, discriminator_fake_loss=1.327, generator_loss=27.09, generator_mel_loss=17.87, generator_kl_loss=1.35, generator_dur_loss=1.81, generator_adv_loss=1.815, generator_feat_match_loss=4.248, over 70.00 samples.], tot_loss[discriminator_loss=2.724, discriminator_real_loss=1.377, discriminator_fake_loss=1.348, generator_loss=27.72, generator_mel_loss=18.04, generator_kl_loss=1.382, generator_dur_loss=1.768, generator_adv_loss=1.926, generator_feat_match_loss=4.604, over 1923.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 17:52:51,952 INFO [train.py:527] (2/6) Epoch 408, batch 82, global_batch_idx: 50550, batch size: 48, loss[discriminator_loss=2.721, discriminator_real_loss=1.409, discriminator_fake_loss=1.313, generator_loss=28.19, generator_mel_loss=18.27, generator_kl_loss=1.6, generator_dur_loss=1.659, generator_adv_loss=1.966, generator_feat_match_loss=4.695, over 48.00 samples.], tot_loss[discriminator_loss=2.725, discriminator_real_loss=1.383, discriminator_fake_loss=1.342, generator_loss=27.84, generator_mel_loss=18.09, generator_kl_loss=1.401, generator_dur_loss=1.762, generator_adv_loss=1.946, generator_feat_match_loss=4.636, over 4734.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 17:54:46,907 INFO [train.py:919] (2/6) Start epoch 409
2024-03-13 17:55:34,359 INFO [train.py:527] (2/6) Epoch 409, batch 8, global_batch_idx: 50600, batch size: 31, loss[discriminator_loss=2.649, discriminator_real_loss=1.256, discriminator_fake_loss=1.393, generator_loss=28.35, generator_mel_loss=18.28, generator_kl_loss=1.524, generator_dur_loss=1.642, generator_adv_loss=2.007, generator_feat_match_loss=4.897, over 31.00 samples.], tot_loss[discriminator_loss=2.693, discriminator_real_loss=1.372, discriminator_fake_loss=1.321, generator_loss=28.21, generator_mel_loss=18.12, generator_kl_loss=1.405, generator_dur_loss=1.772, generator_adv_loss=1.99, generator_feat_match_loss=4.927, over 515.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 17:55:34,364 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 17:55:42,243 INFO [train.py:591] (2/6) Epoch 409, validation: discriminator_loss=2.737, discriminator_real_loss=1.413, discriminator_fake_loss=1.323, generator_loss=27.31, generator_mel_loss=18.66, generator_kl_loss=1.288, generator_dur_loss=1.834, generator_adv_loss=1.885, generator_feat_match_loss=3.637, over 100.00 samples.
2024-03-13 17:55:42,245 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 17:58:01,427 INFO [train.py:527] (2/6) Epoch 409, batch 58, global_batch_idx: 50650, batch size: 45, loss[discriminator_loss=2.662, discriminator_real_loss=1.262, discriminator_fake_loss=1.4, generator_loss=29.55, generator_mel_loss=18.86, generator_kl_loss=1.605, generator_dur_loss=1.697, generator_adv_loss=1.943, generator_feat_match_loss=5.448, over 45.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.371, discriminator_fake_loss=1.344, generator_loss=27.98, generator_mel_loss=18.1, generator_kl_loss=1.378, generator_dur_loss=1.782, generator_adv_loss=1.951, generator_feat_match_loss=4.774, over 3647.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 18:00:17,683 INFO [train.py:527] (2/6) Epoch 409, batch 108, global_batch_idx: 50700, batch size: 36, loss[discriminator_loss=2.69, discriminator_real_loss=1.341, discriminator_fake_loss=1.349, generator_loss=28.87, generator_mel_loss=18.91, generator_kl_loss=1.638, generator_dur_loss=1.664, generator_adv_loss=1.94, generator_feat_match_loss=4.718, over 36.00 samples.], tot_loss[discriminator_loss=2.711, discriminator_real_loss=1.37, discriminator_fake_loss=1.341, generator_loss=27.98, generator_mel_loss=18.09, generator_kl_loss=1.394, generator_dur_loss=1.772, generator_adv_loss=1.948, generator_feat_match_loss=4.777, over 6533.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 18:01:00,012 INFO [train.py:919] (2/6) Start epoch 410
2024-03-13 18:02:59,006 INFO [train.py:527] (2/6) Epoch 410, batch 34, global_batch_idx: 50750, batch size: 55, loss[discriminator_loss=2.745, discriminator_real_loss=1.423, discriminator_fake_loss=1.321, generator_loss=28.62, generator_mel_loss=18.18, generator_kl_loss=1.382, generator_dur_loss=1.711, generator_adv_loss=2.143, generator_feat_match_loss=5.21, over 55.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.369, discriminator_fake_loss=1.348, generator_loss=27.96, generator_mel_loss=18.11, generator_kl_loss=1.392, generator_dur_loss=1.727, generator_adv_loss=1.972, generator_feat_match_loss=4.763, over 2078.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 18:05:17,678 INFO [train.py:527] (2/6) Epoch 410, batch 84, global_batch_idx: 50800, batch size: 25, loss[discriminator_loss=2.694, discriminator_real_loss=1.451, discriminator_fake_loss=1.243, generator_loss=29.22, generator_mel_loss=18.72, generator_kl_loss=1.72, generator_dur_loss=1.553, generator_adv_loss=1.843, generator_feat_match_loss=5.39, over 25.00 samples.], tot_loss[discriminator_loss=2.717, discriminator_real_loss=1.377, discriminator_fake_loss=1.34, generator_loss=27.98, generator_mel_loss=18.1, generator_kl_loss=1.404, generator_dur_loss=1.738, generator_adv_loss=1.967, generator_feat_match_loss=4.765, over 4875.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 18:05:17,679 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 18:05:26,739 INFO [train.py:591] (2/6) Epoch 410, validation: discriminator_loss=2.764, discriminator_real_loss=1.383, discriminator_fake_loss=1.381, generator_loss=27.16, generator_mel_loss=18.4, generator_kl_loss=1.374, generator_dur_loss=1.794, generator_adv_loss=1.795, generator_feat_match_loss=3.795, over 100.00 samples.
2024-03-13 18:05:26,740 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 18:07:15,482 INFO [train.py:919] (2/6) Start epoch 411
2024-03-13 18:08:06,530 INFO [train.py:527] (2/6) Epoch 411, batch 10, global_batch_idx: 50850, batch size: 48, loss[discriminator_loss=2.717, discriminator_real_loss=1.386, discriminator_fake_loss=1.332, generator_loss=28.49, generator_mel_loss=18.4, generator_kl_loss=1.481, generator_dur_loss=1.7, generator_adv_loss=2.111, generator_feat_match_loss=4.799, over 48.00 samples.], tot_loss[discriminator_loss=2.709, discriminator_real_loss=1.357, discriminator_fake_loss=1.352, generator_loss=28.14, generator_mel_loss=18.16, generator_kl_loss=1.42, generator_dur_loss=1.782, generator_adv_loss=1.958, generator_feat_match_loss=4.823, over 669.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 18:10:22,404 INFO [train.py:527] (2/6) Epoch 411, batch 60, global_batch_idx: 50900, batch size: 66, loss[discriminator_loss=2.725, discriminator_real_loss=1.377, discriminator_fake_loss=1.347, generator_loss=28.45, generator_mel_loss=18.04, generator_kl_loss=1.514, generator_dur_loss=1.797, generator_adv_loss=1.933, generator_feat_match_loss=5.165, over 66.00 samples.], tot_loss[discriminator_loss=2.711, discriminator_real_loss=1.367, discriminator_fake_loss=1.344, generator_loss=28.06, generator_mel_loss=18.14, generator_kl_loss=1.442, generator_dur_loss=1.742, generator_adv_loss=1.95, generator_feat_match_loss=4.788, over 3447.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 18:12:40,482 INFO [train.py:527] (2/6) Epoch 411, batch 110, global_batch_idx: 50950, batch size: 59, loss[discriminator_loss=2.693, discriminator_real_loss=1.384, discriminator_fake_loss=1.309, generator_loss=27.91, generator_mel_loss=17.91, generator_kl_loss=1.356, generator_dur_loss=1.733, generator_adv_loss=2.036, generator_feat_match_loss=4.87, over 59.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.371, discriminator_fake_loss=1.344, generator_loss=27.99, generator_mel_loss=18.11, generator_kl_loss=1.436, generator_dur_loss=1.735, generator_adv_loss=1.953, generator_feat_match_loss=4.751, over 6247.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 18:13:19,974 INFO [train.py:919] (2/6) Start epoch 412
2024-03-13 18:15:23,112 INFO [train.py:527] (2/6) Epoch 412, batch 36, global_batch_idx: 51000, batch size: 55, loss[discriminator_loss=2.706, discriminator_real_loss=1.366, discriminator_fake_loss=1.34, generator_loss=28.07, generator_mel_loss=18.07, generator_kl_loss=1.535, generator_dur_loss=1.745, generator_adv_loss=1.87, generator_feat_match_loss=4.847, over 55.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.369, discriminator_fake_loss=1.346, generator_loss=27.88, generator_mel_loss=18.02, generator_kl_loss=1.4, generator_dur_loss=1.766, generator_adv_loss=1.945, generator_feat_match_loss=4.747, over 2281.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 18:15:23,113 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 18:15:30,954 INFO [train.py:591] (2/6) Epoch 412, validation: discriminator_loss=2.748, discriminator_real_loss=1.361, discriminator_fake_loss=1.387, generator_loss=26.67, generator_mel_loss=18.35, generator_kl_loss=1.218, generator_dur_loss=1.81, generator_adv_loss=1.756, generator_feat_match_loss=3.537, over 100.00 samples.
2024-03-13 18:15:30,955 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 18:17:48,777 INFO [train.py:527] (2/6) Epoch 412, batch 86, global_batch_idx: 51050, batch size: 72, loss[discriminator_loss=2.713, discriminator_real_loss=1.314, discriminator_fake_loss=1.399, generator_loss=27.48, generator_mel_loss=18.02, generator_kl_loss=1.378, generator_dur_loss=1.816, generator_adv_loss=1.889, generator_feat_match_loss=4.374, over 72.00 samples.], tot_loss[discriminator_loss=2.714, discriminator_real_loss=1.369, discriminator_fake_loss=1.345, generator_loss=27.91, generator_mel_loss=18.09, generator_kl_loss=1.409, generator_dur_loss=1.752, generator_adv_loss=1.945, generator_feat_match_loss=4.716, over 5029.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 18:19:30,269 INFO [train.py:919] (2/6) Start epoch 413
2024-03-13 18:20:26,278 INFO [train.py:527] (2/6) Epoch 413, batch 12, global_batch_idx: 51100, batch size: 48, loss[discriminator_loss=2.729, discriminator_real_loss=1.49, discriminator_fake_loss=1.239, generator_loss=27.99, generator_mel_loss=18.34, generator_kl_loss=1.434, generator_dur_loss=1.707, generator_adv_loss=1.974, generator_feat_match_loss=4.541, over 48.00 samples.], tot_loss[discriminator_loss=2.698, discriminator_real_loss=1.375, discriminator_fake_loss=1.324, generator_loss=28.22, generator_mel_loss=18.13, generator_kl_loss=1.445, generator_dur_loss=1.742, generator_adv_loss=2.013, generator_feat_match_loss=4.891, over 723.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 18:22:47,528 INFO [train.py:527] (2/6) Epoch 413, batch 62, global_batch_idx: 51150, batch size: 42, loss[discriminator_loss=2.773, discriminator_real_loss=1.383, discriminator_fake_loss=1.39, generator_loss=28.53, generator_mel_loss=18.6, generator_kl_loss=1.552, generator_dur_loss=1.676, generator_adv_loss=1.836, generator_feat_match_loss=4.866, over 42.00 samples.], tot_loss[discriminator_loss=2.709, discriminator_real_loss=1.372, discriminator_fake_loss=1.337, generator_loss=28.12, generator_mel_loss=18.15, generator_kl_loss=1.443, generator_dur_loss=1.751, generator_adv_loss=1.967, generator_feat_match_loss=4.816, over 3564.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 18:25:05,906 INFO [train.py:527] (2/6) Epoch 413, batch 112, global_batch_idx: 51200, batch size: 88, loss[discriminator_loss=2.677, discriminator_real_loss=1.322, discriminator_fake_loss=1.355, generator_loss=27.8, generator_mel_loss=18.05, generator_kl_loss=1.423, generator_dur_loss=1.745, generator_adv_loss=2.016, generator_feat_match_loss=4.568, over 88.00 samples.], tot_loss[discriminator_loss=2.711, discriminator_real_loss=1.371, discriminator_fake_loss=1.34, generator_loss=28.09, generator_mel_loss=18.16, generator_kl_loss=1.435, generator_dur_loss=1.747, generator_adv_loss=1.958, generator_feat_match_loss=4.797, over 6362.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 18:25:05,908 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 18:25:14,605 INFO [train.py:591] (2/6) Epoch 413, validation: discriminator_loss=2.755, discriminator_real_loss=1.459, discriminator_fake_loss=1.296, generator_loss=27.05, generator_mel_loss=18.22, generator_kl_loss=1.273, generator_dur_loss=1.791, generator_adv_loss=1.897, generator_feat_match_loss=3.872, over 100.00 samples.
2024-03-13 18:25:14,607 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 18:25:44,364 INFO [train.py:919] (2/6) Start epoch 414
2024-03-13 18:27:51,394 INFO [train.py:527] (2/6) Epoch 414, batch 38, global_batch_idx: 51250, batch size: 88, loss[discriminator_loss=2.722, discriminator_real_loss=1.326, discriminator_fake_loss=1.396, generator_loss=27.58, generator_mel_loss=17.99, generator_kl_loss=1.335, generator_dur_loss=1.757, generator_adv_loss=1.856, generator_feat_match_loss=4.638, over 88.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.374, discriminator_fake_loss=1.342, generator_loss=27.82, generator_mel_loss=18.05, generator_kl_loss=1.407, generator_dur_loss=1.74, generator_adv_loss=1.944, generator_feat_match_loss=4.676, over 2251.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 18:30:07,692 INFO [train.py:527] (2/6) Epoch 414, batch 88, global_batch_idx: 51300, batch size: 56, loss[discriminator_loss=2.718, discriminator_real_loss=1.435, discriminator_fake_loss=1.283, generator_loss=28.14, generator_mel_loss=17.96, generator_kl_loss=1.336, generator_dur_loss=1.773, generator_adv_loss=1.925, generator_feat_match_loss=5.153, over 56.00 samples.], tot_loss[discriminator_loss=2.714, discriminator_real_loss=1.37, discriminator_fake_loss=1.343, generator_loss=27.91, generator_mel_loss=18.07, generator_kl_loss=1.422, generator_dur_loss=1.738, generator_adv_loss=1.951, generator_feat_match_loss=4.722, over 5056.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 18:31:45,776 INFO [train.py:919] (2/6) Start epoch 415
2024-03-13 18:32:48,726 INFO [train.py:527] (2/6) Epoch 415, batch 14, global_batch_idx: 51350, batch size: 47, loss[discriminator_loss=2.736, discriminator_real_loss=1.38, discriminator_fake_loss=1.356, generator_loss=28.25, generator_mel_loss=18.43, generator_kl_loss=1.436, generator_dur_loss=1.724, generator_adv_loss=1.884, generator_feat_match_loss=4.769, over 47.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.388, discriminator_fake_loss=1.328, generator_loss=28, generator_mel_loss=18.03, generator_kl_loss=1.402, generator_dur_loss=1.74, generator_adv_loss=1.962, generator_feat_match_loss=4.87, over 832.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 18:35:05,723 INFO [train.py:527] (2/6) Epoch 415, batch 64, global_batch_idx: 51400, batch size: 55, loss[discriminator_loss=2.656, discriminator_real_loss=1.258, discriminator_fake_loss=1.398, generator_loss=28.63, generator_mel_loss=18.08, generator_kl_loss=1.602, generator_dur_loss=1.623, generator_adv_loss=1.976, generator_feat_match_loss=5.344, over 55.00 samples.], tot_loss[discriminator_loss=2.704, discriminator_real_loss=1.374, discriminator_fake_loss=1.331, generator_loss=28, generator_mel_loss=18.05, generator_kl_loss=1.412, generator_dur_loss=1.755, generator_adv_loss=1.948, generator_feat_match_loss=4.833, over 3737.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 18:35:05,724 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 18:35:13,672 INFO [train.py:591] (2/6) Epoch 415, validation: discriminator_loss=2.738, discriminator_real_loss=1.5, discriminator_fake_loss=1.239, generator_loss=25.83, generator_mel_loss=17.34, generator_kl_loss=1.242, generator_dur_loss=1.823, generator_adv_loss=1.931, generator_feat_match_loss=3.496, over 100.00 samples.
2024-03-13 18:35:13,673 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 18:37:33,149 INFO [train.py:527] (2/6) Epoch 415, batch 114, global_batch_idx: 51450, batch size: 31, loss[discriminator_loss=2.704, discriminator_real_loss=1.394, discriminator_fake_loss=1.31, generator_loss=27.89, generator_mel_loss=18.6, generator_kl_loss=1.644, generator_dur_loss=1.624, generator_adv_loss=1.835, generator_feat_match_loss=4.185, over 31.00 samples.], tot_loss[discriminator_loss=2.706, discriminator_real_loss=1.372, discriminator_fake_loss=1.334, generator_loss=27.99, generator_mel_loss=18.06, generator_kl_loss=1.418, generator_dur_loss=1.759, generator_adv_loss=1.944, generator_feat_match_loss=4.802, over 6526.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 18:38:00,907 INFO [train.py:919] (2/6) Start epoch 416
2024-03-13 18:40:16,395 INFO [train.py:527] (2/6) Epoch 416, batch 40, global_batch_idx: 51500, batch size: 48, loss[discriminator_loss=2.763, discriminator_real_loss=1.281, discriminator_fake_loss=1.482, generator_loss=28.4, generator_mel_loss=17.89, generator_kl_loss=1.546, generator_dur_loss=1.689, generator_adv_loss=2.251, generator_feat_match_loss=5.025, over 48.00 samples.], tot_loss[discriminator_loss=2.711, discriminator_real_loss=1.375, discriminator_fake_loss=1.337, generator_loss=28.03, generator_mel_loss=18.09, generator_kl_loss=1.413, generator_dur_loss=1.776, generator_adv_loss=1.956, generator_feat_match_loss=4.79, over 2437.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 18:42:34,150 INFO [train.py:527] (2/6) Epoch 416, batch 90, global_batch_idx: 51550, batch size: 62, loss[discriminator_loss=2.687, discriminator_real_loss=1.303, discriminator_fake_loss=1.385, generator_loss=28.68, generator_mel_loss=18.33, generator_kl_loss=1.427, generator_dur_loss=1.697, generator_adv_loss=1.916, generator_feat_match_loss=5.307, over 62.00 samples.], tot_loss[discriminator_loss=2.712, discriminator_real_loss=1.373, discriminator_fake_loss=1.339, generator_loss=27.92, generator_mel_loss=18.06, generator_kl_loss=1.411, generator_dur_loss=1.767, generator_adv_loss=1.946, generator_feat_match_loss=4.735, over 5166.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 18:44:03,608 INFO [train.py:919] (2/6) Start epoch 417
2024-03-13 18:45:10,646 INFO [train.py:527] (2/6) Epoch 417, batch 16, global_batch_idx: 51600, batch size: 68, loss[discriminator_loss=2.699, discriminator_real_loss=1.408, discriminator_fake_loss=1.291, generator_loss=27.65, generator_mel_loss=18.23, generator_kl_loss=1.351, generator_dur_loss=1.762, generator_adv_loss=1.931, generator_feat_match_loss=4.369, over 68.00 samples.], tot_loss[discriminator_loss=2.724, discriminator_real_loss=1.371, discriminator_fake_loss=1.353, generator_loss=28.05, generator_mel_loss=18.23, generator_kl_loss=1.428, generator_dur_loss=1.741, generator_adv_loss=1.93, generator_feat_match_loss=4.716, over 916.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 18:45:10,648 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 18:45:18,452 INFO [train.py:591] (2/6) Epoch 417, validation: discriminator_loss=2.71, discriminator_real_loss=1.355, discriminator_fake_loss=1.354, generator_loss=26.6, generator_mel_loss=18.32, generator_kl_loss=1.193, generator_dur_loss=1.823, generator_adv_loss=1.818, generator_feat_match_loss=3.452, over 100.00 samples.
2024-03-13 18:45:18,453 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 18:47:36,719 INFO [train.py:527] (2/6) Epoch 417, batch 66, global_batch_idx: 51650, batch size: 68, loss[discriminator_loss=2.752, discriminator_real_loss=1.341, discriminator_fake_loss=1.412, generator_loss=27.06, generator_mel_loss=17.66, generator_kl_loss=1.262, generator_dur_loss=1.772, generator_adv_loss=1.936, generator_feat_match_loss=4.434, over 68.00 samples.], tot_loss[discriminator_loss=2.705, discriminator_real_loss=1.366, discriminator_fake_loss=1.339, generator_loss=28.08, generator_mel_loss=18.19, generator_kl_loss=1.415, generator_dur_loss=1.745, generator_adv_loss=1.947, generator_feat_match_loss=4.791, over 3593.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 18:49:56,185 INFO [train.py:527] (2/6) Epoch 417, batch 116, global_batch_idx: 51700, batch size: 58, loss[discriminator_loss=2.765, discriminator_real_loss=1.445, discriminator_fake_loss=1.32, generator_loss=27.18, generator_mel_loss=17.74, generator_kl_loss=1.343, generator_dur_loss=1.759, generator_adv_loss=2.034, generator_feat_match_loss=4.307, over 58.00 samples.], tot_loss[discriminator_loss=2.707, discriminator_real_loss=1.367, discriminator_fake_loss=1.34, generator_loss=28.03, generator_mel_loss=18.15, generator_kl_loss=1.42, generator_dur_loss=1.752, generator_adv_loss=1.945, generator_feat_match_loss=4.759, over 6483.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 18:50:18,323 INFO [train.py:919] (2/6) Start epoch 418
2024-03-13 18:52:38,448 INFO [train.py:527] (2/6) Epoch 418, batch 42, global_batch_idx: 51750, batch size: 45, loss[discriminator_loss=2.642, discriminator_real_loss=1.368, discriminator_fake_loss=1.274, generator_loss=28.3, generator_mel_loss=18.19, generator_kl_loss=1.539, generator_dur_loss=1.654, generator_adv_loss=2.044, generator_feat_match_loss=4.873, over 45.00 samples.], tot_loss[discriminator_loss=2.711, discriminator_real_loss=1.371, discriminator_fake_loss=1.34, generator_loss=28.09, generator_mel_loss=18.18, generator_kl_loss=1.411, generator_dur_loss=1.766, generator_adv_loss=1.95, generator_feat_match_loss=4.781, over 2426.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 18:54:54,640 INFO [train.py:527] (2/6) Epoch 418, batch 92, global_batch_idx: 51800, batch size: 70, loss[discriminator_loss=2.687, discriminator_real_loss=1.322, discriminator_fake_loss=1.366, generator_loss=28.62, generator_mel_loss=18.5, generator_kl_loss=1.405, generator_dur_loss=1.764, generator_adv_loss=2.125, generator_feat_match_loss=4.824, over 70.00 samples.], tot_loss[discriminator_loss=2.709, discriminator_real_loss=1.371, discriminator_fake_loss=1.337, generator_loss=28.1, generator_mel_loss=18.17, generator_kl_loss=1.428, generator_dur_loss=1.76, generator_adv_loss=1.959, generator_feat_match_loss=4.789, over 5243.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 18:54:54,641 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 18:55:03,511 INFO [train.py:591] (2/6) Epoch 418, validation: discriminator_loss=2.779, discriminator_real_loss=1.581, discriminator_fake_loss=1.198, generator_loss=27.26, generator_mel_loss=18.42, generator_kl_loss=1.248, generator_dur_loss=1.792, generator_adv_loss=2.023, generator_feat_match_loss=3.77, over 100.00 samples.
2024-03-13 18:55:03,512 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 18:56:31,805 INFO [train.py:919] (2/6) Start epoch 419
2024-03-13 18:57:48,417 INFO [train.py:527] (2/6) Epoch 419, batch 18, global_batch_idx: 51850, batch size: 96, loss[discriminator_loss=2.731, discriminator_real_loss=1.402, discriminator_fake_loss=1.328, generator_loss=27.78, generator_mel_loss=17.83, generator_kl_loss=1.301, generator_dur_loss=1.822, generator_adv_loss=1.858, generator_feat_match_loss=4.967, over 96.00 samples.], tot_loss[discriminator_loss=2.73, discriminator_real_loss=1.39, discriminator_fake_loss=1.34, generator_loss=28.08, generator_mel_loss=18.14, generator_kl_loss=1.448, generator_dur_loss=1.738, generator_adv_loss=1.976, generator_feat_match_loss=4.776, over 1099.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 19:00:10,295 INFO [train.py:527] (2/6) Epoch 419, batch 68, global_batch_idx: 51900, batch size: 52, loss[discriminator_loss=2.708, discriminator_real_loss=1.331, discriminator_fake_loss=1.376, generator_loss=27.83, generator_mel_loss=18.03, generator_kl_loss=1.389, generator_dur_loss=1.753, generator_adv_loss=2.009, generator_feat_match_loss=4.649, over 52.00 samples.], tot_loss[discriminator_loss=2.728, discriminator_real_loss=1.378, discriminator_fake_loss=1.35, generator_loss=28.04, generator_mel_loss=18.13, generator_kl_loss=1.421, generator_dur_loss=1.752, generator_adv_loss=1.956, generator_feat_match_loss=4.788, over 4040.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 19:02:22,565 INFO [train.py:527] (2/6) Epoch 419, batch 118, global_batch_idx: 51950, batch size: 45, loss[discriminator_loss=2.675, discriminator_real_loss=1.377, discriminator_fake_loss=1.298, generator_loss=27.54, generator_mel_loss=17.94, generator_kl_loss=1.532, generator_dur_loss=1.659, generator_adv_loss=2.049, generator_feat_match_loss=4.365, over 45.00 samples.], tot_loss[discriminator_loss=2.719, discriminator_real_loss=1.374, discriminator_fake_loss=1.344, generator_loss=28.01, generator_mel_loss=18.1, generator_kl_loss=1.42, generator_dur_loss=1.751, generator_adv_loss=1.956, generator_feat_match_loss=4.782, over 6864.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 19:02:38,157 INFO [train.py:919] (2/6) Start epoch 420
2024-03-13 19:05:05,376 INFO [train.py:527] (2/6) Epoch 420, batch 44, global_batch_idx: 52000, batch size: 88, loss[discriminator_loss=2.752, discriminator_real_loss=1.392, discriminator_fake_loss=1.36, generator_loss=27.9, generator_mel_loss=17.98, generator_kl_loss=1.381, generator_dur_loss=1.886, generator_adv_loss=1.905, generator_feat_match_loss=4.751, over 88.00 samples.], tot_loss[discriminator_loss=2.717, discriminator_real_loss=1.376, discriminator_fake_loss=1.341, generator_loss=27.85, generator_mel_loss=18.06, generator_kl_loss=1.4, generator_dur_loss=1.761, generator_adv_loss=1.941, generator_feat_match_loss=4.683, over 2638.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 19:05:05,378 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 19:05:13,469 INFO [train.py:591] (2/6) Epoch 420, validation: discriminator_loss=2.774, discriminator_real_loss=1.481, discriminator_fake_loss=1.293, generator_loss=27.64, generator_mel_loss=18.58, generator_kl_loss=1.209, generator_dur_loss=1.812, generator_adv_loss=1.936, generator_feat_match_loss=4.108, over 100.00 samples.
2024-03-13 19:05:13,470 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 19:07:32,965 INFO [train.py:527] (2/6) Epoch 420, batch 94, global_batch_idx: 52050, batch size: 14, loss[discriminator_loss=2.602, discriminator_real_loss=1.396, discriminator_fake_loss=1.206, generator_loss=29.88, generator_mel_loss=18.47, generator_kl_loss=1.834, generator_dur_loss=1.602, generator_adv_loss=2.133, generator_feat_match_loss=5.837, over 14.00 samples.], tot_loss[discriminator_loss=2.708, discriminator_real_loss=1.366, discriminator_fake_loss=1.342, generator_loss=27.87, generator_mel_loss=18.04, generator_kl_loss=1.401, generator_dur_loss=1.76, generator_adv_loss=1.944, generator_feat_match_loss=4.721, over 5501.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 19:08:54,081 INFO [train.py:919] (2/6) Start epoch 421
2024-03-13 19:10:15,604 INFO [train.py:527] (2/6) Epoch 421, batch 20, global_batch_idx: 52100, batch size: 66, loss[discriminator_loss=2.707, discriminator_real_loss=1.281, discriminator_fake_loss=1.425, generator_loss=28.31, generator_mel_loss=18.01, generator_kl_loss=1.448, generator_dur_loss=1.731, generator_adv_loss=2.032, generator_feat_match_loss=5.086, over 66.00 samples.], tot_loss[discriminator_loss=2.698, discriminator_real_loss=1.359, discriminator_fake_loss=1.339, generator_loss=28.08, generator_mel_loss=18.12, generator_kl_loss=1.409, generator_dur_loss=1.772, generator_adv_loss=1.958, generator_feat_match_loss=4.828, over 1214.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 19:12:34,672 INFO [train.py:527] (2/6) Epoch 421, batch 70, global_batch_idx: 52150, batch size: 48, loss[discriminator_loss=2.694, discriminator_real_loss=1.398, discriminator_fake_loss=1.296, generator_loss=29.06, generator_mel_loss=18.46, generator_kl_loss=1.541, generator_dur_loss=1.7, generator_adv_loss=1.909, generator_feat_match_loss=5.453, over 48.00 samples.], tot_loss[discriminator_loss=2.703, discriminator_real_loss=1.37, discriminator_fake_loss=1.332, generator_loss=28.09, generator_mel_loss=18.11, generator_kl_loss=1.41, generator_dur_loss=1.776, generator_adv_loss=1.951, generator_feat_match_loss=4.84, over 4129.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 19:14:48,340 INFO [train.py:527] (2/6) Epoch 421, batch 120, global_batch_idx: 52200, batch size: 58, loss[discriminator_loss=2.735, discriminator_real_loss=1.339, discriminator_fake_loss=1.396, generator_loss=28.26, generator_mel_loss=18.01, generator_kl_loss=1.468, generator_dur_loss=1.793, generator_adv_loss=2.111, generator_feat_match_loss=4.877, over 58.00 samples.], tot_loss[discriminator_loss=2.709, discriminator_real_loss=1.373, discriminator_fake_loss=1.336, generator_loss=28.09, generator_mel_loss=18.1, generator_kl_loss=1.41, generator_dur_loss=1.776, generator_adv_loss=1.956, generator_feat_match_loss=4.84, over 7104.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 19:14:48,342 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 19:14:57,113 INFO [train.py:591] (2/6) Epoch 421, validation: discriminator_loss=2.767, discriminator_real_loss=1.497, discriminator_fake_loss=1.27, generator_loss=27.06, generator_mel_loss=18.58, generator_kl_loss=1.219, generator_dur_loss=1.818, generator_adv_loss=1.896, generator_feat_match_loss=3.554, over 100.00 samples.
2024-03-13 19:14:57,114 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 19:15:07,309 INFO [train.py:919] (2/6) Start epoch 422
2024-03-13 19:17:39,990 INFO [train.py:527] (2/6) Epoch 422, batch 46, global_batch_idx: 52250, batch size: 80, loss[discriminator_loss=2.756, discriminator_real_loss=1.413, discriminator_fake_loss=1.343, generator_loss=27.13, generator_mel_loss=17.85, generator_kl_loss=1.455, generator_dur_loss=1.822, generator_adv_loss=1.94, generator_feat_match_loss=4.063, over 80.00 samples.], tot_loss[discriminator_loss=2.722, discriminator_real_loss=1.377, discriminator_fake_loss=1.346, generator_loss=28, generator_mel_loss=18.1, generator_kl_loss=1.399, generator_dur_loss=1.764, generator_adv_loss=1.952, generator_feat_match_loss=4.783, over 2834.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 19:19:59,242 INFO [train.py:527] (2/6) Epoch 422, batch 96, global_batch_idx: 52300, batch size: 96, loss[discriminator_loss=2.731, discriminator_real_loss=1.293, discriminator_fake_loss=1.438, generator_loss=27.69, generator_mel_loss=17.59, generator_kl_loss=1.404, generator_dur_loss=1.846, generator_adv_loss=1.971, generator_feat_match_loss=4.873, over 96.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.369, discriminator_fake_loss=1.346, generator_loss=27.93, generator_mel_loss=18.05, generator_kl_loss=1.406, generator_dur_loss=1.762, generator_adv_loss=1.943, generator_feat_match_loss=4.764, over 5698.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 19:21:13,696 INFO [train.py:919] (2/6) Start epoch 423
2024-03-13 19:22:39,205 INFO [train.py:527] (2/6) Epoch 423, batch 22, global_batch_idx: 52350, batch size: 62, loss[discriminator_loss=2.683, discriminator_real_loss=1.405, discriminator_fake_loss=1.278, generator_loss=27.16, generator_mel_loss=17.98, generator_kl_loss=1.367, generator_dur_loss=1.753, generator_adv_loss=1.882, generator_feat_match_loss=4.18, over 62.00 samples.], tot_loss[discriminator_loss=2.707, discriminator_real_loss=1.374, discriminator_fake_loss=1.333, generator_loss=27.87, generator_mel_loss=18.07, generator_kl_loss=1.365, generator_dur_loss=1.801, generator_adv_loss=1.957, generator_feat_match_loss=4.674, over 1452.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 19:24:57,157 INFO [train.py:527] (2/6) Epoch 423, batch 72, global_batch_idx: 52400, batch size: 52, loss[discriminator_loss=2.741, discriminator_real_loss=1.234, discriminator_fake_loss=1.507, generator_loss=29.58, generator_mel_loss=18.41, generator_kl_loss=1.549, generator_dur_loss=1.696, generator_adv_loss=2.262, generator_feat_match_loss=5.663, over 52.00 samples.], tot_loss[discriminator_loss=2.704, discriminator_real_loss=1.359, discriminator_fake_loss=1.344, generator_loss=27.97, generator_mel_loss=18.04, generator_kl_loss=1.409, generator_dur_loss=1.77, generator_adv_loss=1.952, generator_feat_match_loss=4.791, over 4241.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 19:24:57,159 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 19:25:05,341 INFO [train.py:591] (2/6) Epoch 423, validation: discriminator_loss=2.891, discriminator_real_loss=1.675, discriminator_fake_loss=1.215, generator_loss=27.09, generator_mel_loss=17.91, generator_kl_loss=1.23, generator_dur_loss=1.832, generator_adv_loss=2.277, generator_feat_match_loss=3.847, over 100.00 samples.
2024-03-13 19:25:05,342 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 19:27:23,338 INFO [train.py:527] (2/6) Epoch 423, batch 122, global_batch_idx: 52450, batch size: 15, loss[discriminator_loss=2.774, discriminator_real_loss=1.375, discriminator_fake_loss=1.399, generator_loss=30.24, generator_mel_loss=19.06, generator_kl_loss=1.901, generator_dur_loss=1.597, generator_adv_loss=1.903, generator_feat_match_loss=5.778, over 15.00 samples.], tot_loss[discriminator_loss=2.703, discriminator_real_loss=1.364, discriminator_fake_loss=1.34, generator_loss=27.99, generator_mel_loss=18.04, generator_kl_loss=1.409, generator_dur_loss=1.767, generator_adv_loss=1.963, generator_feat_match_loss=4.808, over 7085.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 19:27:28,158 INFO [train.py:919] (2/6) Start epoch 424
2024-03-13 19:30:06,234 INFO [train.py:527] (2/6) Epoch 424, batch 48, global_batch_idx: 52500, batch size: 52, loss[discriminator_loss=2.741, discriminator_real_loss=1.371, discriminator_fake_loss=1.37, generator_loss=27.61, generator_mel_loss=17.71, generator_kl_loss=1.691, generator_dur_loss=1.697, generator_adv_loss=1.991, generator_feat_match_loss=4.523, over 52.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.367, discriminator_fake_loss=1.347, generator_loss=27.92, generator_mel_loss=18.06, generator_kl_loss=1.413, generator_dur_loss=1.743, generator_adv_loss=1.945, generator_feat_match_loss=4.751, over 2818.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 19:32:24,306 INFO [train.py:527] (2/6) Epoch 424, batch 98, global_batch_idx: 52550, batch size: 47, loss[discriminator_loss=2.761, discriminator_real_loss=1.45, discriminator_fake_loss=1.311, generator_loss=28.84, generator_mel_loss=18.41, generator_kl_loss=1.414, generator_dur_loss=1.68, generator_adv_loss=2.086, generator_feat_match_loss=5.25, over 47.00 samples.], tot_loss[discriminator_loss=2.718, discriminator_real_loss=1.375, discriminator_fake_loss=1.343, generator_loss=27.95, generator_mel_loss=18.08, generator_kl_loss=1.416, generator_dur_loss=1.744, generator_adv_loss=1.949, generator_feat_match_loss=4.764, over 5713.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 19:33:33,000 INFO [train.py:919] (2/6) Start epoch 425
2024-03-13 19:35:02,164 INFO [train.py:527] (2/6) Epoch 425, batch 24, global_batch_idx: 52600, batch size: 77, loss[discriminator_loss=2.689, discriminator_real_loss=1.296, discriminator_fake_loss=1.393, generator_loss=28.39, generator_mel_loss=18.01, generator_kl_loss=1.383, generator_dur_loss=1.845, generator_adv_loss=2.008, generator_feat_match_loss=5.142, over 77.00 samples.], tot_loss[discriminator_loss=2.695, discriminator_real_loss=1.356, discriminator_fake_loss=1.339, generator_loss=27.88, generator_mel_loss=18.02, generator_kl_loss=1.435, generator_dur_loss=1.771, generator_adv_loss=1.926, generator_feat_match_loss=4.737, over 1468.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 19:35:02,166 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 19:35:10,065 INFO [train.py:591] (2/6) Epoch 425, validation: discriminator_loss=2.718, discriminator_real_loss=1.424, discriminator_fake_loss=1.294, generator_loss=27.08, generator_mel_loss=18.35, generator_kl_loss=1.196, generator_dur_loss=1.825, generator_adv_loss=1.974, generator_feat_match_loss=3.734, over 100.00 samples.
2024-03-13 19:35:10,066 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 19:37:30,458 INFO [train.py:527] (2/6) Epoch 425, batch 74, global_batch_idx: 52650, batch size: 31, loss[discriminator_loss=2.682, discriminator_real_loss=1.468, discriminator_fake_loss=1.214, generator_loss=28.5, generator_mel_loss=18.13, generator_kl_loss=1.656, generator_dur_loss=1.634, generator_adv_loss=2.203, generator_feat_match_loss=4.875, over 31.00 samples.], tot_loss[discriminator_loss=2.713, discriminator_real_loss=1.369, discriminator_fake_loss=1.344, generator_loss=27.88, generator_mel_loss=17.99, generator_kl_loss=1.411, generator_dur_loss=1.766, generator_adv_loss=1.941, generator_feat_match_loss=4.773, over 4510.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 19:39:45,492 INFO [train.py:919] (2/6) Start epoch 426
2024-03-13 19:40:10,336 INFO [train.py:527] (2/6) Epoch 426, batch 0, global_batch_idx: 52700, batch size: 96, loss[discriminator_loss=2.754, discriminator_real_loss=1.399, discriminator_fake_loss=1.355, generator_loss=27.55, generator_mel_loss=17.6, generator_kl_loss=1.315, generator_dur_loss=1.856, generator_adv_loss=1.859, generator_feat_match_loss=4.917, over 96.00 samples.], tot_loss[discriminator_loss=2.754, discriminator_real_loss=1.399, discriminator_fake_loss=1.355, generator_loss=27.55, generator_mel_loss=17.6, generator_kl_loss=1.315, generator_dur_loss=1.856, generator_adv_loss=1.859, generator_feat_match_loss=4.917, over 96.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 19:42:32,616 INFO [train.py:527] (2/6) Epoch 426, batch 50, global_batch_idx: 52750, batch size: 62, loss[discriminator_loss=2.692, discriminator_real_loss=1.461, discriminator_fake_loss=1.231, generator_loss=27.62, generator_mel_loss=18.11, generator_kl_loss=1.33, generator_dur_loss=1.787, generator_adv_loss=2.031, generator_feat_match_loss=4.365, over 62.00 samples.], tot_loss[discriminator_loss=2.727, discriminator_real_loss=1.376, discriminator_fake_loss=1.351, generator_loss=28.18, generator_mel_loss=18.21, generator_kl_loss=1.415, generator_dur_loss=1.772, generator_adv_loss=1.931, generator_feat_match_loss=4.855, over 3050.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 19:44:48,299 INFO [train.py:527] (2/6) Epoch 426, batch 100, global_batch_idx: 52800, batch size: 36, loss[discriminator_loss=2.735, discriminator_real_loss=1.33, discriminator_fake_loss=1.405, generator_loss=28.71, generator_mel_loss=18.28, generator_kl_loss=1.528, generator_dur_loss=1.667, generator_adv_loss=2.027, generator_feat_match_loss=5.207, over 36.00 samples.], tot_loss[discriminator_loss=2.721, discriminator_real_loss=1.375, discriminator_fake_loss=1.346, generator_loss=28.04, generator_mel_loss=18.12, generator_kl_loss=1.422, generator_dur_loss=1.761, generator_adv_loss=1.939, generator_feat_match_loss=4.796, over 5800.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 19:44:48,301 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 19:44:57,102 INFO [train.py:591] (2/6) Epoch 426, validation: discriminator_loss=2.772, discriminator_real_loss=1.461, discriminator_fake_loss=1.311, generator_loss=27.14, generator_mel_loss=18.28, generator_kl_loss=1.227, generator_dur_loss=1.818, generator_adv_loss=1.978, generator_feat_match_loss=3.839, over 100.00 samples.
2024-03-13 19:44:57,103 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 19:46:03,092 INFO [train.py:919] (2/6) Start epoch 427
2024-03-13 19:47:37,231 INFO [train.py:527] (2/6) Epoch 427, batch 26, global_batch_idx: 52850, batch size: 66, loss[discriminator_loss=2.675, discriminator_real_loss=1.317, discriminator_fake_loss=1.359, generator_loss=27.78, generator_mel_loss=17.76, generator_kl_loss=1.478, generator_dur_loss=1.789, generator_adv_loss=1.898, generator_feat_match_loss=4.851, over 66.00 samples.], tot_loss[discriminator_loss=2.722, discriminator_real_loss=1.378, discriminator_fake_loss=1.344, generator_loss=27.89, generator_mel_loss=18.12, generator_kl_loss=1.401, generator_dur_loss=1.746, generator_adv_loss=1.943, generator_feat_match_loss=4.685, over 1461.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 19:49:57,009 INFO [train.py:527] (2/6) Epoch 427, batch 76, global_batch_idx: 52900, batch size: 31, loss[discriminator_loss=2.684, discriminator_real_loss=1.416, discriminator_fake_loss=1.269, generator_loss=27.44, generator_mel_loss=17.68, generator_kl_loss=1.239, generator_dur_loss=1.661, generator_adv_loss=2.126, generator_feat_match_loss=4.729, over 31.00 samples.], tot_loss[discriminator_loss=2.721, discriminator_real_loss=1.373, discriminator_fake_loss=1.347, generator_loss=27.96, generator_mel_loss=18.07, generator_kl_loss=1.416, generator_dur_loss=1.747, generator_adv_loss=1.964, generator_feat_match_loss=4.76, over 4286.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 19:52:09,382 INFO [train.py:919] (2/6) Start epoch 428
2024-03-13 19:52:39,502 INFO [train.py:527] (2/6) Epoch 428, batch 2, global_batch_idx: 52950, batch size: 36, loss[discriminator_loss=2.686, discriminator_real_loss=1.263, discriminator_fake_loss=1.423, generator_loss=28.65, generator_mel_loss=18.15, generator_kl_loss=1.684, generator_dur_loss=1.641, generator_adv_loss=2.061, generator_feat_match_loss=5.112, over 36.00 samples.], tot_loss[discriminator_loss=2.719, discriminator_real_loss=1.395, discriminator_fake_loss=1.324, generator_loss=28.42, generator_mel_loss=18.31, generator_kl_loss=1.503, generator_dur_loss=1.702, generator_adv_loss=1.916, generator_feat_match_loss=4.989, over 149.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 19:54:59,001 INFO [train.py:527] (2/6) Epoch 428, batch 52, global_batch_idx: 53000, batch size: 77, loss[discriminator_loss=2.734, discriminator_real_loss=1.292, discriminator_fake_loss=1.442, generator_loss=28.46, generator_mel_loss=18.19, generator_kl_loss=1.354, generator_dur_loss=1.797, generator_adv_loss=2.045, generator_feat_match_loss=5.081, over 77.00 samples.], tot_loss[discriminator_loss=2.718, discriminator_real_loss=1.371, discriminator_fake_loss=1.347, generator_loss=28, generator_mel_loss=18.08, generator_kl_loss=1.424, generator_dur_loss=1.739, generator_adv_loss=1.947, generator_feat_match_loss=4.808, over 2829.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 19:54:59,003 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 19:55:07,118 INFO [train.py:591] (2/6) Epoch 428, validation: discriminator_loss=2.731, discriminator_real_loss=1.543, discriminator_fake_loss=1.188, generator_loss=27.28, generator_mel_loss=18.15, generator_kl_loss=1.172, generator_dur_loss=1.804, generator_adv_loss=2.059, generator_feat_match_loss=4.093, over 100.00 samples.
2024-03-13 19:55:07,119 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 19:57:24,504 INFO [train.py:527] (2/6) Epoch 428, batch 102, global_batch_idx: 53050, batch size: 74, loss[discriminator_loss=2.644, discriminator_real_loss=1.28, discriminator_fake_loss=1.365, generator_loss=28.38, generator_mel_loss=18.12, generator_kl_loss=1.304, generator_dur_loss=1.819, generator_adv_loss=1.978, generator_feat_match_loss=5.157, over 74.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.371, discriminator_fake_loss=1.344, generator_loss=28, generator_mel_loss=18.1, generator_kl_loss=1.421, generator_dur_loss=1.753, generator_adv_loss=1.941, generator_feat_match_loss=4.783, over 5864.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 19:58:22,648 INFO [train.py:919] (2/6) Start epoch 429
2024-03-13 20:00:04,601 INFO [train.py:527] (2/6) Epoch 429, batch 28, global_batch_idx: 53100, batch size: 31, loss[discriminator_loss=2.708, discriminator_real_loss=1.484, discriminator_fake_loss=1.224, generator_loss=29.01, generator_mel_loss=18.75, generator_kl_loss=1.542, generator_dur_loss=1.568, generator_adv_loss=2.131, generator_feat_match_loss=5.024, over 31.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.37, discriminator_fake_loss=1.347, generator_loss=27.87, generator_mel_loss=18.06, generator_kl_loss=1.408, generator_dur_loss=1.76, generator_adv_loss=1.956, generator_feat_match_loss=4.687, over 1654.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 20:02:26,064 INFO [train.py:527] (2/6) Epoch 429, batch 78, global_batch_idx: 53150, batch size: 42, loss[discriminator_loss=2.694, discriminator_real_loss=1.407, discriminator_fake_loss=1.287, generator_loss=27.24, generator_mel_loss=17.82, generator_kl_loss=1.289, generator_dur_loss=1.665, generator_adv_loss=1.891, generator_feat_match_loss=4.586, over 42.00 samples.], tot_loss[discriminator_loss=2.718, discriminator_real_loss=1.379, discriminator_fake_loss=1.339, generator_loss=27.82, generator_mel_loss=18.03, generator_kl_loss=1.413, generator_dur_loss=1.758, generator_adv_loss=1.945, generator_feat_match_loss=4.674, over 4476.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 20:04:26,514 INFO [train.py:919] (2/6) Start epoch 430
2024-03-13 20:05:00,196 INFO [train.py:527] (2/6) Epoch 430, batch 4, global_batch_idx: 53200, batch size: 88, loss[discriminator_loss=2.738, discriminator_real_loss=1.382, discriminator_fake_loss=1.355, generator_loss=27.45, generator_mel_loss=17.68, generator_kl_loss=1.353, generator_dur_loss=1.879, generator_adv_loss=1.874, generator_feat_match_loss=4.669, over 88.00 samples.], tot_loss[discriminator_loss=2.731, discriminator_real_loss=1.384, discriminator_fake_loss=1.347, generator_loss=27.84, generator_mel_loss=17.95, generator_kl_loss=1.4, generator_dur_loss=1.804, generator_adv_loss=1.954, generator_feat_match_loss=4.731, over 294.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 20:05:00,199 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 20:05:08,014 INFO [train.py:591] (2/6) Epoch 430, validation: discriminator_loss=2.768, discriminator_real_loss=1.384, discriminator_fake_loss=1.383, generator_loss=27.81, generator_mel_loss=19.1, generator_kl_loss=1.206, generator_dur_loss=1.806, generator_adv_loss=1.75, generator_feat_match_loss=3.952, over 100.00 samples.
2024-03-13 20:05:08,017 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 20:07:29,635 INFO [train.py:527] (2/6) Epoch 430, batch 54, global_batch_idx: 53250, batch size: 56, loss[discriminator_loss=2.702, discriminator_real_loss=1.334, discriminator_fake_loss=1.368, generator_loss=26.6, generator_mel_loss=17.29, generator_kl_loss=1.47, generator_dur_loss=1.677, generator_adv_loss=1.941, generator_feat_match_loss=4.224, over 56.00 samples.], tot_loss[discriminator_loss=2.724, discriminator_real_loss=1.375, discriminator_fake_loss=1.349, generator_loss=27.95, generator_mel_loss=18.09, generator_kl_loss=1.407, generator_dur_loss=1.769, generator_adv_loss=1.943, generator_feat_match_loss=4.736, over 3225.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 20:09:49,005 INFO [train.py:527] (2/6) Epoch 430, batch 104, global_batch_idx: 53300, batch size: 70, loss[discriminator_loss=2.624, discriminator_real_loss=1.327, discriminator_fake_loss=1.297, generator_loss=28.39, generator_mel_loss=18.31, generator_kl_loss=1.302, generator_dur_loss=1.775, generator_adv_loss=1.932, generator_feat_match_loss=5.072, over 70.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.371, discriminator_fake_loss=1.345, generator_loss=27.99, generator_mel_loss=18.11, generator_kl_loss=1.414, generator_dur_loss=1.764, generator_adv_loss=1.95, generator_feat_match_loss=4.755, over 6055.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 20:10:41,860 INFO [train.py:919] (2/6) Start epoch 431
2024-03-13 20:12:27,681 INFO [train.py:527] (2/6) Epoch 431, batch 30, global_batch_idx: 53350, batch size: 53, loss[discriminator_loss=2.78, discriminator_real_loss=1.406, discriminator_fake_loss=1.374, generator_loss=27.04, generator_mel_loss=17.83, generator_kl_loss=1.331, generator_dur_loss=1.684, generator_adv_loss=1.819, generator_feat_match_loss=4.376, over 53.00 samples.], tot_loss[discriminator_loss=2.71, discriminator_real_loss=1.364, discriminator_fake_loss=1.346, generator_loss=28.08, generator_mel_loss=18.08, generator_kl_loss=1.384, generator_dur_loss=1.764, generator_adv_loss=1.953, generator_feat_match_loss=4.893, over 1948.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 20:14:43,607 INFO [train.py:527] (2/6) Epoch 431, batch 80, global_batch_idx: 53400, batch size: 36, loss[discriminator_loss=2.718, discriminator_real_loss=1.431, discriminator_fake_loss=1.286, generator_loss=27.59, generator_mel_loss=17.45, generator_kl_loss=1.495, generator_dur_loss=1.73, generator_adv_loss=2.069, generator_feat_match_loss=4.838, over 36.00 samples.], tot_loss[discriminator_loss=2.713, discriminator_real_loss=1.374, discriminator_fake_loss=1.339, generator_loss=28.01, generator_mel_loss=18.06, generator_kl_loss=1.405, generator_dur_loss=1.761, generator_adv_loss=1.959, generator_feat_match_loss=4.831, over 4787.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 20:14:43,609 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 20:14:51,580 INFO [train.py:591] (2/6) Epoch 431, validation: discriminator_loss=2.781, discriminator_real_loss=1.454, discriminator_fake_loss=1.327, generator_loss=26.56, generator_mel_loss=17.71, generator_kl_loss=1.241, generator_dur_loss=1.836, generator_adv_loss=1.938, generator_feat_match_loss=3.835, over 100.00 samples.
2024-03-13 20:14:51,582 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 20:16:53,599 INFO [train.py:919] (2/6) Start epoch 432
2024-03-13 20:17:34,605 INFO [train.py:527] (2/6) Epoch 432, batch 6, global_batch_idx: 53450, batch size: 59, loss[discriminator_loss=2.752, discriminator_real_loss=1.398, discriminator_fake_loss=1.355, generator_loss=28.45, generator_mel_loss=18.49, generator_kl_loss=1.478, generator_dur_loss=1.748, generator_adv_loss=1.945, generator_feat_match_loss=4.795, over 59.00 samples.], tot_loss[discriminator_loss=2.738, discriminator_real_loss=1.362, discriminator_fake_loss=1.376, generator_loss=27.98, generator_mel_loss=17.98, generator_kl_loss=1.471, generator_dur_loss=1.759, generator_adv_loss=1.931, generator_feat_match_loss=4.837, over 402.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 20:19:56,415 INFO [train.py:527] (2/6) Epoch 432, batch 56, global_batch_idx: 53500, batch size: 31, loss[discriminator_loss=2.725, discriminator_real_loss=1.484, discriminator_fake_loss=1.242, generator_loss=27.94, generator_mel_loss=18.01, generator_kl_loss=1.668, generator_dur_loss=1.681, generator_adv_loss=1.946, generator_feat_match_loss=4.638, over 31.00 samples.], tot_loss[discriminator_loss=2.718, discriminator_real_loss=1.361, discriminator_fake_loss=1.357, generator_loss=28.19, generator_mel_loss=18.11, generator_kl_loss=1.435, generator_dur_loss=1.774, generator_adv_loss=1.954, generator_feat_match_loss=4.92, over 3274.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 20:22:15,141 INFO [train.py:527] (2/6) Epoch 432, batch 106, global_batch_idx: 53550, batch size: 45, loss[discriminator_loss=2.729, discriminator_real_loss=1.421, discriminator_fake_loss=1.308, generator_loss=28.62, generator_mel_loss=18.35, generator_kl_loss=1.455, generator_dur_loss=1.708, generator_adv_loss=1.802, generator_feat_match_loss=5.309, over 45.00 samples.], tot_loss[discriminator_loss=2.714, discriminator_real_loss=1.367, discriminator_fake_loss=1.348, generator_loss=28.1, generator_mel_loss=18.08, generator_kl_loss=1.435, generator_dur_loss=1.763, generator_adv_loss=1.951, generator_feat_match_loss=4.876, over 5926.00 samples.], cur_lr_g: 1.90e-04, cur_lr_d: 1.90e-04, 
2024-03-13 20:23:01,923 INFO [train.py:919] (2/6) Start epoch 433
2024-03-13 20:24:55,041 INFO [train.py:527] (2/6) Epoch 433, batch 32, global_batch_idx: 53600, batch size: 56, loss[discriminator_loss=2.691, discriminator_real_loss=1.369, discriminator_fake_loss=1.322, generator_loss=27.28, generator_mel_loss=17.62, generator_kl_loss=1.504, generator_dur_loss=1.671, generator_adv_loss=1.959, generator_feat_match_loss=4.523, over 56.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.38, discriminator_fake_loss=1.337, generator_loss=27.95, generator_mel_loss=18.09, generator_kl_loss=1.369, generator_dur_loss=1.796, generator_adv_loss=1.951, generator_feat_match_loss=4.745, over 2125.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 20:24:55,043 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 20:25:02,939 INFO [train.py:591] (2/6) Epoch 433, validation: discriminator_loss=2.762, discriminator_real_loss=1.486, discriminator_fake_loss=1.276, generator_loss=26.89, generator_mel_loss=17.98, generator_kl_loss=1.272, generator_dur_loss=1.838, generator_adv_loss=1.909, generator_feat_match_loss=3.895, over 100.00 samples.
2024-03-13 20:25:02,940 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 20:27:20,282 INFO [train.py:527] (2/6) Epoch 433, batch 82, global_batch_idx: 53650, batch size: 39, loss[discriminator_loss=2.737, discriminator_real_loss=1.375, discriminator_fake_loss=1.361, generator_loss=28.89, generator_mel_loss=18.37, generator_kl_loss=1.56, generator_dur_loss=1.709, generator_adv_loss=2.075, generator_feat_match_loss=5.172, over 39.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.374, discriminator_fake_loss=1.342, generator_loss=27.93, generator_mel_loss=18.04, generator_kl_loss=1.391, generator_dur_loss=1.776, generator_adv_loss=1.943, generator_feat_match_loss=4.78, over 4873.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 20:29:12,891 INFO [train.py:919] (2/6) Start epoch 434
2024-03-13 20:29:56,721 INFO [train.py:527] (2/6) Epoch 434, batch 8, global_batch_idx: 53700, batch size: 52, loss[discriminator_loss=2.728, discriminator_real_loss=1.464, discriminator_fake_loss=1.264, generator_loss=28.58, generator_mel_loss=18.22, generator_kl_loss=1.42, generator_dur_loss=1.709, generator_adv_loss=1.874, generator_feat_match_loss=5.349, over 52.00 samples.], tot_loss[discriminator_loss=2.727, discriminator_real_loss=1.383, discriminator_fake_loss=1.344, generator_loss=28.24, generator_mel_loss=18.26, generator_kl_loss=1.407, generator_dur_loss=1.748, generator_adv_loss=1.959, generator_feat_match_loss=4.867, over 544.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 20:32:14,612 INFO [train.py:527] (2/6) Epoch 434, batch 58, global_batch_idx: 53750, batch size: 48, loss[discriminator_loss=2.725, discriminator_real_loss=1.382, discriminator_fake_loss=1.342, generator_loss=27.66, generator_mel_loss=18.15, generator_kl_loss=1.555, generator_dur_loss=1.742, generator_adv_loss=1.942, generator_feat_match_loss=4.271, over 48.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.383, discriminator_fake_loss=1.343, generator_loss=27.97, generator_mel_loss=18.06, generator_kl_loss=1.423, generator_dur_loss=1.756, generator_adv_loss=1.95, generator_feat_match_loss=4.775, over 3339.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 20:34:33,480 INFO [train.py:527] (2/6) Epoch 434, batch 108, global_batch_idx: 53800, batch size: 56, loss[discriminator_loss=2.799, discriminator_real_loss=1.492, discriminator_fake_loss=1.307, generator_loss=26.86, generator_mel_loss=17.73, generator_kl_loss=1.289, generator_dur_loss=1.768, generator_adv_loss=1.861, generator_feat_match_loss=4.214, over 56.00 samples.], tot_loss[discriminator_loss=2.721, discriminator_real_loss=1.376, discriminator_fake_loss=1.345, generator_loss=27.98, generator_mel_loss=18.07, generator_kl_loss=1.42, generator_dur_loss=1.747, generator_adv_loss=1.949, generator_feat_match_loss=4.786, over 6040.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 20:34:33,481 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 20:34:42,396 INFO [train.py:591] (2/6) Epoch 434, validation: discriminator_loss=2.76, discriminator_real_loss=1.447, discriminator_fake_loss=1.313, generator_loss=26.69, generator_mel_loss=18.37, generator_kl_loss=1.187, generator_dur_loss=1.837, generator_adv_loss=1.852, generator_feat_match_loss=3.445, over 100.00 samples.
2024-03-13 20:34:42,397 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 20:35:24,835 INFO [train.py:919] (2/6) Start epoch 435
2024-03-13 20:37:25,024 INFO [train.py:527] (2/6) Epoch 435, batch 34, global_batch_idx: 53850, batch size: 70, loss[discriminator_loss=2.704, discriminator_real_loss=1.372, discriminator_fake_loss=1.332, generator_loss=28.34, generator_mel_loss=18.08, generator_kl_loss=1.489, generator_dur_loss=1.798, generator_adv_loss=1.924, generator_feat_match_loss=5.049, over 70.00 samples.], tot_loss[discriminator_loss=2.73, discriminator_real_loss=1.38, discriminator_fake_loss=1.351, generator_loss=28.04, generator_mel_loss=18.09, generator_kl_loss=1.423, generator_dur_loss=1.771, generator_adv_loss=1.939, generator_feat_match_loss=4.815, over 1968.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 20:39:41,082 INFO [train.py:527] (2/6) Epoch 435, batch 84, global_batch_idx: 53900, batch size: 55, loss[discriminator_loss=2.791, discriminator_real_loss=1.409, discriminator_fake_loss=1.382, generator_loss=28.4, generator_mel_loss=18.71, generator_kl_loss=1.44, generator_dur_loss=1.713, generator_adv_loss=1.885, generator_feat_match_loss=4.646, over 55.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.381, discriminator_fake_loss=1.345, generator_loss=28.05, generator_mel_loss=18.12, generator_kl_loss=1.436, generator_dur_loss=1.753, generator_adv_loss=1.943, generator_feat_match_loss=4.793, over 4675.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 20:41:32,041 INFO [train.py:919] (2/6) Start epoch 436
2024-03-13 20:42:23,689 INFO [train.py:527] (2/6) Epoch 436, batch 10, global_batch_idx: 53950, batch size: 53, loss[discriminator_loss=2.703, discriminator_real_loss=1.405, discriminator_fake_loss=1.298, generator_loss=27.68, generator_mel_loss=18.19, generator_kl_loss=1.383, generator_dur_loss=1.702, generator_adv_loss=1.943, generator_feat_match_loss=4.461, over 53.00 samples.], tot_loss[discriminator_loss=2.722, discriminator_real_loss=1.365, discriminator_fake_loss=1.357, generator_loss=27.74, generator_mel_loss=17.98, generator_kl_loss=1.455, generator_dur_loss=1.77, generator_adv_loss=1.914, generator_feat_match_loss=4.622, over 607.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 20:44:40,890 INFO [train.py:527] (2/6) Epoch 436, batch 60, global_batch_idx: 54000, batch size: 59, loss[discriminator_loss=2.716, discriminator_real_loss=1.385, discriminator_fake_loss=1.332, generator_loss=28.37, generator_mel_loss=17.9, generator_kl_loss=1.544, generator_dur_loss=1.687, generator_adv_loss=2.027, generator_feat_match_loss=5.214, over 59.00 samples.], tot_loss[discriminator_loss=2.717, discriminator_real_loss=1.369, discriminator_fake_loss=1.347, generator_loss=27.94, generator_mel_loss=18.05, generator_kl_loss=1.449, generator_dur_loss=1.746, generator_adv_loss=1.952, generator_feat_match_loss=4.737, over 3491.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 20:44:40,892 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 20:44:49,016 INFO [train.py:591] (2/6) Epoch 436, validation: discriminator_loss=2.777, discriminator_real_loss=1.482, discriminator_fake_loss=1.295, generator_loss=27.09, generator_mel_loss=18.27, generator_kl_loss=1.112, generator_dur_loss=1.792, generator_adv_loss=1.962, generator_feat_match_loss=3.957, over 100.00 samples.
2024-03-13 20:44:49,017 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 20:47:08,845 INFO [train.py:527] (2/6) Epoch 436, batch 110, global_batch_idx: 54050, batch size: 88, loss[discriminator_loss=2.758, discriminator_real_loss=1.329, discriminator_fake_loss=1.43, generator_loss=27.29, generator_mel_loss=18.08, generator_kl_loss=1.177, generator_dur_loss=1.871, generator_adv_loss=1.861, generator_feat_match_loss=4.308, over 88.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.372, discriminator_fake_loss=1.348, generator_loss=27.93, generator_mel_loss=18.06, generator_kl_loss=1.435, generator_dur_loss=1.748, generator_adv_loss=1.943, generator_feat_match_loss=4.751, over 6266.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 20:47:45,371 INFO [train.py:919] (2/6) Start epoch 437
2024-03-13 20:49:50,276 INFO [train.py:527] (2/6) Epoch 437, batch 36, global_batch_idx: 54100, batch size: 50, loss[discriminator_loss=2.737, discriminator_real_loss=1.329, discriminator_fake_loss=1.408, generator_loss=28.75, generator_mel_loss=18.68, generator_kl_loss=1.416, generator_dur_loss=1.7, generator_adv_loss=1.925, generator_feat_match_loss=5.029, over 50.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.37, discriminator_fake_loss=1.345, generator_loss=28.01, generator_mel_loss=18.01, generator_kl_loss=1.415, generator_dur_loss=1.766, generator_adv_loss=1.95, generator_feat_match_loss=4.874, over 2203.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 20:52:06,275 INFO [train.py:527] (2/6) Epoch 437, batch 86, global_batch_idx: 54150, batch size: 47, loss[discriminator_loss=2.544, discriminator_real_loss=1.305, discriminator_fake_loss=1.24, generator_loss=29.2, generator_mel_loss=18.01, generator_kl_loss=1.524, generator_dur_loss=1.673, generator_adv_loss=2.305, generator_feat_match_loss=5.69, over 47.00 samples.], tot_loss[discriminator_loss=2.707, discriminator_real_loss=1.364, discriminator_fake_loss=1.343, generator_loss=28.07, generator_mel_loss=18.03, generator_kl_loss=1.436, generator_dur_loss=1.757, generator_adv_loss=1.953, generator_feat_match_loss=4.898, over 4944.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 20:53:51,205 INFO [train.py:919] (2/6) Start epoch 438
2024-03-13 20:54:48,964 INFO [train.py:527] (2/6) Epoch 438, batch 12, global_batch_idx: 54200, batch size: 42, loss[discriminator_loss=2.67, discriminator_real_loss=1.286, discriminator_fake_loss=1.384, generator_loss=28.99, generator_mel_loss=18.21, generator_kl_loss=1.508, generator_dur_loss=1.66, generator_adv_loss=1.97, generator_feat_match_loss=5.635, over 42.00 samples.], tot_loss[discriminator_loss=2.712, discriminator_real_loss=1.343, discriminator_fake_loss=1.37, generator_loss=28.05, generator_mel_loss=18.05, generator_kl_loss=1.385, generator_dur_loss=1.801, generator_adv_loss=1.923, generator_feat_match_loss=4.892, over 849.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 20:54:48,967 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 20:54:56,886 INFO [train.py:591] (2/6) Epoch 438, validation: discriminator_loss=2.744, discriminator_real_loss=1.418, discriminator_fake_loss=1.327, generator_loss=27.28, generator_mel_loss=18.35, generator_kl_loss=1.23, generator_dur_loss=1.82, generator_adv_loss=1.905, generator_feat_match_loss=3.968, over 100.00 samples.
2024-03-13 20:54:56,887 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 20:57:16,533 INFO [train.py:527] (2/6) Epoch 438, batch 62, global_batch_idx: 54250, batch size: 56, loss[discriminator_loss=2.755, discriminator_real_loss=1.424, discriminator_fake_loss=1.332, generator_loss=27.41, generator_mel_loss=17.62, generator_kl_loss=1.367, generator_dur_loss=1.767, generator_adv_loss=1.983, generator_feat_match_loss=4.673, over 56.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.375, discriminator_fake_loss=1.35, generator_loss=27.96, generator_mel_loss=17.99, generator_kl_loss=1.412, generator_dur_loss=1.767, generator_adv_loss=1.941, generator_feat_match_loss=4.851, over 3671.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 20:59:32,972 INFO [train.py:527] (2/6) Epoch 438, batch 112, global_batch_idx: 54300, batch size: 72, loss[discriminator_loss=2.742, discriminator_real_loss=1.364, discriminator_fake_loss=1.378, generator_loss=27.96, generator_mel_loss=17.76, generator_kl_loss=1.429, generator_dur_loss=1.807, generator_adv_loss=2.109, generator_feat_match_loss=4.852, over 72.00 samples.], tot_loss[discriminator_loss=2.719, discriminator_real_loss=1.376, discriminator_fake_loss=1.343, generator_loss=27.99, generator_mel_loss=18.01, generator_kl_loss=1.412, generator_dur_loss=1.758, generator_adv_loss=1.942, generator_feat_match_loss=4.868, over 6335.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 21:00:05,268 INFO [train.py:919] (2/6) Start epoch 439
2024-03-13 21:02:12,240 INFO [train.py:527] (2/6) Epoch 439, batch 38, global_batch_idx: 54350, batch size: 55, loss[discriminator_loss=2.69, discriminator_real_loss=1.391, discriminator_fake_loss=1.299, generator_loss=27.66, generator_mel_loss=17.78, generator_kl_loss=1.413, generator_dur_loss=1.739, generator_adv_loss=1.994, generator_feat_match_loss=4.732, over 55.00 samples.], tot_loss[discriminator_loss=2.694, discriminator_real_loss=1.361, discriminator_fake_loss=1.333, generator_loss=28.24, generator_mel_loss=18.06, generator_kl_loss=1.423, generator_dur_loss=1.776, generator_adv_loss=1.976, generator_feat_match_loss=5.003, over 2226.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 21:04:32,717 INFO [train.py:527] (2/6) Epoch 439, batch 88, global_batch_idx: 54400, batch size: 31, loss[discriminator_loss=2.686, discriminator_real_loss=1.347, discriminator_fake_loss=1.339, generator_loss=28.69, generator_mel_loss=18.45, generator_kl_loss=1.516, generator_dur_loss=1.625, generator_adv_loss=2.042, generator_feat_match_loss=5.064, over 31.00 samples.], tot_loss[discriminator_loss=2.707, discriminator_real_loss=1.366, discriminator_fake_loss=1.341, generator_loss=28.03, generator_mel_loss=18.03, generator_kl_loss=1.407, generator_dur_loss=1.773, generator_adv_loss=1.957, generator_feat_match_loss=4.865, over 5143.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 21:04:32,719 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 21:04:41,977 INFO [train.py:591] (2/6) Epoch 439, validation: discriminator_loss=2.799, discriminator_real_loss=1.513, discriminator_fake_loss=1.286, generator_loss=26.4, generator_mel_loss=18.01, generator_kl_loss=1.244, generator_dur_loss=1.829, generator_adv_loss=1.923, generator_feat_match_loss=3.392, over 100.00 samples.
2024-03-13 21:04:41,978 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 21:06:19,008 INFO [train.py:919] (2/6) Start epoch 440
2024-03-13 21:07:20,420 INFO [train.py:527] (2/6) Epoch 440, batch 14, global_batch_idx: 54450, batch size: 64, loss[discriminator_loss=2.695, discriminator_real_loss=1.291, discriminator_fake_loss=1.404, generator_loss=29.47, generator_mel_loss=18.69, generator_kl_loss=1.469, generator_dur_loss=1.787, generator_adv_loss=2.142, generator_feat_match_loss=5.374, over 64.00 samples.], tot_loss[discriminator_loss=2.704, discriminator_real_loss=1.359, discriminator_fake_loss=1.345, generator_loss=28.02, generator_mel_loss=18.13, generator_kl_loss=1.381, generator_dur_loss=1.768, generator_adv_loss=1.946, generator_feat_match_loss=4.8, over 904.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 21:09:37,433 INFO [train.py:527] (2/6) Epoch 440, batch 64, global_batch_idx: 54500, batch size: 77, loss[discriminator_loss=2.728, discriminator_real_loss=1.425, discriminator_fake_loss=1.303, generator_loss=27.47, generator_mel_loss=18.02, generator_kl_loss=1.348, generator_dur_loss=1.842, generator_adv_loss=1.884, generator_feat_match_loss=4.379, over 77.00 samples.], tot_loss[discriminator_loss=2.722, discriminator_real_loss=1.374, discriminator_fake_loss=1.347, generator_loss=28.07, generator_mel_loss=18.15, generator_kl_loss=1.421, generator_dur_loss=1.742, generator_adv_loss=1.946, generator_feat_match_loss=4.814, over 3629.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 21:11:56,640 INFO [train.py:527] (2/6) Epoch 440, batch 114, global_batch_idx: 54550, batch size: 56, loss[discriminator_loss=2.754, discriminator_real_loss=1.385, discriminator_fake_loss=1.369, generator_loss=27.88, generator_mel_loss=18.02, generator_kl_loss=1.287, generator_dur_loss=1.745, generator_adv_loss=1.939, generator_feat_match_loss=4.892, over 56.00 samples.], tot_loss[discriminator_loss=2.718, discriminator_real_loss=1.373, discriminator_fake_loss=1.346, generator_loss=28.1, generator_mel_loss=18.14, generator_kl_loss=1.416, generator_dur_loss=1.749, generator_adv_loss=1.955, generator_feat_match_loss=4.836, over 6657.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 21:12:24,538 INFO [train.py:919] (2/6) Start epoch 441
2024-03-13 21:14:37,087 INFO [train.py:527] (2/6) Epoch 441, batch 40, global_batch_idx: 54600, batch size: 72, loss[discriminator_loss=2.781, discriminator_real_loss=1.419, discriminator_fake_loss=1.363, generator_loss=28.04, generator_mel_loss=18.28, generator_kl_loss=1.299, generator_dur_loss=1.778, generator_adv_loss=1.773, generator_feat_match_loss=4.901, over 72.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.375, discriminator_fake_loss=1.34, generator_loss=28.1, generator_mel_loss=18.13, generator_kl_loss=1.434, generator_dur_loss=1.755, generator_adv_loss=1.941, generator_feat_match_loss=4.839, over 2146.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 21:14:37,088 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 21:14:45,258 INFO [train.py:591] (2/6) Epoch 441, validation: discriminator_loss=2.753, discriminator_real_loss=1.449, discriminator_fake_loss=1.304, generator_loss=26.88, generator_mel_loss=18.1, generator_kl_loss=1.25, generator_dur_loss=1.816, generator_adv_loss=1.859, generator_feat_match_loss=3.86, over 100.00 samples.
2024-03-13 21:14:45,259 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 21:17:05,699 INFO [train.py:527] (2/6) Epoch 441, batch 90, global_batch_idx: 54650, batch size: 47, loss[discriminator_loss=2.689, discriminator_real_loss=1.336, discriminator_fake_loss=1.353, generator_loss=28.25, generator_mel_loss=18.01, generator_kl_loss=1.666, generator_dur_loss=1.637, generator_adv_loss=2.06, generator_feat_match_loss=4.87, over 47.00 samples.], tot_loss[discriminator_loss=2.712, discriminator_real_loss=1.371, discriminator_fake_loss=1.341, generator_loss=28.09, generator_mel_loss=18.13, generator_kl_loss=1.405, generator_dur_loss=1.758, generator_adv_loss=1.957, generator_feat_match_loss=4.844, over 5151.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 21:18:39,858 INFO [train.py:919] (2/6) Start epoch 442
2024-03-13 21:19:46,968 INFO [train.py:527] (2/6) Epoch 442, batch 16, global_batch_idx: 54700, batch size: 70, loss[discriminator_loss=2.701, discriminator_real_loss=1.428, discriminator_fake_loss=1.273, generator_loss=28.52, generator_mel_loss=18.14, generator_kl_loss=1.338, generator_dur_loss=1.799, generator_adv_loss=1.984, generator_feat_match_loss=5.266, over 70.00 samples.], tot_loss[discriminator_loss=2.723, discriminator_real_loss=1.38, discriminator_fake_loss=1.344, generator_loss=28.21, generator_mel_loss=18.17, generator_kl_loss=1.42, generator_dur_loss=1.737, generator_adv_loss=1.962, generator_feat_match_loss=4.914, over 939.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 21:22:08,427 INFO [train.py:527] (2/6) Epoch 442, batch 66, global_batch_idx: 54750, batch size: 62, loss[discriminator_loss=2.747, discriminator_real_loss=1.428, discriminator_fake_loss=1.32, generator_loss=27.21, generator_mel_loss=17.79, generator_kl_loss=1.376, generator_dur_loss=1.801, generator_adv_loss=1.929, generator_feat_match_loss=4.307, over 62.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.379, discriminator_fake_loss=1.337, generator_loss=27.97, generator_mel_loss=18.03, generator_kl_loss=1.403, generator_dur_loss=1.757, generator_adv_loss=1.958, generator_feat_match_loss=4.823, over 4017.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 21:24:26,447 INFO [train.py:527] (2/6) Epoch 442, batch 116, global_batch_idx: 54800, batch size: 47, loss[discriminator_loss=2.624, discriminator_real_loss=1.387, discriminator_fake_loss=1.237, generator_loss=30.5, generator_mel_loss=19.07, generator_kl_loss=1.526, generator_dur_loss=1.695, generator_adv_loss=2.09, generator_feat_match_loss=6.115, over 47.00 samples.], tot_loss[discriminator_loss=2.717, discriminator_real_loss=1.38, discriminator_fake_loss=1.337, generator_loss=28.03, generator_mel_loss=18.07, generator_kl_loss=1.416, generator_dur_loss=1.749, generator_adv_loss=1.955, generator_feat_match_loss=4.835, over 6546.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 21:24:26,449 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 21:24:35,319 INFO [train.py:591] (2/6) Epoch 442, validation: discriminator_loss=2.789, discriminator_real_loss=1.452, discriminator_fake_loss=1.337, generator_loss=27.65, generator_mel_loss=18.86, generator_kl_loss=1.358, generator_dur_loss=1.83, generator_adv_loss=1.862, generator_feat_match_loss=3.744, over 100.00 samples.
2024-03-13 21:24:35,321 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 21:24:54,279 INFO [train.py:919] (2/6) Start epoch 443
2024-03-13 21:27:15,703 INFO [train.py:527] (2/6) Epoch 443, batch 42, global_batch_idx: 54850, batch size: 64, loss[discriminator_loss=2.714, discriminator_real_loss=1.314, discriminator_fake_loss=1.4, generator_loss=27.63, generator_mel_loss=17.63, generator_kl_loss=1.249, generator_dur_loss=1.793, generator_adv_loss=1.99, generator_feat_match_loss=4.966, over 64.00 samples.], tot_loss[discriminator_loss=2.727, discriminator_real_loss=1.381, discriminator_fake_loss=1.347, generator_loss=28.14, generator_mel_loss=18.06, generator_kl_loss=1.424, generator_dur_loss=1.759, generator_adv_loss=1.949, generator_feat_match_loss=4.946, over 2456.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 21:29:35,336 INFO [train.py:527] (2/6) Epoch 443, batch 92, global_batch_idx: 54900, batch size: 66, loss[discriminator_loss=2.651, discriminator_real_loss=1.352, discriminator_fake_loss=1.298, generator_loss=29.41, generator_mel_loss=18.62, generator_kl_loss=1.435, generator_dur_loss=1.78, generator_adv_loss=2.155, generator_feat_match_loss=5.419, over 66.00 samples.], tot_loss[discriminator_loss=2.717, discriminator_real_loss=1.37, discriminator_fake_loss=1.347, generator_loss=28.26, generator_mel_loss=18.1, generator_kl_loss=1.416, generator_dur_loss=1.762, generator_adv_loss=1.983, generator_feat_match_loss=5, over 5320.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 21:30:59,368 INFO [train.py:919] (2/6) Start epoch 444
2024-03-13 21:32:11,053 INFO [train.py:527] (2/6) Epoch 444, batch 18, global_batch_idx: 54950, batch size: 68, loss[discriminator_loss=2.754, discriminator_real_loss=1.365, discriminator_fake_loss=1.39, generator_loss=28.38, generator_mel_loss=18.39, generator_kl_loss=1.295, generator_dur_loss=1.818, generator_adv_loss=1.877, generator_feat_match_loss=4.993, over 68.00 samples.], tot_loss[discriminator_loss=2.727, discriminator_real_loss=1.381, discriminator_fake_loss=1.346, generator_loss=28.34, generator_mel_loss=18.25, generator_kl_loss=1.425, generator_dur_loss=1.766, generator_adv_loss=1.954, generator_feat_match_loss=4.947, over 1187.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 21:34:31,960 INFO [train.py:527] (2/6) Epoch 444, batch 68, global_batch_idx: 55000, batch size: 59, loss[discriminator_loss=2.774, discriminator_real_loss=1.457, discriminator_fake_loss=1.318, generator_loss=27.53, generator_mel_loss=18.01, generator_kl_loss=1.357, generator_dur_loss=1.699, generator_adv_loss=1.908, generator_feat_match_loss=4.556, over 59.00 samples.], tot_loss[discriminator_loss=2.723, discriminator_real_loss=1.383, discriminator_fake_loss=1.34, generator_loss=28.11, generator_mel_loss=18.12, generator_kl_loss=1.425, generator_dur_loss=1.764, generator_adv_loss=1.952, generator_feat_match_loss=4.852, over 4044.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 21:34:31,962 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 21:34:40,032 INFO [train.py:591] (2/6) Epoch 444, validation: discriminator_loss=2.77, discriminator_real_loss=1.474, discriminator_fake_loss=1.296, generator_loss=27.27, generator_mel_loss=18.42, generator_kl_loss=1.313, generator_dur_loss=1.839, generator_adv_loss=1.899, generator_feat_match_loss=3.804, over 100.00 samples.
2024-03-13 21:34:40,033 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 21:36:56,039 INFO [train.py:527] (2/6) Epoch 444, batch 118, global_batch_idx: 55050, batch size: 31, loss[discriminator_loss=2.684, discriminator_real_loss=1.377, discriminator_fake_loss=1.307, generator_loss=28.35, generator_mel_loss=18.59, generator_kl_loss=1.536, generator_dur_loss=1.628, generator_adv_loss=1.92, generator_feat_match_loss=4.671, over 31.00 samples.], tot_loss[discriminator_loss=2.723, discriminator_real_loss=1.383, discriminator_fake_loss=1.34, generator_loss=28.01, generator_mel_loss=18.07, generator_kl_loss=1.426, generator_dur_loss=1.762, generator_adv_loss=1.947, generator_feat_match_loss=4.801, over 6817.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 21:37:11,265 INFO [train.py:919] (2/6) Start epoch 445
2024-03-13 21:39:41,586 INFO [train.py:527] (2/6) Epoch 445, batch 44, global_batch_idx: 55100, batch size: 68, loss[discriminator_loss=2.663, discriminator_real_loss=1.268, discriminator_fake_loss=1.395, generator_loss=28.69, generator_mel_loss=17.95, generator_kl_loss=1.443, generator_dur_loss=1.774, generator_adv_loss=2.095, generator_feat_match_loss=5.429, over 68.00 samples.], tot_loss[discriminator_loss=2.707, discriminator_real_loss=1.365, discriminator_fake_loss=1.342, generator_loss=28.07, generator_mel_loss=18.11, generator_kl_loss=1.419, generator_dur_loss=1.772, generator_adv_loss=1.949, generator_feat_match_loss=4.828, over 2599.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 21:42:00,812 INFO [train.py:527] (2/6) Epoch 445, batch 94, global_batch_idx: 55150, batch size: 83, loss[discriminator_loss=2.724, discriminator_real_loss=1.36, discriminator_fake_loss=1.364, generator_loss=28.04, generator_mel_loss=18.27, generator_kl_loss=1.301, generator_dur_loss=1.849, generator_adv_loss=1.865, generator_feat_match_loss=4.752, over 83.00 samples.], tot_loss[discriminator_loss=2.712, discriminator_real_loss=1.373, discriminator_fake_loss=1.34, generator_loss=28.18, generator_mel_loss=18.14, generator_kl_loss=1.42, generator_dur_loss=1.768, generator_adv_loss=1.96, generator_feat_match_loss=4.894, over 5471.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 21:43:17,449 INFO [train.py:919] (2/6) Start epoch 446
2024-03-13 21:44:33,593 INFO [train.py:527] (2/6) Epoch 446, batch 20, global_batch_idx: 55200, batch size: 56, loss[discriminator_loss=2.721, discriminator_real_loss=1.471, discriminator_fake_loss=1.25, generator_loss=28.95, generator_mel_loss=18.45, generator_kl_loss=1.717, generator_dur_loss=1.65, generator_adv_loss=1.909, generator_feat_match_loss=5.223, over 56.00 samples.], tot_loss[discriminator_loss=2.719, discriminator_real_loss=1.394, discriminator_fake_loss=1.325, generator_loss=28.09, generator_mel_loss=18.09, generator_kl_loss=1.447, generator_dur_loss=1.718, generator_adv_loss=1.952, generator_feat_match_loss=4.88, over 1068.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 21:44:33,595 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 21:44:41,676 INFO [train.py:591] (2/6) Epoch 446, validation: discriminator_loss=2.779, discriminator_real_loss=1.447, discriminator_fake_loss=1.332, generator_loss=26.72, generator_mel_loss=18.09, generator_kl_loss=1.257, generator_dur_loss=1.837, generator_adv_loss=1.85, generator_feat_match_loss=3.689, over 100.00 samples.
2024-03-13 21:44:41,677 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 21:46:59,747 INFO [train.py:527] (2/6) Epoch 446, batch 70, global_batch_idx: 55250, batch size: 42, loss[discriminator_loss=2.744, discriminator_real_loss=1.46, discriminator_fake_loss=1.284, generator_loss=28.86, generator_mel_loss=18.25, generator_kl_loss=1.534, generator_dur_loss=1.664, generator_adv_loss=1.93, generator_feat_match_loss=5.483, over 42.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.376, discriminator_fake_loss=1.339, generator_loss=28.25, generator_mel_loss=18.18, generator_kl_loss=1.452, generator_dur_loss=1.738, generator_adv_loss=1.952, generator_feat_match_loss=4.932, over 3779.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 21:49:19,345 INFO [train.py:527] (2/6) Epoch 446, batch 120, global_batch_idx: 55300, batch size: 48, loss[discriminator_loss=2.753, discriminator_real_loss=1.429, discriminator_fake_loss=1.324, generator_loss=27.26, generator_mel_loss=17.55, generator_kl_loss=1.556, generator_dur_loss=1.708, generator_adv_loss=2.039, generator_feat_match_loss=4.402, over 48.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.377, discriminator_fake_loss=1.339, generator_loss=28.18, generator_mel_loss=18.15, generator_kl_loss=1.437, generator_dur_loss=1.75, generator_adv_loss=1.96, generator_feat_match_loss=4.883, over 6598.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 21:49:29,326 INFO [train.py:919] (2/6) Start epoch 447
2024-03-13 21:52:03,006 INFO [train.py:527] (2/6) Epoch 447, batch 46, global_batch_idx: 55350, batch size: 44, loss[discriminator_loss=2.69, discriminator_real_loss=1.399, discriminator_fake_loss=1.29, generator_loss=28.84, generator_mel_loss=18.39, generator_kl_loss=1.353, generator_dur_loss=1.673, generator_adv_loss=2.132, generator_feat_match_loss=5.293, over 44.00 samples.], tot_loss[discriminator_loss=2.718, discriminator_real_loss=1.372, discriminator_fake_loss=1.346, generator_loss=28.04, generator_mel_loss=18.09, generator_kl_loss=1.403, generator_dur_loss=1.779, generator_adv_loss=1.947, generator_feat_match_loss=4.818, over 2867.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 21:54:22,891 INFO [train.py:527] (2/6) Epoch 447, batch 96, global_batch_idx: 55400, batch size: 80, loss[discriminator_loss=2.712, discriminator_real_loss=1.385, discriminator_fake_loss=1.327, generator_loss=28.22, generator_mel_loss=18.1, generator_kl_loss=1.267, generator_dur_loss=1.772, generator_adv_loss=2.038, generator_feat_match_loss=5.042, over 80.00 samples.], tot_loss[discriminator_loss=2.714, discriminator_real_loss=1.367, discriminator_fake_loss=1.347, generator_loss=28.05, generator_mel_loss=18.06, generator_kl_loss=1.403, generator_dur_loss=1.778, generator_adv_loss=1.948, generator_feat_match_loss=4.859, over 5840.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 21:54:22,893 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 21:54:31,586 INFO [train.py:591] (2/6) Epoch 447, validation: discriminator_loss=2.762, discriminator_real_loss=1.484, discriminator_fake_loss=1.278, generator_loss=26.71, generator_mel_loss=18.1, generator_kl_loss=1.29, generator_dur_loss=1.837, generator_adv_loss=1.976, generator_feat_match_loss=3.501, over 100.00 samples.
2024-03-13 21:54:31,588 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 21:55:45,166 INFO [train.py:919] (2/6) Start epoch 448
2024-03-13 21:57:09,233 INFO [train.py:527] (2/6) Epoch 448, batch 22, global_batch_idx: 55450, batch size: 47, loss[discriminator_loss=2.703, discriminator_real_loss=1.408, discriminator_fake_loss=1.295, generator_loss=27.74, generator_mel_loss=17.89, generator_kl_loss=1.429, generator_dur_loss=1.736, generator_adv_loss=1.854, generator_feat_match_loss=4.835, over 47.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.373, discriminator_fake_loss=1.343, generator_loss=28.02, generator_mel_loss=18.07, generator_kl_loss=1.398, generator_dur_loss=1.765, generator_adv_loss=1.96, generator_feat_match_loss=4.826, over 1312.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 21:59:27,804 INFO [train.py:527] (2/6) Epoch 448, batch 72, global_batch_idx: 55500, batch size: 74, loss[discriminator_loss=2.767, discriminator_real_loss=1.437, discriminator_fake_loss=1.329, generator_loss=28.5, generator_mel_loss=18.3, generator_kl_loss=1.32, generator_dur_loss=1.794, generator_adv_loss=1.93, generator_feat_match_loss=5.155, over 74.00 samples.], tot_loss[discriminator_loss=2.708, discriminator_real_loss=1.365, discriminator_fake_loss=1.343, generator_loss=28.14, generator_mel_loss=18.1, generator_kl_loss=1.409, generator_dur_loss=1.768, generator_adv_loss=1.953, generator_feat_match_loss=4.913, over 4053.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 22:01:46,060 INFO [train.py:527] (2/6) Epoch 448, batch 122, global_batch_idx: 55550, batch size: 55, loss[discriminator_loss=2.686, discriminator_real_loss=1.373, discriminator_fake_loss=1.313, generator_loss=29.03, generator_mel_loss=18.7, generator_kl_loss=1.444, generator_dur_loss=1.722, generator_adv_loss=1.935, generator_feat_match_loss=5.235, over 55.00 samples.], tot_loss[discriminator_loss=2.711, discriminator_real_loss=1.368, discriminator_fake_loss=1.343, generator_loss=28.11, generator_mel_loss=18.1, generator_kl_loss=1.405, generator_dur_loss=1.762, generator_adv_loss=1.954, generator_feat_match_loss=4.885, over 6924.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 22:01:51,097 INFO [train.py:919] (2/6) Start epoch 449
2024-03-13 22:04:26,678 INFO [train.py:527] (2/6) Epoch 449, batch 48, global_batch_idx: 55600, batch size: 72, loss[discriminator_loss=2.677, discriminator_real_loss=1.298, discriminator_fake_loss=1.379, generator_loss=28.57, generator_mel_loss=17.99, generator_kl_loss=1.476, generator_dur_loss=1.798, generator_adv_loss=1.851, generator_feat_match_loss=5.455, over 72.00 samples.], tot_loss[discriminator_loss=2.729, discriminator_real_loss=1.385, discriminator_fake_loss=1.344, generator_loss=28.1, generator_mel_loss=18.12, generator_kl_loss=1.432, generator_dur_loss=1.75, generator_adv_loss=1.939, generator_feat_match_loss=4.864, over 2730.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 22:04:26,680 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 22:04:34,678 INFO [train.py:591] (2/6) Epoch 449, validation: discriminator_loss=2.757, discriminator_real_loss=1.339, discriminator_fake_loss=1.419, generator_loss=26.97, generator_mel_loss=18.16, generator_kl_loss=1.266, generator_dur_loss=1.819, generator_adv_loss=1.777, generator_feat_match_loss=3.945, over 100.00 samples.
2024-03-13 22:04:34,679 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 22:06:50,824 INFO [train.py:527] (2/6) Epoch 449, batch 98, global_batch_idx: 55650, batch size: 70, loss[discriminator_loss=2.735, discriminator_real_loss=1.483, discriminator_fake_loss=1.251, generator_loss=28.45, generator_mel_loss=18.09, generator_kl_loss=1.248, generator_dur_loss=1.792, generator_adv_loss=2.097, generator_feat_match_loss=5.227, over 70.00 samples.], tot_loss[discriminator_loss=2.721, discriminator_real_loss=1.376, discriminator_fake_loss=1.345, generator_loss=28.04, generator_mel_loss=18.08, generator_kl_loss=1.413, generator_dur_loss=1.748, generator_adv_loss=1.948, generator_feat_match_loss=4.85, over 5530.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 22:08:03,285 INFO [train.py:919] (2/6) Start epoch 450
2024-03-13 22:09:34,077 INFO [train.py:527] (2/6) Epoch 450, batch 24, global_batch_idx: 55700, batch size: 64, loss[discriminator_loss=2.724, discriminator_real_loss=1.396, discriminator_fake_loss=1.329, generator_loss=28.39, generator_mel_loss=18.27, generator_kl_loss=1.432, generator_dur_loss=1.763, generator_adv_loss=1.895, generator_feat_match_loss=5.025, over 64.00 samples.], tot_loss[discriminator_loss=2.706, discriminator_real_loss=1.368, discriminator_fake_loss=1.338, generator_loss=27.86, generator_mel_loss=17.97, generator_kl_loss=1.38, generator_dur_loss=1.747, generator_adv_loss=1.951, generator_feat_match_loss=4.81, over 1505.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 22:11:52,364 INFO [train.py:527] (2/6) Epoch 450, batch 74, global_batch_idx: 55750, batch size: 68, loss[discriminator_loss=2.693, discriminator_real_loss=1.37, discriminator_fake_loss=1.323, generator_loss=26.87, generator_mel_loss=17.25, generator_kl_loss=1.332, generator_dur_loss=1.796, generator_adv_loss=1.924, generator_feat_match_loss=4.568, over 68.00 samples.], tot_loss[discriminator_loss=2.701, discriminator_real_loss=1.357, discriminator_fake_loss=1.344, generator_loss=28.11, generator_mel_loss=18.06, generator_kl_loss=1.39, generator_dur_loss=1.757, generator_adv_loss=1.973, generator_feat_match_loss=4.936, over 4384.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 22:14:08,469 INFO [train.py:919] (2/6) Start epoch 451
2024-03-13 22:14:31,925 INFO [train.py:527] (2/6) Epoch 451, batch 0, global_batch_idx: 55800, batch size: 31, loss[discriminator_loss=2.756, discriminator_real_loss=1.306, discriminator_fake_loss=1.45, generator_loss=28.26, generator_mel_loss=18.1, generator_kl_loss=1.515, generator_dur_loss=1.626, generator_adv_loss=1.938, generator_feat_match_loss=5.086, over 31.00 samples.], tot_loss[discriminator_loss=2.756, discriminator_real_loss=1.306, discriminator_fake_loss=1.45, generator_loss=28.26, generator_mel_loss=18.1, generator_kl_loss=1.515, generator_dur_loss=1.626, generator_adv_loss=1.938, generator_feat_match_loss=5.086, over 31.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 22:14:31,929 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 22:14:39,769 INFO [train.py:591] (2/6) Epoch 451, validation: discriminator_loss=2.782, discriminator_real_loss=1.506, discriminator_fake_loss=1.276, generator_loss=26.31, generator_mel_loss=18.03, generator_kl_loss=1.253, generator_dur_loss=1.825, generator_adv_loss=1.882, generator_feat_match_loss=3.323, over 100.00 samples.
2024-03-13 22:14:39,771 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 22:16:57,332 INFO [train.py:527] (2/6) Epoch 451, batch 50, global_batch_idx: 55850, batch size: 56, loss[discriminator_loss=2.779, discriminator_real_loss=1.37, discriminator_fake_loss=1.41, generator_loss=27.58, generator_mel_loss=17.79, generator_kl_loss=1.322, generator_dur_loss=1.704, generator_adv_loss=1.983, generator_feat_match_loss=4.776, over 56.00 samples.], tot_loss[discriminator_loss=2.727, discriminator_real_loss=1.381, discriminator_fake_loss=1.346, generator_loss=28.05, generator_mel_loss=18.07, generator_kl_loss=1.411, generator_dur_loss=1.749, generator_adv_loss=1.935, generator_feat_match_loss=4.877, over 2794.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 22:19:14,532 INFO [train.py:527] (2/6) Epoch 451, batch 100, global_batch_idx: 55900, batch size: 47, loss[discriminator_loss=2.841, discriminator_real_loss=1.38, discriminator_fake_loss=1.461, generator_loss=28.28, generator_mel_loss=18.54, generator_kl_loss=1.357, generator_dur_loss=1.728, generator_adv_loss=1.892, generator_feat_match_loss=4.76, over 47.00 samples.], tot_loss[discriminator_loss=2.721, discriminator_real_loss=1.375, discriminator_fake_loss=1.346, generator_loss=27.96, generator_mel_loss=18.02, generator_kl_loss=1.402, generator_dur_loss=1.754, generator_adv_loss=1.937, generator_feat_match_loss=4.851, over 5817.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 22:20:20,728 INFO [train.py:919] (2/6) Start epoch 452
2024-03-13 22:21:57,281 INFO [train.py:527] (2/6) Epoch 452, batch 26, global_batch_idx: 55950, batch size: 52, loss[discriminator_loss=2.746, discriminator_real_loss=1.404, discriminator_fake_loss=1.342, generator_loss=28.03, generator_mel_loss=18.04, generator_kl_loss=1.518, generator_dur_loss=1.725, generator_adv_loss=1.953, generator_feat_match_loss=4.791, over 52.00 samples.], tot_loss[discriminator_loss=2.718, discriminator_real_loss=1.38, discriminator_fake_loss=1.338, generator_loss=28.11, generator_mel_loss=18.12, generator_kl_loss=1.438, generator_dur_loss=1.76, generator_adv_loss=1.954, generator_feat_match_loss=4.837, over 1648.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 22:24:17,353 INFO [train.py:527] (2/6) Epoch 452, batch 76, global_batch_idx: 56000, batch size: 61, loss[discriminator_loss=2.742, discriminator_real_loss=1.404, discriminator_fake_loss=1.339, generator_loss=27.89, generator_mel_loss=17.97, generator_kl_loss=1.48, generator_dur_loss=1.773, generator_adv_loss=1.973, generator_feat_match_loss=4.694, over 61.00 samples.], tot_loss[discriminator_loss=2.712, discriminator_real_loss=1.369, discriminator_fake_loss=1.343, generator_loss=28.1, generator_mel_loss=18.09, generator_kl_loss=1.427, generator_dur_loss=1.759, generator_adv_loss=1.956, generator_feat_match_loss=4.872, over 4553.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 22:24:17,354 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 22:24:25,386 INFO [train.py:591] (2/6) Epoch 452, validation: discriminator_loss=2.778, discriminator_real_loss=1.488, discriminator_fake_loss=1.29, generator_loss=26.94, generator_mel_loss=18.1, generator_kl_loss=1.215, generator_dur_loss=1.844, generator_adv_loss=1.931, generator_feat_match_loss=3.847, over 100.00 samples.
2024-03-13 22:24:25,387 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 22:26:33,650 INFO [train.py:919] (2/6) Start epoch 453
2024-03-13 22:27:01,569 INFO [train.py:527] (2/6) Epoch 453, batch 2, global_batch_idx: 56050, batch size: 48, loss[discriminator_loss=2.699, discriminator_real_loss=1.416, discriminator_fake_loss=1.282, generator_loss=28.03, generator_mel_loss=17.95, generator_kl_loss=1.403, generator_dur_loss=1.695, generator_adv_loss=2.096, generator_feat_match_loss=4.891, over 48.00 samples.], tot_loss[discriminator_loss=2.702, discriminator_real_loss=1.382, discriminator_fake_loss=1.32, generator_loss=28.04, generator_mel_loss=17.92, generator_kl_loss=1.384, generator_dur_loss=1.771, generator_adv_loss=1.997, generator_feat_match_loss=4.962, over 176.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 22:29:16,631 INFO [train.py:527] (2/6) Epoch 453, batch 52, global_batch_idx: 56100, batch size: 70, loss[discriminator_loss=2.703, discriminator_real_loss=1.323, discriminator_fake_loss=1.38, generator_loss=28.55, generator_mel_loss=18.17, generator_kl_loss=1.299, generator_dur_loss=1.805, generator_adv_loss=2.117, generator_feat_match_loss=5.163, over 70.00 samples.], tot_loss[discriminator_loss=2.719, discriminator_real_loss=1.374, discriminator_fake_loss=1.346, generator_loss=28.15, generator_mel_loss=18.09, generator_kl_loss=1.393, generator_dur_loss=1.779, generator_adv_loss=1.962, generator_feat_match_loss=4.918, over 3188.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 22:31:35,326 INFO [train.py:527] (2/6) Epoch 453, batch 102, global_batch_idx: 56150, batch size: 31, loss[discriminator_loss=2.743, discriminator_real_loss=1.447, discriminator_fake_loss=1.296, generator_loss=26.87, generator_mel_loss=17.84, generator_kl_loss=1.574, generator_dur_loss=1.633, generator_adv_loss=2.017, generator_feat_match_loss=3.801, over 31.00 samples.], tot_loss[discriminator_loss=2.725, discriminator_real_loss=1.38, discriminator_fake_loss=1.345, generator_loss=28.08, generator_mel_loss=18.08, generator_kl_loss=1.398, generator_dur_loss=1.766, generator_adv_loss=1.955, generator_feat_match_loss=4.874, over 6033.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 22:32:35,759 INFO [train.py:919] (2/6) Start epoch 454
2024-03-13 22:34:17,165 INFO [train.py:527] (2/6) Epoch 454, batch 28, global_batch_idx: 56200, batch size: 25, loss[discriminator_loss=2.752, discriminator_real_loss=1.35, discriminator_fake_loss=1.402, generator_loss=29.4, generator_mel_loss=17.99, generator_kl_loss=1.874, generator_dur_loss=1.592, generator_adv_loss=2.096, generator_feat_match_loss=5.844, over 25.00 samples.], tot_loss[discriminator_loss=2.713, discriminator_real_loss=1.351, discriminator_fake_loss=1.361, generator_loss=28.31, generator_mel_loss=18.16, generator_kl_loss=1.44, generator_dur_loss=1.746, generator_adv_loss=2.019, generator_feat_match_loss=4.943, over 1489.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 22:34:17,167 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 22:34:25,074 INFO [train.py:591] (2/6) Epoch 454, validation: discriminator_loss=2.785, discriminator_real_loss=1.482, discriminator_fake_loss=1.302, generator_loss=27.43, generator_mel_loss=18.39, generator_kl_loss=1.257, generator_dur_loss=1.828, generator_adv_loss=1.899, generator_feat_match_loss=4.065, over 100.00 samples.
2024-03-13 22:34:25,075 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 22:36:45,224 INFO [train.py:527] (2/6) Epoch 454, batch 78, global_batch_idx: 56250, batch size: 61, loss[discriminator_loss=2.723, discriminator_real_loss=1.391, discriminator_fake_loss=1.333, generator_loss=27.89, generator_mel_loss=17.79, generator_kl_loss=1.397, generator_dur_loss=1.76, generator_adv_loss=2.013, generator_feat_match_loss=4.931, over 61.00 samples.], tot_loss[discriminator_loss=2.725, discriminator_real_loss=1.378, discriminator_fake_loss=1.347, generator_loss=28.08, generator_mel_loss=18.08, generator_kl_loss=1.411, generator_dur_loss=1.764, generator_adv_loss=1.977, generator_feat_match_loss=4.843, over 4418.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 22:38:49,983 INFO [train.py:919] (2/6) Start epoch 455
2024-03-13 22:39:24,151 INFO [train.py:527] (2/6) Epoch 455, batch 4, global_batch_idx: 56300, batch size: 56, loss[discriminator_loss=2.788, discriminator_real_loss=1.353, discriminator_fake_loss=1.435, generator_loss=27.99, generator_mel_loss=18.17, generator_kl_loss=1.387, generator_dur_loss=1.77, generator_adv_loss=1.923, generator_feat_match_loss=4.746, over 56.00 samples.], tot_loss[discriminator_loss=2.746, discriminator_real_loss=1.408, discriminator_fake_loss=1.339, generator_loss=28.14, generator_mel_loss=18.06, generator_kl_loss=1.463, generator_dur_loss=1.722, generator_adv_loss=1.967, generator_feat_match_loss=4.927, over 204.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 22:41:43,647 INFO [train.py:527] (2/6) Epoch 455, batch 54, global_batch_idx: 56350, batch size: 59, loss[discriminator_loss=2.74, discriminator_real_loss=1.315, discriminator_fake_loss=1.425, generator_loss=26.85, generator_mel_loss=17.61, generator_kl_loss=1.431, generator_dur_loss=1.7, generator_adv_loss=1.908, generator_feat_match_loss=4.202, over 59.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.379, discriminator_fake_loss=1.347, generator_loss=27.84, generator_mel_loss=17.98, generator_kl_loss=1.42, generator_dur_loss=1.748, generator_adv_loss=1.939, generator_feat_match_loss=4.758, over 3157.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 22:44:02,042 INFO [train.py:527] (2/6) Epoch 455, batch 104, global_batch_idx: 56400, batch size: 80, loss[discriminator_loss=2.643, discriminator_real_loss=1.266, discriminator_fake_loss=1.377, generator_loss=28.63, generator_mel_loss=18.48, generator_kl_loss=1.404, generator_dur_loss=1.793, generator_adv_loss=2.086, generator_feat_match_loss=4.865, over 80.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.37, discriminator_fake_loss=1.345, generator_loss=27.98, generator_mel_loss=18.06, generator_kl_loss=1.415, generator_dur_loss=1.748, generator_adv_loss=1.949, generator_feat_match_loss=4.809, over 6076.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 22:44:02,043 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 22:44:11,041 INFO [train.py:591] (2/6) Epoch 455, validation: discriminator_loss=2.763, discriminator_real_loss=1.513, discriminator_fake_loss=1.25, generator_loss=27.47, generator_mel_loss=18.5, generator_kl_loss=1.143, generator_dur_loss=1.829, generator_adv_loss=2.035, generator_feat_match_loss=3.965, over 100.00 samples.
2024-03-13 22:44:11,042 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 22:45:05,146 INFO [train.py:919] (2/6) Start epoch 456
2024-03-13 22:46:51,749 INFO [train.py:527] (2/6) Epoch 456, batch 30, global_batch_idx: 56450, batch size: 44, loss[discriminator_loss=2.73, discriminator_real_loss=1.344, discriminator_fake_loss=1.386, generator_loss=27.37, generator_mel_loss=18.28, generator_kl_loss=1.364, generator_dur_loss=1.725, generator_adv_loss=2.101, generator_feat_match_loss=3.906, over 44.00 samples.], tot_loss[discriminator_loss=2.714, discriminator_real_loss=1.375, discriminator_fake_loss=1.339, generator_loss=27.96, generator_mel_loss=18.07, generator_kl_loss=1.441, generator_dur_loss=1.755, generator_adv_loss=1.934, generator_feat_match_loss=4.758, over 1693.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 22:49:11,350 INFO [train.py:527] (2/6) Epoch 456, batch 80, global_batch_idx: 56500, batch size: 66, loss[discriminator_loss=2.745, discriminator_real_loss=1.427, discriminator_fake_loss=1.318, generator_loss=28.32, generator_mel_loss=18.17, generator_kl_loss=1.561, generator_dur_loss=1.786, generator_adv_loss=1.927, generator_feat_match_loss=4.877, over 66.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.375, discriminator_fake_loss=1.34, generator_loss=28.1, generator_mel_loss=18.12, generator_kl_loss=1.409, generator_dur_loss=1.761, generator_adv_loss=1.947, generator_feat_match_loss=4.862, over 4698.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 22:51:12,264 INFO [train.py:919] (2/6) Start epoch 457
2024-03-13 22:51:51,402 INFO [train.py:527] (2/6) Epoch 457, batch 6, global_batch_idx: 56550, batch size: 64, loss[discriminator_loss=2.754, discriminator_real_loss=1.394, discriminator_fake_loss=1.36, generator_loss=28.45, generator_mel_loss=18.17, generator_kl_loss=1.33, generator_dur_loss=1.741, generator_adv_loss=2.001, generator_feat_match_loss=5.216, over 64.00 samples.], tot_loss[discriminator_loss=2.743, discriminator_real_loss=1.386, discriminator_fake_loss=1.357, generator_loss=28.07, generator_mel_loss=18.05, generator_kl_loss=1.436, generator_dur_loss=1.786, generator_adv_loss=1.934, generator_feat_match_loss=4.866, over 466.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 22:54:13,891 INFO [train.py:527] (2/6) Epoch 457, batch 56, global_batch_idx: 56600, batch size: 68, loss[discriminator_loss=2.757, discriminator_real_loss=1.409, discriminator_fake_loss=1.349, generator_loss=27.09, generator_mel_loss=17.54, generator_kl_loss=1.419, generator_dur_loss=1.799, generator_adv_loss=1.962, generator_feat_match_loss=4.375, over 68.00 samples.], tot_loss[discriminator_loss=2.728, discriminator_real_loss=1.378, discriminator_fake_loss=1.35, generator_loss=27.95, generator_mel_loss=17.99, generator_kl_loss=1.406, generator_dur_loss=1.788, generator_adv_loss=1.952, generator_feat_match_loss=4.814, over 3531.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 22:54:13,893 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 22:54:21,933 INFO [train.py:591] (2/6) Epoch 457, validation: discriminator_loss=2.738, discriminator_real_loss=1.474, discriminator_fake_loss=1.264, generator_loss=26.53, generator_mel_loss=18.11, generator_kl_loss=1.237, generator_dur_loss=1.824, generator_adv_loss=1.89, generator_feat_match_loss=3.468, over 100.00 samples.
2024-03-13 22:54:21,934 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 22:56:41,943 INFO [train.py:527] (2/6) Epoch 457, batch 106, global_batch_idx: 56650, batch size: 56, loss[discriminator_loss=2.749, discriminator_real_loss=1.397, discriminator_fake_loss=1.352, generator_loss=27.49, generator_mel_loss=17.68, generator_kl_loss=1.445, generator_dur_loss=1.736, generator_adv_loss=2.059, generator_feat_match_loss=4.563, over 56.00 samples.], tot_loss[discriminator_loss=2.727, discriminator_real_loss=1.38, discriminator_fake_loss=1.347, generator_loss=27.96, generator_mel_loss=18.04, generator_kl_loss=1.413, generator_dur_loss=1.782, generator_adv_loss=1.951, generator_feat_match_loss=4.78, over 6549.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 22:57:26,619 INFO [train.py:919] (2/6) Start epoch 458
2024-03-13 22:59:21,185 INFO [train.py:527] (2/6) Epoch 458, batch 32, global_batch_idx: 56700, batch size: 88, loss[discriminator_loss=2.739, discriminator_real_loss=1.424, discriminator_fake_loss=1.315, generator_loss=27.95, generator_mel_loss=17.99, generator_kl_loss=1.271, generator_dur_loss=1.863, generator_adv_loss=1.837, generator_feat_match_loss=4.991, over 88.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.374, discriminator_fake_loss=1.347, generator_loss=28.05, generator_mel_loss=18.08, generator_kl_loss=1.386, generator_dur_loss=1.781, generator_adv_loss=1.944, generator_feat_match_loss=4.865, over 2006.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 23:01:40,106 INFO [train.py:527] (2/6) Epoch 458, batch 82, global_batch_idx: 56750, batch size: 45, loss[discriminator_loss=2.74, discriminator_real_loss=1.403, discriminator_fake_loss=1.336, generator_loss=27.41, generator_mel_loss=17.77, generator_kl_loss=1.499, generator_dur_loss=1.698, generator_adv_loss=1.902, generator_feat_match_loss=4.538, over 45.00 samples.], tot_loss[discriminator_loss=2.713, discriminator_real_loss=1.365, discriminator_fake_loss=1.348, generator_loss=27.99, generator_mel_loss=18.03, generator_kl_loss=1.398, generator_dur_loss=1.776, generator_adv_loss=1.949, generator_feat_match_loss=4.839, over 4919.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 23:03:34,265 INFO [train.py:919] (2/6) Start epoch 459
2024-03-13 23:04:20,574 INFO [train.py:527] (2/6) Epoch 459, batch 8, global_batch_idx: 56800, batch size: 64, loss[discriminator_loss=2.786, discriminator_real_loss=1.568, discriminator_fake_loss=1.218, generator_loss=27.94, generator_mel_loss=18.03, generator_kl_loss=1.64, generator_dur_loss=1.718, generator_adv_loss=1.909, generator_feat_match_loss=4.641, over 64.00 samples.], tot_loss[discriminator_loss=2.759, discriminator_real_loss=1.393, discriminator_fake_loss=1.366, generator_loss=27.99, generator_mel_loss=18.02, generator_kl_loss=1.416, generator_dur_loss=1.75, generator_adv_loss=2.013, generator_feat_match_loss=4.788, over 578.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 23:04:20,577 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 23:04:28,785 INFO [train.py:591] (2/6) Epoch 459, validation: discriminator_loss=2.756, discriminator_real_loss=1.415, discriminator_fake_loss=1.342, generator_loss=26.56, generator_mel_loss=18.05, generator_kl_loss=1.314, generator_dur_loss=1.787, generator_adv_loss=1.917, generator_feat_match_loss=3.492, over 100.00 samples.
2024-03-13 23:04:28,788 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 23:06:47,992 INFO [train.py:527] (2/6) Epoch 459, batch 58, global_batch_idx: 56850, batch size: 13, loss[discriminator_loss=2.718, discriminator_real_loss=1.284, discriminator_fake_loss=1.434, generator_loss=29.63, generator_mel_loss=18.98, generator_kl_loss=1.776, generator_dur_loss=1.717, generator_adv_loss=2.145, generator_feat_match_loss=5.011, over 13.00 samples.], tot_loss[discriminator_loss=2.711, discriminator_real_loss=1.373, discriminator_fake_loss=1.338, generator_loss=28.02, generator_mel_loss=18.03, generator_kl_loss=1.429, generator_dur_loss=1.739, generator_adv_loss=1.959, generator_feat_match_loss=4.864, over 3338.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 23:09:07,415 INFO [train.py:527] (2/6) Epoch 459, batch 108, global_batch_idx: 56900, batch size: 12, loss[discriminator_loss=2.705, discriminator_real_loss=1.279, discriminator_fake_loss=1.426, generator_loss=29.42, generator_mel_loss=19.21, generator_kl_loss=1.759, generator_dur_loss=1.601, generator_adv_loss=2.013, generator_feat_match_loss=4.84, over 12.00 samples.], tot_loss[discriminator_loss=2.708, discriminator_real_loss=1.373, discriminator_fake_loss=1.334, generator_loss=28.06, generator_mel_loss=18.04, generator_kl_loss=1.421, generator_dur_loss=1.743, generator_adv_loss=1.969, generator_feat_match_loss=4.891, over 6168.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 23:09:50,429 INFO [train.py:919] (2/6) Start epoch 460
2024-03-13 23:11:48,819 INFO [train.py:527] (2/6) Epoch 460, batch 34, global_batch_idx: 56950, batch size: 31, loss[discriminator_loss=2.747, discriminator_real_loss=1.499, discriminator_fake_loss=1.249, generator_loss=27.03, generator_mel_loss=17.96, generator_kl_loss=1.513, generator_dur_loss=1.712, generator_adv_loss=1.889, generator_feat_match_loss=3.959, over 31.00 samples.], tot_loss[discriminator_loss=2.724, discriminator_real_loss=1.379, discriminator_fake_loss=1.345, generator_loss=28.11, generator_mel_loss=18.13, generator_kl_loss=1.43, generator_dur_loss=1.751, generator_adv_loss=1.95, generator_feat_match_loss=4.852, over 1935.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 23:14:09,529 INFO [train.py:527] (2/6) Epoch 460, batch 84, global_batch_idx: 57000, batch size: 61, loss[discriminator_loss=2.736, discriminator_real_loss=1.34, discriminator_fake_loss=1.396, generator_loss=28.68, generator_mel_loss=18.52, generator_kl_loss=1.354, generator_dur_loss=1.79, generator_adv_loss=1.995, generator_feat_match_loss=5.022, over 61.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.373, discriminator_fake_loss=1.342, generator_loss=28.13, generator_mel_loss=18.09, generator_kl_loss=1.408, generator_dur_loss=1.763, generator_adv_loss=1.951, generator_feat_match_loss=4.921, over 4889.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 23:14:09,531 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 23:14:18,393 INFO [train.py:591] (2/6) Epoch 460, validation: discriminator_loss=2.79, discriminator_real_loss=1.545, discriminator_fake_loss=1.245, generator_loss=26.98, generator_mel_loss=18.17, generator_kl_loss=1.213, generator_dur_loss=1.823, generator_adv_loss=1.988, generator_feat_match_loss=3.778, over 100.00 samples.
2024-03-13 23:14:18,394 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 23:16:10,168 INFO [train.py:919] (2/6) Start epoch 461
2024-03-13 23:17:02,048 INFO [train.py:527] (2/6) Epoch 461, batch 10, global_batch_idx: 57050, batch size: 80, loss[discriminator_loss=2.741, discriminator_real_loss=1.405, discriminator_fake_loss=1.337, generator_loss=26.86, generator_mel_loss=17.91, generator_kl_loss=1.265, generator_dur_loss=1.851, generator_adv_loss=1.769, generator_feat_match_loss=4.067, over 80.00 samples.], tot_loss[discriminator_loss=2.704, discriminator_real_loss=1.373, discriminator_fake_loss=1.331, generator_loss=27.96, generator_mel_loss=17.97, generator_kl_loss=1.395, generator_dur_loss=1.78, generator_adv_loss=1.922, generator_feat_match_loss=4.889, over 676.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 23:19:22,936 INFO [train.py:527] (2/6) Epoch 461, batch 60, global_batch_idx: 57100, batch size: 72, loss[discriminator_loss=2.685, discriminator_real_loss=1.307, discriminator_fake_loss=1.377, generator_loss=28.07, generator_mel_loss=17.88, generator_kl_loss=1.278, generator_dur_loss=1.831, generator_adv_loss=2.007, generator_feat_match_loss=5.07, over 72.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.373, discriminator_fake_loss=1.343, generator_loss=27.97, generator_mel_loss=18.03, generator_kl_loss=1.383, generator_dur_loss=1.761, generator_adv_loss=1.944, generator_feat_match_loss=4.85, over 3707.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 23:21:41,997 INFO [train.py:527] (2/6) Epoch 461, batch 110, global_batch_idx: 57150, batch size: 42, loss[discriminator_loss=2.726, discriminator_real_loss=1.412, discriminator_fake_loss=1.314, generator_loss=27.7, generator_mel_loss=18.21, generator_kl_loss=1.575, generator_dur_loss=1.624, generator_adv_loss=1.947, generator_feat_match_loss=4.345, over 42.00 samples.], tot_loss[discriminator_loss=2.719, discriminator_real_loss=1.378, discriminator_fake_loss=1.341, generator_loss=27.93, generator_mel_loss=18.03, generator_kl_loss=1.402, generator_dur_loss=1.745, generator_adv_loss=1.949, generator_feat_match_loss=4.806, over 6463.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 23:22:19,184 INFO [train.py:919] (2/6) Start epoch 462
2024-03-13 23:24:25,921 INFO [train.py:527] (2/6) Epoch 462, batch 36, global_batch_idx: 57200, batch size: 55, loss[discriminator_loss=2.738, discriminator_real_loss=1.301, discriminator_fake_loss=1.437, generator_loss=28.6, generator_mel_loss=18.49, generator_kl_loss=1.53, generator_dur_loss=1.725, generator_adv_loss=2.069, generator_feat_match_loss=4.781, over 55.00 samples.], tot_loss[discriminator_loss=2.736, discriminator_real_loss=1.38, discriminator_fake_loss=1.356, generator_loss=28.05, generator_mel_loss=18.1, generator_kl_loss=1.421, generator_dur_loss=1.735, generator_adv_loss=1.941, generator_feat_match_loss=4.848, over 2075.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 23:24:25,923 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 23:24:33,975 INFO [train.py:591] (2/6) Epoch 462, validation: discriminator_loss=2.77, discriminator_real_loss=1.451, discriminator_fake_loss=1.318, generator_loss=26.88, generator_mel_loss=18.14, generator_kl_loss=1.209, generator_dur_loss=1.803, generator_adv_loss=1.881, generator_feat_match_loss=3.847, over 100.00 samples.
2024-03-13 23:24:33,976 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 23:26:50,870 INFO [train.py:527] (2/6) Epoch 462, batch 86, global_batch_idx: 57250, batch size: 56, loss[discriminator_loss=2.744, discriminator_real_loss=1.437, discriminator_fake_loss=1.307, generator_loss=28.23, generator_mel_loss=18.29, generator_kl_loss=1.497, generator_dur_loss=1.685, generator_adv_loss=1.81, generator_feat_match_loss=4.945, over 56.00 samples.], tot_loss[discriminator_loss=2.724, discriminator_real_loss=1.384, discriminator_fake_loss=1.34, generator_loss=28.02, generator_mel_loss=18.05, generator_kl_loss=1.421, generator_dur_loss=1.74, generator_adv_loss=1.951, generator_feat_match_loss=4.852, over 4873.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 23:28:36,563 INFO [train.py:919] (2/6) Start epoch 463
2024-03-13 23:29:31,961 INFO [train.py:527] (2/6) Epoch 463, batch 12, global_batch_idx: 57300, batch size: 80, loss[discriminator_loss=2.734, discriminator_real_loss=1.379, discriminator_fake_loss=1.356, generator_loss=27.67, generator_mel_loss=17.93, generator_kl_loss=1.378, generator_dur_loss=1.773, generator_adv_loss=1.853, generator_feat_match_loss=4.733, over 80.00 samples.], tot_loss[discriminator_loss=2.727, discriminator_real_loss=1.367, discriminator_fake_loss=1.36, generator_loss=27.83, generator_mel_loss=18.08, generator_kl_loss=1.449, generator_dur_loss=1.74, generator_adv_loss=1.92, generator_feat_match_loss=4.64, over 701.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 23:31:50,204 INFO [train.py:527] (2/6) Epoch 463, batch 62, global_batch_idx: 57350, batch size: 96, loss[discriminator_loss=2.72, discriminator_real_loss=1.258, discriminator_fake_loss=1.462, generator_loss=29.04, generator_mel_loss=18.54, generator_kl_loss=1.376, generator_dur_loss=1.833, generator_adv_loss=2.051, generator_feat_match_loss=5.233, over 96.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.374, discriminator_fake_loss=1.342, generator_loss=28.01, generator_mel_loss=18.06, generator_kl_loss=1.388, generator_dur_loss=1.754, generator_adv_loss=1.954, generator_feat_match_loss=4.852, over 3497.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 23:34:12,351 INFO [train.py:527] (2/6) Epoch 463, batch 112, global_batch_idx: 57400, batch size: 25, loss[discriminator_loss=2.757, discriminator_real_loss=1.372, discriminator_fake_loss=1.385, generator_loss=28.15, generator_mel_loss=19.01, generator_kl_loss=1.691, generator_dur_loss=1.605, generator_adv_loss=1.873, generator_feat_match_loss=3.977, over 25.00 samples.], tot_loss[discriminator_loss=2.723, discriminator_real_loss=1.377, discriminator_fake_loss=1.346, generator_loss=28, generator_mel_loss=18.07, generator_kl_loss=1.394, generator_dur_loss=1.76, generator_adv_loss=1.947, generator_feat_match_loss=4.826, over 6433.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 23:34:12,353 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 23:34:21,113 INFO [train.py:591] (2/6) Epoch 463, validation: discriminator_loss=2.716, discriminator_real_loss=1.355, discriminator_fake_loss=1.361, generator_loss=26.53, generator_mel_loss=17.99, generator_kl_loss=1.175, generator_dur_loss=1.819, generator_adv_loss=1.822, generator_feat_match_loss=3.73, over 100.00 samples.
2024-03-13 23:34:21,114 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 23:34:55,019 INFO [train.py:919] (2/6) Start epoch 464
2024-03-13 23:37:06,131 INFO [train.py:527] (2/6) Epoch 464, batch 38, global_batch_idx: 57450, batch size: 80, loss[discriminator_loss=2.718, discriminator_real_loss=1.414, discriminator_fake_loss=1.304, generator_loss=27.83, generator_mel_loss=17.99, generator_kl_loss=1.423, generator_dur_loss=1.795, generator_adv_loss=1.811, generator_feat_match_loss=4.811, over 80.00 samples.], tot_loss[discriminator_loss=2.713, discriminator_real_loss=1.366, discriminator_fake_loss=1.348, generator_loss=27.9, generator_mel_loss=18.04, generator_kl_loss=1.414, generator_dur_loss=1.769, generator_adv_loss=1.944, generator_feat_match_loss=4.733, over 2315.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 23:39:24,456 INFO [train.py:527] (2/6) Epoch 464, batch 88, global_batch_idx: 57500, batch size: 36, loss[discriminator_loss=2.675, discriminator_real_loss=1.302, discriminator_fake_loss=1.373, generator_loss=30, generator_mel_loss=18.81, generator_kl_loss=1.621, generator_dur_loss=1.657, generator_adv_loss=1.816, generator_feat_match_loss=6.102, over 36.00 samples.], tot_loss[discriminator_loss=2.709, discriminator_real_loss=1.368, discriminator_fake_loss=1.341, generator_loss=28.03, generator_mel_loss=18.05, generator_kl_loss=1.422, generator_dur_loss=1.767, generator_adv_loss=1.953, generator_feat_match_loss=4.838, over 5095.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 23:41:04,224 INFO [train.py:919] (2/6) Start epoch 465
2024-03-13 23:42:06,793 INFO [train.py:527] (2/6) Epoch 465, batch 14, global_batch_idx: 57550, batch size: 53, loss[discriminator_loss=2.744, discriminator_real_loss=1.367, discriminator_fake_loss=1.376, generator_loss=28.26, generator_mel_loss=18.32, generator_kl_loss=1.302, generator_dur_loss=1.769, generator_adv_loss=2.085, generator_feat_match_loss=4.781, over 53.00 samples.], tot_loss[discriminator_loss=2.719, discriminator_real_loss=1.384, discriminator_fake_loss=1.335, generator_loss=27.81, generator_mel_loss=17.95, generator_kl_loss=1.398, generator_dur_loss=1.774, generator_adv_loss=1.96, generator_feat_match_loss=4.73, over 991.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 23:44:25,181 INFO [train.py:527] (2/6) Epoch 465, batch 64, global_batch_idx: 57600, batch size: 42, loss[discriminator_loss=2.701, discriminator_real_loss=1.296, discriminator_fake_loss=1.405, generator_loss=28.93, generator_mel_loss=18.77, generator_kl_loss=1.529, generator_dur_loss=1.635, generator_adv_loss=1.968, generator_feat_match_loss=5.022, over 42.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.378, discriminator_fake_loss=1.341, generator_loss=27.91, generator_mel_loss=17.95, generator_kl_loss=1.426, generator_dur_loss=1.748, generator_adv_loss=1.945, generator_feat_match_loss=4.843, over 3883.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 23:44:25,183 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 23:44:33,225 INFO [train.py:591] (2/6) Epoch 465, validation: discriminator_loss=2.722, discriminator_real_loss=1.484, discriminator_fake_loss=1.238, generator_loss=27.3, generator_mel_loss=18.26, generator_kl_loss=1.27, generator_dur_loss=1.798, generator_adv_loss=1.937, generator_feat_match_loss=4.031, over 100.00 samples.
2024-03-13 23:44:33,225 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 23:46:49,312 INFO [train.py:527] (2/6) Epoch 465, batch 114, global_batch_idx: 57650, batch size: 56, loss[discriminator_loss=2.685, discriminator_real_loss=1.416, discriminator_fake_loss=1.269, generator_loss=27.78, generator_mel_loss=18.14, generator_kl_loss=1.375, generator_dur_loss=1.732, generator_adv_loss=1.803, generator_feat_match_loss=4.725, over 56.00 samples.], tot_loss[discriminator_loss=2.719, discriminator_real_loss=1.376, discriminator_fake_loss=1.343, generator_loss=27.96, generator_mel_loss=17.99, generator_kl_loss=1.421, generator_dur_loss=1.746, generator_adv_loss=1.944, generator_feat_match_loss=4.858, over 6643.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 23:47:16,157 INFO [train.py:919] (2/6) Start epoch 466
2024-03-13 23:49:34,355 INFO [train.py:527] (2/6) Epoch 466, batch 40, global_batch_idx: 57700, batch size: 52, loss[discriminator_loss=2.739, discriminator_real_loss=1.424, discriminator_fake_loss=1.315, generator_loss=28.11, generator_mel_loss=18.59, generator_kl_loss=1.491, generator_dur_loss=1.72, generator_adv_loss=1.834, generator_feat_match_loss=4.477, over 52.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.369, discriminator_fake_loss=1.351, generator_loss=28.03, generator_mel_loss=18.04, generator_kl_loss=1.43, generator_dur_loss=1.751, generator_adv_loss=1.939, generator_feat_match_loss=4.872, over 2334.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 23:51:52,886 INFO [train.py:527] (2/6) Epoch 466, batch 90, global_batch_idx: 57750, batch size: 53, loss[discriminator_loss=2.747, discriminator_real_loss=1.359, discriminator_fake_loss=1.389, generator_loss=29.07, generator_mel_loss=18.66, generator_kl_loss=1.46, generator_dur_loss=1.642, generator_adv_loss=1.989, generator_feat_match_loss=5.324, over 53.00 samples.], tot_loss[discriminator_loss=2.718, discriminator_real_loss=1.371, discriminator_fake_loss=1.347, generator_loss=28.01, generator_mel_loss=18.05, generator_kl_loss=1.415, generator_dur_loss=1.756, generator_adv_loss=1.944, generator_feat_match_loss=4.85, over 5190.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 23:53:26,170 INFO [train.py:919] (2/6) Start epoch 467
2024-03-13 23:54:34,135 INFO [train.py:527] (2/6) Epoch 467, batch 16, global_batch_idx: 57800, batch size: 80, loss[discriminator_loss=2.681, discriminator_real_loss=1.336, discriminator_fake_loss=1.345, generator_loss=27.83, generator_mel_loss=17.85, generator_kl_loss=1.223, generator_dur_loss=1.807, generator_adv_loss=2.029, generator_feat_match_loss=4.926, over 80.00 samples.], tot_loss[discriminator_loss=2.719, discriminator_real_loss=1.367, discriminator_fake_loss=1.352, generator_loss=28.22, generator_mel_loss=18, generator_kl_loss=1.416, generator_dur_loss=1.741, generator_adv_loss=1.954, generator_feat_match_loss=5.108, over 953.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 23:54:34,137 INFO [train.py:581] (2/6) Computing validation loss
2024-03-13 23:54:42,160 INFO [train.py:591] (2/6) Epoch 467, validation: discriminator_loss=2.753, discriminator_real_loss=1.437, discriminator_fake_loss=1.316, generator_loss=27.38, generator_mel_loss=18.34, generator_kl_loss=1.376, generator_dur_loss=1.807, generator_adv_loss=1.921, generator_feat_match_loss=3.94, over 100.00 samples.
2024-03-13 23:54:42,161 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-13 23:57:00,030 INFO [train.py:527] (2/6) Epoch 467, batch 66, global_batch_idx: 57850, batch size: 17, loss[discriminator_loss=2.76, discriminator_real_loss=1.406, discriminator_fake_loss=1.354, generator_loss=30.24, generator_mel_loss=19.13, generator_kl_loss=1.826, generator_dur_loss=1.547, generator_adv_loss=1.975, generator_feat_match_loss=5.752, over 17.00 samples.], tot_loss[discriminator_loss=2.717, discriminator_real_loss=1.378, discriminator_fake_loss=1.34, generator_loss=28.01, generator_mel_loss=18.02, generator_kl_loss=1.426, generator_dur_loss=1.756, generator_adv_loss=1.947, generator_feat_match_loss=4.864, over 3658.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 23:59:19,443 INFO [train.py:527] (2/6) Epoch 467, batch 116, global_batch_idx: 57900, batch size: 45, loss[discriminator_loss=2.699, discriminator_real_loss=1.393, discriminator_fake_loss=1.306, generator_loss=27.71, generator_mel_loss=18.09, generator_kl_loss=1.435, generator_dur_loss=1.711, generator_adv_loss=1.825, generator_feat_match_loss=4.656, over 45.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.372, discriminator_fake_loss=1.343, generator_loss=28.01, generator_mel_loss=18, generator_kl_loss=1.429, generator_dur_loss=1.764, generator_adv_loss=1.942, generator_feat_match_loss=4.872, over 6531.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-13 23:59:41,497 INFO [train.py:919] (2/6) Start epoch 468
2024-03-14 00:02:04,332 INFO [train.py:527] (2/6) Epoch 468, batch 42, global_batch_idx: 57950, batch size: 52, loss[discriminator_loss=2.755, discriminator_real_loss=1.524, discriminator_fake_loss=1.23, generator_loss=27.62, generator_mel_loss=17.86, generator_kl_loss=1.449, generator_dur_loss=1.716, generator_adv_loss=1.839, generator_feat_match_loss=4.762, over 52.00 samples.], tot_loss[discriminator_loss=2.714, discriminator_real_loss=1.373, discriminator_fake_loss=1.34, generator_loss=28.05, generator_mel_loss=17.92, generator_kl_loss=1.435, generator_dur_loss=1.771, generator_adv_loss=1.957, generator_feat_match_loss=4.958, over 2505.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-14 00:04:24,944 INFO [train.py:527] (2/6) Epoch 468, batch 92, global_batch_idx: 58000, batch size: 55, loss[discriminator_loss=2.712, discriminator_real_loss=1.402, discriminator_fake_loss=1.31, generator_loss=27.79, generator_mel_loss=18.48, generator_kl_loss=1.486, generator_dur_loss=1.722, generator_adv_loss=2.049, generator_feat_match_loss=4.051, over 55.00 samples.], tot_loss[discriminator_loss=2.712, discriminator_real_loss=1.373, discriminator_fake_loss=1.338, generator_loss=27.97, generator_mel_loss=17.94, generator_kl_loss=1.44, generator_dur_loss=1.759, generator_adv_loss=1.96, generator_feat_match_loss=4.872, over 5342.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-14 00:04:24,946 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 00:04:34,034 INFO [train.py:591] (2/6) Epoch 468, validation: discriminator_loss=2.717, discriminator_real_loss=1.497, discriminator_fake_loss=1.219, generator_loss=28.21, generator_mel_loss=18.77, generator_kl_loss=1.172, generator_dur_loss=1.832, generator_adv_loss=2.018, generator_feat_match_loss=4.414, over 100.00 samples.
2024-03-14 00:04:34,035 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 00:05:57,588 INFO [train.py:919] (2/6) Start epoch 469
2024-03-14 00:07:12,699 INFO [train.py:527] (2/6) Epoch 469, batch 18, global_batch_idx: 58050, batch size: 48, loss[discriminator_loss=2.817, discriminator_real_loss=1.361, discriminator_fake_loss=1.456, generator_loss=28.24, generator_mel_loss=17.77, generator_kl_loss=1.689, generator_dur_loss=1.681, generator_adv_loss=2.119, generator_feat_match_loss=4.976, over 48.00 samples.], tot_loss[discriminator_loss=2.734, discriminator_real_loss=1.381, discriminator_fake_loss=1.353, generator_loss=28.05, generator_mel_loss=18.05, generator_kl_loss=1.408, generator_dur_loss=1.779, generator_adv_loss=1.946, generator_feat_match_loss=4.861, over 1102.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-14 00:09:35,761 INFO [train.py:527] (2/6) Epoch 469, batch 68, global_batch_idx: 58100, batch size: 68, loss[discriminator_loss=2.663, discriminator_real_loss=1.362, discriminator_fake_loss=1.301, generator_loss=28.44, generator_mel_loss=17.92, generator_kl_loss=1.366, generator_dur_loss=1.809, generator_adv_loss=1.978, generator_feat_match_loss=5.373, over 68.00 samples.], tot_loss[discriminator_loss=2.734, discriminator_real_loss=1.386, discriminator_fake_loss=1.347, generator_loss=27.92, generator_mel_loss=17.98, generator_kl_loss=1.397, generator_dur_loss=1.774, generator_adv_loss=1.936, generator_feat_match_loss=4.837, over 4179.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-14 00:11:56,350 INFO [train.py:527] (2/6) Epoch 469, batch 118, global_batch_idx: 58150, batch size: 42, loss[discriminator_loss=2.658, discriminator_real_loss=1.3, discriminator_fake_loss=1.357, generator_loss=28.53, generator_mel_loss=17.97, generator_kl_loss=1.498, generator_dur_loss=1.71, generator_adv_loss=2.1, generator_feat_match_loss=5.248, over 42.00 samples.], tot_loss[discriminator_loss=2.723, discriminator_real_loss=1.377, discriminator_fake_loss=1.346, generator_loss=28.03, generator_mel_loss=18.02, generator_kl_loss=1.401, generator_dur_loss=1.773, generator_adv_loss=1.936, generator_feat_match_loss=4.903, over 7031.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-14 00:12:10,189 INFO [train.py:919] (2/6) Start epoch 470
2024-03-14 00:14:36,350 INFO [train.py:527] (2/6) Epoch 470, batch 44, global_batch_idx: 58200, batch size: 61, loss[discriminator_loss=2.632, discriminator_real_loss=1.321, discriminator_fake_loss=1.31, generator_loss=28.03, generator_mel_loss=17.79, generator_kl_loss=1.328, generator_dur_loss=1.79, generator_adv_loss=2.053, generator_feat_match_loss=5.06, over 61.00 samples.], tot_loss[discriminator_loss=2.708, discriminator_real_loss=1.367, discriminator_fake_loss=1.341, generator_loss=28.01, generator_mel_loss=17.94, generator_kl_loss=1.422, generator_dur_loss=1.768, generator_adv_loss=1.941, generator_feat_match_loss=4.941, over 2598.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-14 00:14:36,352 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 00:14:44,173 INFO [train.py:591] (2/6) Epoch 470, validation: discriminator_loss=2.713, discriminator_real_loss=1.448, discriminator_fake_loss=1.264, generator_loss=27.15, generator_mel_loss=18.23, generator_kl_loss=1.214, generator_dur_loss=1.836, generator_adv_loss=1.973, generator_feat_match_loss=3.9, over 100.00 samples.
2024-03-14 00:14:44,174 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 00:17:05,872 INFO [train.py:527] (2/6) Epoch 470, batch 94, global_batch_idx: 58250, batch size: 70, loss[discriminator_loss=2.665, discriminator_real_loss=1.444, discriminator_fake_loss=1.221, generator_loss=27.8, generator_mel_loss=18.22, generator_kl_loss=1.217, generator_dur_loss=1.837, generator_adv_loss=1.799, generator_feat_match_loss=4.73, over 70.00 samples.], tot_loss[discriminator_loss=2.708, discriminator_real_loss=1.369, discriminator_fake_loss=1.339, generator_loss=27.96, generator_mel_loss=17.95, generator_kl_loss=1.4, generator_dur_loss=1.776, generator_adv_loss=1.94, generator_feat_match_loss=4.903, over 5584.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-14 00:18:32,269 INFO [train.py:919] (2/6) Start epoch 471
2024-03-14 00:19:56,191 INFO [train.py:527] (2/6) Epoch 471, batch 20, global_batch_idx: 58300, batch size: 66, loss[discriminator_loss=2.692, discriminator_real_loss=1.361, discriminator_fake_loss=1.331, generator_loss=28.19, generator_mel_loss=18.14, generator_kl_loss=1.328, generator_dur_loss=1.787, generator_adv_loss=1.957, generator_feat_match_loss=4.971, over 66.00 samples.], tot_loss[discriminator_loss=2.714, discriminator_real_loss=1.376, discriminator_fake_loss=1.338, generator_loss=28.09, generator_mel_loss=17.98, generator_kl_loss=1.397, generator_dur_loss=1.782, generator_adv_loss=1.942, generator_feat_match_loss=4.99, over 1376.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-14 00:22:19,689 INFO [train.py:527] (2/6) Epoch 471, batch 70, global_batch_idx: 58350, batch size: 53, loss[discriminator_loss=2.708, discriminator_real_loss=1.421, discriminator_fake_loss=1.287, generator_loss=28.87, generator_mel_loss=18.48, generator_kl_loss=1.532, generator_dur_loss=1.696, generator_adv_loss=2.049, generator_feat_match_loss=5.118, over 53.00 samples.], tot_loss[discriminator_loss=2.718, discriminator_real_loss=1.379, discriminator_fake_loss=1.339, generator_loss=28.03, generator_mel_loss=18.01, generator_kl_loss=1.409, generator_dur_loss=1.768, generator_adv_loss=1.954, generator_feat_match_loss=4.885, over 4335.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-14 00:24:37,728 INFO [train.py:527] (2/6) Epoch 471, batch 120, global_batch_idx: 58400, batch size: 58, loss[discriminator_loss=2.716, discriminator_real_loss=1.396, discriminator_fake_loss=1.32, generator_loss=27.85, generator_mel_loss=18.1, generator_kl_loss=1.389, generator_dur_loss=1.769, generator_adv_loss=1.784, generator_feat_match_loss=4.802, over 58.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.374, discriminator_fake_loss=1.342, generator_loss=28.07, generator_mel_loss=18.03, generator_kl_loss=1.404, generator_dur_loss=1.763, generator_adv_loss=1.946, generator_feat_match_loss=4.927, over 7141.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-14 00:24:37,730 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 00:24:46,223 INFO [train.py:591] (2/6) Epoch 471, validation: discriminator_loss=2.756, discriminator_real_loss=1.348, discriminator_fake_loss=1.408, generator_loss=26.82, generator_mel_loss=18.25, generator_kl_loss=1.196, generator_dur_loss=1.841, generator_adv_loss=1.775, generator_feat_match_loss=3.765, over 100.00 samples.
2024-03-14 00:24:46,224 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 00:24:55,076 INFO [train.py:919] (2/6) Start epoch 472
2024-03-14 00:27:26,516 INFO [train.py:527] (2/6) Epoch 472, batch 46, global_batch_idx: 58450, batch size: 56, loss[discriminator_loss=2.678, discriminator_real_loss=1.279, discriminator_fake_loss=1.399, generator_loss=28.18, generator_mel_loss=18.16, generator_kl_loss=1.279, generator_dur_loss=1.737, generator_adv_loss=2.033, generator_feat_match_loss=4.977, over 56.00 samples.], tot_loss[discriminator_loss=2.714, discriminator_real_loss=1.374, discriminator_fake_loss=1.34, generator_loss=28.05, generator_mel_loss=18.07, generator_kl_loss=1.433, generator_dur_loss=1.741, generator_adv_loss=1.94, generator_feat_match_loss=4.86, over 2515.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-14 00:29:48,970 INFO [train.py:527] (2/6) Epoch 472, batch 96, global_batch_idx: 58500, batch size: 96, loss[discriminator_loss=2.736, discriminator_real_loss=1.246, discriminator_fake_loss=1.49, generator_loss=27.77, generator_mel_loss=17.59, generator_kl_loss=1.326, generator_dur_loss=1.812, generator_adv_loss=2.127, generator_feat_match_loss=4.909, over 96.00 samples.], tot_loss[discriminator_loss=2.718, discriminator_real_loss=1.374, discriminator_fake_loss=1.344, generator_loss=28.03, generator_mel_loss=18.01, generator_kl_loss=1.42, generator_dur_loss=1.743, generator_adv_loss=1.948, generator_feat_match_loss=4.913, over 5403.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-14 00:31:07,666 INFO [train.py:919] (2/6) Start epoch 473
2024-03-14 00:32:34,968 INFO [train.py:527] (2/6) Epoch 473, batch 22, global_batch_idx: 58550, batch size: 25, loss[discriminator_loss=2.688, discriminator_real_loss=1.361, discriminator_fake_loss=1.327, generator_loss=29.19, generator_mel_loss=18.27, generator_kl_loss=1.7, generator_dur_loss=1.56, generator_adv_loss=1.896, generator_feat_match_loss=5.759, over 25.00 samples.], tot_loss[discriminator_loss=2.729, discriminator_real_loss=1.384, discriminator_fake_loss=1.344, generator_loss=28.14, generator_mel_loss=18.09, generator_kl_loss=1.45, generator_dur_loss=1.735, generator_adv_loss=1.946, generator_feat_match_loss=4.917, over 1277.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-14 00:34:57,248 INFO [train.py:527] (2/6) Epoch 473, batch 72, global_batch_idx: 58600, batch size: 44, loss[discriminator_loss=2.684, discriminator_real_loss=1.399, discriminator_fake_loss=1.285, generator_loss=27.39, generator_mel_loss=17.54, generator_kl_loss=1.523, generator_dur_loss=1.672, generator_adv_loss=1.773, generator_feat_match_loss=4.875, over 44.00 samples.], tot_loss[discriminator_loss=2.729, discriminator_real_loss=1.375, discriminator_fake_loss=1.355, generator_loss=28.11, generator_mel_loss=18.03, generator_kl_loss=1.446, generator_dur_loss=1.736, generator_adv_loss=1.958, generator_feat_match_loss=4.942, over 3873.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-14 00:34:57,250 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 00:35:05,378 INFO [train.py:591] (2/6) Epoch 473, validation: discriminator_loss=2.796, discriminator_real_loss=1.353, discriminator_fake_loss=1.442, generator_loss=26.19, generator_mel_loss=17.77, generator_kl_loss=1.184, generator_dur_loss=1.819, generator_adv_loss=1.691, generator_feat_match_loss=3.723, over 100.00 samples.
2024-03-14 00:35:05,378 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 00:37:25,851 INFO [train.py:527] (2/6) Epoch 473, batch 122, global_batch_idx: 58650, batch size: 72, loss[discriminator_loss=2.694, discriminator_real_loss=1.38, discriminator_fake_loss=1.315, generator_loss=28.38, generator_mel_loss=18.08, generator_kl_loss=1.437, generator_dur_loss=1.843, generator_adv_loss=2.078, generator_feat_match_loss=4.94, over 72.00 samples.], tot_loss[discriminator_loss=2.722, discriminator_real_loss=1.378, discriminator_fake_loss=1.344, generator_loss=28.11, generator_mel_loss=18.03, generator_kl_loss=1.418, generator_dur_loss=1.75, generator_adv_loss=1.954, generator_feat_match_loss=4.96, over 6781.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-14 00:37:30,548 INFO [train.py:919] (2/6) Start epoch 474
2024-03-14 00:40:13,570 INFO [train.py:527] (2/6) Epoch 474, batch 48, global_batch_idx: 58700, batch size: 68, loss[discriminator_loss=2.727, discriminator_real_loss=1.363, discriminator_fake_loss=1.365, generator_loss=28.07, generator_mel_loss=17.73, generator_kl_loss=1.364, generator_dur_loss=1.794, generator_adv_loss=2.137, generator_feat_match_loss=5.053, over 68.00 samples.], tot_loss[discriminator_loss=2.718, discriminator_real_loss=1.375, discriminator_fake_loss=1.343, generator_loss=28.19, generator_mel_loss=18.09, generator_kl_loss=1.414, generator_dur_loss=1.761, generator_adv_loss=1.947, generator_feat_match_loss=4.976, over 2772.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-14 00:42:34,311 INFO [train.py:527] (2/6) Epoch 474, batch 98, global_batch_idx: 58750, batch size: 53, loss[discriminator_loss=2.678, discriminator_real_loss=1.296, discriminator_fake_loss=1.382, generator_loss=28.75, generator_mel_loss=18.14, generator_kl_loss=1.508, generator_dur_loss=1.657, generator_adv_loss=2.001, generator_feat_match_loss=5.446, over 53.00 samples.], tot_loss[discriminator_loss=2.723, discriminator_real_loss=1.376, discriminator_fake_loss=1.347, generator_loss=28.1, generator_mel_loss=18.06, generator_kl_loss=1.418, generator_dur_loss=1.761, generator_adv_loss=1.938, generator_feat_match_loss=4.923, over 5657.00 samples.], cur_lr_g: 1.89e-04, cur_lr_d: 1.89e-04, 
2024-03-14 00:43:48,590 INFO [train.py:919] (2/6) Start epoch 475
2024-03-14 00:45:23,518 INFO [train.py:527] (2/6) Epoch 475, batch 24, global_batch_idx: 58800, batch size: 52, loss[discriminator_loss=2.823, discriminator_real_loss=1.45, discriminator_fake_loss=1.374, generator_loss=27.85, generator_mel_loss=17.78, generator_kl_loss=1.368, generator_dur_loss=1.717, generator_adv_loss=1.879, generator_feat_match_loss=5.103, over 52.00 samples.], tot_loss[discriminator_loss=2.722, discriminator_real_loss=1.367, discriminator_fake_loss=1.356, generator_loss=28.04, generator_mel_loss=18.01, generator_kl_loss=1.38, generator_dur_loss=1.79, generator_adv_loss=1.93, generator_feat_match_loss=4.925, over 1634.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 00:45:23,520 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 00:45:31,209 INFO [train.py:591] (2/6) Epoch 475, validation: discriminator_loss=2.769, discriminator_real_loss=1.347, discriminator_fake_loss=1.422, generator_loss=26.55, generator_mel_loss=18.26, generator_kl_loss=1.245, generator_dur_loss=1.828, generator_adv_loss=1.754, generator_feat_match_loss=3.463, over 100.00 samples.
2024-03-14 00:45:31,210 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 00:47:52,132 INFO [train.py:527] (2/6) Epoch 475, batch 74, global_batch_idx: 58850, batch size: 14, loss[discriminator_loss=2.621, discriminator_real_loss=1.328, discriminator_fake_loss=1.293, generator_loss=28.72, generator_mel_loss=18.53, generator_kl_loss=1.501, generator_dur_loss=1.611, generator_adv_loss=2.007, generator_feat_match_loss=5.07, over 14.00 samples.], tot_loss[discriminator_loss=2.723, discriminator_real_loss=1.373, discriminator_fake_loss=1.35, generator_loss=27.92, generator_mel_loss=17.97, generator_kl_loss=1.385, generator_dur_loss=1.765, generator_adv_loss=1.933, generator_feat_match_loss=4.869, over 4672.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 00:50:09,606 INFO [train.py:919] (2/6) Start epoch 476
2024-03-14 00:50:34,901 INFO [train.py:527] (2/6) Epoch 476, batch 0, global_batch_idx: 58900, batch size: 52, loss[discriminator_loss=2.684, discriminator_real_loss=1.329, discriminator_fake_loss=1.355, generator_loss=28.07, generator_mel_loss=18.22, generator_kl_loss=1.397, generator_dur_loss=1.701, generator_adv_loss=1.973, generator_feat_match_loss=4.781, over 52.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.329, discriminator_fake_loss=1.355, generator_loss=28.07, generator_mel_loss=18.22, generator_kl_loss=1.397, generator_dur_loss=1.701, generator_adv_loss=1.973, generator_feat_match_loss=4.781, over 52.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 00:52:59,220 INFO [train.py:527] (2/6) Epoch 476, batch 50, global_batch_idx: 58950, batch size: 47, loss[discriminator_loss=2.703, discriminator_real_loss=1.423, discriminator_fake_loss=1.279, generator_loss=27.57, generator_mel_loss=17.87, generator_kl_loss=1.618, generator_dur_loss=1.713, generator_adv_loss=1.845, generator_feat_match_loss=4.521, over 47.00 samples.], tot_loss[discriminator_loss=2.7, discriminator_real_loss=1.369, discriminator_fake_loss=1.331, generator_loss=28.16, generator_mel_loss=18.02, generator_kl_loss=1.406, generator_dur_loss=1.766, generator_adv_loss=1.947, generator_feat_match_loss=5.018, over 2989.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 00:55:19,642 INFO [train.py:527] (2/6) Epoch 476, batch 100, global_batch_idx: 59000, batch size: 64, loss[discriminator_loss=2.712, discriminator_real_loss=1.454, discriminator_fake_loss=1.258, generator_loss=28.34, generator_mel_loss=18.67, generator_kl_loss=1.362, generator_dur_loss=1.768, generator_adv_loss=1.894, generator_feat_match_loss=4.651, over 64.00 samples.], tot_loss[discriminator_loss=2.707, discriminator_real_loss=1.371, discriminator_fake_loss=1.336, generator_loss=28.11, generator_mel_loss=17.99, generator_kl_loss=1.407, generator_dur_loss=1.76, generator_adv_loss=1.966, generator_feat_match_loss=4.98, over 5781.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 00:55:19,644 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 00:55:28,426 INFO [train.py:591] (2/6) Epoch 476, validation: discriminator_loss=2.743, discriminator_real_loss=1.426, discriminator_fake_loss=1.317, generator_loss=26.56, generator_mel_loss=18.08, generator_kl_loss=1.197, generator_dur_loss=1.79, generator_adv_loss=1.856, generator_feat_match_loss=3.641, over 100.00 samples.
2024-03-14 00:55:28,427 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 00:56:31,384 INFO [train.py:919] (2/6) Start epoch 477
2024-03-14 00:58:09,187 INFO [train.py:527] (2/6) Epoch 477, batch 26, global_batch_idx: 59050, batch size: 64, loss[discriminator_loss=2.75, discriminator_real_loss=1.458, discriminator_fake_loss=1.291, generator_loss=27.53, generator_mel_loss=17.75, generator_kl_loss=1.359, generator_dur_loss=1.776, generator_adv_loss=1.858, generator_feat_match_loss=4.792, over 64.00 samples.], tot_loss[discriminator_loss=2.714, discriminator_real_loss=1.385, discriminator_fake_loss=1.329, generator_loss=28.04, generator_mel_loss=18.01, generator_kl_loss=1.413, generator_dur_loss=1.739, generator_adv_loss=1.948, generator_feat_match_loss=4.928, over 1492.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 01:00:33,456 INFO [train.py:527] (2/6) Epoch 477, batch 76, global_batch_idx: 59100, batch size: 74, loss[discriminator_loss=2.749, discriminator_real_loss=1.341, discriminator_fake_loss=1.408, generator_loss=27.41, generator_mel_loss=18.04, generator_kl_loss=1.254, generator_dur_loss=1.818, generator_adv_loss=1.953, generator_feat_match_loss=4.344, over 74.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.378, discriminator_fake_loss=1.337, generator_loss=28.01, generator_mel_loss=17.97, generator_kl_loss=1.406, generator_dur_loss=1.752, generator_adv_loss=1.946, generator_feat_match_loss=4.935, over 4502.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 01:02:41,812 INFO [train.py:919] (2/6) Start epoch 478
2024-03-14 01:03:10,992 INFO [train.py:527] (2/6) Epoch 478, batch 2, global_batch_idx: 59150, batch size: 45, loss[discriminator_loss=2.817, discriminator_real_loss=1.64, discriminator_fake_loss=1.177, generator_loss=28.98, generator_mel_loss=18.76, generator_kl_loss=1.415, generator_dur_loss=1.69, generator_adv_loss=1.999, generator_feat_match_loss=5.117, over 45.00 samples.], tot_loss[discriminator_loss=2.84, discriminator_real_loss=1.506, discriminator_fake_loss=1.334, generator_loss=28.19, generator_mel_loss=18.42, generator_kl_loss=1.428, generator_dur_loss=1.699, generator_adv_loss=1.963, generator_feat_match_loss=4.685, over 154.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 01:05:34,169 INFO [train.py:527] (2/6) Epoch 478, batch 52, global_batch_idx: 59200, batch size: 53, loss[discriminator_loss=2.621, discriminator_real_loss=1.341, discriminator_fake_loss=1.28, generator_loss=28.35, generator_mel_loss=17.72, generator_kl_loss=1.298, generator_dur_loss=1.719, generator_adv_loss=1.991, generator_feat_match_loss=5.626, over 53.00 samples.], tot_loss[discriminator_loss=2.727, discriminator_real_loss=1.383, discriminator_fake_loss=1.343, generator_loss=27.92, generator_mel_loss=18, generator_kl_loss=1.394, generator_dur_loss=1.751, generator_adv_loss=1.934, generator_feat_match_loss=4.84, over 3032.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 01:05:34,171 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 01:05:41,916 INFO [train.py:591] (2/6) Epoch 478, validation: discriminator_loss=2.71, discriminator_real_loss=1.383, discriminator_fake_loss=1.327, generator_loss=27.1, generator_mel_loss=18.43, generator_kl_loss=1.199, generator_dur_loss=1.801, generator_adv_loss=1.869, generator_feat_match_loss=3.803, over 100.00 samples.
2024-03-14 01:05:41,917 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 01:08:05,676 INFO [train.py:527] (2/6) Epoch 478, batch 102, global_batch_idx: 59250, batch size: 44, loss[discriminator_loss=2.679, discriminator_real_loss=1.297, discriminator_fake_loss=1.382, generator_loss=29.75, generator_mel_loss=18.57, generator_kl_loss=1.675, generator_dur_loss=1.669, generator_adv_loss=2.013, generator_feat_match_loss=5.82, over 44.00 samples.], tot_loss[discriminator_loss=2.721, discriminator_real_loss=1.377, discriminator_fake_loss=1.344, generator_loss=28, generator_mel_loss=18.01, generator_kl_loss=1.411, generator_dur_loss=1.755, generator_adv_loss=1.937, generator_feat_match_loss=4.884, over 5778.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 01:09:04,810 INFO [train.py:919] (2/6) Start epoch 479
2024-03-14 01:10:51,330 INFO [train.py:527] (2/6) Epoch 479, batch 28, global_batch_idx: 59300, batch size: 70, loss[discriminator_loss=2.711, discriminator_real_loss=1.338, discriminator_fake_loss=1.372, generator_loss=28.2, generator_mel_loss=17.93, generator_kl_loss=1.378, generator_dur_loss=1.797, generator_adv_loss=2.041, generator_feat_match_loss=5.051, over 70.00 samples.], tot_loss[discriminator_loss=2.714, discriminator_real_loss=1.364, discriminator_fake_loss=1.35, generator_loss=28.12, generator_mel_loss=18, generator_kl_loss=1.444, generator_dur_loss=1.75, generator_adv_loss=1.956, generator_feat_match_loss=4.977, over 1618.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 01:13:13,902 INFO [train.py:527] (2/6) Epoch 479, batch 78, global_batch_idx: 59350, batch size: 66, loss[discriminator_loss=2.731, discriminator_real_loss=1.35, discriminator_fake_loss=1.38, generator_loss=28.54, generator_mel_loss=18.05, generator_kl_loss=1.467, generator_dur_loss=1.759, generator_adv_loss=1.913, generator_feat_match_loss=5.356, over 66.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.372, discriminator_fake_loss=1.343, generator_loss=28.04, generator_mel_loss=17.99, generator_kl_loss=1.418, generator_dur_loss=1.76, generator_adv_loss=1.959, generator_feat_match_loss=4.915, over 4570.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 01:15:20,656 INFO [train.py:919] (2/6) Start epoch 480
2024-03-14 01:15:56,134 INFO [train.py:527] (2/6) Epoch 480, batch 4, global_batch_idx: 59400, batch size: 72, loss[discriminator_loss=2.751, discriminator_real_loss=1.367, discriminator_fake_loss=1.384, generator_loss=28.19, generator_mel_loss=18.03, generator_kl_loss=1.483, generator_dur_loss=1.84, generator_adv_loss=2.027, generator_feat_match_loss=4.809, over 72.00 samples.], tot_loss[discriminator_loss=2.738, discriminator_real_loss=1.38, discriminator_fake_loss=1.358, generator_loss=28.18, generator_mel_loss=18.01, generator_kl_loss=1.412, generator_dur_loss=1.769, generator_adv_loss=1.945, generator_feat_match_loss=5.049, over 314.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 01:15:56,137 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 01:16:03,715 INFO [train.py:591] (2/6) Epoch 480, validation: discriminator_loss=2.809, discriminator_real_loss=1.507, discriminator_fake_loss=1.302, generator_loss=27.04, generator_mel_loss=18.29, generator_kl_loss=1.284, generator_dur_loss=1.825, generator_adv_loss=1.928, generator_feat_match_loss=3.717, over 100.00 samples.
2024-03-14 01:16:03,717 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 01:18:25,500 INFO [train.py:527] (2/6) Epoch 480, batch 54, global_batch_idx: 59450, batch size: 55, loss[discriminator_loss=2.615, discriminator_real_loss=1.325, discriminator_fake_loss=1.29, generator_loss=28.46, generator_mel_loss=17.93, generator_kl_loss=1.485, generator_dur_loss=1.74, generator_adv_loss=2.148, generator_feat_match_loss=5.159, over 55.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.373, discriminator_fake_loss=1.346, generator_loss=28.15, generator_mel_loss=17.97, generator_kl_loss=1.414, generator_dur_loss=1.757, generator_adv_loss=1.972, generator_feat_match_loss=5.038, over 3244.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 01:20:46,714 INFO [train.py:527] (2/6) Epoch 480, batch 104, global_batch_idx: 59500, batch size: 53, loss[discriminator_loss=2.665, discriminator_real_loss=1.377, discriminator_fake_loss=1.288, generator_loss=28.14, generator_mel_loss=18.25, generator_kl_loss=1.379, generator_dur_loss=1.72, generator_adv_loss=1.979, generator_feat_match_loss=4.809, over 53.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.376, discriminator_fake_loss=1.339, generator_loss=28.1, generator_mel_loss=17.98, generator_kl_loss=1.416, generator_dur_loss=1.754, generator_adv_loss=1.968, generator_feat_match_loss=4.982, over 5936.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 01:21:42,599 INFO [train.py:919] (2/6) Start epoch 481
2024-03-14 01:23:35,343 INFO [train.py:527] (2/6) Epoch 481, batch 30, global_batch_idx: 59550, batch size: 62, loss[discriminator_loss=2.735, discriminator_real_loss=1.396, discriminator_fake_loss=1.339, generator_loss=27.53, generator_mel_loss=17.59, generator_kl_loss=1.403, generator_dur_loss=1.717, generator_adv_loss=2.085, generator_feat_match_loss=4.732, over 62.00 samples.], tot_loss[discriminator_loss=2.722, discriminator_real_loss=1.364, discriminator_fake_loss=1.359, generator_loss=28.18, generator_mel_loss=18.1, generator_kl_loss=1.414, generator_dur_loss=1.769, generator_adv_loss=1.949, generator_feat_match_loss=4.951, over 1770.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 01:26:00,094 INFO [train.py:527] (2/6) Epoch 481, batch 80, global_batch_idx: 59600, batch size: 70, loss[discriminator_loss=2.739, discriminator_real_loss=1.362, discriminator_fake_loss=1.377, generator_loss=28.41, generator_mel_loss=18.28, generator_kl_loss=1.269, generator_dur_loss=1.84, generator_adv_loss=1.919, generator_feat_match_loss=5.1, over 70.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.365, discriminator_fake_loss=1.351, generator_loss=28.08, generator_mel_loss=18.03, generator_kl_loss=1.377, generator_dur_loss=1.759, generator_adv_loss=1.952, generator_feat_match_loss=4.969, over 4659.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 01:26:00,095 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 01:26:08,545 INFO [train.py:591] (2/6) Epoch 481, validation: discriminator_loss=2.778, discriminator_real_loss=1.453, discriminator_fake_loss=1.325, generator_loss=26.79, generator_mel_loss=18.06, generator_kl_loss=1.274, generator_dur_loss=1.817, generator_adv_loss=1.858, generator_feat_match_loss=3.779, over 100.00 samples.
2024-03-14 01:26:08,546 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 01:28:08,657 INFO [train.py:919] (2/6) Start epoch 482
2024-03-14 01:28:50,730 INFO [train.py:527] (2/6) Epoch 482, batch 6, global_batch_idx: 59650, batch size: 77, loss[discriminator_loss=2.692, discriminator_real_loss=1.373, discriminator_fake_loss=1.318, generator_loss=28.37, generator_mel_loss=17.96, generator_kl_loss=1.381, generator_dur_loss=1.812, generator_adv_loss=1.85, generator_feat_match_loss=5.368, over 77.00 samples.], tot_loss[discriminator_loss=2.74, discriminator_real_loss=1.394, discriminator_fake_loss=1.345, generator_loss=28.34, generator_mel_loss=17.99, generator_kl_loss=1.378, generator_dur_loss=1.759, generator_adv_loss=1.989, generator_feat_match_loss=5.22, over 464.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 01:31:11,799 INFO [train.py:527] (2/6) Epoch 482, batch 56, global_batch_idx: 59700, batch size: 66, loss[discriminator_loss=2.687, discriminator_real_loss=1.377, discriminator_fake_loss=1.31, generator_loss=28.35, generator_mel_loss=17.9, generator_kl_loss=1.441, generator_dur_loss=1.771, generator_adv_loss=2.009, generator_feat_match_loss=5.23, over 66.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.38, discriminator_fake_loss=1.34, generator_loss=28.08, generator_mel_loss=17.98, generator_kl_loss=1.422, generator_dur_loss=1.751, generator_adv_loss=1.963, generator_feat_match_loss=4.958, over 3240.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 01:33:31,839 INFO [train.py:527] (2/6) Epoch 482, batch 106, global_batch_idx: 59750, batch size: 42, loss[discriminator_loss=2.671, discriminator_real_loss=1.375, discriminator_fake_loss=1.296, generator_loss=28.29, generator_mel_loss=17.94, generator_kl_loss=1.484, generator_dur_loss=1.705, generator_adv_loss=1.897, generator_feat_match_loss=5.265, over 42.00 samples.], tot_loss[discriminator_loss=2.717, discriminator_real_loss=1.376, discriminator_fake_loss=1.341, generator_loss=28.06, generator_mel_loss=17.97, generator_kl_loss=1.42, generator_dur_loss=1.757, generator_adv_loss=1.956, generator_feat_match_loss=4.955, over 6164.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 01:34:23,946 INFO [train.py:919] (2/6) Start epoch 483
2024-03-14 01:36:18,606 INFO [train.py:527] (2/6) Epoch 483, batch 32, global_batch_idx: 59800, batch size: 16, loss[discriminator_loss=2.551, discriminator_real_loss=1.225, discriminator_fake_loss=1.326, generator_loss=33.84, generator_mel_loss=20.14, generator_kl_loss=1.978, generator_dur_loss=1.532, generator_adv_loss=2.451, generator_feat_match_loss=7.736, over 16.00 samples.], tot_loss[discriminator_loss=2.708, discriminator_real_loss=1.37, discriminator_fake_loss=1.338, generator_loss=28.19, generator_mel_loss=18, generator_kl_loss=1.44, generator_dur_loss=1.776, generator_adv_loss=1.952, generator_feat_match_loss=5.023, over 1975.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 01:36:18,609 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 01:36:26,623 INFO [train.py:591] (2/6) Epoch 483, validation: discriminator_loss=2.745, discriminator_real_loss=1.502, discriminator_fake_loss=1.242, generator_loss=26.89, generator_mel_loss=18.14, generator_kl_loss=1.281, generator_dur_loss=1.805, generator_adv_loss=1.944, generator_feat_match_loss=3.723, over 100.00 samples.
2024-03-14 01:36:26,624 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 01:38:50,079 INFO [train.py:527] (2/6) Epoch 483, batch 82, global_batch_idx: 59850, batch size: 55, loss[discriminator_loss=2.709, discriminator_real_loss=1.404, discriminator_fake_loss=1.306, generator_loss=27.87, generator_mel_loss=18.09, generator_kl_loss=1.397, generator_dur_loss=1.726, generator_adv_loss=1.937, generator_feat_match_loss=4.723, over 55.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.373, discriminator_fake_loss=1.342, generator_loss=28.13, generator_mel_loss=18.04, generator_kl_loss=1.427, generator_dur_loss=1.775, generator_adv_loss=1.945, generator_feat_match_loss=4.943, over 4953.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 01:40:45,648 INFO [train.py:919] (2/6) Start epoch 484
2024-03-14 01:41:33,078 INFO [train.py:527] (2/6) Epoch 484, batch 8, global_batch_idx: 59900, batch size: 36, loss[discriminator_loss=2.688, discriminator_real_loss=1.453, discriminator_fake_loss=1.235, generator_loss=27.59, generator_mel_loss=17.64, generator_kl_loss=1.613, generator_dur_loss=1.707, generator_adv_loss=2.08, generator_feat_match_loss=4.558, over 36.00 samples.], tot_loss[discriminator_loss=2.703, discriminator_real_loss=1.391, discriminator_fake_loss=1.311, generator_loss=27.91, generator_mel_loss=17.9, generator_kl_loss=1.354, generator_dur_loss=1.787, generator_adv_loss=1.987, generator_feat_match_loss=4.882, over 555.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 01:43:54,263 INFO [train.py:527] (2/6) Epoch 484, batch 58, global_batch_idx: 59950, batch size: 49, loss[discriminator_loss=2.725, discriminator_real_loss=1.372, discriminator_fake_loss=1.353, generator_loss=28.71, generator_mel_loss=17.94, generator_kl_loss=1.511, generator_dur_loss=1.686, generator_adv_loss=2.226, generator_feat_match_loss=5.346, over 49.00 samples.], tot_loss[discriminator_loss=2.707, discriminator_real_loss=1.37, discriminator_fake_loss=1.337, generator_loss=28.14, generator_mel_loss=18, generator_kl_loss=1.425, generator_dur_loss=1.769, generator_adv_loss=1.961, generator_feat_match_loss=4.991, over 3465.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 01:46:14,330 INFO [train.py:527] (2/6) Epoch 484, batch 108, global_batch_idx: 60000, batch size: 74, loss[discriminator_loss=2.68, discriminator_real_loss=1.297, discriminator_fake_loss=1.384, generator_loss=29.07, generator_mel_loss=18.82, generator_kl_loss=1.352, generator_dur_loss=1.836, generator_adv_loss=1.786, generator_feat_match_loss=5.271, over 74.00 samples.], tot_loss[discriminator_loss=2.711, discriminator_real_loss=1.368, discriminator_fake_loss=1.344, generator_loss=28.19, generator_mel_loss=18.04, generator_kl_loss=1.426, generator_dur_loss=1.76, generator_adv_loss=1.958, generator_feat_match_loss=5, over 6064.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 01:46:14,332 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 01:46:22,958 INFO [train.py:591] (2/6) Epoch 484, validation: discriminator_loss=2.761, discriminator_real_loss=1.313, discriminator_fake_loss=1.447, generator_loss=26.9, generator_mel_loss=18.08, generator_kl_loss=1.285, generator_dur_loss=1.83, generator_adv_loss=1.697, generator_feat_match_loss=4.007, over 100.00 samples.
2024-03-14 01:46:22,959 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 01:47:06,246 INFO [train.py:919] (2/6) Start epoch 485
2024-03-14 01:49:07,748 INFO [train.py:527] (2/6) Epoch 485, batch 34, global_batch_idx: 60050, batch size: 45, loss[discriminator_loss=2.745, discriminator_real_loss=1.32, discriminator_fake_loss=1.424, generator_loss=28.07, generator_mel_loss=17.98, generator_kl_loss=1.514, generator_dur_loss=1.652, generator_adv_loss=2, generator_feat_match_loss=4.925, over 45.00 samples.], tot_loss[discriminator_loss=2.719, discriminator_real_loss=1.375, discriminator_fake_loss=1.344, generator_loss=28.06, generator_mel_loss=17.93, generator_kl_loss=1.386, generator_dur_loss=1.772, generator_adv_loss=1.968, generator_feat_match_loss=5.004, over 2184.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 01:51:25,578 INFO [train.py:527] (2/6) Epoch 485, batch 84, global_batch_idx: 60100, batch size: 88, loss[discriminator_loss=2.73, discriminator_real_loss=1.388, discriminator_fake_loss=1.342, generator_loss=27.92, generator_mel_loss=18.24, generator_kl_loss=1.317, generator_dur_loss=1.856, generator_adv_loss=1.894, generator_feat_match_loss=4.613, over 88.00 samples.], tot_loss[discriminator_loss=2.721, discriminator_real_loss=1.376, discriminator_fake_loss=1.345, generator_loss=28.09, generator_mel_loss=18.01, generator_kl_loss=1.408, generator_dur_loss=1.757, generator_adv_loss=1.96, generator_feat_match_loss=4.955, over 4935.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 01:53:13,723 INFO [train.py:919] (2/6) Start epoch 486
2024-03-14 01:54:02,943 INFO [train.py:527] (2/6) Epoch 486, batch 10, global_batch_idx: 60150, batch size: 36, loss[discriminator_loss=2.794, discriminator_real_loss=1.277, discriminator_fake_loss=1.517, generator_loss=28.73, generator_mel_loss=18.37, generator_kl_loss=1.623, generator_dur_loss=1.735, generator_adv_loss=1.748, generator_feat_match_loss=5.25, over 36.00 samples.], tot_loss[discriminator_loss=2.724, discriminator_real_loss=1.372, discriminator_fake_loss=1.352, generator_loss=28.42, generator_mel_loss=18.22, generator_kl_loss=1.443, generator_dur_loss=1.714, generator_adv_loss=1.981, generator_feat_match_loss=5.06, over 523.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 01:56:22,098 INFO [train.py:527] (2/6) Epoch 486, batch 60, global_batch_idx: 60200, batch size: 70, loss[discriminator_loss=2.713, discriminator_real_loss=1.406, discriminator_fake_loss=1.307, generator_loss=26.96, generator_mel_loss=17.25, generator_kl_loss=1.175, generator_dur_loss=1.82, generator_adv_loss=1.885, generator_feat_match_loss=4.831, over 70.00 samples.], tot_loss[discriminator_loss=2.713, discriminator_real_loss=1.378, discriminator_fake_loss=1.335, generator_loss=28.19, generator_mel_loss=18.1, generator_kl_loss=1.411, generator_dur_loss=1.748, generator_adv_loss=1.954, generator_feat_match_loss=4.981, over 3431.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 01:56:22,100 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 01:56:30,163 INFO [train.py:591] (2/6) Epoch 486, validation: discriminator_loss=2.72, discriminator_real_loss=1.342, discriminator_fake_loss=1.377, generator_loss=26.58, generator_mel_loss=18.11, generator_kl_loss=1.117, generator_dur_loss=1.813, generator_adv_loss=1.773, generator_feat_match_loss=3.764, over 100.00 samples.
2024-03-14 01:56:30,165 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 01:58:51,801 INFO [train.py:527] (2/6) Epoch 486, batch 110, global_batch_idx: 60250, batch size: 66, loss[discriminator_loss=2.722, discriminator_real_loss=1.315, discriminator_fake_loss=1.408, generator_loss=28.12, generator_mel_loss=17.92, generator_kl_loss=1.481, generator_dur_loss=1.742, generator_adv_loss=1.999, generator_feat_match_loss=4.971, over 66.00 samples.], tot_loss[discriminator_loss=2.709, discriminator_real_loss=1.368, discriminator_fake_loss=1.342, generator_loss=28.19, generator_mel_loss=18.05, generator_kl_loss=1.415, generator_dur_loss=1.746, generator_adv_loss=1.958, generator_feat_match_loss=5.021, over 6167.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 01:59:26,844 INFO [train.py:919] (2/6) Start epoch 487
2024-03-14 02:01:30,057 INFO [train.py:527] (2/6) Epoch 487, batch 36, global_batch_idx: 60300, batch size: 80, loss[discriminator_loss=2.733, discriminator_real_loss=1.448, discriminator_fake_loss=1.286, generator_loss=28.21, generator_mel_loss=18.21, generator_kl_loss=1.276, generator_dur_loss=1.838, generator_adv_loss=1.933, generator_feat_match_loss=4.949, over 80.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.376, discriminator_fake_loss=1.344, generator_loss=28.07, generator_mel_loss=18, generator_kl_loss=1.431, generator_dur_loss=1.734, generator_adv_loss=1.942, generator_feat_match_loss=4.972, over 2156.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 02:03:49,131 INFO [train.py:527] (2/6) Epoch 487, batch 86, global_batch_idx: 60350, batch size: 68, loss[discriminator_loss=2.713, discriminator_real_loss=1.23, discriminator_fake_loss=1.483, generator_loss=29.06, generator_mel_loss=18.28, generator_kl_loss=1.309, generator_dur_loss=1.74, generator_adv_loss=1.966, generator_feat_match_loss=5.763, over 68.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.371, discriminator_fake_loss=1.343, generator_loss=28.13, generator_mel_loss=18.02, generator_kl_loss=1.423, generator_dur_loss=1.746, generator_adv_loss=1.95, generator_feat_match_loss=4.996, over 5112.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 02:05:35,194 INFO [train.py:919] (2/6) Start epoch 488
2024-03-14 02:06:34,167 INFO [train.py:527] (2/6) Epoch 488, batch 12, global_batch_idx: 60400, batch size: 64, loss[discriminator_loss=2.727, discriminator_real_loss=1.464, discriminator_fake_loss=1.263, generator_loss=28, generator_mel_loss=18.09, generator_kl_loss=1.394, generator_dur_loss=1.756, generator_adv_loss=1.847, generator_feat_match_loss=4.921, over 64.00 samples.], tot_loss[discriminator_loss=2.723, discriminator_real_loss=1.395, discriminator_fake_loss=1.328, generator_loss=28.04, generator_mel_loss=17.97, generator_kl_loss=1.359, generator_dur_loss=1.78, generator_adv_loss=1.966, generator_feat_match_loss=4.96, over 810.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 02:06:34,170 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 02:06:42,167 INFO [train.py:591] (2/6) Epoch 488, validation: discriminator_loss=2.793, discriminator_real_loss=1.419, discriminator_fake_loss=1.374, generator_loss=27.17, generator_mel_loss=18.41, generator_kl_loss=1.266, generator_dur_loss=1.805, generator_adv_loss=1.847, generator_feat_match_loss=3.841, over 100.00 samples.
2024-03-14 02:06:42,168 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 02:09:02,869 INFO [train.py:527] (2/6) Epoch 488, batch 62, global_batch_idx: 60450, batch size: 72, loss[discriminator_loss=2.709, discriminator_real_loss=1.393, discriminator_fake_loss=1.316, generator_loss=27.89, generator_mel_loss=17.76, generator_kl_loss=1.456, generator_dur_loss=1.779, generator_adv_loss=1.992, generator_feat_match_loss=4.897, over 72.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.379, discriminator_fake_loss=1.341, generator_loss=28.09, generator_mel_loss=17.95, generator_kl_loss=1.401, generator_dur_loss=1.76, generator_adv_loss=1.957, generator_feat_match_loss=5.027, over 3761.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 02:11:20,212 INFO [train.py:527] (2/6) Epoch 488, batch 112, global_batch_idx: 60500, batch size: 64, loss[discriminator_loss=2.73, discriminator_real_loss=1.307, discriminator_fake_loss=1.423, generator_loss=27.22, generator_mel_loss=17.65, generator_kl_loss=1.33, generator_dur_loss=1.773, generator_adv_loss=2, generator_feat_match_loss=4.468, over 64.00 samples.], tot_loss[discriminator_loss=2.717, discriminator_real_loss=1.377, discriminator_fake_loss=1.34, generator_loss=28.01, generator_mel_loss=17.94, generator_kl_loss=1.396, generator_dur_loss=1.758, generator_adv_loss=1.954, generator_feat_match_loss=4.968, over 6661.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 02:11:51,073 INFO [train.py:919] (2/6) Start epoch 489
2024-03-14 02:14:00,794 INFO [train.py:527] (2/6) Epoch 489, batch 38, global_batch_idx: 60550, batch size: 44, loss[discriminator_loss=2.673, discriminator_real_loss=1.283, discriminator_fake_loss=1.39, generator_loss=28.42, generator_mel_loss=17.72, generator_kl_loss=1.448, generator_dur_loss=1.704, generator_adv_loss=1.898, generator_feat_match_loss=5.649, over 44.00 samples.], tot_loss[discriminator_loss=2.719, discriminator_real_loss=1.372, discriminator_fake_loss=1.347, generator_loss=28.2, generator_mel_loss=18.04, generator_kl_loss=1.432, generator_dur_loss=1.745, generator_adv_loss=1.977, generator_feat_match_loss=5.007, over 2217.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 02:16:20,628 INFO [train.py:527] (2/6) Epoch 489, batch 88, global_batch_idx: 60600, batch size: 74, loss[discriminator_loss=2.737, discriminator_real_loss=1.357, discriminator_fake_loss=1.38, generator_loss=27.94, generator_mel_loss=17.94, generator_kl_loss=1.412, generator_dur_loss=1.779, generator_adv_loss=1.939, generator_feat_match_loss=4.871, over 74.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.368, discriminator_fake_loss=1.347, generator_loss=28.2, generator_mel_loss=18.01, generator_kl_loss=1.418, generator_dur_loss=1.753, generator_adv_loss=1.963, generator_feat_match_loss=5.053, over 5215.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 02:16:20,629 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 02:16:29,498 INFO [train.py:591] (2/6) Epoch 489, validation: discriminator_loss=2.774, discriminator_real_loss=1.513, discriminator_fake_loss=1.261, generator_loss=27.55, generator_mel_loss=18.22, generator_kl_loss=1.264, generator_dur_loss=1.804, generator_adv_loss=1.977, generator_feat_match_loss=4.282, over 100.00 samples.
2024-03-14 02:16:29,499 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 02:18:06,743 INFO [train.py:919] (2/6) Start epoch 490
2024-03-14 02:19:10,405 INFO [train.py:527] (2/6) Epoch 490, batch 14, global_batch_idx: 60650, batch size: 61, loss[discriminator_loss=2.727, discriminator_real_loss=1.401, discriminator_fake_loss=1.326, generator_loss=28.21, generator_mel_loss=18.18, generator_kl_loss=1.49, generator_dur_loss=1.738, generator_adv_loss=2.031, generator_feat_match_loss=4.78, over 61.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.364, discriminator_fake_loss=1.356, generator_loss=27.74, generator_mel_loss=17.73, generator_kl_loss=1.411, generator_dur_loss=1.767, generator_adv_loss=1.95, generator_feat_match_loss=4.881, over 1009.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 02:21:27,303 INFO [train.py:527] (2/6) Epoch 490, batch 64, global_batch_idx: 60700, batch size: 58, loss[discriminator_loss=2.683, discriminator_real_loss=1.367, discriminator_fake_loss=1.315, generator_loss=28.48, generator_mel_loss=18.16, generator_kl_loss=1.391, generator_dur_loss=1.698, generator_adv_loss=2.017, generator_feat_match_loss=5.214, over 58.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.371, discriminator_fake_loss=1.348, generator_loss=28.08, generator_mel_loss=17.92, generator_kl_loss=1.442, generator_dur_loss=1.733, generator_adv_loss=1.981, generator_feat_match_loss=5.004, over 3669.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 02:23:47,072 INFO [train.py:527] (2/6) Epoch 490, batch 114, global_batch_idx: 60750, batch size: 70, loss[discriminator_loss=2.727, discriminator_real_loss=1.477, discriminator_fake_loss=1.25, generator_loss=26.53, generator_mel_loss=17.17, generator_kl_loss=1.08, generator_dur_loss=1.809, generator_adv_loss=1.866, generator_feat_match_loss=4.599, over 70.00 samples.], tot_loss[discriminator_loss=2.717, discriminator_real_loss=1.375, discriminator_fake_loss=1.343, generator_loss=28.04, generator_mel_loss=17.95, generator_kl_loss=1.426, generator_dur_loss=1.735, generator_adv_loss=1.961, generator_feat_match_loss=4.969, over 6616.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 02:24:12,981 INFO [train.py:919] (2/6) Start epoch 491
2024-03-14 02:26:29,233 INFO [train.py:527] (2/6) Epoch 491, batch 40, global_batch_idx: 60800, batch size: 55, loss[discriminator_loss=2.68, discriminator_real_loss=1.365, discriminator_fake_loss=1.315, generator_loss=28.13, generator_mel_loss=18.05, generator_kl_loss=1.353, generator_dur_loss=1.733, generator_adv_loss=2.071, generator_feat_match_loss=4.926, over 55.00 samples.], tot_loss[discriminator_loss=2.718, discriminator_real_loss=1.373, discriminator_fake_loss=1.345, generator_loss=27.94, generator_mel_loss=17.94, generator_kl_loss=1.405, generator_dur_loss=1.748, generator_adv_loss=1.95, generator_feat_match_loss=4.893, over 2446.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 02:26:29,235 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 02:26:37,143 INFO [train.py:591] (2/6) Epoch 491, validation: discriminator_loss=2.776, discriminator_real_loss=1.472, discriminator_fake_loss=1.304, generator_loss=26.72, generator_mel_loss=17.81, generator_kl_loss=1.207, generator_dur_loss=1.834, generator_adv_loss=1.958, generator_feat_match_loss=3.919, over 100.00 samples.
2024-03-14 02:26:37,144 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 02:28:55,232 INFO [train.py:527] (2/6) Epoch 491, batch 90, global_batch_idx: 60850, batch size: 59, loss[discriminator_loss=2.676, discriminator_real_loss=1.409, discriminator_fake_loss=1.267, generator_loss=28.52, generator_mel_loss=17.8, generator_kl_loss=1.497, generator_dur_loss=1.748, generator_adv_loss=1.939, generator_feat_match_loss=5.532, over 59.00 samples.], tot_loss[discriminator_loss=2.714, discriminator_real_loss=1.376, discriminator_fake_loss=1.339, generator_loss=27.99, generator_mel_loss=17.95, generator_kl_loss=1.41, generator_dur_loss=1.757, generator_adv_loss=1.96, generator_feat_match_loss=4.915, over 5362.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 02:30:28,504 INFO [train.py:919] (2/6) Start epoch 492
2024-03-14 02:31:38,291 INFO [train.py:527] (2/6) Epoch 492, batch 16, global_batch_idx: 60900, batch size: 42, loss[discriminator_loss=2.85, discriminator_real_loss=1.513, discriminator_fake_loss=1.337, generator_loss=26.91, generator_mel_loss=17.65, generator_kl_loss=1.511, generator_dur_loss=1.687, generator_adv_loss=1.823, generator_feat_match_loss=4.233, over 42.00 samples.], tot_loss[discriminator_loss=2.737, discriminator_real_loss=1.381, discriminator_fake_loss=1.356, generator_loss=27.74, generator_mel_loss=17.94, generator_kl_loss=1.394, generator_dur_loss=1.768, generator_adv_loss=1.925, generator_feat_match_loss=4.709, over 989.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 02:33:57,949 INFO [train.py:527] (2/6) Epoch 492, batch 66, global_batch_idx: 60950, batch size: 58, loss[discriminator_loss=2.663, discriminator_real_loss=1.389, discriminator_fake_loss=1.274, generator_loss=27.48, generator_mel_loss=17.89, generator_kl_loss=1.352, generator_dur_loss=1.78, generator_adv_loss=1.871, generator_feat_match_loss=4.583, over 58.00 samples.], tot_loss[discriminator_loss=2.725, discriminator_real_loss=1.369, discriminator_fake_loss=1.356, generator_loss=28.02, generator_mel_loss=18.03, generator_kl_loss=1.387, generator_dur_loss=1.781, generator_adv_loss=1.94, generator_feat_match_loss=4.88, over 3917.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 02:36:17,295 INFO [train.py:527] (2/6) Epoch 492, batch 116, global_batch_idx: 61000, batch size: 47, loss[discriminator_loss=2.74, discriminator_real_loss=1.4, discriminator_fake_loss=1.34, generator_loss=27.65, generator_mel_loss=17.83, generator_kl_loss=1.336, generator_dur_loss=1.718, generator_adv_loss=2.118, generator_feat_match_loss=4.656, over 47.00 samples.], tot_loss[discriminator_loss=2.719, discriminator_real_loss=1.369, discriminator_fake_loss=1.35, generator_loss=28.02, generator_mel_loss=17.99, generator_kl_loss=1.392, generator_dur_loss=1.781, generator_adv_loss=1.947, generator_feat_match_loss=4.911, over 6905.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 02:36:17,297 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 02:36:26,119 INFO [train.py:591] (2/6) Epoch 492, validation: discriminator_loss=2.795, discriminator_real_loss=1.56, discriminator_fake_loss=1.235, generator_loss=27.04, generator_mel_loss=18.32, generator_kl_loss=1.27, generator_dur_loss=1.83, generator_adv_loss=1.987, generator_feat_match_loss=3.637, over 100.00 samples.
2024-03-14 02:36:26,120 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 02:36:47,404 INFO [train.py:919] (2/6) Start epoch 493
2024-03-14 02:39:06,977 INFO [train.py:527] (2/6) Epoch 493, batch 42, global_batch_idx: 61050, batch size: 50, loss[discriminator_loss=2.688, discriminator_real_loss=1.293, discriminator_fake_loss=1.395, generator_loss=28.63, generator_mel_loss=18.1, generator_kl_loss=1.5, generator_dur_loss=1.693, generator_adv_loss=1.985, generator_feat_match_loss=5.351, over 50.00 samples.], tot_loss[discriminator_loss=2.714, discriminator_real_loss=1.373, discriminator_fake_loss=1.342, generator_loss=28.09, generator_mel_loss=18.01, generator_kl_loss=1.404, generator_dur_loss=1.754, generator_adv_loss=1.947, generator_feat_match_loss=4.979, over 2458.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 02:41:26,017 INFO [train.py:527] (2/6) Epoch 493, batch 92, global_batch_idx: 61100, batch size: 14, loss[discriminator_loss=2.615, discriminator_real_loss=1.242, discriminator_fake_loss=1.373, generator_loss=31.03, generator_mel_loss=19.46, generator_kl_loss=1.892, generator_dur_loss=1.549, generator_adv_loss=1.956, generator_feat_match_loss=6.17, over 14.00 samples.], tot_loss[discriminator_loss=2.712, discriminator_real_loss=1.369, discriminator_fake_loss=1.343, generator_loss=28.08, generator_mel_loss=18.02, generator_kl_loss=1.404, generator_dur_loss=1.752, generator_adv_loss=1.945, generator_feat_match_loss=4.964, over 5332.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 02:42:52,051 INFO [train.py:919] (2/6) Start epoch 494
2024-03-14 02:44:05,480 INFO [train.py:527] (2/6) Epoch 494, batch 18, global_batch_idx: 61150, batch size: 80, loss[discriminator_loss=2.724, discriminator_real_loss=1.373, discriminator_fake_loss=1.351, generator_loss=27.2, generator_mel_loss=17.54, generator_kl_loss=1.292, generator_dur_loss=1.793, generator_adv_loss=1.883, generator_feat_match_loss=4.692, over 80.00 samples.], tot_loss[discriminator_loss=2.713, discriminator_real_loss=1.366, discriminator_fake_loss=1.347, generator_loss=27.95, generator_mel_loss=17.98, generator_kl_loss=1.399, generator_dur_loss=1.742, generator_adv_loss=1.933, generator_feat_match_loss=4.893, over 1102.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 02:46:26,308 INFO [train.py:527] (2/6) Epoch 494, batch 68, global_batch_idx: 61200, batch size: 88, loss[discriminator_loss=2.637, discriminator_real_loss=1.257, discriminator_fake_loss=1.38, generator_loss=28.12, generator_mel_loss=17.8, generator_kl_loss=1.302, generator_dur_loss=1.785, generator_adv_loss=1.957, generator_feat_match_loss=5.275, over 88.00 samples.], tot_loss[discriminator_loss=2.71, discriminator_real_loss=1.368, discriminator_fake_loss=1.341, generator_loss=28.05, generator_mel_loss=17.99, generator_kl_loss=1.441, generator_dur_loss=1.726, generator_adv_loss=1.946, generator_feat_match_loss=4.943, over 3904.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 02:46:26,310 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 02:46:34,379 INFO [train.py:591] (2/6) Epoch 494, validation: discriminator_loss=2.735, discriminator_real_loss=1.48, discriminator_fake_loss=1.256, generator_loss=26.8, generator_mel_loss=18.13, generator_kl_loss=1.329, generator_dur_loss=1.809, generator_adv_loss=1.932, generator_feat_match_loss=3.602, over 100.00 samples.
2024-03-14 02:46:34,380 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 02:48:51,418 INFO [train.py:527] (2/6) Epoch 494, batch 118, global_batch_idx: 61250, batch size: 64, loss[discriminator_loss=2.777, discriminator_real_loss=1.28, discriminator_fake_loss=1.496, generator_loss=28.76, generator_mel_loss=18.45, generator_kl_loss=1.471, generator_dur_loss=1.772, generator_adv_loss=1.841, generator_feat_match_loss=5.229, over 64.00 samples.], tot_loss[discriminator_loss=2.712, discriminator_real_loss=1.368, discriminator_fake_loss=1.344, generator_loss=28.08, generator_mel_loss=17.99, generator_kl_loss=1.427, generator_dur_loss=1.739, generator_adv_loss=1.95, generator_feat_match_loss=4.974, over 6879.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 02:49:06,829 INFO [train.py:919] (2/6) Start epoch 495
2024-03-14 02:51:31,735 INFO [train.py:527] (2/6) Epoch 495, batch 44, global_batch_idx: 61300, batch size: 55, loss[discriminator_loss=2.622, discriminator_real_loss=1.324, discriminator_fake_loss=1.298, generator_loss=27.78, generator_mel_loss=18.07, generator_kl_loss=1.428, generator_dur_loss=1.72, generator_adv_loss=1.958, generator_feat_match_loss=4.609, over 55.00 samples.], tot_loss[discriminator_loss=2.714, discriminator_real_loss=1.376, discriminator_fake_loss=1.338, generator_loss=28.1, generator_mel_loss=18.03, generator_kl_loss=1.431, generator_dur_loss=1.744, generator_adv_loss=1.941, generator_feat_match_loss=4.957, over 2479.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 02:53:52,191 INFO [train.py:527] (2/6) Epoch 495, batch 94, global_batch_idx: 61350, batch size: 55, loss[discriminator_loss=2.705, discriminator_real_loss=1.363, discriminator_fake_loss=1.342, generator_loss=27.85, generator_mel_loss=18.06, generator_kl_loss=1.467, generator_dur_loss=1.713, generator_adv_loss=1.96, generator_feat_match_loss=4.654, over 55.00 samples.], tot_loss[discriminator_loss=2.712, discriminator_real_loss=1.374, discriminator_fake_loss=1.338, generator_loss=28.18, generator_mel_loss=18.04, generator_kl_loss=1.418, generator_dur_loss=1.749, generator_adv_loss=1.951, generator_feat_match_loss=5.021, over 5281.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 02:55:13,023 INFO [train.py:919] (2/6) Start epoch 496
2024-03-14 02:56:33,654 INFO [train.py:527] (2/6) Epoch 496, batch 20, global_batch_idx: 61400, batch size: 44, loss[discriminator_loss=2.706, discriminator_real_loss=1.324, discriminator_fake_loss=1.382, generator_loss=27.55, generator_mel_loss=17.92, generator_kl_loss=1.446, generator_dur_loss=1.715, generator_adv_loss=1.98, generator_feat_match_loss=4.491, over 44.00 samples.], tot_loss[discriminator_loss=2.707, discriminator_real_loss=1.36, discriminator_fake_loss=1.347, generator_loss=28.3, generator_mel_loss=18.11, generator_kl_loss=1.41, generator_dur_loss=1.741, generator_adv_loss=1.949, generator_feat_match_loss=5.083, over 1184.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 02:56:33,656 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 02:56:41,778 INFO [train.py:591] (2/6) Epoch 496, validation: discriminator_loss=2.804, discriminator_real_loss=1.479, discriminator_fake_loss=1.325, generator_loss=26.64, generator_mel_loss=18.11, generator_kl_loss=1.165, generator_dur_loss=1.803, generator_adv_loss=1.929, generator_feat_match_loss=3.628, over 100.00 samples.
2024-03-14 02:56:41,779 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 02:59:00,494 INFO [train.py:527] (2/6) Epoch 496, batch 70, global_batch_idx: 61450, batch size: 17, loss[discriminator_loss=2.628, discriminator_real_loss=1.356, discriminator_fake_loss=1.272, generator_loss=30.21, generator_mel_loss=18.38, generator_kl_loss=1.984, generator_dur_loss=1.596, generator_adv_loss=1.952, generator_feat_match_loss=6.299, over 17.00 samples.], tot_loss[discriminator_loss=2.711, discriminator_real_loss=1.37, discriminator_fake_loss=1.341, generator_loss=28.26, generator_mel_loss=18.1, generator_kl_loss=1.417, generator_dur_loss=1.75, generator_adv_loss=1.936, generator_feat_match_loss=5.058, over 4008.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 03:01:19,045 INFO [train.py:527] (2/6) Epoch 496, batch 120, global_batch_idx: 61500, batch size: 15, loss[discriminator_loss=2.679, discriminator_real_loss=1.356, discriminator_fake_loss=1.323, generator_loss=29.6, generator_mel_loss=18.53, generator_kl_loss=1.564, generator_dur_loss=1.628, generator_adv_loss=1.94, generator_feat_match_loss=5.933, over 15.00 samples.], tot_loss[discriminator_loss=2.713, discriminator_real_loss=1.373, discriminator_fake_loss=1.34, generator_loss=28.19, generator_mel_loss=18.05, generator_kl_loss=1.423, generator_dur_loss=1.754, generator_adv_loss=1.946, generator_feat_match_loss=5.019, over 6869.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 03:01:29,326 INFO [train.py:919] (2/6) Start epoch 497
2024-03-14 03:04:01,909 INFO [train.py:527] (2/6) Epoch 497, batch 46, global_batch_idx: 61550, batch size: 58, loss[discriminator_loss=2.725, discriminator_real_loss=1.314, discriminator_fake_loss=1.411, generator_loss=27.97, generator_mel_loss=18.06, generator_kl_loss=1.34, generator_dur_loss=1.806, generator_adv_loss=2.066, generator_feat_match_loss=4.705, over 58.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.368, discriminator_fake_loss=1.347, generator_loss=28.22, generator_mel_loss=18, generator_kl_loss=1.413, generator_dur_loss=1.757, generator_adv_loss=1.966, generator_feat_match_loss=5.084, over 2704.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 03:06:17,962 INFO [train.py:527] (2/6) Epoch 497, batch 96, global_batch_idx: 61600, batch size: 55, loss[discriminator_loss=2.772, discriminator_real_loss=1.412, discriminator_fake_loss=1.36, generator_loss=27.18, generator_mel_loss=17.72, generator_kl_loss=1.532, generator_dur_loss=1.652, generator_adv_loss=1.96, generator_feat_match_loss=4.315, over 55.00 samples.], tot_loss[discriminator_loss=2.713, discriminator_real_loss=1.367, discriminator_fake_loss=1.345, generator_loss=28.22, generator_mel_loss=18.01, generator_kl_loss=1.421, generator_dur_loss=1.759, generator_adv_loss=1.961, generator_feat_match_loss=5.072, over 5534.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 03:06:17,964 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 03:06:26,499 INFO [train.py:591] (2/6) Epoch 497, validation: discriminator_loss=2.775, discriminator_real_loss=1.402, discriminator_fake_loss=1.373, generator_loss=26.94, generator_mel_loss=18.35, generator_kl_loss=1.209, generator_dur_loss=1.826, generator_adv_loss=1.895, generator_feat_match_loss=3.657, over 100.00 samples.
2024-03-14 03:06:26,500 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 03:07:42,401 INFO [train.py:919] (2/6) Start epoch 498
2024-03-14 03:09:08,308 INFO [train.py:527] (2/6) Epoch 498, batch 22, global_batch_idx: 61650, batch size: 44, loss[discriminator_loss=2.698, discriminator_real_loss=1.327, discriminator_fake_loss=1.371, generator_loss=28.12, generator_mel_loss=17.65, generator_kl_loss=1.397, generator_dur_loss=1.669, generator_adv_loss=2.004, generator_feat_match_loss=5.399, over 44.00 samples.], tot_loss[discriminator_loss=2.727, discriminator_real_loss=1.394, discriminator_fake_loss=1.332, generator_loss=27.96, generator_mel_loss=17.96, generator_kl_loss=1.415, generator_dur_loss=1.733, generator_adv_loss=1.931, generator_feat_match_loss=4.917, over 1196.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 03:11:26,802 INFO [train.py:527] (2/6) Epoch 498, batch 72, global_batch_idx: 61700, batch size: 36, loss[discriminator_loss=2.72, discriminator_real_loss=1.411, discriminator_fake_loss=1.309, generator_loss=28.78, generator_mel_loss=17.95, generator_kl_loss=1.618, generator_dur_loss=1.665, generator_adv_loss=1.901, generator_feat_match_loss=5.641, over 36.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.375, discriminator_fake_loss=1.34, generator_loss=28.12, generator_mel_loss=17.96, generator_kl_loss=1.43, generator_dur_loss=1.755, generator_adv_loss=1.946, generator_feat_match_loss=5.023, over 4087.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 03:13:45,222 INFO [train.py:527] (2/6) Epoch 498, batch 122, global_batch_idx: 61750, batch size: 14, loss[discriminator_loss=2.804, discriminator_real_loss=1.385, discriminator_fake_loss=1.419, generator_loss=27.5, generator_mel_loss=17.44, generator_kl_loss=1.72, generator_dur_loss=1.589, generator_adv_loss=1.963, generator_feat_match_loss=4.786, over 14.00 samples.], tot_loss[discriminator_loss=2.714, discriminator_real_loss=1.374, discriminator_fake_loss=1.34, generator_loss=28.11, generator_mel_loss=17.97, generator_kl_loss=1.436, generator_dur_loss=1.755, generator_adv_loss=1.953, generator_feat_match_loss=5.005, over 6690.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 03:13:50,046 INFO [train.py:919] (2/6) Start epoch 499
2024-03-14 03:16:23,901 INFO [train.py:527] (2/6) Epoch 499, batch 48, global_batch_idx: 61800, batch size: 66, loss[discriminator_loss=2.744, discriminator_real_loss=1.403, discriminator_fake_loss=1.341, generator_loss=28.13, generator_mel_loss=18.01, generator_kl_loss=1.465, generator_dur_loss=1.796, generator_adv_loss=1.874, generator_feat_match_loss=4.983, over 66.00 samples.], tot_loss[discriminator_loss=2.717, discriminator_real_loss=1.367, discriminator_fake_loss=1.35, generator_loss=28.22, generator_mel_loss=18.01, generator_kl_loss=1.431, generator_dur_loss=1.757, generator_adv_loss=1.951, generator_feat_match_loss=5.068, over 2840.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 03:16:23,902 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 03:16:31,894 INFO [train.py:591] (2/6) Epoch 499, validation: discriminator_loss=2.737, discriminator_real_loss=1.354, discriminator_fake_loss=1.383, generator_loss=27.07, generator_mel_loss=17.98, generator_kl_loss=1.183, generator_dur_loss=1.836, generator_adv_loss=1.837, generator_feat_match_loss=4.243, over 100.00 samples.
2024-03-14 03:16:31,895 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 03:18:47,761 INFO [train.py:527] (2/6) Epoch 499, batch 98, global_batch_idx: 61850, batch size: 70, loss[discriminator_loss=2.695, discriminator_real_loss=1.401, discriminator_fake_loss=1.294, generator_loss=28.61, generator_mel_loss=18.13, generator_kl_loss=1.301, generator_dur_loss=1.808, generator_adv_loss=2.153, generator_feat_match_loss=5.227, over 70.00 samples.], tot_loss[discriminator_loss=2.714, discriminator_real_loss=1.373, discriminator_fake_loss=1.341, generator_loss=28.23, generator_mel_loss=17.99, generator_kl_loss=1.412, generator_dur_loss=1.763, generator_adv_loss=1.967, generator_feat_match_loss=5.091, over 5756.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 03:20:01,018 INFO [train.py:919] (2/6) Start epoch 500
2024-03-14 03:21:33,408 INFO [train.py:527] (2/6) Epoch 500, batch 24, global_batch_idx: 61900, batch size: 39, loss[discriminator_loss=2.694, discriminator_real_loss=1.391, discriminator_fake_loss=1.303, generator_loss=27.44, generator_mel_loss=17.61, generator_kl_loss=1.595, generator_dur_loss=1.727, generator_adv_loss=1.867, generator_feat_match_loss=4.643, over 39.00 samples.], tot_loss[discriminator_loss=2.725, discriminator_real_loss=1.38, discriminator_fake_loss=1.345, generator_loss=27.92, generator_mel_loss=17.94, generator_kl_loss=1.396, generator_dur_loss=1.764, generator_adv_loss=1.918, generator_feat_match_loss=4.902, over 1489.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 03:23:53,896 INFO [train.py:527] (2/6) Epoch 500, batch 74, global_batch_idx: 61950, batch size: 42, loss[discriminator_loss=2.708, discriminator_real_loss=1.421, discriminator_fake_loss=1.286, generator_loss=29.29, generator_mel_loss=18.52, generator_kl_loss=1.574, generator_dur_loss=1.702, generator_adv_loss=1.855, generator_feat_match_loss=5.639, over 42.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.375, discriminator_fake_loss=1.34, generator_loss=28.15, generator_mel_loss=17.99, generator_kl_loss=1.428, generator_dur_loss=1.761, generator_adv_loss=1.948, generator_feat_match_loss=5.028, over 4358.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 03:26:08,066 INFO [train.py:919] (2/6) Start epoch 501
2024-03-14 03:26:30,842 INFO [train.py:527] (2/6) Epoch 501, batch 0, global_batch_idx: 62000, batch size: 36, loss[discriminator_loss=2.739, discriminator_real_loss=1.356, discriminator_fake_loss=1.383, generator_loss=28.51, generator_mel_loss=17.81, generator_kl_loss=1.651, generator_dur_loss=1.688, generator_adv_loss=1.915, generator_feat_match_loss=5.446, over 36.00 samples.], tot_loss[discriminator_loss=2.739, discriminator_real_loss=1.356, discriminator_fake_loss=1.383, generator_loss=28.51, generator_mel_loss=17.81, generator_kl_loss=1.651, generator_dur_loss=1.688, generator_adv_loss=1.915, generator_feat_match_loss=5.446, over 36.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 03:26:30,845 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 03:26:38,676 INFO [train.py:591] (2/6) Epoch 501, validation: discriminator_loss=2.8, discriminator_real_loss=1.447, discriminator_fake_loss=1.353, generator_loss=27, generator_mel_loss=18.25, generator_kl_loss=1.239, generator_dur_loss=1.813, generator_adv_loss=1.859, generator_feat_match_loss=3.835, over 100.00 samples.
2024-03-14 03:26:38,678 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 03:29:01,870 INFO [train.py:527] (2/6) Epoch 501, batch 50, global_batch_idx: 62050, batch size: 80, loss[discriminator_loss=2.767, discriminator_real_loss=1.429, discriminator_fake_loss=1.338, generator_loss=27.72, generator_mel_loss=17.9, generator_kl_loss=1.312, generator_dur_loss=1.807, generator_adv_loss=1.96, generator_feat_match_loss=4.737, over 80.00 samples.], tot_loss[discriminator_loss=2.728, discriminator_real_loss=1.38, discriminator_fake_loss=1.348, generator_loss=28.05, generator_mel_loss=17.97, generator_kl_loss=1.397, generator_dur_loss=1.764, generator_adv_loss=1.943, generator_feat_match_loss=4.981, over 3099.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 03:31:20,021 INFO [train.py:527] (2/6) Epoch 501, batch 100, global_batch_idx: 62100, batch size: 59, loss[discriminator_loss=2.734, discriminator_real_loss=1.467, discriminator_fake_loss=1.267, generator_loss=27.18, generator_mel_loss=17.65, generator_kl_loss=1.35, generator_dur_loss=1.732, generator_adv_loss=1.877, generator_feat_match_loss=4.574, over 59.00 samples.], tot_loss[discriminator_loss=2.718, discriminator_real_loss=1.376, discriminator_fake_loss=1.342, generator_loss=28.08, generator_mel_loss=17.96, generator_kl_loss=1.404, generator_dur_loss=1.76, generator_adv_loss=1.955, generator_feat_match_loss=4.998, over 5949.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 03:32:19,422 INFO [train.py:919] (2/6) Start epoch 502
2024-03-14 03:33:55,578 INFO [train.py:527] (2/6) Epoch 502, batch 26, global_batch_idx: 62150, batch size: 68, loss[discriminator_loss=2.7, discriminator_real_loss=1.264, discriminator_fake_loss=1.437, generator_loss=28.76, generator_mel_loss=18.14, generator_kl_loss=1.381, generator_dur_loss=1.753, generator_adv_loss=2.164, generator_feat_match_loss=5.321, over 68.00 samples.], tot_loss[discriminator_loss=2.698, discriminator_real_loss=1.363, discriminator_fake_loss=1.335, generator_loss=28.24, generator_mel_loss=17.98, generator_kl_loss=1.405, generator_dur_loss=1.776, generator_adv_loss=1.978, generator_feat_match_loss=5.097, over 1642.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 03:36:15,028 INFO [train.py:527] (2/6) Epoch 502, batch 76, global_batch_idx: 62200, batch size: 72, loss[discriminator_loss=2.738, discriminator_real_loss=1.391, discriminator_fake_loss=1.347, generator_loss=27.4, generator_mel_loss=17.48, generator_kl_loss=1.279, generator_dur_loss=1.816, generator_adv_loss=2.015, generator_feat_match_loss=4.808, over 72.00 samples.], tot_loss[discriminator_loss=2.709, discriminator_real_loss=1.374, discriminator_fake_loss=1.335, generator_loss=28.22, generator_mel_loss=17.99, generator_kl_loss=1.417, generator_dur_loss=1.763, generator_adv_loss=1.963, generator_feat_match_loss=5.093, over 4383.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 03:36:15,030 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 03:36:23,146 INFO [train.py:591] (2/6) Epoch 502, validation: discriminator_loss=2.775, discriminator_real_loss=1.546, discriminator_fake_loss=1.23, generator_loss=27.43, generator_mel_loss=17.95, generator_kl_loss=1.265, generator_dur_loss=1.815, generator_adv_loss=2.04, generator_feat_match_loss=4.354, over 100.00 samples.
2024-03-14 03:36:23,147 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 03:38:34,563 INFO [train.py:919] (2/6) Start epoch 503
2024-03-14 03:39:03,004 INFO [train.py:527] (2/6) Epoch 503, batch 2, global_batch_idx: 62250, batch size: 48, loss[discriminator_loss=2.777, discriminator_real_loss=1.427, discriminator_fake_loss=1.35, generator_loss=27.71, generator_mel_loss=17.89, generator_kl_loss=1.429, generator_dur_loss=1.675, generator_adv_loss=1.977, generator_feat_match_loss=4.739, over 48.00 samples.], tot_loss[discriminator_loss=2.73, discriminator_real_loss=1.372, discriminator_fake_loss=1.358, generator_loss=28.69, generator_mel_loss=18.22, generator_kl_loss=1.516, generator_dur_loss=1.679, generator_adv_loss=1.95, generator_feat_match_loss=5.325, over 134.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 03:41:21,216 INFO [train.py:527] (2/6) Epoch 503, batch 52, global_batch_idx: 62300, batch size: 47, loss[discriminator_loss=2.698, discriminator_real_loss=1.327, discriminator_fake_loss=1.37, generator_loss=29.23, generator_mel_loss=18.34, generator_kl_loss=1.486, generator_dur_loss=1.734, generator_adv_loss=1.98, generator_feat_match_loss=5.692, over 47.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.378, discriminator_fake_loss=1.339, generator_loss=28.19, generator_mel_loss=17.98, generator_kl_loss=1.42, generator_dur_loss=1.764, generator_adv_loss=1.961, generator_feat_match_loss=5.067, over 2927.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 03:43:38,642 INFO [train.py:527] (2/6) Epoch 503, batch 102, global_batch_idx: 62350, batch size: 59, loss[discriminator_loss=2.711, discriminator_real_loss=1.47, discriminator_fake_loss=1.241, generator_loss=27.53, generator_mel_loss=17.58, generator_kl_loss=1.402, generator_dur_loss=1.767, generator_adv_loss=2.049, generator_feat_match_loss=4.73, over 59.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.381, discriminator_fake_loss=1.339, generator_loss=28.16, generator_mel_loss=17.98, generator_kl_loss=1.427, generator_dur_loss=1.755, generator_adv_loss=1.958, generator_feat_match_loss=5.037, over 5618.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 03:44:40,062 INFO [train.py:919] (2/6) Start epoch 504
2024-03-14 03:46:22,684 INFO [train.py:527] (2/6) Epoch 504, batch 28, global_batch_idx: 62400, batch size: 68, loss[discriminator_loss=2.754, discriminator_real_loss=1.384, discriminator_fake_loss=1.37, generator_loss=28.11, generator_mel_loss=17.65, generator_kl_loss=1.296, generator_dur_loss=1.799, generator_adv_loss=2.036, generator_feat_match_loss=5.327, over 68.00 samples.], tot_loss[discriminator_loss=2.702, discriminator_real_loss=1.365, discriminator_fake_loss=1.337, generator_loss=28.16, generator_mel_loss=17.96, generator_kl_loss=1.399, generator_dur_loss=1.761, generator_adv_loss=1.964, generator_feat_match_loss=5.072, over 1737.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 03:46:22,685 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 03:46:30,662 INFO [train.py:591] (2/6) Epoch 504, validation: discriminator_loss=2.765, discriminator_real_loss=1.536, discriminator_fake_loss=1.229, generator_loss=27.01, generator_mel_loss=18.04, generator_kl_loss=1.208, generator_dur_loss=1.818, generator_adv_loss=2.003, generator_feat_match_loss=3.946, over 100.00 samples.
2024-03-14 03:46:30,664 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 03:48:48,878 INFO [train.py:527] (2/6) Epoch 504, batch 78, global_batch_idx: 62450, batch size: 25, loss[discriminator_loss=2.681, discriminator_real_loss=1.429, discriminator_fake_loss=1.252, generator_loss=29.26, generator_mel_loss=18.5, generator_kl_loss=1.832, generator_dur_loss=1.574, generator_adv_loss=1.934, generator_feat_match_loss=5.414, over 25.00 samples.], tot_loss[discriminator_loss=2.709, discriminator_real_loss=1.366, discriminator_fake_loss=1.342, generator_loss=28.24, generator_mel_loss=18.01, generator_kl_loss=1.415, generator_dur_loss=1.762, generator_adv_loss=1.949, generator_feat_match_loss=5.099, over 4639.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 03:50:54,054 INFO [train.py:919] (2/6) Start epoch 505
2024-03-14 03:51:28,728 INFO [train.py:527] (2/6) Epoch 505, batch 4, global_batch_idx: 62500, batch size: 45, loss[discriminator_loss=2.735, discriminator_real_loss=1.3, discriminator_fake_loss=1.434, generator_loss=27.22, generator_mel_loss=17.16, generator_kl_loss=1.525, generator_dur_loss=1.682, generator_adv_loss=1.917, generator_feat_match_loss=4.934, over 45.00 samples.], tot_loss[discriminator_loss=2.701, discriminator_real_loss=1.364, discriminator_fake_loss=1.337, generator_loss=27.84, generator_mel_loss=17.86, generator_kl_loss=1.5, generator_dur_loss=1.694, generator_adv_loss=1.928, generator_feat_match_loss=4.853, over 243.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 03:53:49,000 INFO [train.py:527] (2/6) Epoch 505, batch 54, global_batch_idx: 62550, batch size: 56, loss[discriminator_loss=2.686, discriminator_real_loss=1.361, discriminator_fake_loss=1.325, generator_loss=28.33, generator_mel_loss=17.83, generator_kl_loss=1.513, generator_dur_loss=1.772, generator_adv_loss=1.956, generator_feat_match_loss=5.257, over 56.00 samples.], tot_loss[discriminator_loss=2.708, discriminator_real_loss=1.366, discriminator_fake_loss=1.342, generator_loss=28.28, generator_mel_loss=18.02, generator_kl_loss=1.429, generator_dur_loss=1.769, generator_adv_loss=1.941, generator_feat_match_loss=5.122, over 3176.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 03:56:08,521 INFO [train.py:527] (2/6) Epoch 505, batch 104, global_batch_idx: 62600, batch size: 39, loss[discriminator_loss=2.712, discriminator_real_loss=1.323, discriminator_fake_loss=1.389, generator_loss=28.27, generator_mel_loss=18.13, generator_kl_loss=1.47, generator_dur_loss=1.706, generator_adv_loss=1.879, generator_feat_match_loss=5.086, over 39.00 samples.], tot_loss[discriminator_loss=2.709, discriminator_real_loss=1.368, discriminator_fake_loss=1.341, generator_loss=28.22, generator_mel_loss=17.98, generator_kl_loss=1.425, generator_dur_loss=1.764, generator_adv_loss=1.947, generator_feat_match_loss=5.104, over 5939.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 03:56:08,523 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 03:56:17,700 INFO [train.py:591] (2/6) Epoch 505, validation: discriminator_loss=2.747, discriminator_real_loss=1.384, discriminator_fake_loss=1.363, generator_loss=26.82, generator_mel_loss=17.9, generator_kl_loss=1.215, generator_dur_loss=1.821, generator_adv_loss=1.816, generator_feat_match_loss=4.067, over 100.00 samples.
2024-03-14 03:56:17,701 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 03:57:09,553 INFO [train.py:919] (2/6) Start epoch 506
2024-03-14 03:58:56,621 INFO [train.py:527] (2/6) Epoch 506, batch 30, global_batch_idx: 62650, batch size: 66, loss[discriminator_loss=2.667, discriminator_real_loss=1.322, discriminator_fake_loss=1.345, generator_loss=27.89, generator_mel_loss=17.88, generator_kl_loss=1.408, generator_dur_loss=1.728, generator_adv_loss=2.105, generator_feat_match_loss=4.774, over 66.00 samples.], tot_loss[discriminator_loss=2.717, discriminator_real_loss=1.375, discriminator_fake_loss=1.342, generator_loss=28.11, generator_mel_loss=17.93, generator_kl_loss=1.435, generator_dur_loss=1.755, generator_adv_loss=1.979, generator_feat_match_loss=5.007, over 1744.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 04:01:18,752 INFO [train.py:527] (2/6) Epoch 506, batch 80, global_batch_idx: 62700, batch size: 96, loss[discriminator_loss=2.707, discriminator_real_loss=1.318, discriminator_fake_loss=1.389, generator_loss=27.42, generator_mel_loss=17.72, generator_kl_loss=1.322, generator_dur_loss=1.868, generator_adv_loss=1.893, generator_feat_match_loss=4.617, over 96.00 samples.], tot_loss[discriminator_loss=2.717, discriminator_real_loss=1.377, discriminator_fake_loss=1.34, generator_loss=28.13, generator_mel_loss=17.96, generator_kl_loss=1.429, generator_dur_loss=1.756, generator_adv_loss=1.965, generator_feat_match_loss=5.026, over 4565.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 04:03:16,562 INFO [train.py:919] (2/6) Start epoch 507
2024-03-14 04:03:55,923 INFO [train.py:527] (2/6) Epoch 507, batch 6, global_batch_idx: 62750, batch size: 48, loss[discriminator_loss=2.654, discriminator_real_loss=1.332, discriminator_fake_loss=1.322, generator_loss=28.38, generator_mel_loss=17.92, generator_kl_loss=1.429, generator_dur_loss=1.71, generator_adv_loss=2.011, generator_feat_match_loss=5.316, over 48.00 samples.], tot_loss[discriminator_loss=2.698, discriminator_real_loss=1.348, discriminator_fake_loss=1.35, generator_loss=28.46, generator_mel_loss=17.97, generator_kl_loss=1.451, generator_dur_loss=1.729, generator_adv_loss=1.947, generator_feat_match_loss=5.364, over 373.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 04:06:15,458 INFO [train.py:527] (2/6) Epoch 507, batch 56, global_batch_idx: 62800, batch size: 70, loss[discriminator_loss=2.769, discriminator_real_loss=1.4, discriminator_fake_loss=1.369, generator_loss=26.46, generator_mel_loss=17.43, generator_kl_loss=1.265, generator_dur_loss=1.792, generator_adv_loss=1.912, generator_feat_match_loss=4.066, over 70.00 samples.], tot_loss[discriminator_loss=2.717, discriminator_real_loss=1.373, discriminator_fake_loss=1.343, generator_loss=28.02, generator_mel_loss=17.94, generator_kl_loss=1.376, generator_dur_loss=1.756, generator_adv_loss=1.958, generator_feat_match_loss=4.989, over 3293.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 04:06:15,460 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 04:06:23,525 INFO [train.py:591] (2/6) Epoch 507, validation: discriminator_loss=2.725, discriminator_real_loss=1.389, discriminator_fake_loss=1.335, generator_loss=26.94, generator_mel_loss=18.08, generator_kl_loss=1.132, generator_dur_loss=1.809, generator_adv_loss=1.812, generator_feat_match_loss=4.108, over 100.00 samples.
2024-03-14 04:06:23,526 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 04:08:41,879 INFO [train.py:527] (2/6) Epoch 507, batch 106, global_batch_idx: 62850, batch size: 31, loss[discriminator_loss=2.773, discriminator_real_loss=1.432, discriminator_fake_loss=1.341, generator_loss=27.25, generator_mel_loss=18.41, generator_kl_loss=1.278, generator_dur_loss=1.749, generator_adv_loss=1.973, generator_feat_match_loss=3.843, over 31.00 samples.], tot_loss[discriminator_loss=2.719, discriminator_real_loss=1.377, discriminator_fake_loss=1.341, generator_loss=28.06, generator_mel_loss=17.95, generator_kl_loss=1.389, generator_dur_loss=1.759, generator_adv_loss=1.96, generator_feat_match_loss=5.002, over 6144.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 04:09:30,212 INFO [train.py:919] (2/6) Start epoch 508
2024-03-14 04:11:20,132 INFO [train.py:527] (2/6) Epoch 508, batch 32, global_batch_idx: 62900, batch size: 70, loss[discriminator_loss=2.667, discriminator_real_loss=1.336, discriminator_fake_loss=1.331, generator_loss=29.51, generator_mel_loss=18.44, generator_kl_loss=1.452, generator_dur_loss=1.844, generator_adv_loss=1.858, generator_feat_match_loss=5.913, over 70.00 samples.], tot_loss[discriminator_loss=2.718, discriminator_real_loss=1.369, discriminator_fake_loss=1.349, generator_loss=28.21, generator_mel_loss=18, generator_kl_loss=1.4, generator_dur_loss=1.755, generator_adv_loss=1.972, generator_feat_match_loss=5.09, over 1902.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 04:13:42,034 INFO [train.py:527] (2/6) Epoch 508, batch 82, global_batch_idx: 62950, batch size: 68, loss[discriminator_loss=2.735, discriminator_real_loss=1.412, discriminator_fake_loss=1.323, generator_loss=27.6, generator_mel_loss=18.02, generator_kl_loss=1.442, generator_dur_loss=1.746, generator_adv_loss=1.871, generator_feat_match_loss=4.523, over 68.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.37, discriminator_fake_loss=1.347, generator_loss=28.19, generator_mel_loss=18.05, generator_kl_loss=1.419, generator_dur_loss=1.747, generator_adv_loss=1.957, generator_feat_match_loss=5.022, over 4481.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 04:15:36,603 INFO [train.py:919] (2/6) Start epoch 509
2024-03-14 04:16:22,871 INFO [train.py:527] (2/6) Epoch 509, batch 8, global_batch_idx: 63000, batch size: 72, loss[discriminator_loss=2.719, discriminator_real_loss=1.41, discriminator_fake_loss=1.308, generator_loss=27.37, generator_mel_loss=17.74, generator_kl_loss=1.44, generator_dur_loss=1.723, generator_adv_loss=1.839, generator_feat_match_loss=4.635, over 72.00 samples.], tot_loss[discriminator_loss=2.688, discriminator_real_loss=1.377, discriminator_fake_loss=1.311, generator_loss=28.09, generator_mel_loss=17.88, generator_kl_loss=1.384, generator_dur_loss=1.773, generator_adv_loss=1.987, generator_feat_match_loss=5.068, over 582.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 04:16:22,912 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 04:16:30,826 INFO [train.py:591] (2/6) Epoch 509, validation: discriminator_loss=2.748, discriminator_real_loss=1.351, discriminator_fake_loss=1.397, generator_loss=26.76, generator_mel_loss=17.9, generator_kl_loss=1.346, generator_dur_loss=1.796, generator_adv_loss=1.768, generator_feat_match_loss=3.948, over 100.00 samples.
2024-03-14 04:16:30,831 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 04:18:51,761 INFO [train.py:527] (2/6) Epoch 509, batch 58, global_batch_idx: 63050, batch size: 62, loss[discriminator_loss=2.74, discriminator_real_loss=1.26, discriminator_fake_loss=1.479, generator_loss=28.01, generator_mel_loss=17.61, generator_kl_loss=1.495, generator_dur_loss=1.715, generator_adv_loss=1.957, generator_feat_match_loss=5.23, over 62.00 samples.], tot_loss[discriminator_loss=2.712, discriminator_real_loss=1.37, discriminator_fake_loss=1.342, generator_loss=28.16, generator_mel_loss=18.02, generator_kl_loss=1.424, generator_dur_loss=1.737, generator_adv_loss=1.958, generator_feat_match_loss=5.027, over 3245.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 04:21:11,279 INFO [train.py:527] (2/6) Epoch 509, batch 108, global_batch_idx: 63100, batch size: 74, loss[discriminator_loss=2.765, discriminator_real_loss=1.445, discriminator_fake_loss=1.321, generator_loss=27.81, generator_mel_loss=17.97, generator_kl_loss=1.38, generator_dur_loss=1.737, generator_adv_loss=1.831, generator_feat_match_loss=4.895, over 74.00 samples.], tot_loss[discriminator_loss=2.711, discriminator_real_loss=1.372, discriminator_fake_loss=1.339, generator_loss=28.2, generator_mel_loss=18.03, generator_kl_loss=1.413, generator_dur_loss=1.741, generator_adv_loss=1.965, generator_feat_match_loss=5.053, over 6280.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 04:21:55,219 INFO [train.py:919] (2/6) Start epoch 510
2024-03-14 04:23:52,089 INFO [train.py:527] (2/6) Epoch 510, batch 34, global_batch_idx: 63150, batch size: 95, loss[discriminator_loss=2.807, discriminator_real_loss=1.284, discriminator_fake_loss=1.524, generator_loss=27.24, generator_mel_loss=17.31, generator_kl_loss=1.347, generator_dur_loss=1.842, generator_adv_loss=2.054, generator_feat_match_loss=4.681, over 95.00 samples.], tot_loss[discriminator_loss=2.717, discriminator_real_loss=1.364, discriminator_fake_loss=1.353, generator_loss=28.16, generator_mel_loss=18.01, generator_kl_loss=1.414, generator_dur_loss=1.729, generator_adv_loss=1.955, generator_feat_match_loss=5.044, over 2088.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 04:26:11,934 INFO [train.py:527] (2/6) Epoch 510, batch 84, global_batch_idx: 63200, batch size: 70, loss[discriminator_loss=2.69, discriminator_real_loss=1.335, discriminator_fake_loss=1.356, generator_loss=28.12, generator_mel_loss=17.93, generator_kl_loss=1.355, generator_dur_loss=1.824, generator_adv_loss=2.059, generator_feat_match_loss=4.953, over 70.00 samples.], tot_loss[discriminator_loss=2.714, discriminator_real_loss=1.364, discriminator_fake_loss=1.35, generator_loss=28.12, generator_mel_loss=17.97, generator_kl_loss=1.413, generator_dur_loss=1.749, generator_adv_loss=1.95, generator_feat_match_loss=5.037, over 5016.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 04:26:11,936 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 04:26:21,111 INFO [train.py:591] (2/6) Epoch 510, validation: discriminator_loss=2.738, discriminator_real_loss=1.447, discriminator_fake_loss=1.291, generator_loss=26.77, generator_mel_loss=17.99, generator_kl_loss=1.289, generator_dur_loss=1.815, generator_adv_loss=1.943, generator_feat_match_loss=3.734, over 100.00 samples.
2024-03-14 04:26:21,112 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 04:28:09,866 INFO [train.py:919] (2/6) Start epoch 511
2024-03-14 04:29:03,939 INFO [train.py:527] (2/6) Epoch 511, batch 10, global_batch_idx: 63250, batch size: 44, loss[discriminator_loss=2.777, discriminator_real_loss=1.334, discriminator_fake_loss=1.442, generator_loss=28.01, generator_mel_loss=17.76, generator_kl_loss=1.495, generator_dur_loss=1.7, generator_adv_loss=1.997, generator_feat_match_loss=5.065, over 44.00 samples.], tot_loss[discriminator_loss=2.696, discriminator_real_loss=1.373, discriminator_fake_loss=1.323, generator_loss=28.08, generator_mel_loss=17.91, generator_kl_loss=1.378, generator_dur_loss=1.751, generator_adv_loss=1.983, generator_feat_match_loss=5.057, over 624.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 04:31:24,653 INFO [train.py:527] (2/6) Epoch 511, batch 60, global_batch_idx: 63300, batch size: 39, loss[discriminator_loss=2.713, discriminator_real_loss=1.39, discriminator_fake_loss=1.323, generator_loss=27.79, generator_mel_loss=17.76, generator_kl_loss=1.442, generator_dur_loss=1.707, generator_adv_loss=1.858, generator_feat_match_loss=5.021, over 39.00 samples.], tot_loss[discriminator_loss=2.709, discriminator_real_loss=1.373, discriminator_fake_loss=1.336, generator_loss=28.09, generator_mel_loss=17.96, generator_kl_loss=1.401, generator_dur_loss=1.764, generator_adv_loss=1.963, generator_feat_match_loss=5.006, over 3563.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 04:33:43,487 INFO [train.py:527] (2/6) Epoch 511, batch 110, global_batch_idx: 63350, batch size: 13, loss[discriminator_loss=2.624, discriminator_real_loss=1.234, discriminator_fake_loss=1.39, generator_loss=31.47, generator_mel_loss=18.98, generator_kl_loss=1.898, generator_dur_loss=1.603, generator_adv_loss=2.077, generator_feat_match_loss=6.906, over 13.00 samples.], tot_loss[discriminator_loss=2.706, discriminator_real_loss=1.37, discriminator_fake_loss=1.336, generator_loss=28.14, generator_mel_loss=17.97, generator_kl_loss=1.405, generator_dur_loss=1.76, generator_adv_loss=1.957, generator_feat_match_loss=5.042, over 6234.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 04:34:19,307 INFO [train.py:919] (2/6) Start epoch 512
2024-03-14 04:36:22,521 INFO [train.py:527] (2/6) Epoch 512, batch 36, global_batch_idx: 63400, batch size: 45, loss[discriminator_loss=2.748, discriminator_real_loss=1.393, discriminator_fake_loss=1.355, generator_loss=28.36, generator_mel_loss=17.81, generator_kl_loss=1.511, generator_dur_loss=1.689, generator_adv_loss=2.005, generator_feat_match_loss=5.337, over 45.00 samples.], tot_loss[discriminator_loss=2.712, discriminator_real_loss=1.365, discriminator_fake_loss=1.347, generator_loss=28.33, generator_mel_loss=18.07, generator_kl_loss=1.449, generator_dur_loss=1.754, generator_adv_loss=1.963, generator_feat_match_loss=5.092, over 2000.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 04:36:22,523 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 04:36:30,269 INFO [train.py:591] (2/6) Epoch 512, validation: discriminator_loss=2.746, discriminator_real_loss=1.444, discriminator_fake_loss=1.302, generator_loss=27.11, generator_mel_loss=18.15, generator_kl_loss=1.337, generator_dur_loss=1.83, generator_adv_loss=1.897, generator_feat_match_loss=3.894, over 100.00 samples.
2024-03-14 04:36:30,270 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 04:38:46,883 INFO [train.py:527] (2/6) Epoch 512, batch 86, global_batch_idx: 63450, batch size: 53, loss[discriminator_loss=2.751, discriminator_real_loss=1.469, discriminator_fake_loss=1.282, generator_loss=27.31, generator_mel_loss=17.63, generator_kl_loss=1.5, generator_dur_loss=1.684, generator_adv_loss=1.919, generator_feat_match_loss=4.583, over 53.00 samples.], tot_loss[discriminator_loss=2.717, discriminator_real_loss=1.372, discriminator_fake_loss=1.345, generator_loss=28.24, generator_mel_loss=18.02, generator_kl_loss=1.439, generator_dur_loss=1.756, generator_adv_loss=1.957, generator_feat_match_loss=5.067, over 4637.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 04:40:33,512 INFO [train.py:919] (2/6) Start epoch 513
2024-03-14 04:41:33,124 INFO [train.py:527] (2/6) Epoch 513, batch 12, global_batch_idx: 63500, batch size: 42, loss[discriminator_loss=2.75, discriminator_real_loss=1.451, discriminator_fake_loss=1.299, generator_loss=27.78, generator_mel_loss=18.23, generator_kl_loss=1.426, generator_dur_loss=1.755, generator_adv_loss=1.795, generator_feat_match_loss=4.577, over 42.00 samples.], tot_loss[discriminator_loss=2.71, discriminator_real_loss=1.377, discriminator_fake_loss=1.333, generator_loss=28.2, generator_mel_loss=17.99, generator_kl_loss=1.354, generator_dur_loss=1.791, generator_adv_loss=1.948, generator_feat_match_loss=5.119, over 810.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 04:43:53,187 INFO [train.py:527] (2/6) Epoch 513, batch 62, global_batch_idx: 63550, batch size: 80, loss[discriminator_loss=2.714, discriminator_real_loss=1.401, discriminator_fake_loss=1.313, generator_loss=28.22, generator_mel_loss=17.88, generator_kl_loss=1.43, generator_dur_loss=1.806, generator_adv_loss=1.924, generator_feat_match_loss=5.175, over 80.00 samples.], tot_loss[discriminator_loss=2.721, discriminator_real_loss=1.38, discriminator_fake_loss=1.341, generator_loss=28.13, generator_mel_loss=17.99, generator_kl_loss=1.398, generator_dur_loss=1.772, generator_adv_loss=1.939, generator_feat_match_loss=5.025, over 3711.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 04:46:10,248 INFO [train.py:527] (2/6) Epoch 513, batch 112, global_batch_idx: 63600, batch size: 39, loss[discriminator_loss=2.655, discriminator_real_loss=1.349, discriminator_fake_loss=1.306, generator_loss=30.01, generator_mel_loss=18.91, generator_kl_loss=1.602, generator_dur_loss=1.673, generator_adv_loss=2.002, generator_feat_match_loss=5.822, over 39.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.374, discriminator_fake_loss=1.341, generator_loss=28.19, generator_mel_loss=17.98, generator_kl_loss=1.409, generator_dur_loss=1.767, generator_adv_loss=1.976, generator_feat_match_loss=5.056, over 6371.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 04:46:10,249 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 04:46:19,192 INFO [train.py:591] (2/6) Epoch 513, validation: discriminator_loss=2.719, discriminator_real_loss=1.431, discriminator_fake_loss=1.288, generator_loss=27.09, generator_mel_loss=18.16, generator_kl_loss=1.158, generator_dur_loss=1.847, generator_adv_loss=1.954, generator_feat_match_loss=3.979, over 100.00 samples.
2024-03-14 04:46:19,193 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 04:46:48,271 INFO [train.py:919] (2/6) Start epoch 514
2024-03-14 04:48:59,902 INFO [train.py:527] (2/6) Epoch 514, batch 38, global_batch_idx: 63650, batch size: 53, loss[discriminator_loss=2.654, discriminator_real_loss=1.301, discriminator_fake_loss=1.354, generator_loss=28.6, generator_mel_loss=18.39, generator_kl_loss=1.406, generator_dur_loss=1.73, generator_adv_loss=1.984, generator_feat_match_loss=5.094, over 53.00 samples.], tot_loss[discriminator_loss=2.711, discriminator_real_loss=1.375, discriminator_fake_loss=1.336, generator_loss=28.15, generator_mel_loss=17.95, generator_kl_loss=1.395, generator_dur_loss=1.772, generator_adv_loss=1.96, generator_feat_match_loss=5.071, over 2295.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 04:51:21,670 INFO [train.py:527] (2/6) Epoch 514, batch 88, global_batch_idx: 63700, batch size: 52, loss[discriminator_loss=2.681, discriminator_real_loss=1.319, discriminator_fake_loss=1.362, generator_loss=28.37, generator_mel_loss=17.95, generator_kl_loss=1.613, generator_dur_loss=1.677, generator_adv_loss=1.819, generator_feat_match_loss=5.316, over 52.00 samples.], tot_loss[discriminator_loss=2.708, discriminator_real_loss=1.369, discriminator_fake_loss=1.339, generator_loss=28.27, generator_mel_loss=18.02, generator_kl_loss=1.429, generator_dur_loss=1.763, generator_adv_loss=1.952, generator_feat_match_loss=5.109, over 5135.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 04:52:58,791 INFO [train.py:919] (2/6) Start epoch 515
2024-03-14 04:54:00,980 INFO [train.py:527] (2/6) Epoch 515, batch 14, global_batch_idx: 63750, batch size: 66, loss[discriminator_loss=2.736, discriminator_real_loss=1.461, discriminator_fake_loss=1.275, generator_loss=27.39, generator_mel_loss=17.76, generator_kl_loss=1.183, generator_dur_loss=1.769, generator_adv_loss=1.952, generator_feat_match_loss=4.729, over 66.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.362, discriminator_fake_loss=1.354, generator_loss=28.09, generator_mel_loss=18.1, generator_kl_loss=1.377, generator_dur_loss=1.737, generator_adv_loss=1.955, generator_feat_match_loss=4.927, over 851.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 04:56:20,928 INFO [train.py:527] (2/6) Epoch 515, batch 64, global_batch_idx: 63800, batch size: 55, loss[discriminator_loss=2.651, discriminator_real_loss=1.387, discriminator_fake_loss=1.264, generator_loss=29.32, generator_mel_loss=18.41, generator_kl_loss=1.574, generator_dur_loss=1.727, generator_adv_loss=2.081, generator_feat_match_loss=5.528, over 55.00 samples.], tot_loss[discriminator_loss=2.719, discriminator_real_loss=1.369, discriminator_fake_loss=1.35, generator_loss=28.18, generator_mel_loss=18.02, generator_kl_loss=1.428, generator_dur_loss=1.754, generator_adv_loss=1.95, generator_feat_match_loss=5.029, over 3657.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 04:56:20,929 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 04:56:28,858 INFO [train.py:591] (2/6) Epoch 515, validation: discriminator_loss=2.737, discriminator_real_loss=1.473, discriminator_fake_loss=1.264, generator_loss=27.6, generator_mel_loss=18.64, generator_kl_loss=1.278, generator_dur_loss=1.822, generator_adv_loss=1.891, generator_feat_match_loss=3.967, over 100.00 samples.
2024-03-14 04:56:28,859 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 04:58:48,091 INFO [train.py:527] (2/6) Epoch 515, batch 114, global_batch_idx: 63850, batch size: 25, loss[discriminator_loss=2.707, discriminator_real_loss=1.362, discriminator_fake_loss=1.344, generator_loss=30.63, generator_mel_loss=19.07, generator_kl_loss=1.781, generator_dur_loss=1.579, generator_adv_loss=1.909, generator_feat_match_loss=6.287, over 25.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.372, discriminator_fake_loss=1.343, generator_loss=28.2, generator_mel_loss=18.01, generator_kl_loss=1.429, generator_dur_loss=1.753, generator_adv_loss=1.956, generator_feat_match_loss=5.048, over 6548.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 04:59:15,647 INFO [train.py:919] (2/6) Start epoch 516
2024-03-14 05:01:29,174 INFO [train.py:527] (2/6) Epoch 516, batch 40, global_batch_idx: 63900, batch size: 83, loss[discriminator_loss=2.73, discriminator_real_loss=1.419, discriminator_fake_loss=1.312, generator_loss=27.72, generator_mel_loss=18.2, generator_kl_loss=1.306, generator_dur_loss=1.864, generator_adv_loss=1.824, generator_feat_match_loss=4.532, over 83.00 samples.], tot_loss[discriminator_loss=2.704, discriminator_real_loss=1.369, discriminator_fake_loss=1.336, generator_loss=28.17, generator_mel_loss=17.97, generator_kl_loss=1.412, generator_dur_loss=1.747, generator_adv_loss=1.953, generator_feat_match_loss=5.095, over 2315.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 05:03:47,512 INFO [train.py:527] (2/6) Epoch 516, batch 90, global_batch_idx: 63950, batch size: 56, loss[discriminator_loss=2.755, discriminator_real_loss=1.424, discriminator_fake_loss=1.331, generator_loss=28.34, generator_mel_loss=17.91, generator_kl_loss=1.62, generator_dur_loss=1.731, generator_adv_loss=1.941, generator_feat_match_loss=5.135, over 56.00 samples.], tot_loss[discriminator_loss=2.711, discriminator_real_loss=1.372, discriminator_fake_loss=1.34, generator_loss=28.12, generator_mel_loss=17.95, generator_kl_loss=1.429, generator_dur_loss=1.751, generator_adv_loss=1.947, generator_feat_match_loss=5.037, over 5135.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 05:05:19,848 INFO [train.py:919] (2/6) Start epoch 517
2024-03-14 05:06:28,758 INFO [train.py:527] (2/6) Epoch 517, batch 16, global_batch_idx: 64000, batch size: 47, loss[discriminator_loss=2.735, discriminator_real_loss=1.41, discriminator_fake_loss=1.324, generator_loss=27.3, generator_mel_loss=17.72, generator_kl_loss=1.591, generator_dur_loss=1.693, generator_adv_loss=1.912, generator_feat_match_loss=4.385, over 47.00 samples.], tot_loss[discriminator_loss=2.701, discriminator_real_loss=1.364, discriminator_fake_loss=1.336, generator_loss=27.99, generator_mel_loss=17.87, generator_kl_loss=1.404, generator_dur_loss=1.738, generator_adv_loss=1.936, generator_feat_match_loss=5.04, over 963.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 05:06:28,759 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 05:06:36,606 INFO [train.py:591] (2/6) Epoch 517, validation: discriminator_loss=2.771, discriminator_real_loss=1.411, discriminator_fake_loss=1.36, generator_loss=26.76, generator_mel_loss=17.97, generator_kl_loss=1.252, generator_dur_loss=1.828, generator_adv_loss=1.814, generator_feat_match_loss=3.899, over 100.00 samples.
2024-03-14 05:06:36,608 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 05:08:59,616 INFO [train.py:527] (2/6) Epoch 517, batch 66, global_batch_idx: 64050, batch size: 74, loss[discriminator_loss=2.699, discriminator_real_loss=1.347, discriminator_fake_loss=1.352, generator_loss=27.74, generator_mel_loss=18.06, generator_kl_loss=1.365, generator_dur_loss=1.782, generator_adv_loss=2.028, generator_feat_match_loss=4.503, over 74.00 samples.], tot_loss[discriminator_loss=2.703, discriminator_real_loss=1.366, discriminator_fake_loss=1.337, generator_loss=28.1, generator_mel_loss=17.9, generator_kl_loss=1.411, generator_dur_loss=1.752, generator_adv_loss=1.957, generator_feat_match_loss=5.088, over 3820.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 05:11:15,921 INFO [train.py:527] (2/6) Epoch 517, batch 116, global_batch_idx: 64100, batch size: 44, loss[discriminator_loss=2.717, discriminator_real_loss=1.377, discriminator_fake_loss=1.34, generator_loss=28.72, generator_mel_loss=18.47, generator_kl_loss=1.474, generator_dur_loss=1.683, generator_adv_loss=1.894, generator_feat_match_loss=5.194, over 44.00 samples.], tot_loss[discriminator_loss=2.713, discriminator_real_loss=1.37, discriminator_fake_loss=1.343, generator_loss=28.11, generator_mel_loss=17.93, generator_kl_loss=1.41, generator_dur_loss=1.759, generator_adv_loss=1.949, generator_feat_match_loss=5.062, over 6870.00 samples.], cur_lr_g: 1.88e-04, cur_lr_d: 1.88e-04, 
2024-03-14 05:11:37,903 INFO [train.py:919] (2/6) Start epoch 518
2024-03-14 05:13:58,916 INFO [train.py:527] (2/6) Epoch 518, batch 42, global_batch_idx: 64150, batch size: 58, loss[discriminator_loss=2.715, discriminator_real_loss=1.454, discriminator_fake_loss=1.261, generator_loss=27, generator_mel_loss=17.78, generator_kl_loss=1.252, generator_dur_loss=1.752, generator_adv_loss=1.815, generator_feat_match_loss=4.404, over 58.00 samples.], tot_loss[discriminator_loss=2.71, discriminator_real_loss=1.378, discriminator_fake_loss=1.332, generator_loss=28.12, generator_mel_loss=17.92, generator_kl_loss=1.397, generator_dur_loss=1.753, generator_adv_loss=1.942, generator_feat_match_loss=5.104, over 2455.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 05:16:18,578 INFO [train.py:527] (2/6) Epoch 518, batch 92, global_batch_idx: 64200, batch size: 39, loss[discriminator_loss=2.708, discriminator_real_loss=1.425, discriminator_fake_loss=1.283, generator_loss=28.83, generator_mel_loss=18.43, generator_kl_loss=1.45, generator_dur_loss=1.719, generator_adv_loss=1.893, generator_feat_match_loss=5.341, over 39.00 samples.], tot_loss[discriminator_loss=2.712, discriminator_real_loss=1.377, discriminator_fake_loss=1.335, generator_loss=28.14, generator_mel_loss=17.94, generator_kl_loss=1.392, generator_dur_loss=1.765, generator_adv_loss=1.952, generator_feat_match_loss=5.093, over 5395.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 05:16:18,580 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 05:16:27,419 INFO [train.py:591] (2/6) Epoch 518, validation: discriminator_loss=2.75, discriminator_real_loss=1.371, discriminator_fake_loss=1.379, generator_loss=27.32, generator_mel_loss=18.42, generator_kl_loss=1.186, generator_dur_loss=1.828, generator_adv_loss=1.755, generator_feat_match_loss=4.132, over 100.00 samples.
2024-03-14 05:16:27,421 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 05:17:52,779 INFO [train.py:919] (2/6) Start epoch 519
2024-03-14 05:19:05,983 INFO [train.py:527] (2/6) Epoch 519, batch 18, global_batch_idx: 64250, batch size: 42, loss[discriminator_loss=2.669, discriminator_real_loss=1.342, discriminator_fake_loss=1.327, generator_loss=28.21, generator_mel_loss=18.11, generator_kl_loss=1.617, generator_dur_loss=1.657, generator_adv_loss=1.995, generator_feat_match_loss=4.827, over 42.00 samples.], tot_loss[discriminator_loss=2.692, discriminator_real_loss=1.357, discriminator_fake_loss=1.335, generator_loss=28.16, generator_mel_loss=17.97, generator_kl_loss=1.411, generator_dur_loss=1.754, generator_adv_loss=1.943, generator_feat_match_loss=5.083, over 1050.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 05:21:24,503 INFO [train.py:527] (2/6) Epoch 519, batch 68, global_batch_idx: 64300, batch size: 50, loss[discriminator_loss=2.747, discriminator_real_loss=1.333, discriminator_fake_loss=1.414, generator_loss=28.66, generator_mel_loss=18.11, generator_kl_loss=1.517, generator_dur_loss=1.677, generator_adv_loss=1.944, generator_feat_match_loss=5.411, over 50.00 samples.], tot_loss[discriminator_loss=2.705, discriminator_real_loss=1.369, discriminator_fake_loss=1.336, generator_loss=28.23, generator_mel_loss=17.96, generator_kl_loss=1.438, generator_dur_loss=1.755, generator_adv_loss=1.958, generator_feat_match_loss=5.118, over 3794.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 05:23:42,064 INFO [train.py:527] (2/6) Epoch 519, batch 118, global_batch_idx: 64350, batch size: 83, loss[discriminator_loss=2.637, discriminator_real_loss=1.341, discriminator_fake_loss=1.296, generator_loss=28.81, generator_mel_loss=17.76, generator_kl_loss=1.347, generator_dur_loss=1.814, generator_adv_loss=2.187, generator_feat_match_loss=5.708, over 83.00 samples.], tot_loss[discriminator_loss=2.706, discriminator_real_loss=1.365, discriminator_fake_loss=1.341, generator_loss=28.27, generator_mel_loss=17.96, generator_kl_loss=1.427, generator_dur_loss=1.763, generator_adv_loss=1.983, generator_feat_match_loss=5.14, over 6699.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 05:23:58,220 INFO [train.py:919] (2/6) Start epoch 520
2024-03-14 05:26:22,339 INFO [train.py:527] (2/6) Epoch 520, batch 44, global_batch_idx: 64400, batch size: 56, loss[discriminator_loss=2.682, discriminator_real_loss=1.344, discriminator_fake_loss=1.338, generator_loss=28.34, generator_mel_loss=17.91, generator_kl_loss=1.392, generator_dur_loss=1.741, generator_adv_loss=1.976, generator_feat_match_loss=5.317, over 56.00 samples.], tot_loss[discriminator_loss=2.713, discriminator_real_loss=1.371, discriminator_fake_loss=1.341, generator_loss=28.12, generator_mel_loss=18.01, generator_kl_loss=1.419, generator_dur_loss=1.756, generator_adv_loss=1.944, generator_feat_match_loss=4.992, over 2613.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 05:26:22,341 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 05:26:30,251 INFO [train.py:591] (2/6) Epoch 520, validation: discriminator_loss=2.739, discriminator_real_loss=1.432, discriminator_fake_loss=1.306, generator_loss=27.31, generator_mel_loss=18.27, generator_kl_loss=1.261, generator_dur_loss=1.832, generator_adv_loss=1.899, generator_feat_match_loss=4.044, over 100.00 samples.
2024-03-14 05:26:30,253 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 05:28:48,673 INFO [train.py:527] (2/6) Epoch 520, batch 94, global_batch_idx: 64450, batch size: 52, loss[discriminator_loss=2.745, discriminator_real_loss=1.446, discriminator_fake_loss=1.3, generator_loss=27.45, generator_mel_loss=17.69, generator_kl_loss=1.437, generator_dur_loss=1.752, generator_adv_loss=1.847, generator_feat_match_loss=4.72, over 52.00 samples.], tot_loss[discriminator_loss=2.71, discriminator_real_loss=1.373, discriminator_fake_loss=1.337, generator_loss=28.11, generator_mel_loss=17.98, generator_kl_loss=1.41, generator_dur_loss=1.755, generator_adv_loss=1.945, generator_feat_match_loss=5.019, over 5486.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 05:30:10,008 INFO [train.py:919] (2/6) Start epoch 521
2024-03-14 05:31:30,895 INFO [train.py:527] (2/6) Epoch 521, batch 20, global_batch_idx: 64500, batch size: 68, loss[discriminator_loss=2.718, discriminator_real_loss=1.364, discriminator_fake_loss=1.353, generator_loss=28.83, generator_mel_loss=17.76, generator_kl_loss=1.438, generator_dur_loss=1.794, generator_adv_loss=2.066, generator_feat_match_loss=5.767, over 68.00 samples.], tot_loss[discriminator_loss=2.704, discriminator_real_loss=1.363, discriminator_fake_loss=1.341, generator_loss=28.51, generator_mel_loss=18.15, generator_kl_loss=1.48, generator_dur_loss=1.741, generator_adv_loss=1.979, generator_feat_match_loss=5.151, over 1100.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 05:33:50,000 INFO [train.py:527] (2/6) Epoch 521, batch 70, global_batch_idx: 64550, batch size: 47, loss[discriminator_loss=2.739, discriminator_real_loss=1.422, discriminator_fake_loss=1.317, generator_loss=27.75, generator_mel_loss=17.88, generator_kl_loss=1.32, generator_dur_loss=1.698, generator_adv_loss=2.105, generator_feat_match_loss=4.746, over 47.00 samples.], tot_loss[discriminator_loss=2.707, discriminator_real_loss=1.366, discriminator_fake_loss=1.341, generator_loss=28.22, generator_mel_loss=18.02, generator_kl_loss=1.431, generator_dur_loss=1.742, generator_adv_loss=1.956, generator_feat_match_loss=5.074, over 3930.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 05:36:07,751 INFO [train.py:527] (2/6) Epoch 521, batch 120, global_batch_idx: 64600, batch size: 25, loss[discriminator_loss=2.702, discriminator_real_loss=1.394, discriminator_fake_loss=1.308, generator_loss=28.83, generator_mel_loss=18.31, generator_kl_loss=1.559, generator_dur_loss=1.548, generator_adv_loss=2.136, generator_feat_match_loss=5.28, over 25.00 samples.], tot_loss[discriminator_loss=2.709, discriminator_real_loss=1.363, discriminator_fake_loss=1.346, generator_loss=28.24, generator_mel_loss=18.03, generator_kl_loss=1.423, generator_dur_loss=1.748, generator_adv_loss=1.958, generator_feat_match_loss=5.083, over 6701.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 05:36:07,753 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 05:36:16,582 INFO [train.py:591] (2/6) Epoch 521, validation: discriminator_loss=2.667, discriminator_real_loss=1.456, discriminator_fake_loss=1.211, generator_loss=27.99, generator_mel_loss=18.52, generator_kl_loss=1.214, generator_dur_loss=1.819, generator_adv_loss=2.026, generator_feat_match_loss=4.408, over 100.00 samples.
2024-03-14 05:36:16,583 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 05:36:25,756 INFO [train.py:919] (2/6) Start epoch 522
2024-03-14 05:38:57,167 INFO [train.py:527] (2/6) Epoch 522, batch 46, global_batch_idx: 64650, batch size: 15, loss[discriminator_loss=2.773, discriminator_real_loss=1.442, discriminator_fake_loss=1.331, generator_loss=27.78, generator_mel_loss=18.48, generator_kl_loss=1.739, generator_dur_loss=1.631, generator_adv_loss=1.88, generator_feat_match_loss=4.056, over 15.00 samples.], tot_loss[discriminator_loss=2.708, discriminator_real_loss=1.378, discriminator_fake_loss=1.33, generator_loss=28.13, generator_mel_loss=17.93, generator_kl_loss=1.404, generator_dur_loss=1.767, generator_adv_loss=1.955, generator_feat_match_loss=5.077, over 2682.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 05:41:15,684 INFO [train.py:527] (2/6) Epoch 522, batch 96, global_batch_idx: 64700, batch size: 31, loss[discriminator_loss=2.703, discriminator_real_loss=1.41, discriminator_fake_loss=1.293, generator_loss=28.12, generator_mel_loss=17.66, generator_kl_loss=1.632, generator_dur_loss=1.728, generator_adv_loss=1.854, generator_feat_match_loss=5.241, over 31.00 samples.], tot_loss[discriminator_loss=2.71, discriminator_real_loss=1.376, discriminator_fake_loss=1.334, generator_loss=28.21, generator_mel_loss=17.99, generator_kl_loss=1.416, generator_dur_loss=1.758, generator_adv_loss=1.96, generator_feat_match_loss=5.091, over 5290.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 05:42:30,619 INFO [train.py:919] (2/6) Start epoch 523
2024-03-14 05:43:53,432 INFO [train.py:527] (2/6) Epoch 523, batch 22, global_batch_idx: 64750, batch size: 66, loss[discriminator_loss=2.756, discriminator_real_loss=1.443, discriminator_fake_loss=1.313, generator_loss=27.3, generator_mel_loss=17.58, generator_kl_loss=1.32, generator_dur_loss=1.812, generator_adv_loss=1.891, generator_feat_match_loss=4.703, over 66.00 samples.], tot_loss[discriminator_loss=2.723, discriminator_real_loss=1.373, discriminator_fake_loss=1.35, generator_loss=28.08, generator_mel_loss=17.92, generator_kl_loss=1.428, generator_dur_loss=1.747, generator_adv_loss=1.936, generator_feat_match_loss=5.046, over 1329.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 05:46:13,636 INFO [train.py:527] (2/6) Epoch 523, batch 72, global_batch_idx: 64800, batch size: 72, loss[discriminator_loss=2.685, discriminator_real_loss=1.357, discriminator_fake_loss=1.328, generator_loss=28.73, generator_mel_loss=18, generator_kl_loss=1.405, generator_dur_loss=1.804, generator_adv_loss=1.928, generator_feat_match_loss=5.592, over 72.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.366, discriminator_fake_loss=1.349, generator_loss=28.14, generator_mel_loss=17.96, generator_kl_loss=1.398, generator_dur_loss=1.769, generator_adv_loss=1.948, generator_feat_match_loss=5.069, over 4557.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 05:46:13,637 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 05:46:21,897 INFO [train.py:591] (2/6) Epoch 523, validation: discriminator_loss=2.77, discriminator_real_loss=1.417, discriminator_fake_loss=1.352, generator_loss=26.84, generator_mel_loss=18.17, generator_kl_loss=1.277, generator_dur_loss=1.817, generator_adv_loss=1.897, generator_feat_match_loss=3.677, over 100.00 samples.
2024-03-14 05:46:21,898 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 05:48:40,686 INFO [train.py:527] (2/6) Epoch 523, batch 122, global_batch_idx: 64850, batch size: 42, loss[discriminator_loss=2.698, discriminator_real_loss=1.29, discriminator_fake_loss=1.408, generator_loss=28.84, generator_mel_loss=18.26, generator_kl_loss=1.607, generator_dur_loss=1.655, generator_adv_loss=2.012, generator_feat_match_loss=5.306, over 42.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.371, discriminator_fake_loss=1.345, generator_loss=28.17, generator_mel_loss=17.98, generator_kl_loss=1.407, generator_dur_loss=1.761, generator_adv_loss=1.949, generator_feat_match_loss=5.076, over 7332.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 05:48:45,645 INFO [train.py:919] (2/6) Start epoch 524
2024-03-14 05:51:24,146 INFO [train.py:527] (2/6) Epoch 524, batch 48, global_batch_idx: 64900, batch size: 42, loss[discriminator_loss=2.693, discriminator_real_loss=1.382, discriminator_fake_loss=1.311, generator_loss=28.37, generator_mel_loss=17.93, generator_kl_loss=1.536, generator_dur_loss=1.68, generator_adv_loss=2.052, generator_feat_match_loss=5.175, over 42.00 samples.], tot_loss[discriminator_loss=2.699, discriminator_real_loss=1.371, discriminator_fake_loss=1.328, generator_loss=28.33, generator_mel_loss=17.92, generator_kl_loss=1.413, generator_dur_loss=1.758, generator_adv_loss=2.007, generator_feat_match_loss=5.229, over 2909.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 05:53:42,488 INFO [train.py:527] (2/6) Epoch 524, batch 98, global_batch_idx: 64950, batch size: 47, loss[discriminator_loss=2.718, discriminator_real_loss=1.293, discriminator_fake_loss=1.425, generator_loss=28.52, generator_mel_loss=18.24, generator_kl_loss=1.521, generator_dur_loss=1.678, generator_adv_loss=2.079, generator_feat_match_loss=4.999, over 47.00 samples.], tot_loss[discriminator_loss=2.703, discriminator_real_loss=1.369, discriminator_fake_loss=1.334, generator_loss=28.34, generator_mel_loss=17.98, generator_kl_loss=1.446, generator_dur_loss=1.74, generator_adv_loss=1.979, generator_feat_match_loss=5.197, over 5623.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 05:54:51,697 INFO [train.py:919] (2/6) Start epoch 525
2024-03-14 05:56:19,696 INFO [train.py:527] (2/6) Epoch 525, batch 24, global_batch_idx: 65000, batch size: 42, loss[discriminator_loss=2.72, discriminator_real_loss=1.394, discriminator_fake_loss=1.326, generator_loss=27.63, generator_mel_loss=18.1, generator_kl_loss=1.348, generator_dur_loss=1.681, generator_adv_loss=1.967, generator_feat_match_loss=4.533, over 42.00 samples.], tot_loss[discriminator_loss=2.722, discriminator_real_loss=1.384, discriminator_fake_loss=1.338, generator_loss=28.03, generator_mel_loss=17.9, generator_kl_loss=1.402, generator_dur_loss=1.752, generator_adv_loss=1.946, generator_feat_match_loss=5.026, over 1411.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 05:56:19,698 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 05:56:27,761 INFO [train.py:591] (2/6) Epoch 525, validation: discriminator_loss=2.767, discriminator_real_loss=1.462, discriminator_fake_loss=1.305, generator_loss=27.39, generator_mel_loss=18.51, generator_kl_loss=1.305, generator_dur_loss=1.834, generator_adv_loss=1.915, generator_feat_match_loss=3.833, over 100.00 samples.
2024-03-14 05:56:27,762 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 05:58:47,362 INFO [train.py:527] (2/6) Epoch 525, batch 74, global_batch_idx: 65050, batch size: 64, loss[discriminator_loss=2.678, discriminator_real_loss=1.28, discriminator_fake_loss=1.397, generator_loss=27.84, generator_mel_loss=17.32, generator_kl_loss=1.504, generator_dur_loss=1.75, generator_adv_loss=2.088, generator_feat_match_loss=5.175, over 64.00 samples.], tot_loss[discriminator_loss=2.712, discriminator_real_loss=1.375, discriminator_fake_loss=1.337, generator_loss=28.13, generator_mel_loss=17.95, generator_kl_loss=1.416, generator_dur_loss=1.754, generator_adv_loss=1.956, generator_feat_match_loss=5.061, over 4234.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 06:01:06,798 INFO [train.py:919] (2/6) Start epoch 526
2024-03-14 06:01:28,264 INFO [train.py:527] (2/6) Epoch 526, batch 0, global_batch_idx: 65100, batch size: 47, loss[discriminator_loss=2.777, discriminator_real_loss=1.424, discriminator_fake_loss=1.352, generator_loss=27.4, generator_mel_loss=17.9, generator_kl_loss=1.528, generator_dur_loss=1.687, generator_adv_loss=1.928, generator_feat_match_loss=4.357, over 47.00 samples.], tot_loss[discriminator_loss=2.777, discriminator_real_loss=1.424, discriminator_fake_loss=1.352, generator_loss=27.4, generator_mel_loss=17.9, generator_kl_loss=1.528, generator_dur_loss=1.687, generator_adv_loss=1.928, generator_feat_match_loss=4.357, over 47.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 06:03:46,308 INFO [train.py:527] (2/6) Epoch 526, batch 50, global_batch_idx: 65150, batch size: 83, loss[discriminator_loss=2.703, discriminator_real_loss=1.367, discriminator_fake_loss=1.336, generator_loss=27.71, generator_mel_loss=17.72, generator_kl_loss=1.386, generator_dur_loss=1.86, generator_adv_loss=1.88, generator_feat_match_loss=4.862, over 83.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.378, discriminator_fake_loss=1.337, generator_loss=28.28, generator_mel_loss=18.06, generator_kl_loss=1.442, generator_dur_loss=1.741, generator_adv_loss=1.949, generator_feat_match_loss=5.093, over 2622.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 06:06:02,920 INFO [train.py:527] (2/6) Epoch 526, batch 100, global_batch_idx: 65200, batch size: 61, loss[discriminator_loss=2.691, discriminator_real_loss=1.378, discriminator_fake_loss=1.313, generator_loss=27.87, generator_mel_loss=17.95, generator_kl_loss=1.433, generator_dur_loss=1.772, generator_adv_loss=1.962, generator_feat_match_loss=4.748, over 61.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.378, discriminator_fake_loss=1.342, generator_loss=28.22, generator_mel_loss=18.02, generator_kl_loss=1.433, generator_dur_loss=1.749, generator_adv_loss=1.947, generator_feat_match_loss=5.075, over 5456.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 06:06:02,922 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 06:06:11,752 INFO [train.py:591] (2/6) Epoch 526, validation: discriminator_loss=2.717, discriminator_real_loss=1.44, discriminator_fake_loss=1.277, generator_loss=26.98, generator_mel_loss=18.07, generator_kl_loss=1.209, generator_dur_loss=1.835, generator_adv_loss=1.877, generator_feat_match_loss=3.989, over 100.00 samples.
2024-03-14 06:06:11,753 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 06:07:16,321 INFO [train.py:919] (2/6) Start epoch 527
2024-03-14 06:08:53,162 INFO [train.py:527] (2/6) Epoch 527, batch 26, global_batch_idx: 65250, batch size: 36, loss[discriminator_loss=2.648, discriminator_real_loss=1.301, discriminator_fake_loss=1.348, generator_loss=29.92, generator_mel_loss=18.53, generator_kl_loss=1.583, generator_dur_loss=1.671, generator_adv_loss=1.963, generator_feat_match_loss=6.176, over 36.00 samples.], tot_loss[discriminator_loss=2.698, discriminator_real_loss=1.376, discriminator_fake_loss=1.322, generator_loss=28.2, generator_mel_loss=17.92, generator_kl_loss=1.42, generator_dur_loss=1.786, generator_adv_loss=2.011, generator_feat_match_loss=5.067, over 1662.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 06:11:14,359 INFO [train.py:527] (2/6) Epoch 527, batch 76, global_batch_idx: 65300, batch size: 60, loss[discriminator_loss=2.664, discriminator_real_loss=1.302, discriminator_fake_loss=1.362, generator_loss=29, generator_mel_loss=18.52, generator_kl_loss=1.397, generator_dur_loss=1.754, generator_adv_loss=1.945, generator_feat_match_loss=5.383, over 60.00 samples.], tot_loss[discriminator_loss=2.701, discriminator_real_loss=1.372, discriminator_fake_loss=1.329, generator_loss=28.14, generator_mel_loss=17.91, generator_kl_loss=1.407, generator_dur_loss=1.779, generator_adv_loss=1.98, generator_feat_match_loss=5.062, over 4687.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 06:13:25,125 INFO [train.py:919] (2/6) Start epoch 528
2024-03-14 06:13:54,181 INFO [train.py:527] (2/6) Epoch 528, batch 2, global_batch_idx: 65350, batch size: 64, loss[discriminator_loss=2.69, discriminator_real_loss=1.376, discriminator_fake_loss=1.314, generator_loss=27.98, generator_mel_loss=18.17, generator_kl_loss=1.467, generator_dur_loss=1.754, generator_adv_loss=1.876, generator_feat_match_loss=4.707, over 64.00 samples.], tot_loss[discriminator_loss=2.691, discriminator_real_loss=1.355, discriminator_fake_loss=1.336, generator_loss=28.04, generator_mel_loss=17.89, generator_kl_loss=1.418, generator_dur_loss=1.76, generator_adv_loss=1.945, generator_feat_match_loss=5.027, over 215.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 06:16:12,075 INFO [train.py:527] (2/6) Epoch 528, batch 52, global_batch_idx: 65400, batch size: 56, loss[discriminator_loss=2.704, discriminator_real_loss=1.385, discriminator_fake_loss=1.319, generator_loss=28.64, generator_mel_loss=18.14, generator_kl_loss=1.434, generator_dur_loss=1.724, generator_adv_loss=1.966, generator_feat_match_loss=5.378, over 56.00 samples.], tot_loss[discriminator_loss=2.718, discriminator_real_loss=1.372, discriminator_fake_loss=1.345, generator_loss=28.13, generator_mel_loss=17.94, generator_kl_loss=1.418, generator_dur_loss=1.759, generator_adv_loss=1.955, generator_feat_match_loss=5.062, over 3083.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 06:16:12,077 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 06:16:20,250 INFO [train.py:591] (2/6) Epoch 528, validation: discriminator_loss=2.737, discriminator_real_loss=1.382, discriminator_fake_loss=1.355, generator_loss=28.12, generator_mel_loss=18.68, generator_kl_loss=1.231, generator_dur_loss=1.843, generator_adv_loss=1.888, generator_feat_match_loss=4.475, over 100.00 samples.
2024-03-14 06:16:20,251 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 06:18:39,653 INFO [train.py:527] (2/6) Epoch 528, batch 102, global_batch_idx: 65450, batch size: 39, loss[discriminator_loss=2.684, discriminator_real_loss=1.338, discriminator_fake_loss=1.345, generator_loss=29.25, generator_mel_loss=18.1, generator_kl_loss=1.45, generator_dur_loss=1.696, generator_adv_loss=2.085, generator_feat_match_loss=5.911, over 39.00 samples.], tot_loss[discriminator_loss=2.713, discriminator_real_loss=1.372, discriminator_fake_loss=1.341, generator_loss=28.11, generator_mel_loss=17.94, generator_kl_loss=1.405, generator_dur_loss=1.762, generator_adv_loss=1.956, generator_feat_match_loss=5.052, over 6019.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 06:19:39,926 INFO [train.py:919] (2/6) Start epoch 529
2024-03-14 06:21:21,294 INFO [train.py:527] (2/6) Epoch 529, batch 28, global_batch_idx: 65500, batch size: 61, loss[discriminator_loss=2.719, discriminator_real_loss=1.398, discriminator_fake_loss=1.321, generator_loss=28.72, generator_mel_loss=17.86, generator_kl_loss=1.462, generator_dur_loss=1.754, generator_adv_loss=2.085, generator_feat_match_loss=5.564, over 61.00 samples.], tot_loss[discriminator_loss=2.706, discriminator_real_loss=1.369, discriminator_fake_loss=1.337, generator_loss=28.49, generator_mel_loss=18.04, generator_kl_loss=1.432, generator_dur_loss=1.742, generator_adv_loss=1.969, generator_feat_match_loss=5.307, over 1518.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 06:23:39,378 INFO [train.py:527] (2/6) Epoch 529, batch 78, global_batch_idx: 65550, batch size: 74, loss[discriminator_loss=2.72, discriminator_real_loss=1.46, discriminator_fake_loss=1.26, generator_loss=28.01, generator_mel_loss=18.15, generator_kl_loss=1.49, generator_dur_loss=1.803, generator_adv_loss=1.847, generator_feat_match_loss=4.724, over 74.00 samples.], tot_loss[discriminator_loss=2.703, discriminator_real_loss=1.365, discriminator_fake_loss=1.337, generator_loss=28.37, generator_mel_loss=18.01, generator_kl_loss=1.427, generator_dur_loss=1.747, generator_adv_loss=1.967, generator_feat_match_loss=5.223, over 4372.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 06:25:45,201 INFO [train.py:919] (2/6) Start epoch 530
2024-03-14 06:26:19,683 INFO [train.py:527] (2/6) Epoch 530, batch 4, global_batch_idx: 65600, batch size: 39, loss[discriminator_loss=2.723, discriminator_real_loss=1.323, discriminator_fake_loss=1.4, generator_loss=27.53, generator_mel_loss=17.6, generator_kl_loss=1.463, generator_dur_loss=1.668, generator_adv_loss=1.913, generator_feat_match_loss=4.89, over 39.00 samples.], tot_loss[discriminator_loss=2.718, discriminator_real_loss=1.357, discriminator_fake_loss=1.361, generator_loss=27.96, generator_mel_loss=17.83, generator_kl_loss=1.409, generator_dur_loss=1.755, generator_adv_loss=1.928, generator_feat_match_loss=5.035, over 301.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 06:26:19,687 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 06:26:27,498 INFO [train.py:591] (2/6) Epoch 530, validation: discriminator_loss=2.788, discriminator_real_loss=1.417, discriminator_fake_loss=1.371, generator_loss=27.05, generator_mel_loss=18.14, generator_kl_loss=1.191, generator_dur_loss=1.821, generator_adv_loss=1.847, generator_feat_match_loss=4.059, over 100.00 samples.
2024-03-14 06:26:27,501 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 06:28:44,978 INFO [train.py:527] (2/6) Epoch 530, batch 54, global_batch_idx: 65650, batch size: 83, loss[discriminator_loss=2.601, discriminator_real_loss=1.275, discriminator_fake_loss=1.325, generator_loss=28.98, generator_mel_loss=18.22, generator_kl_loss=1.26, generator_dur_loss=1.859, generator_adv_loss=1.927, generator_feat_match_loss=5.713, over 83.00 samples.], tot_loss[discriminator_loss=2.699, discriminator_real_loss=1.361, discriminator_fake_loss=1.338, generator_loss=28.2, generator_mel_loss=17.92, generator_kl_loss=1.398, generator_dur_loss=1.762, generator_adv_loss=1.959, generator_feat_match_loss=5.157, over 3164.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 06:31:02,579 INFO [train.py:527] (2/6) Epoch 530, batch 104, global_batch_idx: 65700, batch size: 88, loss[discriminator_loss=2.654, discriminator_real_loss=1.255, discriminator_fake_loss=1.399, generator_loss=28.75, generator_mel_loss=17.82, generator_kl_loss=1.371, generator_dur_loss=1.872, generator_adv_loss=1.979, generator_feat_match_loss=5.71, over 88.00 samples.], tot_loss[discriminator_loss=2.7, discriminator_real_loss=1.362, discriminator_fake_loss=1.338, generator_loss=28.3, generator_mel_loss=17.96, generator_kl_loss=1.403, generator_dur_loss=1.76, generator_adv_loss=1.968, generator_feat_match_loss=5.214, over 6047.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 06:31:58,298 INFO [train.py:919] (2/6) Start epoch 531
2024-03-14 06:33:43,947 INFO [train.py:527] (2/6) Epoch 531, batch 30, global_batch_idx: 65750, batch size: 42, loss[discriminator_loss=2.749, discriminator_real_loss=1.486, discriminator_fake_loss=1.263, generator_loss=28.26, generator_mel_loss=17.66, generator_kl_loss=1.671, generator_dur_loss=1.676, generator_adv_loss=1.92, generator_feat_match_loss=5.331, over 42.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.371, discriminator_fake_loss=1.345, generator_loss=28.28, generator_mel_loss=18.01, generator_kl_loss=1.375, generator_dur_loss=1.748, generator_adv_loss=1.949, generator_feat_match_loss=5.198, over 1804.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 06:36:02,399 INFO [train.py:527] (2/6) Epoch 531, batch 80, global_batch_idx: 65800, batch size: 39, loss[discriminator_loss=2.612, discriminator_real_loss=1.275, discriminator_fake_loss=1.337, generator_loss=29.81, generator_mel_loss=18.5, generator_kl_loss=1.547, generator_dur_loss=1.704, generator_adv_loss=1.998, generator_feat_match_loss=6.06, over 39.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.376, discriminator_fake_loss=1.339, generator_loss=28.32, generator_mel_loss=18.04, generator_kl_loss=1.401, generator_dur_loss=1.746, generator_adv_loss=1.961, generator_feat_match_loss=5.175, over 4535.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 06:36:02,400 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 06:36:10,372 INFO [train.py:591] (2/6) Epoch 531, validation: discriminator_loss=2.722, discriminator_real_loss=1.419, discriminator_fake_loss=1.303, generator_loss=27.24, generator_mel_loss=18.22, generator_kl_loss=1.31, generator_dur_loss=1.819, generator_adv_loss=1.926, generator_feat_match_loss=3.968, over 100.00 samples.
2024-03-14 06:36:10,373 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 06:38:10,764 INFO [train.py:919] (2/6) Start epoch 532
2024-03-14 06:38:51,759 INFO [train.py:527] (2/6) Epoch 532, batch 6, global_batch_idx: 65850, batch size: 50, loss[discriminator_loss=2.688, discriminator_real_loss=1.451, discriminator_fake_loss=1.238, generator_loss=28.87, generator_mel_loss=18.29, generator_kl_loss=1.609, generator_dur_loss=1.689, generator_adv_loss=1.841, generator_feat_match_loss=5.445, over 50.00 samples.], tot_loss[discriminator_loss=2.712, discriminator_real_loss=1.385, discriminator_fake_loss=1.327, generator_loss=28.66, generator_mel_loss=18.06, generator_kl_loss=1.525, generator_dur_loss=1.725, generator_adv_loss=1.971, generator_feat_match_loss=5.374, over 363.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 06:41:13,541 INFO [train.py:527] (2/6) Epoch 532, batch 56, global_batch_idx: 65900, batch size: 83, loss[discriminator_loss=2.703, discriminator_real_loss=1.377, discriminator_fake_loss=1.326, generator_loss=27.83, generator_mel_loss=18.01, generator_kl_loss=1.44, generator_dur_loss=1.845, generator_adv_loss=1.887, generator_feat_match_loss=4.651, over 83.00 samples.], tot_loss[discriminator_loss=2.706, discriminator_real_loss=1.36, discriminator_fake_loss=1.345, generator_loss=28.22, generator_mel_loss=17.99, generator_kl_loss=1.416, generator_dur_loss=1.76, generator_adv_loss=1.961, generator_feat_match_loss=5.092, over 3509.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 06:43:37,036 INFO [train.py:527] (2/6) Epoch 532, batch 106, global_batch_idx: 65950, batch size: 50, loss[discriminator_loss=2.764, discriminator_real_loss=1.436, discriminator_fake_loss=1.328, generator_loss=27.25, generator_mel_loss=17.64, generator_kl_loss=1.462, generator_dur_loss=1.665, generator_adv_loss=1.842, generator_feat_match_loss=4.638, over 50.00 samples.], tot_loss[discriminator_loss=2.71, discriminator_real_loss=1.362, discriminator_fake_loss=1.348, generator_loss=28.21, generator_mel_loss=17.98, generator_kl_loss=1.41, generator_dur_loss=1.759, generator_adv_loss=1.949, generator_feat_match_loss=5.108, over 6583.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 06:44:26,013 INFO [train.py:919] (2/6) Start epoch 533
2024-03-14 06:46:21,524 INFO [train.py:527] (2/6) Epoch 533, batch 32, global_batch_idx: 66000, batch size: 44, loss[discriminator_loss=2.688, discriminator_real_loss=1.244, discriminator_fake_loss=1.444, generator_loss=28.83, generator_mel_loss=17.75, generator_kl_loss=1.694, generator_dur_loss=1.653, generator_adv_loss=2.053, generator_feat_match_loss=5.687, over 44.00 samples.], tot_loss[discriminator_loss=2.706, discriminator_real_loss=1.362, discriminator_fake_loss=1.345, generator_loss=28.41, generator_mel_loss=18.05, generator_kl_loss=1.43, generator_dur_loss=1.765, generator_adv_loss=1.971, generator_feat_match_loss=5.201, over 1888.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 06:46:21,526 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 06:46:29,365 INFO [train.py:591] (2/6) Epoch 533, validation: discriminator_loss=2.755, discriminator_real_loss=1.419, discriminator_fake_loss=1.335, generator_loss=27, generator_mel_loss=18.14, generator_kl_loss=1.185, generator_dur_loss=1.804, generator_adv_loss=1.902, generator_feat_match_loss=3.976, over 100.00 samples.
2024-03-14 06:46:29,366 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 06:48:50,891 INFO [train.py:527] (2/6) Epoch 533, batch 82, global_batch_idx: 66050, batch size: 62, loss[discriminator_loss=2.686, discriminator_real_loss=1.343, discriminator_fake_loss=1.344, generator_loss=28.81, generator_mel_loss=18.2, generator_kl_loss=1.361, generator_dur_loss=1.743, generator_adv_loss=1.925, generator_feat_match_loss=5.582, over 62.00 samples.], tot_loss[discriminator_loss=2.704, discriminator_real_loss=1.365, discriminator_fake_loss=1.339, generator_loss=28.36, generator_mel_loss=18.05, generator_kl_loss=1.408, generator_dur_loss=1.758, generator_adv_loss=1.968, generator_feat_match_loss=5.182, over 4813.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 06:50:46,697 INFO [train.py:919] (2/6) Start epoch 534
2024-03-14 06:51:32,906 INFO [train.py:527] (2/6) Epoch 534, batch 8, global_batch_idx: 66100, batch size: 77, loss[discriminator_loss=2.738, discriminator_real_loss=1.335, discriminator_fake_loss=1.403, generator_loss=27.27, generator_mel_loss=17.5, generator_kl_loss=1.423, generator_dur_loss=1.785, generator_adv_loss=1.893, generator_feat_match_loss=4.668, over 77.00 samples.], tot_loss[discriminator_loss=2.709, discriminator_real_loss=1.358, discriminator_fake_loss=1.352, generator_loss=28.56, generator_mel_loss=18.05, generator_kl_loss=1.392, generator_dur_loss=1.767, generator_adv_loss=2, generator_feat_match_loss=5.35, over 575.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 06:53:53,990 INFO [train.py:527] (2/6) Epoch 534, batch 58, global_batch_idx: 66150, batch size: 25, loss[discriminator_loss=2.634, discriminator_real_loss=1.377, discriminator_fake_loss=1.257, generator_loss=30.6, generator_mel_loss=18.73, generator_kl_loss=1.725, generator_dur_loss=1.617, generator_adv_loss=1.948, generator_feat_match_loss=6.576, over 25.00 samples.], tot_loss[discriminator_loss=2.709, discriminator_real_loss=1.368, discriminator_fake_loss=1.341, generator_loss=28.37, generator_mel_loss=18.02, generator_kl_loss=1.419, generator_dur_loss=1.751, generator_adv_loss=1.976, generator_feat_match_loss=5.201, over 3429.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 06:56:16,904 INFO [train.py:527] (2/6) Epoch 534, batch 108, global_batch_idx: 66200, batch size: 45, loss[discriminator_loss=2.616, discriminator_real_loss=1.315, discriminator_fake_loss=1.301, generator_loss=29.35, generator_mel_loss=18.72, generator_kl_loss=1.547, generator_dur_loss=1.641, generator_adv_loss=2.113, generator_feat_match_loss=5.326, over 45.00 samples.], tot_loss[discriminator_loss=2.713, discriminator_real_loss=1.372, discriminator_fake_loss=1.341, generator_loss=28.29, generator_mel_loss=18.02, generator_kl_loss=1.404, generator_dur_loss=1.75, generator_adv_loss=1.964, generator_feat_match_loss=5.147, over 6245.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 06:56:16,906 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 06:56:25,598 INFO [train.py:591] (2/6) Epoch 534, validation: discriminator_loss=2.697, discriminator_real_loss=1.422, discriminator_fake_loss=1.275, generator_loss=27.49, generator_mel_loss=18.53, generator_kl_loss=1.262, generator_dur_loss=1.822, generator_adv_loss=1.92, generator_feat_match_loss=3.952, over 100.00 samples.
2024-03-14 06:56:25,599 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 06:57:07,544 INFO [train.py:919] (2/6) Start epoch 535
2024-03-14 06:59:13,055 INFO [train.py:527] (2/6) Epoch 535, batch 34, global_batch_idx: 66250, batch size: 47, loss[discriminator_loss=2.688, discriminator_real_loss=1.288, discriminator_fake_loss=1.4, generator_loss=27.85, generator_mel_loss=18.11, generator_kl_loss=1.457, generator_dur_loss=1.713, generator_adv_loss=2.073, generator_feat_match_loss=4.493, over 47.00 samples.], tot_loss[discriminator_loss=2.723, discriminator_real_loss=1.379, discriminator_fake_loss=1.344, generator_loss=28.23, generator_mel_loss=17.91, generator_kl_loss=1.443, generator_dur_loss=1.749, generator_adv_loss=1.956, generator_feat_match_loss=5.171, over 2066.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 07:01:34,861 INFO [train.py:527] (2/6) Epoch 535, batch 84, global_batch_idx: 66300, batch size: 62, loss[discriminator_loss=2.656, discriminator_real_loss=1.319, discriminator_fake_loss=1.337, generator_loss=29.08, generator_mel_loss=18.25, generator_kl_loss=1.366, generator_dur_loss=1.74, generator_adv_loss=2.177, generator_feat_match_loss=5.55, over 62.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.369, discriminator_fake_loss=1.345, generator_loss=28.27, generator_mel_loss=17.95, generator_kl_loss=1.422, generator_dur_loss=1.759, generator_adv_loss=1.963, generator_feat_match_loss=5.178, over 5004.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 07:03:21,921 INFO [train.py:919] (2/6) Start epoch 536
2024-03-14 07:04:14,432 INFO [train.py:527] (2/6) Epoch 536, batch 10, global_batch_idx: 66350, batch size: 74, loss[discriminator_loss=2.709, discriminator_real_loss=1.423, discriminator_fake_loss=1.286, generator_loss=28.08, generator_mel_loss=17.95, generator_kl_loss=1.333, generator_dur_loss=1.784, generator_adv_loss=1.841, generator_feat_match_loss=5.174, over 74.00 samples.], tot_loss[discriminator_loss=2.739, discriminator_real_loss=1.375, discriminator_fake_loss=1.364, generator_loss=28.28, generator_mel_loss=18.08, generator_kl_loss=1.392, generator_dur_loss=1.746, generator_adv_loss=1.921, generator_feat_match_loss=5.138, over 629.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 07:06:35,730 INFO [train.py:527] (2/6) Epoch 536, batch 60, global_batch_idx: 66400, batch size: 56, loss[discriminator_loss=2.736, discriminator_real_loss=1.334, discriminator_fake_loss=1.402, generator_loss=28.29, generator_mel_loss=17.74, generator_kl_loss=1.455, generator_dur_loss=1.68, generator_adv_loss=1.991, generator_feat_match_loss=5.426, over 56.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.365, discriminator_fake_loss=1.351, generator_loss=28.06, generator_mel_loss=17.91, generator_kl_loss=1.391, generator_dur_loss=1.74, generator_adv_loss=1.926, generator_feat_match_loss=5.094, over 3690.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 07:06:35,732 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 07:06:43,889 INFO [train.py:591] (2/6) Epoch 536, validation: discriminator_loss=2.741, discriminator_real_loss=1.502, discriminator_fake_loss=1.239, generator_loss=27.44, generator_mel_loss=18.3, generator_kl_loss=1.335, generator_dur_loss=1.789, generator_adv_loss=2.005, generator_feat_match_loss=4.017, over 100.00 samples.
2024-03-14 07:06:43,891 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 07:09:05,005 INFO [train.py:527] (2/6) Epoch 536, batch 110, global_batch_idx: 66450, batch size: 44, loss[discriminator_loss=2.669, discriminator_real_loss=1.296, discriminator_fake_loss=1.373, generator_loss=29.58, generator_mel_loss=18.38, generator_kl_loss=1.589, generator_dur_loss=1.662, generator_adv_loss=1.813, generator_feat_match_loss=6.137, over 44.00 samples.], tot_loss[discriminator_loss=2.709, discriminator_real_loss=1.366, discriminator_fake_loss=1.342, generator_loss=28.18, generator_mel_loss=17.95, generator_kl_loss=1.4, generator_dur_loss=1.741, generator_adv_loss=1.941, generator_feat_match_loss=5.151, over 6661.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 07:09:43,385 INFO [train.py:919] (2/6) Start epoch 537
2024-03-14 07:11:48,653 INFO [train.py:527] (2/6) Epoch 537, batch 36, global_batch_idx: 66500, batch size: 52, loss[discriminator_loss=2.743, discriminator_real_loss=1.51, discriminator_fake_loss=1.232, generator_loss=27.84, generator_mel_loss=17.88, generator_kl_loss=1.562, generator_dur_loss=1.675, generator_adv_loss=1.863, generator_feat_match_loss=4.865, over 52.00 samples.], tot_loss[discriminator_loss=2.704, discriminator_real_loss=1.372, discriminator_fake_loss=1.332, generator_loss=28.18, generator_mel_loss=17.91, generator_kl_loss=1.396, generator_dur_loss=1.761, generator_adv_loss=1.968, generator_feat_match_loss=5.146, over 2292.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 07:14:06,686 INFO [train.py:527] (2/6) Epoch 537, batch 86, global_batch_idx: 66550, batch size: 50, loss[discriminator_loss=2.692, discriminator_real_loss=1.237, discriminator_fake_loss=1.455, generator_loss=28.62, generator_mel_loss=18.04, generator_kl_loss=1.458, generator_dur_loss=1.725, generator_adv_loss=2.07, generator_feat_match_loss=5.335, over 50.00 samples.], tot_loss[discriminator_loss=2.708, discriminator_real_loss=1.37, discriminator_fake_loss=1.338, generator_loss=28.22, generator_mel_loss=17.95, generator_kl_loss=1.412, generator_dur_loss=1.751, generator_adv_loss=1.958, generator_feat_match_loss=5.144, over 5031.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 07:15:53,904 INFO [train.py:919] (2/6) Start epoch 538
2024-03-14 07:16:52,537 INFO [train.py:527] (2/6) Epoch 538, batch 12, global_batch_idx: 66600, batch size: 70, loss[discriminator_loss=2.688, discriminator_real_loss=1.39, discriminator_fake_loss=1.298, generator_loss=28.65, generator_mel_loss=18.23, generator_kl_loss=1.212, generator_dur_loss=1.771, generator_adv_loss=1.844, generator_feat_match_loss=5.595, over 70.00 samples.], tot_loss[discriminator_loss=2.719, discriminator_real_loss=1.377, discriminator_fake_loss=1.342, generator_loss=28.6, generator_mel_loss=18.16, generator_kl_loss=1.399, generator_dur_loss=1.708, generator_adv_loss=1.95, generator_feat_match_loss=5.384, over 693.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 07:16:52,541 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 07:17:00,245 INFO [train.py:591] (2/6) Epoch 538, validation: discriminator_loss=2.742, discriminator_real_loss=1.367, discriminator_fake_loss=1.375, generator_loss=27.95, generator_mel_loss=18.66, generator_kl_loss=1.243, generator_dur_loss=1.795, generator_adv_loss=1.757, generator_feat_match_loss=4.496, over 100.00 samples.
2024-03-14 07:17:00,246 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 07:19:21,650 INFO [train.py:527] (2/6) Epoch 538, batch 62, global_batch_idx: 66650, batch size: 66, loss[discriminator_loss=2.656, discriminator_real_loss=1.31, discriminator_fake_loss=1.346, generator_loss=27.91, generator_mel_loss=17.74, generator_kl_loss=1.455, generator_dur_loss=1.717, generator_adv_loss=2.063, generator_feat_match_loss=4.933, over 66.00 samples.], tot_loss[discriminator_loss=2.706, discriminator_real_loss=1.363, discriminator_fake_loss=1.344, generator_loss=28.41, generator_mel_loss=18.07, generator_kl_loss=1.421, generator_dur_loss=1.714, generator_adv_loss=1.967, generator_feat_match_loss=5.242, over 3568.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 07:21:42,598 INFO [train.py:527] (2/6) Epoch 538, batch 112, global_batch_idx: 66700, batch size: 52, loss[discriminator_loss=2.672, discriminator_real_loss=1.335, discriminator_fake_loss=1.337, generator_loss=29.05, generator_mel_loss=18.22, generator_kl_loss=1.453, generator_dur_loss=1.683, generator_adv_loss=2.118, generator_feat_match_loss=5.579, over 52.00 samples.], tot_loss[discriminator_loss=2.713, discriminator_real_loss=1.366, discriminator_fake_loss=1.347, generator_loss=28.31, generator_mel_loss=18.04, generator_kl_loss=1.405, generator_dur_loss=1.725, generator_adv_loss=1.957, generator_feat_match_loss=5.177, over 6620.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 07:22:15,685 INFO [train.py:919] (2/6) Start epoch 539
2024-03-14 07:24:30,697 INFO [train.py:527] (2/6) Epoch 539, batch 38, global_batch_idx: 66750, batch size: 44, loss[discriminator_loss=2.723, discriminator_real_loss=1.4, discriminator_fake_loss=1.323, generator_loss=27.97, generator_mel_loss=17.81, generator_kl_loss=1.563, generator_dur_loss=1.681, generator_adv_loss=1.855, generator_feat_match_loss=5.056, over 44.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.368, discriminator_fake_loss=1.349, generator_loss=28.46, generator_mel_loss=18.1, generator_kl_loss=1.402, generator_dur_loss=1.766, generator_adv_loss=1.968, generator_feat_match_loss=5.228, over 2401.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 07:26:51,967 INFO [train.py:527] (2/6) Epoch 539, batch 88, global_batch_idx: 66800, batch size: 31, loss[discriminator_loss=2.73, discriminator_real_loss=1.429, discriminator_fake_loss=1.301, generator_loss=28.54, generator_mel_loss=18.28, generator_kl_loss=1.582, generator_dur_loss=1.672, generator_adv_loss=2.063, generator_feat_match_loss=4.943, over 31.00 samples.], tot_loss[discriminator_loss=2.705, discriminator_real_loss=1.366, discriminator_fake_loss=1.339, generator_loss=28.27, generator_mel_loss=18.02, generator_kl_loss=1.417, generator_dur_loss=1.753, generator_adv_loss=1.968, generator_feat_match_loss=5.111, over 5142.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 07:26:51,969 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 07:27:00,806 INFO [train.py:591] (2/6) Epoch 539, validation: discriminator_loss=2.707, discriminator_real_loss=1.441, discriminator_fake_loss=1.266, generator_loss=27.6, generator_mel_loss=18.11, generator_kl_loss=1.223, generator_dur_loss=1.811, generator_adv_loss=1.981, generator_feat_match_loss=4.481, over 100.00 samples.
2024-03-14 07:27:00,807 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 07:28:39,723 INFO [train.py:919] (2/6) Start epoch 540
2024-03-14 07:29:44,255 INFO [train.py:527] (2/6) Epoch 540, batch 14, global_batch_idx: 66850, batch size: 53, loss[discriminator_loss=2.714, discriminator_real_loss=1.457, discriminator_fake_loss=1.257, generator_loss=28.62, generator_mel_loss=17.79, generator_kl_loss=1.465, generator_dur_loss=1.717, generator_adv_loss=1.891, generator_feat_match_loss=5.759, over 53.00 samples.], tot_loss[discriminator_loss=2.705, discriminator_real_loss=1.363, discriminator_fake_loss=1.343, generator_loss=28.56, generator_mel_loss=18.01, generator_kl_loss=1.41, generator_dur_loss=1.767, generator_adv_loss=1.965, generator_feat_match_loss=5.414, over 957.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 07:32:07,946 INFO [train.py:527] (2/6) Epoch 540, batch 64, global_batch_idx: 66900, batch size: 83, loss[discriminator_loss=2.75, discriminator_real_loss=1.419, discriminator_fake_loss=1.332, generator_loss=29.12, generator_mel_loss=18.4, generator_kl_loss=1.342, generator_dur_loss=1.79, generator_adv_loss=2.023, generator_feat_match_loss=5.561, over 83.00 samples.], tot_loss[discriminator_loss=2.709, discriminator_real_loss=1.368, discriminator_fake_loss=1.341, generator_loss=28.33, generator_mel_loss=17.99, generator_kl_loss=1.431, generator_dur_loss=1.751, generator_adv_loss=1.962, generator_feat_match_loss=5.191, over 3796.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 07:34:28,369 INFO [train.py:527] (2/6) Epoch 540, batch 114, global_batch_idx: 66950, batch size: 74, loss[discriminator_loss=2.701, discriminator_real_loss=1.382, discriminator_fake_loss=1.318, generator_loss=27.62, generator_mel_loss=17.58, generator_kl_loss=1.438, generator_dur_loss=1.78, generator_adv_loss=1.874, generator_feat_match_loss=4.954, over 74.00 samples.], tot_loss[discriminator_loss=2.706, discriminator_real_loss=1.369, discriminator_fake_loss=1.337, generator_loss=28.29, generator_mel_loss=17.99, generator_kl_loss=1.418, generator_dur_loss=1.753, generator_adv_loss=1.969, generator_feat_match_loss=5.161, over 6674.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 07:34:52,762 INFO [train.py:919] (2/6) Start epoch 541
2024-03-14 07:37:09,375 INFO [train.py:527] (2/6) Epoch 541, batch 40, global_batch_idx: 67000, batch size: 70, loss[discriminator_loss=2.681, discriminator_real_loss=1.347, discriminator_fake_loss=1.334, generator_loss=27.84, generator_mel_loss=17.9, generator_kl_loss=1.465, generator_dur_loss=1.743, generator_adv_loss=1.961, generator_feat_match_loss=4.764, over 70.00 samples.], tot_loss[discriminator_loss=2.717, discriminator_real_loss=1.37, discriminator_fake_loss=1.347, generator_loss=28.31, generator_mel_loss=18.05, generator_kl_loss=1.428, generator_dur_loss=1.728, generator_adv_loss=1.953, generator_feat_match_loss=5.146, over 2266.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 07:37:09,377 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 07:37:17,460 INFO [train.py:591] (2/6) Epoch 541, validation: discriminator_loss=2.687, discriminator_real_loss=1.429, discriminator_fake_loss=1.258, generator_loss=26.9, generator_mel_loss=18, generator_kl_loss=1.238, generator_dur_loss=1.771, generator_adv_loss=1.944, generator_feat_match_loss=3.941, over 100.00 samples.
2024-03-14 07:37:17,461 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 07:39:39,330 INFO [train.py:527] (2/6) Epoch 541, batch 90, global_batch_idx: 67050, batch size: 18, loss[discriminator_loss=2.777, discriminator_real_loss=1.39, discriminator_fake_loss=1.387, generator_loss=29.01, generator_mel_loss=18.36, generator_kl_loss=1.995, generator_dur_loss=1.492, generator_adv_loss=1.881, generator_feat_match_loss=5.279, over 18.00 samples.], tot_loss[discriminator_loss=2.71, discriminator_real_loss=1.371, discriminator_fake_loss=1.339, generator_loss=28.22, generator_mel_loss=17.99, generator_kl_loss=1.419, generator_dur_loss=1.727, generator_adv_loss=1.956, generator_feat_match_loss=5.123, over 5073.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 07:41:13,428 INFO [train.py:919] (2/6) Start epoch 542
2024-03-14 07:42:24,590 INFO [train.py:527] (2/6) Epoch 542, batch 16, global_batch_idx: 67100, batch size: 70, loss[discriminator_loss=2.724, discriminator_real_loss=1.306, discriminator_fake_loss=1.418, generator_loss=28.68, generator_mel_loss=18, generator_kl_loss=1.42, generator_dur_loss=1.741, generator_adv_loss=2.047, generator_feat_match_loss=5.472, over 70.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.387, discriminator_fake_loss=1.334, generator_loss=28.19, generator_mel_loss=17.95, generator_kl_loss=1.366, generator_dur_loss=1.744, generator_adv_loss=1.962, generator_feat_match_loss=5.169, over 1124.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 07:44:46,027 INFO [train.py:527] (2/6) Epoch 542, batch 66, global_batch_idx: 67150, batch size: 13, loss[discriminator_loss=2.754, discriminator_real_loss=1.316, discriminator_fake_loss=1.437, generator_loss=29.57, generator_mel_loss=18.41, generator_kl_loss=1.956, generator_dur_loss=1.616, generator_adv_loss=2.006, generator_feat_match_loss=5.579, over 13.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.375, discriminator_fake_loss=1.345, generator_loss=28.26, generator_mel_loss=18.02, generator_kl_loss=1.403, generator_dur_loss=1.742, generator_adv_loss=1.949, generator_feat_match_loss=5.151, over 4157.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 07:47:07,923 INFO [train.py:527] (2/6) Epoch 542, batch 116, global_batch_idx: 67200, batch size: 48, loss[discriminator_loss=2.736, discriminator_real_loss=1.321, discriminator_fake_loss=1.415, generator_loss=28.39, generator_mel_loss=18.31, generator_kl_loss=1.463, generator_dur_loss=1.671, generator_adv_loss=1.92, generator_feat_match_loss=5.027, over 48.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.372, discriminator_fake_loss=1.344, generator_loss=28.24, generator_mel_loss=17.99, generator_kl_loss=1.402, generator_dur_loss=1.745, generator_adv_loss=1.961, generator_feat_match_loss=5.136, over 7150.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 07:47:07,925 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 07:47:16,875 INFO [train.py:591] (2/6) Epoch 542, validation: discriminator_loss=2.756, discriminator_real_loss=1.447, discriminator_fake_loss=1.308, generator_loss=26.58, generator_mel_loss=17.74, generator_kl_loss=1.208, generator_dur_loss=1.803, generator_adv_loss=1.908, generator_feat_match_loss=3.927, over 100.00 samples.
2024-03-14 07:47:16,876 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 07:47:39,577 INFO [train.py:919] (2/6) Start epoch 543
2024-03-14 07:50:02,763 INFO [train.py:527] (2/6) Epoch 543, batch 42, global_batch_idx: 67250, batch size: 52, loss[discriminator_loss=2.703, discriminator_real_loss=1.372, discriminator_fake_loss=1.331, generator_loss=27.47, generator_mel_loss=17.74, generator_kl_loss=1.289, generator_dur_loss=1.71, generator_adv_loss=1.981, generator_feat_match_loss=4.751, over 52.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.371, discriminator_fake_loss=1.344, generator_loss=28.12, generator_mel_loss=17.92, generator_kl_loss=1.428, generator_dur_loss=1.748, generator_adv_loss=1.962, generator_feat_match_loss=5.056, over 2531.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 07:52:24,882 INFO [train.py:527] (2/6) Epoch 543, batch 92, global_batch_idx: 67300, batch size: 44, loss[discriminator_loss=2.687, discriminator_real_loss=1.301, discriminator_fake_loss=1.386, generator_loss=29.74, generator_mel_loss=18.43, generator_kl_loss=1.568, generator_dur_loss=1.672, generator_adv_loss=1.964, generator_feat_match_loss=6.107, over 44.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.374, discriminator_fake_loss=1.342, generator_loss=28.17, generator_mel_loss=17.96, generator_kl_loss=1.426, generator_dur_loss=1.747, generator_adv_loss=1.956, generator_feat_match_loss=5.085, over 5277.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 07:53:50,778 INFO [train.py:919] (2/6) Start epoch 544
2024-03-14 07:55:06,345 INFO [train.py:527] (2/6) Epoch 544, batch 18, global_batch_idx: 67350, batch size: 59, loss[discriminator_loss=2.656, discriminator_real_loss=1.324, discriminator_fake_loss=1.332, generator_loss=28.47, generator_mel_loss=17.92, generator_kl_loss=1.446, generator_dur_loss=1.722, generator_adv_loss=2.099, generator_feat_match_loss=5.284, over 59.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.384, discriminator_fake_loss=1.342, generator_loss=28.07, generator_mel_loss=17.87, generator_kl_loss=1.374, generator_dur_loss=1.786, generator_adv_loss=1.977, generator_feat_match_loss=5.059, over 1193.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 07:57:29,480 INFO [train.py:527] (2/6) Epoch 544, batch 68, global_batch_idx: 67400, batch size: 56, loss[discriminator_loss=2.6, discriminator_real_loss=1.265, discriminator_fake_loss=1.335, generator_loss=28.27, generator_mel_loss=17.81, generator_kl_loss=1.211, generator_dur_loss=1.776, generator_adv_loss=2.1, generator_feat_match_loss=5.369, over 56.00 samples.], tot_loss[discriminator_loss=2.705, discriminator_real_loss=1.365, discriminator_fake_loss=1.339, generator_loss=28.29, generator_mel_loss=17.94, generator_kl_loss=1.377, generator_dur_loss=1.774, generator_adv_loss=1.993, generator_feat_match_loss=5.211, over 4297.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 07:57:29,482 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 07:57:37,700 INFO [train.py:591] (2/6) Epoch 544, validation: discriminator_loss=2.705, discriminator_real_loss=1.46, discriminator_fake_loss=1.245, generator_loss=26.94, generator_mel_loss=18.07, generator_kl_loss=1.162, generator_dur_loss=1.826, generator_adv_loss=1.986, generator_feat_match_loss=3.896, over 100.00 samples.
2024-03-14 07:57:37,701 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 07:59:57,159 INFO [train.py:527] (2/6) Epoch 544, batch 118, global_batch_idx: 67450, batch size: 15, loss[discriminator_loss=2.576, discriminator_real_loss=1.374, discriminator_fake_loss=1.202, generator_loss=30.91, generator_mel_loss=19.08, generator_kl_loss=1.734, generator_dur_loss=1.621, generator_adv_loss=2.175, generator_feat_match_loss=6.303, over 15.00 samples.], tot_loss[discriminator_loss=2.702, discriminator_real_loss=1.367, discriminator_fake_loss=1.335, generator_loss=28.3, generator_mel_loss=17.95, generator_kl_loss=1.4, generator_dur_loss=1.772, generator_adv_loss=1.981, generator_feat_match_loss=5.191, over 7128.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 08:00:12,585 INFO [train.py:919] (2/6) Start epoch 545
2024-03-14 08:02:42,088 INFO [train.py:527] (2/6) Epoch 545, batch 44, global_batch_idx: 67500, batch size: 44, loss[discriminator_loss=2.621, discriminator_real_loss=1.306, discriminator_fake_loss=1.316, generator_loss=29.62, generator_mel_loss=18.36, generator_kl_loss=1.679, generator_dur_loss=1.687, generator_adv_loss=1.888, generator_feat_match_loss=6.009, over 44.00 samples.], tot_loss[discriminator_loss=2.712, discriminator_real_loss=1.374, discriminator_fake_loss=1.338, generator_loss=28.42, generator_mel_loss=18.1, generator_kl_loss=1.433, generator_dur_loss=1.74, generator_adv_loss=1.95, generator_feat_match_loss=5.197, over 2501.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 08:05:03,566 INFO [train.py:527] (2/6) Epoch 545, batch 94, global_batch_idx: 67550, batch size: 62, loss[discriminator_loss=2.659, discriminator_real_loss=1.328, discriminator_fake_loss=1.332, generator_loss=28.89, generator_mel_loss=18.36, generator_kl_loss=1.391, generator_dur_loss=1.709, generator_adv_loss=2.019, generator_feat_match_loss=5.412, over 62.00 samples.], tot_loss[discriminator_loss=2.706, discriminator_real_loss=1.37, discriminator_fake_loss=1.337, generator_loss=28.37, generator_mel_loss=18.03, generator_kl_loss=1.433, generator_dur_loss=1.739, generator_adv_loss=1.96, generator_feat_match_loss=5.209, over 5118.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 08:06:26,029 INFO [train.py:919] (2/6) Start epoch 546
2024-03-14 08:07:45,776 INFO [train.py:527] (2/6) Epoch 546, batch 20, global_batch_idx: 67600, batch size: 56, loss[discriminator_loss=2.736, discriminator_real_loss=1.4, discriminator_fake_loss=1.336, generator_loss=27.89, generator_mel_loss=17.99, generator_kl_loss=1.368, generator_dur_loss=1.772, generator_adv_loss=1.988, generator_feat_match_loss=4.775, over 56.00 samples.], tot_loss[discriminator_loss=2.722, discriminator_real_loss=1.375, discriminator_fake_loss=1.347, generator_loss=28.33, generator_mel_loss=17.97, generator_kl_loss=1.421, generator_dur_loss=1.757, generator_adv_loss=1.969, generator_feat_match_loss=5.218, over 1225.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 08:07:45,780 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 08:07:53,539 INFO [train.py:591] (2/6) Epoch 546, validation: discriminator_loss=2.74, discriminator_real_loss=1.402, discriminator_fake_loss=1.338, generator_loss=27.3, generator_mel_loss=18.33, generator_kl_loss=1.175, generator_dur_loss=1.816, generator_adv_loss=1.849, generator_feat_match_loss=4.129, over 100.00 samples.
2024-03-14 08:07:53,540 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 08:10:17,461 INFO [train.py:527] (2/6) Epoch 546, batch 70, global_batch_idx: 67650, batch size: 68, loss[discriminator_loss=2.689, discriminator_real_loss=1.308, discriminator_fake_loss=1.382, generator_loss=28.45, generator_mel_loss=18.14, generator_kl_loss=1.305, generator_dur_loss=1.835, generator_adv_loss=2.101, generator_feat_match_loss=5.068, over 68.00 samples.], tot_loss[discriminator_loss=2.713, discriminator_real_loss=1.373, discriminator_fake_loss=1.34, generator_loss=28.31, generator_mel_loss=17.97, generator_kl_loss=1.414, generator_dur_loss=1.76, generator_adv_loss=1.96, generator_feat_match_loss=5.206, over 4166.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 08:12:33,766 INFO [train.py:527] (2/6) Epoch 546, batch 120, global_batch_idx: 67700, batch size: 83, loss[discriminator_loss=2.704, discriminator_real_loss=1.397, discriminator_fake_loss=1.307, generator_loss=27.5, generator_mel_loss=17.76, generator_kl_loss=1.193, generator_dur_loss=1.84, generator_adv_loss=1.861, generator_feat_match_loss=4.849, over 83.00 samples.], tot_loss[discriminator_loss=2.717, discriminator_real_loss=1.377, discriminator_fake_loss=1.339, generator_loss=28.28, generator_mel_loss=17.98, generator_kl_loss=1.409, generator_dur_loss=1.759, generator_adv_loss=1.959, generator_feat_match_loss=5.169, over 6956.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 08:12:44,053 INFO [train.py:919] (2/6) Start epoch 547
2024-03-14 08:15:20,931 INFO [train.py:527] (2/6) Epoch 547, batch 46, global_batch_idx: 67750, batch size: 80, loss[discriminator_loss=2.656, discriminator_real_loss=1.335, discriminator_fake_loss=1.321, generator_loss=27.58, generator_mel_loss=17.42, generator_kl_loss=1.38, generator_dur_loss=1.752, generator_adv_loss=2.05, generator_feat_match_loss=4.983, over 80.00 samples.], tot_loss[discriminator_loss=2.695, discriminator_real_loss=1.354, discriminator_fake_loss=1.341, generator_loss=28.34, generator_mel_loss=17.99, generator_kl_loss=1.428, generator_dur_loss=1.759, generator_adv_loss=1.983, generator_feat_match_loss=5.181, over 2879.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 08:17:44,025 INFO [train.py:527] (2/6) Epoch 547, batch 96, global_batch_idx: 67800, batch size: 66, loss[discriminator_loss=2.693, discriminator_real_loss=1.308, discriminator_fake_loss=1.385, generator_loss=27.64, generator_mel_loss=17.95, generator_kl_loss=1.426, generator_dur_loss=1.75, generator_adv_loss=1.947, generator_feat_match_loss=4.564, over 66.00 samples.], tot_loss[discriminator_loss=2.703, discriminator_real_loss=1.359, discriminator_fake_loss=1.344, generator_loss=28.28, generator_mel_loss=17.96, generator_kl_loss=1.433, generator_dur_loss=1.749, generator_adv_loss=1.965, generator_feat_match_loss=5.177, over 5729.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 08:17:44,027 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 08:17:52,789 INFO [train.py:591] (2/6) Epoch 547, validation: discriminator_loss=2.694, discriminator_real_loss=1.453, discriminator_fake_loss=1.242, generator_loss=27.37, generator_mel_loss=18.18, generator_kl_loss=1.259, generator_dur_loss=1.805, generator_adv_loss=1.966, generator_feat_match_loss=4.164, over 100.00 samples.
2024-03-14 08:17:52,790 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 08:19:07,109 INFO [train.py:919] (2/6) Start epoch 548
2024-03-14 08:20:34,432 INFO [train.py:527] (2/6) Epoch 548, batch 22, global_batch_idx: 67850, batch size: 39, loss[discriminator_loss=2.723, discriminator_real_loss=1.43, discriminator_fake_loss=1.293, generator_loss=27.85, generator_mel_loss=17.89, generator_kl_loss=1.604, generator_dur_loss=1.685, generator_adv_loss=1.982, generator_feat_match_loss=4.686, over 39.00 samples.], tot_loss[discriminator_loss=2.701, discriminator_real_loss=1.362, discriminator_fake_loss=1.339, generator_loss=28.28, generator_mel_loss=17.96, generator_kl_loss=1.429, generator_dur_loss=1.744, generator_adv_loss=1.972, generator_feat_match_loss=5.178, over 1305.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 08:22:55,388 INFO [train.py:527] (2/6) Epoch 548, batch 72, global_batch_idx: 67900, batch size: 80, loss[discriminator_loss=2.752, discriminator_real_loss=1.346, discriminator_fake_loss=1.406, generator_loss=27.86, generator_mel_loss=17.75, generator_kl_loss=1.625, generator_dur_loss=1.766, generator_adv_loss=1.959, generator_feat_match_loss=4.766, over 80.00 samples.], tot_loss[discriminator_loss=2.708, discriminator_real_loss=1.362, discriminator_fake_loss=1.345, generator_loss=28.33, generator_mel_loss=17.98, generator_kl_loss=1.446, generator_dur_loss=1.723, generator_adv_loss=1.955, generator_feat_match_loss=5.228, over 4076.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 08:25:18,958 INFO [train.py:527] (2/6) Epoch 548, batch 122, global_batch_idx: 67950, batch size: 53, loss[discriminator_loss=2.783, discriminator_real_loss=1.483, discriminator_fake_loss=1.3, generator_loss=28.91, generator_mel_loss=18.29, generator_kl_loss=1.388, generator_dur_loss=1.674, generator_adv_loss=2.008, generator_feat_match_loss=5.549, over 53.00 samples.], tot_loss[discriminator_loss=2.709, discriminator_real_loss=1.365, discriminator_fake_loss=1.344, generator_loss=28.24, generator_mel_loss=17.98, generator_kl_loss=1.425, generator_dur_loss=1.727, generator_adv_loss=1.957, generator_feat_match_loss=5.152, over 7125.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 08:25:23,659 INFO [train.py:919] (2/6) Start epoch 549
2024-03-14 08:28:01,972 INFO [train.py:527] (2/6) Epoch 549, batch 48, global_batch_idx: 68000, batch size: 48, loss[discriminator_loss=2.682, discriminator_real_loss=1.37, discriminator_fake_loss=1.312, generator_loss=28.24, generator_mel_loss=18.21, generator_kl_loss=1.457, generator_dur_loss=1.652, generator_adv_loss=1.862, generator_feat_match_loss=5.056, over 48.00 samples.], tot_loss[discriminator_loss=2.708, discriminator_real_loss=1.374, discriminator_fake_loss=1.334, generator_loss=28.4, generator_mel_loss=18.08, generator_kl_loss=1.388, generator_dur_loss=1.74, generator_adv_loss=1.963, generator_feat_match_loss=5.232, over 2730.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 08:28:01,974 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 08:28:10,807 INFO [train.py:591] (2/6) Epoch 549, validation: discriminator_loss=2.754, discriminator_real_loss=1.367, discriminator_fake_loss=1.386, generator_loss=27.6, generator_mel_loss=18.45, generator_kl_loss=1.279, generator_dur_loss=1.814, generator_adv_loss=1.831, generator_feat_match_loss=4.225, over 100.00 samples.
2024-03-14 08:28:10,808 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 08:30:31,614 INFO [train.py:527] (2/6) Epoch 549, batch 98, global_batch_idx: 68050, batch size: 88, loss[discriminator_loss=2.742, discriminator_real_loss=1.313, discriminator_fake_loss=1.428, generator_loss=29.15, generator_mel_loss=18.09, generator_kl_loss=1.403, generator_dur_loss=1.857, generator_adv_loss=2.046, generator_feat_match_loss=5.761, over 88.00 samples.], tot_loss[discriminator_loss=2.704, discriminator_real_loss=1.371, discriminator_fake_loss=1.332, generator_loss=28.4, generator_mel_loss=18.03, generator_kl_loss=1.403, generator_dur_loss=1.747, generator_adv_loss=1.981, generator_feat_match_loss=5.238, over 5578.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 08:31:43,955 INFO [train.py:919] (2/6) Start epoch 550
2024-03-14 08:33:15,759 INFO [train.py:527] (2/6) Epoch 550, batch 24, global_batch_idx: 68100, batch size: 61, loss[discriminator_loss=2.678, discriminator_real_loss=1.341, discriminator_fake_loss=1.337, generator_loss=28.69, generator_mel_loss=18.32, generator_kl_loss=1.494, generator_dur_loss=1.74, generator_adv_loss=2.008, generator_feat_match_loss=5.123, over 61.00 samples.], tot_loss[discriminator_loss=2.694, discriminator_real_loss=1.359, discriminator_fake_loss=1.335, generator_loss=28.43, generator_mel_loss=18.08, generator_kl_loss=1.404, generator_dur_loss=1.755, generator_adv_loss=1.962, generator_feat_match_loss=5.229, over 1449.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 08:35:34,007 INFO [train.py:527] (2/6) Epoch 550, batch 74, global_batch_idx: 68150, batch size: 83, loss[discriminator_loss=2.657, discriminator_real_loss=1.34, discriminator_fake_loss=1.317, generator_loss=27.95, generator_mel_loss=17.77, generator_kl_loss=1.22, generator_dur_loss=1.831, generator_adv_loss=1.992, generator_feat_match_loss=5.135, over 83.00 samples.], tot_loss[discriminator_loss=2.696, discriminator_real_loss=1.362, discriminator_fake_loss=1.333, generator_loss=28.37, generator_mel_loss=18.02, generator_kl_loss=1.411, generator_dur_loss=1.751, generator_adv_loss=1.966, generator_feat_match_loss=5.224, over 4242.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 08:37:55,183 INFO [train.py:919] (2/6) Start epoch 551
2024-03-14 08:38:19,000 INFO [train.py:527] (2/6) Epoch 551, batch 0, global_batch_idx: 68200, batch size: 50, loss[discriminator_loss=2.69, discriminator_real_loss=1.385, discriminator_fake_loss=1.304, generator_loss=28.49, generator_mel_loss=18.39, generator_kl_loss=1.404, generator_dur_loss=1.685, generator_adv_loss=2.011, generator_feat_match_loss=4.992, over 50.00 samples.], tot_loss[discriminator_loss=2.69, discriminator_real_loss=1.385, discriminator_fake_loss=1.304, generator_loss=28.49, generator_mel_loss=18.39, generator_kl_loss=1.404, generator_dur_loss=1.685, generator_adv_loss=2.011, generator_feat_match_loss=4.992, over 50.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 08:38:19,003 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 08:38:26,773 INFO [train.py:591] (2/6) Epoch 551, validation: discriminator_loss=2.758, discriminator_real_loss=1.493, discriminator_fake_loss=1.265, generator_loss=27.76, generator_mel_loss=18.48, generator_kl_loss=1.211, generator_dur_loss=1.817, generator_adv_loss=1.948, generator_feat_match_loss=4.306, over 100.00 samples.
2024-03-14 08:38:26,775 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 08:40:50,289 INFO [train.py:527] (2/6) Epoch 551, batch 50, global_batch_idx: 68250, batch size: 66, loss[discriminator_loss=2.643, discriminator_real_loss=1.303, discriminator_fake_loss=1.34, generator_loss=29.4, generator_mel_loss=18.1, generator_kl_loss=1.236, generator_dur_loss=1.802, generator_adv_loss=2.01, generator_feat_match_loss=6.25, over 66.00 samples.], tot_loss[discriminator_loss=2.687, discriminator_real_loss=1.354, discriminator_fake_loss=1.332, generator_loss=28.44, generator_mel_loss=18.09, generator_kl_loss=1.43, generator_dur_loss=1.756, generator_adv_loss=1.975, generator_feat_match_loss=5.191, over 2796.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 08:43:11,421 INFO [train.py:527] (2/6) Epoch 551, batch 100, global_batch_idx: 68300, batch size: 74, loss[discriminator_loss=2.724, discriminator_real_loss=1.462, discriminator_fake_loss=1.262, generator_loss=28.09, generator_mel_loss=18, generator_kl_loss=1.384, generator_dur_loss=1.772, generator_adv_loss=1.815, generator_feat_match_loss=5.126, over 74.00 samples.], tot_loss[discriminator_loss=2.694, discriminator_real_loss=1.359, discriminator_fake_loss=1.335, generator_loss=28.39, generator_mel_loss=18.02, generator_kl_loss=1.42, generator_dur_loss=1.751, generator_adv_loss=1.974, generator_feat_match_loss=5.231, over 5514.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 08:44:14,975 INFO [train.py:919] (2/6) Start epoch 552
2024-03-14 08:45:53,536 INFO [train.py:527] (2/6) Epoch 552, batch 26, global_batch_idx: 68350, batch size: 44, loss[discriminator_loss=2.653, discriminator_real_loss=1.392, discriminator_fake_loss=1.26, generator_loss=29.66, generator_mel_loss=18.65, generator_kl_loss=1.417, generator_dur_loss=1.687, generator_adv_loss=2.099, generator_feat_match_loss=5.805, over 44.00 samples.], tot_loss[discriminator_loss=2.694, discriminator_real_loss=1.367, discriminator_fake_loss=1.327, generator_loss=28.3, generator_mel_loss=17.92, generator_kl_loss=1.399, generator_dur_loss=1.756, generator_adv_loss=1.978, generator_feat_match_loss=5.248, over 1674.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 08:48:15,130 INFO [train.py:527] (2/6) Epoch 552, batch 76, global_batch_idx: 68400, batch size: 48, loss[discriminator_loss=2.687, discriminator_real_loss=1.382, discriminator_fake_loss=1.306, generator_loss=28.67, generator_mel_loss=18.17, generator_kl_loss=1.517, generator_dur_loss=1.687, generator_adv_loss=1.941, generator_feat_match_loss=5.353, over 48.00 samples.], tot_loss[discriminator_loss=2.705, discriminator_real_loss=1.373, discriminator_fake_loss=1.333, generator_loss=28.33, generator_mel_loss=17.95, generator_kl_loss=1.417, generator_dur_loss=1.756, generator_adv_loss=1.965, generator_feat_match_loss=5.24, over 4728.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 08:48:15,132 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 08:48:23,804 INFO [train.py:591] (2/6) Epoch 552, validation: discriminator_loss=2.71, discriminator_real_loss=1.453, discriminator_fake_loss=1.257, generator_loss=27.34, generator_mel_loss=18.36, generator_kl_loss=1.226, generator_dur_loss=1.809, generator_adv_loss=1.958, generator_feat_match_loss=3.99, over 100.00 samples.
2024-03-14 08:48:23,805 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 08:50:34,137 INFO [train.py:919] (2/6) Start epoch 553
2024-03-14 08:51:04,245 INFO [train.py:527] (2/6) Epoch 553, batch 2, global_batch_idx: 68450, batch size: 47, loss[discriminator_loss=2.684, discriminator_real_loss=1.333, discriminator_fake_loss=1.352, generator_loss=28.48, generator_mel_loss=18.05, generator_kl_loss=1.469, generator_dur_loss=1.723, generator_adv_loss=1.95, generator_feat_match_loss=5.289, over 47.00 samples.], tot_loss[discriminator_loss=2.748, discriminator_real_loss=1.352, discriminator_fake_loss=1.396, generator_loss=28.56, generator_mel_loss=17.99, generator_kl_loss=1.506, generator_dur_loss=1.759, generator_adv_loss=2.004, generator_feat_match_loss=5.308, over 157.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 08:53:26,871 INFO [train.py:527] (2/6) Epoch 553, batch 52, global_batch_idx: 68500, batch size: 96, loss[discriminator_loss=2.692, discriminator_real_loss=1.371, discriminator_fake_loss=1.321, generator_loss=28.98, generator_mel_loss=17.98, generator_kl_loss=1.277, generator_dur_loss=1.872, generator_adv_loss=2.016, generator_feat_match_loss=5.828, over 96.00 samples.], tot_loss[discriminator_loss=2.702, discriminator_real_loss=1.359, discriminator_fake_loss=1.343, generator_loss=28.24, generator_mel_loss=17.95, generator_kl_loss=1.379, generator_dur_loss=1.77, generator_adv_loss=1.962, generator_feat_match_loss=5.184, over 3279.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 08:55:46,702 INFO [train.py:527] (2/6) Epoch 553, batch 102, global_batch_idx: 68550, batch size: 25, loss[discriminator_loss=2.677, discriminator_real_loss=1.439, discriminator_fake_loss=1.238, generator_loss=30.27, generator_mel_loss=18.81, generator_kl_loss=1.796, generator_dur_loss=1.56, generator_adv_loss=2.098, generator_feat_match_loss=6.012, over 25.00 samples.], tot_loss[discriminator_loss=2.705, discriminator_real_loss=1.363, discriminator_fake_loss=1.342, generator_loss=28.29, generator_mel_loss=17.96, generator_kl_loss=1.403, generator_dur_loss=1.755, generator_adv_loss=1.956, generator_feat_match_loss=5.219, over 5919.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 08:56:48,244 INFO [train.py:919] (2/6) Start epoch 554
2024-03-14 08:58:31,872 INFO [train.py:527] (2/6) Epoch 554, batch 28, global_batch_idx: 68600, batch size: 48, loss[discriminator_loss=2.746, discriminator_real_loss=1.454, discriminator_fake_loss=1.293, generator_loss=27.69, generator_mel_loss=17.88, generator_kl_loss=1.554, generator_dur_loss=1.676, generator_adv_loss=1.825, generator_feat_match_loss=4.758, over 48.00 samples.], tot_loss[discriminator_loss=2.714, discriminator_real_loss=1.374, discriminator_fake_loss=1.339, generator_loss=28.41, generator_mel_loss=18, generator_kl_loss=1.413, generator_dur_loss=1.747, generator_adv_loss=1.957, generator_feat_match_loss=5.291, over 1601.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 08:58:31,874 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 08:58:40,005 INFO [train.py:591] (2/6) Epoch 554, validation: discriminator_loss=2.799, discriminator_real_loss=1.363, discriminator_fake_loss=1.436, generator_loss=26.83, generator_mel_loss=18.15, generator_kl_loss=1.3, generator_dur_loss=1.813, generator_adv_loss=1.742, generator_feat_match_loss=3.828, over 100.00 samples.
2024-03-14 08:58:40,006 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 09:00:58,332 INFO [train.py:527] (2/6) Epoch 554, batch 78, global_batch_idx: 68650, batch size: 16, loss[discriminator_loss=2.622, discriminator_real_loss=1.347, discriminator_fake_loss=1.275, generator_loss=30.11, generator_mel_loss=18.64, generator_kl_loss=1.806, generator_dur_loss=1.621, generator_adv_loss=2.062, generator_feat_match_loss=5.976, over 16.00 samples.], tot_loss[discriminator_loss=2.704, discriminator_real_loss=1.365, discriminator_fake_loss=1.339, generator_loss=28.38, generator_mel_loss=17.96, generator_kl_loss=1.431, generator_dur_loss=1.739, generator_adv_loss=1.968, generator_feat_match_loss=5.28, over 4151.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 09:03:08,588 INFO [train.py:919] (2/6) Start epoch 555
2024-03-14 09:03:43,923 INFO [train.py:527] (2/6) Epoch 555, batch 4, global_batch_idx: 68700, batch size: 68, loss[discriminator_loss=2.675, discriminator_real_loss=1.328, discriminator_fake_loss=1.347, generator_loss=27.98, generator_mel_loss=17.56, generator_kl_loss=1.376, generator_dur_loss=1.693, generator_adv_loss=2.047, generator_feat_match_loss=5.308, over 68.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.385, discriminator_fake_loss=1.33, generator_loss=28.19, generator_mel_loss=17.88, generator_kl_loss=1.433, generator_dur_loss=1.718, generator_adv_loss=1.971, generator_feat_match_loss=5.194, over 306.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 09:06:07,526 INFO [train.py:527] (2/6) Epoch 555, batch 54, global_batch_idx: 68750, batch size: 96, loss[discriminator_loss=2.677, discriminator_real_loss=1.327, discriminator_fake_loss=1.35, generator_loss=27.64, generator_mel_loss=17.7, generator_kl_loss=1.191, generator_dur_loss=1.832, generator_adv_loss=1.949, generator_feat_match_loss=4.96, over 96.00 samples.], tot_loss[discriminator_loss=2.704, discriminator_real_loss=1.363, discriminator_fake_loss=1.34, generator_loss=28.28, generator_mel_loss=17.97, generator_kl_loss=1.406, generator_dur_loss=1.75, generator_adv_loss=1.962, generator_feat_match_loss=5.189, over 3162.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 09:08:29,722 INFO [train.py:527] (2/6) Epoch 555, batch 104, global_batch_idx: 68800, batch size: 42, loss[discriminator_loss=2.73, discriminator_real_loss=1.461, discriminator_fake_loss=1.269, generator_loss=27.45, generator_mel_loss=17.61, generator_kl_loss=1.47, generator_dur_loss=1.658, generator_adv_loss=1.891, generator_feat_match_loss=4.822, over 42.00 samples.], tot_loss[discriminator_loss=2.71, discriminator_real_loss=1.368, discriminator_fake_loss=1.343, generator_loss=28.28, generator_mel_loss=18, generator_kl_loss=1.409, generator_dur_loss=1.751, generator_adv_loss=1.958, generator_feat_match_loss=5.167, over 5975.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 09:08:29,724 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 09:08:38,552 INFO [train.py:591] (2/6) Epoch 555, validation: discriminator_loss=2.751, discriminator_real_loss=1.348, discriminator_fake_loss=1.403, generator_loss=27.21, generator_mel_loss=18.31, generator_kl_loss=1.253, generator_dur_loss=1.809, generator_adv_loss=1.761, generator_feat_match_loss=4.076, over 100.00 samples.
2024-03-14 09:08:38,553 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 09:09:32,727 INFO [train.py:919] (2/6) Start epoch 556
2024-03-14 09:11:22,838 INFO [train.py:527] (2/6) Epoch 556, batch 30, global_batch_idx: 68850, batch size: 68, loss[discriminator_loss=2.748, discriminator_real_loss=1.406, discriminator_fake_loss=1.342, generator_loss=27.96, generator_mel_loss=17.83, generator_kl_loss=1.321, generator_dur_loss=1.796, generator_adv_loss=1.976, generator_feat_match_loss=5.034, over 68.00 samples.], tot_loss[discriminator_loss=2.688, discriminator_real_loss=1.357, discriminator_fake_loss=1.331, generator_loss=28.75, generator_mel_loss=18.04, generator_kl_loss=1.44, generator_dur_loss=1.743, generator_adv_loss=2.013, generator_feat_match_loss=5.51, over 1760.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 09:13:42,392 INFO [train.py:527] (2/6) Epoch 556, batch 80, global_batch_idx: 68900, batch size: 96, loss[discriminator_loss=2.718, discriminator_real_loss=1.347, discriminator_fake_loss=1.371, generator_loss=27.05, generator_mel_loss=17.21, generator_kl_loss=1.255, generator_dur_loss=1.857, generator_adv_loss=1.948, generator_feat_match_loss=4.788, over 96.00 samples.], tot_loss[discriminator_loss=2.708, discriminator_real_loss=1.374, discriminator_fake_loss=1.334, generator_loss=28.4, generator_mel_loss=17.97, generator_kl_loss=1.422, generator_dur_loss=1.749, generator_adv_loss=1.982, generator_feat_match_loss=5.269, over 4481.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 09:15:43,980 INFO [train.py:919] (2/6) Start epoch 557
2024-03-14 09:16:26,714 INFO [train.py:527] (2/6) Epoch 557, batch 6, global_batch_idx: 68950, batch size: 25, loss[discriminator_loss=2.642, discriminator_real_loss=1.326, discriminator_fake_loss=1.316, generator_loss=30.95, generator_mel_loss=19.34, generator_kl_loss=1.792, generator_dur_loss=1.538, generator_adv_loss=1.867, generator_feat_match_loss=6.42, over 25.00 samples.], tot_loss[discriminator_loss=2.7, discriminator_real_loss=1.336, discriminator_fake_loss=1.364, generator_loss=28.12, generator_mel_loss=17.75, generator_kl_loss=1.451, generator_dur_loss=1.789, generator_adv_loss=1.963, generator_feat_match_loss=5.173, over 437.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 09:18:48,184 INFO [train.py:527] (2/6) Epoch 557, batch 56, global_batch_idx: 69000, batch size: 50, loss[discriminator_loss=2.692, discriminator_real_loss=1.398, discriminator_fake_loss=1.295, generator_loss=29.25, generator_mel_loss=18.41, generator_kl_loss=1.55, generator_dur_loss=1.677, generator_adv_loss=2.004, generator_feat_match_loss=5.608, over 50.00 samples.], tot_loss[discriminator_loss=2.709, discriminator_real_loss=1.373, discriminator_fake_loss=1.336, generator_loss=28.16, generator_mel_loss=17.94, generator_kl_loss=1.41, generator_dur_loss=1.763, generator_adv_loss=1.954, generator_feat_match_loss=5.092, over 3435.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 09:18:48,186 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 09:18:56,043 INFO [train.py:591] (2/6) Epoch 557, validation: discriminator_loss=2.752, discriminator_real_loss=1.44, discriminator_fake_loss=1.312, generator_loss=27.3, generator_mel_loss=17.78, generator_kl_loss=1.173, generator_dur_loss=1.798, generator_adv_loss=1.926, generator_feat_match_loss=4.623, over 100.00 samples.
2024-03-14 09:18:56,044 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 09:21:15,875 INFO [train.py:527] (2/6) Epoch 557, batch 106, global_batch_idx: 69050, batch size: 96, loss[discriminator_loss=2.722, discriminator_real_loss=1.414, discriminator_fake_loss=1.307, generator_loss=27.63, generator_mel_loss=17.55, generator_kl_loss=1.391, generator_dur_loss=1.878, generator_adv_loss=1.9, generator_feat_match_loss=4.914, over 96.00 samples.], tot_loss[discriminator_loss=2.714, discriminator_real_loss=1.377, discriminator_fake_loss=1.337, generator_loss=28.25, generator_mel_loss=17.98, generator_kl_loss=1.417, generator_dur_loss=1.755, generator_adv_loss=1.961, generator_feat_match_loss=5.137, over 6143.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 09:22:06,385 INFO [train.py:919] (2/6) Start epoch 558
2024-03-14 09:24:03,497 INFO [train.py:527] (2/6) Epoch 558, batch 32, global_batch_idx: 69100, batch size: 50, loss[discriminator_loss=2.717, discriminator_real_loss=1.474, discriminator_fake_loss=1.243, generator_loss=28.5, generator_mel_loss=18.09, generator_kl_loss=1.53, generator_dur_loss=1.699, generator_adv_loss=1.95, generator_feat_match_loss=5.224, over 50.00 samples.], tot_loss[discriminator_loss=2.708, discriminator_real_loss=1.374, discriminator_fake_loss=1.334, generator_loss=28.26, generator_mel_loss=17.99, generator_kl_loss=1.406, generator_dur_loss=1.742, generator_adv_loss=1.969, generator_feat_match_loss=5.155, over 1836.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 09:26:24,133 INFO [train.py:527] (2/6) Epoch 558, batch 82, global_batch_idx: 69150, batch size: 80, loss[discriminator_loss=2.72, discriminator_real_loss=1.389, discriminator_fake_loss=1.33, generator_loss=27.88, generator_mel_loss=18.06, generator_kl_loss=1.494, generator_dur_loss=1.802, generator_adv_loss=1.878, generator_feat_match_loss=4.647, over 80.00 samples.], tot_loss[discriminator_loss=2.704, discriminator_real_loss=1.365, discriminator_fake_loss=1.338, generator_loss=28.3, generator_mel_loss=18.02, generator_kl_loss=1.416, generator_dur_loss=1.749, generator_adv_loss=1.966, generator_feat_match_loss=5.146, over 4665.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 09:28:20,816 INFO [train.py:919] (2/6) Start epoch 559
2024-03-14 09:29:07,825 INFO [train.py:527] (2/6) Epoch 559, batch 8, global_batch_idx: 69200, batch size: 52, loss[discriminator_loss=2.709, discriminator_real_loss=1.383, discriminator_fake_loss=1.326, generator_loss=28.65, generator_mel_loss=18.04, generator_kl_loss=1.544, generator_dur_loss=1.651, generator_adv_loss=1.897, generator_feat_match_loss=5.518, over 52.00 samples.], tot_loss[discriminator_loss=2.729, discriminator_real_loss=1.37, discriminator_fake_loss=1.359, generator_loss=28.22, generator_mel_loss=17.92, generator_kl_loss=1.419, generator_dur_loss=1.754, generator_adv_loss=1.954, generator_feat_match_loss=5.171, over 600.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 09:29:07,827 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 09:29:15,986 INFO [train.py:591] (2/6) Epoch 559, validation: discriminator_loss=2.722, discriminator_real_loss=1.383, discriminator_fake_loss=1.339, generator_loss=27.66, generator_mel_loss=18.38, generator_kl_loss=1.27, generator_dur_loss=1.798, generator_adv_loss=1.825, generator_feat_match_loss=4.393, over 100.00 samples.
2024-03-14 09:29:16,014 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 09:31:36,850 INFO [train.py:527] (2/6) Epoch 559, batch 58, global_batch_idx: 69250, batch size: 42, loss[discriminator_loss=2.683, discriminator_real_loss=1.429, discriminator_fake_loss=1.253, generator_loss=29.43, generator_mel_loss=18.82, generator_kl_loss=1.529, generator_dur_loss=1.632, generator_adv_loss=1.938, generator_feat_match_loss=5.508, over 42.00 samples.], tot_loss[discriminator_loss=2.703, discriminator_real_loss=1.366, discriminator_fake_loss=1.337, generator_loss=28.36, generator_mel_loss=17.99, generator_kl_loss=1.418, generator_dur_loss=1.739, generator_adv_loss=1.962, generator_feat_match_loss=5.246, over 3449.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 09:33:58,933 INFO [train.py:527] (2/6) Epoch 559, batch 108, global_batch_idx: 69300, batch size: 70, loss[discriminator_loss=2.686, discriminator_real_loss=1.408, discriminator_fake_loss=1.278, generator_loss=26.91, generator_mel_loss=17.34, generator_kl_loss=1.355, generator_dur_loss=1.749, generator_adv_loss=1.89, generator_feat_match_loss=4.568, over 70.00 samples.], tot_loss[discriminator_loss=2.703, discriminator_real_loss=1.368, discriminator_fake_loss=1.335, generator_loss=28.35, generator_mel_loss=17.95, generator_kl_loss=1.416, generator_dur_loss=1.751, generator_adv_loss=1.965, generator_feat_match_loss=5.278, over 6409.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 09:34:40,725 INFO [train.py:919] (2/6) Start epoch 560
2024-03-14 09:36:42,391 INFO [train.py:527] (2/6) Epoch 560, batch 34, global_batch_idx: 69350, batch size: 52, loss[discriminator_loss=2.692, discriminator_real_loss=1.402, discriminator_fake_loss=1.29, generator_loss=27.89, generator_mel_loss=17.76, generator_kl_loss=1.624, generator_dur_loss=1.679, generator_adv_loss=1.864, generator_feat_match_loss=4.956, over 52.00 samples.], tot_loss[discriminator_loss=2.701, discriminator_real_loss=1.36, discriminator_fake_loss=1.341, generator_loss=28.3, generator_mel_loss=17.9, generator_kl_loss=1.399, generator_dur_loss=1.755, generator_adv_loss=1.955, generator_feat_match_loss=5.291, over 2023.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 09:39:03,985 INFO [train.py:527] (2/6) Epoch 560, batch 84, global_batch_idx: 69400, batch size: 55, loss[discriminator_loss=2.712, discriminator_real_loss=1.396, discriminator_fake_loss=1.316, generator_loss=28.83, generator_mel_loss=18.49, generator_kl_loss=1.463, generator_dur_loss=1.708, generator_adv_loss=1.951, generator_feat_match_loss=5.219, over 55.00 samples.], tot_loss[discriminator_loss=2.708, discriminator_real_loss=1.364, discriminator_fake_loss=1.343, generator_loss=28.33, generator_mel_loss=17.95, generator_kl_loss=1.419, generator_dur_loss=1.754, generator_adv_loss=1.96, generator_feat_match_loss=5.25, over 4904.00 samples.], cur_lr_g: 1.87e-04, cur_lr_d: 1.87e-04, 
2024-03-14 09:39:03,987 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 09:39:13,163 INFO [train.py:591] (2/6) Epoch 560, validation: discriminator_loss=2.76, discriminator_real_loss=1.461, discriminator_fake_loss=1.3, generator_loss=27.48, generator_mel_loss=18.44, generator_kl_loss=1.17, generator_dur_loss=1.817, generator_adv_loss=1.925, generator_feat_match_loss=4.129, over 100.00 samples.
2024-03-14 09:39:13,164 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 09:40:59,933 INFO [train.py:919] (2/6) Start epoch 561
2024-03-14 09:41:52,103 INFO [train.py:527] (2/6) Epoch 561, batch 10, global_batch_idx: 69450, batch size: 42, loss[discriminator_loss=2.758, discriminator_real_loss=1.48, discriminator_fake_loss=1.278, generator_loss=27.76, generator_mel_loss=18.2, generator_kl_loss=1.551, generator_dur_loss=1.653, generator_adv_loss=1.897, generator_feat_match_loss=4.451, over 42.00 samples.], tot_loss[discriminator_loss=2.712, discriminator_real_loss=1.355, discriminator_fake_loss=1.357, generator_loss=28.36, generator_mel_loss=18.07, generator_kl_loss=1.405, generator_dur_loss=1.769, generator_adv_loss=1.947, generator_feat_match_loss=5.171, over 681.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 09:44:11,604 INFO [train.py:527] (2/6) Epoch 561, batch 60, global_batch_idx: 69500, batch size: 74, loss[discriminator_loss=2.675, discriminator_real_loss=1.285, discriminator_fake_loss=1.39, generator_loss=27.59, generator_mel_loss=17.68, generator_kl_loss=1.352, generator_dur_loss=1.769, generator_adv_loss=2.145, generator_feat_match_loss=4.648, over 74.00 samples.], tot_loss[discriminator_loss=2.704, discriminator_real_loss=1.361, discriminator_fake_loss=1.343, generator_loss=28.34, generator_mel_loss=17.96, generator_kl_loss=1.428, generator_dur_loss=1.737, generator_adv_loss=1.963, generator_feat_match_loss=5.253, over 3480.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 09:46:29,824 INFO [train.py:527] (2/6) Epoch 561, batch 110, global_batch_idx: 69550, batch size: 77, loss[discriminator_loss=2.707, discriminator_real_loss=1.363, discriminator_fake_loss=1.344, generator_loss=28.23, generator_mel_loss=18.06, generator_kl_loss=1.363, generator_dur_loss=1.807, generator_adv_loss=2.018, generator_feat_match_loss=4.984, over 77.00 samples.], tot_loss[discriminator_loss=2.705, discriminator_real_loss=1.364, discriminator_fake_loss=1.341, generator_loss=28.38, generator_mel_loss=17.97, generator_kl_loss=1.432, generator_dur_loss=1.74, generator_adv_loss=1.963, generator_feat_match_loss=5.278, over 6405.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 09:47:07,708 INFO [train.py:919] (2/6) Start epoch 562
2024-03-14 09:49:14,024 INFO [train.py:527] (2/6) Epoch 562, batch 36, global_batch_idx: 69600, batch size: 31, loss[discriminator_loss=2.667, discriminator_real_loss=1.345, discriminator_fake_loss=1.322, generator_loss=29.49, generator_mel_loss=18.37, generator_kl_loss=1.669, generator_dur_loss=1.602, generator_adv_loss=2.093, generator_feat_match_loss=5.748, over 31.00 samples.], tot_loss[discriminator_loss=2.714, discriminator_real_loss=1.365, discriminator_fake_loss=1.349, generator_loss=28.35, generator_mel_loss=17.99, generator_kl_loss=1.406, generator_dur_loss=1.772, generator_adv_loss=1.956, generator_feat_match_loss=5.228, over 2266.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 09:49:14,025 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 09:49:21,868 INFO [train.py:591] (2/6) Epoch 562, validation: discriminator_loss=2.774, discriminator_real_loss=1.497, discriminator_fake_loss=1.277, generator_loss=27.95, generator_mel_loss=18.5, generator_kl_loss=1.244, generator_dur_loss=1.815, generator_adv_loss=2.012, generator_feat_match_loss=4.385, over 100.00 samples.
2024-03-14 09:49:21,869 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 09:51:41,006 INFO [train.py:527] (2/6) Epoch 562, batch 86, global_batch_idx: 69650, batch size: 15, loss[discriminator_loss=2.665, discriminator_real_loss=1.328, discriminator_fake_loss=1.337, generator_loss=29.4, generator_mel_loss=18.08, generator_kl_loss=1.81, generator_dur_loss=1.615, generator_adv_loss=2.07, generator_feat_match_loss=5.823, over 15.00 samples.], tot_loss[discriminator_loss=2.713, discriminator_real_loss=1.376, discriminator_fake_loss=1.337, generator_loss=28.34, generator_mel_loss=17.99, generator_kl_loss=1.408, generator_dur_loss=1.766, generator_adv_loss=1.962, generator_feat_match_loss=5.211, over 5120.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 09:53:22,912 INFO [train.py:919] (2/6) Start epoch 563
2024-03-14 09:54:19,235 INFO [train.py:527] (2/6) Epoch 563, batch 12, global_batch_idx: 69700, batch size: 88, loss[discriminator_loss=2.661, discriminator_real_loss=1.269, discriminator_fake_loss=1.393, generator_loss=28.99, generator_mel_loss=18.19, generator_kl_loss=1.338, generator_dur_loss=1.914, generator_adv_loss=1.973, generator_feat_match_loss=5.58, over 88.00 samples.], tot_loss[discriminator_loss=2.683, discriminator_real_loss=1.352, discriminator_fake_loss=1.331, generator_loss=28.41, generator_mel_loss=17.95, generator_kl_loss=1.391, generator_dur_loss=1.802, generator_adv_loss=1.96, generator_feat_match_loss=5.305, over 837.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 09:56:37,477 INFO [train.py:527] (2/6) Epoch 563, batch 62, global_batch_idx: 69750, batch size: 44, loss[discriminator_loss=2.71, discriminator_real_loss=1.501, discriminator_fake_loss=1.209, generator_loss=28.09, generator_mel_loss=17.82, generator_kl_loss=1.574, generator_dur_loss=1.66, generator_adv_loss=2.113, generator_feat_match_loss=4.922, over 44.00 samples.], tot_loss[discriminator_loss=2.702, discriminator_real_loss=1.366, discriminator_fake_loss=1.335, generator_loss=28.52, generator_mel_loss=18.03, generator_kl_loss=1.453, generator_dur_loss=1.747, generator_adv_loss=1.977, generator_feat_match_loss=5.31, over 3481.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 09:59:00,213 INFO [train.py:527] (2/6) Epoch 563, batch 112, global_batch_idx: 69800, batch size: 56, loss[discriminator_loss=2.673, discriminator_real_loss=1.379, discriminator_fake_loss=1.295, generator_loss=27.97, generator_mel_loss=17.84, generator_kl_loss=1.512, generator_dur_loss=1.691, generator_adv_loss=1.944, generator_feat_match_loss=4.985, over 56.00 samples.], tot_loss[discriminator_loss=2.698, discriminator_real_loss=1.371, discriminator_fake_loss=1.327, generator_loss=28.42, generator_mel_loss=17.99, generator_kl_loss=1.423, generator_dur_loss=1.753, generator_adv_loss=1.975, generator_feat_match_loss=5.286, over 6413.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 09:59:00,214 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 09:59:08,735 INFO [train.py:591] (2/6) Epoch 563, validation: discriminator_loss=2.728, discriminator_real_loss=1.386, discriminator_fake_loss=1.342, generator_loss=26.35, generator_mel_loss=17.75, generator_kl_loss=1.292, generator_dur_loss=1.808, generator_adv_loss=1.812, generator_feat_match_loss=3.694, over 100.00 samples.
2024-03-14 09:59:08,737 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 09:59:37,639 INFO [train.py:919] (2/6) Start epoch 564
2024-03-14 10:01:47,472 INFO [train.py:527] (2/6) Epoch 564, batch 38, global_batch_idx: 69850, batch size: 13, loss[discriminator_loss=2.642, discriminator_real_loss=1.499, discriminator_fake_loss=1.144, generator_loss=28.79, generator_mel_loss=18.01, generator_kl_loss=1.925, generator_dur_loss=1.614, generator_adv_loss=1.986, generator_feat_match_loss=5.252, over 13.00 samples.], tot_loss[discriminator_loss=2.693, discriminator_real_loss=1.37, discriminator_fake_loss=1.323, generator_loss=28.53, generator_mel_loss=17.99, generator_kl_loss=1.424, generator_dur_loss=1.749, generator_adv_loss=1.995, generator_feat_match_loss=5.367, over 2089.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 10:04:04,316 INFO [train.py:527] (2/6) Epoch 564, batch 88, global_batch_idx: 69900, batch size: 47, loss[discriminator_loss=2.695, discriminator_real_loss=1.403, discriminator_fake_loss=1.293, generator_loss=27.61, generator_mel_loss=17.62, generator_kl_loss=1.443, generator_dur_loss=1.66, generator_adv_loss=1.872, generator_feat_match_loss=5.014, over 47.00 samples.], tot_loss[discriminator_loss=2.695, discriminator_real_loss=1.364, discriminator_fake_loss=1.331, generator_loss=28.46, generator_mel_loss=17.97, generator_kl_loss=1.413, generator_dur_loss=1.752, generator_adv_loss=1.981, generator_feat_match_loss=5.344, over 4976.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 10:05:43,459 INFO [train.py:919] (2/6) Start epoch 565
2024-03-14 10:06:48,915 INFO [train.py:527] (2/6) Epoch 565, batch 14, global_batch_idx: 69950, batch size: 58, loss[discriminator_loss=2.693, discriminator_real_loss=1.279, discriminator_fake_loss=1.414, generator_loss=28.15, generator_mel_loss=18.01, generator_kl_loss=1.454, generator_dur_loss=1.729, generator_adv_loss=2.02, generator_feat_match_loss=4.942, over 58.00 samples.], tot_loss[discriminator_loss=2.706, discriminator_real_loss=1.373, discriminator_fake_loss=1.333, generator_loss=28.2, generator_mel_loss=18.01, generator_kl_loss=1.395, generator_dur_loss=1.779, generator_adv_loss=1.952, generator_feat_match_loss=5.061, over 949.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 10:09:07,113 INFO [train.py:527] (2/6) Epoch 565, batch 64, global_batch_idx: 70000, batch size: 62, loss[discriminator_loss=2.729, discriminator_real_loss=1.411, discriminator_fake_loss=1.318, generator_loss=28.45, generator_mel_loss=17.87, generator_kl_loss=1.47, generator_dur_loss=1.712, generator_adv_loss=1.981, generator_feat_match_loss=5.417, over 62.00 samples.], tot_loss[discriminator_loss=2.707, discriminator_real_loss=1.369, discriminator_fake_loss=1.338, generator_loss=28.33, generator_mel_loss=18, generator_kl_loss=1.397, generator_dur_loss=1.753, generator_adv_loss=1.953, generator_feat_match_loss=5.222, over 3959.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 10:09:07,114 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 10:09:15,109 INFO [train.py:591] (2/6) Epoch 565, validation: discriminator_loss=2.737, discriminator_real_loss=1.367, discriminator_fake_loss=1.37, generator_loss=27.8, generator_mel_loss=18.61, generator_kl_loss=1.183, generator_dur_loss=1.796, generator_adv_loss=1.851, generator_feat_match_loss=4.361, over 100.00 samples.
2024-03-14 10:09:15,110 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 10:11:33,388 INFO [train.py:527] (2/6) Epoch 565, batch 114, global_batch_idx: 70050, batch size: 72, loss[discriminator_loss=2.702, discriminator_real_loss=1.304, discriminator_fake_loss=1.398, generator_loss=28.59, generator_mel_loss=18.28, generator_kl_loss=1.245, generator_dur_loss=1.786, generator_adv_loss=2.092, generator_feat_match_loss=5.187, over 72.00 samples.], tot_loss[discriminator_loss=2.702, discriminator_real_loss=1.364, discriminator_fake_loss=1.337, generator_loss=28.46, generator_mel_loss=18.05, generator_kl_loss=1.416, generator_dur_loss=1.748, generator_adv_loss=1.969, generator_feat_match_loss=5.28, over 6802.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 10:11:58,823 INFO [train.py:919] (2/6) Start epoch 566
2024-03-14 10:14:15,707 INFO [train.py:527] (2/6) Epoch 566, batch 40, global_batch_idx: 70100, batch size: 42, loss[discriminator_loss=2.739, discriminator_real_loss=1.382, discriminator_fake_loss=1.357, generator_loss=27.24, generator_mel_loss=17.48, generator_kl_loss=1.548, generator_dur_loss=1.693, generator_adv_loss=1.985, generator_feat_match_loss=4.541, over 42.00 samples.], tot_loss[discriminator_loss=2.708, discriminator_real_loss=1.37, discriminator_fake_loss=1.338, generator_loss=28.41, generator_mel_loss=17.99, generator_kl_loss=1.411, generator_dur_loss=1.766, generator_adv_loss=1.955, generator_feat_match_loss=5.283, over 2388.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 10:16:36,141 INFO [train.py:527] (2/6) Epoch 566, batch 90, global_batch_idx: 70150, batch size: 66, loss[discriminator_loss=2.666, discriminator_real_loss=1.36, discriminator_fake_loss=1.306, generator_loss=28.72, generator_mel_loss=17.85, generator_kl_loss=1.384, generator_dur_loss=1.812, generator_adv_loss=2.086, generator_feat_match_loss=5.594, over 66.00 samples.], tot_loss[discriminator_loss=2.706, discriminator_real_loss=1.367, discriminator_fake_loss=1.338, generator_loss=28.45, generator_mel_loss=18.02, generator_kl_loss=1.421, generator_dur_loss=1.751, generator_adv_loss=1.966, generator_feat_match_loss=5.298, over 5045.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 10:18:08,293 INFO [train.py:919] (2/6) Start epoch 567
2024-03-14 10:19:16,564 INFO [train.py:527] (2/6) Epoch 567, batch 16, global_batch_idx: 70200, batch size: 52, loss[discriminator_loss=2.724, discriminator_real_loss=1.381, discriminator_fake_loss=1.343, generator_loss=28.05, generator_mel_loss=17.83, generator_kl_loss=1.569, generator_dur_loss=1.704, generator_adv_loss=1.943, generator_feat_match_loss=5, over 52.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.372, discriminator_fake_loss=1.344, generator_loss=28.1, generator_mel_loss=17.86, generator_kl_loss=1.429, generator_dur_loss=1.739, generator_adv_loss=1.959, generator_feat_match_loss=5.109, over 968.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 10:19:16,566 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 10:19:24,539 INFO [train.py:591] (2/6) Epoch 567, validation: discriminator_loss=2.776, discriminator_real_loss=1.402, discriminator_fake_loss=1.374, generator_loss=27.35, generator_mel_loss=18.82, generator_kl_loss=1.179, generator_dur_loss=1.806, generator_adv_loss=1.829, generator_feat_match_loss=3.711, over 100.00 samples.
2024-03-14 10:19:24,540 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 10:21:43,335 INFO [train.py:527] (2/6) Epoch 567, batch 66, global_batch_idx: 70250, batch size: 72, loss[discriminator_loss=2.742, discriminator_real_loss=1.426, discriminator_fake_loss=1.316, generator_loss=27.04, generator_mel_loss=17.47, generator_kl_loss=1.262, generator_dur_loss=1.774, generator_adv_loss=1.797, generator_feat_match_loss=4.737, over 72.00 samples.], tot_loss[discriminator_loss=2.711, discriminator_real_loss=1.369, discriminator_fake_loss=1.342, generator_loss=28.33, generator_mel_loss=17.96, generator_kl_loss=1.42, generator_dur_loss=1.749, generator_adv_loss=1.961, generator_feat_match_loss=5.235, over 3787.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 10:24:02,234 INFO [train.py:527] (2/6) Epoch 567, batch 116, global_batch_idx: 70300, batch size: 14, loss[discriminator_loss=2.627, discriminator_real_loss=1.222, discriminator_fake_loss=1.406, generator_loss=32.13, generator_mel_loss=20.43, generator_kl_loss=1.697, generator_dur_loss=1.533, generator_adv_loss=2.028, generator_feat_match_loss=6.439, over 14.00 samples.], tot_loss[discriminator_loss=2.712, discriminator_real_loss=1.367, discriminator_fake_loss=1.344, generator_loss=28.35, generator_mel_loss=17.96, generator_kl_loss=1.422, generator_dur_loss=1.744, generator_adv_loss=1.962, generator_feat_match_loss=5.258, over 6721.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 10:24:23,417 INFO [train.py:919] (2/6) Start epoch 568
2024-03-14 10:26:47,022 INFO [train.py:527] (2/6) Epoch 568, batch 42, global_batch_idx: 70350, batch size: 70, loss[discriminator_loss=2.739, discriminator_real_loss=1.279, discriminator_fake_loss=1.46, generator_loss=28.54, generator_mel_loss=18.43, generator_kl_loss=1.403, generator_dur_loss=1.812, generator_adv_loss=2.012, generator_feat_match_loss=4.881, over 70.00 samples.], tot_loss[discriminator_loss=2.711, discriminator_real_loss=1.369, discriminator_fake_loss=1.342, generator_loss=28.45, generator_mel_loss=18, generator_kl_loss=1.427, generator_dur_loss=1.745, generator_adv_loss=1.967, generator_feat_match_loss=5.312, over 2505.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 10:29:06,493 INFO [train.py:527] (2/6) Epoch 568, batch 92, global_batch_idx: 70400, batch size: 31, loss[discriminator_loss=2.567, discriminator_real_loss=1.304, discriminator_fake_loss=1.263, generator_loss=29.06, generator_mel_loss=18.58, generator_kl_loss=1.613, generator_dur_loss=1.62, generator_adv_loss=2.03, generator_feat_match_loss=5.217, over 31.00 samples.], tot_loss[discriminator_loss=2.705, discriminator_real_loss=1.366, discriminator_fake_loss=1.339, generator_loss=28.47, generator_mel_loss=18, generator_kl_loss=1.416, generator_dur_loss=1.754, generator_adv_loss=1.97, generator_feat_match_loss=5.331, over 5440.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 10:29:06,495 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 10:29:15,280 INFO [train.py:591] (2/6) Epoch 568, validation: discriminator_loss=2.809, discriminator_real_loss=1.305, discriminator_fake_loss=1.504, generator_loss=27.65, generator_mel_loss=18.58, generator_kl_loss=1.196, generator_dur_loss=1.813, generator_adv_loss=1.674, generator_feat_match_loss=4.381, over 100.00 samples.
2024-03-14 10:29:15,281 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 10:30:42,360 INFO [train.py:919] (2/6) Start epoch 569
2024-03-14 10:31:56,615 INFO [train.py:527] (2/6) Epoch 569, batch 18, global_batch_idx: 70450, batch size: 45, loss[discriminator_loss=2.679, discriminator_real_loss=1.42, discriminator_fake_loss=1.259, generator_loss=28.34, generator_mel_loss=17.8, generator_kl_loss=1.689, generator_dur_loss=1.655, generator_adv_loss=1.942, generator_feat_match_loss=5.256, over 45.00 samples.], tot_loss[discriminator_loss=2.706, discriminator_real_loss=1.361, discriminator_fake_loss=1.345, generator_loss=28.37, generator_mel_loss=18.05, generator_kl_loss=1.47, generator_dur_loss=1.714, generator_adv_loss=1.97, generator_feat_match_loss=5.166, over 959.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 10:34:16,959 INFO [train.py:527] (2/6) Epoch 569, batch 68, global_batch_idx: 70500, batch size: 83, loss[discriminator_loss=2.702, discriminator_real_loss=1.24, discriminator_fake_loss=1.462, generator_loss=27.92, generator_mel_loss=18.05, generator_kl_loss=1.236, generator_dur_loss=1.831, generator_adv_loss=2.095, generator_feat_match_loss=4.71, over 83.00 samples.], tot_loss[discriminator_loss=2.705, discriminator_real_loss=1.365, discriminator_fake_loss=1.34, generator_loss=28.42, generator_mel_loss=18.01, generator_kl_loss=1.392, generator_dur_loss=1.756, generator_adv_loss=1.966, generator_feat_match_loss=5.295, over 4124.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 10:36:35,852 INFO [train.py:527] (2/6) Epoch 569, batch 118, global_batch_idx: 70550, batch size: 88, loss[discriminator_loss=2.766, discriminator_real_loss=1.305, discriminator_fake_loss=1.461, generator_loss=28.19, generator_mel_loss=18.02, generator_kl_loss=1.265, generator_dur_loss=1.892, generator_adv_loss=1.93, generator_feat_match_loss=5.076, over 88.00 samples.], tot_loss[discriminator_loss=2.701, discriminator_real_loss=1.361, discriminator_fake_loss=1.34, generator_loss=28.44, generator_mel_loss=18.02, generator_kl_loss=1.394, generator_dur_loss=1.758, generator_adv_loss=1.974, generator_feat_match_loss=5.298, over 6954.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 10:36:51,828 INFO [train.py:919] (2/6) Start epoch 570
2024-03-14 10:39:15,971 INFO [train.py:527] (2/6) Epoch 570, batch 44, global_batch_idx: 70600, batch size: 25, loss[discriminator_loss=2.727, discriminator_real_loss=1.441, discriminator_fake_loss=1.286, generator_loss=29.51, generator_mel_loss=18.66, generator_kl_loss=1.804, generator_dur_loss=1.52, generator_adv_loss=1.867, generator_feat_match_loss=5.666, over 25.00 samples.], tot_loss[discriminator_loss=2.693, discriminator_real_loss=1.366, discriminator_fake_loss=1.327, generator_loss=28.37, generator_mel_loss=18, generator_kl_loss=1.424, generator_dur_loss=1.753, generator_adv_loss=1.973, generator_feat_match_loss=5.222, over 2626.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 10:39:15,973 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 10:39:24,036 INFO [train.py:591] (2/6) Epoch 570, validation: discriminator_loss=2.732, discriminator_real_loss=1.37, discriminator_fake_loss=1.362, generator_loss=27.4, generator_mel_loss=18.38, generator_kl_loss=1.202, generator_dur_loss=1.795, generator_adv_loss=1.795, generator_feat_match_loss=4.225, over 100.00 samples.
2024-03-14 10:39:24,037 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 10:41:42,114 INFO [train.py:527] (2/6) Epoch 570, batch 94, global_batch_idx: 70650, batch size: 52, loss[discriminator_loss=2.712, discriminator_real_loss=1.386, discriminator_fake_loss=1.326, generator_loss=29.39, generator_mel_loss=18.21, generator_kl_loss=1.477, generator_dur_loss=1.713, generator_adv_loss=2.036, generator_feat_match_loss=5.957, over 52.00 samples.], tot_loss[discriminator_loss=2.697, discriminator_real_loss=1.369, discriminator_fake_loss=1.328, generator_loss=28.39, generator_mel_loss=18.01, generator_kl_loss=1.423, generator_dur_loss=1.746, generator_adv_loss=1.973, generator_feat_match_loss=5.23, over 5296.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 10:43:05,028 INFO [train.py:919] (2/6) Start epoch 571
2024-03-14 10:44:25,908 INFO [train.py:527] (2/6) Epoch 571, batch 20, global_batch_idx: 70700, batch size: 12, loss[discriminator_loss=2.698, discriminator_real_loss=1.389, discriminator_fake_loss=1.309, generator_loss=28.66, generator_mel_loss=17.39, generator_kl_loss=1.792, generator_dur_loss=1.558, generator_adv_loss=1.877, generator_feat_match_loss=6.039, over 12.00 samples.], tot_loss[discriminator_loss=2.693, discriminator_real_loss=1.353, discriminator_fake_loss=1.34, generator_loss=28.21, generator_mel_loss=17.91, generator_kl_loss=1.394, generator_dur_loss=1.777, generator_adv_loss=1.958, generator_feat_match_loss=5.173, over 1248.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 10:46:43,895 INFO [train.py:527] (2/6) Epoch 571, batch 70, global_batch_idx: 70750, batch size: 74, loss[discriminator_loss=2.687, discriminator_real_loss=1.461, discriminator_fake_loss=1.226, generator_loss=28.19, generator_mel_loss=17.67, generator_kl_loss=1.165, generator_dur_loss=1.798, generator_adv_loss=1.992, generator_feat_match_loss=5.559, over 74.00 samples.], tot_loss[discriminator_loss=2.703, discriminator_real_loss=1.363, discriminator_fake_loss=1.34, generator_loss=28.29, generator_mel_loss=17.94, generator_kl_loss=1.398, generator_dur_loss=1.759, generator_adv_loss=1.958, generator_feat_match_loss=5.239, over 4181.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 10:49:02,178 INFO [train.py:527] (2/6) Epoch 571, batch 120, global_batch_idx: 70800, batch size: 31, loss[discriminator_loss=2.594, discriminator_real_loss=1.368, discriminator_fake_loss=1.226, generator_loss=30.26, generator_mel_loss=18.65, generator_kl_loss=1.576, generator_dur_loss=1.636, generator_adv_loss=2.021, generator_feat_match_loss=6.377, over 31.00 samples.], tot_loss[discriminator_loss=2.701, discriminator_real_loss=1.366, discriminator_fake_loss=1.335, generator_loss=28.41, generator_mel_loss=17.98, generator_kl_loss=1.408, generator_dur_loss=1.75, generator_adv_loss=1.966, generator_feat_match_loss=5.304, over 6924.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 10:49:02,180 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 10:49:10,965 INFO [train.py:591] (2/6) Epoch 571, validation: discriminator_loss=2.778, discriminator_real_loss=1.319, discriminator_fake_loss=1.459, generator_loss=27.05, generator_mel_loss=18.21, generator_kl_loss=1.249, generator_dur_loss=1.805, generator_adv_loss=1.701, generator_feat_match_loss=4.082, over 100.00 samples.
2024-03-14 10:49:10,966 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 10:49:20,853 INFO [train.py:919] (2/6) Start epoch 572
2024-03-14 10:51:52,205 INFO [train.py:527] (2/6) Epoch 572, batch 46, global_batch_idx: 70850, batch size: 70, loss[discriminator_loss=2.656, discriminator_real_loss=1.373, discriminator_fake_loss=1.282, generator_loss=28.33, generator_mel_loss=17.92, generator_kl_loss=1.283, generator_dur_loss=1.783, generator_adv_loss=1.956, generator_feat_match_loss=5.383, over 70.00 samples.], tot_loss[discriminator_loss=2.713, discriminator_real_loss=1.377, discriminator_fake_loss=1.336, generator_loss=28.21, generator_mel_loss=17.96, generator_kl_loss=1.383, generator_dur_loss=1.745, generator_adv_loss=1.959, generator_feat_match_loss=5.165, over 2688.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 10:54:11,192 INFO [train.py:527] (2/6) Epoch 572, batch 96, global_batch_idx: 70900, batch size: 66, loss[discriminator_loss=2.725, discriminator_real_loss=1.44, discriminator_fake_loss=1.284, generator_loss=28.01, generator_mel_loss=17.82, generator_kl_loss=1.377, generator_dur_loss=1.791, generator_adv_loss=1.953, generator_feat_match_loss=5.07, over 66.00 samples.], tot_loss[discriminator_loss=2.708, discriminator_real_loss=1.372, discriminator_fake_loss=1.336, generator_loss=28.27, generator_mel_loss=17.96, generator_kl_loss=1.401, generator_dur_loss=1.744, generator_adv_loss=1.96, generator_feat_match_loss=5.214, over 5543.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 10:55:27,797 INFO [train.py:919] (2/6) Start epoch 573
2024-03-14 10:56:53,852 INFO [train.py:527] (2/6) Epoch 573, batch 22, global_batch_idx: 70950, batch size: 61, loss[discriminator_loss=2.664, discriminator_real_loss=1.346, discriminator_fake_loss=1.317, generator_loss=28.83, generator_mel_loss=17.98, generator_kl_loss=1.354, generator_dur_loss=1.772, generator_adv_loss=2.037, generator_feat_match_loss=5.689, over 61.00 samples.], tot_loss[discriminator_loss=2.697, discriminator_real_loss=1.355, discriminator_fake_loss=1.343, generator_loss=28.57, generator_mel_loss=18.12, generator_kl_loss=1.397, generator_dur_loss=1.756, generator_adv_loss=1.956, generator_feat_match_loss=5.348, over 1324.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 10:59:14,979 INFO [train.py:527] (2/6) Epoch 573, batch 72, global_batch_idx: 71000, batch size: 80, loss[discriminator_loss=2.679, discriminator_real_loss=1.339, discriminator_fake_loss=1.34, generator_loss=28.68, generator_mel_loss=18.37, generator_kl_loss=1.355, generator_dur_loss=1.876, generator_adv_loss=1.961, generator_feat_match_loss=5.122, over 80.00 samples.], tot_loss[discriminator_loss=2.706, discriminator_real_loss=1.366, discriminator_fake_loss=1.34, generator_loss=28.4, generator_mel_loss=18.01, generator_kl_loss=1.395, generator_dur_loss=1.759, generator_adv_loss=1.959, generator_feat_match_loss=5.274, over 4348.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 10:59:14,980 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 10:59:23,686 INFO [train.py:591] (2/6) Epoch 573, validation: discriminator_loss=2.787, discriminator_real_loss=1.403, discriminator_fake_loss=1.384, generator_loss=27.98, generator_mel_loss=18.39, generator_kl_loss=1.265, generator_dur_loss=1.82, generator_adv_loss=1.848, generator_feat_match_loss=4.654, over 100.00 samples.
2024-03-14 10:59:23,687 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 11:01:39,162 INFO [train.py:527] (2/6) Epoch 573, batch 122, global_batch_idx: 71050, batch size: 13, loss[discriminator_loss=2.817, discriminator_real_loss=1.49, discriminator_fake_loss=1.327, generator_loss=27.32, generator_mel_loss=17.69, generator_kl_loss=1.794, generator_dur_loss=1.552, generator_adv_loss=1.889, generator_feat_match_loss=4.395, over 13.00 samples.], tot_loss[discriminator_loss=2.703, discriminator_real_loss=1.364, discriminator_fake_loss=1.339, generator_loss=28.43, generator_mel_loss=18.02, generator_kl_loss=1.407, generator_dur_loss=1.761, generator_adv_loss=1.959, generator_feat_match_loss=5.284, over 7239.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 11:01:44,601 INFO [train.py:919] (2/6) Start epoch 574
2024-03-14 11:04:18,830 INFO [train.py:527] (2/6) Epoch 574, batch 48, global_batch_idx: 71100, batch size: 44, loss[discriminator_loss=2.653, discriminator_real_loss=1.432, discriminator_fake_loss=1.221, generator_loss=29.49, generator_mel_loss=18.55, generator_kl_loss=1.598, generator_dur_loss=1.695, generator_adv_loss=2.02, generator_feat_match_loss=5.629, over 44.00 samples.], tot_loss[discriminator_loss=2.692, discriminator_real_loss=1.364, discriminator_fake_loss=1.328, generator_loss=28.57, generator_mel_loss=18.03, generator_kl_loss=1.423, generator_dur_loss=1.735, generator_adv_loss=1.974, generator_feat_match_loss=5.402, over 2690.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 11:06:39,762 INFO [train.py:527] (2/6) Epoch 574, batch 98, global_batch_idx: 71150, batch size: 74, loss[discriminator_loss=2.639, discriminator_real_loss=1.355, discriminator_fake_loss=1.284, generator_loss=28.09, generator_mel_loss=17.65, generator_kl_loss=1.377, generator_dur_loss=1.784, generator_adv_loss=1.96, generator_feat_match_loss=5.318, over 74.00 samples.], tot_loss[discriminator_loss=2.696, discriminator_real_loss=1.366, discriminator_fake_loss=1.33, generator_loss=28.52, generator_mel_loss=18.06, generator_kl_loss=1.414, generator_dur_loss=1.751, generator_adv_loss=1.978, generator_feat_match_loss=5.319, over 5786.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 11:07:51,480 INFO [train.py:919] (2/6) Start epoch 575
2024-03-14 11:09:22,371 INFO [train.py:527] (2/6) Epoch 575, batch 24, global_batch_idx: 71200, batch size: 52, loss[discriminator_loss=2.722, discriminator_real_loss=1.347, discriminator_fake_loss=1.375, generator_loss=27.6, generator_mel_loss=17.83, generator_kl_loss=1.338, generator_dur_loss=1.742, generator_adv_loss=2.059, generator_feat_match_loss=4.632, over 52.00 samples.], tot_loss[discriminator_loss=2.709, discriminator_real_loss=1.365, discriminator_fake_loss=1.344, generator_loss=28.32, generator_mel_loss=17.94, generator_kl_loss=1.455, generator_dur_loss=1.741, generator_adv_loss=1.951, generator_feat_match_loss=5.236, over 1380.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 11:09:22,373 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 11:09:30,378 INFO [train.py:591] (2/6) Epoch 575, validation: discriminator_loss=2.755, discriminator_real_loss=1.447, discriminator_fake_loss=1.308, generator_loss=27.86, generator_mel_loss=18.44, generator_kl_loss=1.293, generator_dur_loss=1.801, generator_adv_loss=1.956, generator_feat_match_loss=4.369, over 100.00 samples.
2024-03-14 11:09:30,379 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 11:11:48,588 INFO [train.py:527] (2/6) Epoch 575, batch 74, global_batch_idx: 71250, batch size: 64, loss[discriminator_loss=2.702, discriminator_real_loss=1.363, discriminator_fake_loss=1.34, generator_loss=29.13, generator_mel_loss=18.26, generator_kl_loss=1.542, generator_dur_loss=1.712, generator_adv_loss=2.046, generator_feat_match_loss=5.568, over 64.00 samples.], tot_loss[discriminator_loss=2.707, discriminator_real_loss=1.371, discriminator_fake_loss=1.335, generator_loss=28.53, generator_mel_loss=18.05, generator_kl_loss=1.437, generator_dur_loss=1.735, generator_adv_loss=1.983, generator_feat_match_loss=5.321, over 4124.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 11:14:03,843 INFO [train.py:919] (2/6) Start epoch 576
2024-03-14 11:14:27,772 INFO [train.py:527] (2/6) Epoch 576, batch 0, global_batch_idx: 71300, batch size: 61, loss[discriminator_loss=2.692, discriminator_real_loss=1.359, discriminator_fake_loss=1.332, generator_loss=27.88, generator_mel_loss=17.69, generator_kl_loss=1.402, generator_dur_loss=1.743, generator_adv_loss=2.145, generator_feat_match_loss=4.893, over 61.00 samples.], tot_loss[discriminator_loss=2.692, discriminator_real_loss=1.359, discriminator_fake_loss=1.332, generator_loss=27.88, generator_mel_loss=17.69, generator_kl_loss=1.402, generator_dur_loss=1.743, generator_adv_loss=2.145, generator_feat_match_loss=4.893, over 61.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 11:16:46,076 INFO [train.py:527] (2/6) Epoch 576, batch 50, global_batch_idx: 71350, batch size: 66, loss[discriminator_loss=2.657, discriminator_real_loss=1.419, discriminator_fake_loss=1.238, generator_loss=29.34, generator_mel_loss=18.26, generator_kl_loss=1.533, generator_dur_loss=1.717, generator_adv_loss=1.84, generator_feat_match_loss=5.984, over 66.00 samples.], tot_loss[discriminator_loss=2.703, discriminator_real_loss=1.362, discriminator_fake_loss=1.341, generator_loss=28.69, generator_mel_loss=18.13, generator_kl_loss=1.426, generator_dur_loss=1.745, generator_adv_loss=1.974, generator_feat_match_loss=5.415, over 2840.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 11:19:06,120 INFO [train.py:527] (2/6) Epoch 576, batch 100, global_batch_idx: 71400, batch size: 74, loss[discriminator_loss=2.713, discriminator_real_loss=1.341, discriminator_fake_loss=1.373, generator_loss=28.41, generator_mel_loss=17.97, generator_kl_loss=1.29, generator_dur_loss=1.782, generator_adv_loss=2.058, generator_feat_match_loss=5.31, over 74.00 samples.], tot_loss[discriminator_loss=2.706, discriminator_real_loss=1.362, discriminator_fake_loss=1.344, generator_loss=28.46, generator_mel_loss=18.02, generator_kl_loss=1.4, generator_dur_loss=1.754, generator_adv_loss=1.966, generator_feat_match_loss=5.321, over 5833.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 11:19:06,122 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 11:19:15,119 INFO [train.py:591] (2/6) Epoch 576, validation: discriminator_loss=2.765, discriminator_real_loss=1.525, discriminator_fake_loss=1.24, generator_loss=27.47, generator_mel_loss=17.97, generator_kl_loss=1.262, generator_dur_loss=1.826, generator_adv_loss=2.129, generator_feat_match_loss=4.284, over 100.00 samples.
2024-03-14 11:19:15,120 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 11:20:16,994 INFO [train.py:919] (2/6) Start epoch 577
2024-03-14 11:21:54,974 INFO [train.py:527] (2/6) Epoch 577, batch 26, global_batch_idx: 71450, batch size: 53, loss[discriminator_loss=2.756, discriminator_real_loss=1.445, discriminator_fake_loss=1.31, generator_loss=28.22, generator_mel_loss=18.22, generator_kl_loss=1.421, generator_dur_loss=1.735, generator_adv_loss=1.852, generator_feat_match_loss=4.993, over 53.00 samples.], tot_loss[discriminator_loss=2.701, discriminator_real_loss=1.363, discriminator_fake_loss=1.338, generator_loss=28.55, generator_mel_loss=18.02, generator_kl_loss=1.4, generator_dur_loss=1.76, generator_adv_loss=1.971, generator_feat_match_loss=5.395, over 1495.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 11:24:14,111 INFO [train.py:527] (2/6) Epoch 577, batch 76, global_batch_idx: 71500, batch size: 55, loss[discriminator_loss=2.715, discriminator_real_loss=1.456, discriminator_fake_loss=1.259, generator_loss=27.65, generator_mel_loss=17.66, generator_kl_loss=1.364, generator_dur_loss=1.679, generator_adv_loss=1.902, generator_feat_match_loss=5.044, over 55.00 samples.], tot_loss[discriminator_loss=2.708, discriminator_real_loss=1.371, discriminator_fake_loss=1.338, generator_loss=28.51, generator_mel_loss=18.04, generator_kl_loss=1.428, generator_dur_loss=1.743, generator_adv_loss=1.967, generator_feat_match_loss=5.341, over 4202.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 11:26:21,142 INFO [train.py:919] (2/6) Start epoch 578
2024-03-14 11:26:50,738 INFO [train.py:527] (2/6) Epoch 578, batch 2, global_batch_idx: 71550, batch size: 14, loss[discriminator_loss=2.652, discriminator_real_loss=1.311, discriminator_fake_loss=1.341, generator_loss=30.92, generator_mel_loss=18.36, generator_kl_loss=1.598, generator_dur_loss=1.642, generator_adv_loss=2.045, generator_feat_match_loss=7.272, over 14.00 samples.], tot_loss[discriminator_loss=2.708, discriminator_real_loss=1.313, discriminator_fake_loss=1.396, generator_loss=28.95, generator_mel_loss=17.98, generator_kl_loss=1.513, generator_dur_loss=1.68, generator_adv_loss=1.947, generator_feat_match_loss=5.828, over 106.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 11:29:09,126 INFO [train.py:527] (2/6) Epoch 578, batch 52, global_batch_idx: 71600, batch size: 62, loss[discriminator_loss=2.718, discriminator_real_loss=1.382, discriminator_fake_loss=1.336, generator_loss=27.61, generator_mel_loss=17.79, generator_kl_loss=1.35, generator_dur_loss=1.754, generator_adv_loss=2.063, generator_feat_match_loss=4.645, over 62.00 samples.], tot_loss[discriminator_loss=2.706, discriminator_real_loss=1.372, discriminator_fake_loss=1.334, generator_loss=28.33, generator_mel_loss=18.01, generator_kl_loss=1.408, generator_dur_loss=1.734, generator_adv_loss=1.954, generator_feat_match_loss=5.218, over 2829.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 11:29:09,128 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 11:29:17,345 INFO [train.py:591] (2/6) Epoch 578, validation: discriminator_loss=2.695, discriminator_real_loss=1.409, discriminator_fake_loss=1.287, generator_loss=26.72, generator_mel_loss=17.84, generator_kl_loss=1.224, generator_dur_loss=1.803, generator_adv_loss=1.928, generator_feat_match_loss=3.927, over 100.00 samples.
2024-03-14 11:29:17,346 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 11:31:36,488 INFO [train.py:527] (2/6) Epoch 578, batch 102, global_batch_idx: 71650, batch size: 52, loss[discriminator_loss=2.74, discriminator_real_loss=1.314, discriminator_fake_loss=1.427, generator_loss=28.39, generator_mel_loss=18.18, generator_kl_loss=1.372, generator_dur_loss=1.684, generator_adv_loss=2.036, generator_feat_match_loss=5.126, over 52.00 samples.], tot_loss[discriminator_loss=2.702, discriminator_real_loss=1.368, discriminator_fake_loss=1.333, generator_loss=28.48, generator_mel_loss=18.07, generator_kl_loss=1.432, generator_dur_loss=1.729, generator_adv_loss=1.962, generator_feat_match_loss=5.285, over 5457.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 11:32:35,042 INFO [train.py:919] (2/6) Start epoch 579
2024-03-14 11:34:17,741 INFO [train.py:527] (2/6) Epoch 579, batch 28, global_batch_idx: 71700, batch size: 72, loss[discriminator_loss=2.739, discriminator_real_loss=1.4, discriminator_fake_loss=1.339, generator_loss=27.67, generator_mel_loss=17.83, generator_kl_loss=1.238, generator_dur_loss=1.804, generator_adv_loss=1.897, generator_feat_match_loss=4.905, over 72.00 samples.], tot_loss[discriminator_loss=2.717, discriminator_real_loss=1.373, discriminator_fake_loss=1.343, generator_loss=28.37, generator_mel_loss=18.05, generator_kl_loss=1.404, generator_dur_loss=1.744, generator_adv_loss=1.948, generator_feat_match_loss=5.222, over 1641.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 11:36:37,134 INFO [train.py:527] (2/6) Epoch 579, batch 78, global_batch_idx: 71750, batch size: 58, loss[discriminator_loss=2.712, discriminator_real_loss=1.452, discriminator_fake_loss=1.261, generator_loss=27.7, generator_mel_loss=17.61, generator_kl_loss=1.376, generator_dur_loss=1.766, generator_adv_loss=2.059, generator_feat_match_loss=4.891, over 58.00 samples.], tot_loss[discriminator_loss=2.707, discriminator_real_loss=1.363, discriminator_fake_loss=1.344, generator_loss=28.41, generator_mel_loss=17.99, generator_kl_loss=1.398, generator_dur_loss=1.752, generator_adv_loss=1.992, generator_feat_match_loss=5.278, over 4428.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 11:38:43,208 INFO [train.py:919] (2/6) Start epoch 580
2024-03-14 11:39:18,841 INFO [train.py:527] (2/6) Epoch 580, batch 4, global_batch_idx: 71800, batch size: 48, loss[discriminator_loss=2.661, discriminator_real_loss=1.251, discriminator_fake_loss=1.41, generator_loss=29.6, generator_mel_loss=18.05, generator_kl_loss=1.628, generator_dur_loss=1.631, generator_adv_loss=2.193, generator_feat_match_loss=6.105, over 48.00 samples.], tot_loss[discriminator_loss=2.703, discriminator_real_loss=1.362, discriminator_fake_loss=1.341, generator_loss=28.74, generator_mel_loss=17.94, generator_kl_loss=1.394, generator_dur_loss=1.758, generator_adv_loss=1.98, generator_feat_match_loss=5.662, over 346.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 11:39:18,844 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 11:39:26,756 INFO [train.py:591] (2/6) Epoch 580, validation: discriminator_loss=2.809, discriminator_real_loss=1.511, discriminator_fake_loss=1.299, generator_loss=27.2, generator_mel_loss=18.01, generator_kl_loss=1.221, generator_dur_loss=1.822, generator_adv_loss=1.993, generator_feat_match_loss=4.153, over 100.00 samples.
2024-03-14 11:39:26,758 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 11:41:44,295 INFO [train.py:527] (2/6) Epoch 580, batch 54, global_batch_idx: 71850, batch size: 59, loss[discriminator_loss=2.757, discriminator_real_loss=1.502, discriminator_fake_loss=1.255, generator_loss=26.92, generator_mel_loss=17.44, generator_kl_loss=1.319, generator_dur_loss=1.719, generator_adv_loss=1.79, generator_feat_match_loss=4.645, over 59.00 samples.], tot_loss[discriminator_loss=2.703, discriminator_real_loss=1.37, discriminator_fake_loss=1.333, generator_loss=28.46, generator_mel_loss=18.02, generator_kl_loss=1.409, generator_dur_loss=1.76, generator_adv_loss=1.971, generator_feat_match_loss=5.3, over 3337.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 11:44:03,566 INFO [train.py:527] (2/6) Epoch 580, batch 104, global_batch_idx: 71900, batch size: 61, loss[discriminator_loss=2.76, discriminator_real_loss=1.507, discriminator_fake_loss=1.253, generator_loss=27.36, generator_mel_loss=17.49, generator_kl_loss=1.253, generator_dur_loss=1.788, generator_adv_loss=1.899, generator_feat_match_loss=4.921, over 61.00 samples.], tot_loss[discriminator_loss=2.708, discriminator_real_loss=1.371, discriminator_fake_loss=1.336, generator_loss=28.41, generator_mel_loss=17.99, generator_kl_loss=1.406, generator_dur_loss=1.762, generator_adv_loss=1.969, generator_feat_match_loss=5.285, over 6321.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 11:44:56,809 INFO [train.py:919] (2/6) Start epoch 581
2024-03-14 11:46:43,777 INFO [train.py:527] (2/6) Epoch 581, batch 30, global_batch_idx: 71950, batch size: 72, loss[discriminator_loss=2.743, discriminator_real_loss=1.349, discriminator_fake_loss=1.394, generator_loss=28.34, generator_mel_loss=17.89, generator_kl_loss=1.375, generator_dur_loss=1.83, generator_adv_loss=1.954, generator_feat_match_loss=5.287, over 72.00 samples.], tot_loss[discriminator_loss=2.714, discriminator_real_loss=1.378, discriminator_fake_loss=1.337, generator_loss=28.42, generator_mel_loss=17.95, generator_kl_loss=1.411, generator_dur_loss=1.745, generator_adv_loss=1.965, generator_feat_match_loss=5.346, over 1842.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 11:49:02,162 INFO [train.py:527] (2/6) Epoch 581, batch 80, global_batch_idx: 72000, batch size: 62, loss[discriminator_loss=2.728, discriminator_real_loss=1.474, discriminator_fake_loss=1.255, generator_loss=28.64, generator_mel_loss=18, generator_kl_loss=1.396, generator_dur_loss=1.767, generator_adv_loss=1.975, generator_feat_match_loss=5.511, over 62.00 samples.], tot_loss[discriminator_loss=2.704, discriminator_real_loss=1.372, discriminator_fake_loss=1.332, generator_loss=28.5, generator_mel_loss=18, generator_kl_loss=1.415, generator_dur_loss=1.742, generator_adv_loss=1.967, generator_feat_match_loss=5.372, over 4640.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 11:49:02,163 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 11:49:11,009 INFO [train.py:591] (2/6) Epoch 581, validation: discriminator_loss=2.754, discriminator_real_loss=1.407, discriminator_fake_loss=1.347, generator_loss=27.71, generator_mel_loss=18.3, generator_kl_loss=1.216, generator_dur_loss=1.806, generator_adv_loss=1.855, generator_feat_match_loss=4.537, over 100.00 samples.
2024-03-14 11:49:11,010 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 11:51:11,240 INFO [train.py:919] (2/6) Start epoch 582
2024-03-14 11:51:50,769 INFO [train.py:527] (2/6) Epoch 582, batch 6, global_batch_idx: 72050, batch size: 62, loss[discriminator_loss=2.679, discriminator_real_loss=1.306, discriminator_fake_loss=1.372, generator_loss=28.55, generator_mel_loss=18.3, generator_kl_loss=1.445, generator_dur_loss=1.74, generator_adv_loss=1.94, generator_feat_match_loss=5.128, over 62.00 samples.], tot_loss[discriminator_loss=2.69, discriminator_real_loss=1.341, discriminator_fake_loss=1.349, generator_loss=28.46, generator_mel_loss=18.05, generator_kl_loss=1.47, generator_dur_loss=1.739, generator_adv_loss=1.936, generator_feat_match_loss=5.263, over 407.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 11:54:09,063 INFO [train.py:527] (2/6) Epoch 582, batch 56, global_batch_idx: 72100, batch size: 61, loss[discriminator_loss=2.711, discriminator_real_loss=1.453, discriminator_fake_loss=1.257, generator_loss=27.45, generator_mel_loss=17.92, generator_kl_loss=1.259, generator_dur_loss=1.777, generator_adv_loss=1.848, generator_feat_match_loss=4.643, over 61.00 samples.], tot_loss[discriminator_loss=2.698, discriminator_real_loss=1.361, discriminator_fake_loss=1.337, generator_loss=28.5, generator_mel_loss=18.08, generator_kl_loss=1.426, generator_dur_loss=1.755, generator_adv_loss=1.963, generator_feat_match_loss=5.279, over 3183.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 11:56:29,814 INFO [train.py:527] (2/6) Epoch 582, batch 106, global_batch_idx: 72150, batch size: 15, loss[discriminator_loss=2.716, discriminator_real_loss=1.393, discriminator_fake_loss=1.323, generator_loss=27.73, generator_mel_loss=17.75, generator_kl_loss=1.563, generator_dur_loss=1.609, generator_adv_loss=1.709, generator_feat_match_loss=5.096, over 15.00 samples.], tot_loss[discriminator_loss=2.697, discriminator_real_loss=1.361, discriminator_fake_loss=1.336, generator_loss=28.52, generator_mel_loss=18.04, generator_kl_loss=1.412, generator_dur_loss=1.756, generator_adv_loss=1.967, generator_feat_match_loss=5.337, over 6133.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 11:57:17,813 INFO [train.py:919] (2/6) Start epoch 583
2024-03-14 11:59:10,469 INFO [train.py:527] (2/6) Epoch 583, batch 32, global_batch_idx: 72200, batch size: 77, loss[discriminator_loss=2.709, discriminator_real_loss=1.291, discriminator_fake_loss=1.418, generator_loss=28.48, generator_mel_loss=18.05, generator_kl_loss=1.402, generator_dur_loss=1.814, generator_adv_loss=1.94, generator_feat_match_loss=5.275, over 77.00 samples.], tot_loss[discriminator_loss=2.682, discriminator_real_loss=1.365, discriminator_fake_loss=1.317, generator_loss=28.54, generator_mel_loss=18, generator_kl_loss=1.416, generator_dur_loss=1.754, generator_adv_loss=1.999, generator_feat_match_loss=5.372, over 2005.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 11:59:10,470 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 11:59:18,464 INFO [train.py:591] (2/6) Epoch 583, validation: discriminator_loss=2.773, discriminator_real_loss=1.405, discriminator_fake_loss=1.368, generator_loss=27.33, generator_mel_loss=18.31, generator_kl_loss=1.174, generator_dur_loss=1.809, generator_adv_loss=1.85, generator_feat_match_loss=4.194, over 100.00 samples.
2024-03-14 11:59:18,464 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 12:01:36,786 INFO [train.py:527] (2/6) Epoch 583, batch 82, global_batch_idx: 72250, batch size: 58, loss[discriminator_loss=2.728, discriminator_real_loss=1.345, discriminator_fake_loss=1.384, generator_loss=28.95, generator_mel_loss=18.35, generator_kl_loss=1.463, generator_dur_loss=1.687, generator_adv_loss=2.022, generator_feat_match_loss=5.429, over 58.00 samples.], tot_loss[discriminator_loss=2.694, discriminator_real_loss=1.365, discriminator_fake_loss=1.329, generator_loss=28.5, generator_mel_loss=18.02, generator_kl_loss=1.406, generator_dur_loss=1.756, generator_adv_loss=1.979, generator_feat_match_loss=5.334, over 4933.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 12:03:31,017 INFO [train.py:919] (2/6) Start epoch 584
2024-03-14 12:04:18,530 INFO [train.py:527] (2/6) Epoch 584, batch 8, global_batch_idx: 72300, batch size: 70, loss[discriminator_loss=2.711, discriminator_real_loss=1.323, discriminator_fake_loss=1.388, generator_loss=28.42, generator_mel_loss=17.82, generator_kl_loss=1.329, generator_dur_loss=1.796, generator_adv_loss=2.05, generator_feat_match_loss=5.429, over 70.00 samples.], tot_loss[discriminator_loss=2.665, discriminator_real_loss=1.343, discriminator_fake_loss=1.322, generator_loss=29.05, generator_mel_loss=18.12, generator_kl_loss=1.441, generator_dur_loss=1.76, generator_adv_loss=2.013, generator_feat_match_loss=5.719, over 557.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 12:06:33,535 INFO [train.py:527] (2/6) Epoch 584, batch 58, global_batch_idx: 72350, batch size: 88, loss[discriminator_loss=2.707, discriminator_real_loss=1.374, discriminator_fake_loss=1.333, generator_loss=27.97, generator_mel_loss=17.74, generator_kl_loss=1.357, generator_dur_loss=1.885, generator_adv_loss=1.897, generator_feat_match_loss=5.094, over 88.00 samples.], tot_loss[discriminator_loss=2.696, discriminator_real_loss=1.357, discriminator_fake_loss=1.339, generator_loss=28.56, generator_mel_loss=17.97, generator_kl_loss=1.418, generator_dur_loss=1.755, generator_adv_loss=1.974, generator_feat_match_loss=5.44, over 3553.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 12:08:53,081 INFO [train.py:527] (2/6) Epoch 584, batch 108, global_batch_idx: 72400, batch size: 55, loss[discriminator_loss=2.763, discriminator_real_loss=1.37, discriminator_fake_loss=1.392, generator_loss=27.02, generator_mel_loss=17.67, generator_kl_loss=1.423, generator_dur_loss=1.711, generator_adv_loss=1.968, generator_feat_match_loss=4.251, over 55.00 samples.], tot_loss[discriminator_loss=2.707, discriminator_real_loss=1.367, discriminator_fake_loss=1.34, generator_loss=28.57, generator_mel_loss=18.03, generator_kl_loss=1.416, generator_dur_loss=1.753, generator_adv_loss=1.979, generator_feat_match_loss=5.39, over 6495.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 12:08:53,082 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 12:09:02,014 INFO [train.py:591] (2/6) Epoch 584, validation: discriminator_loss=2.738, discriminator_real_loss=1.487, discriminator_fake_loss=1.251, generator_loss=27.72, generator_mel_loss=18.38, generator_kl_loss=1.309, generator_dur_loss=1.808, generator_adv_loss=1.99, generator_feat_match_loss=4.232, over 100.00 samples.
2024-03-14 12:09:02,015 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 12:09:45,729 INFO [train.py:919] (2/6) Start epoch 585
2024-03-14 12:11:44,715 INFO [train.py:527] (2/6) Epoch 585, batch 34, global_batch_idx: 72450, batch size: 42, loss[discriminator_loss=2.794, discriminator_real_loss=1.455, discriminator_fake_loss=1.339, generator_loss=27.89, generator_mel_loss=18.19, generator_kl_loss=1.376, generator_dur_loss=1.735, generator_adv_loss=2.017, generator_feat_match_loss=4.568, over 42.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.382, discriminator_fake_loss=1.334, generator_loss=28.48, generator_mel_loss=18.08, generator_kl_loss=1.408, generator_dur_loss=1.708, generator_adv_loss=1.981, generator_feat_match_loss=5.302, over 1732.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 12:14:02,754 INFO [train.py:527] (2/6) Epoch 585, batch 84, global_batch_idx: 72500, batch size: 62, loss[discriminator_loss=2.693, discriminator_real_loss=1.37, discriminator_fake_loss=1.323, generator_loss=27.85, generator_mel_loss=17.96, generator_kl_loss=1.327, generator_dur_loss=1.743, generator_adv_loss=1.907, generator_feat_match_loss=4.914, over 62.00 samples.], tot_loss[discriminator_loss=2.708, discriminator_real_loss=1.37, discriminator_fake_loss=1.338, generator_loss=28.51, generator_mel_loss=18.05, generator_kl_loss=1.409, generator_dur_loss=1.733, generator_adv_loss=1.983, generator_feat_match_loss=5.331, over 4553.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 12:15:54,449 INFO [train.py:919] (2/6) Start epoch 586
2024-03-14 12:16:44,957 INFO [train.py:527] (2/6) Epoch 586, batch 10, global_batch_idx: 72550, batch size: 68, loss[discriminator_loss=2.608, discriminator_real_loss=1.281, discriminator_fake_loss=1.327, generator_loss=29.38, generator_mel_loss=18.03, generator_kl_loss=1.342, generator_dur_loss=1.766, generator_adv_loss=2.14, generator_feat_match_loss=6.102, over 68.00 samples.], tot_loss[discriminator_loss=2.7, discriminator_real_loss=1.358, discriminator_fake_loss=1.342, generator_loss=28.38, generator_mel_loss=18.02, generator_kl_loss=1.431, generator_dur_loss=1.697, generator_adv_loss=1.968, generator_feat_match_loss=5.27, over 556.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 12:19:05,861 INFO [train.py:527] (2/6) Epoch 586, batch 60, global_batch_idx: 72600, batch size: 48, loss[discriminator_loss=2.693, discriminator_real_loss=1.388, discriminator_fake_loss=1.305, generator_loss=29.13, generator_mel_loss=18.06, generator_kl_loss=1.493, generator_dur_loss=1.653, generator_adv_loss=1.987, generator_feat_match_loss=5.932, over 48.00 samples.], tot_loss[discriminator_loss=2.708, discriminator_real_loss=1.362, discriminator_fake_loss=1.346, generator_loss=28.43, generator_mel_loss=17.99, generator_kl_loss=1.42, generator_dur_loss=1.741, generator_adv_loss=1.965, generator_feat_match_loss=5.321, over 3484.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 12:19:05,863 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 12:19:13,988 INFO [train.py:591] (2/6) Epoch 586, validation: discriminator_loss=2.753, discriminator_real_loss=1.447, discriminator_fake_loss=1.306, generator_loss=27.23, generator_mel_loss=18.08, generator_kl_loss=1.24, generator_dur_loss=1.796, generator_adv_loss=1.931, generator_feat_match_loss=4.183, over 100.00 samples.
2024-03-14 12:19:13,989 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 12:21:36,636 INFO [train.py:527] (2/6) Epoch 586, batch 110, global_batch_idx: 72650, batch size: 96, loss[discriminator_loss=2.713, discriminator_real_loss=1.375, discriminator_fake_loss=1.338, generator_loss=28.26, generator_mel_loss=17.95, generator_kl_loss=1.368, generator_dur_loss=1.906, generator_adv_loss=1.945, generator_feat_match_loss=5.092, over 96.00 samples.], tot_loss[discriminator_loss=2.707, discriminator_real_loss=1.366, discriminator_fake_loss=1.341, generator_loss=28.37, generator_mel_loss=17.97, generator_kl_loss=1.396, generator_dur_loss=1.76, generator_adv_loss=1.958, generator_feat_match_loss=5.285, over 6698.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 12:22:13,374 INFO [train.py:919] (2/6) Start epoch 587
2024-03-14 12:24:15,715 INFO [train.py:527] (2/6) Epoch 587, batch 36, global_batch_idx: 72700, batch size: 25, loss[discriminator_loss=2.764, discriminator_real_loss=1.446, discriminator_fake_loss=1.318, generator_loss=28.05, generator_mel_loss=18.17, generator_kl_loss=1.423, generator_dur_loss=1.615, generator_adv_loss=1.816, generator_feat_match_loss=5.025, over 25.00 samples.], tot_loss[discriminator_loss=2.71, discriminator_real_loss=1.364, discriminator_fake_loss=1.346, generator_loss=28.44, generator_mel_loss=18.06, generator_kl_loss=1.403, generator_dur_loss=1.741, generator_adv_loss=1.954, generator_feat_match_loss=5.288, over 1997.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 12:26:32,087 INFO [train.py:527] (2/6) Epoch 587, batch 86, global_batch_idx: 72750, batch size: 70, loss[discriminator_loss=2.7, discriminator_real_loss=1.431, discriminator_fake_loss=1.27, generator_loss=27.42, generator_mel_loss=17.72, generator_kl_loss=1.296, generator_dur_loss=1.793, generator_adv_loss=1.912, generator_feat_match_loss=4.7, over 70.00 samples.], tot_loss[discriminator_loss=2.703, discriminator_real_loss=1.367, discriminator_fake_loss=1.336, generator_loss=28.51, generator_mel_loss=18.07, generator_kl_loss=1.426, generator_dur_loss=1.736, generator_adv_loss=1.963, generator_feat_match_loss=5.312, over 4634.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 12:28:18,675 INFO [train.py:919] (2/6) Start epoch 588
2024-03-14 12:29:14,981 INFO [train.py:527] (2/6) Epoch 588, batch 12, global_batch_idx: 72800, batch size: 44, loss[discriminator_loss=2.685, discriminator_real_loss=1.362, discriminator_fake_loss=1.323, generator_loss=28.46, generator_mel_loss=17.48, generator_kl_loss=1.6, generator_dur_loss=1.685, generator_adv_loss=1.97, generator_feat_match_loss=5.724, over 44.00 samples.], tot_loss[discriminator_loss=2.694, discriminator_real_loss=1.354, discriminator_fake_loss=1.339, generator_loss=28.55, generator_mel_loss=17.87, generator_kl_loss=1.456, generator_dur_loss=1.743, generator_adv_loss=1.955, generator_feat_match_loss=5.527, over 764.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 12:29:14,984 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 12:29:22,919 INFO [train.py:591] (2/6) Epoch 588, validation: discriminator_loss=2.725, discriminator_real_loss=1.376, discriminator_fake_loss=1.349, generator_loss=27.57, generator_mel_loss=18.14, generator_kl_loss=1.264, generator_dur_loss=1.813, generator_adv_loss=1.845, generator_feat_match_loss=4.51, over 100.00 samples.
2024-03-14 12:29:22,920 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 12:31:42,095 INFO [train.py:527] (2/6) Epoch 588, batch 62, global_batch_idx: 72850, batch size: 58, loss[discriminator_loss=2.683, discriminator_real_loss=1.356, discriminator_fake_loss=1.326, generator_loss=27.91, generator_mel_loss=17.61, generator_kl_loss=1.363, generator_dur_loss=1.72, generator_adv_loss=1.887, generator_feat_match_loss=5.331, over 58.00 samples.], tot_loss[discriminator_loss=2.699, discriminator_real_loss=1.36, discriminator_fake_loss=1.339, generator_loss=28.57, generator_mel_loss=17.97, generator_kl_loss=1.422, generator_dur_loss=1.748, generator_adv_loss=1.961, generator_feat_match_loss=5.46, over 3707.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 12:34:01,576 INFO [train.py:527] (2/6) Epoch 588, batch 112, global_batch_idx: 72900, batch size: 74, loss[discriminator_loss=2.73, discriminator_real_loss=1.369, discriminator_fake_loss=1.361, generator_loss=27.99, generator_mel_loss=18.16, generator_kl_loss=1.195, generator_dur_loss=1.819, generator_adv_loss=2.049, generator_feat_match_loss=4.763, over 74.00 samples.], tot_loss[discriminator_loss=2.698, discriminator_real_loss=1.364, discriminator_fake_loss=1.334, generator_loss=28.58, generator_mel_loss=18.02, generator_kl_loss=1.429, generator_dur_loss=1.743, generator_adv_loss=1.978, generator_feat_match_loss=5.41, over 6396.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 12:34:33,236 INFO [train.py:919] (2/6) Start epoch 589
2024-03-14 12:36:39,677 INFO [train.py:527] (2/6) Epoch 589, batch 38, global_batch_idx: 72950, batch size: 59, loss[discriminator_loss=2.719, discriminator_real_loss=1.289, discriminator_fake_loss=1.43, generator_loss=28.87, generator_mel_loss=18.25, generator_kl_loss=1.347, generator_dur_loss=1.733, generator_adv_loss=1.903, generator_feat_match_loss=5.645, over 59.00 samples.], tot_loss[discriminator_loss=2.71, discriminator_real_loss=1.37, discriminator_fake_loss=1.339, generator_loss=28.51, generator_mel_loss=18, generator_kl_loss=1.433, generator_dur_loss=1.729, generator_adv_loss=1.98, generator_feat_match_loss=5.372, over 2113.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 12:38:59,569 INFO [train.py:527] (2/6) Epoch 589, batch 88, global_batch_idx: 73000, batch size: 70, loss[discriminator_loss=2.749, discriminator_real_loss=1.396, discriminator_fake_loss=1.352, generator_loss=27.93, generator_mel_loss=18.19, generator_kl_loss=1.181, generator_dur_loss=1.839, generator_adv_loss=1.883, generator_feat_match_loss=4.837, over 70.00 samples.], tot_loss[discriminator_loss=2.717, discriminator_real_loss=1.376, discriminator_fake_loss=1.341, generator_loss=28.41, generator_mel_loss=17.98, generator_kl_loss=1.406, generator_dur_loss=1.738, generator_adv_loss=1.977, generator_feat_match_loss=5.311, over 5016.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 12:38:59,571 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 12:39:08,253 INFO [train.py:591] (2/6) Epoch 589, validation: discriminator_loss=2.756, discriminator_real_loss=1.378, discriminator_fake_loss=1.378, generator_loss=27.21, generator_mel_loss=18.36, generator_kl_loss=1.156, generator_dur_loss=1.813, generator_adv_loss=1.789, generator_feat_match_loss=4.092, over 100.00 samples.
2024-03-14 12:39:08,254 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 12:40:45,783 INFO [train.py:919] (2/6) Start epoch 590
2024-03-14 12:41:47,472 INFO [train.py:527] (2/6) Epoch 590, batch 14, global_batch_idx: 73050, batch size: 45, loss[discriminator_loss=2.691, discriminator_real_loss=1.353, discriminator_fake_loss=1.338, generator_loss=28.31, generator_mel_loss=18.15, generator_kl_loss=1.499, generator_dur_loss=1.672, generator_adv_loss=2.009, generator_feat_match_loss=4.984, over 45.00 samples.], tot_loss[discriminator_loss=2.713, discriminator_real_loss=1.388, discriminator_fake_loss=1.325, generator_loss=28.45, generator_mel_loss=18.01, generator_kl_loss=1.429, generator_dur_loss=1.765, generator_adv_loss=1.966, generator_feat_match_loss=5.283, over 859.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 12:44:08,839 INFO [train.py:527] (2/6) Epoch 590, batch 64, global_batch_idx: 73100, batch size: 44, loss[discriminator_loss=2.65, discriminator_real_loss=1.286, discriminator_fake_loss=1.363, generator_loss=29.29, generator_mel_loss=17.92, generator_kl_loss=1.581, generator_dur_loss=1.704, generator_adv_loss=2.177, generator_feat_match_loss=5.905, over 44.00 samples.], tot_loss[discriminator_loss=2.701, discriminator_real_loss=1.368, discriminator_fake_loss=1.333, generator_loss=28.52, generator_mel_loss=18.03, generator_kl_loss=1.411, generator_dur_loss=1.753, generator_adv_loss=1.973, generator_feat_match_loss=5.352, over 3640.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 12:46:26,633 INFO [train.py:527] (2/6) Epoch 590, batch 114, global_batch_idx: 73150, batch size: 61, loss[discriminator_loss=2.682, discriminator_real_loss=1.402, discriminator_fake_loss=1.28, generator_loss=28.26, generator_mel_loss=17.58, generator_kl_loss=1.503, generator_dur_loss=1.77, generator_adv_loss=2.068, generator_feat_match_loss=5.335, over 61.00 samples.], tot_loss[discriminator_loss=2.707, discriminator_real_loss=1.37, discriminator_fake_loss=1.337, generator_loss=28.5, generator_mel_loss=18.02, generator_kl_loss=1.408, generator_dur_loss=1.753, generator_adv_loss=1.989, generator_feat_match_loss=5.33, over 6529.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 12:46:53,449 INFO [train.py:919] (2/6) Start epoch 591
2024-03-14 12:49:10,759 INFO [train.py:527] (2/6) Epoch 591, batch 40, global_batch_idx: 73200, batch size: 96, loss[discriminator_loss=2.677, discriminator_real_loss=1.383, discriminator_fake_loss=1.294, generator_loss=27.95, generator_mel_loss=17.81, generator_kl_loss=1.324, generator_dur_loss=1.894, generator_adv_loss=1.887, generator_feat_match_loss=5.037, over 96.00 samples.], tot_loss[discriminator_loss=2.697, discriminator_real_loss=1.37, discriminator_fake_loss=1.327, generator_loss=28.63, generator_mel_loss=18.05, generator_kl_loss=1.397, generator_dur_loss=1.768, generator_adv_loss=1.97, generator_feat_match_loss=5.444, over 2416.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 12:49:10,761 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 12:49:18,755 INFO [train.py:591] (2/6) Epoch 591, validation: discriminator_loss=2.735, discriminator_real_loss=1.399, discriminator_fake_loss=1.336, generator_loss=27.3, generator_mel_loss=18.09, generator_kl_loss=1.265, generator_dur_loss=1.809, generator_adv_loss=1.869, generator_feat_match_loss=4.263, over 100.00 samples.
2024-03-14 12:49:18,756 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 12:51:37,330 INFO [train.py:527] (2/6) Epoch 591, batch 90, global_batch_idx: 73250, batch size: 52, loss[discriminator_loss=2.743, discriminator_real_loss=1.255, discriminator_fake_loss=1.489, generator_loss=28.32, generator_mel_loss=18.32, generator_kl_loss=1.546, generator_dur_loss=1.74, generator_adv_loss=1.892, generator_feat_match_loss=4.825, over 52.00 samples.], tot_loss[discriminator_loss=2.707, discriminator_real_loss=1.368, discriminator_fake_loss=1.339, generator_loss=28.6, generator_mel_loss=18.04, generator_kl_loss=1.418, generator_dur_loss=1.762, generator_adv_loss=1.967, generator_feat_match_loss=5.413, over 5292.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 12:53:08,850 INFO [train.py:919] (2/6) Start epoch 592
2024-03-14 12:54:18,443 INFO [train.py:527] (2/6) Epoch 592, batch 16, global_batch_idx: 73300, batch size: 39, loss[discriminator_loss=2.666, discriminator_real_loss=1.352, discriminator_fake_loss=1.313, generator_loss=29.51, generator_mel_loss=18.08, generator_kl_loss=1.674, generator_dur_loss=1.703, generator_adv_loss=2.107, generator_feat_match_loss=5.94, over 39.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.371, discriminator_fake_loss=1.314, generator_loss=28.46, generator_mel_loss=18.02, generator_kl_loss=1.387, generator_dur_loss=1.778, generator_adv_loss=1.953, generator_feat_match_loss=5.317, over 1022.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 12:56:37,664 INFO [train.py:527] (2/6) Epoch 592, batch 66, global_batch_idx: 73350, batch size: 42, loss[discriminator_loss=2.734, discriminator_real_loss=1.368, discriminator_fake_loss=1.366, generator_loss=26.94, generator_mel_loss=17.74, generator_kl_loss=1.492, generator_dur_loss=1.702, generator_adv_loss=1.885, generator_feat_match_loss=4.121, over 42.00 samples.], tot_loss[discriminator_loss=2.698, discriminator_real_loss=1.363, discriminator_fake_loss=1.334, generator_loss=28.52, generator_mel_loss=18.03, generator_kl_loss=1.435, generator_dur_loss=1.757, generator_adv_loss=1.949, generator_feat_match_loss=5.354, over 3553.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 12:58:58,798 INFO [train.py:527] (2/6) Epoch 592, batch 116, global_batch_idx: 73400, batch size: 59, loss[discriminator_loss=2.729, discriminator_real_loss=1.262, discriminator_fake_loss=1.466, generator_loss=28.36, generator_mel_loss=17.94, generator_kl_loss=1.457, generator_dur_loss=1.763, generator_adv_loss=2.025, generator_feat_match_loss=5.178, over 59.00 samples.], tot_loss[discriminator_loss=2.702, discriminator_real_loss=1.366, discriminator_fake_loss=1.336, generator_loss=28.53, generator_mel_loss=18.03, generator_kl_loss=1.424, generator_dur_loss=1.764, generator_adv_loss=1.956, generator_feat_match_loss=5.357, over 6640.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 12:58:58,799 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 12:59:07,931 INFO [train.py:591] (2/6) Epoch 592, validation: discriminator_loss=2.751, discriminator_real_loss=1.511, discriminator_fake_loss=1.239, generator_loss=27.84, generator_mel_loss=18.23, generator_kl_loss=1.2, generator_dur_loss=1.824, generator_adv_loss=2.03, generator_feat_match_loss=4.553, over 100.00 samples.
2024-03-14 12:59:07,932 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 12:59:29,385 INFO [train.py:919] (2/6) Start epoch 593
2024-03-14 13:01:48,772 INFO [train.py:527] (2/6) Epoch 593, batch 42, global_batch_idx: 73450, batch size: 83, loss[discriminator_loss=2.692, discriminator_real_loss=1.382, discriminator_fake_loss=1.31, generator_loss=28.11, generator_mel_loss=17.64, generator_kl_loss=1.243, generator_dur_loss=1.846, generator_adv_loss=1.983, generator_feat_match_loss=5.404, over 83.00 samples.], tot_loss[discriminator_loss=2.699, discriminator_real_loss=1.358, discriminator_fake_loss=1.341, generator_loss=28.51, generator_mel_loss=18.06, generator_kl_loss=1.427, generator_dur_loss=1.757, generator_adv_loss=1.968, generator_feat_match_loss=5.298, over 2317.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 13:04:07,607 INFO [train.py:527] (2/6) Epoch 593, batch 92, global_batch_idx: 73500, batch size: 60, loss[discriminator_loss=2.691, discriminator_real_loss=1.442, discriminator_fake_loss=1.249, generator_loss=27.59, generator_mel_loss=17.87, generator_kl_loss=1.262, generator_dur_loss=1.736, generator_adv_loss=1.955, generator_feat_match_loss=4.766, over 60.00 samples.], tot_loss[discriminator_loss=2.694, discriminator_real_loss=1.36, discriminator_fake_loss=1.334, generator_loss=28.53, generator_mel_loss=18.05, generator_kl_loss=1.415, generator_dur_loss=1.747, generator_adv_loss=1.972, generator_feat_match_loss=5.347, over 4995.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 13:05:34,411 INFO [train.py:919] (2/6) Start epoch 594
2024-03-14 13:06:50,818 INFO [train.py:527] (2/6) Epoch 594, batch 18, global_batch_idx: 73550, batch size: 53, loss[discriminator_loss=2.744, discriminator_real_loss=1.375, discriminator_fake_loss=1.369, generator_loss=27.7, generator_mel_loss=17.72, generator_kl_loss=1.434, generator_dur_loss=1.735, generator_adv_loss=2.029, generator_feat_match_loss=4.775, over 53.00 samples.], tot_loss[discriminator_loss=2.674, discriminator_real_loss=1.338, discriminator_fake_loss=1.336, generator_loss=28.77, generator_mel_loss=18.09, generator_kl_loss=1.372, generator_dur_loss=1.776, generator_adv_loss=1.978, generator_feat_match_loss=5.558, over 1173.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 13:09:08,320 INFO [train.py:527] (2/6) Epoch 594, batch 68, global_batch_idx: 73600, batch size: 52, loss[discriminator_loss=2.697, discriminator_real_loss=1.409, discriminator_fake_loss=1.288, generator_loss=28.49, generator_mel_loss=17.83, generator_kl_loss=1.346, generator_dur_loss=1.703, generator_adv_loss=2.002, generator_feat_match_loss=5.606, over 52.00 samples.], tot_loss[discriminator_loss=2.696, discriminator_real_loss=1.362, discriminator_fake_loss=1.334, generator_loss=28.46, generator_mel_loss=18, generator_kl_loss=1.399, generator_dur_loss=1.764, generator_adv_loss=1.964, generator_feat_match_loss=5.33, over 4049.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 13:09:08,322 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 13:09:17,139 INFO [train.py:591] (2/6) Epoch 594, validation: discriminator_loss=2.726, discriminator_real_loss=1.396, discriminator_fake_loss=1.33, generator_loss=27.5, generator_mel_loss=18.34, generator_kl_loss=1.188, generator_dur_loss=1.814, generator_adv_loss=1.887, generator_feat_match_loss=4.266, over 100.00 samples.
2024-03-14 13:09:17,141 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 13:11:35,016 INFO [train.py:527] (2/6) Epoch 594, batch 118, global_batch_idx: 73650, batch size: 47, loss[discriminator_loss=2.69, discriminator_real_loss=1.351, discriminator_fake_loss=1.339, generator_loss=27.77, generator_mel_loss=17.49, generator_kl_loss=1.494, generator_dur_loss=1.715, generator_adv_loss=2.007, generator_feat_match_loss=5.055, over 47.00 samples.], tot_loss[discriminator_loss=2.696, discriminator_real_loss=1.361, discriminator_fake_loss=1.335, generator_loss=28.45, generator_mel_loss=17.99, generator_kl_loss=1.387, generator_dur_loss=1.769, generator_adv_loss=1.967, generator_feat_match_loss=5.335, over 7177.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 13:11:50,115 INFO [train.py:919] (2/6) Start epoch 595
2024-03-14 13:14:15,295 INFO [train.py:527] (2/6) Epoch 595, batch 44, global_batch_idx: 73700, batch size: 59, loss[discriminator_loss=2.664, discriminator_real_loss=1.428, discriminator_fake_loss=1.236, generator_loss=28.69, generator_mel_loss=17.96, generator_kl_loss=1.425, generator_dur_loss=1.703, generator_adv_loss=1.927, generator_feat_match_loss=5.681, over 59.00 samples.], tot_loss[discriminator_loss=2.701, discriminator_real_loss=1.366, discriminator_fake_loss=1.335, generator_loss=28.44, generator_mel_loss=17.97, generator_kl_loss=1.428, generator_dur_loss=1.747, generator_adv_loss=1.967, generator_feat_match_loss=5.325, over 2568.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 13:16:36,062 INFO [train.py:527] (2/6) Epoch 595, batch 94, global_batch_idx: 73750, batch size: 15, loss[discriminator_loss=2.63, discriminator_real_loss=1.315, discriminator_fake_loss=1.316, generator_loss=28.7, generator_mel_loss=17.95, generator_kl_loss=1.936, generator_dur_loss=1.598, generator_adv_loss=2.043, generator_feat_match_loss=5.168, over 15.00 samples.], tot_loss[discriminator_loss=2.703, discriminator_real_loss=1.365, discriminator_fake_loss=1.338, generator_loss=28.54, generator_mel_loss=18.03, generator_kl_loss=1.435, generator_dur_loss=1.751, generator_adv_loss=1.968, generator_feat_match_loss=5.355, over 5429.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 13:17:55,669 INFO [train.py:919] (2/6) Start epoch 596
2024-03-14 13:19:12,867 INFO [train.py:527] (2/6) Epoch 596, batch 20, global_batch_idx: 73800, batch size: 64, loss[discriminator_loss=2.723, discriminator_real_loss=1.399, discriminator_fake_loss=1.325, generator_loss=28.58, generator_mel_loss=17.91, generator_kl_loss=1.246, generator_dur_loss=1.808, generator_adv_loss=1.884, generator_feat_match_loss=5.731, over 64.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.382, discriminator_fake_loss=1.335, generator_loss=28.52, generator_mel_loss=18.05, generator_kl_loss=1.406, generator_dur_loss=1.754, generator_adv_loss=1.973, generator_feat_match_loss=5.335, over 1144.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 13:19:12,868 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 13:19:20,981 INFO [train.py:591] (2/6) Epoch 596, validation: discriminator_loss=2.747, discriminator_real_loss=1.402, discriminator_fake_loss=1.344, generator_loss=27.21, generator_mel_loss=18.33, generator_kl_loss=1.287, generator_dur_loss=1.792, generator_adv_loss=1.801, generator_feat_match_loss=4.006, over 100.00 samples.
2024-03-14 13:19:20,982 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 13:21:39,520 INFO [train.py:527] (2/6) Epoch 596, batch 70, global_batch_idx: 73850, batch size: 62, loss[discriminator_loss=2.742, discriminator_real_loss=1.437, discriminator_fake_loss=1.305, generator_loss=27.3, generator_mel_loss=17.52, generator_kl_loss=1.551, generator_dur_loss=1.686, generator_adv_loss=1.988, generator_feat_match_loss=4.563, over 62.00 samples.], tot_loss[discriminator_loss=2.707, discriminator_real_loss=1.37, discriminator_fake_loss=1.338, generator_loss=28.54, generator_mel_loss=18.06, generator_kl_loss=1.411, generator_dur_loss=1.753, generator_adv_loss=1.978, generator_feat_match_loss=5.33, over 4085.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 13:23:57,247 INFO [train.py:527] (2/6) Epoch 596, batch 120, global_batch_idx: 73900, batch size: 66, loss[discriminator_loss=2.702, discriminator_real_loss=1.328, discriminator_fake_loss=1.374, generator_loss=27.83, generator_mel_loss=17.83, generator_kl_loss=1.236, generator_dur_loss=1.799, generator_adv_loss=1.91, generator_feat_match_loss=5.052, over 66.00 samples.], tot_loss[discriminator_loss=2.707, discriminator_real_loss=1.368, discriminator_fake_loss=1.339, generator_loss=28.5, generator_mel_loss=18.03, generator_kl_loss=1.416, generator_dur_loss=1.751, generator_adv_loss=1.978, generator_feat_match_loss=5.322, over 7002.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 13:24:08,671 INFO [train.py:919] (2/6) Start epoch 597
2024-03-14 13:26:40,741 INFO [train.py:527] (2/6) Epoch 597, batch 46, global_batch_idx: 73950, batch size: 39, loss[discriminator_loss=2.7, discriminator_real_loss=1.356, discriminator_fake_loss=1.343, generator_loss=27.82, generator_mel_loss=18.02, generator_kl_loss=1.454, generator_dur_loss=1.7, generator_adv_loss=1.996, generator_feat_match_loss=4.656, over 39.00 samples.], tot_loss[discriminator_loss=2.707, discriminator_real_loss=1.374, discriminator_fake_loss=1.334, generator_loss=28.51, generator_mel_loss=18.02, generator_kl_loss=1.431, generator_dur_loss=1.742, generator_adv_loss=1.973, generator_feat_match_loss=5.338, over 2624.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 13:29:01,380 INFO [train.py:527] (2/6) Epoch 597, batch 96, global_batch_idx: 74000, batch size: 74, loss[discriminator_loss=2.705, discriminator_real_loss=1.314, discriminator_fake_loss=1.391, generator_loss=27.73, generator_mel_loss=17.82, generator_kl_loss=1.407, generator_dur_loss=1.802, generator_adv_loss=2.002, generator_feat_match_loss=4.696, over 74.00 samples.], tot_loss[discriminator_loss=2.713, discriminator_real_loss=1.373, discriminator_fake_loss=1.34, generator_loss=28.5, generator_mel_loss=18.07, generator_kl_loss=1.424, generator_dur_loss=1.752, generator_adv_loss=1.96, generator_feat_match_loss=5.297, over 5529.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 13:29:01,382 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 13:29:10,117 INFO [train.py:591] (2/6) Epoch 597, validation: discriminator_loss=2.738, discriminator_real_loss=1.466, discriminator_fake_loss=1.271, generator_loss=27, generator_mel_loss=18.13, generator_kl_loss=1.24, generator_dur_loss=1.825, generator_adv_loss=1.864, generator_feat_match_loss=3.936, over 100.00 samples.
2024-03-14 13:29:10,118 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 13:30:22,438 INFO [train.py:919] (2/6) Start epoch 598
2024-03-14 13:31:45,912 INFO [train.py:527] (2/6) Epoch 598, batch 22, global_batch_idx: 74050, batch size: 39, loss[discriminator_loss=2.65, discriminator_real_loss=1.367, discriminator_fake_loss=1.283, generator_loss=28.25, generator_mel_loss=17.76, generator_kl_loss=1.527, generator_dur_loss=1.701, generator_adv_loss=2.006, generator_feat_match_loss=5.255, over 39.00 samples.], tot_loss[discriminator_loss=2.699, discriminator_real_loss=1.365, discriminator_fake_loss=1.334, generator_loss=28.64, generator_mel_loss=18.06, generator_kl_loss=1.436, generator_dur_loss=1.737, generator_adv_loss=1.96, generator_feat_match_loss=5.445, over 1208.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 13:34:05,461 INFO [train.py:527] (2/6) Epoch 598, batch 72, global_batch_idx: 74100, batch size: 68, loss[discriminator_loss=2.688, discriminator_real_loss=1.4, discriminator_fake_loss=1.288, generator_loss=28.43, generator_mel_loss=17.78, generator_kl_loss=1.367, generator_dur_loss=1.788, generator_adv_loss=1.938, generator_feat_match_loss=5.563, over 68.00 samples.], tot_loss[discriminator_loss=2.698, discriminator_real_loss=1.364, discriminator_fake_loss=1.334, generator_loss=28.59, generator_mel_loss=18.03, generator_kl_loss=1.405, generator_dur_loss=1.764, generator_adv_loss=1.967, generator_feat_match_loss=5.429, over 4198.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 13:36:21,496 INFO [train.py:527] (2/6) Epoch 598, batch 122, global_batch_idx: 74150, batch size: 25, loss[discriminator_loss=2.711, discriminator_real_loss=1.368, discriminator_fake_loss=1.343, generator_loss=29.09, generator_mel_loss=18.51, generator_kl_loss=1.576, generator_dur_loss=1.577, generator_adv_loss=1.969, generator_feat_match_loss=5.454, over 25.00 samples.], tot_loss[discriminator_loss=2.703, discriminator_real_loss=1.368, discriminator_fake_loss=1.335, generator_loss=28.59, generator_mel_loss=18.04, generator_kl_loss=1.403, generator_dur_loss=1.757, generator_adv_loss=1.966, generator_feat_match_loss=5.429, over 6901.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 13:36:26,883 INFO [train.py:919] (2/6) Start epoch 599
2024-03-14 13:39:04,744 INFO [train.py:527] (2/6) Epoch 599, batch 48, global_batch_idx: 74200, batch size: 45, loss[discriminator_loss=2.744, discriminator_real_loss=1.299, discriminator_fake_loss=1.444, generator_loss=28.73, generator_mel_loss=18.28, generator_kl_loss=1.544, generator_dur_loss=1.68, generator_adv_loss=1.998, generator_feat_match_loss=5.229, over 45.00 samples.], tot_loss[discriminator_loss=2.712, discriminator_real_loss=1.376, discriminator_fake_loss=1.336, generator_loss=28.52, generator_mel_loss=18.01, generator_kl_loss=1.411, generator_dur_loss=1.757, generator_adv_loss=1.965, generator_feat_match_loss=5.368, over 2864.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 13:39:04,746 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 13:39:12,921 INFO [train.py:591] (2/6) Epoch 599, validation: discriminator_loss=2.758, discriminator_real_loss=1.444, discriminator_fake_loss=1.314, generator_loss=26.97, generator_mel_loss=17.84, generator_kl_loss=1.218, generator_dur_loss=1.802, generator_adv_loss=1.894, generator_feat_match_loss=4.218, over 100.00 samples.
2024-03-14 13:39:12,922 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 13:41:35,653 INFO [train.py:527] (2/6) Epoch 599, batch 98, global_batch_idx: 74250, batch size: 45, loss[discriminator_loss=2.667, discriminator_real_loss=1.382, discriminator_fake_loss=1.286, generator_loss=29.16, generator_mel_loss=18.45, generator_kl_loss=1.794, generator_dur_loss=1.659, generator_adv_loss=1.928, generator_feat_match_loss=5.328, over 45.00 samples.], tot_loss[discriminator_loss=2.706, discriminator_real_loss=1.373, discriminator_fake_loss=1.333, generator_loss=28.54, generator_mel_loss=18.02, generator_kl_loss=1.416, generator_dur_loss=1.76, generator_adv_loss=1.968, generator_feat_match_loss=5.381, over 5849.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 13:42:43,101 INFO [train.py:919] (2/6) Start epoch 600
2024-03-14 13:44:13,861 INFO [train.py:527] (2/6) Epoch 600, batch 24, global_batch_idx: 74300, batch size: 50, loss[discriminator_loss=2.655, discriminator_real_loss=1.371, discriminator_fake_loss=1.285, generator_loss=28.84, generator_mel_loss=18.6, generator_kl_loss=1.385, generator_dur_loss=1.681, generator_adv_loss=1.98, generator_feat_match_loss=5.187, over 50.00 samples.], tot_loss[discriminator_loss=2.696, discriminator_real_loss=1.361, discriminator_fake_loss=1.336, generator_loss=28.63, generator_mel_loss=18.09, generator_kl_loss=1.448, generator_dur_loss=1.731, generator_adv_loss=1.965, generator_feat_match_loss=5.398, over 1374.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 13:46:29,163 INFO [train.py:527] (2/6) Epoch 600, batch 74, global_batch_idx: 74350, batch size: 53, loss[discriminator_loss=2.761, discriminator_real_loss=1.431, discriminator_fake_loss=1.33, generator_loss=29.51, generator_mel_loss=18.27, generator_kl_loss=1.494, generator_dur_loss=1.702, generator_adv_loss=2.06, generator_feat_match_loss=5.98, over 53.00 samples.], tot_loss[discriminator_loss=2.686, discriminator_real_loss=1.353, discriminator_fake_loss=1.333, generator_loss=28.76, generator_mel_loss=18.1, generator_kl_loss=1.425, generator_dur_loss=1.732, generator_adv_loss=2, generator_feat_match_loss=5.5, over 4076.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 13:48:48,459 INFO [train.py:919] (2/6) Start epoch 601
2024-03-14 13:49:13,042 INFO [train.py:527] (2/6) Epoch 601, batch 0, global_batch_idx: 74400, batch size: 25, loss[discriminator_loss=2.663, discriminator_real_loss=1.412, discriminator_fake_loss=1.25, generator_loss=29.47, generator_mel_loss=19.1, generator_kl_loss=1.81, generator_dur_loss=1.586, generator_adv_loss=2.002, generator_feat_match_loss=4.981, over 25.00 samples.], tot_loss[discriminator_loss=2.663, discriminator_real_loss=1.412, discriminator_fake_loss=1.25, generator_loss=29.47, generator_mel_loss=19.1, generator_kl_loss=1.81, generator_dur_loss=1.586, generator_adv_loss=2.002, generator_feat_match_loss=4.981, over 25.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 13:49:13,045 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 13:49:21,057 INFO [train.py:591] (2/6) Epoch 601, validation: discriminator_loss=2.735, discriminator_real_loss=1.363, discriminator_fake_loss=1.373, generator_loss=26.98, generator_mel_loss=18.09, generator_kl_loss=1.216, generator_dur_loss=1.794, generator_adv_loss=1.801, generator_feat_match_loss=4.075, over 100.00 samples.
2024-03-14 13:49:21,059 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 13:51:41,532 INFO [train.py:527] (2/6) Epoch 601, batch 50, global_batch_idx: 74450, batch size: 96, loss[discriminator_loss=2.72, discriminator_real_loss=1.354, discriminator_fake_loss=1.366, generator_loss=28.21, generator_mel_loss=17.89, generator_kl_loss=1.27, generator_dur_loss=1.878, generator_adv_loss=2.031, generator_feat_match_loss=5.145, over 96.00 samples.], tot_loss[discriminator_loss=2.708, discriminator_real_loss=1.367, discriminator_fake_loss=1.341, generator_loss=28.42, generator_mel_loss=17.94, generator_kl_loss=1.431, generator_dur_loss=1.754, generator_adv_loss=1.953, generator_feat_match_loss=5.347, over 2971.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 13:53:59,535 INFO [train.py:527] (2/6) Epoch 601, batch 100, global_batch_idx: 74500, batch size: 39, loss[discriminator_loss=2.723, discriminator_real_loss=1.287, discriminator_fake_loss=1.436, generator_loss=28.83, generator_mel_loss=18.7, generator_kl_loss=1.519, generator_dur_loss=1.662, generator_adv_loss=2.044, generator_feat_match_loss=4.911, over 39.00 samples.], tot_loss[discriminator_loss=2.707, discriminator_real_loss=1.368, discriminator_fake_loss=1.339, generator_loss=28.48, generator_mel_loss=17.99, generator_kl_loss=1.435, generator_dur_loss=1.75, generator_adv_loss=1.961, generator_feat_match_loss=5.35, over 5693.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 13:55:06,589 INFO [train.py:919] (2/6) Start epoch 602
2024-03-14 13:56:40,651 INFO [train.py:527] (2/6) Epoch 602, batch 26, global_batch_idx: 74550, batch size: 72, loss[discriminator_loss=2.701, discriminator_real_loss=1.31, discriminator_fake_loss=1.391, generator_loss=28.21, generator_mel_loss=17.58, generator_kl_loss=1.326, generator_dur_loss=1.802, generator_adv_loss=1.999, generator_feat_match_loss=5.505, over 72.00 samples.], tot_loss[discriminator_loss=2.703, discriminator_real_loss=1.371, discriminator_fake_loss=1.332, generator_loss=28.59, generator_mel_loss=17.99, generator_kl_loss=1.43, generator_dur_loss=1.762, generator_adv_loss=1.986, generator_feat_match_loss=5.432, over 1650.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 13:58:59,317 INFO [train.py:527] (2/6) Epoch 602, batch 76, global_batch_idx: 74600, batch size: 39, loss[discriminator_loss=2.763, discriminator_real_loss=1.574, discriminator_fake_loss=1.189, generator_loss=26.81, generator_mel_loss=18.05, generator_kl_loss=1.308, generator_dur_loss=1.68, generator_adv_loss=1.77, generator_feat_match_loss=4.004, over 39.00 samples.], tot_loss[discriminator_loss=2.71, discriminator_real_loss=1.373, discriminator_fake_loss=1.337, generator_loss=28.55, generator_mel_loss=18.02, generator_kl_loss=1.419, generator_dur_loss=1.753, generator_adv_loss=1.969, generator_feat_match_loss=5.396, over 4577.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 13:58:59,319 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 13:59:08,244 INFO [train.py:591] (2/6) Epoch 602, validation: discriminator_loss=2.754, discriminator_real_loss=1.314, discriminator_fake_loss=1.44, generator_loss=27.16, generator_mel_loss=18.23, generator_kl_loss=1.299, generator_dur_loss=1.809, generator_adv_loss=1.708, generator_feat_match_loss=4.116, over 100.00 samples.
2024-03-14 13:59:08,247 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 14:01:20,836 INFO [train.py:919] (2/6) Start epoch 603
2024-03-14 14:01:46,500 INFO [train.py:527] (2/6) Epoch 603, batch 2, global_batch_idx: 74650, batch size: 25, loss[discriminator_loss=2.663, discriminator_real_loss=1.372, discriminator_fake_loss=1.291, generator_loss=29.97, generator_mel_loss=18.77, generator_kl_loss=1.733, generator_dur_loss=1.563, generator_adv_loss=2.015, generator_feat_match_loss=5.887, over 25.00 samples.], tot_loss[discriminator_loss=2.688, discriminator_real_loss=1.331, discriminator_fake_loss=1.356, generator_loss=29.24, generator_mel_loss=18.33, generator_kl_loss=1.566, generator_dur_loss=1.699, generator_adv_loss=1.967, generator_feat_match_loss=5.675, over 128.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 14:04:04,884 INFO [train.py:527] (2/6) Epoch 603, batch 52, global_batch_idx: 74700, batch size: 52, loss[discriminator_loss=2.739, discriminator_real_loss=1.36, discriminator_fake_loss=1.379, generator_loss=29.07, generator_mel_loss=18.31, generator_kl_loss=1.564, generator_dur_loss=1.673, generator_adv_loss=1.941, generator_feat_match_loss=5.585, over 52.00 samples.], tot_loss[discriminator_loss=2.706, discriminator_real_loss=1.367, discriminator_fake_loss=1.339, generator_loss=28.56, generator_mel_loss=18.09, generator_kl_loss=1.394, generator_dur_loss=1.744, generator_adv_loss=1.972, generator_feat_match_loss=5.368, over 3074.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 14:06:22,717 INFO [train.py:527] (2/6) Epoch 603, batch 102, global_batch_idx: 74750, batch size: 88, loss[discriminator_loss=2.734, discriminator_real_loss=1.407, discriminator_fake_loss=1.327, generator_loss=28.43, generator_mel_loss=17.83, generator_kl_loss=1.12, generator_dur_loss=1.859, generator_adv_loss=1.891, generator_feat_match_loss=5.731, over 88.00 samples.], tot_loss[discriminator_loss=2.707, discriminator_real_loss=1.367, discriminator_fake_loss=1.34, generator_loss=28.51, generator_mel_loss=18.03, generator_kl_loss=1.402, generator_dur_loss=1.749, generator_adv_loss=1.965, generator_feat_match_loss=5.369, over 5989.00 samples.], cur_lr_g: 1.86e-04, cur_lr_d: 1.86e-04, 
2024-03-14 14:07:25,556 INFO [train.py:919] (2/6) Start epoch 604
2024-03-14 14:09:09,320 INFO [train.py:527] (2/6) Epoch 604, batch 28, global_batch_idx: 74800, batch size: 55, loss[discriminator_loss=2.691, discriminator_real_loss=1.452, discriminator_fake_loss=1.239, generator_loss=29.07, generator_mel_loss=18.44, generator_kl_loss=1.469, generator_dur_loss=1.673, generator_adv_loss=1.963, generator_feat_match_loss=5.525, over 55.00 samples.], tot_loss[discriminator_loss=2.692, discriminator_real_loss=1.367, discriminator_fake_loss=1.325, generator_loss=28.54, generator_mel_loss=17.95, generator_kl_loss=1.423, generator_dur_loss=1.73, generator_adv_loss=1.995, generator_feat_match_loss=5.437, over 1663.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 14:09:09,322 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 14:09:17,230 INFO [train.py:591] (2/6) Epoch 604, validation: discriminator_loss=2.716, discriminator_real_loss=1.339, discriminator_fake_loss=1.377, generator_loss=27.63, generator_mel_loss=18.5, generator_kl_loss=1.246, generator_dur_loss=1.771, generator_adv_loss=1.832, generator_feat_match_loss=4.284, over 100.00 samples.
2024-03-14 14:09:17,231 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 14:11:36,557 INFO [train.py:527] (2/6) Epoch 604, batch 78, global_batch_idx: 74850, batch size: 42, loss[discriminator_loss=2.718, discriminator_real_loss=1.442, discriminator_fake_loss=1.276, generator_loss=27.82, generator_mel_loss=17.52, generator_kl_loss=1.509, generator_dur_loss=1.677, generator_adv_loss=1.94, generator_feat_match_loss=5.173, over 42.00 samples.], tot_loss[discriminator_loss=2.71, discriminator_real_loss=1.374, discriminator_fake_loss=1.335, generator_loss=28.54, generator_mel_loss=18.01, generator_kl_loss=1.424, generator_dur_loss=1.73, generator_adv_loss=1.98, generator_feat_match_loss=5.389, over 4541.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 14:13:39,984 INFO [train.py:919] (2/6) Start epoch 605
2024-03-14 14:14:16,477 INFO [train.py:527] (2/6) Epoch 605, batch 4, global_batch_idx: 74900, batch size: 88, loss[discriminator_loss=2.67, discriminator_real_loss=1.316, discriminator_fake_loss=1.354, generator_loss=29.22, generator_mel_loss=18.36, generator_kl_loss=1.285, generator_dur_loss=1.861, generator_adv_loss=1.911, generator_feat_match_loss=5.803, over 88.00 samples.], tot_loss[discriminator_loss=2.734, discriminator_real_loss=1.38, discriminator_fake_loss=1.353, generator_loss=28.61, generator_mel_loss=18.22, generator_kl_loss=1.393, generator_dur_loss=1.791, generator_adv_loss=1.929, generator_feat_match_loss=5.276, over 331.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 14:16:33,173 INFO [train.py:527] (2/6) Epoch 605, batch 54, global_batch_idx: 74950, batch size: 44, loss[discriminator_loss=2.666, discriminator_real_loss=1.28, discriminator_fake_loss=1.386, generator_loss=29.48, generator_mel_loss=18.12, generator_kl_loss=1.576, generator_dur_loss=1.691, generator_adv_loss=2.123, generator_feat_match_loss=5.969, over 44.00 samples.], tot_loss[discriminator_loss=2.705, discriminator_real_loss=1.363, discriminator_fake_loss=1.342, generator_loss=28.49, generator_mel_loss=18.05, generator_kl_loss=1.419, generator_dur_loss=1.744, generator_adv_loss=1.95, generator_feat_match_loss=5.334, over 3176.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 14:18:54,464 INFO [train.py:527] (2/6) Epoch 605, batch 104, global_batch_idx: 75000, batch size: 74, loss[discriminator_loss=2.738, discriminator_real_loss=1.447, discriminator_fake_loss=1.291, generator_loss=28.12, generator_mel_loss=18.04, generator_kl_loss=1.194, generator_dur_loss=1.788, generator_adv_loss=1.859, generator_feat_match_loss=5.235, over 74.00 samples.], tot_loss[discriminator_loss=2.709, discriminator_real_loss=1.37, discriminator_fake_loss=1.339, generator_loss=28.49, generator_mel_loss=18.07, generator_kl_loss=1.397, generator_dur_loss=1.753, generator_adv_loss=1.953, generator_feat_match_loss=5.315, over 6223.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 14:18:54,466 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 14:19:03,050 INFO [train.py:591] (2/6) Epoch 605, validation: discriminator_loss=2.722, discriminator_real_loss=1.388, discriminator_fake_loss=1.334, generator_loss=27.13, generator_mel_loss=18.15, generator_kl_loss=1.287, generator_dur_loss=1.809, generator_adv_loss=1.841, generator_feat_match_loss=4.041, over 100.00 samples.
2024-03-14 14:19:03,051 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 14:19:55,203 INFO [train.py:919] (2/6) Start epoch 606
2024-03-14 14:21:42,313 INFO [train.py:527] (2/6) Epoch 606, batch 30, global_batch_idx: 75050, batch size: 58, loss[discriminator_loss=2.735, discriminator_real_loss=1.374, discriminator_fake_loss=1.361, generator_loss=27.57, generator_mel_loss=17.61, generator_kl_loss=1.407, generator_dur_loss=1.744, generator_adv_loss=1.969, generator_feat_match_loss=4.832, over 58.00 samples.], tot_loss[discriminator_loss=2.688, discriminator_real_loss=1.362, discriminator_fake_loss=1.326, generator_loss=28.52, generator_mel_loss=17.98, generator_kl_loss=1.41, generator_dur_loss=1.754, generator_adv_loss=1.986, generator_feat_match_loss=5.382, over 1852.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 14:24:04,831 INFO [train.py:527] (2/6) Epoch 606, batch 80, global_batch_idx: 75100, batch size: 53, loss[discriminator_loss=2.645, discriminator_real_loss=1.31, discriminator_fake_loss=1.335, generator_loss=29.73, generator_mel_loss=18.32, generator_kl_loss=1.608, generator_dur_loss=1.653, generator_adv_loss=2.011, generator_feat_match_loss=6.14, over 53.00 samples.], tot_loss[discriminator_loss=2.702, discriminator_real_loss=1.367, discriminator_fake_loss=1.335, generator_loss=28.45, generator_mel_loss=17.96, generator_kl_loss=1.398, generator_dur_loss=1.768, generator_adv_loss=1.965, generator_feat_match_loss=5.358, over 4968.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 14:26:05,035 INFO [train.py:919] (2/6) Start epoch 607
2024-03-14 14:26:45,414 INFO [train.py:527] (2/6) Epoch 607, batch 6, global_batch_idx: 75150, batch size: 64, loss[discriminator_loss=2.679, discriminator_real_loss=1.314, discriminator_fake_loss=1.365, generator_loss=28.55, generator_mel_loss=17.96, generator_kl_loss=1.325, generator_dur_loss=1.776, generator_adv_loss=1.975, generator_feat_match_loss=5.516, over 64.00 samples.], tot_loss[discriminator_loss=2.721, discriminator_real_loss=1.394, discriminator_fake_loss=1.327, generator_loss=28.31, generator_mel_loss=18.17, generator_kl_loss=1.392, generator_dur_loss=1.716, generator_adv_loss=1.969, generator_feat_match_loss=5.062, over 378.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 14:29:01,033 INFO [train.py:527] (2/6) Epoch 607, batch 56, global_batch_idx: 75200, batch size: 56, loss[discriminator_loss=2.725, discriminator_real_loss=1.366, discriminator_fake_loss=1.359, generator_loss=28.74, generator_mel_loss=18.06, generator_kl_loss=1.41, generator_dur_loss=1.701, generator_adv_loss=1.958, generator_feat_match_loss=5.61, over 56.00 samples.], tot_loss[discriminator_loss=2.705, discriminator_real_loss=1.367, discriminator_fake_loss=1.338, generator_loss=28.65, generator_mel_loss=18.17, generator_kl_loss=1.432, generator_dur_loss=1.731, generator_adv_loss=1.967, generator_feat_match_loss=5.348, over 3102.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 14:29:01,034 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 14:29:09,186 INFO [train.py:591] (2/6) Epoch 607, validation: discriminator_loss=2.745, discriminator_real_loss=1.433, discriminator_fake_loss=1.312, generator_loss=27.1, generator_mel_loss=18.15, generator_kl_loss=1.205, generator_dur_loss=1.797, generator_adv_loss=1.883, generator_feat_match_loss=4.067, over 100.00 samples.
2024-03-14 14:29:09,187 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 14:31:28,904 INFO [train.py:527] (2/6) Epoch 607, batch 106, global_batch_idx: 75250, batch size: 47, loss[discriminator_loss=2.78, discriminator_real_loss=1.257, discriminator_fake_loss=1.523, generator_loss=29.82, generator_mel_loss=18.4, generator_kl_loss=1.597, generator_dur_loss=1.619, generator_adv_loss=2.332, generator_feat_match_loss=5.87, over 47.00 samples.], tot_loss[discriminator_loss=2.706, discriminator_real_loss=1.367, discriminator_fake_loss=1.338, generator_loss=28.6, generator_mel_loss=18.09, generator_kl_loss=1.409, generator_dur_loss=1.737, generator_adv_loss=1.975, generator_feat_match_loss=5.381, over 6118.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 14:32:17,635 INFO [train.py:919] (2/6) Start epoch 608
2024-03-14 14:34:09,971 INFO [train.py:527] (2/6) Epoch 608, batch 32, global_batch_idx: 75300, batch size: 44, loss[discriminator_loss=2.601, discriminator_real_loss=1.302, discriminator_fake_loss=1.299, generator_loss=30.01, generator_mel_loss=18.27, generator_kl_loss=1.745, generator_dur_loss=1.693, generator_adv_loss=2.051, generator_feat_match_loss=6.251, over 44.00 samples.], tot_loss[discriminator_loss=2.681, discriminator_real_loss=1.367, discriminator_fake_loss=1.314, generator_loss=28.57, generator_mel_loss=17.97, generator_kl_loss=1.429, generator_dur_loss=1.728, generator_adv_loss=1.992, generator_feat_match_loss=5.452, over 1875.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 14:36:29,425 INFO [train.py:527] (2/6) Epoch 608, batch 82, global_batch_idx: 75350, batch size: 83, loss[discriminator_loss=2.689, discriminator_real_loss=1.32, discriminator_fake_loss=1.369, generator_loss=28.8, generator_mel_loss=17.97, generator_kl_loss=1.329, generator_dur_loss=1.811, generator_adv_loss=2.095, generator_feat_match_loss=5.588, over 83.00 samples.], tot_loss[discriminator_loss=2.691, discriminator_real_loss=1.369, discriminator_fake_loss=1.322, generator_loss=28.47, generator_mel_loss=17.93, generator_kl_loss=1.414, generator_dur_loss=1.737, generator_adv_loss=1.979, generator_feat_match_loss=5.413, over 4663.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 14:38:21,343 INFO [train.py:919] (2/6) Start epoch 609
2024-03-14 14:39:08,790 INFO [train.py:527] (2/6) Epoch 609, batch 8, global_batch_idx: 75400, batch size: 52, loss[discriminator_loss=2.696, discriminator_real_loss=1.369, discriminator_fake_loss=1.327, generator_loss=29.47, generator_mel_loss=18.07, generator_kl_loss=1.54, generator_dur_loss=1.681, generator_adv_loss=2.102, generator_feat_match_loss=6.083, over 52.00 samples.], tot_loss[discriminator_loss=2.708, discriminator_real_loss=1.375, discriminator_fake_loss=1.333, generator_loss=28.57, generator_mel_loss=18.1, generator_kl_loss=1.468, generator_dur_loss=1.713, generator_adv_loss=1.935, generator_feat_match_loss=5.356, over 503.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 14:39:08,792 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 14:39:16,785 INFO [train.py:591] (2/6) Epoch 609, validation: discriminator_loss=2.72, discriminator_real_loss=1.486, discriminator_fake_loss=1.235, generator_loss=27.72, generator_mel_loss=18.25, generator_kl_loss=1.291, generator_dur_loss=1.806, generator_adv_loss=2.001, generator_feat_match_loss=4.371, over 100.00 samples.
2024-03-14 14:39:16,787 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 14:41:33,441 INFO [train.py:527] (2/6) Epoch 609, batch 58, global_batch_idx: 75450, batch size: 55, loss[discriminator_loss=2.756, discriminator_real_loss=1.378, discriminator_fake_loss=1.377, generator_loss=27.9, generator_mel_loss=18.13, generator_kl_loss=1.399, generator_dur_loss=1.712, generator_adv_loss=1.944, generator_feat_match_loss=4.713, over 55.00 samples.], tot_loss[discriminator_loss=2.702, discriminator_real_loss=1.373, discriminator_fake_loss=1.329, generator_loss=28.49, generator_mel_loss=18.06, generator_kl_loss=1.449, generator_dur_loss=1.733, generator_adv_loss=1.956, generator_feat_match_loss=5.302, over 3332.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 14:43:52,367 INFO [train.py:527] (2/6) Epoch 609, batch 108, global_batch_idx: 75500, batch size: 62, loss[discriminator_loss=2.714, discriminator_real_loss=1.288, discriminator_fake_loss=1.426, generator_loss=28.56, generator_mel_loss=18.42, generator_kl_loss=1.39, generator_dur_loss=1.808, generator_adv_loss=1.973, generator_feat_match_loss=4.965, over 62.00 samples.], tot_loss[discriminator_loss=2.703, discriminator_real_loss=1.37, discriminator_fake_loss=1.333, generator_loss=28.56, generator_mel_loss=18.05, generator_kl_loss=1.43, generator_dur_loss=1.741, generator_adv_loss=1.963, generator_feat_match_loss=5.375, over 6324.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 14:44:36,116 INFO [train.py:919] (2/6) Start epoch 610
2024-03-14 14:46:32,236 INFO [train.py:527] (2/6) Epoch 610, batch 34, global_batch_idx: 75550, batch size: 59, loss[discriminator_loss=2.705, discriminator_real_loss=1.357, discriminator_fake_loss=1.348, generator_loss=28.85, generator_mel_loss=18, generator_kl_loss=1.38, generator_dur_loss=1.753, generator_adv_loss=2.081, generator_feat_match_loss=5.637, over 59.00 samples.], tot_loss[discriminator_loss=2.718, discriminator_real_loss=1.374, discriminator_fake_loss=1.344, generator_loss=28.61, generator_mel_loss=18.08, generator_kl_loss=1.432, generator_dur_loss=1.724, generator_adv_loss=1.976, generator_feat_match_loss=5.402, over 1853.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 14:48:50,521 INFO [train.py:527] (2/6) Epoch 610, batch 84, global_batch_idx: 75600, batch size: 47, loss[discriminator_loss=2.762, discriminator_real_loss=1.422, discriminator_fake_loss=1.341, generator_loss=27.47, generator_mel_loss=17.48, generator_kl_loss=1.422, generator_dur_loss=1.704, generator_adv_loss=1.786, generator_feat_match_loss=5.077, over 47.00 samples.], tot_loss[discriminator_loss=2.713, discriminator_real_loss=1.372, discriminator_fake_loss=1.341, generator_loss=28.53, generator_mel_loss=18.05, generator_kl_loss=1.424, generator_dur_loss=1.746, generator_adv_loss=1.961, generator_feat_match_loss=5.355, over 4684.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 14:48:50,523 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 14:48:59,261 INFO [train.py:591] (2/6) Epoch 610, validation: discriminator_loss=2.757, discriminator_real_loss=1.375, discriminator_fake_loss=1.382, generator_loss=27.32, generator_mel_loss=18.16, generator_kl_loss=1.119, generator_dur_loss=1.829, generator_adv_loss=1.845, generator_feat_match_loss=4.371, over 100.00 samples.
2024-03-14 14:48:59,262 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 14:50:50,340 INFO [train.py:919] (2/6) Start epoch 611
2024-03-14 14:51:41,452 INFO [train.py:527] (2/6) Epoch 611, batch 10, global_batch_idx: 75650, batch size: 42, loss[discriminator_loss=2.709, discriminator_real_loss=1.343, discriminator_fake_loss=1.366, generator_loss=28.78, generator_mel_loss=18.19, generator_kl_loss=1.418, generator_dur_loss=1.67, generator_adv_loss=2.01, generator_feat_match_loss=5.488, over 42.00 samples.], tot_loss[discriminator_loss=2.713, discriminator_real_loss=1.343, discriminator_fake_loss=1.37, generator_loss=28.74, generator_mel_loss=18.09, generator_kl_loss=1.459, generator_dur_loss=1.769, generator_adv_loss=1.978, generator_feat_match_loss=5.445, over 674.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 14:53:58,107 INFO [train.py:527] (2/6) Epoch 611, batch 60, global_batch_idx: 75700, batch size: 80, loss[discriminator_loss=2.707, discriminator_real_loss=1.347, discriminator_fake_loss=1.36, generator_loss=28.58, generator_mel_loss=17.78, generator_kl_loss=1.392, generator_dur_loss=1.823, generator_adv_loss=2.011, generator_feat_match_loss=5.567, over 80.00 samples.], tot_loss[discriminator_loss=2.712, discriminator_real_loss=1.369, discriminator_fake_loss=1.343, generator_loss=28.57, generator_mel_loss=18.02, generator_kl_loss=1.411, generator_dur_loss=1.774, generator_adv_loss=1.981, generator_feat_match_loss=5.38, over 3603.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 14:56:18,212 INFO [train.py:527] (2/6) Epoch 611, batch 110, global_batch_idx: 75750, batch size: 36, loss[discriminator_loss=2.677, discriminator_real_loss=1.321, discriminator_fake_loss=1.356, generator_loss=28.85, generator_mel_loss=17.37, generator_kl_loss=1.56, generator_dur_loss=1.675, generator_adv_loss=1.992, generator_feat_match_loss=6.262, over 36.00 samples.], tot_loss[discriminator_loss=2.709, discriminator_real_loss=1.369, discriminator_fake_loss=1.34, generator_loss=28.48, generator_mel_loss=17.99, generator_kl_loss=1.415, generator_dur_loss=1.762, generator_adv_loss=1.972, generator_feat_match_loss=5.349, over 6391.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 14:56:57,056 INFO [train.py:919] (2/6) Start epoch 612
2024-03-14 14:59:01,057 INFO [train.py:527] (2/6) Epoch 612, batch 36, global_batch_idx: 75800, batch size: 80, loss[discriminator_loss=2.672, discriminator_real_loss=1.295, discriminator_fake_loss=1.377, generator_loss=28.61, generator_mel_loss=17.74, generator_kl_loss=1.236, generator_dur_loss=1.816, generator_adv_loss=1.985, generator_feat_match_loss=5.825, over 80.00 samples.], tot_loss[discriminator_loss=2.692, discriminator_real_loss=1.359, discriminator_fake_loss=1.334, generator_loss=28.62, generator_mel_loss=18.07, generator_kl_loss=1.418, generator_dur_loss=1.739, generator_adv_loss=1.96, generator_feat_match_loss=5.436, over 1896.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 14:59:01,058 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 14:59:08,883 INFO [train.py:591] (2/6) Epoch 612, validation: discriminator_loss=2.739, discriminator_real_loss=1.439, discriminator_fake_loss=1.3, generator_loss=28.23, generator_mel_loss=18.53, generator_kl_loss=1.212, generator_dur_loss=1.82, generator_adv_loss=1.946, generator_feat_match_loss=4.718, over 100.00 samples.
2024-03-14 14:59:08,884 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 15:01:27,428 INFO [train.py:527] (2/6) Epoch 612, batch 86, global_batch_idx: 75850, batch size: 66, loss[discriminator_loss=2.73, discriminator_real_loss=1.355, discriminator_fake_loss=1.374, generator_loss=28.03, generator_mel_loss=17.58, generator_kl_loss=1.441, generator_dur_loss=1.713, generator_adv_loss=2.056, generator_feat_match_loss=5.236, over 66.00 samples.], tot_loss[discriminator_loss=2.699, discriminator_real_loss=1.362, discriminator_fake_loss=1.337, generator_loss=28.68, generator_mel_loss=18.04, generator_kl_loss=1.437, generator_dur_loss=1.75, generator_adv_loss=1.974, generator_feat_match_loss=5.482, over 4739.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 15:03:12,772 INFO [train.py:919] (2/6) Start epoch 613
2024-03-14 15:04:09,345 INFO [train.py:527] (2/6) Epoch 613, batch 12, global_batch_idx: 75900, batch size: 48, loss[discriminator_loss=2.663, discriminator_real_loss=1.377, discriminator_fake_loss=1.287, generator_loss=28.61, generator_mel_loss=18.13, generator_kl_loss=1.33, generator_dur_loss=1.704, generator_adv_loss=1.911, generator_feat_match_loss=5.538, over 48.00 samples.], tot_loss[discriminator_loss=2.69, discriminator_real_loss=1.356, discriminator_fake_loss=1.334, generator_loss=28.26, generator_mel_loss=17.98, generator_kl_loss=1.433, generator_dur_loss=1.713, generator_adv_loss=1.946, generator_feat_match_loss=5.183, over 651.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 15:06:27,981 INFO [train.py:527] (2/6) Epoch 613, batch 62, global_batch_idx: 75950, batch size: 77, loss[discriminator_loss=2.679, discriminator_real_loss=1.392, discriminator_fake_loss=1.287, generator_loss=28.64, generator_mel_loss=17.58, generator_kl_loss=1.272, generator_dur_loss=1.803, generator_adv_loss=2.047, generator_feat_match_loss=5.944, over 77.00 samples.], tot_loss[discriminator_loss=2.701, discriminator_real_loss=1.369, discriminator_fake_loss=1.332, generator_loss=28.46, generator_mel_loss=17.99, generator_kl_loss=1.423, generator_dur_loss=1.737, generator_adv_loss=1.968, generator_feat_match_loss=5.342, over 3411.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 15:08:46,741 INFO [train.py:527] (2/6) Epoch 613, batch 112, global_batch_idx: 76000, batch size: 88, loss[discriminator_loss=2.727, discriminator_real_loss=1.419, discriminator_fake_loss=1.308, generator_loss=27.63, generator_mel_loss=17.65, generator_kl_loss=1.342, generator_dur_loss=1.866, generator_adv_loss=1.818, generator_feat_match_loss=4.961, over 88.00 samples.], tot_loss[discriminator_loss=2.704, discriminator_real_loss=1.37, discriminator_fake_loss=1.334, generator_loss=28.5, generator_mel_loss=18, generator_kl_loss=1.415, generator_dur_loss=1.745, generator_adv_loss=1.968, generator_feat_match_loss=5.373, over 6227.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 15:08:46,742 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 15:08:55,768 INFO [train.py:591] (2/6) Epoch 613, validation: discriminator_loss=2.732, discriminator_real_loss=1.369, discriminator_fake_loss=1.363, generator_loss=26.41, generator_mel_loss=17.51, generator_kl_loss=1.192, generator_dur_loss=1.815, generator_adv_loss=1.822, generator_feat_match_loss=4.074, over 100.00 samples.
2024-03-14 15:08:55,769 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 15:09:29,545 INFO [train.py:919] (2/6) Start epoch 614
2024-03-14 15:11:40,239 INFO [train.py:527] (2/6) Epoch 614, batch 38, global_batch_idx: 76050, batch size: 50, loss[discriminator_loss=2.702, discriminator_real_loss=1.388, discriminator_fake_loss=1.314, generator_loss=27.16, generator_mel_loss=17.37, generator_kl_loss=1.535, generator_dur_loss=1.695, generator_adv_loss=2.056, generator_feat_match_loss=4.504, over 50.00 samples.], tot_loss[discriminator_loss=2.699, discriminator_real_loss=1.363, discriminator_fake_loss=1.336, generator_loss=28.51, generator_mel_loss=17.98, generator_kl_loss=1.422, generator_dur_loss=1.753, generator_adv_loss=1.967, generator_feat_match_loss=5.389, over 2352.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 15:14:00,554 INFO [train.py:527] (2/6) Epoch 614, batch 88, global_batch_idx: 76100, batch size: 31, loss[discriminator_loss=2.703, discriminator_real_loss=1.346, discriminator_fake_loss=1.357, generator_loss=29.1, generator_mel_loss=18.68, generator_kl_loss=1.61, generator_dur_loss=1.609, generator_adv_loss=1.963, generator_feat_match_loss=5.239, over 31.00 samples.], tot_loss[discriminator_loss=2.699, discriminator_real_loss=1.363, discriminator_fake_loss=1.336, generator_loss=28.56, generator_mel_loss=17.98, generator_kl_loss=1.427, generator_dur_loss=1.753, generator_adv_loss=1.973, generator_feat_match_loss=5.432, over 5111.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 15:15:37,080 INFO [train.py:919] (2/6) Start epoch 615
2024-03-14 15:16:41,711 INFO [train.py:527] (2/6) Epoch 615, batch 14, global_batch_idx: 76150, batch size: 39, loss[discriminator_loss=2.758, discriminator_real_loss=1.334, discriminator_fake_loss=1.424, generator_loss=28.65, generator_mel_loss=18.27, generator_kl_loss=1.488, generator_dur_loss=1.697, generator_adv_loss=1.937, generator_feat_match_loss=5.256, over 39.00 samples.], tot_loss[discriminator_loss=2.702, discriminator_real_loss=1.366, discriminator_fake_loss=1.336, generator_loss=28.63, generator_mel_loss=18.1, generator_kl_loss=1.43, generator_dur_loss=1.741, generator_adv_loss=1.982, generator_feat_match_loss=5.374, over 862.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 15:18:59,498 INFO [train.py:527] (2/6) Epoch 615, batch 64, global_batch_idx: 76200, batch size: 59, loss[discriminator_loss=2.76, discriminator_real_loss=1.484, discriminator_fake_loss=1.277, generator_loss=28.14, generator_mel_loss=17.59, generator_kl_loss=1.474, generator_dur_loss=1.716, generator_adv_loss=1.893, generator_feat_match_loss=5.47, over 59.00 samples.], tot_loss[discriminator_loss=2.704, discriminator_real_loss=1.362, discriminator_fake_loss=1.342, generator_loss=28.48, generator_mel_loss=17.97, generator_kl_loss=1.417, generator_dur_loss=1.749, generator_adv_loss=1.969, generator_feat_match_loss=5.378, over 3696.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 15:18:59,499 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 15:19:08,427 INFO [train.py:591] (2/6) Epoch 615, validation: discriminator_loss=2.76, discriminator_real_loss=1.37, discriminator_fake_loss=1.391, generator_loss=27.78, generator_mel_loss=18.31, generator_kl_loss=1.348, generator_dur_loss=1.799, generator_adv_loss=1.79, generator_feat_match_loss=4.526, over 100.00 samples.
2024-03-14 15:19:08,428 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 15:21:28,240 INFO [train.py:527] (2/6) Epoch 615, batch 114, global_batch_idx: 76250, batch size: 47, loss[discriminator_loss=2.743, discriminator_real_loss=1.416, discriminator_fake_loss=1.327, generator_loss=29.05, generator_mel_loss=18.18, generator_kl_loss=1.575, generator_dur_loss=1.705, generator_adv_loss=2.02, generator_feat_match_loss=5.573, over 47.00 samples.], tot_loss[discriminator_loss=2.704, discriminator_real_loss=1.363, discriminator_fake_loss=1.342, generator_loss=28.44, generator_mel_loss=17.96, generator_kl_loss=1.414, generator_dur_loss=1.743, generator_adv_loss=1.969, generator_feat_match_loss=5.349, over 6525.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 15:21:54,335 INFO [train.py:919] (2/6) Start epoch 616
2024-03-14 15:24:09,249 INFO [train.py:527] (2/6) Epoch 616, batch 40, global_batch_idx: 76300, batch size: 61, loss[discriminator_loss=2.66, discriminator_real_loss=1.272, discriminator_fake_loss=1.388, generator_loss=28.68, generator_mel_loss=18.15, generator_kl_loss=1.237, generator_dur_loss=1.738, generator_adv_loss=2.081, generator_feat_match_loss=5.472, over 61.00 samples.], tot_loss[discriminator_loss=2.707, discriminator_real_loss=1.366, discriminator_fake_loss=1.341, generator_loss=28.53, generator_mel_loss=18, generator_kl_loss=1.41, generator_dur_loss=1.769, generator_adv_loss=1.966, generator_feat_match_loss=5.376, over 2473.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 15:26:26,399 INFO [train.py:527] (2/6) Epoch 616, batch 90, global_batch_idx: 76350, batch size: 83, loss[discriminator_loss=2.703, discriminator_real_loss=1.37, discriminator_fake_loss=1.333, generator_loss=29.94, generator_mel_loss=18.58, generator_kl_loss=1.414, generator_dur_loss=1.811, generator_adv_loss=1.965, generator_feat_match_loss=6.174, over 83.00 samples.], tot_loss[discriminator_loss=2.709, discriminator_real_loss=1.366, discriminator_fake_loss=1.343, generator_loss=28.57, generator_mel_loss=18.03, generator_kl_loss=1.415, generator_dur_loss=1.752, generator_adv_loss=1.975, generator_feat_match_loss=5.393, over 5166.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 15:28:00,365 INFO [train.py:919] (2/6) Start epoch 617
2024-03-14 15:29:07,874 INFO [train.py:527] (2/6) Epoch 617, batch 16, global_batch_idx: 76400, batch size: 61, loss[discriminator_loss=2.638, discriminator_real_loss=1.287, discriminator_fake_loss=1.351, generator_loss=28.88, generator_mel_loss=17.99, generator_kl_loss=1.436, generator_dur_loss=1.683, generator_adv_loss=1.825, generator_feat_match_loss=5.95, over 61.00 samples.], tot_loss[discriminator_loss=2.688, discriminator_real_loss=1.36, discriminator_fake_loss=1.328, generator_loss=28.41, generator_mel_loss=17.9, generator_kl_loss=1.434, generator_dur_loss=1.715, generator_adv_loss=1.945, generator_feat_match_loss=5.412, over 941.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 15:29:07,876 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 15:29:16,008 INFO [train.py:591] (2/6) Epoch 617, validation: discriminator_loss=2.792, discriminator_real_loss=1.402, discriminator_fake_loss=1.39, generator_loss=26.97, generator_mel_loss=18.09, generator_kl_loss=1.223, generator_dur_loss=1.79, generator_adv_loss=1.766, generator_feat_match_loss=4.101, over 100.00 samples.
2024-03-14 15:29:16,010 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 15:31:36,491 INFO [train.py:527] (2/6) Epoch 617, batch 66, global_batch_idx: 76450, batch size: 72, loss[discriminator_loss=2.671, discriminator_real_loss=1.343, discriminator_fake_loss=1.328, generator_loss=28.93, generator_mel_loss=18.12, generator_kl_loss=1.378, generator_dur_loss=1.758, generator_adv_loss=1.991, generator_feat_match_loss=5.681, over 72.00 samples.], tot_loss[discriminator_loss=2.696, discriminator_real_loss=1.37, discriminator_fake_loss=1.326, generator_loss=28.56, generator_mel_loss=17.98, generator_kl_loss=1.41, generator_dur_loss=1.732, generator_adv_loss=1.976, generator_feat_match_loss=5.459, over 3838.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 15:33:53,708 INFO [train.py:527] (2/6) Epoch 617, batch 116, global_batch_idx: 76500, batch size: 66, loss[discriminator_loss=2.65, discriminator_real_loss=1.294, discriminator_fake_loss=1.356, generator_loss=28.71, generator_mel_loss=18.54, generator_kl_loss=1.292, generator_dur_loss=1.743, generator_adv_loss=2.087, generator_feat_match_loss=5.051, over 66.00 samples.], tot_loss[discriminator_loss=2.696, discriminator_real_loss=1.365, discriminator_fake_loss=1.331, generator_loss=28.51, generator_mel_loss=17.99, generator_kl_loss=1.412, generator_dur_loss=1.738, generator_adv_loss=1.973, generator_feat_match_loss=5.397, over 6811.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 15:34:14,295 INFO [train.py:919] (2/6) Start epoch 618
2024-03-14 15:36:33,341 INFO [train.py:527] (2/6) Epoch 618, batch 42, global_batch_idx: 76550, batch size: 50, loss[discriminator_loss=2.686, discriminator_real_loss=1.415, discriminator_fake_loss=1.271, generator_loss=27.98, generator_mel_loss=17.67, generator_kl_loss=1.341, generator_dur_loss=1.712, generator_adv_loss=1.885, generator_feat_match_loss=5.366, over 50.00 samples.], tot_loss[discriminator_loss=2.698, discriminator_real_loss=1.358, discriminator_fake_loss=1.341, generator_loss=28.53, generator_mel_loss=18, generator_kl_loss=1.416, generator_dur_loss=1.747, generator_adv_loss=1.968, generator_feat_match_loss=5.399, over 2464.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 15:38:53,465 INFO [train.py:527] (2/6) Epoch 618, batch 92, global_batch_idx: 76600, batch size: 31, loss[discriminator_loss=2.724, discriminator_real_loss=1.362, discriminator_fake_loss=1.363, generator_loss=29.84, generator_mel_loss=19.18, generator_kl_loss=1.798, generator_dur_loss=1.625, generator_adv_loss=2.006, generator_feat_match_loss=5.223, over 31.00 samples.], tot_loss[discriminator_loss=2.701, discriminator_real_loss=1.362, discriminator_fake_loss=1.339, generator_loss=28.51, generator_mel_loss=18.04, generator_kl_loss=1.432, generator_dur_loss=1.735, generator_adv_loss=1.968, generator_feat_match_loss=5.331, over 5231.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 15:38:53,467 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 15:39:02,304 INFO [train.py:591] (2/6) Epoch 618, validation: discriminator_loss=2.737, discriminator_real_loss=1.457, discriminator_fake_loss=1.28, generator_loss=28.13, generator_mel_loss=18.57, generator_kl_loss=1.192, generator_dur_loss=1.785, generator_adv_loss=2.007, generator_feat_match_loss=4.574, over 100.00 samples.
2024-03-14 15:39:02,305 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 15:40:29,588 INFO [train.py:919] (2/6) Start epoch 619
2024-03-14 15:41:44,082 INFO [train.py:527] (2/6) Epoch 619, batch 18, global_batch_idx: 76650, batch size: 47, loss[discriminator_loss=2.679, discriminator_real_loss=1.34, discriminator_fake_loss=1.338, generator_loss=28.98, generator_mel_loss=18.17, generator_kl_loss=1.454, generator_dur_loss=1.647, generator_adv_loss=2.086, generator_feat_match_loss=5.628, over 47.00 samples.], tot_loss[discriminator_loss=2.692, discriminator_real_loss=1.369, discriminator_fake_loss=1.323, generator_loss=28.45, generator_mel_loss=17.98, generator_kl_loss=1.436, generator_dur_loss=1.707, generator_adv_loss=1.987, generator_feat_match_loss=5.349, over 1135.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 15:44:04,011 INFO [train.py:527] (2/6) Epoch 619, batch 68, global_batch_idx: 76700, batch size: 44, loss[discriminator_loss=2.656, discriminator_real_loss=1.365, discriminator_fake_loss=1.292, generator_loss=28.41, generator_mel_loss=18.16, generator_kl_loss=1.572, generator_dur_loss=1.661, generator_adv_loss=1.971, generator_feat_match_loss=5.049, over 44.00 samples.], tot_loss[discriminator_loss=2.7, discriminator_real_loss=1.368, discriminator_fake_loss=1.332, generator_loss=28.37, generator_mel_loss=17.92, generator_kl_loss=1.428, generator_dur_loss=1.716, generator_adv_loss=1.969, generator_feat_match_loss=5.334, over 4090.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 15:46:21,632 INFO [train.py:527] (2/6) Epoch 619, batch 118, global_batch_idx: 76750, batch size: 15, loss[discriminator_loss=2.79, discriminator_real_loss=1.374, discriminator_fake_loss=1.416, generator_loss=30.54, generator_mel_loss=19.32, generator_kl_loss=1.716, generator_dur_loss=1.546, generator_adv_loss=2.172, generator_feat_match_loss=5.779, over 15.00 samples.], tot_loss[discriminator_loss=2.7, discriminator_real_loss=1.364, discriminator_fake_loss=1.335, generator_loss=28.47, generator_mel_loss=17.97, generator_kl_loss=1.432, generator_dur_loss=1.719, generator_adv_loss=1.969, generator_feat_match_loss=5.388, over 6863.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 15:46:37,270 INFO [train.py:919] (2/6) Start epoch 620
2024-03-14 15:49:01,649 INFO [train.py:527] (2/6) Epoch 620, batch 44, global_batch_idx: 76800, batch size: 59, loss[discriminator_loss=2.705, discriminator_real_loss=1.458, discriminator_fake_loss=1.247, generator_loss=28.02, generator_mel_loss=17.85, generator_kl_loss=1.371, generator_dur_loss=1.711, generator_adv_loss=1.818, generator_feat_match_loss=5.269, over 59.00 samples.], tot_loss[discriminator_loss=2.694, discriminator_real_loss=1.359, discriminator_fake_loss=1.335, generator_loss=28.65, generator_mel_loss=18.02, generator_kl_loss=1.441, generator_dur_loss=1.713, generator_adv_loss=1.973, generator_feat_match_loss=5.504, over 2473.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 15:49:01,651 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 15:49:09,772 INFO [train.py:591] (2/6) Epoch 620, validation: discriminator_loss=2.76, discriminator_real_loss=1.379, discriminator_fake_loss=1.381, generator_loss=27.65, generator_mel_loss=18.3, generator_kl_loss=1.32, generator_dur_loss=1.786, generator_adv_loss=1.781, generator_feat_match_loss=4.468, over 100.00 samples.
2024-03-14 15:49:09,773 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 15:51:27,797 INFO [train.py:527] (2/6) Epoch 620, batch 94, global_batch_idx: 76850, batch size: 66, loss[discriminator_loss=2.712, discriminator_real_loss=1.378, discriminator_fake_loss=1.334, generator_loss=27.09, generator_mel_loss=17.49, generator_kl_loss=1.397, generator_dur_loss=1.761, generator_adv_loss=1.973, generator_feat_match_loss=4.47, over 66.00 samples.], tot_loss[discriminator_loss=2.699, discriminator_real_loss=1.36, discriminator_fake_loss=1.339, generator_loss=28.52, generator_mel_loss=17.97, generator_kl_loss=1.426, generator_dur_loss=1.73, generator_adv_loss=1.963, generator_feat_match_loss=5.431, over 5428.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 15:52:52,339 INFO [train.py:919] (2/6) Start epoch 621
2024-03-14 15:54:12,849 INFO [train.py:527] (2/6) Epoch 621, batch 20, global_batch_idx: 76900, batch size: 39, loss[discriminator_loss=2.727, discriminator_real_loss=1.332, discriminator_fake_loss=1.395, generator_loss=28.79, generator_mel_loss=18.15, generator_kl_loss=1.425, generator_dur_loss=1.67, generator_adv_loss=2.077, generator_feat_match_loss=5.464, over 39.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.356, discriminator_fake_loss=1.329, generator_loss=28.91, generator_mel_loss=18.06, generator_kl_loss=1.401, generator_dur_loss=1.732, generator_adv_loss=1.976, generator_feat_match_loss=5.741, over 1239.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 15:56:29,089 INFO [train.py:527] (2/6) Epoch 621, batch 70, global_batch_idx: 76950, batch size: 70, loss[discriminator_loss=2.671, discriminator_real_loss=1.42, discriminator_fake_loss=1.25, generator_loss=28.7, generator_mel_loss=17.75, generator_kl_loss=1.366, generator_dur_loss=1.774, generator_adv_loss=1.938, generator_feat_match_loss=5.873, over 70.00 samples.], tot_loss[discriminator_loss=2.694, discriminator_real_loss=1.364, discriminator_fake_loss=1.329, generator_loss=28.68, generator_mel_loss=18.02, generator_kl_loss=1.45, generator_dur_loss=1.722, generator_adv_loss=1.978, generator_feat_match_loss=5.507, over 3777.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 15:58:46,204 INFO [train.py:527] (2/6) Epoch 621, batch 120, global_batch_idx: 77000, batch size: 77, loss[discriminator_loss=2.764, discriminator_real_loss=1.432, discriminator_fake_loss=1.333, generator_loss=27.89, generator_mel_loss=17.89, generator_kl_loss=1.372, generator_dur_loss=1.836, generator_adv_loss=1.74, generator_feat_match_loss=5.05, over 77.00 samples.], tot_loss[discriminator_loss=2.701, discriminator_real_loss=1.368, discriminator_fake_loss=1.333, generator_loss=28.65, generator_mel_loss=18, generator_kl_loss=1.44, generator_dur_loss=1.738, generator_adv_loss=2, generator_feat_match_loss=5.469, over 6685.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 15:58:46,205 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 15:58:54,768 INFO [train.py:591] (2/6) Epoch 621, validation: discriminator_loss=2.75, discriminator_real_loss=1.291, discriminator_fake_loss=1.459, generator_loss=27.94, generator_mel_loss=18.84, generator_kl_loss=1.224, generator_dur_loss=1.817, generator_adv_loss=1.724, generator_feat_match_loss=4.334, over 100.00 samples.
2024-03-14 15:58:54,769 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 15:59:04,646 INFO [train.py:919] (2/6) Start epoch 622
2024-03-14 16:01:37,718 INFO [train.py:527] (2/6) Epoch 622, batch 46, global_batch_idx: 77050, batch size: 44, loss[discriminator_loss=2.67, discriminator_real_loss=1.302, discriminator_fake_loss=1.368, generator_loss=28.99, generator_mel_loss=18.42, generator_kl_loss=1.68, generator_dur_loss=1.652, generator_adv_loss=2.042, generator_feat_match_loss=5.199, over 44.00 samples.], tot_loss[discriminator_loss=2.689, discriminator_real_loss=1.364, discriminator_fake_loss=1.324, generator_loss=28.71, generator_mel_loss=18.06, generator_kl_loss=1.465, generator_dur_loss=1.725, generator_adv_loss=1.983, generator_feat_match_loss=5.477, over 2499.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 16:03:59,765 INFO [train.py:527] (2/6) Epoch 622, batch 96, global_batch_idx: 77100, batch size: 53, loss[discriminator_loss=2.716, discriminator_real_loss=1.439, discriminator_fake_loss=1.277, generator_loss=27.32, generator_mel_loss=17.56, generator_kl_loss=1.401, generator_dur_loss=1.684, generator_adv_loss=1.929, generator_feat_match_loss=4.749, over 53.00 samples.], tot_loss[discriminator_loss=2.7, discriminator_real_loss=1.369, discriminator_fake_loss=1.331, generator_loss=28.64, generator_mel_loss=18.06, generator_kl_loss=1.441, generator_dur_loss=1.739, generator_adv_loss=1.971, generator_feat_match_loss=5.433, over 5430.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 16:05:14,766 INFO [train.py:919] (2/6) Start epoch 623
2024-03-14 16:06:39,157 INFO [train.py:527] (2/6) Epoch 623, batch 22, global_batch_idx: 77150, batch size: 42, loss[discriminator_loss=2.709, discriminator_real_loss=1.425, discriminator_fake_loss=1.284, generator_loss=27.99, generator_mel_loss=18.1, generator_kl_loss=1.319, generator_dur_loss=1.72, generator_adv_loss=1.86, generator_feat_match_loss=4.999, over 42.00 samples.], tot_loss[discriminator_loss=2.714, discriminator_real_loss=1.39, discriminator_fake_loss=1.324, generator_loss=28.3, generator_mel_loss=17.92, generator_kl_loss=1.385, generator_dur_loss=1.745, generator_adv_loss=1.977, generator_feat_match_loss=5.271, over 1302.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 16:08:58,380 INFO [train.py:527] (2/6) Epoch 623, batch 72, global_batch_idx: 77200, batch size: 66, loss[discriminator_loss=2.658, discriminator_real_loss=1.369, discriminator_fake_loss=1.289, generator_loss=28.36, generator_mel_loss=17.72, generator_kl_loss=1.316, generator_dur_loss=1.751, generator_adv_loss=1.981, generator_feat_match_loss=5.591, over 66.00 samples.], tot_loss[discriminator_loss=2.696, discriminator_real_loss=1.363, discriminator_fake_loss=1.333, generator_loss=28.5, generator_mel_loss=17.99, generator_kl_loss=1.394, generator_dur_loss=1.737, generator_adv_loss=1.967, generator_feat_match_loss=5.418, over 4111.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 16:08:58,381 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 16:09:07,223 INFO [train.py:591] (2/6) Epoch 623, validation: discriminator_loss=2.696, discriminator_real_loss=1.386, discriminator_fake_loss=1.31, generator_loss=26.81, generator_mel_loss=18.35, generator_kl_loss=1.231, generator_dur_loss=1.774, generator_adv_loss=1.872, generator_feat_match_loss=3.584, over 100.00 samples.
2024-03-14 16:09:07,224 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 16:11:25,885 INFO [train.py:527] (2/6) Epoch 623, batch 122, global_batch_idx: 77250, batch size: 31, loss[discriminator_loss=2.729, discriminator_real_loss=1.312, discriminator_fake_loss=1.417, generator_loss=28.4, generator_mel_loss=18.11, generator_kl_loss=1.471, generator_dur_loss=1.64, generator_adv_loss=2.099, generator_feat_match_loss=5.084, over 31.00 samples.], tot_loss[discriminator_loss=2.696, discriminator_real_loss=1.367, discriminator_fake_loss=1.329, generator_loss=28.55, generator_mel_loss=18, generator_kl_loss=1.416, generator_dur_loss=1.725, generator_adv_loss=1.975, generator_feat_match_loss=5.439, over 6701.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 16:11:31,005 INFO [train.py:919] (2/6) Start epoch 624
2024-03-14 16:14:06,379 INFO [train.py:527] (2/6) Epoch 624, batch 48, global_batch_idx: 77300, batch size: 55, loss[discriminator_loss=2.656, discriminator_real_loss=1.321, discriminator_fake_loss=1.336, generator_loss=29.2, generator_mel_loss=18.24, generator_kl_loss=1.554, generator_dur_loss=1.661, generator_adv_loss=2.063, generator_feat_match_loss=5.682, over 55.00 samples.], tot_loss[discriminator_loss=2.695, discriminator_real_loss=1.367, discriminator_fake_loss=1.328, generator_loss=28.57, generator_mel_loss=18.02, generator_kl_loss=1.445, generator_dur_loss=1.721, generator_adv_loss=1.978, generator_feat_match_loss=5.403, over 2692.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 16:16:24,652 INFO [train.py:527] (2/6) Epoch 624, batch 98, global_batch_idx: 77350, batch size: 48, loss[discriminator_loss=2.746, discriminator_real_loss=1.449, discriminator_fake_loss=1.297, generator_loss=27.98, generator_mel_loss=17.68, generator_kl_loss=1.498, generator_dur_loss=1.637, generator_adv_loss=1.829, generator_feat_match_loss=5.341, over 48.00 samples.], tot_loss[discriminator_loss=2.704, discriminator_real_loss=1.373, discriminator_fake_loss=1.331, generator_loss=28.57, generator_mel_loss=18.01, generator_kl_loss=1.446, generator_dur_loss=1.716, generator_adv_loss=1.973, generator_feat_match_loss=5.428, over 5283.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 16:17:35,513 INFO [train.py:919] (2/6) Start epoch 625
2024-03-14 16:19:06,948 INFO [train.py:527] (2/6) Epoch 625, batch 24, global_batch_idx: 77400, batch size: 25, loss[discriminator_loss=2.596, discriminator_real_loss=1.304, discriminator_fake_loss=1.292, generator_loss=30.65, generator_mel_loss=18.74, generator_kl_loss=1.813, generator_dur_loss=1.536, generator_adv_loss=2.029, generator_feat_match_loss=6.535, over 25.00 samples.], tot_loss[discriminator_loss=2.713, discriminator_real_loss=1.361, discriminator_fake_loss=1.352, generator_loss=28.56, generator_mel_loss=18.02, generator_kl_loss=1.421, generator_dur_loss=1.72, generator_adv_loss=1.981, generator_feat_match_loss=5.415, over 1387.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 16:19:06,949 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 16:19:15,007 INFO [train.py:591] (2/6) Epoch 625, validation: discriminator_loss=2.787, discriminator_real_loss=1.394, discriminator_fake_loss=1.393, generator_loss=27.75, generator_mel_loss=18.58, generator_kl_loss=1.218, generator_dur_loss=1.788, generator_adv_loss=1.8, generator_feat_match_loss=4.369, over 100.00 samples.
2024-03-14 16:19:15,008 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 16:21:33,738 INFO [train.py:527] (2/6) Epoch 625, batch 74, global_batch_idx: 77450, batch size: 61, loss[discriminator_loss=2.745, discriminator_real_loss=1.369, discriminator_fake_loss=1.376, generator_loss=28.04, generator_mel_loss=18, generator_kl_loss=1.39, generator_dur_loss=1.751, generator_adv_loss=2.012, generator_feat_match_loss=4.887, over 61.00 samples.], tot_loss[discriminator_loss=2.705, discriminator_real_loss=1.365, discriminator_fake_loss=1.34, generator_loss=28.57, generator_mel_loss=17.97, generator_kl_loss=1.437, generator_dur_loss=1.725, generator_adv_loss=1.981, generator_feat_match_loss=5.458, over 4046.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 16:23:51,097 INFO [train.py:919] (2/6) Start epoch 626
2024-03-14 16:24:13,200 INFO [train.py:527] (2/6) Epoch 626, batch 0, global_batch_idx: 77500, batch size: 96, loss[discriminator_loss=2.663, discriminator_real_loss=1.328, discriminator_fake_loss=1.335, generator_loss=28.6, generator_mel_loss=17.82, generator_kl_loss=1.344, generator_dur_loss=1.935, generator_adv_loss=2.083, generator_feat_match_loss=5.423, over 96.00 samples.], tot_loss[discriminator_loss=2.663, discriminator_real_loss=1.328, discriminator_fake_loss=1.335, generator_loss=28.6, generator_mel_loss=17.82, generator_kl_loss=1.344, generator_dur_loss=1.935, generator_adv_loss=2.083, generator_feat_match_loss=5.423, over 96.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 16:26:30,706 INFO [train.py:527] (2/6) Epoch 626, batch 50, global_batch_idx: 77550, batch size: 96, loss[discriminator_loss=2.69, discriminator_real_loss=1.36, discriminator_fake_loss=1.331, generator_loss=28.52, generator_mel_loss=17.81, generator_kl_loss=1.148, generator_dur_loss=1.884, generator_adv_loss=2.024, generator_feat_match_loss=5.662, over 96.00 samples.], tot_loss[discriminator_loss=2.705, discriminator_real_loss=1.372, discriminator_fake_loss=1.333, generator_loss=28.54, generator_mel_loss=17.94, generator_kl_loss=1.409, generator_dur_loss=1.756, generator_adv_loss=1.967, generator_feat_match_loss=5.465, over 3011.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 16:28:48,470 INFO [train.py:527] (2/6) Epoch 626, batch 100, global_batch_idx: 77600, batch size: 83, loss[discriminator_loss=2.709, discriminator_real_loss=1.387, discriminator_fake_loss=1.322, generator_loss=28.99, generator_mel_loss=18.19, generator_kl_loss=1.514, generator_dur_loss=1.87, generator_adv_loss=1.998, generator_feat_match_loss=5.417, over 83.00 samples.], tot_loss[discriminator_loss=2.695, discriminator_real_loss=1.365, discriminator_fake_loss=1.33, generator_loss=28.5, generator_mel_loss=17.93, generator_kl_loss=1.408, generator_dur_loss=1.76, generator_adv_loss=1.974, generator_feat_match_loss=5.435, over 5917.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 16:28:48,472 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 16:28:57,308 INFO [train.py:591] (2/6) Epoch 626, validation: discriminator_loss=2.77, discriminator_real_loss=1.421, discriminator_fake_loss=1.349, generator_loss=28.55, generator_mel_loss=18.8, generator_kl_loss=1.313, generator_dur_loss=1.817, generator_adv_loss=1.934, generator_feat_match_loss=4.69, over 100.00 samples.
2024-03-14 16:28:57,309 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 16:30:03,136 INFO [train.py:919] (2/6) Start epoch 627
2024-03-14 16:31:38,190 INFO [train.py:527] (2/6) Epoch 627, batch 26, global_batch_idx: 77650, batch size: 68, loss[discriminator_loss=2.664, discriminator_real_loss=1.352, discriminator_fake_loss=1.312, generator_loss=28.4, generator_mel_loss=17.77, generator_kl_loss=1.398, generator_dur_loss=1.808, generator_adv_loss=1.868, generator_feat_match_loss=5.56, over 68.00 samples.], tot_loss[discriminator_loss=2.702, discriminator_real_loss=1.365, discriminator_fake_loss=1.337, generator_loss=28.54, generator_mel_loss=17.89, generator_kl_loss=1.438, generator_dur_loss=1.749, generator_adv_loss=1.972, generator_feat_match_loss=5.491, over 1540.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 16:33:58,508 INFO [train.py:527] (2/6) Epoch 627, batch 76, global_batch_idx: 77700, batch size: 48, loss[discriminator_loss=2.672, discriminator_real_loss=1.288, discriminator_fake_loss=1.384, generator_loss=29.34, generator_mel_loss=18.26, generator_kl_loss=1.544, generator_dur_loss=1.707, generator_adv_loss=1.917, generator_feat_match_loss=5.916, over 48.00 samples.], tot_loss[discriminator_loss=2.692, discriminator_real_loss=1.358, discriminator_fake_loss=1.334, generator_loss=28.62, generator_mel_loss=17.96, generator_kl_loss=1.415, generator_dur_loss=1.757, generator_adv_loss=1.973, generator_feat_match_loss=5.514, over 4480.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 16:36:10,037 INFO [train.py:919] (2/6) Start epoch 628
2024-03-14 16:36:40,012 INFO [train.py:527] (2/6) Epoch 628, batch 2, global_batch_idx: 77750, batch size: 56, loss[discriminator_loss=2.731, discriminator_real_loss=1.41, discriminator_fake_loss=1.321, generator_loss=27.58, generator_mel_loss=17.64, generator_kl_loss=1.446, generator_dur_loss=1.665, generator_adv_loss=2.044, generator_feat_match_loss=4.782, over 56.00 samples.], tot_loss[discriminator_loss=2.698, discriminator_real_loss=1.338, discriminator_fake_loss=1.36, generator_loss=28.42, generator_mel_loss=18.03, generator_kl_loss=1.378, generator_dur_loss=1.738, generator_adv_loss=1.988, generator_feat_match_loss=5.281, over 183.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 16:39:00,307 INFO [train.py:527] (2/6) Epoch 628, batch 52, global_batch_idx: 77800, batch size: 48, loss[discriminator_loss=2.712, discriminator_real_loss=1.41, discriminator_fake_loss=1.301, generator_loss=29.15, generator_mel_loss=18.01, generator_kl_loss=1.625, generator_dur_loss=1.656, generator_adv_loss=1.93, generator_feat_match_loss=5.93, over 48.00 samples.], tot_loss[discriminator_loss=2.704, discriminator_real_loss=1.364, discriminator_fake_loss=1.34, generator_loss=28.55, generator_mel_loss=18.01, generator_kl_loss=1.415, generator_dur_loss=1.75, generator_adv_loss=1.965, generator_feat_match_loss=5.416, over 2976.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 16:39:00,309 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 16:39:08,520 INFO [train.py:591] (2/6) Epoch 628, validation: discriminator_loss=2.75, discriminator_real_loss=1.409, discriminator_fake_loss=1.341, generator_loss=26.74, generator_mel_loss=17.86, generator_kl_loss=1.223, generator_dur_loss=1.809, generator_adv_loss=1.878, generator_feat_match_loss=3.963, over 100.00 samples.
2024-03-14 16:39:08,521 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 16:41:26,722 INFO [train.py:527] (2/6) Epoch 628, batch 102, global_batch_idx: 77850, batch size: 88, loss[discriminator_loss=2.7, discriminator_real_loss=1.352, discriminator_fake_loss=1.348, generator_loss=28.32, generator_mel_loss=17.73, generator_kl_loss=1.264, generator_dur_loss=1.855, generator_adv_loss=2.003, generator_feat_match_loss=5.472, over 88.00 samples.], tot_loss[discriminator_loss=2.7, discriminator_real_loss=1.36, discriminator_fake_loss=1.34, generator_loss=28.56, generator_mel_loss=17.98, generator_kl_loss=1.423, generator_dur_loss=1.749, generator_adv_loss=1.968, generator_feat_match_loss=5.437, over 5859.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 16:42:25,213 INFO [train.py:919] (2/6) Start epoch 629
2024-03-14 16:44:07,026 INFO [train.py:527] (2/6) Epoch 629, batch 28, global_batch_idx: 77900, batch size: 36, loss[discriminator_loss=2.724, discriminator_real_loss=1.416, discriminator_fake_loss=1.308, generator_loss=28.65, generator_mel_loss=17.81, generator_kl_loss=1.537, generator_dur_loss=1.715, generator_adv_loss=2.003, generator_feat_match_loss=5.585, over 36.00 samples.], tot_loss[discriminator_loss=2.703, discriminator_real_loss=1.361, discriminator_fake_loss=1.342, generator_loss=28.56, generator_mel_loss=18.02, generator_kl_loss=1.424, generator_dur_loss=1.764, generator_adv_loss=1.966, generator_feat_match_loss=5.383, over 1679.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 16:46:27,940 INFO [train.py:527] (2/6) Epoch 629, batch 78, global_batch_idx: 77950, batch size: 59, loss[discriminator_loss=2.664, discriminator_real_loss=1.398, discriminator_fake_loss=1.266, generator_loss=28.81, generator_mel_loss=18.18, generator_kl_loss=1.367, generator_dur_loss=1.773, generator_adv_loss=2.021, generator_feat_match_loss=5.468, over 59.00 samples.], tot_loss[discriminator_loss=2.694, discriminator_real_loss=1.359, discriminator_fake_loss=1.335, generator_loss=28.66, generator_mel_loss=18, generator_kl_loss=1.44, generator_dur_loss=1.756, generator_adv_loss=1.974, generator_feat_match_loss=5.484, over 4410.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 16:48:29,034 INFO [train.py:919] (2/6) Start epoch 630
2024-03-14 16:49:03,378 INFO [train.py:527] (2/6) Epoch 630, batch 4, global_batch_idx: 78000, batch size: 72, loss[discriminator_loss=2.725, discriminator_real_loss=1.379, discriminator_fake_loss=1.346, generator_loss=28.53, generator_mel_loss=17.86, generator_kl_loss=1.398, generator_dur_loss=1.71, generator_adv_loss=1.979, generator_feat_match_loss=5.587, over 72.00 samples.], tot_loss[discriminator_loss=2.697, discriminator_real_loss=1.348, discriminator_fake_loss=1.349, generator_loss=28.52, generator_mel_loss=18.01, generator_kl_loss=1.424, generator_dur_loss=1.696, generator_adv_loss=1.938, generator_feat_match_loss=5.45, over 246.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 16:49:03,382 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 16:49:11,213 INFO [train.py:591] (2/6) Epoch 630, validation: discriminator_loss=2.726, discriminator_real_loss=1.44, discriminator_fake_loss=1.286, generator_loss=27.32, generator_mel_loss=18.55, generator_kl_loss=1.224, generator_dur_loss=1.794, generator_adv_loss=1.879, generator_feat_match_loss=3.873, over 100.00 samples.
2024-03-14 16:49:11,215 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 16:51:32,531 INFO [train.py:527] (2/6) Epoch 630, batch 54, global_batch_idx: 78050, batch size: 96, loss[discriminator_loss=2.702, discriminator_real_loss=1.387, discriminator_fake_loss=1.314, generator_loss=28.02, generator_mel_loss=17.53, generator_kl_loss=1.217, generator_dur_loss=1.862, generator_adv_loss=1.892, generator_feat_match_loss=5.517, over 96.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.378, discriminator_fake_loss=1.336, generator_loss=28.38, generator_mel_loss=17.9, generator_kl_loss=1.421, generator_dur_loss=1.74, generator_adv_loss=1.968, generator_feat_match_loss=5.358, over 3136.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 16:53:47,791 INFO [train.py:527] (2/6) Epoch 630, batch 104, global_batch_idx: 78100, batch size: 48, loss[discriminator_loss=2.743, discriminator_real_loss=1.34, discriminator_fake_loss=1.403, generator_loss=29.37, generator_mel_loss=18.3, generator_kl_loss=1.541, generator_dur_loss=1.64, generator_adv_loss=1.953, generator_feat_match_loss=5.929, over 48.00 samples.], tot_loss[discriminator_loss=2.708, discriminator_real_loss=1.372, discriminator_fake_loss=1.336, generator_loss=28.43, generator_mel_loss=17.92, generator_kl_loss=1.421, generator_dur_loss=1.734, generator_adv_loss=1.968, generator_feat_match_loss=5.384, over 5880.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 16:54:41,256 INFO [train.py:919] (2/6) Start epoch 631
2024-03-14 16:56:27,400 INFO [train.py:527] (2/6) Epoch 631, batch 30, global_batch_idx: 78150, batch size: 49, loss[discriminator_loss=2.728, discriminator_real_loss=1.417, discriminator_fake_loss=1.311, generator_loss=29.23, generator_mel_loss=18.15, generator_kl_loss=1.534, generator_dur_loss=1.677, generator_adv_loss=2.112, generator_feat_match_loss=5.753, over 49.00 samples.], tot_loss[discriminator_loss=2.725, discriminator_real_loss=1.37, discriminator_fake_loss=1.355, generator_loss=28.59, generator_mel_loss=18.01, generator_kl_loss=1.471, generator_dur_loss=1.745, generator_adv_loss=1.958, generator_feat_match_loss=5.408, over 1759.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 16:58:46,240 INFO [train.py:527] (2/6) Epoch 631, batch 80, global_batch_idx: 78200, batch size: 47, loss[discriminator_loss=2.691, discriminator_real_loss=1.44, discriminator_fake_loss=1.251, generator_loss=28.4, generator_mel_loss=18.2, generator_kl_loss=1.407, generator_dur_loss=1.655, generator_adv_loss=1.992, generator_feat_match_loss=5.148, over 47.00 samples.], tot_loss[discriminator_loss=2.715, discriminator_real_loss=1.371, discriminator_fake_loss=1.344, generator_loss=28.54, generator_mel_loss=17.99, generator_kl_loss=1.42, generator_dur_loss=1.76, generator_adv_loss=1.972, generator_feat_match_loss=5.403, over 4851.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 16:58:46,243 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 16:58:55,115 INFO [train.py:591] (2/6) Epoch 631, validation: discriminator_loss=2.755, discriminator_real_loss=1.418, discriminator_fake_loss=1.337, generator_loss=28.09, generator_mel_loss=18.49, generator_kl_loss=1.212, generator_dur_loss=1.811, generator_adv_loss=1.905, generator_feat_match_loss=4.679, over 100.00 samples.
2024-03-14 16:58:55,116 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 17:00:57,037 INFO [train.py:919] (2/6) Start epoch 632
2024-03-14 17:01:38,912 INFO [train.py:527] (2/6) Epoch 632, batch 6, global_batch_idx: 78250, batch size: 62, loss[discriminator_loss=2.689, discriminator_real_loss=1.402, discriminator_fake_loss=1.287, generator_loss=29.23, generator_mel_loss=18.18, generator_kl_loss=1.414, generator_dur_loss=1.757, generator_adv_loss=2.032, generator_feat_match_loss=5.854, over 62.00 samples.], tot_loss[discriminator_loss=2.66, discriminator_real_loss=1.364, discriminator_fake_loss=1.297, generator_loss=28.78, generator_mel_loss=18.02, generator_kl_loss=1.374, generator_dur_loss=1.778, generator_adv_loss=2.001, generator_feat_match_loss=5.607, over 492.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 17:03:55,682 INFO [train.py:527] (2/6) Epoch 632, batch 56, global_batch_idx: 78300, batch size: 70, loss[discriminator_loss=2.722, discriminator_real_loss=1.378, discriminator_fake_loss=1.345, generator_loss=27.93, generator_mel_loss=17.79, generator_kl_loss=1.244, generator_dur_loss=1.806, generator_adv_loss=1.944, generator_feat_match_loss=5.144, over 70.00 samples.], tot_loss[discriminator_loss=2.696, discriminator_real_loss=1.367, discriminator_fake_loss=1.329, generator_loss=28.49, generator_mel_loss=17.95, generator_kl_loss=1.394, generator_dur_loss=1.761, generator_adv_loss=1.967, generator_feat_match_loss=5.417, over 3532.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 17:06:17,398 INFO [train.py:527] (2/6) Epoch 632, batch 106, global_batch_idx: 78350, batch size: 55, loss[discriminator_loss=2.68, discriminator_real_loss=1.41, discriminator_fake_loss=1.271, generator_loss=27.71, generator_mel_loss=17.98, generator_kl_loss=1.364, generator_dur_loss=1.787, generator_adv_loss=1.843, generator_feat_match_loss=4.733, over 55.00 samples.], tot_loss[discriminator_loss=2.7, discriminator_real_loss=1.368, discriminator_fake_loss=1.332, generator_loss=28.57, generator_mel_loss=17.98, generator_kl_loss=1.412, generator_dur_loss=1.744, generator_adv_loss=1.97, generator_feat_match_loss=5.457, over 6144.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 17:07:03,815 INFO [train.py:919] (2/6) Start epoch 633
2024-03-14 17:08:58,898 INFO [train.py:527] (2/6) Epoch 633, batch 32, global_batch_idx: 78400, batch size: 42, loss[discriminator_loss=2.721, discriminator_real_loss=1.283, discriminator_fake_loss=1.438, generator_loss=28.22, generator_mel_loss=17.88, generator_kl_loss=1.543, generator_dur_loss=1.677, generator_adv_loss=1.972, generator_feat_match_loss=5.149, over 42.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.377, discriminator_fake_loss=1.339, generator_loss=28.47, generator_mel_loss=18.03, generator_kl_loss=1.407, generator_dur_loss=1.733, generator_adv_loss=1.966, generator_feat_match_loss=5.334, over 1825.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 17:08:58,900 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 17:09:07,180 INFO [train.py:591] (2/6) Epoch 633, validation: discriminator_loss=2.741, discriminator_real_loss=1.458, discriminator_fake_loss=1.283, generator_loss=28.12, generator_mel_loss=18.28, generator_kl_loss=1.256, generator_dur_loss=1.797, generator_adv_loss=2.012, generator_feat_match_loss=4.773, over 100.00 samples.
2024-03-14 17:09:07,181 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 17:11:28,196 INFO [train.py:527] (2/6) Epoch 633, batch 82, global_batch_idx: 78450, batch size: 45, loss[discriminator_loss=2.668, discriminator_real_loss=1.38, discriminator_fake_loss=1.289, generator_loss=29.06, generator_mel_loss=18.35, generator_kl_loss=1.493, generator_dur_loss=1.679, generator_adv_loss=2.095, generator_feat_match_loss=5.442, over 45.00 samples.], tot_loss[discriminator_loss=2.702, discriminator_real_loss=1.367, discriminator_fake_loss=1.336, generator_loss=28.49, generator_mel_loss=17.98, generator_kl_loss=1.409, generator_dur_loss=1.739, generator_adv_loss=1.968, generator_feat_match_loss=5.394, over 4823.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 17:13:20,742 INFO [train.py:919] (2/6) Start epoch 634
2024-03-14 17:14:04,064 INFO [train.py:527] (2/6) Epoch 634, batch 8, global_batch_idx: 78500, batch size: 52, loss[discriminator_loss=2.753, discriminator_real_loss=1.404, discriminator_fake_loss=1.349, generator_loss=28.3, generator_mel_loss=17.9, generator_kl_loss=1.493, generator_dur_loss=1.73, generator_adv_loss=1.95, generator_feat_match_loss=5.227, over 52.00 samples.], tot_loss[discriminator_loss=2.726, discriminator_real_loss=1.379, discriminator_fake_loss=1.347, generator_loss=28.74, generator_mel_loss=18.11, generator_kl_loss=1.412, generator_dur_loss=1.751, generator_adv_loss=1.979, generator_feat_match_loss=5.485, over 586.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 17:16:22,890 INFO [train.py:527] (2/6) Epoch 634, batch 58, global_batch_idx: 78550, batch size: 68, loss[discriminator_loss=2.767, discriminator_real_loss=1.353, discriminator_fake_loss=1.414, generator_loss=28.61, generator_mel_loss=17.89, generator_kl_loss=1.273, generator_dur_loss=1.788, generator_adv_loss=1.915, generator_feat_match_loss=5.745, over 68.00 samples.], tot_loss[discriminator_loss=2.696, discriminator_real_loss=1.365, discriminator_fake_loss=1.331, generator_loss=28.71, generator_mel_loss=18.04, generator_kl_loss=1.405, generator_dur_loss=1.731, generator_adv_loss=1.981, generator_feat_match_loss=5.553, over 3430.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 17:18:42,616 INFO [train.py:527] (2/6) Epoch 634, batch 108, global_batch_idx: 78600, batch size: 88, loss[discriminator_loss=2.685, discriminator_real_loss=1.324, discriminator_fake_loss=1.362, generator_loss=27.77, generator_mel_loss=17.67, generator_kl_loss=1.291, generator_dur_loss=1.812, generator_adv_loss=1.858, generator_feat_match_loss=5.141, over 88.00 samples.], tot_loss[discriminator_loss=2.701, discriminator_real_loss=1.366, discriminator_fake_loss=1.336, generator_loss=28.6, generator_mel_loss=17.98, generator_kl_loss=1.408, generator_dur_loss=1.739, generator_adv_loss=1.976, generator_feat_match_loss=5.499, over 6376.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 17:18:42,617 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 17:18:51,364 INFO [train.py:591] (2/6) Epoch 634, validation: discriminator_loss=2.718, discriminator_real_loss=1.369, discriminator_fake_loss=1.348, generator_loss=26.9, generator_mel_loss=18.02, generator_kl_loss=1.312, generator_dur_loss=1.802, generator_adv_loss=1.768, generator_feat_match_loss=3.992, over 100.00 samples.
2024-03-14 17:18:51,364 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 17:19:33,274 INFO [train.py:919] (2/6) Start epoch 635
2024-03-14 17:21:33,245 INFO [train.py:527] (2/6) Epoch 635, batch 34, global_batch_idx: 78650, batch size: 45, loss[discriminator_loss=2.684, discriminator_real_loss=1.387, discriminator_fake_loss=1.297, generator_loss=28.41, generator_mel_loss=17.47, generator_kl_loss=1.574, generator_dur_loss=1.655, generator_adv_loss=1.924, generator_feat_match_loss=5.786, over 45.00 samples.], tot_loss[discriminator_loss=2.704, discriminator_real_loss=1.368, discriminator_fake_loss=1.336, generator_loss=28.49, generator_mel_loss=17.88, generator_kl_loss=1.443, generator_dur_loss=1.739, generator_adv_loss=1.985, generator_feat_match_loss=5.438, over 2000.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 17:23:53,417 INFO [train.py:527] (2/6) Epoch 635, batch 84, global_batch_idx: 78700, batch size: 61, loss[discriminator_loss=2.728, discriminator_real_loss=1.383, discriminator_fake_loss=1.345, generator_loss=29.46, generator_mel_loss=18.65, generator_kl_loss=1.203, generator_dur_loss=1.733, generator_adv_loss=1.987, generator_feat_match_loss=5.889, over 61.00 samples.], tot_loss[discriminator_loss=2.696, discriminator_real_loss=1.361, discriminator_fake_loss=1.335, generator_loss=28.53, generator_mel_loss=17.95, generator_kl_loss=1.409, generator_dur_loss=1.756, generator_adv_loss=1.981, generator_feat_match_loss=5.436, over 5054.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 17:25:40,992 INFO [train.py:919] (2/6) Start epoch 636
2024-03-14 17:26:32,587 INFO [train.py:527] (2/6) Epoch 636, batch 10, global_batch_idx: 78750, batch size: 83, loss[discriminator_loss=2.608, discriminator_real_loss=1.279, discriminator_fake_loss=1.329, generator_loss=28.74, generator_mel_loss=18.1, generator_kl_loss=1.302, generator_dur_loss=1.869, generator_adv_loss=1.957, generator_feat_match_loss=5.516, over 83.00 samples.], tot_loss[discriminator_loss=2.693, discriminator_real_loss=1.358, discriminator_fake_loss=1.335, generator_loss=28.87, generator_mel_loss=18.06, generator_kl_loss=1.398, generator_dur_loss=1.762, generator_adv_loss=1.978, generator_feat_match_loss=5.67, over 652.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 17:28:51,952 INFO [train.py:527] (2/6) Epoch 636, batch 60, global_batch_idx: 78800, batch size: 39, loss[discriminator_loss=2.709, discriminator_real_loss=1.393, discriminator_fake_loss=1.317, generator_loss=28.42, generator_mel_loss=17.92, generator_kl_loss=1.452, generator_dur_loss=1.68, generator_adv_loss=1.939, generator_feat_match_loss=5.425, over 39.00 samples.], tot_loss[discriminator_loss=2.696, discriminator_real_loss=1.358, discriminator_fake_loss=1.337, generator_loss=28.8, generator_mel_loss=18.08, generator_kl_loss=1.417, generator_dur_loss=1.75, generator_adv_loss=1.971, generator_feat_match_loss=5.576, over 3401.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 17:28:51,954 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 17:29:00,092 INFO [train.py:591] (2/6) Epoch 636, validation: discriminator_loss=2.778, discriminator_real_loss=1.396, discriminator_fake_loss=1.382, generator_loss=27.24, generator_mel_loss=18.22, generator_kl_loss=1.223, generator_dur_loss=1.803, generator_adv_loss=1.794, generator_feat_match_loss=4.2, over 100.00 samples.
2024-03-14 17:29:00,093 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 17:31:19,344 INFO [train.py:527] (2/6) Epoch 636, batch 110, global_batch_idx: 78850, batch size: 15, loss[discriminator_loss=2.669, discriminator_real_loss=1.312, discriminator_fake_loss=1.357, generator_loss=30.79, generator_mel_loss=18.9, generator_kl_loss=1.838, generator_dur_loss=1.51, generator_adv_loss=2.035, generator_feat_match_loss=6.505, over 15.00 samples.], tot_loss[discriminator_loss=2.694, discriminator_real_loss=1.359, discriminator_fake_loss=1.335, generator_loss=28.71, generator_mel_loss=18.05, generator_kl_loss=1.402, generator_dur_loss=1.75, generator_adv_loss=1.979, generator_feat_match_loss=5.528, over 6252.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 17:31:55,279 INFO [train.py:919] (2/6) Start epoch 637
2024-03-14 17:34:01,428 INFO [train.py:527] (2/6) Epoch 637, batch 36, global_batch_idx: 78900, batch size: 55, loss[discriminator_loss=2.707, discriminator_real_loss=1.326, discriminator_fake_loss=1.381, generator_loss=28.13, generator_mel_loss=17.84, generator_kl_loss=1.409, generator_dur_loss=1.678, generator_adv_loss=1.976, generator_feat_match_loss=5.228, over 55.00 samples.], tot_loss[discriminator_loss=2.687, discriminator_real_loss=1.356, discriminator_fake_loss=1.331, generator_loss=28.75, generator_mel_loss=18.06, generator_kl_loss=1.396, generator_dur_loss=1.732, generator_adv_loss=1.991, generator_feat_match_loss=5.578, over 2075.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 17:36:21,651 INFO [train.py:527] (2/6) Epoch 637, batch 86, global_batch_idx: 78950, batch size: 15, loss[discriminator_loss=2.667, discriminator_real_loss=1.474, discriminator_fake_loss=1.193, generator_loss=29.74, generator_mel_loss=18.37, generator_kl_loss=1.779, generator_dur_loss=1.502, generator_adv_loss=2.018, generator_feat_match_loss=6.072, over 15.00 samples.], tot_loss[discriminator_loss=2.691, discriminator_real_loss=1.36, discriminator_fake_loss=1.331, generator_loss=28.62, generator_mel_loss=18, generator_kl_loss=1.398, generator_dur_loss=1.738, generator_adv_loss=1.982, generator_feat_match_loss=5.511, over 4918.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 17:38:04,905 INFO [train.py:919] (2/6) Start epoch 638
2024-03-14 17:39:02,850 INFO [train.py:527] (2/6) Epoch 638, batch 12, global_batch_idx: 79000, batch size: 77, loss[discriminator_loss=2.654, discriminator_real_loss=1.264, discriminator_fake_loss=1.39, generator_loss=28.91, generator_mel_loss=17.65, generator_kl_loss=1.439, generator_dur_loss=1.764, generator_adv_loss=2.124, generator_feat_match_loss=5.935, over 77.00 samples.], tot_loss[discriminator_loss=2.68, discriminator_real_loss=1.346, discriminator_fake_loss=1.334, generator_loss=28.65, generator_mel_loss=17.89, generator_kl_loss=1.447, generator_dur_loss=1.707, generator_adv_loss=2.004, generator_feat_match_loss=5.6, over 665.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 17:39:02,854 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 17:39:10,863 INFO [train.py:591] (2/6) Epoch 638, validation: discriminator_loss=2.766, discriminator_real_loss=1.487, discriminator_fake_loss=1.279, generator_loss=27.09, generator_mel_loss=17.94, generator_kl_loss=1.158, generator_dur_loss=1.771, generator_adv_loss=2.034, generator_feat_match_loss=4.187, over 100.00 samples.
2024-03-14 17:39:10,864 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 17:41:29,720 INFO [train.py:527] (2/6) Epoch 638, batch 62, global_batch_idx: 79050, batch size: 74, loss[discriminator_loss=2.763, discriminator_real_loss=1.413, discriminator_fake_loss=1.35, generator_loss=28.7, generator_mel_loss=18.1, generator_kl_loss=1.297, generator_dur_loss=1.758, generator_adv_loss=1.935, generator_feat_match_loss=5.606, over 74.00 samples.], tot_loss[discriminator_loss=2.702, discriminator_real_loss=1.365, discriminator_fake_loss=1.337, generator_loss=28.61, generator_mel_loss=17.95, generator_kl_loss=1.429, generator_dur_loss=1.721, generator_adv_loss=1.974, generator_feat_match_loss=5.528, over 3429.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 17:43:49,003 INFO [train.py:527] (2/6) Epoch 638, batch 112, global_batch_idx: 79100, batch size: 56, loss[discriminator_loss=2.645, discriminator_real_loss=1.445, discriminator_fake_loss=1.2, generator_loss=27.88, generator_mel_loss=17.83, generator_kl_loss=1.424, generator_dur_loss=1.755, generator_adv_loss=1.88, generator_feat_match_loss=4.992, over 56.00 samples.], tot_loss[discriminator_loss=2.706, discriminator_real_loss=1.369, discriminator_fake_loss=1.338, generator_loss=28.54, generator_mel_loss=17.95, generator_kl_loss=1.418, generator_dur_loss=1.738, generator_adv_loss=1.966, generator_feat_match_loss=5.464, over 6310.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 17:44:19,182 INFO [train.py:919] (2/6) Start epoch 639
2024-03-14 17:46:30,031 INFO [train.py:527] (2/6) Epoch 639, batch 38, global_batch_idx: 79150, batch size: 56, loss[discriminator_loss=2.748, discriminator_real_loss=1.445, discriminator_fake_loss=1.303, generator_loss=28.25, generator_mel_loss=17.84, generator_kl_loss=1.363, generator_dur_loss=1.728, generator_adv_loss=2.06, generator_feat_match_loss=5.257, over 56.00 samples.], tot_loss[discriminator_loss=2.695, discriminator_real_loss=1.366, discriminator_fake_loss=1.329, generator_loss=28.74, generator_mel_loss=18.05, generator_kl_loss=1.461, generator_dur_loss=1.748, generator_adv_loss=1.982, generator_feat_match_loss=5.499, over 2203.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 17:48:47,254 INFO [train.py:527] (2/6) Epoch 639, batch 88, global_batch_idx: 79200, batch size: 66, loss[discriminator_loss=2.646, discriminator_real_loss=1.35, discriminator_fake_loss=1.296, generator_loss=29, generator_mel_loss=18.29, generator_kl_loss=1.444, generator_dur_loss=1.738, generator_adv_loss=2.061, generator_feat_match_loss=5.473, over 66.00 samples.], tot_loss[discriminator_loss=2.69, discriminator_real_loss=1.359, discriminator_fake_loss=1.331, generator_loss=28.75, generator_mel_loss=18, generator_kl_loss=1.45, generator_dur_loss=1.75, generator_adv_loss=2.014, generator_feat_match_loss=5.532, over 5045.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 17:48:47,256 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 17:48:56,149 INFO [train.py:591] (2/6) Epoch 639, validation: discriminator_loss=2.739, discriminator_real_loss=1.471, discriminator_fake_loss=1.268, generator_loss=27.94, generator_mel_loss=18.03, generator_kl_loss=1.41, generator_dur_loss=1.795, generator_adv_loss=2.035, generator_feat_match_loss=4.675, over 100.00 samples.
2024-03-14 17:48:56,151 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 17:50:32,522 INFO [train.py:919] (2/6) Start epoch 640
2024-03-14 17:51:37,849 INFO [train.py:527] (2/6) Epoch 640, batch 14, global_batch_idx: 79250, batch size: 53, loss[discriminator_loss=2.623, discriminator_real_loss=1.323, discriminator_fake_loss=1.3, generator_loss=29.05, generator_mel_loss=18.26, generator_kl_loss=1.5, generator_dur_loss=1.652, generator_adv_loss=1.934, generator_feat_match_loss=5.698, over 53.00 samples.], tot_loss[discriminator_loss=2.682, discriminator_real_loss=1.362, discriminator_fake_loss=1.32, generator_loss=28.86, generator_mel_loss=18.03, generator_kl_loss=1.474, generator_dur_loss=1.727, generator_adv_loss=1.98, generator_feat_match_loss=5.647, over 780.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 17:53:54,784 INFO [train.py:527] (2/6) Epoch 640, batch 64, global_batch_idx: 79300, batch size: 53, loss[discriminator_loss=2.685, discriminator_real_loss=1.387, discriminator_fake_loss=1.299, generator_loss=29.62, generator_mel_loss=18.2, generator_kl_loss=1.433, generator_dur_loss=1.737, generator_adv_loss=2.046, generator_feat_match_loss=6.205, over 53.00 samples.], tot_loss[discriminator_loss=2.687, discriminator_real_loss=1.358, discriminator_fake_loss=1.329, generator_loss=28.69, generator_mel_loss=17.95, generator_kl_loss=1.422, generator_dur_loss=1.747, generator_adv_loss=1.984, generator_feat_match_loss=5.591, over 3733.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 17:56:14,324 INFO [train.py:527] (2/6) Epoch 640, batch 114, global_batch_idx: 79350, batch size: 74, loss[discriminator_loss=2.679, discriminator_real_loss=1.336, discriminator_fake_loss=1.343, generator_loss=28.9, generator_mel_loss=17.99, generator_kl_loss=1.335, generator_dur_loss=1.787, generator_adv_loss=1.984, generator_feat_match_loss=5.81, over 74.00 samples.], tot_loss[discriminator_loss=2.696, discriminator_real_loss=1.363, discriminator_fake_loss=1.332, generator_loss=28.65, generator_mel_loss=17.95, generator_kl_loss=1.418, generator_dur_loss=1.753, generator_adv_loss=1.972, generator_feat_match_loss=5.556, over 6721.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 17:56:40,311 INFO [train.py:919] (2/6) Start epoch 641
2024-03-14 17:58:56,453 INFO [train.py:527] (2/6) Epoch 641, batch 40, global_batch_idx: 79400, batch size: 44, loss[discriminator_loss=2.655, discriminator_real_loss=1.371, discriminator_fake_loss=1.284, generator_loss=29.37, generator_mel_loss=18.04, generator_kl_loss=1.691, generator_dur_loss=1.685, generator_adv_loss=1.948, generator_feat_match_loss=6.005, over 44.00 samples.], tot_loss[discriminator_loss=2.693, discriminator_real_loss=1.369, discriminator_fake_loss=1.324, generator_loss=28.57, generator_mel_loss=17.95, generator_kl_loss=1.411, generator_dur_loss=1.763, generator_adv_loss=1.987, generator_feat_match_loss=5.452, over 2438.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 17:58:56,455 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 17:59:04,409 INFO [train.py:591] (2/6) Epoch 641, validation: discriminator_loss=2.781, discriminator_real_loss=1.342, discriminator_fake_loss=1.439, generator_loss=27.18, generator_mel_loss=18.07, generator_kl_loss=1.282, generator_dur_loss=1.84, generator_adv_loss=1.758, generator_feat_match_loss=4.235, over 100.00 samples.
2024-03-14 17:59:04,410 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 18:01:24,925 INFO [train.py:527] (2/6) Epoch 641, batch 90, global_batch_idx: 79450, batch size: 72, loss[discriminator_loss=2.771, discriminator_real_loss=1.421, discriminator_fake_loss=1.35, generator_loss=27.62, generator_mel_loss=17.48, generator_kl_loss=1.312, generator_dur_loss=1.828, generator_adv_loss=1.931, generator_feat_match_loss=5.069, over 72.00 samples.], tot_loss[discriminator_loss=2.695, discriminator_real_loss=1.368, discriminator_fake_loss=1.328, generator_loss=28.62, generator_mel_loss=17.97, generator_kl_loss=1.412, generator_dur_loss=1.764, generator_adv_loss=1.983, generator_feat_match_loss=5.49, over 5316.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 18:02:56,077 INFO [train.py:919] (2/6) Start epoch 642
2024-03-14 18:04:05,227 INFO [train.py:527] (2/6) Epoch 642, batch 16, global_batch_idx: 79500, batch size: 25, loss[discriminator_loss=2.686, discriminator_real_loss=1.475, discriminator_fake_loss=1.211, generator_loss=28.72, generator_mel_loss=18.52, generator_kl_loss=1.736, generator_dur_loss=1.548, generator_adv_loss=1.911, generator_feat_match_loss=5.009, over 25.00 samples.], tot_loss[discriminator_loss=2.698, discriminator_real_loss=1.358, discriminator_fake_loss=1.34, generator_loss=28.54, generator_mel_loss=18.11, generator_kl_loss=1.395, generator_dur_loss=1.751, generator_adv_loss=1.946, generator_feat_match_loss=5.332, over 968.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 18:06:24,284 INFO [train.py:527] (2/6) Epoch 642, batch 66, global_batch_idx: 79550, batch size: 55, loss[discriminator_loss=2.722, discriminator_real_loss=1.331, discriminator_fake_loss=1.391, generator_loss=28.9, generator_mel_loss=18.08, generator_kl_loss=1.358, generator_dur_loss=1.761, generator_adv_loss=2.231, generator_feat_match_loss=5.468, over 55.00 samples.], tot_loss[discriminator_loss=2.695, discriminator_real_loss=1.361, discriminator_fake_loss=1.335, generator_loss=28.63, generator_mel_loss=18.05, generator_kl_loss=1.428, generator_dur_loss=1.749, generator_adv_loss=1.975, generator_feat_match_loss=5.424, over 3720.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 18:08:44,247 INFO [train.py:527] (2/6) Epoch 642, batch 116, global_batch_idx: 79600, batch size: 39, loss[discriminator_loss=2.703, discriminator_real_loss=1.396, discriminator_fake_loss=1.307, generator_loss=29.46, generator_mel_loss=18.7, generator_kl_loss=1.563, generator_dur_loss=1.685, generator_adv_loss=1.932, generator_feat_match_loss=5.579, over 39.00 samples.], tot_loss[discriminator_loss=2.702, discriminator_real_loss=1.369, discriminator_fake_loss=1.333, generator_loss=28.66, generator_mel_loss=18.02, generator_kl_loss=1.429, generator_dur_loss=1.753, generator_adv_loss=1.992, generator_feat_match_loss=5.465, over 6561.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 18:08:44,249 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 18:08:52,920 INFO [train.py:591] (2/6) Epoch 642, validation: discriminator_loss=2.71, discriminator_real_loss=1.316, discriminator_fake_loss=1.395, generator_loss=27.72, generator_mel_loss=18.36, generator_kl_loss=1.407, generator_dur_loss=1.821, generator_adv_loss=1.883, generator_feat_match_loss=4.249, over 100.00 samples.
2024-03-14 18:08:52,921 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 18:09:15,020 INFO [train.py:919] (2/6) Start epoch 643
2024-03-14 18:11:35,656 INFO [train.py:527] (2/6) Epoch 643, batch 42, global_batch_idx: 79650, batch size: 58, loss[discriminator_loss=2.716, discriminator_real_loss=1.381, discriminator_fake_loss=1.334, generator_loss=28.06, generator_mel_loss=18, generator_kl_loss=1.322, generator_dur_loss=1.726, generator_adv_loss=1.925, generator_feat_match_loss=5.085, over 58.00 samples.], tot_loss[discriminator_loss=2.696, discriminator_real_loss=1.37, discriminator_fake_loss=1.326, generator_loss=28.52, generator_mel_loss=17.92, generator_kl_loss=1.418, generator_dur_loss=1.774, generator_adv_loss=1.985, generator_feat_match_loss=5.428, over 2675.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 18:13:54,511 INFO [train.py:527] (2/6) Epoch 643, batch 92, global_batch_idx: 79700, batch size: 16, loss[discriminator_loss=2.614, discriminator_real_loss=1.37, discriminator_fake_loss=1.244, generator_loss=31.79, generator_mel_loss=19.1, generator_kl_loss=1.735, generator_dur_loss=1.558, generator_adv_loss=2.091, generator_feat_match_loss=7.304, over 16.00 samples.], tot_loss[discriminator_loss=2.695, discriminator_real_loss=1.364, discriminator_fake_loss=1.331, generator_loss=28.52, generator_mel_loss=17.92, generator_kl_loss=1.414, generator_dur_loss=1.767, generator_adv_loss=1.976, generator_feat_match_loss=5.438, over 5639.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 18:15:22,783 INFO [train.py:919] (2/6) Start epoch 644
2024-03-14 18:16:39,342 INFO [train.py:527] (2/6) Epoch 644, batch 18, global_batch_idx: 79750, batch size: 50, loss[discriminator_loss=2.663, discriminator_real_loss=1.343, discriminator_fake_loss=1.32, generator_loss=27.96, generator_mel_loss=17.91, generator_kl_loss=1.319, generator_dur_loss=1.799, generator_adv_loss=1.949, generator_feat_match_loss=4.978, over 50.00 samples.], tot_loss[discriminator_loss=2.7, discriminator_real_loss=1.364, discriminator_fake_loss=1.336, generator_loss=28.55, generator_mel_loss=17.95, generator_kl_loss=1.377, generator_dur_loss=1.782, generator_adv_loss=1.959, generator_feat_match_loss=5.484, over 1212.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 18:18:58,842 INFO [train.py:527] (2/6) Epoch 644, batch 68, global_batch_idx: 79800, batch size: 39, loss[discriminator_loss=2.689, discriminator_real_loss=1.48, discriminator_fake_loss=1.209, generator_loss=28.13, generator_mel_loss=17.98, generator_kl_loss=1.505, generator_dur_loss=1.722, generator_adv_loss=2.001, generator_feat_match_loss=4.923, over 39.00 samples.], tot_loss[discriminator_loss=2.693, discriminator_real_loss=1.36, discriminator_fake_loss=1.333, generator_loss=28.66, generator_mel_loss=17.97, generator_kl_loss=1.411, generator_dur_loss=1.768, generator_adv_loss=1.975, generator_feat_match_loss=5.54, over 4050.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 18:18:58,844 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 18:19:07,779 INFO [train.py:591] (2/6) Epoch 644, validation: discriminator_loss=2.725, discriminator_real_loss=1.409, discriminator_fake_loss=1.316, generator_loss=27.35, generator_mel_loss=18.23, generator_kl_loss=1.156, generator_dur_loss=1.814, generator_adv_loss=1.872, generator_feat_match_loss=4.274, over 100.00 samples.
2024-03-14 18:19:07,780 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 18:21:27,660 INFO [train.py:527] (2/6) Epoch 644, batch 118, global_batch_idx: 79850, batch size: 25, loss[discriminator_loss=2.702, discriminator_real_loss=1.337, discriminator_fake_loss=1.365, generator_loss=30.4, generator_mel_loss=18.59, generator_kl_loss=1.772, generator_dur_loss=1.546, generator_adv_loss=2.02, generator_feat_match_loss=6.471, over 25.00 samples.], tot_loss[discriminator_loss=2.698, discriminator_real_loss=1.364, discriminator_fake_loss=1.334, generator_loss=28.67, generator_mel_loss=18.04, generator_kl_loss=1.42, generator_dur_loss=1.76, generator_adv_loss=1.971, generator_feat_match_loss=5.481, over 6773.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 18:21:43,789 INFO [train.py:919] (2/6) Start epoch 645
2024-03-14 18:24:13,439 INFO [train.py:527] (2/6) Epoch 645, batch 44, global_batch_idx: 79900, batch size: 55, loss[discriminator_loss=2.679, discriminator_real_loss=1.416, discriminator_fake_loss=1.263, generator_loss=28.73, generator_mel_loss=18.06, generator_kl_loss=1.605, generator_dur_loss=1.676, generator_adv_loss=2.004, generator_feat_match_loss=5.393, over 55.00 samples.], tot_loss[discriminator_loss=2.695, discriminator_real_loss=1.374, discriminator_fake_loss=1.321, generator_loss=28.72, generator_mel_loss=18.05, generator_kl_loss=1.407, generator_dur_loss=1.762, generator_adv_loss=1.979, generator_feat_match_loss=5.521, over 2594.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 18:26:34,821 INFO [train.py:527] (2/6) Epoch 645, batch 94, global_batch_idx: 79950, batch size: 58, loss[discriminator_loss=2.721, discriminator_real_loss=1.246, discriminator_fake_loss=1.475, generator_loss=29.45, generator_mel_loss=18.22, generator_kl_loss=1.404, generator_dur_loss=1.684, generator_adv_loss=2.093, generator_feat_match_loss=6.05, over 58.00 samples.], tot_loss[discriminator_loss=2.69, discriminator_real_loss=1.364, discriminator_fake_loss=1.325, generator_loss=28.76, generator_mel_loss=18.03, generator_kl_loss=1.419, generator_dur_loss=1.758, generator_adv_loss=1.986, generator_feat_match_loss=5.569, over 5495.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 18:27:54,062 INFO [train.py:919] (2/6) Start epoch 646
2024-03-14 18:29:16,772 INFO [train.py:527] (2/6) Epoch 646, batch 20, global_batch_idx: 80000, batch size: 53, loss[discriminator_loss=2.685, discriminator_real_loss=1.42, discriminator_fake_loss=1.265, generator_loss=28.11, generator_mel_loss=17.74, generator_kl_loss=1.383, generator_dur_loss=1.734, generator_adv_loss=1.88, generator_feat_match_loss=5.374, over 53.00 samples.], tot_loss[discriminator_loss=2.707, discriminator_real_loss=1.37, discriminator_fake_loss=1.336, generator_loss=28.75, generator_mel_loss=18.02, generator_kl_loss=1.442, generator_dur_loss=1.761, generator_adv_loss=1.981, generator_feat_match_loss=5.544, over 1238.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 18:29:16,773 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 18:29:24,873 INFO [train.py:591] (2/6) Epoch 646, validation: discriminator_loss=2.734, discriminator_real_loss=1.391, discriminator_fake_loss=1.343, generator_loss=27.28, generator_mel_loss=18.04, generator_kl_loss=1.169, generator_dur_loss=1.815, generator_adv_loss=1.777, generator_feat_match_loss=4.481, over 100.00 samples.
2024-03-14 18:29:24,875 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 18:31:44,423 INFO [train.py:527] (2/6) Epoch 646, batch 70, global_batch_idx: 80050, batch size: 42, loss[discriminator_loss=2.692, discriminator_real_loss=1.385, discriminator_fake_loss=1.307, generator_loss=28.79, generator_mel_loss=18.02, generator_kl_loss=1.5, generator_dur_loss=1.707, generator_adv_loss=2.032, generator_feat_match_loss=5.527, over 42.00 samples.], tot_loss[discriminator_loss=2.695, discriminator_real_loss=1.363, discriminator_fake_loss=1.332, generator_loss=28.65, generator_mel_loss=17.98, generator_kl_loss=1.431, generator_dur_loss=1.749, generator_adv_loss=1.976, generator_feat_match_loss=5.514, over 3972.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 18:34:03,567 INFO [train.py:527] (2/6) Epoch 646, batch 120, global_batch_idx: 80100, batch size: 13, loss[discriminator_loss=2.645, discriminator_real_loss=1.206, discriminator_fake_loss=1.439, generator_loss=29.95, generator_mel_loss=18.45, generator_kl_loss=1.767, generator_dur_loss=1.6, generator_adv_loss=2.163, generator_feat_match_loss=5.966, over 13.00 samples.], tot_loss[discriminator_loss=2.696, discriminator_real_loss=1.359, discriminator_fake_loss=1.336, generator_loss=28.66, generator_mel_loss=17.99, generator_kl_loss=1.438, generator_dur_loss=1.749, generator_adv_loss=1.973, generator_feat_match_loss=5.508, over 6722.00 samples.], cur_lr_g: 1.85e-04, cur_lr_d: 1.85e-04, 
2024-03-14 18:34:12,624 INFO [train.py:919] (2/6) Start epoch 647
2024-03-14 18:36:49,303 INFO [train.py:527] (2/6) Epoch 647, batch 46, global_batch_idx: 80150, batch size: 56, loss[discriminator_loss=2.739, discriminator_real_loss=1.447, discriminator_fake_loss=1.293, generator_loss=27.94, generator_mel_loss=17.47, generator_kl_loss=1.399, generator_dur_loss=1.715, generator_adv_loss=2.062, generator_feat_match_loss=5.29, over 56.00 samples.], tot_loss[discriminator_loss=2.708, discriminator_real_loss=1.373, discriminator_fake_loss=1.335, generator_loss=28.54, generator_mel_loss=18, generator_kl_loss=1.427, generator_dur_loss=1.764, generator_adv_loss=1.979, generator_feat_match_loss=5.371, over 2819.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 18:39:08,890 INFO [train.py:527] (2/6) Epoch 647, batch 96, global_batch_idx: 80200, batch size: 66, loss[discriminator_loss=2.637, discriminator_real_loss=1.285, discriminator_fake_loss=1.352, generator_loss=28.8, generator_mel_loss=18.05, generator_kl_loss=1.539, generator_dur_loss=1.742, generator_adv_loss=2.062, generator_feat_match_loss=5.412, over 66.00 samples.], tot_loss[discriminator_loss=2.704, discriminator_real_loss=1.365, discriminator_fake_loss=1.339, generator_loss=28.65, generator_mel_loss=18.01, generator_kl_loss=1.428, generator_dur_loss=1.752, generator_adv_loss=1.983, generator_feat_match_loss=5.478, over 5476.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 18:39:08,892 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 18:39:17,850 INFO [train.py:591] (2/6) Epoch 647, validation: discriminator_loss=2.737, discriminator_real_loss=1.457, discriminator_fake_loss=1.28, generator_loss=27.18, generator_mel_loss=17.86, generator_kl_loss=1.308, generator_dur_loss=1.817, generator_adv_loss=1.983, generator_feat_match_loss=4.211, over 100.00 samples.
2024-03-14 18:39:17,851 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 18:40:36,005 INFO [train.py:919] (2/6) Start epoch 648
2024-03-14 18:42:03,936 INFO [train.py:527] (2/6) Epoch 648, batch 22, global_batch_idx: 80250, batch size: 58, loss[discriminator_loss=2.741, discriminator_real_loss=1.359, discriminator_fake_loss=1.383, generator_loss=27.88, generator_mel_loss=17.76, generator_kl_loss=1.469, generator_dur_loss=1.74, generator_adv_loss=1.981, generator_feat_match_loss=4.932, over 58.00 samples.], tot_loss[discriminator_loss=2.71, discriminator_real_loss=1.368, discriminator_fake_loss=1.342, generator_loss=28.53, generator_mel_loss=18.01, generator_kl_loss=1.44, generator_dur_loss=1.724, generator_adv_loss=1.979, generator_feat_match_loss=5.379, over 1187.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 18:44:22,209 INFO [train.py:527] (2/6) Epoch 648, batch 72, global_batch_idx: 80300, batch size: 16, loss[discriminator_loss=2.75, discriminator_real_loss=1.352, discriminator_fake_loss=1.397, generator_loss=29.68, generator_mel_loss=18.93, generator_kl_loss=1.884, generator_dur_loss=1.598, generator_adv_loss=1.897, generator_feat_match_loss=5.371, over 16.00 samples.], tot_loss[discriminator_loss=2.709, discriminator_real_loss=1.371, discriminator_fake_loss=1.338, generator_loss=28.66, generator_mel_loss=18.04, generator_kl_loss=1.428, generator_dur_loss=1.733, generator_adv_loss=1.978, generator_feat_match_loss=5.481, over 3784.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 18:46:42,997 INFO [train.py:527] (2/6) Epoch 648, batch 122, global_batch_idx: 80350, batch size: 58, loss[discriminator_loss=2.764, discriminator_real_loss=1.463, discriminator_fake_loss=1.301, generator_loss=28.84, generator_mel_loss=18.58, generator_kl_loss=1.466, generator_dur_loss=1.75, generator_adv_loss=1.89, generator_feat_match_loss=5.146, over 58.00 samples.], tot_loss[discriminator_loss=2.705, discriminator_real_loss=1.367, discriminator_fake_loss=1.337, generator_loss=28.65, generator_mel_loss=18.02, generator_kl_loss=1.421, generator_dur_loss=1.745, generator_adv_loss=1.984, generator_feat_match_loss=5.473, over 6589.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 18:46:48,433 INFO [train.py:919] (2/6) Start epoch 649
2024-03-14 18:49:23,171 INFO [train.py:527] (2/6) Epoch 649, batch 48, global_batch_idx: 80400, batch size: 72, loss[discriminator_loss=2.66, discriminator_real_loss=1.316, discriminator_fake_loss=1.344, generator_loss=28.67, generator_mel_loss=18.04, generator_kl_loss=1.207, generator_dur_loss=1.79, generator_adv_loss=1.974, generator_feat_match_loss=5.661, over 72.00 samples.], tot_loss[discriminator_loss=2.698, discriminator_real_loss=1.362, discriminator_fake_loss=1.335, generator_loss=28.53, generator_mel_loss=17.94, generator_kl_loss=1.4, generator_dur_loss=1.759, generator_adv_loss=1.973, generator_feat_match_loss=5.463, over 2916.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 18:49:23,174 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 18:49:31,231 INFO [train.py:591] (2/6) Epoch 649, validation: discriminator_loss=2.692, discriminator_real_loss=1.378, discriminator_fake_loss=1.313, generator_loss=27.1, generator_mel_loss=17.88, generator_kl_loss=1.266, generator_dur_loss=1.811, generator_adv_loss=1.928, generator_feat_match_loss=4.224, over 100.00 samples.
2024-03-14 18:49:31,232 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 18:51:51,867 INFO [train.py:527] (2/6) Epoch 649, batch 98, global_batch_idx: 80450, batch size: 47, loss[discriminator_loss=2.733, discriminator_real_loss=1.405, discriminator_fake_loss=1.328, generator_loss=27.98, generator_mel_loss=18.07, generator_kl_loss=1.471, generator_dur_loss=1.704, generator_adv_loss=1.94, generator_feat_match_loss=4.792, over 47.00 samples.], tot_loss[discriminator_loss=2.688, discriminator_real_loss=1.362, discriminator_fake_loss=1.327, generator_loss=28.61, generator_mel_loss=17.96, generator_kl_loss=1.404, generator_dur_loss=1.759, generator_adv_loss=1.996, generator_feat_match_loss=5.494, over 5661.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 18:53:00,773 INFO [train.py:919] (2/6) Start epoch 650
2024-03-14 18:54:29,832 INFO [train.py:527] (2/6) Epoch 650, batch 24, global_batch_idx: 80500, batch size: 68, loss[discriminator_loss=2.664, discriminator_real_loss=1.291, discriminator_fake_loss=1.373, generator_loss=28.68, generator_mel_loss=18.12, generator_kl_loss=1.386, generator_dur_loss=1.78, generator_adv_loss=1.976, generator_feat_match_loss=5.42, over 68.00 samples.], tot_loss[discriminator_loss=2.702, discriminator_real_loss=1.362, discriminator_fake_loss=1.34, generator_loss=28.59, generator_mel_loss=17.96, generator_kl_loss=1.374, generator_dur_loss=1.79, generator_adv_loss=1.955, generator_feat_match_loss=5.507, over 1607.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 18:56:49,017 INFO [train.py:527] (2/6) Epoch 650, batch 74, global_batch_idx: 80550, batch size: 31, loss[discriminator_loss=2.761, discriminator_real_loss=1.43, discriminator_fake_loss=1.332, generator_loss=29.74, generator_mel_loss=18.36, generator_kl_loss=1.595, generator_dur_loss=1.605, generator_adv_loss=1.858, generator_feat_match_loss=6.325, over 31.00 samples.], tot_loss[discriminator_loss=2.695, discriminator_real_loss=1.362, discriminator_fake_loss=1.333, generator_loss=28.55, generator_mel_loss=17.95, generator_kl_loss=1.391, generator_dur_loss=1.775, generator_adv_loss=1.97, generator_feat_match_loss=5.471, over 4560.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 18:59:05,000 INFO [train.py:919] (2/6) Start epoch 651
2024-03-14 18:59:29,146 INFO [train.py:527] (2/6) Epoch 651, batch 0, global_batch_idx: 80600, batch size: 42, loss[discriminator_loss=2.721, discriminator_real_loss=1.472, discriminator_fake_loss=1.249, generator_loss=28.42, generator_mel_loss=18.42, generator_kl_loss=1.522, generator_dur_loss=1.718, generator_adv_loss=1.954, generator_feat_match_loss=4.798, over 42.00 samples.], tot_loss[discriminator_loss=2.721, discriminator_real_loss=1.472, discriminator_fake_loss=1.249, generator_loss=28.42, generator_mel_loss=18.42, generator_kl_loss=1.522, generator_dur_loss=1.718, generator_adv_loss=1.954, generator_feat_match_loss=4.798, over 42.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 18:59:29,149 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 18:59:36,909 INFO [train.py:591] (2/6) Epoch 651, validation: discriminator_loss=2.733, discriminator_real_loss=1.396, discriminator_fake_loss=1.337, generator_loss=27.56, generator_mel_loss=18.3, generator_kl_loss=1.281, generator_dur_loss=1.793, generator_adv_loss=1.882, generator_feat_match_loss=4.305, over 100.00 samples.
2024-03-14 18:59:36,922 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 19:01:55,831 INFO [train.py:527] (2/6) Epoch 651, batch 50, global_batch_idx: 80650, batch size: 62, loss[discriminator_loss=2.725, discriminator_real_loss=1.432, discriminator_fake_loss=1.293, generator_loss=28.11, generator_mel_loss=17.78, generator_kl_loss=1.392, generator_dur_loss=1.741, generator_adv_loss=2.021, generator_feat_match_loss=5.182, over 62.00 samples.], tot_loss[discriminator_loss=2.701, discriminator_real_loss=1.368, discriminator_fake_loss=1.334, generator_loss=28.61, generator_mel_loss=18, generator_kl_loss=1.404, generator_dur_loss=1.752, generator_adv_loss=1.972, generator_feat_match_loss=5.483, over 2955.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 19:04:14,991 INFO [train.py:527] (2/6) Epoch 651, batch 100, global_batch_idx: 80700, batch size: 74, loss[discriminator_loss=2.664, discriminator_real_loss=1.338, discriminator_fake_loss=1.326, generator_loss=28.85, generator_mel_loss=18.31, generator_kl_loss=1.237, generator_dur_loss=1.801, generator_adv_loss=1.979, generator_feat_match_loss=5.527, over 74.00 samples.], tot_loss[discriminator_loss=2.695, discriminator_real_loss=1.363, discriminator_fake_loss=1.332, generator_loss=28.65, generator_mel_loss=17.97, generator_kl_loss=1.411, generator_dur_loss=1.759, generator_adv_loss=1.97, generator_feat_match_loss=5.538, over 5927.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 19:05:20,017 INFO [train.py:919] (2/6) Start epoch 652
2024-03-14 19:06:57,740 INFO [train.py:527] (2/6) Epoch 652, batch 26, global_batch_idx: 80750, batch size: 66, loss[discriminator_loss=2.633, discriminator_real_loss=1.332, discriminator_fake_loss=1.301, generator_loss=30.23, generator_mel_loss=18.12, generator_kl_loss=1.631, generator_dur_loss=1.777, generator_adv_loss=2.043, generator_feat_match_loss=6.658, over 66.00 samples.], tot_loss[discriminator_loss=2.68, discriminator_real_loss=1.34, discriminator_fake_loss=1.34, generator_loss=28.67, generator_mel_loss=17.97, generator_kl_loss=1.44, generator_dur_loss=1.755, generator_adv_loss=1.966, generator_feat_match_loss=5.541, over 1571.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 19:09:15,662 INFO [train.py:527] (2/6) Epoch 652, batch 76, global_batch_idx: 80800, batch size: 52, loss[discriminator_loss=2.736, discriminator_real_loss=1.477, discriminator_fake_loss=1.259, generator_loss=27.74, generator_mel_loss=17.85, generator_kl_loss=1.396, generator_dur_loss=1.734, generator_adv_loss=1.897, generator_feat_match_loss=4.867, over 52.00 samples.], tot_loss[discriminator_loss=2.695, discriminator_real_loss=1.357, discriminator_fake_loss=1.338, generator_loss=28.56, generator_mel_loss=17.96, generator_kl_loss=1.411, generator_dur_loss=1.759, generator_adv_loss=1.967, generator_feat_match_loss=5.466, over 4431.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 19:09:15,663 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 19:09:24,373 INFO [train.py:591] (2/6) Epoch 652, validation: discriminator_loss=2.745, discriminator_real_loss=1.351, discriminator_fake_loss=1.393, generator_loss=27.25, generator_mel_loss=17.96, generator_kl_loss=1.27, generator_dur_loss=1.824, generator_adv_loss=1.842, generator_feat_match_loss=4.36, over 100.00 samples.
2024-03-14 19:09:24,374 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 19:11:35,719 INFO [train.py:919] (2/6) Start epoch 653
2024-03-14 19:12:05,007 INFO [train.py:527] (2/6) Epoch 653, batch 2, global_batch_idx: 80850, batch size: 96, loss[discriminator_loss=2.684, discriminator_real_loss=1.307, discriminator_fake_loss=1.377, generator_loss=28.6, generator_mel_loss=17.86, generator_kl_loss=1.395, generator_dur_loss=1.812, generator_adv_loss=2.014, generator_feat_match_loss=5.521, over 96.00 samples.], tot_loss[discriminator_loss=2.681, discriminator_real_loss=1.314, discriminator_fake_loss=1.367, generator_loss=28.79, generator_mel_loss=17.98, generator_kl_loss=1.424, generator_dur_loss=1.803, generator_adv_loss=1.996, generator_feat_match_loss=5.588, over 174.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 19:14:23,275 INFO [train.py:527] (2/6) Epoch 653, batch 52, global_batch_idx: 80900, batch size: 52, loss[discriminator_loss=2.643, discriminator_real_loss=1.272, discriminator_fake_loss=1.371, generator_loss=29.17, generator_mel_loss=18.22, generator_kl_loss=1.554, generator_dur_loss=1.643, generator_adv_loss=1.946, generator_feat_match_loss=5.811, over 52.00 samples.], tot_loss[discriminator_loss=2.698, discriminator_real_loss=1.356, discriminator_fake_loss=1.342, generator_loss=28.59, generator_mel_loss=17.92, generator_kl_loss=1.411, generator_dur_loss=1.765, generator_adv_loss=1.975, generator_feat_match_loss=5.513, over 3185.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 19:16:43,846 INFO [train.py:527] (2/6) Epoch 653, batch 102, global_batch_idx: 80950, batch size: 96, loss[discriminator_loss=2.656, discriminator_real_loss=1.326, discriminator_fake_loss=1.33, generator_loss=28.04, generator_mel_loss=17.42, generator_kl_loss=1.218, generator_dur_loss=1.845, generator_adv_loss=2.174, generator_feat_match_loss=5.382, over 96.00 samples.], tot_loss[discriminator_loss=2.692, discriminator_real_loss=1.357, discriminator_fake_loss=1.335, generator_loss=28.64, generator_mel_loss=17.92, generator_kl_loss=1.416, generator_dur_loss=1.76, generator_adv_loss=1.985, generator_feat_match_loss=5.562, over 6128.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 19:17:43,553 INFO [train.py:919] (2/6) Start epoch 654
2024-03-14 19:19:27,277 INFO [train.py:527] (2/6) Epoch 654, batch 28, global_batch_idx: 81000, batch size: 77, loss[discriminator_loss=2.661, discriminator_real_loss=1.291, discriminator_fake_loss=1.37, generator_loss=29.09, generator_mel_loss=18.08, generator_kl_loss=1.413, generator_dur_loss=1.815, generator_adv_loss=1.98, generator_feat_match_loss=5.805, over 77.00 samples.], tot_loss[discriminator_loss=2.701, discriminator_real_loss=1.361, discriminator_fake_loss=1.34, generator_loss=28.53, generator_mel_loss=17.95, generator_kl_loss=1.421, generator_dur_loss=1.758, generator_adv_loss=1.961, generator_feat_match_loss=5.445, over 1828.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 19:19:27,278 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 19:19:35,258 INFO [train.py:591] (2/6) Epoch 654, validation: discriminator_loss=2.727, discriminator_real_loss=1.422, discriminator_fake_loss=1.305, generator_loss=28.25, generator_mel_loss=18.52, generator_kl_loss=1.227, generator_dur_loss=1.821, generator_adv_loss=1.954, generator_feat_match_loss=4.725, over 100.00 samples.
2024-03-14 19:19:35,259 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 19:21:51,315 INFO [train.py:527] (2/6) Epoch 654, batch 78, global_batch_idx: 81050, batch size: 25, loss[discriminator_loss=2.747, discriminator_real_loss=1.425, discriminator_fake_loss=1.322, generator_loss=28.61, generator_mel_loss=17.91, generator_kl_loss=1.657, generator_dur_loss=1.549, generator_adv_loss=1.914, generator_feat_match_loss=5.58, over 25.00 samples.], tot_loss[discriminator_loss=2.694, discriminator_real_loss=1.36, discriminator_fake_loss=1.333, generator_loss=28.58, generator_mel_loss=17.93, generator_kl_loss=1.436, generator_dur_loss=1.744, generator_adv_loss=1.975, generator_feat_match_loss=5.489, over 4551.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 19:24:00,563 INFO [train.py:919] (2/6) Start epoch 655
2024-03-14 19:24:35,429 INFO [train.py:527] (2/6) Epoch 655, batch 4, global_batch_idx: 81100, batch size: 68, loss[discriminator_loss=2.775, discriminator_real_loss=1.287, discriminator_fake_loss=1.487, generator_loss=29.04, generator_mel_loss=18.05, generator_kl_loss=1.434, generator_dur_loss=1.792, generator_adv_loss=2.083, generator_feat_match_loss=5.679, over 68.00 samples.], tot_loss[discriminator_loss=2.711, discriminator_real_loss=1.38, discriminator_fake_loss=1.331, generator_loss=28.64, generator_mel_loss=17.89, generator_kl_loss=1.365, generator_dur_loss=1.769, generator_adv_loss=2.05, generator_feat_match_loss=5.562, over 335.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 19:26:53,586 INFO [train.py:527] (2/6) Epoch 655, batch 54, global_batch_idx: 81150, batch size: 39, loss[discriminator_loss=2.665, discriminator_real_loss=1.316, discriminator_fake_loss=1.349, generator_loss=29.01, generator_mel_loss=17.94, generator_kl_loss=1.53, generator_dur_loss=1.674, generator_adv_loss=1.958, generator_feat_match_loss=5.909, over 39.00 samples.], tot_loss[discriminator_loss=2.68, discriminator_real_loss=1.351, discriminator_fake_loss=1.329, generator_loss=28.73, generator_mel_loss=17.96, generator_kl_loss=1.429, generator_dur_loss=1.752, generator_adv_loss=2.02, generator_feat_match_loss=5.567, over 3168.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 19:29:13,882 INFO [train.py:527] (2/6) Epoch 655, batch 104, global_batch_idx: 81200, batch size: 31, loss[discriminator_loss=2.701, discriminator_real_loss=1.371, discriminator_fake_loss=1.33, generator_loss=29.6, generator_mel_loss=17.87, generator_kl_loss=1.557, generator_dur_loss=1.562, generator_adv_loss=2.082, generator_feat_match_loss=6.53, over 31.00 samples.], tot_loss[discriminator_loss=2.689, discriminator_real_loss=1.358, discriminator_fake_loss=1.331, generator_loss=28.72, generator_mel_loss=17.98, generator_kl_loss=1.43, generator_dur_loss=1.743, generator_adv_loss=2.007, generator_feat_match_loss=5.564, over 5875.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 19:29:13,883 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 19:29:22,651 INFO [train.py:591] (2/6) Epoch 655, validation: discriminator_loss=2.713, discriminator_real_loss=1.431, discriminator_fake_loss=1.283, generator_loss=26.94, generator_mel_loss=18.27, generator_kl_loss=1.221, generator_dur_loss=1.801, generator_adv_loss=1.897, generator_feat_match_loss=3.747, over 100.00 samples.
2024-03-14 19:29:22,652 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 19:30:14,061 INFO [train.py:919] (2/6) Start epoch 656
2024-03-14 19:32:03,258 INFO [train.py:527] (2/6) Epoch 656, batch 30, global_batch_idx: 81250, batch size: 62, loss[discriminator_loss=2.694, discriminator_real_loss=1.394, discriminator_fake_loss=1.3, generator_loss=28.44, generator_mel_loss=17.75, generator_kl_loss=1.47, generator_dur_loss=1.666, generator_adv_loss=1.931, generator_feat_match_loss=5.628, over 62.00 samples.], tot_loss[discriminator_loss=2.695, discriminator_real_loss=1.365, discriminator_fake_loss=1.331, generator_loss=28.37, generator_mel_loss=17.79, generator_kl_loss=1.357, generator_dur_loss=1.762, generator_adv_loss=1.974, generator_feat_match_loss=5.48, over 1918.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 19:34:21,013 INFO [train.py:527] (2/6) Epoch 656, batch 80, global_batch_idx: 81300, batch size: 55, loss[discriminator_loss=2.703, discriminator_real_loss=1.371, discriminator_fake_loss=1.332, generator_loss=28.51, generator_mel_loss=17.77, generator_kl_loss=1.531, generator_dur_loss=1.657, generator_adv_loss=2.102, generator_feat_match_loss=5.447, over 55.00 samples.], tot_loss[discriminator_loss=2.691, discriminator_real_loss=1.362, discriminator_fake_loss=1.329, generator_loss=28.53, generator_mel_loss=17.85, generator_kl_loss=1.39, generator_dur_loss=1.759, generator_adv_loss=1.989, generator_feat_match_loss=5.545, over 4808.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 19:36:16,589 INFO [train.py:919] (2/6) Start epoch 657
2024-03-14 19:36:56,976 INFO [train.py:527] (2/6) Epoch 657, batch 6, global_batch_idx: 81350, batch size: 39, loss[discriminator_loss=2.704, discriminator_real_loss=1.32, discriminator_fake_loss=1.384, generator_loss=29.37, generator_mel_loss=18.27, generator_kl_loss=1.404, generator_dur_loss=1.638, generator_adv_loss=1.915, generator_feat_match_loss=6.145, over 39.00 samples.], tot_loss[discriminator_loss=2.687, discriminator_real_loss=1.37, discriminator_fake_loss=1.317, generator_loss=28.75, generator_mel_loss=18.18, generator_kl_loss=1.449, generator_dur_loss=1.749, generator_adv_loss=1.936, generator_feat_match_loss=5.436, over 370.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 19:39:13,451 INFO [train.py:527] (2/6) Epoch 657, batch 56, global_batch_idx: 81400, batch size: 44, loss[discriminator_loss=2.715, discriminator_real_loss=1.289, discriminator_fake_loss=1.426, generator_loss=28.8, generator_mel_loss=18.17, generator_kl_loss=1.558, generator_dur_loss=1.762, generator_adv_loss=2.053, generator_feat_match_loss=5.261, over 44.00 samples.], tot_loss[discriminator_loss=2.681, discriminator_real_loss=1.347, discriminator_fake_loss=1.334, generator_loss=28.76, generator_mel_loss=18, generator_kl_loss=1.42, generator_dur_loss=1.752, generator_adv_loss=1.972, generator_feat_match_loss=5.616, over 3203.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 19:39:13,453 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 19:39:21,547 INFO [train.py:591] (2/6) Epoch 657, validation: discriminator_loss=2.725, discriminator_real_loss=1.434, discriminator_fake_loss=1.291, generator_loss=28.32, generator_mel_loss=18.37, generator_kl_loss=1.234, generator_dur_loss=1.811, generator_adv_loss=1.975, generator_feat_match_loss=4.928, over 100.00 samples.
2024-03-14 19:39:21,548 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 19:41:39,011 INFO [train.py:527] (2/6) Epoch 657, batch 106, global_batch_idx: 81450, batch size: 61, loss[discriminator_loss=2.688, discriminator_real_loss=1.359, discriminator_fake_loss=1.329, generator_loss=29.15, generator_mel_loss=18.18, generator_kl_loss=1.484, generator_dur_loss=1.757, generator_adv_loss=2.007, generator_feat_match_loss=5.719, over 61.00 samples.], tot_loss[discriminator_loss=2.688, discriminator_real_loss=1.355, discriminator_fake_loss=1.334, generator_loss=28.69, generator_mel_loss=17.98, generator_kl_loss=1.414, generator_dur_loss=1.754, generator_adv_loss=1.974, generator_feat_match_loss=5.572, over 6066.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 19:42:30,122 INFO [train.py:919] (2/6) Start epoch 658
2024-03-14 19:44:21,205 INFO [train.py:527] (2/6) Epoch 658, batch 32, global_batch_idx: 81500, batch size: 66, loss[discriminator_loss=2.675, discriminator_real_loss=1.39, discriminator_fake_loss=1.285, generator_loss=28.47, generator_mel_loss=18.02, generator_kl_loss=1.545, generator_dur_loss=1.783, generator_adv_loss=2.001, generator_feat_match_loss=5.126, over 66.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.361, discriminator_fake_loss=1.323, generator_loss=28.64, generator_mel_loss=17.88, generator_kl_loss=1.416, generator_dur_loss=1.752, generator_adv_loss=1.988, generator_feat_match_loss=5.61, over 1910.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 19:46:41,894 INFO [train.py:527] (2/6) Epoch 658, batch 82, global_batch_idx: 81550, batch size: 88, loss[discriminator_loss=2.746, discriminator_real_loss=1.434, discriminator_fake_loss=1.312, generator_loss=28.25, generator_mel_loss=17.97, generator_kl_loss=1.23, generator_dur_loss=1.812, generator_adv_loss=2.084, generator_feat_match_loss=5.153, over 88.00 samples.], tot_loss[discriminator_loss=2.696, discriminator_real_loss=1.36, discriminator_fake_loss=1.336, generator_loss=28.77, generator_mel_loss=17.98, generator_kl_loss=1.424, generator_dur_loss=1.747, generator_adv_loss=1.991, generator_feat_match_loss=5.629, over 4719.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 19:48:38,043 INFO [train.py:919] (2/6) Start epoch 659
2024-03-14 19:49:23,442 INFO [train.py:527] (2/6) Epoch 659, batch 8, global_batch_idx: 81600, batch size: 42, loss[discriminator_loss=2.74, discriminator_real_loss=1.307, discriminator_fake_loss=1.433, generator_loss=29.78, generator_mel_loss=18.7, generator_kl_loss=1.538, generator_dur_loss=1.693, generator_adv_loss=1.965, generator_feat_match_loss=5.881, over 42.00 samples.], tot_loss[discriminator_loss=2.669, discriminator_real_loss=1.342, discriminator_fake_loss=1.328, generator_loss=28.74, generator_mel_loss=18, generator_kl_loss=1.402, generator_dur_loss=1.746, generator_adv_loss=1.976, generator_feat_match_loss=5.618, over 493.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 19:49:23,445 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 19:49:31,216 INFO [train.py:591] (2/6) Epoch 659, validation: discriminator_loss=2.73, discriminator_real_loss=1.438, discriminator_fake_loss=1.292, generator_loss=27.54, generator_mel_loss=17.99, generator_kl_loss=1.298, generator_dur_loss=1.818, generator_adv_loss=1.966, generator_feat_match_loss=4.469, over 100.00 samples.
2024-03-14 19:49:31,237 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 19:51:49,927 INFO [train.py:527] (2/6) Epoch 659, batch 58, global_batch_idx: 81650, batch size: 52, loss[discriminator_loss=2.683, discriminator_real_loss=1.428, discriminator_fake_loss=1.255, generator_loss=28.69, generator_mel_loss=18.03, generator_kl_loss=1.433, generator_dur_loss=1.712, generator_adv_loss=1.854, generator_feat_match_loss=5.666, over 52.00 samples.], tot_loss[discriminator_loss=2.687, discriminator_real_loss=1.358, discriminator_fake_loss=1.329, generator_loss=28.61, generator_mel_loss=17.96, generator_kl_loss=1.384, generator_dur_loss=1.748, generator_adv_loss=1.974, generator_feat_match_loss=5.543, over 3317.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 19:54:08,796 INFO [train.py:527] (2/6) Epoch 659, batch 108, global_batch_idx: 81700, batch size: 25, loss[discriminator_loss=2.631, discriminator_real_loss=1.293, discriminator_fake_loss=1.338, generator_loss=30.21, generator_mel_loss=18.76, generator_kl_loss=1.717, generator_dur_loss=1.598, generator_adv_loss=2.037, generator_feat_match_loss=6.096, over 25.00 samples.], tot_loss[discriminator_loss=2.689, discriminator_real_loss=1.359, discriminator_fake_loss=1.33, generator_loss=28.56, generator_mel_loss=17.92, generator_kl_loss=1.391, generator_dur_loss=1.756, generator_adv_loss=1.979, generator_feat_match_loss=5.521, over 6264.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 19:54:51,559 INFO [train.py:919] (2/6) Start epoch 660
2024-03-14 19:56:52,237 INFO [train.py:527] (2/6) Epoch 660, batch 34, global_batch_idx: 81750, batch size: 70, loss[discriminator_loss=2.718, discriminator_real_loss=1.384, discriminator_fake_loss=1.334, generator_loss=28.59, generator_mel_loss=17.92, generator_kl_loss=1.298, generator_dur_loss=1.75, generator_adv_loss=1.957, generator_feat_match_loss=5.663, over 70.00 samples.], tot_loss[discriminator_loss=2.707, discriminator_real_loss=1.371, discriminator_fake_loss=1.336, generator_loss=28.47, generator_mel_loss=17.86, generator_kl_loss=1.376, generator_dur_loss=1.775, generator_adv_loss=1.977, generator_feat_match_loss=5.474, over 2221.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 19:59:10,383 INFO [train.py:527] (2/6) Epoch 660, batch 84, global_batch_idx: 81800, batch size: 52, loss[discriminator_loss=2.778, discriminator_real_loss=1.437, discriminator_fake_loss=1.341, generator_loss=27.45, generator_mel_loss=17.52, generator_kl_loss=1.487, generator_dur_loss=1.676, generator_adv_loss=2.007, generator_feat_match_loss=4.767, over 52.00 samples.], tot_loss[discriminator_loss=2.712, discriminator_real_loss=1.374, discriminator_fake_loss=1.338, generator_loss=28.47, generator_mel_loss=17.9, generator_kl_loss=1.382, generator_dur_loss=1.762, generator_adv_loss=1.975, generator_feat_match_loss=5.448, over 5097.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 19:59:10,385 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 19:59:19,067 INFO [train.py:591] (2/6) Epoch 660, validation: discriminator_loss=2.743, discriminator_real_loss=1.505, discriminator_fake_loss=1.239, generator_loss=27.23, generator_mel_loss=17.83, generator_kl_loss=1.269, generator_dur_loss=1.817, generator_adv_loss=1.957, generator_feat_match_loss=4.361, over 100.00 samples.
2024-03-14 19:59:19,068 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 20:01:08,062 INFO [train.py:919] (2/6) Start epoch 661
2024-03-14 20:02:02,452 INFO [train.py:527] (2/6) Epoch 661, batch 10, global_batch_idx: 81850, batch size: 52, loss[discriminator_loss=2.673, discriminator_real_loss=1.294, discriminator_fake_loss=1.379, generator_loss=28.5, generator_mel_loss=17.71, generator_kl_loss=1.587, generator_dur_loss=1.69, generator_adv_loss=1.998, generator_feat_match_loss=5.514, over 52.00 samples.], tot_loss[discriminator_loss=2.72, discriminator_real_loss=1.364, discriminator_fake_loss=1.356, generator_loss=28.7, generator_mel_loss=17.94, generator_kl_loss=1.46, generator_dur_loss=1.74, generator_adv_loss=1.965, generator_feat_match_loss=5.594, over 587.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 20:04:22,924 INFO [train.py:527] (2/6) Epoch 661, batch 60, global_batch_idx: 81900, batch size: 88, loss[discriminator_loss=2.732, discriminator_real_loss=1.345, discriminator_fake_loss=1.387, generator_loss=29.14, generator_mel_loss=18.29, generator_kl_loss=1.371, generator_dur_loss=1.775, generator_adv_loss=1.987, generator_feat_match_loss=5.714, over 88.00 samples.], tot_loss[discriminator_loss=2.7, discriminator_real_loss=1.367, discriminator_fake_loss=1.333, generator_loss=28.71, generator_mel_loss=17.95, generator_kl_loss=1.443, generator_dur_loss=1.741, generator_adv_loss=1.991, generator_feat_match_loss=5.583, over 3399.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 20:06:41,366 INFO [train.py:527] (2/6) Epoch 661, batch 110, global_batch_idx: 81950, batch size: 74, loss[discriminator_loss=2.641, discriminator_real_loss=1.288, discriminator_fake_loss=1.353, generator_loss=28.66, generator_mel_loss=17.85, generator_kl_loss=1.207, generator_dur_loss=1.738, generator_adv_loss=1.996, generator_feat_match_loss=5.866, over 74.00 samples.], tot_loss[discriminator_loss=2.697, discriminator_real_loss=1.368, discriminator_fake_loss=1.329, generator_loss=28.62, generator_mel_loss=17.91, generator_kl_loss=1.42, generator_dur_loss=1.739, generator_adv_loss=1.984, generator_feat_match_loss=5.565, over 6423.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 20:07:18,098 INFO [train.py:919] (2/6) Start epoch 662
2024-03-14 20:09:23,476 INFO [train.py:527] (2/6) Epoch 662, batch 36, global_batch_idx: 82000, batch size: 52, loss[discriminator_loss=2.607, discriminator_real_loss=1.349, discriminator_fake_loss=1.258, generator_loss=28.41, generator_mel_loss=18, generator_kl_loss=1.321, generator_dur_loss=1.716, generator_adv_loss=1.994, generator_feat_match_loss=5.386, over 52.00 samples.], tot_loss[discriminator_loss=2.688, discriminator_real_loss=1.364, discriminator_fake_loss=1.323, generator_loss=28.78, generator_mel_loss=17.94, generator_kl_loss=1.41, generator_dur_loss=1.742, generator_adv_loss=2.021, generator_feat_match_loss=5.669, over 2265.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 20:09:23,478 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 20:09:31,285 INFO [train.py:591] (2/6) Epoch 662, validation: discriminator_loss=2.753, discriminator_real_loss=1.382, discriminator_fake_loss=1.371, generator_loss=27.58, generator_mel_loss=18.17, generator_kl_loss=1.241, generator_dur_loss=1.811, generator_adv_loss=1.83, generator_feat_match_loss=4.526, over 100.00 samples.
2024-03-14 20:09:31,285 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 20:11:49,890 INFO [train.py:527] (2/6) Epoch 662, batch 86, global_batch_idx: 82050, batch size: 83, loss[discriminator_loss=2.723, discriminator_real_loss=1.334, discriminator_fake_loss=1.39, generator_loss=28.86, generator_mel_loss=17.75, generator_kl_loss=1.42, generator_dur_loss=1.862, generator_adv_loss=1.993, generator_feat_match_loss=5.83, over 83.00 samples.], tot_loss[discriminator_loss=2.695, discriminator_real_loss=1.364, discriminator_fake_loss=1.331, generator_loss=28.65, generator_mel_loss=17.91, generator_kl_loss=1.415, generator_dur_loss=1.749, generator_adv_loss=2, generator_feat_match_loss=5.57, over 5048.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 20:13:30,615 INFO [train.py:919] (2/6) Start epoch 663
2024-03-14 20:14:30,132 INFO [train.py:527] (2/6) Epoch 663, batch 12, global_batch_idx: 82100, batch size: 74, loss[discriminator_loss=2.744, discriminator_real_loss=1.325, discriminator_fake_loss=1.42, generator_loss=28.87, generator_mel_loss=18.07, generator_kl_loss=1.379, generator_dur_loss=1.784, generator_adv_loss=1.963, generator_feat_match_loss=5.677, over 74.00 samples.], tot_loss[discriminator_loss=2.711, discriminator_real_loss=1.379, discriminator_fake_loss=1.332, generator_loss=28.32, generator_mel_loss=17.88, generator_kl_loss=1.379, generator_dur_loss=1.801, generator_adv_loss=1.962, generator_feat_match_loss=5.296, over 896.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 20:16:47,567 INFO [train.py:527] (2/6) Epoch 663, batch 62, global_batch_idx: 82150, batch size: 60, loss[discriminator_loss=2.739, discriminator_real_loss=1.357, discriminator_fake_loss=1.383, generator_loss=28.13, generator_mel_loss=17.68, generator_kl_loss=1.261, generator_dur_loss=1.743, generator_adv_loss=1.944, generator_feat_match_loss=5.506, over 60.00 samples.], tot_loss[discriminator_loss=2.703, discriminator_real_loss=1.369, discriminator_fake_loss=1.334, generator_loss=28.52, generator_mel_loss=17.96, generator_kl_loss=1.416, generator_dur_loss=1.76, generator_adv_loss=1.961, generator_feat_match_loss=5.42, over 3874.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 20:19:06,832 INFO [train.py:527] (2/6) Epoch 663, batch 112, global_batch_idx: 82200, batch size: 45, loss[discriminator_loss=2.658, discriminator_real_loss=1.431, discriminator_fake_loss=1.227, generator_loss=28.86, generator_mel_loss=17.76, generator_kl_loss=1.619, generator_dur_loss=1.681, generator_adv_loss=2.043, generator_feat_match_loss=5.758, over 45.00 samples.], tot_loss[discriminator_loss=2.694, discriminator_real_loss=1.364, discriminator_fake_loss=1.33, generator_loss=28.53, generator_mel_loss=17.93, generator_kl_loss=1.415, generator_dur_loss=1.757, generator_adv_loss=1.977, generator_feat_match_loss=5.459, over 6814.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 20:19:06,834 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 20:19:15,747 INFO [train.py:591] (2/6) Epoch 663, validation: discriminator_loss=2.75, discriminator_real_loss=1.405, discriminator_fake_loss=1.344, generator_loss=27.35, generator_mel_loss=18.29, generator_kl_loss=1.192, generator_dur_loss=1.804, generator_adv_loss=1.894, generator_feat_match_loss=4.17, over 100.00 samples.
2024-03-14 20:19:15,748 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 20:19:44,427 INFO [train.py:919] (2/6) Start epoch 664
2024-03-14 20:21:53,640 INFO [train.py:527] (2/6) Epoch 664, batch 38, global_batch_idx: 82250, batch size: 72, loss[discriminator_loss=2.685, discriminator_real_loss=1.332, discriminator_fake_loss=1.353, generator_loss=28.43, generator_mel_loss=17.47, generator_kl_loss=1.545, generator_dur_loss=1.809, generator_adv_loss=1.994, generator_feat_match_loss=5.614, over 72.00 samples.], tot_loss[discriminator_loss=2.699, discriminator_real_loss=1.358, discriminator_fake_loss=1.34, generator_loss=28.48, generator_mel_loss=17.89, generator_kl_loss=1.428, generator_dur_loss=1.751, generator_adv_loss=1.971, generator_feat_match_loss=5.448, over 2233.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 20:24:12,467 INFO [train.py:527] (2/6) Epoch 664, batch 88, global_batch_idx: 82300, batch size: 88, loss[discriminator_loss=2.614, discriminator_real_loss=1.305, discriminator_fake_loss=1.309, generator_loss=29.49, generator_mel_loss=18.06, generator_kl_loss=1.26, generator_dur_loss=1.933, generator_adv_loss=1.95, generator_feat_match_loss=6.296, over 88.00 samples.], tot_loss[discriminator_loss=2.689, discriminator_real_loss=1.362, discriminator_fake_loss=1.328, generator_loss=28.61, generator_mel_loss=17.92, generator_kl_loss=1.421, generator_dur_loss=1.763, generator_adv_loss=1.975, generator_feat_match_loss=5.532, over 5207.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 20:25:51,669 INFO [train.py:919] (2/6) Start epoch 665
2024-03-14 20:26:54,155 INFO [train.py:527] (2/6) Epoch 665, batch 14, global_batch_idx: 82350, batch size: 74, loss[discriminator_loss=2.725, discriminator_real_loss=1.337, discriminator_fake_loss=1.388, generator_loss=28.7, generator_mel_loss=18, generator_kl_loss=1.29, generator_dur_loss=1.782, generator_adv_loss=2.265, generator_feat_match_loss=5.363, over 74.00 samples.], tot_loss[discriminator_loss=2.691, discriminator_real_loss=1.35, discriminator_fake_loss=1.341, generator_loss=28.74, generator_mel_loss=18.01, generator_kl_loss=1.451, generator_dur_loss=1.735, generator_adv_loss=2.002, generator_feat_match_loss=5.542, over 850.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 20:29:13,294 INFO [train.py:527] (2/6) Epoch 665, batch 64, global_batch_idx: 82400, batch size: 72, loss[discriminator_loss=2.703, discriminator_real_loss=1.442, discriminator_fake_loss=1.261, generator_loss=28.23, generator_mel_loss=17.49, generator_kl_loss=1.354, generator_dur_loss=1.812, generator_adv_loss=1.906, generator_feat_match_loss=5.663, over 72.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.358, discriminator_fake_loss=1.327, generator_loss=28.7, generator_mel_loss=17.96, generator_kl_loss=1.418, generator_dur_loss=1.759, generator_adv_loss=1.988, generator_feat_match_loss=5.581, over 3854.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 20:29:13,296 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 20:29:21,241 INFO [train.py:591] (2/6) Epoch 665, validation: discriminator_loss=2.712, discriminator_real_loss=1.331, discriminator_fake_loss=1.381, generator_loss=27.3, generator_mel_loss=18.25, generator_kl_loss=1.151, generator_dur_loss=1.805, generator_adv_loss=1.796, generator_feat_match_loss=4.296, over 100.00 samples.
2024-03-14 20:29:21,242 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 20:31:40,213 INFO [train.py:527] (2/6) Epoch 665, batch 114, global_batch_idx: 82450, batch size: 58, loss[discriminator_loss=2.676, discriminator_real_loss=1.375, discriminator_fake_loss=1.302, generator_loss=28.9, generator_mel_loss=17.82, generator_kl_loss=1.62, generator_dur_loss=1.729, generator_adv_loss=2.005, generator_feat_match_loss=5.728, over 58.00 samples.], tot_loss[discriminator_loss=2.691, discriminator_real_loss=1.359, discriminator_fake_loss=1.332, generator_loss=28.67, generator_mel_loss=17.94, generator_kl_loss=1.42, generator_dur_loss=1.755, generator_adv_loss=1.982, generator_feat_match_loss=5.576, over 6791.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 20:32:03,483 INFO [train.py:919] (2/6) Start epoch 666
2024-03-14 20:34:16,502 INFO [train.py:527] (2/6) Epoch 666, batch 40, global_batch_idx: 82500, batch size: 36, loss[discriminator_loss=2.666, discriminator_real_loss=1.384, discriminator_fake_loss=1.282, generator_loss=28.87, generator_mel_loss=18.02, generator_kl_loss=1.495, generator_dur_loss=1.705, generator_adv_loss=1.937, generator_feat_match_loss=5.718, over 36.00 samples.], tot_loss[discriminator_loss=2.699, discriminator_real_loss=1.359, discriminator_fake_loss=1.34, generator_loss=28.56, generator_mel_loss=17.93, generator_kl_loss=1.426, generator_dur_loss=1.746, generator_adv_loss=1.96, generator_feat_match_loss=5.496, over 2277.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 20:36:37,946 INFO [train.py:527] (2/6) Epoch 666, batch 90, global_batch_idx: 82550, batch size: 77, loss[discriminator_loss=2.638, discriminator_real_loss=1.326, discriminator_fake_loss=1.312, generator_loss=29.52, generator_mel_loss=18.32, generator_kl_loss=1.229, generator_dur_loss=1.825, generator_adv_loss=1.989, generator_feat_match_loss=6.158, over 77.00 samples.], tot_loss[discriminator_loss=2.695, discriminator_real_loss=1.36, discriminator_fake_loss=1.335, generator_loss=28.65, generator_mel_loss=17.92, generator_kl_loss=1.412, generator_dur_loss=1.757, generator_adv_loss=1.973, generator_feat_match_loss=5.581, over 5193.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 20:38:13,415 INFO [train.py:919] (2/6) Start epoch 667
2024-03-14 20:39:20,982 INFO [train.py:527] (2/6) Epoch 667, batch 16, global_batch_idx: 82600, batch size: 45, loss[discriminator_loss=2.628, discriminator_real_loss=1.29, discriminator_fake_loss=1.338, generator_loss=30.62, generator_mel_loss=18.26, generator_kl_loss=1.669, generator_dur_loss=1.718, generator_adv_loss=2.178, generator_feat_match_loss=6.792, over 45.00 samples.], tot_loss[discriminator_loss=2.688, discriminator_real_loss=1.37, discriminator_fake_loss=1.318, generator_loss=28.85, generator_mel_loss=18.01, generator_kl_loss=1.424, generator_dur_loss=1.742, generator_adv_loss=2, generator_feat_match_loss=5.674, over 901.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 20:39:20,983 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 20:39:28,899 INFO [train.py:591] (2/6) Epoch 667, validation: discriminator_loss=2.756, discriminator_real_loss=1.445, discriminator_fake_loss=1.311, generator_loss=27.3, generator_mel_loss=18.35, generator_kl_loss=1.207, generator_dur_loss=1.823, generator_adv_loss=1.978, generator_feat_match_loss=3.941, over 100.00 samples.
2024-03-14 20:39:28,900 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 20:41:49,076 INFO [train.py:527] (2/6) Epoch 667, batch 66, global_batch_idx: 82650, batch size: 96, loss[discriminator_loss=2.699, discriminator_real_loss=1.399, discriminator_fake_loss=1.3, generator_loss=27.84, generator_mel_loss=17.53, generator_kl_loss=1.215, generator_dur_loss=1.858, generator_adv_loss=1.902, generator_feat_match_loss=5.335, over 96.00 samples.], tot_loss[discriminator_loss=2.678, discriminator_real_loss=1.356, discriminator_fake_loss=1.322, generator_loss=28.76, generator_mel_loss=17.93, generator_kl_loss=1.436, generator_dur_loss=1.75, generator_adv_loss=1.99, generator_feat_match_loss=5.649, over 3722.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 20:44:05,831 INFO [train.py:527] (2/6) Epoch 667, batch 116, global_batch_idx: 82700, batch size: 70, loss[discriminator_loss=2.712, discriminator_real_loss=1.334, discriminator_fake_loss=1.378, generator_loss=29.58, generator_mel_loss=18.06, generator_kl_loss=1.245, generator_dur_loss=1.789, generator_adv_loss=2.216, generator_feat_match_loss=6.273, over 70.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.358, discriminator_fake_loss=1.327, generator_loss=28.83, generator_mel_loss=17.96, generator_kl_loss=1.438, generator_dur_loss=1.742, generator_adv_loss=2.015, generator_feat_match_loss=5.668, over 6479.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 20:44:27,607 INFO [train.py:919] (2/6) Start epoch 668
2024-03-14 20:46:49,160 INFO [train.py:527] (2/6) Epoch 668, batch 42, global_batch_idx: 82750, batch size: 31, loss[discriminator_loss=2.775, discriminator_real_loss=1.375, discriminator_fake_loss=1.4, generator_loss=27.02, generator_mel_loss=17.84, generator_kl_loss=1.585, generator_dur_loss=1.607, generator_adv_loss=1.87, generator_feat_match_loss=4.119, over 31.00 samples.], tot_loss[discriminator_loss=2.679, discriminator_real_loss=1.357, discriminator_fake_loss=1.321, generator_loss=28.65, generator_mel_loss=17.88, generator_kl_loss=1.393, generator_dur_loss=1.753, generator_adv_loss=1.983, generator_feat_match_loss=5.635, over 2336.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 20:49:06,887 INFO [train.py:527] (2/6) Epoch 668, batch 92, global_batch_idx: 82800, batch size: 68, loss[discriminator_loss=2.734, discriminator_real_loss=1.379, discriminator_fake_loss=1.354, generator_loss=28.24, generator_mel_loss=17.89, generator_kl_loss=1.346, generator_dur_loss=1.799, generator_adv_loss=1.89, generator_feat_match_loss=5.31, over 68.00 samples.], tot_loss[discriminator_loss=2.688, discriminator_real_loss=1.362, discriminator_fake_loss=1.326, generator_loss=28.71, generator_mel_loss=17.95, generator_kl_loss=1.427, generator_dur_loss=1.752, generator_adv_loss=1.974, generator_feat_match_loss=5.61, over 5080.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 20:49:06,889 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 20:49:15,926 INFO [train.py:591] (2/6) Epoch 668, validation: discriminator_loss=2.728, discriminator_real_loss=1.387, discriminator_fake_loss=1.341, generator_loss=27.17, generator_mel_loss=17.94, generator_kl_loss=1.286, generator_dur_loss=1.82, generator_adv_loss=1.855, generator_feat_match_loss=4.277, over 100.00 samples.
2024-03-14 20:49:15,927 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 20:50:40,313 INFO [train.py:919] (2/6) Start epoch 669
2024-03-14 20:51:52,990 INFO [train.py:527] (2/6) Epoch 669, batch 18, global_batch_idx: 82850, batch size: 55, loss[discriminator_loss=2.664, discriminator_real_loss=1.319, discriminator_fake_loss=1.345, generator_loss=29.47, generator_mel_loss=18.38, generator_kl_loss=1.329, generator_dur_loss=1.675, generator_adv_loss=2.146, generator_feat_match_loss=5.942, over 55.00 samples.], tot_loss[discriminator_loss=2.687, discriminator_real_loss=1.36, discriminator_fake_loss=1.328, generator_loss=28.94, generator_mel_loss=18.1, generator_kl_loss=1.413, generator_dur_loss=1.757, generator_adv_loss=1.994, generator_feat_match_loss=5.678, over 1107.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 20:54:14,662 INFO [train.py:527] (2/6) Epoch 669, batch 68, global_batch_idx: 82900, batch size: 80, loss[discriminator_loss=2.683, discriminator_real_loss=1.415, discriminator_fake_loss=1.267, generator_loss=27.81, generator_mel_loss=17.51, generator_kl_loss=1.468, generator_dur_loss=1.84, generator_adv_loss=1.855, generator_feat_match_loss=5.145, over 80.00 samples.], tot_loss[discriminator_loss=2.694, discriminator_real_loss=1.363, discriminator_fake_loss=1.331, generator_loss=28.71, generator_mel_loss=17.96, generator_kl_loss=1.418, generator_dur_loss=1.76, generator_adv_loss=1.979, generator_feat_match_loss=5.587, over 4070.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 20:56:30,678 INFO [train.py:527] (2/6) Epoch 669, batch 118, global_batch_idx: 82950, batch size: 61, loss[discriminator_loss=2.651, discriminator_real_loss=1.335, discriminator_fake_loss=1.316, generator_loss=29.41, generator_mel_loss=18.4, generator_kl_loss=1.344, generator_dur_loss=1.782, generator_adv_loss=1.981, generator_feat_match_loss=5.906, over 61.00 samples.], tot_loss[discriminator_loss=2.699, discriminator_real_loss=1.366, discriminator_fake_loss=1.333, generator_loss=28.7, generator_mel_loss=17.97, generator_kl_loss=1.426, generator_dur_loss=1.754, generator_adv_loss=1.981, generator_feat_match_loss=5.568, over 6769.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 20:56:45,039 INFO [train.py:919] (2/6) Start epoch 670
2024-03-14 20:59:08,305 INFO [train.py:527] (2/6) Epoch 670, batch 44, global_batch_idx: 83000, batch size: 70, loss[discriminator_loss=2.657, discriminator_real_loss=1.316, discriminator_fake_loss=1.341, generator_loss=28.38, generator_mel_loss=17.87, generator_kl_loss=1.308, generator_dur_loss=1.823, generator_adv_loss=1.944, generator_feat_match_loss=5.433, over 70.00 samples.], tot_loss[discriminator_loss=2.689, discriminator_real_loss=1.359, discriminator_fake_loss=1.33, generator_loss=28.69, generator_mel_loss=18.01, generator_kl_loss=1.425, generator_dur_loss=1.748, generator_adv_loss=1.985, generator_feat_match_loss=5.524, over 2483.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 20:59:08,307 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 20:59:16,319 INFO [train.py:591] (2/6) Epoch 670, validation: discriminator_loss=2.723, discriminator_real_loss=1.346, discriminator_fake_loss=1.377, generator_loss=27.62, generator_mel_loss=18.49, generator_kl_loss=1.238, generator_dur_loss=1.816, generator_adv_loss=1.838, generator_feat_match_loss=4.239, over 100.00 samples.
2024-03-14 20:59:16,320 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 21:01:37,663 INFO [train.py:527] (2/6) Epoch 670, batch 94, global_batch_idx: 83050, batch size: 59, loss[discriminator_loss=2.672, discriminator_real_loss=1.33, discriminator_fake_loss=1.342, generator_loss=29.67, generator_mel_loss=18.36, generator_kl_loss=1.562, generator_dur_loss=1.718, generator_adv_loss=2.099, generator_feat_match_loss=5.935, over 59.00 samples.], tot_loss[discriminator_loss=2.692, discriminator_real_loss=1.359, discriminator_fake_loss=1.333, generator_loss=28.66, generator_mel_loss=17.95, generator_kl_loss=1.4, generator_dur_loss=1.757, generator_adv_loss=1.995, generator_feat_match_loss=5.554, over 5444.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 21:02:57,032 INFO [train.py:919] (2/6) Start epoch 671
2024-03-14 21:04:15,697 INFO [train.py:527] (2/6) Epoch 671, batch 20, global_batch_idx: 83100, batch size: 62, loss[discriminator_loss=2.724, discriminator_real_loss=1.507, discriminator_fake_loss=1.217, generator_loss=28.17, generator_mel_loss=17.68, generator_kl_loss=1.355, generator_dur_loss=1.777, generator_adv_loss=1.902, generator_feat_match_loss=5.463, over 62.00 samples.], tot_loss[discriminator_loss=2.693, discriminator_real_loss=1.373, discriminator_fake_loss=1.319, generator_loss=28.72, generator_mel_loss=18.04, generator_kl_loss=1.46, generator_dur_loss=1.727, generator_adv_loss=1.973, generator_feat_match_loss=5.522, over 1020.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 21:06:31,269 INFO [train.py:527] (2/6) Epoch 671, batch 70, global_batch_idx: 83150, batch size: 47, loss[discriminator_loss=2.726, discriminator_real_loss=1.337, discriminator_fake_loss=1.389, generator_loss=28.35, generator_mel_loss=17.97, generator_kl_loss=1.471, generator_dur_loss=1.651, generator_adv_loss=2.03, generator_feat_match_loss=5.232, over 47.00 samples.], tot_loss[discriminator_loss=2.699, discriminator_real_loss=1.371, discriminator_fake_loss=1.328, generator_loss=28.55, generator_mel_loss=17.92, generator_kl_loss=1.431, generator_dur_loss=1.727, generator_adv_loss=1.987, generator_feat_match_loss=5.48, over 3785.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 21:08:49,696 INFO [train.py:527] (2/6) Epoch 671, batch 120, global_batch_idx: 83200, batch size: 72, loss[discriminator_loss=2.692, discriminator_real_loss=1.298, discriminator_fake_loss=1.394, generator_loss=28.87, generator_mel_loss=17.98, generator_kl_loss=1.315, generator_dur_loss=1.783, generator_adv_loss=2.063, generator_feat_match_loss=5.729, over 72.00 samples.], tot_loss[discriminator_loss=2.697, discriminator_real_loss=1.369, discriminator_fake_loss=1.328, generator_loss=28.59, generator_mel_loss=17.92, generator_kl_loss=1.434, generator_dur_loss=1.73, generator_adv_loss=1.982, generator_feat_match_loss=5.519, over 6554.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 21:08:49,699 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 21:08:58,668 INFO [train.py:591] (2/6) Epoch 671, validation: discriminator_loss=2.733, discriminator_real_loss=1.469, discriminator_fake_loss=1.264, generator_loss=28.24, generator_mel_loss=18.47, generator_kl_loss=1.303, generator_dur_loss=1.81, generator_adv_loss=1.97, generator_feat_match_loss=4.685, over 100.00 samples.
2024-03-14 21:08:58,669 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 21:09:09,514 INFO [train.py:919] (2/6) Start epoch 672
2024-03-14 21:11:38,112 INFO [train.py:527] (2/6) Epoch 672, batch 46, global_batch_idx: 83250, batch size: 50, loss[discriminator_loss=2.76, discriminator_real_loss=1.395, discriminator_fake_loss=1.365, generator_loss=28.35, generator_mel_loss=17.91, generator_kl_loss=1.321, generator_dur_loss=1.704, generator_adv_loss=1.978, generator_feat_match_loss=5.439, over 50.00 samples.], tot_loss[discriminator_loss=2.71, discriminator_real_loss=1.366, discriminator_fake_loss=1.344, generator_loss=28.73, generator_mel_loss=17.97, generator_kl_loss=1.423, generator_dur_loss=1.74, generator_adv_loss=1.97, generator_feat_match_loss=5.633, over 2695.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 21:13:55,393 INFO [train.py:527] (2/6) Epoch 672, batch 96, global_batch_idx: 83300, batch size: 58, loss[discriminator_loss=2.679, discriminator_real_loss=1.346, discriminator_fake_loss=1.332, generator_loss=29.06, generator_mel_loss=18.36, generator_kl_loss=1.605, generator_dur_loss=1.666, generator_adv_loss=1.893, generator_feat_match_loss=5.532, over 58.00 samples.], tot_loss[discriminator_loss=2.699, discriminator_real_loss=1.364, discriminator_fake_loss=1.335, generator_loss=28.71, generator_mel_loss=17.97, generator_kl_loss=1.419, generator_dur_loss=1.737, generator_adv_loss=1.989, generator_feat_match_loss=5.601, over 5464.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 21:15:13,720 INFO [train.py:919] (2/6) Start epoch 673
2024-03-14 21:16:38,361 INFO [train.py:527] (2/6) Epoch 673, batch 22, global_batch_idx: 83350, batch size: 31, loss[discriminator_loss=2.657, discriminator_real_loss=1.245, discriminator_fake_loss=1.412, generator_loss=29.16, generator_mel_loss=18.27, generator_kl_loss=1.541, generator_dur_loss=1.594, generator_adv_loss=1.887, generator_feat_match_loss=5.866, over 31.00 samples.], tot_loss[discriminator_loss=2.679, discriminator_real_loss=1.351, discriminator_fake_loss=1.328, generator_loss=28.94, generator_mel_loss=18.03, generator_kl_loss=1.445, generator_dur_loss=1.726, generator_adv_loss=2.026, generator_feat_match_loss=5.712, over 1188.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 21:18:57,246 INFO [train.py:527] (2/6) Epoch 673, batch 72, global_batch_idx: 83400, batch size: 45, loss[discriminator_loss=2.725, discriminator_real_loss=1.307, discriminator_fake_loss=1.418, generator_loss=29.24, generator_mel_loss=18.33, generator_kl_loss=1.54, generator_dur_loss=1.675, generator_adv_loss=2.116, generator_feat_match_loss=5.576, over 45.00 samples.], tot_loss[discriminator_loss=2.687, discriminator_real_loss=1.365, discriminator_fake_loss=1.322, generator_loss=28.75, generator_mel_loss=17.98, generator_kl_loss=1.442, generator_dur_loss=1.733, generator_adv_loss=1.997, generator_feat_match_loss=5.607, over 3905.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 21:18:57,247 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 21:19:06,066 INFO [train.py:591] (2/6) Epoch 673, validation: discriminator_loss=2.768, discriminator_real_loss=1.496, discriminator_fake_loss=1.272, generator_loss=27.4, generator_mel_loss=18.23, generator_kl_loss=1.259, generator_dur_loss=1.813, generator_adv_loss=1.969, generator_feat_match_loss=4.125, over 100.00 samples.
2024-03-14 21:19:06,067 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 21:21:22,893 INFO [train.py:527] (2/6) Epoch 673, batch 122, global_batch_idx: 83450, batch size: 16, loss[discriminator_loss=2.746, discriminator_real_loss=1.472, discriminator_fake_loss=1.274, generator_loss=29.43, generator_mel_loss=18.04, generator_kl_loss=1.933, generator_dur_loss=1.552, generator_adv_loss=1.936, generator_feat_match_loss=5.969, over 16.00 samples.], tot_loss[discriminator_loss=2.696, discriminator_real_loss=1.366, discriminator_fake_loss=1.33, generator_loss=28.73, generator_mel_loss=17.98, generator_kl_loss=1.421, generator_dur_loss=1.746, generator_adv_loss=1.985, generator_feat_match_loss=5.591, over 6816.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 21:21:28,244 INFO [train.py:919] (2/6) Start epoch 674
2024-03-14 21:24:02,590 INFO [train.py:527] (2/6) Epoch 674, batch 48, global_batch_idx: 83500, batch size: 55, loss[discriminator_loss=2.655, discriminator_real_loss=1.317, discriminator_fake_loss=1.338, generator_loss=28.99, generator_mel_loss=18.16, generator_kl_loss=1.279, generator_dur_loss=1.66, generator_adv_loss=1.933, generator_feat_match_loss=5.957, over 55.00 samples.], tot_loss[discriminator_loss=2.686, discriminator_real_loss=1.357, discriminator_fake_loss=1.329, generator_loss=28.72, generator_mel_loss=18.02, generator_kl_loss=1.455, generator_dur_loss=1.735, generator_adv_loss=1.974, generator_feat_match_loss=5.536, over 2584.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 21:26:21,361 INFO [train.py:527] (2/6) Epoch 674, batch 98, global_batch_idx: 83550, batch size: 53, loss[discriminator_loss=2.812, discriminator_real_loss=1.324, discriminator_fake_loss=1.488, generator_loss=29.34, generator_mel_loss=18.16, generator_kl_loss=1.49, generator_dur_loss=1.638, generator_adv_loss=1.94, generator_feat_match_loss=6.109, over 53.00 samples.], tot_loss[discriminator_loss=2.69, discriminator_real_loss=1.359, discriminator_fake_loss=1.331, generator_loss=28.69, generator_mel_loss=17.97, generator_kl_loss=1.441, generator_dur_loss=1.739, generator_adv_loss=1.977, generator_feat_match_loss=5.562, over 5377.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 21:27:34,723 INFO [train.py:919] (2/6) Start epoch 675
2024-03-14 21:29:06,030 INFO [train.py:527] (2/6) Epoch 675, batch 24, global_batch_idx: 83600, batch size: 83, loss[discriminator_loss=2.753, discriminator_real_loss=1.491, discriminator_fake_loss=1.262, generator_loss=27.3, generator_mel_loss=17.67, generator_kl_loss=1.326, generator_dur_loss=1.793, generator_adv_loss=1.876, generator_feat_match_loss=4.639, over 83.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.356, discriminator_fake_loss=1.329, generator_loss=28.6, generator_mel_loss=17.87, generator_kl_loss=1.443, generator_dur_loss=1.748, generator_adv_loss=1.969, generator_feat_match_loss=5.569, over 1479.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 21:29:06,032 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 21:29:14,044 INFO [train.py:591] (2/6) Epoch 675, validation: discriminator_loss=2.754, discriminator_real_loss=1.38, discriminator_fake_loss=1.374, generator_loss=26.77, generator_mel_loss=17.64, generator_kl_loss=1.234, generator_dur_loss=1.797, generator_adv_loss=1.825, generator_feat_match_loss=4.268, over 100.00 samples.
2024-03-14 21:29:14,045 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 21:31:34,573 INFO [train.py:527] (2/6) Epoch 675, batch 74, global_batch_idx: 83650, batch size: 45, loss[discriminator_loss=2.732, discriminator_real_loss=1.35, discriminator_fake_loss=1.381, generator_loss=28.9, generator_mel_loss=18.17, generator_kl_loss=1.629, generator_dur_loss=1.692, generator_adv_loss=2.058, generator_feat_match_loss=5.354, over 45.00 samples.], tot_loss[discriminator_loss=2.696, discriminator_real_loss=1.36, discriminator_fake_loss=1.336, generator_loss=28.67, generator_mel_loss=17.92, generator_kl_loss=1.423, generator_dur_loss=1.748, generator_adv_loss=1.975, generator_feat_match_loss=5.598, over 4400.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 21:33:51,239 INFO [train.py:919] (2/6) Start epoch 676
2024-03-14 21:34:15,345 INFO [train.py:527] (2/6) Epoch 676, batch 0, global_batch_idx: 83700, batch size: 64, loss[discriminator_loss=2.664, discriminator_real_loss=1.411, discriminator_fake_loss=1.253, generator_loss=29.04, generator_mel_loss=18.33, generator_kl_loss=1.491, generator_dur_loss=1.788, generator_adv_loss=1.994, generator_feat_match_loss=5.433, over 64.00 samples.], tot_loss[discriminator_loss=2.664, discriminator_real_loss=1.411, discriminator_fake_loss=1.253, generator_loss=29.04, generator_mel_loss=18.33, generator_kl_loss=1.491, generator_dur_loss=1.788, generator_adv_loss=1.994, generator_feat_match_loss=5.433, over 64.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 21:36:34,357 INFO [train.py:527] (2/6) Epoch 676, batch 50, global_batch_idx: 83750, batch size: 14, loss[discriminator_loss=2.584, discriminator_real_loss=1.269, discriminator_fake_loss=1.315, generator_loss=31.98, generator_mel_loss=19.33, generator_kl_loss=1.853, generator_dur_loss=1.549, generator_adv_loss=2.109, generator_feat_match_loss=7.14, over 14.00 samples.], tot_loss[discriminator_loss=2.687, discriminator_real_loss=1.354, discriminator_fake_loss=1.334, generator_loss=28.93, generator_mel_loss=17.98, generator_kl_loss=1.43, generator_dur_loss=1.726, generator_adv_loss=2.043, generator_feat_match_loss=5.747, over 2680.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 21:38:52,544 INFO [train.py:527] (2/6) Epoch 676, batch 100, global_batch_idx: 83800, batch size: 83, loss[discriminator_loss=2.677, discriminator_real_loss=1.339, discriminator_fake_loss=1.338, generator_loss=28.98, generator_mel_loss=18.15, generator_kl_loss=1.349, generator_dur_loss=1.808, generator_adv_loss=2, generator_feat_match_loss=5.675, over 83.00 samples.], tot_loss[discriminator_loss=2.687, discriminator_real_loss=1.365, discriminator_fake_loss=1.322, generator_loss=28.81, generator_mel_loss=17.96, generator_kl_loss=1.426, generator_dur_loss=1.732, generator_adv_loss=2.028, generator_feat_match_loss=5.662, over 5503.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 21:38:52,545 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 21:39:01,205 INFO [train.py:591] (2/6) Epoch 676, validation: discriminator_loss=2.722, discriminator_real_loss=1.392, discriminator_fake_loss=1.33, generator_loss=28, generator_mel_loss=18.27, generator_kl_loss=1.278, generator_dur_loss=1.804, generator_adv_loss=1.943, generator_feat_match_loss=4.706, over 100.00 samples.
2024-03-14 21:39:01,206 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 21:40:06,037 INFO [train.py:919] (2/6) Start epoch 677
2024-03-14 21:41:40,154 INFO [train.py:527] (2/6) Epoch 677, batch 26, global_batch_idx: 83850, batch size: 13, loss[discriminator_loss=2.589, discriminator_real_loss=1.242, discriminator_fake_loss=1.347, generator_loss=30.39, generator_mel_loss=18.45, generator_kl_loss=1.787, generator_dur_loss=1.586, generator_adv_loss=1.966, generator_feat_match_loss=6.6, over 13.00 samples.], tot_loss[discriminator_loss=2.692, discriminator_real_loss=1.353, discriminator_fake_loss=1.339, generator_loss=28.71, generator_mel_loss=17.92, generator_kl_loss=1.426, generator_dur_loss=1.742, generator_adv_loss=1.975, generator_feat_match_loss=5.656, over 1516.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 21:43:57,766 INFO [train.py:527] (2/6) Epoch 677, batch 76, global_batch_idx: 83900, batch size: 96, loss[discriminator_loss=2.633, discriminator_real_loss=1.309, discriminator_fake_loss=1.325, generator_loss=28.49, generator_mel_loss=17.38, generator_kl_loss=1.376, generator_dur_loss=1.839, generator_adv_loss=2.003, generator_feat_match_loss=5.894, over 96.00 samples.], tot_loss[discriminator_loss=2.687, discriminator_real_loss=1.358, discriminator_fake_loss=1.328, generator_loss=28.65, generator_mel_loss=17.92, generator_kl_loss=1.409, generator_dur_loss=1.75, generator_adv_loss=1.99, generator_feat_match_loss=5.581, over 4296.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 21:46:09,892 INFO [train.py:919] (2/6) Start epoch 678
2024-03-14 21:46:39,038 INFO [train.py:527] (2/6) Epoch 678, batch 2, global_batch_idx: 83950, batch size: 44, loss[discriminator_loss=2.656, discriminator_real_loss=1.272, discriminator_fake_loss=1.383, generator_loss=29.09, generator_mel_loss=17.71, generator_kl_loss=1.452, generator_dur_loss=1.663, generator_adv_loss=2.015, generator_feat_match_loss=6.257, over 44.00 samples.], tot_loss[discriminator_loss=2.698, discriminator_real_loss=1.393, discriminator_fake_loss=1.306, generator_loss=28.88, generator_mel_loss=17.98, generator_kl_loss=1.443, generator_dur_loss=1.687, generator_adv_loss=1.946, generator_feat_match_loss=5.827, over 135.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 21:48:57,996 INFO [train.py:527] (2/6) Epoch 678, batch 52, global_batch_idx: 84000, batch size: 25, loss[discriminator_loss=2.681, discriminator_real_loss=1.269, discriminator_fake_loss=1.412, generator_loss=30.27, generator_mel_loss=18.8, generator_kl_loss=1.768, generator_dur_loss=1.578, generator_adv_loss=2.156, generator_feat_match_loss=5.969, over 25.00 samples.], tot_loss[discriminator_loss=2.693, discriminator_real_loss=1.362, discriminator_fake_loss=1.331, generator_loss=28.78, generator_mel_loss=17.99, generator_kl_loss=1.431, generator_dur_loss=1.752, generator_adv_loss=1.976, generator_feat_match_loss=5.631, over 2912.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 21:48:57,998 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 21:49:05,963 INFO [train.py:591] (2/6) Epoch 678, validation: discriminator_loss=2.726, discriminator_real_loss=1.487, discriminator_fake_loss=1.239, generator_loss=27.38, generator_mel_loss=18.14, generator_kl_loss=1.248, generator_dur_loss=1.812, generator_adv_loss=2.012, generator_feat_match_loss=4.169, over 100.00 samples.
2024-03-14 21:49:05,964 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 21:51:21,584 INFO [train.py:527] (2/6) Epoch 678, batch 102, global_batch_idx: 84050, batch size: 58, loss[discriminator_loss=2.69, discriminator_real_loss=1.351, discriminator_fake_loss=1.339, generator_loss=28.92, generator_mel_loss=17.97, generator_kl_loss=1.412, generator_dur_loss=1.754, generator_adv_loss=2.023, generator_feat_match_loss=5.763, over 58.00 samples.], tot_loss[discriminator_loss=2.695, discriminator_real_loss=1.362, discriminator_fake_loss=1.333, generator_loss=28.78, generator_mel_loss=18, generator_kl_loss=1.426, generator_dur_loss=1.747, generator_adv_loss=1.979, generator_feat_match_loss=5.635, over 5662.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 21:52:22,050 INFO [train.py:919] (2/6) Start epoch 679
2024-03-14 21:54:00,273 INFO [train.py:527] (2/6) Epoch 679, batch 28, global_batch_idx: 84100, batch size: 80, loss[discriminator_loss=2.703, discriminator_real_loss=1.404, discriminator_fake_loss=1.299, generator_loss=28.06, generator_mel_loss=18.14, generator_kl_loss=1.318, generator_dur_loss=1.761, generator_adv_loss=1.871, generator_feat_match_loss=4.968, over 80.00 samples.], tot_loss[discriminator_loss=2.691, discriminator_real_loss=1.361, discriminator_fake_loss=1.33, generator_loss=28.65, generator_mel_loss=17.97, generator_kl_loss=1.366, generator_dur_loss=1.777, generator_adv_loss=1.985, generator_feat_match_loss=5.555, over 1830.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 21:56:16,835 INFO [train.py:527] (2/6) Epoch 679, batch 78, global_batch_idx: 84150, batch size: 88, loss[discriminator_loss=2.676, discriminator_real_loss=1.336, discriminator_fake_loss=1.339, generator_loss=29.56, generator_mel_loss=18.02, generator_kl_loss=1.413, generator_dur_loss=1.853, generator_adv_loss=2.041, generator_feat_match_loss=6.235, over 88.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.355, discriminator_fake_loss=1.329, generator_loss=28.77, generator_mel_loss=17.96, generator_kl_loss=1.406, generator_dur_loss=1.76, generator_adv_loss=1.988, generator_feat_match_loss=5.659, over 4677.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 21:58:24,339 INFO [train.py:919] (2/6) Start epoch 680
2024-03-14 21:58:59,278 INFO [train.py:527] (2/6) Epoch 680, batch 4, global_batch_idx: 84200, batch size: 15, loss[discriminator_loss=2.753, discriminator_real_loss=1.417, discriminator_fake_loss=1.336, generator_loss=28.93, generator_mel_loss=18.53, generator_kl_loss=1.632, generator_dur_loss=1.587, generator_adv_loss=1.931, generator_feat_match_loss=5.251, over 15.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.367, discriminator_fake_loss=1.309, generator_loss=29.11, generator_mel_loss=18.45, generator_kl_loss=1.592, generator_dur_loss=1.668, generator_adv_loss=1.982, generator_feat_match_loss=5.416, over 177.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 21:58:59,281 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 21:59:07,139 INFO [train.py:591] (2/6) Epoch 680, validation: discriminator_loss=2.709, discriminator_real_loss=1.417, discriminator_fake_loss=1.293, generator_loss=28.22, generator_mel_loss=18.34, generator_kl_loss=1.261, generator_dur_loss=1.817, generator_adv_loss=1.975, generator_feat_match_loss=4.836, over 100.00 samples.
2024-03-14 21:59:07,141 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 22:01:24,644 INFO [train.py:527] (2/6) Epoch 680, batch 54, global_batch_idx: 84250, batch size: 42, loss[discriminator_loss=2.759, discriminator_real_loss=1.386, discriminator_fake_loss=1.373, generator_loss=29.43, generator_mel_loss=18.13, generator_kl_loss=1.719, generator_dur_loss=1.69, generator_adv_loss=1.872, generator_feat_match_loss=6.018, over 42.00 samples.], tot_loss[discriminator_loss=2.701, discriminator_real_loss=1.371, discriminator_fake_loss=1.331, generator_loss=28.7, generator_mel_loss=17.98, generator_kl_loss=1.475, generator_dur_loss=1.737, generator_adv_loss=1.975, generator_feat_match_loss=5.536, over 2830.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 22:03:44,731 INFO [train.py:527] (2/6) Epoch 680, batch 104, global_batch_idx: 84300, batch size: 64, loss[discriminator_loss=2.698, discriminator_real_loss=1.37, discriminator_fake_loss=1.329, generator_loss=28.47, generator_mel_loss=18.29, generator_kl_loss=1.339, generator_dur_loss=1.797, generator_adv_loss=1.916, generator_feat_match_loss=5.132, over 64.00 samples.], tot_loss[discriminator_loss=2.695, discriminator_real_loss=1.363, discriminator_fake_loss=1.332, generator_loss=28.76, generator_mel_loss=17.99, generator_kl_loss=1.453, generator_dur_loss=1.745, generator_adv_loss=1.997, generator_feat_match_loss=5.582, over 5843.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 22:04:40,356 INFO [train.py:919] (2/6) Start epoch 681
2024-03-14 22:06:29,061 INFO [train.py:527] (2/6) Epoch 681, batch 30, global_batch_idx: 84350, batch size: 53, loss[discriminator_loss=2.634, discriminator_real_loss=1.382, discriminator_fake_loss=1.252, generator_loss=29.24, generator_mel_loss=17.8, generator_kl_loss=1.648, generator_dur_loss=1.686, generator_adv_loss=2.013, generator_feat_match_loss=6.087, over 53.00 samples.], tot_loss[discriminator_loss=2.687, discriminator_real_loss=1.359, discriminator_fake_loss=1.327, generator_loss=28.73, generator_mel_loss=17.93, generator_kl_loss=1.419, generator_dur_loss=1.74, generator_adv_loss=1.991, generator_feat_match_loss=5.64, over 1780.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 22:08:49,534 INFO [train.py:527] (2/6) Epoch 681, batch 80, global_batch_idx: 84400, batch size: 64, loss[discriminator_loss=2.689, discriminator_real_loss=1.361, discriminator_fake_loss=1.328, generator_loss=28.97, generator_mel_loss=17.6, generator_kl_loss=1.364, generator_dur_loss=1.754, generator_adv_loss=1.986, generator_feat_match_loss=6.263, over 64.00 samples.], tot_loss[discriminator_loss=2.688, discriminator_real_loss=1.362, discriminator_fake_loss=1.327, generator_loss=28.58, generator_mel_loss=17.9, generator_kl_loss=1.412, generator_dur_loss=1.748, generator_adv_loss=1.977, generator_feat_match_loss=5.54, over 4791.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 22:08:49,535 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 22:08:58,438 INFO [train.py:591] (2/6) Epoch 681, validation: discriminator_loss=2.728, discriminator_real_loss=1.42, discriminator_fake_loss=1.308, generator_loss=27.78, generator_mel_loss=18.41, generator_kl_loss=1.212, generator_dur_loss=1.813, generator_adv_loss=1.913, generator_feat_match_loss=4.433, over 100.00 samples.
2024-03-14 22:08:58,439 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 22:10:54,426 INFO [train.py:919] (2/6) Start epoch 682
2024-03-14 22:11:36,756 INFO [train.py:527] (2/6) Epoch 682, batch 6, global_batch_idx: 84450, batch size: 74, loss[discriminator_loss=2.694, discriminator_real_loss=1.378, discriminator_fake_loss=1.317, generator_loss=27.87, generator_mel_loss=17.9, generator_kl_loss=1.235, generator_dur_loss=1.852, generator_adv_loss=1.924, generator_feat_match_loss=4.963, over 74.00 samples.], tot_loss[discriminator_loss=2.689, discriminator_real_loss=1.364, discriminator_fake_loss=1.325, generator_loss=28.53, generator_mel_loss=17.91, generator_kl_loss=1.4, generator_dur_loss=1.754, generator_adv_loss=1.97, generator_feat_match_loss=5.501, over 414.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 22:13:52,722 INFO [train.py:527] (2/6) Epoch 682, batch 56, global_batch_idx: 84500, batch size: 96, loss[discriminator_loss=2.667, discriminator_real_loss=1.401, discriminator_fake_loss=1.266, generator_loss=28.38, generator_mel_loss=17.78, generator_kl_loss=1.338, generator_dur_loss=1.904, generator_adv_loss=1.858, generator_feat_match_loss=5.498, over 96.00 samples.], tot_loss[discriminator_loss=2.678, discriminator_real_loss=1.357, discriminator_fake_loss=1.322, generator_loss=28.65, generator_mel_loss=17.92, generator_kl_loss=1.4, generator_dur_loss=1.757, generator_adv_loss=1.988, generator_feat_match_loss=5.591, over 3446.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 22:16:13,608 INFO [train.py:527] (2/6) Epoch 682, batch 106, global_batch_idx: 84550, batch size: 16, loss[discriminator_loss=2.709, discriminator_real_loss=1.506, discriminator_fake_loss=1.204, generator_loss=29.75, generator_mel_loss=18.37, generator_kl_loss=1.658, generator_dur_loss=1.572, generator_adv_loss=2.123, generator_feat_match_loss=6.021, over 16.00 samples.], tot_loss[discriminator_loss=2.686, discriminator_real_loss=1.355, discriminator_fake_loss=1.331, generator_loss=28.72, generator_mel_loss=17.95, generator_kl_loss=1.402, generator_dur_loss=1.76, generator_adv_loss=1.988, generator_feat_match_loss=5.623, over 6260.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 22:17:04,788 INFO [train.py:919] (2/6) Start epoch 683
2024-03-14 22:18:57,700 INFO [train.py:527] (2/6) Epoch 683, batch 32, global_batch_idx: 84600, batch size: 88, loss[discriminator_loss=2.732, discriminator_real_loss=1.308, discriminator_fake_loss=1.424, generator_loss=28.23, generator_mel_loss=17.66, generator_kl_loss=1.274, generator_dur_loss=1.803, generator_adv_loss=2.037, generator_feat_match_loss=5.457, over 88.00 samples.], tot_loss[discriminator_loss=2.703, discriminator_real_loss=1.365, discriminator_fake_loss=1.338, generator_loss=28.7, generator_mel_loss=17.97, generator_kl_loss=1.389, generator_dur_loss=1.755, generator_adv_loss=1.968, generator_feat_match_loss=5.613, over 1877.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 22:18:57,702 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 22:19:05,697 INFO [train.py:591] (2/6) Epoch 683, validation: discriminator_loss=2.729, discriminator_real_loss=1.501, discriminator_fake_loss=1.228, generator_loss=27.2, generator_mel_loss=17.99, generator_kl_loss=1.323, generator_dur_loss=1.799, generator_adv_loss=1.946, generator_feat_match_loss=4.144, over 100.00 samples.
2024-03-14 22:19:05,698 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 22:21:28,095 INFO [train.py:527] (2/6) Epoch 683, batch 82, global_batch_idx: 84650, batch size: 66, loss[discriminator_loss=2.73, discriminator_real_loss=1.396, discriminator_fake_loss=1.334, generator_loss=28.67, generator_mel_loss=18.16, generator_kl_loss=1.441, generator_dur_loss=1.706, generator_adv_loss=1.935, generator_feat_match_loss=5.425, over 66.00 samples.], tot_loss[discriminator_loss=2.701, discriminator_real_loss=1.369, discriminator_fake_loss=1.332, generator_loss=28.61, generator_mel_loss=17.94, generator_kl_loss=1.39, generator_dur_loss=1.751, generator_adv_loss=1.979, generator_feat_match_loss=5.547, over 4779.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 22:23:21,009 INFO [train.py:919] (2/6) Start epoch 684
2024-03-14 22:24:06,547 INFO [train.py:527] (2/6) Epoch 684, batch 8, global_batch_idx: 84700, batch size: 68, loss[discriminator_loss=2.705, discriminator_real_loss=1.361, discriminator_fake_loss=1.344, generator_loss=28.48, generator_mel_loss=18.02, generator_kl_loss=1.367, generator_dur_loss=1.795, generator_adv_loss=1.95, generator_feat_match_loss=5.347, over 68.00 samples.], tot_loss[discriminator_loss=2.688, discriminator_real_loss=1.35, discriminator_fake_loss=1.338, generator_loss=29.05, generator_mel_loss=18.04, generator_kl_loss=1.446, generator_dur_loss=1.714, generator_adv_loss=1.994, generator_feat_match_loss=5.854, over 486.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 22:26:26,002 INFO [train.py:527] (2/6) Epoch 684, batch 58, global_batch_idx: 84750, batch size: 62, loss[discriminator_loss=2.764, discriminator_real_loss=1.457, discriminator_fake_loss=1.307, generator_loss=27.6, generator_mel_loss=17.55, generator_kl_loss=1.324, generator_dur_loss=1.749, generator_adv_loss=1.962, generator_feat_match_loss=5.016, over 62.00 samples.], tot_loss[discriminator_loss=2.699, discriminator_real_loss=1.369, discriminator_fake_loss=1.329, generator_loss=28.67, generator_mel_loss=17.9, generator_kl_loss=1.413, generator_dur_loss=1.735, generator_adv_loss=1.985, generator_feat_match_loss=5.636, over 3322.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 22:28:47,643 INFO [train.py:527] (2/6) Epoch 684, batch 108, global_batch_idx: 84800, batch size: 39, loss[discriminator_loss=2.753, discriminator_real_loss=1.371, discriminator_fake_loss=1.382, generator_loss=28.02, generator_mel_loss=17.87, generator_kl_loss=1.394, generator_dur_loss=1.704, generator_adv_loss=2.033, generator_feat_match_loss=5.021, over 39.00 samples.], tot_loss[discriminator_loss=2.693, discriminator_real_loss=1.363, discriminator_fake_loss=1.33, generator_loss=28.62, generator_mel_loss=17.89, generator_kl_loss=1.423, generator_dur_loss=1.739, generator_adv_loss=1.987, generator_feat_match_loss=5.581, over 6182.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 22:28:47,645 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 22:28:56,612 INFO [train.py:591] (2/6) Epoch 684, validation: discriminator_loss=2.73, discriminator_real_loss=1.43, discriminator_fake_loss=1.3, generator_loss=28.12, generator_mel_loss=18.59, generator_kl_loss=1.203, generator_dur_loss=1.813, generator_adv_loss=1.939, generator_feat_match_loss=4.572, over 100.00 samples.
2024-03-14 22:28:56,613 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 22:29:39,025 INFO [train.py:919] (2/6) Start epoch 685
2024-03-14 22:31:37,853 INFO [train.py:527] (2/6) Epoch 685, batch 34, global_batch_idx: 84850, batch size: 31, loss[discriminator_loss=2.651, discriminator_real_loss=1.344, discriminator_fake_loss=1.307, generator_loss=30.62, generator_mel_loss=18.62, generator_kl_loss=1.448, generator_dur_loss=1.625, generator_adv_loss=2.053, generator_feat_match_loss=6.869, over 31.00 samples.], tot_loss[discriminator_loss=2.69, discriminator_real_loss=1.366, discriminator_fake_loss=1.324, generator_loss=28.69, generator_mel_loss=17.95, generator_kl_loss=1.406, generator_dur_loss=1.733, generator_adv_loss=1.989, generator_feat_match_loss=5.617, over 1893.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 22:33:56,838 INFO [train.py:527] (2/6) Epoch 685, batch 84, global_batch_idx: 84900, batch size: 83, loss[discriminator_loss=2.7, discriminator_real_loss=1.34, discriminator_fake_loss=1.36, generator_loss=28.53, generator_mel_loss=17.73, generator_kl_loss=1.328, generator_dur_loss=1.842, generator_adv_loss=2.06, generator_feat_match_loss=5.564, over 83.00 samples.], tot_loss[discriminator_loss=2.691, discriminator_real_loss=1.366, discriminator_fake_loss=1.325, generator_loss=28.72, generator_mel_loss=17.94, generator_kl_loss=1.407, generator_dur_loss=1.743, generator_adv_loss=1.994, generator_feat_match_loss=5.641, over 4820.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 22:35:45,940 INFO [train.py:919] (2/6) Start epoch 686
2024-03-14 22:36:40,450 INFO [train.py:527] (2/6) Epoch 686, batch 10, global_batch_idx: 84950, batch size: 62, loss[discriminator_loss=2.686, discriminator_real_loss=1.351, discriminator_fake_loss=1.335, generator_loss=28.72, generator_mel_loss=17.99, generator_kl_loss=1.467, generator_dur_loss=1.734, generator_adv_loss=1.947, generator_feat_match_loss=5.578, over 62.00 samples.], tot_loss[discriminator_loss=2.696, discriminator_real_loss=1.364, discriminator_fake_loss=1.333, generator_loss=29.15, generator_mel_loss=18.04, generator_kl_loss=1.413, generator_dur_loss=1.757, generator_adv_loss=1.994, generator_feat_match_loss=5.946, over 680.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 22:38:59,294 INFO [train.py:527] (2/6) Epoch 686, batch 60, global_batch_idx: 85000, batch size: 68, loss[discriminator_loss=2.656, discriminator_real_loss=1.324, discriminator_fake_loss=1.332, generator_loss=27.87, generator_mel_loss=17.68, generator_kl_loss=1.489, generator_dur_loss=1.737, generator_adv_loss=2.083, generator_feat_match_loss=4.884, over 68.00 samples.], tot_loss[discriminator_loss=2.699, discriminator_real_loss=1.363, discriminator_fake_loss=1.336, generator_loss=28.64, generator_mel_loss=17.92, generator_kl_loss=1.418, generator_dur_loss=1.741, generator_adv_loss=1.978, generator_feat_match_loss=5.586, over 3537.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 22:38:59,296 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 22:39:07,402 INFO [train.py:591] (2/6) Epoch 686, validation: discriminator_loss=2.731, discriminator_real_loss=1.513, discriminator_fake_loss=1.218, generator_loss=27.11, generator_mel_loss=17.73, generator_kl_loss=1.243, generator_dur_loss=1.814, generator_adv_loss=2.099, generator_feat_match_loss=4.224, over 100.00 samples.
2024-03-14 22:39:07,403 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 22:41:26,987 INFO [train.py:527] (2/6) Epoch 686, batch 110, global_batch_idx: 85050, batch size: 58, loss[discriminator_loss=2.757, discriminator_real_loss=1.414, discriminator_fake_loss=1.342, generator_loss=28.28, generator_mel_loss=17.71, generator_kl_loss=1.389, generator_dur_loss=1.731, generator_adv_loss=1.922, generator_feat_match_loss=5.525, over 58.00 samples.], tot_loss[discriminator_loss=2.696, discriminator_real_loss=1.362, discriminator_fake_loss=1.334, generator_loss=28.59, generator_mel_loss=17.88, generator_kl_loss=1.415, generator_dur_loss=1.746, generator_adv_loss=1.979, generator_feat_match_loss=5.566, over 6492.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 22:42:04,768 INFO [train.py:919] (2/6) Start epoch 687
2024-03-14 22:44:09,368 INFO [train.py:527] (2/6) Epoch 687, batch 36, global_batch_idx: 85100, batch size: 47, loss[discriminator_loss=2.701, discriminator_real_loss=1.447, discriminator_fake_loss=1.254, generator_loss=27.52, generator_mel_loss=17.87, generator_kl_loss=1.355, generator_dur_loss=1.738, generator_adv_loss=1.902, generator_feat_match_loss=4.652, over 47.00 samples.], tot_loss[discriminator_loss=2.7, discriminator_real_loss=1.364, discriminator_fake_loss=1.336, generator_loss=28.51, generator_mel_loss=17.88, generator_kl_loss=1.41, generator_dur_loss=1.747, generator_adv_loss=1.984, generator_feat_match_loss=5.487, over 1974.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 22:46:28,519 INFO [train.py:527] (2/6) Epoch 687, batch 86, global_batch_idx: 85150, batch size: 70, loss[discriminator_loss=2.674, discriminator_real_loss=1.442, discriminator_fake_loss=1.232, generator_loss=28.96, generator_mel_loss=17.92, generator_kl_loss=1.39, generator_dur_loss=1.775, generator_adv_loss=2.014, generator_feat_match_loss=5.862, over 70.00 samples.], tot_loss[discriminator_loss=2.701, discriminator_real_loss=1.363, discriminator_fake_loss=1.338, generator_loss=28.67, generator_mel_loss=17.89, generator_kl_loss=1.396, generator_dur_loss=1.746, generator_adv_loss=2.031, generator_feat_match_loss=5.609, over 4946.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 22:48:12,469 INFO [train.py:919] (2/6) Start epoch 688
2024-03-14 22:49:10,903 INFO [train.py:527] (2/6) Epoch 688, batch 12, global_batch_idx: 85200, batch size: 80, loss[discriminator_loss=2.662, discriminator_real_loss=1.349, discriminator_fake_loss=1.313, generator_loss=28.87, generator_mel_loss=17.81, generator_kl_loss=1.426, generator_dur_loss=1.844, generator_adv_loss=1.92, generator_feat_match_loss=5.867, over 80.00 samples.], tot_loss[discriminator_loss=2.674, discriminator_real_loss=1.361, discriminator_fake_loss=1.314, generator_loss=28.46, generator_mel_loss=17.82, generator_kl_loss=1.355, generator_dur_loss=1.798, generator_adv_loss=1.979, generator_feat_match_loss=5.511, over 905.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 22:49:10,905 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 22:49:18,930 INFO [train.py:591] (2/6) Epoch 688, validation: discriminator_loss=2.719, discriminator_real_loss=1.377, discriminator_fake_loss=1.342, generator_loss=27.38, generator_mel_loss=18, generator_kl_loss=1.274, generator_dur_loss=1.805, generator_adv_loss=1.824, generator_feat_match_loss=4.473, over 100.00 samples.
2024-03-14 22:49:18,931 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 22:51:34,915 INFO [train.py:527] (2/6) Epoch 688, batch 62, global_batch_idx: 85250, batch size: 59, loss[discriminator_loss=2.693, discriminator_real_loss=1.37, discriminator_fake_loss=1.323, generator_loss=28.27, generator_mel_loss=17.77, generator_kl_loss=1.465, generator_dur_loss=1.754, generator_adv_loss=1.913, generator_feat_match_loss=5.373, over 59.00 samples.], tot_loss[discriminator_loss=2.688, discriminator_real_loss=1.358, discriminator_fake_loss=1.33, generator_loss=28.63, generator_mel_loss=17.88, generator_kl_loss=1.407, generator_dur_loss=1.755, generator_adv_loss=1.983, generator_feat_match_loss=5.613, over 3714.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 22:53:54,677 INFO [train.py:527] (2/6) Epoch 688, batch 112, global_batch_idx: 85300, batch size: 72, loss[discriminator_loss=2.664, discriminator_real_loss=1.321, discriminator_fake_loss=1.343, generator_loss=28.8, generator_mel_loss=17.89, generator_kl_loss=1.492, generator_dur_loss=1.787, generator_adv_loss=2.002, generator_feat_match_loss=5.628, over 72.00 samples.], tot_loss[discriminator_loss=2.694, discriminator_real_loss=1.361, discriminator_fake_loss=1.333, generator_loss=28.71, generator_mel_loss=17.91, generator_kl_loss=1.426, generator_dur_loss=1.753, generator_adv_loss=1.979, generator_feat_match_loss=5.639, over 6639.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 22:54:26,395 INFO [train.py:919] (2/6) Start epoch 689
2024-03-14 22:56:35,011 INFO [train.py:527] (2/6) Epoch 689, batch 38, global_batch_idx: 85350, batch size: 25, loss[discriminator_loss=2.696, discriminator_real_loss=1.353, discriminator_fake_loss=1.343, generator_loss=28.92, generator_mel_loss=18.34, generator_kl_loss=1.714, generator_dur_loss=1.553, generator_adv_loss=2.167, generator_feat_match_loss=5.148, over 25.00 samples.], tot_loss[discriminator_loss=2.704, discriminator_real_loss=1.37, discriminator_fake_loss=1.334, generator_loss=28.44, generator_mel_loss=17.9, generator_kl_loss=1.406, generator_dur_loss=1.725, generator_adv_loss=1.979, generator_feat_match_loss=5.426, over 2054.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 22:58:51,876 INFO [train.py:527] (2/6) Epoch 689, batch 88, global_batch_idx: 85400, batch size: 59, loss[discriminator_loss=2.696, discriminator_real_loss=1.411, discriminator_fake_loss=1.285, generator_loss=28.51, generator_mel_loss=17.88, generator_kl_loss=1.429, generator_dur_loss=1.765, generator_adv_loss=2.081, generator_feat_match_loss=5.353, over 59.00 samples.], tot_loss[discriminator_loss=2.695, discriminator_real_loss=1.362, discriminator_fake_loss=1.333, generator_loss=28.55, generator_mel_loss=17.9, generator_kl_loss=1.425, generator_dur_loss=1.736, generator_adv_loss=1.979, generator_feat_match_loss=5.511, over 4855.00 samples.], cur_lr_g: 1.84e-04, cur_lr_d: 1.84e-04, 
2024-03-14 22:58:51,878 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 22:59:00,798 INFO [train.py:591] (2/6) Epoch 689, validation: discriminator_loss=2.737, discriminator_real_loss=1.46, discriminator_fake_loss=1.277, generator_loss=27.34, generator_mel_loss=18.04, generator_kl_loss=1.309, generator_dur_loss=1.806, generator_adv_loss=1.958, generator_feat_match_loss=4.23, over 100.00 samples.
2024-03-14 22:59:00,799 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 23:00:42,151 INFO [train.py:919] (2/6) Start epoch 690
2024-03-14 23:01:46,912 INFO [train.py:527] (2/6) Epoch 690, batch 14, global_batch_idx: 85450, batch size: 52, loss[discriminator_loss=2.704, discriminator_real_loss=1.349, discriminator_fake_loss=1.355, generator_loss=29.31, generator_mel_loss=17.56, generator_kl_loss=1.383, generator_dur_loss=1.703, generator_adv_loss=2.265, generator_feat_match_loss=6.403, over 52.00 samples.], tot_loss[discriminator_loss=2.709, discriminator_real_loss=1.361, discriminator_fake_loss=1.348, generator_loss=29.11, generator_mel_loss=18, generator_kl_loss=1.411, generator_dur_loss=1.759, generator_adv_loss=2.035, generator_feat_match_loss=5.904, over 941.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-14 23:04:07,189 INFO [train.py:527] (2/6) Epoch 690, batch 64, global_batch_idx: 85500, batch size: 42, loss[discriminator_loss=2.633, discriminator_real_loss=1.347, discriminator_fake_loss=1.287, generator_loss=29.16, generator_mel_loss=18.3, generator_kl_loss=1.515, generator_dur_loss=1.688, generator_adv_loss=2.037, generator_feat_match_loss=5.626, over 42.00 samples.], tot_loss[discriminator_loss=2.691, discriminator_real_loss=1.364, discriminator_fake_loss=1.327, generator_loss=28.77, generator_mel_loss=17.97, generator_kl_loss=1.407, generator_dur_loss=1.743, generator_adv_loss=2.008, generator_feat_match_loss=5.641, over 3779.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-14 23:06:22,283 INFO [train.py:527] (2/6) Epoch 690, batch 114, global_batch_idx: 85550, batch size: 66, loss[discriminator_loss=2.756, discriminator_real_loss=1.446, discriminator_fake_loss=1.31, generator_loss=28.51, generator_mel_loss=17.78, generator_kl_loss=1.336, generator_dur_loss=1.798, generator_adv_loss=1.923, generator_feat_match_loss=5.671, over 66.00 samples.], tot_loss[discriminator_loss=2.691, discriminator_real_loss=1.366, discriminator_fake_loss=1.325, generator_loss=28.76, generator_mel_loss=17.93, generator_kl_loss=1.418, generator_dur_loss=1.735, generator_adv_loss=2.001, generator_feat_match_loss=5.672, over 6351.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-14 23:06:47,674 INFO [train.py:919] (2/6) Start epoch 691
2024-03-14 23:09:01,361 INFO [train.py:527] (2/6) Epoch 691, batch 40, global_batch_idx: 85600, batch size: 61, loss[discriminator_loss=2.716, discriminator_real_loss=1.392, discriminator_fake_loss=1.323, generator_loss=27.84, generator_mel_loss=17.51, generator_kl_loss=1.323, generator_dur_loss=1.714, generator_adv_loss=1.974, generator_feat_match_loss=5.327, over 61.00 samples.], tot_loss[discriminator_loss=2.695, discriminator_real_loss=1.358, discriminator_fake_loss=1.337, generator_loss=28.52, generator_mel_loss=17.91, generator_kl_loss=1.386, generator_dur_loss=1.757, generator_adv_loss=1.987, generator_feat_match_loss=5.485, over 2561.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-14 23:09:01,363 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 23:09:09,451 INFO [train.py:591] (2/6) Epoch 691, validation: discriminator_loss=2.715, discriminator_real_loss=1.397, discriminator_fake_loss=1.319, generator_loss=27.18, generator_mel_loss=17.87, generator_kl_loss=1.276, generator_dur_loss=1.788, generator_adv_loss=1.895, generator_feat_match_loss=4.349, over 100.00 samples.
2024-03-14 23:09:09,452 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 23:11:27,764 INFO [train.py:527] (2/6) Epoch 691, batch 90, global_batch_idx: 85650, batch size: 74, loss[discriminator_loss=2.624, discriminator_real_loss=1.336, discriminator_fake_loss=1.288, generator_loss=29.37, generator_mel_loss=18.22, generator_kl_loss=1.26, generator_dur_loss=1.789, generator_adv_loss=2.009, generator_feat_match_loss=6.091, over 74.00 samples.], tot_loss[discriminator_loss=2.697, discriminator_real_loss=1.362, discriminator_fake_loss=1.335, generator_loss=28.59, generator_mel_loss=17.97, generator_kl_loss=1.404, generator_dur_loss=1.738, generator_adv_loss=1.974, generator_feat_match_loss=5.506, over 5384.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-14 23:13:01,158 INFO [train.py:919] (2/6) Start epoch 692
2024-03-14 23:14:07,509 INFO [train.py:527] (2/6) Epoch 692, batch 16, global_batch_idx: 85700, batch size: 42, loss[discriminator_loss=2.725, discriminator_real_loss=1.273, discriminator_fake_loss=1.452, generator_loss=28.15, generator_mel_loss=17.65, generator_kl_loss=1.483, generator_dur_loss=1.671, generator_adv_loss=2.09, generator_feat_match_loss=5.253, over 42.00 samples.], tot_loss[discriminator_loss=2.687, discriminator_real_loss=1.365, discriminator_fake_loss=1.322, generator_loss=28.63, generator_mel_loss=17.87, generator_kl_loss=1.375, generator_dur_loss=1.744, generator_adv_loss=2.009, generator_feat_match_loss=5.626, over 977.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-14 23:16:27,050 INFO [train.py:527] (2/6) Epoch 692, batch 66, global_batch_idx: 85750, batch size: 59, loss[discriminator_loss=2.672, discriminator_real_loss=1.335, discriminator_fake_loss=1.337, generator_loss=29.32, generator_mel_loss=18.01, generator_kl_loss=1.491, generator_dur_loss=1.695, generator_adv_loss=1.96, generator_feat_match_loss=6.166, over 59.00 samples.], tot_loss[discriminator_loss=2.687, discriminator_real_loss=1.363, discriminator_fake_loss=1.324, generator_loss=28.67, generator_mel_loss=17.94, generator_kl_loss=1.39, generator_dur_loss=1.735, generator_adv_loss=1.993, generator_feat_match_loss=5.603, over 3763.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-14 23:18:45,490 INFO [train.py:527] (2/6) Epoch 692, batch 116, global_batch_idx: 85800, batch size: 52, loss[discriminator_loss=2.667, discriminator_real_loss=1.258, discriminator_fake_loss=1.409, generator_loss=29.72, generator_mel_loss=18.53, generator_kl_loss=1.445, generator_dur_loss=1.688, generator_adv_loss=2.163, generator_feat_match_loss=5.888, over 52.00 samples.], tot_loss[discriminator_loss=2.691, discriminator_real_loss=1.362, discriminator_fake_loss=1.329, generator_loss=28.66, generator_mel_loss=17.94, generator_kl_loss=1.406, generator_dur_loss=1.736, generator_adv_loss=1.988, generator_feat_match_loss=5.593, over 6528.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-14 23:18:45,491 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 23:18:54,409 INFO [train.py:591] (2/6) Epoch 692, validation: discriminator_loss=2.73, discriminator_real_loss=1.472, discriminator_fake_loss=1.258, generator_loss=27.34, generator_mel_loss=18.13, generator_kl_loss=1.279, generator_dur_loss=1.808, generator_adv_loss=2.034, generator_feat_match_loss=4.085, over 100.00 samples.
2024-03-14 23:18:54,410 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 23:19:15,532 INFO [train.py:919] (2/6) Start epoch 693
2024-03-14 23:21:35,683 INFO [train.py:527] (2/6) Epoch 693, batch 42, global_batch_idx: 85850, batch size: 25, loss[discriminator_loss=2.719, discriminator_real_loss=1.302, discriminator_fake_loss=1.416, generator_loss=30.55, generator_mel_loss=19.02, generator_kl_loss=1.77, generator_dur_loss=1.541, generator_adv_loss=1.899, generator_feat_match_loss=6.33, over 25.00 samples.], tot_loss[discriminator_loss=2.691, discriminator_real_loss=1.359, discriminator_fake_loss=1.332, generator_loss=28.67, generator_mel_loss=17.94, generator_kl_loss=1.419, generator_dur_loss=1.748, generator_adv_loss=1.988, generator_feat_match_loss=5.578, over 2398.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-14 23:23:55,403 INFO [train.py:527] (2/6) Epoch 693, batch 92, global_batch_idx: 85900, batch size: 64, loss[discriminator_loss=2.765, discriminator_real_loss=1.469, discriminator_fake_loss=1.296, generator_loss=28.75, generator_mel_loss=18.29, generator_kl_loss=1.096, generator_dur_loss=1.754, generator_adv_loss=2.033, generator_feat_match_loss=5.577, over 64.00 samples.], tot_loss[discriminator_loss=2.695, discriminator_real_loss=1.359, discriminator_fake_loss=1.336, generator_loss=28.62, generator_mel_loss=17.93, generator_kl_loss=1.416, generator_dur_loss=1.744, generator_adv_loss=1.981, generator_feat_match_loss=5.543, over 5340.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-14 23:25:19,951 INFO [train.py:919] (2/6) Start epoch 694
2024-03-14 23:26:34,770 INFO [train.py:527] (2/6) Epoch 694, batch 18, global_batch_idx: 85950, batch size: 77, loss[discriminator_loss=2.674, discriminator_real_loss=1.331, discriminator_fake_loss=1.342, generator_loss=29.03, generator_mel_loss=17.83, generator_kl_loss=1.445, generator_dur_loss=1.82, generator_adv_loss=1.996, generator_feat_match_loss=5.932, over 77.00 samples.], tot_loss[discriminator_loss=2.696, discriminator_real_loss=1.37, discriminator_fake_loss=1.326, generator_loss=28.59, generator_mel_loss=17.95, generator_kl_loss=1.388, generator_dur_loss=1.753, generator_adv_loss=1.971, generator_feat_match_loss=5.531, over 1144.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-14 23:28:56,362 INFO [train.py:527] (2/6) Epoch 694, batch 68, global_batch_idx: 86000, batch size: 70, loss[discriminator_loss=2.627, discriminator_real_loss=1.331, discriminator_fake_loss=1.296, generator_loss=30.18, generator_mel_loss=18.26, generator_kl_loss=1.472, generator_dur_loss=1.75, generator_adv_loss=2.066, generator_feat_match_loss=6.632, over 70.00 samples.], tot_loss[discriminator_loss=2.688, discriminator_real_loss=1.36, discriminator_fake_loss=1.329, generator_loss=28.69, generator_mel_loss=17.93, generator_kl_loss=1.408, generator_dur_loss=1.747, generator_adv_loss=1.98, generator_feat_match_loss=5.626, over 4120.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-14 23:28:56,363 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 23:29:05,263 INFO [train.py:591] (2/6) Epoch 694, validation: discriminator_loss=2.703, discriminator_real_loss=1.38, discriminator_fake_loss=1.323, generator_loss=26.96, generator_mel_loss=17.87, generator_kl_loss=1.186, generator_dur_loss=1.786, generator_adv_loss=1.937, generator_feat_match_loss=4.183, over 100.00 samples.
2024-03-14 23:29:05,264 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 23:31:20,796 INFO [train.py:527] (2/6) Epoch 694, batch 118, global_batch_idx: 86050, batch size: 66, loss[discriminator_loss=2.641, discriminator_real_loss=1.307, discriminator_fake_loss=1.334, generator_loss=30.2, generator_mel_loss=18.37, generator_kl_loss=1.477, generator_dur_loss=1.697, generator_adv_loss=1.924, generator_feat_match_loss=6.74, over 66.00 samples.], tot_loss[discriminator_loss=2.689, discriminator_real_loss=1.359, discriminator_fake_loss=1.33, generator_loss=28.68, generator_mel_loss=17.91, generator_kl_loss=1.415, generator_dur_loss=1.736, generator_adv_loss=1.981, generator_feat_match_loss=5.632, over 6900.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-14 23:31:36,648 INFO [train.py:919] (2/6) Start epoch 695
2024-03-14 23:34:03,419 INFO [train.py:527] (2/6) Epoch 695, batch 44, global_batch_idx: 86100, batch size: 52, loss[discriminator_loss=2.709, discriminator_real_loss=1.42, discriminator_fake_loss=1.289, generator_loss=28.38, generator_mel_loss=18.19, generator_kl_loss=1.436, generator_dur_loss=1.669, generator_adv_loss=2.021, generator_feat_match_loss=5.066, over 52.00 samples.], tot_loss[discriminator_loss=2.706, discriminator_real_loss=1.366, discriminator_fake_loss=1.341, generator_loss=28.72, generator_mel_loss=17.95, generator_kl_loss=1.388, generator_dur_loss=1.748, generator_adv_loss=1.968, generator_feat_match_loss=5.667, over 2715.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-14 23:36:21,409 INFO [train.py:527] (2/6) Epoch 695, batch 94, global_batch_idx: 86150, batch size: 83, loss[discriminator_loss=2.727, discriminator_real_loss=1.375, discriminator_fake_loss=1.352, generator_loss=28.43, generator_mel_loss=18.1, generator_kl_loss=1.266, generator_dur_loss=1.825, generator_adv_loss=2.022, generator_feat_match_loss=5.219, over 83.00 samples.], tot_loss[discriminator_loss=2.696, discriminator_real_loss=1.358, discriminator_fake_loss=1.338, generator_loss=28.78, generator_mel_loss=17.95, generator_kl_loss=1.406, generator_dur_loss=1.741, generator_adv_loss=1.981, generator_feat_match_loss=5.703, over 5577.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-14 23:37:41,108 INFO [train.py:919] (2/6) Start epoch 696
2024-03-14 23:39:00,802 INFO [train.py:527] (2/6) Epoch 696, batch 20, global_batch_idx: 86200, batch size: 83, loss[discriminator_loss=2.658, discriminator_real_loss=1.336, discriminator_fake_loss=1.322, generator_loss=28.95, generator_mel_loss=18.06, generator_kl_loss=1.359, generator_dur_loss=1.817, generator_adv_loss=2.045, generator_feat_match_loss=5.661, over 83.00 samples.], tot_loss[discriminator_loss=2.7, discriminator_real_loss=1.368, discriminator_fake_loss=1.332, generator_loss=28.52, generator_mel_loss=17.96, generator_kl_loss=1.368, generator_dur_loss=1.757, generator_adv_loss=1.982, generator_feat_match_loss=5.45, over 1314.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-14 23:39:00,803 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 23:39:09,020 INFO [train.py:591] (2/6) Epoch 696, validation: discriminator_loss=2.771, discriminator_real_loss=1.451, discriminator_fake_loss=1.32, generator_loss=27.59, generator_mel_loss=18.14, generator_kl_loss=1.222, generator_dur_loss=1.806, generator_adv_loss=1.954, generator_feat_match_loss=4.465, over 100.00 samples.
2024-03-14 23:39:09,022 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 23:41:26,965 INFO [train.py:527] (2/6) Epoch 696, batch 70, global_batch_idx: 86250, batch size: 77, loss[discriminator_loss=2.704, discriminator_real_loss=1.394, discriminator_fake_loss=1.31, generator_loss=28.43, generator_mel_loss=17.43, generator_kl_loss=1.357, generator_dur_loss=1.783, generator_adv_loss=2.05, generator_feat_match_loss=5.817, over 77.00 samples.], tot_loss[discriminator_loss=2.705, discriminator_real_loss=1.368, discriminator_fake_loss=1.337, generator_loss=28.59, generator_mel_loss=17.95, generator_kl_loss=1.391, generator_dur_loss=1.749, generator_adv_loss=1.977, generator_feat_match_loss=5.527, over 4157.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-14 23:43:47,161 INFO [train.py:527] (2/6) Epoch 696, batch 120, global_batch_idx: 86300, batch size: 36, loss[discriminator_loss=2.799, discriminator_real_loss=1.38, discriminator_fake_loss=1.42, generator_loss=28.4, generator_mel_loss=17.49, generator_kl_loss=1.535, generator_dur_loss=1.698, generator_adv_loss=1.926, generator_feat_match_loss=5.751, over 36.00 samples.], tot_loss[discriminator_loss=2.701, discriminator_real_loss=1.367, discriminator_fake_loss=1.334, generator_loss=28.62, generator_mel_loss=17.94, generator_kl_loss=1.397, generator_dur_loss=1.747, generator_adv_loss=1.979, generator_feat_match_loss=5.557, over 6991.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-14 23:43:57,336 INFO [train.py:919] (2/6) Start epoch 697
2024-03-14 23:46:28,268 INFO [train.py:527] (2/6) Epoch 697, batch 46, global_batch_idx: 86350, batch size: 47, loss[discriminator_loss=2.719, discriminator_real_loss=1.322, discriminator_fake_loss=1.398, generator_loss=29.66, generator_mel_loss=18.13, generator_kl_loss=1.586, generator_dur_loss=1.68, generator_adv_loss=1.984, generator_feat_match_loss=6.289, over 47.00 samples.], tot_loss[discriminator_loss=2.703, discriminator_real_loss=1.369, discriminator_fake_loss=1.334, generator_loss=28.69, generator_mel_loss=17.94, generator_kl_loss=1.406, generator_dur_loss=1.734, generator_adv_loss=2.006, generator_feat_match_loss=5.609, over 2889.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-14 23:48:45,591 INFO [train.py:527] (2/6) Epoch 697, batch 96, global_batch_idx: 86400, batch size: 59, loss[discriminator_loss=2.634, discriminator_real_loss=1.285, discriminator_fake_loss=1.349, generator_loss=29.93, generator_mel_loss=17.96, generator_kl_loss=1.375, generator_dur_loss=1.717, generator_adv_loss=2.107, generator_feat_match_loss=6.769, over 59.00 samples.], tot_loss[discriminator_loss=2.705, discriminator_real_loss=1.366, discriminator_fake_loss=1.339, generator_loss=28.65, generator_mel_loss=17.94, generator_kl_loss=1.414, generator_dur_loss=1.732, generator_adv_loss=1.985, generator_feat_match_loss=5.579, over 5781.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-14 23:48:45,593 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 23:48:54,260 INFO [train.py:591] (2/6) Epoch 697, validation: discriminator_loss=2.725, discriminator_real_loss=1.412, discriminator_fake_loss=1.313, generator_loss=28.36, generator_mel_loss=18.65, generator_kl_loss=1.19, generator_dur_loss=1.793, generator_adv_loss=1.97, generator_feat_match_loss=4.759, over 100.00 samples.
2024-03-14 23:48:54,261 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-14 23:50:11,234 INFO [train.py:919] (2/6) Start epoch 698
2024-03-14 23:51:37,798 INFO [train.py:527] (2/6) Epoch 698, batch 22, global_batch_idx: 86450, batch size: 56, loss[discriminator_loss=2.701, discriminator_real_loss=1.458, discriminator_fake_loss=1.244, generator_loss=27.58, generator_mel_loss=17.61, generator_kl_loss=1.358, generator_dur_loss=1.687, generator_adv_loss=1.926, generator_feat_match_loss=5.005, over 56.00 samples.], tot_loss[discriminator_loss=2.718, discriminator_real_loss=1.379, discriminator_fake_loss=1.338, generator_loss=28.35, generator_mel_loss=17.87, generator_kl_loss=1.392, generator_dur_loss=1.741, generator_adv_loss=1.959, generator_feat_match_loss=5.393, over 1366.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-14 23:53:59,563 INFO [train.py:527] (2/6) Epoch 698, batch 72, global_batch_idx: 86500, batch size: 59, loss[discriminator_loss=2.657, discriminator_real_loss=1.287, discriminator_fake_loss=1.37, generator_loss=28.86, generator_mel_loss=17.87, generator_kl_loss=1.497, generator_dur_loss=1.699, generator_adv_loss=2.015, generator_feat_match_loss=5.781, over 59.00 samples.], tot_loss[discriminator_loss=2.7, discriminator_real_loss=1.369, discriminator_fake_loss=1.331, generator_loss=28.52, generator_mel_loss=17.89, generator_kl_loss=1.409, generator_dur_loss=1.732, generator_adv_loss=1.973, generator_feat_match_loss=5.523, over 4158.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-14 23:56:14,833 INFO [train.py:527] (2/6) Epoch 698, batch 122, global_batch_idx: 86550, batch size: 55, loss[discriminator_loss=2.679, discriminator_real_loss=1.406, discriminator_fake_loss=1.273, generator_loss=28.56, generator_mel_loss=17.99, generator_kl_loss=1.42, generator_dur_loss=1.691, generator_adv_loss=1.951, generator_feat_match_loss=5.511, over 55.00 samples.], tot_loss[discriminator_loss=2.694, discriminator_real_loss=1.363, discriminator_fake_loss=1.331, generator_loss=28.54, generator_mel_loss=17.88, generator_kl_loss=1.411, generator_dur_loss=1.727, generator_adv_loss=1.974, generator_feat_match_loss=5.553, over 6906.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-14 23:56:19,485 INFO [train.py:919] (2/6) Start epoch 699
2024-03-14 23:58:57,636 INFO [train.py:527] (2/6) Epoch 699, batch 48, global_batch_idx: 86600, batch size: 55, loss[discriminator_loss=2.666, discriminator_real_loss=1.413, discriminator_fake_loss=1.253, generator_loss=30.6, generator_mel_loss=18.27, generator_kl_loss=1.55, generator_dur_loss=1.706, generator_adv_loss=2.191, generator_feat_match_loss=6.883, over 55.00 samples.], tot_loss[discriminator_loss=2.683, discriminator_real_loss=1.358, discriminator_fake_loss=1.324, generator_loss=28.83, generator_mel_loss=17.91, generator_kl_loss=1.399, generator_dur_loss=1.739, generator_adv_loss=2.014, generator_feat_match_loss=5.769, over 2701.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-14 23:58:57,638 INFO [train.py:581] (2/6) Computing validation loss
2024-03-14 23:59:05,347 INFO [train.py:591] (2/6) Epoch 699, validation: discriminator_loss=2.727, discriminator_real_loss=1.469, discriminator_fake_loss=1.258, generator_loss=28.32, generator_mel_loss=18.63, generator_kl_loss=1.148, generator_dur_loss=1.815, generator_adv_loss=2.007, generator_feat_match_loss=4.716, over 100.00 samples.
2024-03-14 23:59:05,352 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 00:01:23,420 INFO [train.py:527] (2/6) Epoch 699, batch 98, global_batch_idx: 86650, batch size: 47, loss[discriminator_loss=2.735, discriminator_real_loss=1.413, discriminator_fake_loss=1.322, generator_loss=28.76, generator_mel_loss=17.92, generator_kl_loss=1.54, generator_dur_loss=1.683, generator_adv_loss=1.872, generator_feat_match_loss=5.747, over 47.00 samples.], tot_loss[discriminator_loss=2.686, discriminator_real_loss=1.359, discriminator_fake_loss=1.327, generator_loss=28.74, generator_mel_loss=17.91, generator_kl_loss=1.399, generator_dur_loss=1.738, generator_adv_loss=2.001, generator_feat_match_loss=5.692, over 5567.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 00:02:31,309 INFO [train.py:919] (2/6) Start epoch 700
2024-03-15 00:04:01,447 INFO [train.py:527] (2/6) Epoch 700, batch 24, global_batch_idx: 86700, batch size: 50, loss[discriminator_loss=2.696, discriminator_real_loss=1.334, discriminator_fake_loss=1.363, generator_loss=27.96, generator_mel_loss=17.87, generator_kl_loss=1.438, generator_dur_loss=1.718, generator_adv_loss=2.001, generator_feat_match_loss=4.929, over 50.00 samples.], tot_loss[discriminator_loss=2.691, discriminator_real_loss=1.356, discriminator_fake_loss=1.335, generator_loss=28.63, generator_mel_loss=17.87, generator_kl_loss=1.441, generator_dur_loss=1.712, generator_adv_loss=1.974, generator_feat_match_loss=5.631, over 1287.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 00:06:21,337 INFO [train.py:527] (2/6) Epoch 700, batch 74, global_batch_idx: 86750, batch size: 74, loss[discriminator_loss=2.638, discriminator_real_loss=1.345, discriminator_fake_loss=1.293, generator_loss=28.84, generator_mel_loss=18, generator_kl_loss=1.476, generator_dur_loss=1.804, generator_adv_loss=1.979, generator_feat_match_loss=5.582, over 74.00 samples.], tot_loss[discriminator_loss=2.695, discriminator_real_loss=1.363, discriminator_fake_loss=1.332, generator_loss=28.76, generator_mel_loss=17.93, generator_kl_loss=1.421, generator_dur_loss=1.744, generator_adv_loss=1.985, generator_feat_match_loss=5.683, over 4357.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 00:08:37,205 INFO [train.py:919] (2/6) Start epoch 701
2024-03-15 00:09:01,133 INFO [train.py:527] (2/6) Epoch 701, batch 0, global_batch_idx: 86800, batch size: 50, loss[discriminator_loss=2.734, discriminator_real_loss=1.507, discriminator_fake_loss=1.227, generator_loss=29.45, generator_mel_loss=17.84, generator_kl_loss=1.531, generator_dur_loss=1.732, generator_adv_loss=1.942, generator_feat_match_loss=6.41, over 50.00 samples.], tot_loss[discriminator_loss=2.734, discriminator_real_loss=1.507, discriminator_fake_loss=1.227, generator_loss=29.45, generator_mel_loss=17.84, generator_kl_loss=1.531, generator_dur_loss=1.732, generator_adv_loss=1.942, generator_feat_match_loss=6.41, over 50.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 00:09:01,136 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 00:09:08,772 INFO [train.py:591] (2/6) Epoch 701, validation: discriminator_loss=2.773, discriminator_real_loss=1.408, discriminator_fake_loss=1.366, generator_loss=26.99, generator_mel_loss=17.93, generator_kl_loss=1.158, generator_dur_loss=1.813, generator_adv_loss=1.858, generator_feat_match_loss=4.228, over 100.00 samples.
2024-03-15 00:09:08,774 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 00:11:26,792 INFO [train.py:527] (2/6) Epoch 701, batch 50, global_batch_idx: 86850, batch size: 58, loss[discriminator_loss=2.685, discriminator_real_loss=1.464, discriminator_fake_loss=1.22, generator_loss=27.68, generator_mel_loss=17.32, generator_kl_loss=1.212, generator_dur_loss=1.735, generator_adv_loss=2.021, generator_feat_match_loss=5.397, over 58.00 samples.], tot_loss[discriminator_loss=2.701, discriminator_real_loss=1.364, discriminator_fake_loss=1.337, generator_loss=28.73, generator_mel_loss=17.89, generator_kl_loss=1.415, generator_dur_loss=1.761, generator_adv_loss=1.998, generator_feat_match_loss=5.674, over 3038.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 00:13:42,903 INFO [train.py:527] (2/6) Epoch 701, batch 100, global_batch_idx: 86900, batch size: 74, loss[discriminator_loss=2.742, discriminator_real_loss=1.427, discriminator_fake_loss=1.315, generator_loss=27.91, generator_mel_loss=17.56, generator_kl_loss=1.347, generator_dur_loss=1.78, generator_adv_loss=1.866, generator_feat_match_loss=5.354, over 74.00 samples.], tot_loss[discriminator_loss=2.7, discriminator_real_loss=1.367, discriminator_fake_loss=1.333, generator_loss=28.67, generator_mel_loss=17.9, generator_kl_loss=1.43, generator_dur_loss=1.738, generator_adv_loss=1.985, generator_feat_match_loss=5.617, over 5935.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 00:14:51,884 INFO [train.py:919] (2/6) Start epoch 702
2024-03-15 00:16:27,449 INFO [train.py:527] (2/6) Epoch 702, batch 26, global_batch_idx: 86950, batch size: 68, loss[discriminator_loss=2.669, discriminator_real_loss=1.361, discriminator_fake_loss=1.308, generator_loss=28.54, generator_mel_loss=18.15, generator_kl_loss=1.48, generator_dur_loss=1.692, generator_adv_loss=1.944, generator_feat_match_loss=5.273, over 68.00 samples.], tot_loss[discriminator_loss=2.687, discriminator_real_loss=1.357, discriminator_fake_loss=1.331, generator_loss=28.9, generator_mel_loss=18.07, generator_kl_loss=1.394, generator_dur_loss=1.734, generator_adv_loss=1.978, generator_feat_match_loss=5.73, over 1559.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 00:18:46,792 INFO [train.py:527] (2/6) Epoch 702, batch 76, global_batch_idx: 87000, batch size: 70, loss[discriminator_loss=2.692, discriminator_real_loss=1.322, discriminator_fake_loss=1.37, generator_loss=29.37, generator_mel_loss=17.81, generator_kl_loss=1.475, generator_dur_loss=1.775, generator_adv_loss=2.006, generator_feat_match_loss=6.3, over 70.00 samples.], tot_loss[discriminator_loss=2.689, discriminator_real_loss=1.357, discriminator_fake_loss=1.331, generator_loss=28.74, generator_mel_loss=17.96, generator_kl_loss=1.422, generator_dur_loss=1.741, generator_adv_loss=1.973, generator_feat_match_loss=5.643, over 4546.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 00:18:46,794 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 00:18:55,636 INFO [train.py:591] (2/6) Epoch 702, validation: discriminator_loss=2.731, discriminator_real_loss=1.453, discriminator_fake_loss=1.278, generator_loss=26.92, generator_mel_loss=17.75, generator_kl_loss=1.205, generator_dur_loss=1.808, generator_adv_loss=1.981, generator_feat_match_loss=4.181, over 100.00 samples.
2024-03-15 00:18:55,637 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 00:21:07,794 INFO [train.py:919] (2/6) Start epoch 703
2024-03-15 00:21:37,914 INFO [train.py:527] (2/6) Epoch 703, batch 2, global_batch_idx: 87050, batch size: 83, loss[discriminator_loss=2.725, discriminator_real_loss=1.292, discriminator_fake_loss=1.433, generator_loss=28.87, generator_mel_loss=18, generator_kl_loss=1.271, generator_dur_loss=1.832, generator_adv_loss=2.037, generator_feat_match_loss=5.737, over 83.00 samples.], tot_loss[discriminator_loss=2.714, discriminator_real_loss=1.332, discriminator_fake_loss=1.381, generator_loss=28.86, generator_mel_loss=17.93, generator_kl_loss=1.415, generator_dur_loss=1.759, generator_adv_loss=1.983, generator_feat_match_loss=5.773, over 192.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 00:23:57,427 INFO [train.py:527] (2/6) Epoch 703, batch 52, global_batch_idx: 87100, batch size: 72, loss[discriminator_loss=2.692, discriminator_real_loss=1.374, discriminator_fake_loss=1.318, generator_loss=28.07, generator_mel_loss=17.47, generator_kl_loss=1.441, generator_dur_loss=1.787, generator_adv_loss=1.938, generator_feat_match_loss=5.438, over 72.00 samples.], tot_loss[discriminator_loss=2.701, discriminator_real_loss=1.369, discriminator_fake_loss=1.331, generator_loss=28.56, generator_mel_loss=17.9, generator_kl_loss=1.43, generator_dur_loss=1.722, generator_adv_loss=1.979, generator_feat_match_loss=5.537, over 2951.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 00:26:16,244 INFO [train.py:527] (2/6) Epoch 703, batch 102, global_batch_idx: 87150, batch size: 48, loss[discriminator_loss=2.731, discriminator_real_loss=1.328, discriminator_fake_loss=1.403, generator_loss=29.21, generator_mel_loss=18.79, generator_kl_loss=1.646, generator_dur_loss=1.689, generator_adv_loss=1.886, generator_feat_match_loss=5.201, over 48.00 samples.], tot_loss[discriminator_loss=2.7, discriminator_real_loss=1.372, discriminator_fake_loss=1.328, generator_loss=28.68, generator_mel_loss=17.94, generator_kl_loss=1.433, generator_dur_loss=1.73, generator_adv_loss=1.981, generator_feat_match_loss=5.602, over 5618.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 00:27:15,614 INFO [train.py:919] (2/6) Start epoch 704
2024-03-15 00:28:54,994 INFO [train.py:527] (2/6) Epoch 704, batch 28, global_batch_idx: 87200, batch size: 42, loss[discriminator_loss=2.678, discriminator_real_loss=1.367, discriminator_fake_loss=1.311, generator_loss=28.68, generator_mel_loss=18.09, generator_kl_loss=1.523, generator_dur_loss=1.671, generator_adv_loss=1.839, generator_feat_match_loss=5.557, over 42.00 samples.], tot_loss[discriminator_loss=2.705, discriminator_real_loss=1.365, discriminator_fake_loss=1.34, generator_loss=28.63, generator_mel_loss=17.9, generator_kl_loss=1.452, generator_dur_loss=1.727, generator_adv_loss=1.967, generator_feat_match_loss=5.576, over 1508.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 00:28:54,996 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 00:29:02,881 INFO [train.py:591] (2/6) Epoch 704, validation: discriminator_loss=2.716, discriminator_real_loss=1.348, discriminator_fake_loss=1.368, generator_loss=27.35, generator_mel_loss=17.63, generator_kl_loss=1.321, generator_dur_loss=1.806, generator_adv_loss=1.855, generator_feat_match_loss=4.73, over 100.00 samples.
2024-03-15 00:29:02,882 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 00:31:24,697 INFO [train.py:527] (2/6) Epoch 704, batch 78, global_batch_idx: 87250, batch size: 62, loss[discriminator_loss=2.658, discriminator_real_loss=1.242, discriminator_fake_loss=1.416, generator_loss=29.97, generator_mel_loss=18.03, generator_kl_loss=1.482, generator_dur_loss=1.764, generator_adv_loss=2.197, generator_feat_match_loss=6.5, over 62.00 samples.], tot_loss[discriminator_loss=2.693, discriminator_real_loss=1.355, discriminator_fake_loss=1.338, generator_loss=28.75, generator_mel_loss=17.9, generator_kl_loss=1.43, generator_dur_loss=1.736, generator_adv_loss=1.978, generator_feat_match_loss=5.704, over 4395.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 00:33:33,012 INFO [train.py:919] (2/6) Start epoch 705
2024-03-15 00:34:08,448 INFO [train.py:527] (2/6) Epoch 705, batch 4, global_batch_idx: 87300, batch size: 61, loss[discriminator_loss=2.7, discriminator_real_loss=1.361, discriminator_fake_loss=1.339, generator_loss=28.88, generator_mel_loss=18.26, generator_kl_loss=1.5, generator_dur_loss=1.705, generator_adv_loss=2.013, generator_feat_match_loss=5.396, over 61.00 samples.], tot_loss[discriminator_loss=2.714, discriminator_real_loss=1.401, discriminator_fake_loss=1.314, generator_loss=27.98, generator_mel_loss=17.74, generator_kl_loss=1.474, generator_dur_loss=1.74, generator_adv_loss=1.957, generator_feat_match_loss=5.07, over 320.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 00:36:28,294 INFO [train.py:527] (2/6) Epoch 705, batch 54, global_batch_idx: 87350, batch size: 47, loss[discriminator_loss=2.709, discriminator_real_loss=1.401, discriminator_fake_loss=1.308, generator_loss=28.73, generator_mel_loss=18.39, generator_kl_loss=1.458, generator_dur_loss=1.68, generator_adv_loss=1.795, generator_feat_match_loss=5.404, over 47.00 samples.], tot_loss[discriminator_loss=2.698, discriminator_real_loss=1.369, discriminator_fake_loss=1.329, generator_loss=28.6, generator_mel_loss=17.93, generator_kl_loss=1.446, generator_dur_loss=1.713, generator_adv_loss=1.974, generator_feat_match_loss=5.537, over 2987.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 00:38:47,708 INFO [train.py:527] (2/6) Epoch 705, batch 104, global_batch_idx: 87400, batch size: 74, loss[discriminator_loss=2.693, discriminator_real_loss=1.388, discriminator_fake_loss=1.305, generator_loss=28.1, generator_mel_loss=17.72, generator_kl_loss=1.396, generator_dur_loss=1.771, generator_adv_loss=1.908, generator_feat_match_loss=5.312, over 74.00 samples.], tot_loss[discriminator_loss=2.697, discriminator_real_loss=1.369, discriminator_fake_loss=1.329, generator_loss=28.68, generator_mel_loss=17.95, generator_kl_loss=1.429, generator_dur_loss=1.71, generator_adv_loss=1.979, generator_feat_match_loss=5.616, over 5765.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 00:38:47,710 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 00:38:56,479 INFO [train.py:591] (2/6) Epoch 705, validation: discriminator_loss=2.711, discriminator_real_loss=1.31, discriminator_fake_loss=1.4, generator_loss=27, generator_mel_loss=18, generator_kl_loss=1.117, generator_dur_loss=1.766, generator_adv_loss=1.803, generator_feat_match_loss=4.321, over 100.00 samples.
2024-03-15 00:38:56,480 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 00:39:49,209 INFO [train.py:919] (2/6) Start epoch 706
2024-03-15 00:41:36,837 INFO [train.py:527] (2/6) Epoch 706, batch 30, global_batch_idx: 87450, batch size: 72, loss[discriminator_loss=2.707, discriminator_real_loss=1.346, discriminator_fake_loss=1.361, generator_loss=29.37, generator_mel_loss=18.37, generator_kl_loss=1.398, generator_dur_loss=1.775, generator_adv_loss=1.869, generator_feat_match_loss=5.957, over 72.00 samples.], tot_loss[discriminator_loss=2.674, discriminator_real_loss=1.337, discriminator_fake_loss=1.337, generator_loss=28.7, generator_mel_loss=17.94, generator_kl_loss=1.42, generator_dur_loss=1.718, generator_adv_loss=1.982, generator_feat_match_loss=5.642, over 1710.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 00:43:57,085 INFO [train.py:527] (2/6) Epoch 706, batch 80, global_batch_idx: 87500, batch size: 15, loss[discriminator_loss=2.691, discriminator_real_loss=1.33, discriminator_fake_loss=1.362, generator_loss=29.69, generator_mel_loss=18.25, generator_kl_loss=1.837, generator_dur_loss=1.513, generator_adv_loss=2.166, generator_feat_match_loss=5.927, over 15.00 samples.], tot_loss[discriminator_loss=2.683, discriminator_real_loss=1.351, discriminator_fake_loss=1.333, generator_loss=28.76, generator_mel_loss=17.94, generator_kl_loss=1.408, generator_dur_loss=1.723, generator_adv_loss=1.985, generator_feat_match_loss=5.706, over 4681.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 00:45:56,663 INFO [train.py:919] (2/6) Start epoch 707
2024-03-15 00:46:35,728 INFO [train.py:527] (2/6) Epoch 707, batch 6, global_batch_idx: 87550, batch size: 58, loss[discriminator_loss=2.677, discriminator_real_loss=1.411, discriminator_fake_loss=1.266, generator_loss=27.55, generator_mel_loss=17.03, generator_kl_loss=1.409, generator_dur_loss=1.719, generator_adv_loss=1.962, generator_feat_match_loss=5.426, over 58.00 samples.], tot_loss[discriminator_loss=2.665, discriminator_real_loss=1.348, discriminator_fake_loss=1.316, generator_loss=29.09, generator_mel_loss=17.88, generator_kl_loss=1.435, generator_dur_loss=1.741, generator_adv_loss=2.027, generator_feat_match_loss=5.998, over 442.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 00:48:55,421 INFO [train.py:527] (2/6) Epoch 707, batch 56, global_batch_idx: 87600, batch size: 47, loss[discriminator_loss=2.636, discriminator_real_loss=1.32, discriminator_fake_loss=1.316, generator_loss=28.81, generator_mel_loss=17.69, generator_kl_loss=1.513, generator_dur_loss=1.684, generator_adv_loss=1.976, generator_feat_match_loss=5.947, over 47.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.359, discriminator_fake_loss=1.325, generator_loss=28.81, generator_mel_loss=17.93, generator_kl_loss=1.421, generator_dur_loss=1.74, generator_adv_loss=1.995, generator_feat_match_loss=5.719, over 3522.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 00:48:55,423 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 00:49:03,328 INFO [train.py:591] (2/6) Epoch 707, validation: discriminator_loss=2.718, discriminator_real_loss=1.365, discriminator_fake_loss=1.353, generator_loss=28.44, generator_mel_loss=18.22, generator_kl_loss=1.361, generator_dur_loss=1.792, generator_adv_loss=1.916, generator_feat_match_loss=5.142, over 100.00 samples.
2024-03-15 00:49:03,329 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 00:51:23,089 INFO [train.py:527] (2/6) Epoch 707, batch 106, global_batch_idx: 87650, batch size: 39, loss[discriminator_loss=2.627, discriminator_real_loss=1.349, discriminator_fake_loss=1.277, generator_loss=28.95, generator_mel_loss=17.78, generator_kl_loss=1.648, generator_dur_loss=1.699, generator_adv_loss=1.886, generator_feat_match_loss=5.933, over 39.00 samples.], tot_loss[discriminator_loss=2.687, discriminator_real_loss=1.36, discriminator_fake_loss=1.326, generator_loss=28.8, generator_mel_loss=17.9, generator_kl_loss=1.428, generator_dur_loss=1.74, generator_adv_loss=1.989, generator_feat_match_loss=5.742, over 6500.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 00:52:08,691 INFO [train.py:919] (2/6) Start epoch 708
2024-03-15 00:54:01,638 INFO [train.py:527] (2/6) Epoch 708, batch 32, global_batch_idx: 87700, batch size: 45, loss[discriminator_loss=2.63, discriminator_real_loss=1.339, discriminator_fake_loss=1.291, generator_loss=28.52, generator_mel_loss=17.94, generator_kl_loss=1.47, generator_dur_loss=1.693, generator_adv_loss=1.942, generator_feat_match_loss=5.474, over 45.00 samples.], tot_loss[discriminator_loss=2.681, discriminator_real_loss=1.362, discriminator_fake_loss=1.319, generator_loss=28.84, generator_mel_loss=18, generator_kl_loss=1.441, generator_dur_loss=1.746, generator_adv_loss=1.988, generator_feat_match_loss=5.666, over 1910.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 00:56:16,817 INFO [train.py:527] (2/6) Epoch 708, batch 82, global_batch_idx: 87750, batch size: 52, loss[discriminator_loss=2.679, discriminator_real_loss=1.402, discriminator_fake_loss=1.277, generator_loss=29.24, generator_mel_loss=17.88, generator_kl_loss=1.541, generator_dur_loss=1.644, generator_adv_loss=1.995, generator_feat_match_loss=6.174, over 52.00 samples.], tot_loss[discriminator_loss=2.686, discriminator_real_loss=1.357, discriminator_fake_loss=1.329, generator_loss=28.78, generator_mel_loss=17.92, generator_kl_loss=1.437, generator_dur_loss=1.743, generator_adv_loss=1.989, generator_feat_match_loss=5.693, over 4789.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 00:58:15,907 INFO [train.py:919] (2/6) Start epoch 709
2024-03-15 00:59:02,277 INFO [train.py:527] (2/6) Epoch 709, batch 8, global_batch_idx: 87800, batch size: 83, loss[discriminator_loss=2.698, discriminator_real_loss=1.418, discriminator_fake_loss=1.28, generator_loss=28.55, generator_mel_loss=17.83, generator_kl_loss=1.429, generator_dur_loss=1.783, generator_adv_loss=1.967, generator_feat_match_loss=5.539, over 83.00 samples.], tot_loss[discriminator_loss=2.695, discriminator_real_loss=1.373, discriminator_fake_loss=1.322, generator_loss=28.71, generator_mel_loss=17.89, generator_kl_loss=1.417, generator_dur_loss=1.736, generator_adv_loss=2.004, generator_feat_match_loss=5.666, over 539.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 00:59:02,294 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 00:59:10,127 INFO [train.py:591] (2/6) Epoch 709, validation: discriminator_loss=2.722, discriminator_real_loss=1.349, discriminator_fake_loss=1.373, generator_loss=27.44, generator_mel_loss=18.06, generator_kl_loss=1.264, generator_dur_loss=1.792, generator_adv_loss=1.873, generator_feat_match_loss=4.445, over 100.00 samples.
2024-03-15 00:59:10,127 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 01:01:30,085 INFO [train.py:527] (2/6) Epoch 709, batch 58, global_batch_idx: 87850, batch size: 80, loss[discriminator_loss=2.655, discriminator_real_loss=1.372, discriminator_fake_loss=1.283, generator_loss=28.79, generator_mel_loss=17.84, generator_kl_loss=1.367, generator_dur_loss=1.751, generator_adv_loss=2.022, generator_feat_match_loss=5.807, over 80.00 samples.], tot_loss[discriminator_loss=2.691, discriminator_real_loss=1.359, discriminator_fake_loss=1.332, generator_loss=28.81, generator_mel_loss=17.95, generator_kl_loss=1.408, generator_dur_loss=1.73, generator_adv_loss=1.996, generator_feat_match_loss=5.721, over 3459.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 01:03:45,845 INFO [train.py:527] (2/6) Epoch 709, batch 108, global_batch_idx: 87900, batch size: 25, loss[discriminator_loss=2.566, discriminator_real_loss=1.361, discriminator_fake_loss=1.205, generator_loss=29.87, generator_mel_loss=18.65, generator_kl_loss=1.778, generator_dur_loss=1.534, generator_adv_loss=2.11, generator_feat_match_loss=5.799, over 25.00 samples.], tot_loss[discriminator_loss=2.69, discriminator_real_loss=1.359, discriminator_fake_loss=1.331, generator_loss=28.76, generator_mel_loss=17.93, generator_kl_loss=1.422, generator_dur_loss=1.724, generator_adv_loss=1.997, generator_feat_match_loss=5.689, over 6225.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 01:04:30,345 INFO [train.py:919] (2/6) Start epoch 710
2024-03-15 01:06:28,069 INFO [train.py:527] (2/6) Epoch 710, batch 34, global_batch_idx: 87950, batch size: 74, loss[discriminator_loss=2.652, discriminator_real_loss=1.4, discriminator_fake_loss=1.252, generator_loss=28.95, generator_mel_loss=17.86, generator_kl_loss=1.351, generator_dur_loss=1.779, generator_adv_loss=2.053, generator_feat_match_loss=5.899, over 74.00 samples.], tot_loss[discriminator_loss=2.682, discriminator_real_loss=1.362, discriminator_fake_loss=1.319, generator_loss=28.71, generator_mel_loss=17.87, generator_kl_loss=1.435, generator_dur_loss=1.736, generator_adv_loss=2.006, generator_feat_match_loss=5.665, over 1921.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 01:08:49,102 INFO [train.py:527] (2/6) Epoch 710, batch 84, global_batch_idx: 88000, batch size: 53, loss[discriminator_loss=2.686, discriminator_real_loss=1.419, discriminator_fake_loss=1.267, generator_loss=28.48, generator_mel_loss=17.55, generator_kl_loss=1.47, generator_dur_loss=1.671, generator_adv_loss=2, generator_feat_match_loss=5.791, over 53.00 samples.], tot_loss[discriminator_loss=2.688, discriminator_real_loss=1.361, discriminator_fake_loss=1.327, generator_loss=28.81, generator_mel_loss=17.93, generator_kl_loss=1.432, generator_dur_loss=1.74, generator_adv_loss=1.993, generator_feat_match_loss=5.716, over 4835.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 01:08:49,104 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 01:08:57,852 INFO [train.py:591] (2/6) Epoch 710, validation: discriminator_loss=2.703, discriminator_real_loss=1.4, discriminator_fake_loss=1.303, generator_loss=28.46, generator_mel_loss=18.24, generator_kl_loss=1.254, generator_dur_loss=1.804, generator_adv_loss=1.891, generator_feat_match_loss=5.269, over 100.00 samples.
2024-03-15 01:08:57,854 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 01:10:45,300 INFO [train.py:919] (2/6) Start epoch 711
2024-03-15 01:11:37,008 INFO [train.py:527] (2/6) Epoch 711, batch 10, global_batch_idx: 88050, batch size: 77, loss[discriminator_loss=2.76, discriminator_real_loss=1.368, discriminator_fake_loss=1.392, generator_loss=28.33, generator_mel_loss=17.44, generator_kl_loss=1.404, generator_dur_loss=1.832, generator_adv_loss=2.219, generator_feat_match_loss=5.436, over 77.00 samples.], tot_loss[discriminator_loss=2.651, discriminator_real_loss=1.36, discriminator_fake_loss=1.291, generator_loss=29.07, generator_mel_loss=17.7, generator_kl_loss=1.451, generator_dur_loss=1.757, generator_adv_loss=2.224, generator_feat_match_loss=5.939, over 660.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 01:13:57,387 INFO [train.py:527] (2/6) Epoch 711, batch 60, global_batch_idx: 88100, batch size: 96, loss[discriminator_loss=2.637, discriminator_real_loss=1.258, discriminator_fake_loss=1.379, generator_loss=28.69, generator_mel_loss=17.39, generator_kl_loss=1.411, generator_dur_loss=1.849, generator_adv_loss=2.015, generator_feat_match_loss=6.021, over 96.00 samples.], tot_loss[discriminator_loss=2.672, discriminator_real_loss=1.355, discriminator_fake_loss=1.317, generator_loss=28.92, generator_mel_loss=17.91, generator_kl_loss=1.43, generator_dur_loss=1.744, generator_adv_loss=2.055, generator_feat_match_loss=5.785, over 3541.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 01:16:14,966 INFO [train.py:527] (2/6) Epoch 711, batch 110, global_batch_idx: 88150, batch size: 59, loss[discriminator_loss=2.688, discriminator_real_loss=1.363, discriminator_fake_loss=1.325, generator_loss=28.98, generator_mel_loss=17.65, generator_kl_loss=1.451, generator_dur_loss=1.706, generator_adv_loss=2.149, generator_feat_match_loss=6.023, over 59.00 samples.], tot_loss[discriminator_loss=2.679, discriminator_real_loss=1.358, discriminator_fake_loss=1.32, generator_loss=28.88, generator_mel_loss=17.91, generator_kl_loss=1.436, generator_dur_loss=1.739, generator_adv_loss=2.028, generator_feat_match_loss=5.772, over 6243.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 01:16:50,935 INFO [train.py:919] (2/6) Start epoch 712
2024-03-15 01:18:56,816 INFO [train.py:527] (2/6) Epoch 712, batch 36, global_batch_idx: 88200, batch size: 80, loss[discriminator_loss=2.722, discriminator_real_loss=1.356, discriminator_fake_loss=1.366, generator_loss=28.8, generator_mel_loss=17.83, generator_kl_loss=1.336, generator_dur_loss=1.824, generator_adv_loss=1.917, generator_feat_match_loss=5.896, over 80.00 samples.], tot_loss[discriminator_loss=2.688, discriminator_real_loss=1.357, discriminator_fake_loss=1.331, generator_loss=28.91, generator_mel_loss=17.96, generator_kl_loss=1.431, generator_dur_loss=1.737, generator_adv_loss=1.977, generator_feat_match_loss=5.802, over 2162.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 01:18:56,818 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 01:19:04,760 INFO [train.py:591] (2/6) Epoch 712, validation: discriminator_loss=2.741, discriminator_real_loss=1.424, discriminator_fake_loss=1.318, generator_loss=27.55, generator_mel_loss=18.3, generator_kl_loss=1.286, generator_dur_loss=1.807, generator_adv_loss=1.945, generator_feat_match_loss=4.211, over 100.00 samples.
2024-03-15 01:19:04,761 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 01:21:21,804 INFO [train.py:527] (2/6) Epoch 712, batch 86, global_batch_idx: 88250, batch size: 64, loss[discriminator_loss=2.689, discriminator_real_loss=1.302, discriminator_fake_loss=1.387, generator_loss=28.96, generator_mel_loss=17.91, generator_kl_loss=1.524, generator_dur_loss=1.712, generator_adv_loss=2.121, generator_feat_match_loss=5.686, over 64.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.356, discriminator_fake_loss=1.328, generator_loss=28.82, generator_mel_loss=17.93, generator_kl_loss=1.443, generator_dur_loss=1.726, generator_adv_loss=1.984, generator_feat_match_loss=5.73, over 4851.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 01:23:08,486 INFO [train.py:919] (2/6) Start epoch 713
2024-03-15 01:24:05,815 INFO [train.py:527] (2/6) Epoch 713, batch 12, global_batch_idx: 88300, batch size: 31, loss[discriminator_loss=2.689, discriminator_real_loss=1.349, discriminator_fake_loss=1.34, generator_loss=28.5, generator_mel_loss=18, generator_kl_loss=1.619, generator_dur_loss=1.614, generator_adv_loss=1.955, generator_feat_match_loss=5.309, over 31.00 samples.], tot_loss[discriminator_loss=2.697, discriminator_real_loss=1.38, discriminator_fake_loss=1.317, generator_loss=28.84, generator_mel_loss=17.98, generator_kl_loss=1.459, generator_dur_loss=1.713, generator_adv_loss=2.008, generator_feat_match_loss=5.682, over 656.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 01:26:24,685 INFO [train.py:527] (2/6) Epoch 713, batch 62, global_batch_idx: 88350, batch size: 52, loss[discriminator_loss=2.672, discriminator_real_loss=1.372, discriminator_fake_loss=1.301, generator_loss=28.65, generator_mel_loss=17.92, generator_kl_loss=1.417, generator_dur_loss=1.7, generator_adv_loss=2.256, generator_feat_match_loss=5.355, over 52.00 samples.], tot_loss[discriminator_loss=2.695, discriminator_real_loss=1.365, discriminator_fake_loss=1.33, generator_loss=28.8, generator_mel_loss=17.95, generator_kl_loss=1.444, generator_dur_loss=1.737, generator_adv_loss=1.992, generator_feat_match_loss=5.681, over 3373.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 01:28:42,480 INFO [train.py:527] (2/6) Epoch 713, batch 112, global_batch_idx: 88400, batch size: 39, loss[discriminator_loss=2.72, discriminator_real_loss=1.374, discriminator_fake_loss=1.346, generator_loss=28.07, generator_mel_loss=17.54, generator_kl_loss=1.496, generator_dur_loss=1.667, generator_adv_loss=1.932, generator_feat_match_loss=5.442, over 39.00 samples.], tot_loss[discriminator_loss=2.693, discriminator_real_loss=1.365, discriminator_fake_loss=1.328, generator_loss=28.8, generator_mel_loss=17.95, generator_kl_loss=1.434, generator_dur_loss=1.741, generator_adv_loss=1.99, generator_feat_match_loss=5.691, over 6262.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 01:28:42,482 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 01:28:51,052 INFO [train.py:591] (2/6) Epoch 713, validation: discriminator_loss=2.737, discriminator_real_loss=1.362, discriminator_fake_loss=1.375, generator_loss=27.91, generator_mel_loss=18.27, generator_kl_loss=1.279, generator_dur_loss=1.808, generator_adv_loss=1.828, generator_feat_match_loss=4.725, over 100.00 samples.
2024-03-15 01:28:51,053 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 01:29:23,105 INFO [train.py:919] (2/6) Start epoch 714
2024-03-15 01:31:29,657 INFO [train.py:527] (2/6) Epoch 714, batch 38, global_batch_idx: 88450, batch size: 77, loss[discriminator_loss=2.674, discriminator_real_loss=1.359, discriminator_fake_loss=1.315, generator_loss=29.21, generator_mel_loss=17.78, generator_kl_loss=1.281, generator_dur_loss=1.817, generator_adv_loss=2.004, generator_feat_match_loss=6.326, over 77.00 samples.], tot_loss[discriminator_loss=2.707, discriminator_real_loss=1.372, discriminator_fake_loss=1.335, generator_loss=28.45, generator_mel_loss=17.82, generator_kl_loss=1.416, generator_dur_loss=1.743, generator_adv_loss=1.978, generator_feat_match_loss=5.487, over 2202.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 01:33:51,462 INFO [train.py:527] (2/6) Epoch 714, batch 88, global_batch_idx: 88500, batch size: 25, loss[discriminator_loss=2.653, discriminator_real_loss=1.254, discriminator_fake_loss=1.399, generator_loss=30.99, generator_mel_loss=18.19, generator_kl_loss=1.782, generator_dur_loss=1.607, generator_adv_loss=1.952, generator_feat_match_loss=7.466, over 25.00 samples.], tot_loss[discriminator_loss=2.702, discriminator_real_loss=1.368, discriminator_fake_loss=1.333, generator_loss=28.68, generator_mel_loss=17.83, generator_kl_loss=1.413, generator_dur_loss=1.752, generator_adv_loss=2.021, generator_feat_match_loss=5.666, over 5055.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 01:35:29,532 INFO [train.py:919] (2/6) Start epoch 715
2024-03-15 01:36:33,264 INFO [train.py:527] (2/6) Epoch 715, batch 14, global_batch_idx: 88550, batch size: 56, loss[discriminator_loss=2.656, discriminator_real_loss=1.348, discriminator_fake_loss=1.308, generator_loss=28.06, generator_mel_loss=17.4, generator_kl_loss=1.405, generator_dur_loss=1.748, generator_adv_loss=2.063, generator_feat_match_loss=5.44, over 56.00 samples.], tot_loss[discriminator_loss=2.673, discriminator_real_loss=1.351, discriminator_fake_loss=1.322, generator_loss=28.79, generator_mel_loss=17.91, generator_kl_loss=1.396, generator_dur_loss=1.761, generator_adv_loss=1.981, generator_feat_match_loss=5.747, over 882.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 01:38:51,256 INFO [train.py:527] (2/6) Epoch 715, batch 64, global_batch_idx: 88600, batch size: 64, loss[discriminator_loss=2.651, discriminator_real_loss=1.31, discriminator_fake_loss=1.341, generator_loss=28.25, generator_mel_loss=17.61, generator_kl_loss=1.378, generator_dur_loss=1.793, generator_adv_loss=1.9, generator_feat_match_loss=5.574, over 64.00 samples.], tot_loss[discriminator_loss=2.683, discriminator_real_loss=1.353, discriminator_fake_loss=1.329, generator_loss=28.76, generator_mel_loss=17.89, generator_kl_loss=1.406, generator_dur_loss=1.751, generator_adv_loss=1.969, generator_feat_match_loss=5.745, over 3699.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 01:38:51,257 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 01:38:59,984 INFO [train.py:591] (2/6) Epoch 715, validation: discriminator_loss=2.713, discriminator_real_loss=1.368, discriminator_fake_loss=1.345, generator_loss=27.33, generator_mel_loss=18.22, generator_kl_loss=1.306, generator_dur_loss=1.798, generator_adv_loss=1.841, generator_feat_match_loss=4.168, over 100.00 samples.
2024-03-15 01:38:59,985 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 01:41:17,088 INFO [train.py:527] (2/6) Epoch 715, batch 114, global_batch_idx: 88650, batch size: 66, loss[discriminator_loss=2.696, discriminator_real_loss=1.281, discriminator_fake_loss=1.415, generator_loss=29.07, generator_mel_loss=17.97, generator_kl_loss=1.443, generator_dur_loss=1.785, generator_adv_loss=2.063, generator_feat_match_loss=5.808, over 66.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.358, discriminator_fake_loss=1.326, generator_loss=28.73, generator_mel_loss=17.88, generator_kl_loss=1.417, generator_dur_loss=1.744, generator_adv_loss=1.979, generator_feat_match_loss=5.712, over 6433.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 01:41:44,389 INFO [train.py:919] (2/6) Start epoch 716
2024-03-15 01:44:01,671 INFO [train.py:527] (2/6) Epoch 716, batch 40, global_batch_idx: 88700, batch size: 72, loss[discriminator_loss=2.674, discriminator_real_loss=1.398, discriminator_fake_loss=1.276, generator_loss=28.24, generator_mel_loss=17.73, generator_kl_loss=1.311, generator_dur_loss=1.823, generator_adv_loss=1.927, generator_feat_match_loss=5.455, over 72.00 samples.], tot_loss[discriminator_loss=2.678, discriminator_real_loss=1.348, discriminator_fake_loss=1.33, generator_loss=28.82, generator_mel_loss=17.97, generator_kl_loss=1.414, generator_dur_loss=1.761, generator_adv_loss=1.982, generator_feat_match_loss=5.698, over 2384.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 01:46:19,757 INFO [train.py:527] (2/6) Epoch 716, batch 90, global_batch_idx: 88750, batch size: 64, loss[discriminator_loss=2.695, discriminator_real_loss=1.346, discriminator_fake_loss=1.349, generator_loss=28.44, generator_mel_loss=17.87, generator_kl_loss=1.269, generator_dur_loss=1.724, generator_adv_loss=2.017, generator_feat_match_loss=5.567, over 64.00 samples.], tot_loss[discriminator_loss=2.683, discriminator_real_loss=1.354, discriminator_fake_loss=1.329, generator_loss=28.79, generator_mel_loss=17.91, generator_kl_loss=1.403, generator_dur_loss=1.762, generator_adv_loss=1.985, generator_feat_match_loss=5.739, over 5421.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 01:47:50,039 INFO [train.py:919] (2/6) Start epoch 717
2024-03-15 01:48:57,856 INFO [train.py:527] (2/6) Epoch 717, batch 16, global_batch_idx: 88800, batch size: 74, loss[discriminator_loss=2.708, discriminator_real_loss=1.297, discriminator_fake_loss=1.41, generator_loss=29.05, generator_mel_loss=18.28, generator_kl_loss=1.254, generator_dur_loss=1.777, generator_adv_loss=2.084, generator_feat_match_loss=5.658, over 74.00 samples.], tot_loss[discriminator_loss=2.706, discriminator_real_loss=1.369, discriminator_fake_loss=1.337, generator_loss=28.61, generator_mel_loss=17.86, generator_kl_loss=1.422, generator_dur_loss=1.735, generator_adv_loss=1.979, generator_feat_match_loss=5.612, over 946.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 01:48:57,857 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 01:49:05,800 INFO [train.py:591] (2/6) Epoch 717, validation: discriminator_loss=2.746, discriminator_real_loss=1.555, discriminator_fake_loss=1.192, generator_loss=28.01, generator_mel_loss=18.04, generator_kl_loss=1.166, generator_dur_loss=1.807, generator_adv_loss=2.09, generator_feat_match_loss=4.911, over 100.00 samples.
2024-03-15 01:49:05,801 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 01:51:22,279 INFO [train.py:527] (2/6) Epoch 717, batch 66, global_batch_idx: 88850, batch size: 77, loss[discriminator_loss=2.701, discriminator_real_loss=1.313, discriminator_fake_loss=1.388, generator_loss=28.83, generator_mel_loss=17.69, generator_kl_loss=1.242, generator_dur_loss=1.836, generator_adv_loss=2.014, generator_feat_match_loss=6.057, over 77.00 samples.], tot_loss[discriminator_loss=2.692, discriminator_real_loss=1.363, discriminator_fake_loss=1.328, generator_loss=28.81, generator_mel_loss=17.9, generator_kl_loss=1.404, generator_dur_loss=1.759, generator_adv_loss=1.98, generator_feat_match_loss=5.769, over 3936.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 01:53:43,575 INFO [train.py:527] (2/6) Epoch 717, batch 116, global_batch_idx: 88900, batch size: 25, loss[discriminator_loss=2.662, discriminator_real_loss=1.352, discriminator_fake_loss=1.31, generator_loss=30.26, generator_mel_loss=18.08, generator_kl_loss=1.801, generator_dur_loss=1.587, generator_adv_loss=1.84, generator_feat_match_loss=6.953, over 25.00 samples.], tot_loss[discriminator_loss=2.697, discriminator_real_loss=1.364, discriminator_fake_loss=1.333, generator_loss=28.78, generator_mel_loss=17.88, generator_kl_loss=1.418, generator_dur_loss=1.756, generator_adv_loss=1.978, generator_feat_match_loss=5.755, over 6685.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 01:54:04,077 INFO [train.py:919] (2/6) Start epoch 718
2024-03-15 01:56:26,070 INFO [train.py:527] (2/6) Epoch 718, batch 42, global_batch_idx: 88950, batch size: 70, loss[discriminator_loss=2.677, discriminator_real_loss=1.394, discriminator_fake_loss=1.283, generator_loss=30.37, generator_mel_loss=18.3, generator_kl_loss=1.323, generator_dur_loss=1.799, generator_adv_loss=2.25, generator_feat_match_loss=6.705, over 70.00 samples.], tot_loss[discriminator_loss=2.691, discriminator_real_loss=1.361, discriminator_fake_loss=1.33, generator_loss=28.9, generator_mel_loss=17.88, generator_kl_loss=1.396, generator_dur_loss=1.762, generator_adv_loss=2.041, generator_feat_match_loss=5.819, over 2570.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 01:58:45,617 INFO [train.py:527] (2/6) Epoch 718, batch 92, global_batch_idx: 89000, batch size: 36, loss[discriminator_loss=2.69, discriminator_real_loss=1.411, discriminator_fake_loss=1.279, generator_loss=28.06, generator_mel_loss=17.91, generator_kl_loss=1.532, generator_dur_loss=1.785, generator_adv_loss=1.887, generator_feat_match_loss=4.951, over 36.00 samples.], tot_loss[discriminator_loss=2.693, discriminator_real_loss=1.367, discriminator_fake_loss=1.326, generator_loss=28.75, generator_mel_loss=17.86, generator_kl_loss=1.408, generator_dur_loss=1.752, generator_adv_loss=2.023, generator_feat_match_loss=5.704, over 5261.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 01:58:45,619 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 01:58:54,590 INFO [train.py:591] (2/6) Epoch 718, validation: discriminator_loss=2.751, discriminator_real_loss=1.377, discriminator_fake_loss=1.374, generator_loss=27.9, generator_mel_loss=18.22, generator_kl_loss=1.23, generator_dur_loss=1.799, generator_adv_loss=1.831, generator_feat_match_loss=4.812, over 100.00 samples.
2024-03-15 01:58:54,590 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 02:00:21,174 INFO [train.py:919] (2/6) Start epoch 719
2024-03-15 02:01:33,165 INFO [train.py:527] (2/6) Epoch 719, batch 18, global_batch_idx: 89050, batch size: 48, loss[discriminator_loss=2.728, discriminator_real_loss=1.388, discriminator_fake_loss=1.34, generator_loss=28.89, generator_mel_loss=18.01, generator_kl_loss=1.596, generator_dur_loss=1.637, generator_adv_loss=1.945, generator_feat_match_loss=5.7, over 48.00 samples.], tot_loss[discriminator_loss=2.691, discriminator_real_loss=1.361, discriminator_fake_loss=1.33, generator_loss=28.66, generator_mel_loss=17.91, generator_kl_loss=1.355, generator_dur_loss=1.757, generator_adv_loss=1.971, generator_feat_match_loss=5.66, over 1193.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 02:03:52,422 INFO [train.py:527] (2/6) Epoch 719, batch 68, global_batch_idx: 89100, batch size: 31, loss[discriminator_loss=2.736, discriminator_real_loss=1.408, discriminator_fake_loss=1.328, generator_loss=28.48, generator_mel_loss=18.06, generator_kl_loss=1.506, generator_dur_loss=1.604, generator_adv_loss=1.877, generator_feat_match_loss=5.433, over 31.00 samples.], tot_loss[discriminator_loss=2.695, discriminator_real_loss=1.363, discriminator_fake_loss=1.332, generator_loss=28.72, generator_mel_loss=17.92, generator_kl_loss=1.399, generator_dur_loss=1.748, generator_adv_loss=1.98, generator_feat_match_loss=5.674, over 4007.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 02:06:13,079 INFO [train.py:527] (2/6) Epoch 719, batch 118, global_batch_idx: 89150, batch size: 88, loss[discriminator_loss=2.684, discriminator_real_loss=1.37, discriminator_fake_loss=1.314, generator_loss=29.27, generator_mel_loss=18.01, generator_kl_loss=1.316, generator_dur_loss=1.826, generator_adv_loss=1.821, generator_feat_match_loss=6.3, over 88.00 samples.], tot_loss[discriminator_loss=2.695, discriminator_real_loss=1.363, discriminator_fake_loss=1.332, generator_loss=28.65, generator_mel_loss=17.86, generator_kl_loss=1.388, generator_dur_loss=1.749, generator_adv_loss=1.981, generator_feat_match_loss=5.679, over 7139.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 02:06:30,361 INFO [train.py:919] (2/6) Start epoch 720
2024-03-15 02:09:00,188 INFO [train.py:527] (2/6) Epoch 720, batch 44, global_batch_idx: 89200, batch size: 13, loss[discriminator_loss=2.65, discriminator_real_loss=1.35, discriminator_fake_loss=1.3, generator_loss=30.88, generator_mel_loss=18.37, generator_kl_loss=1.958, generator_dur_loss=1.507, generator_adv_loss=2.169, generator_feat_match_loss=6.879, over 13.00 samples.], tot_loss[discriminator_loss=2.681, discriminator_real_loss=1.356, discriminator_fake_loss=1.325, generator_loss=28.75, generator_mel_loss=17.94, generator_kl_loss=1.407, generator_dur_loss=1.724, generator_adv_loss=1.992, generator_feat_match_loss=5.691, over 2569.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 02:09:00,189 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 02:09:08,034 INFO [train.py:591] (2/6) Epoch 720, validation: discriminator_loss=2.705, discriminator_real_loss=1.422, discriminator_fake_loss=1.283, generator_loss=27.27, generator_mel_loss=18.08, generator_kl_loss=1.23, generator_dur_loss=1.789, generator_adv_loss=1.945, generator_feat_match_loss=4.221, over 100.00 samples.
2024-03-15 02:09:08,035 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 02:11:30,217 INFO [train.py:527] (2/6) Epoch 720, batch 94, global_batch_idx: 89250, batch size: 47, loss[discriminator_loss=2.541, discriminator_real_loss=1.306, discriminator_fake_loss=1.235, generator_loss=29.29, generator_mel_loss=17.63, generator_kl_loss=1.469, generator_dur_loss=1.694, generator_adv_loss=2.189, generator_feat_match_loss=6.31, over 47.00 samples.], tot_loss[discriminator_loss=2.686, discriminator_real_loss=1.358, discriminator_fake_loss=1.328, generator_loss=28.8, generator_mel_loss=17.93, generator_kl_loss=1.417, generator_dur_loss=1.728, generator_adv_loss=1.994, generator_feat_match_loss=5.73, over 5454.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 02:12:54,984 INFO [train.py:919] (2/6) Start epoch 721
2024-03-15 02:14:20,693 INFO [train.py:527] (2/6) Epoch 721, batch 20, global_batch_idx: 89300, batch size: 55, loss[discriminator_loss=2.694, discriminator_real_loss=1.406, discriminator_fake_loss=1.288, generator_loss=27.89, generator_mel_loss=17.98, generator_kl_loss=1.358, generator_dur_loss=1.737, generator_adv_loss=2.009, generator_feat_match_loss=4.805, over 55.00 samples.], tot_loss[discriminator_loss=2.698, discriminator_real_loss=1.365, discriminator_fake_loss=1.333, generator_loss=28.73, generator_mel_loss=17.89, generator_kl_loss=1.392, generator_dur_loss=1.736, generator_adv_loss=1.983, generator_feat_match_loss=5.728, over 1170.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 02:16:42,983 INFO [train.py:527] (2/6) Epoch 721, batch 70, global_batch_idx: 89350, batch size: 95, loss[discriminator_loss=2.696, discriminator_real_loss=1.299, discriminator_fake_loss=1.397, generator_loss=28.02, generator_mel_loss=17.41, generator_kl_loss=1.387, generator_dur_loss=1.809, generator_adv_loss=2.031, generator_feat_match_loss=5.377, over 95.00 samples.], tot_loss[discriminator_loss=2.688, discriminator_real_loss=1.358, discriminator_fake_loss=1.329, generator_loss=28.75, generator_mel_loss=17.9, generator_kl_loss=1.409, generator_dur_loss=1.741, generator_adv_loss=1.993, generator_feat_match_loss=5.708, over 4035.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 02:18:59,371 INFO [train.py:527] (2/6) Epoch 721, batch 120, global_batch_idx: 89400, batch size: 68, loss[discriminator_loss=2.676, discriminator_real_loss=1.388, discriminator_fake_loss=1.288, generator_loss=28.2, generator_mel_loss=17.8, generator_kl_loss=1.501, generator_dur_loss=1.78, generator_adv_loss=1.94, generator_feat_match_loss=5.18, over 68.00 samples.], tot_loss[discriminator_loss=2.688, discriminator_real_loss=1.36, discriminator_fake_loss=1.328, generator_loss=28.75, generator_mel_loss=17.92, generator_kl_loss=1.412, generator_dur_loss=1.738, generator_adv_loss=1.989, generator_feat_match_loss=5.692, over 6803.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 02:18:59,373 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 02:19:08,218 INFO [train.py:591] (2/6) Epoch 721, validation: discriminator_loss=2.729, discriminator_real_loss=1.382, discriminator_fake_loss=1.347, generator_loss=26.98, generator_mel_loss=17.75, generator_kl_loss=1.304, generator_dur_loss=1.82, generator_adv_loss=1.826, generator_feat_match_loss=4.277, over 100.00 samples.
2024-03-15 02:19:08,218 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 02:19:17,626 INFO [train.py:919] (2/6) Start epoch 722
2024-03-15 02:21:54,344 INFO [train.py:527] (2/6) Epoch 722, batch 46, global_batch_idx: 89450, batch size: 55, loss[discriminator_loss=2.702, discriminator_real_loss=1.349, discriminator_fake_loss=1.352, generator_loss=27.51, generator_mel_loss=17.31, generator_kl_loss=1.339, generator_dur_loss=1.764, generator_adv_loss=1.999, generator_feat_match_loss=5.104, over 55.00 samples.], tot_loss[discriminator_loss=2.691, discriminator_real_loss=1.359, discriminator_fake_loss=1.332, generator_loss=28.74, generator_mel_loss=17.92, generator_kl_loss=1.425, generator_dur_loss=1.747, generator_adv_loss=1.991, generator_feat_match_loss=5.661, over 2659.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 02:24:16,892 INFO [train.py:527] (2/6) Epoch 722, batch 96, global_batch_idx: 89500, batch size: 50, loss[discriminator_loss=2.69, discriminator_real_loss=1.356, discriminator_fake_loss=1.334, generator_loss=28.76, generator_mel_loss=17.98, generator_kl_loss=1.354, generator_dur_loss=1.678, generator_adv_loss=2.024, generator_feat_match_loss=5.721, over 50.00 samples.], tot_loss[discriminator_loss=2.683, discriminator_real_loss=1.358, discriminator_fake_loss=1.326, generator_loss=28.8, generator_mel_loss=17.91, generator_kl_loss=1.407, generator_dur_loss=1.751, generator_adv_loss=1.997, generator_feat_match_loss=5.74, over 5456.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 02:25:33,015 INFO [train.py:919] (2/6) Start epoch 723
2024-03-15 02:26:58,525 INFO [train.py:527] (2/6) Epoch 723, batch 22, global_batch_idx: 89550, batch size: 48, loss[discriminator_loss=2.757, discriminator_real_loss=1.372, discriminator_fake_loss=1.385, generator_loss=27.63, generator_mel_loss=17.44, generator_kl_loss=1.335, generator_dur_loss=1.711, generator_adv_loss=2.126, generator_feat_match_loss=5.012, over 48.00 samples.], tot_loss[discriminator_loss=2.69, discriminator_real_loss=1.351, discriminator_fake_loss=1.338, generator_loss=28.61, generator_mel_loss=17.76, generator_kl_loss=1.403, generator_dur_loss=1.72, generator_adv_loss=1.992, generator_feat_match_loss=5.736, over 1302.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 02:29:24,516 INFO [train.py:527] (2/6) Epoch 723, batch 72, global_batch_idx: 89600, batch size: 53, loss[discriminator_loss=2.672, discriminator_real_loss=1.263, discriminator_fake_loss=1.41, generator_loss=29.52, generator_mel_loss=18.74, generator_kl_loss=1.301, generator_dur_loss=1.679, generator_adv_loss=1.948, generator_feat_match_loss=5.852, over 53.00 samples.], tot_loss[discriminator_loss=2.693, discriminator_real_loss=1.358, discriminator_fake_loss=1.335, generator_loss=28.71, generator_mel_loss=17.85, generator_kl_loss=1.408, generator_dur_loss=1.732, generator_adv_loss=1.983, generator_feat_match_loss=5.735, over 4275.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 02:29:24,517 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 02:29:32,616 INFO [train.py:591] (2/6) Epoch 723, validation: discriminator_loss=2.731, discriminator_real_loss=1.438, discriminator_fake_loss=1.293, generator_loss=27.29, generator_mel_loss=18.05, generator_kl_loss=1.203, generator_dur_loss=1.799, generator_adv_loss=1.916, generator_feat_match_loss=4.325, over 100.00 samples.
2024-03-15 02:29:32,617 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 02:31:49,190 INFO [train.py:527] (2/6) Epoch 723, batch 122, global_batch_idx: 89650, batch size: 25, loss[discriminator_loss=2.71, discriminator_real_loss=1.401, discriminator_fake_loss=1.309, generator_loss=29.34, generator_mel_loss=18.52, generator_kl_loss=1.654, generator_dur_loss=1.596, generator_adv_loss=1.941, generator_feat_match_loss=5.625, over 25.00 samples.], tot_loss[discriminator_loss=2.695, discriminator_real_loss=1.361, discriminator_fake_loss=1.334, generator_loss=28.77, generator_mel_loss=17.9, generator_kl_loss=1.431, generator_dur_loss=1.728, generator_adv_loss=1.981, generator_feat_match_loss=5.726, over 6891.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 02:31:53,613 INFO [train.py:919] (2/6) Start epoch 724
2024-03-15 02:34:30,861 INFO [train.py:527] (2/6) Epoch 724, batch 48, global_batch_idx: 89700, batch size: 58, loss[discriminator_loss=2.693, discriminator_real_loss=1.256, discriminator_fake_loss=1.437, generator_loss=29.37, generator_mel_loss=18.22, generator_kl_loss=1.405, generator_dur_loss=1.728, generator_adv_loss=2.035, generator_feat_match_loss=5.975, over 58.00 samples.], tot_loss[discriminator_loss=2.69, discriminator_real_loss=1.356, discriminator_fake_loss=1.334, generator_loss=28.88, generator_mel_loss=17.91, generator_kl_loss=1.411, generator_dur_loss=1.748, generator_adv_loss=1.979, generator_feat_match_loss=5.833, over 2888.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 02:36:53,150 INFO [train.py:527] (2/6) Epoch 724, batch 98, global_batch_idx: 89750, batch size: 39, loss[discriminator_loss=2.683, discriminator_real_loss=1.299, discriminator_fake_loss=1.384, generator_loss=28.65, generator_mel_loss=17.52, generator_kl_loss=1.657, generator_dur_loss=1.697, generator_adv_loss=2.008, generator_feat_match_loss=5.774, over 39.00 samples.], tot_loss[discriminator_loss=2.691, discriminator_real_loss=1.357, discriminator_fake_loss=1.334, generator_loss=28.83, generator_mel_loss=17.9, generator_kl_loss=1.424, generator_dur_loss=1.743, generator_adv_loss=1.986, generator_feat_match_loss=5.769, over 5748.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 02:38:04,412 INFO [train.py:919] (2/6) Start epoch 725
2024-03-15 02:39:31,909 INFO [train.py:527] (2/6) Epoch 725, batch 24, global_batch_idx: 89800, batch size: 52, loss[discriminator_loss=2.774, discriminator_real_loss=1.388, discriminator_fake_loss=1.386, generator_loss=27.98, generator_mel_loss=17.81, generator_kl_loss=1.499, generator_dur_loss=1.735, generator_adv_loss=1.847, generator_feat_match_loss=5.088, over 52.00 samples.], tot_loss[discriminator_loss=2.705, discriminator_real_loss=1.361, discriminator_fake_loss=1.343, generator_loss=28.79, generator_mel_loss=17.94, generator_kl_loss=1.419, generator_dur_loss=1.738, generator_adv_loss=1.971, generator_feat_match_loss=5.725, over 1455.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 02:39:31,910 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 02:39:39,700 INFO [train.py:591] (2/6) Epoch 725, validation: discriminator_loss=2.751, discriminator_real_loss=1.342, discriminator_fake_loss=1.409, generator_loss=27.8, generator_mel_loss=18.4, generator_kl_loss=1.14, generator_dur_loss=1.812, generator_adv_loss=1.788, generator_feat_match_loss=4.655, over 100.00 samples.
2024-03-15 02:39:39,701 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 02:41:56,794 INFO [train.py:527] (2/6) Epoch 725, batch 74, global_batch_idx: 89850, batch size: 45, loss[discriminator_loss=2.766, discriminator_real_loss=1.423, discriminator_fake_loss=1.343, generator_loss=27.35, generator_mel_loss=17.59, generator_kl_loss=1.449, generator_dur_loss=1.672, generator_adv_loss=1.8, generator_feat_match_loss=4.837, over 45.00 samples.], tot_loss[discriminator_loss=2.696, discriminator_real_loss=1.36, discriminator_fake_loss=1.335, generator_loss=28.79, generator_mel_loss=17.93, generator_kl_loss=1.422, generator_dur_loss=1.742, generator_adv_loss=1.978, generator_feat_match_loss=5.716, over 4095.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 02:44:14,644 INFO [train.py:919] (2/6) Start epoch 726
2024-03-15 02:44:38,457 INFO [train.py:527] (2/6) Epoch 726, batch 0, global_batch_idx: 89900, batch size: 96, loss[discriminator_loss=2.719, discriminator_real_loss=1.373, discriminator_fake_loss=1.346, generator_loss=28.85, generator_mel_loss=18.03, generator_kl_loss=1.324, generator_dur_loss=1.849, generator_adv_loss=1.867, generator_feat_match_loss=5.78, over 96.00 samples.], tot_loss[discriminator_loss=2.719, discriminator_real_loss=1.373, discriminator_fake_loss=1.346, generator_loss=28.85, generator_mel_loss=18.03, generator_kl_loss=1.324, generator_dur_loss=1.849, generator_adv_loss=1.867, generator_feat_match_loss=5.78, over 96.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 02:46:55,359 INFO [train.py:527] (2/6) Epoch 726, batch 50, global_batch_idx: 89950, batch size: 60, loss[discriminator_loss=2.7, discriminator_real_loss=1.349, discriminator_fake_loss=1.351, generator_loss=28.46, generator_mel_loss=18.24, generator_kl_loss=1.359, generator_dur_loss=1.725, generator_adv_loss=2.018, generator_feat_match_loss=5.119, over 60.00 samples.], tot_loss[discriminator_loss=2.692, discriminator_real_loss=1.362, discriminator_fake_loss=1.331, generator_loss=28.89, generator_mel_loss=17.98, generator_kl_loss=1.416, generator_dur_loss=1.733, generator_adv_loss=1.998, generator_feat_match_loss=5.763, over 2845.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 02:49:12,525 INFO [train.py:527] (2/6) Epoch 726, batch 100, global_batch_idx: 90000, batch size: 74, loss[discriminator_loss=2.657, discriminator_real_loss=1.363, discriminator_fake_loss=1.294, generator_loss=29.02, generator_mel_loss=18.23, generator_kl_loss=1.277, generator_dur_loss=1.841, generator_adv_loss=1.992, generator_feat_match_loss=5.676, over 74.00 samples.], tot_loss[discriminator_loss=2.69, discriminator_real_loss=1.363, discriminator_fake_loss=1.327, generator_loss=28.84, generator_mel_loss=17.91, generator_kl_loss=1.426, generator_dur_loss=1.737, generator_adv_loss=1.994, generator_feat_match_loss=5.768, over 5596.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 02:49:12,526 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 02:49:21,317 INFO [train.py:591] (2/6) Epoch 726, validation: discriminator_loss=2.744, discriminator_real_loss=1.41, discriminator_fake_loss=1.334, generator_loss=27.19, generator_mel_loss=17.97, generator_kl_loss=1.278, generator_dur_loss=1.804, generator_adv_loss=1.87, generator_feat_match_loss=4.264, over 100.00 samples.
2024-03-15 02:49:21,318 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 02:50:26,184 INFO [train.py:919] (2/6) Start epoch 727
2024-03-15 02:52:03,437 INFO [train.py:527] (2/6) Epoch 727, batch 26, global_batch_idx: 90050, batch size: 59, loss[discriminator_loss=2.71, discriminator_real_loss=1.367, discriminator_fake_loss=1.344, generator_loss=27.78, generator_mel_loss=17.73, generator_kl_loss=1.255, generator_dur_loss=1.732, generator_adv_loss=1.86, generator_feat_match_loss=5.199, over 59.00 samples.], tot_loss[discriminator_loss=2.688, discriminator_real_loss=1.353, discriminator_fake_loss=1.334, generator_loss=28.64, generator_mel_loss=17.84, generator_kl_loss=1.404, generator_dur_loss=1.748, generator_adv_loss=1.983, generator_feat_match_loss=5.675, over 1628.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 02:54:22,646 INFO [train.py:527] (2/6) Epoch 727, batch 76, global_batch_idx: 90100, batch size: 64, loss[discriminator_loss=2.687, discriminator_real_loss=1.389, discriminator_fake_loss=1.298, generator_loss=28.35, generator_mel_loss=17.85, generator_kl_loss=1.336, generator_dur_loss=1.755, generator_adv_loss=2.025, generator_feat_match_loss=5.376, over 64.00 samples.], tot_loss[discriminator_loss=2.693, discriminator_real_loss=1.362, discriminator_fake_loss=1.331, generator_loss=28.67, generator_mel_loss=17.85, generator_kl_loss=1.416, generator_dur_loss=1.748, generator_adv_loss=1.986, generator_feat_match_loss=5.672, over 4509.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 02:56:31,058 INFO [train.py:919] (2/6) Start epoch 728
2024-03-15 02:56:59,614 INFO [train.py:527] (2/6) Epoch 728, batch 2, global_batch_idx: 90150, batch size: 77, loss[discriminator_loss=2.689, discriminator_real_loss=1.393, discriminator_fake_loss=1.296, generator_loss=28.67, generator_mel_loss=17.44, generator_kl_loss=1.484, generator_dur_loss=1.811, generator_adv_loss=1.961, generator_feat_match_loss=5.972, over 77.00 samples.], tot_loss[discriminator_loss=2.691, discriminator_real_loss=1.356, discriminator_fake_loss=1.335, generator_loss=29.59, generator_mel_loss=17.95, generator_kl_loss=1.53, generator_dur_loss=1.761, generator_adv_loss=1.984, generator_feat_match_loss=6.364, over 182.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 02:59:17,549 INFO [train.py:527] (2/6) Epoch 728, batch 52, global_batch_idx: 90200, batch size: 44, loss[discriminator_loss=2.755, discriminator_real_loss=1.349, discriminator_fake_loss=1.405, generator_loss=29.63, generator_mel_loss=17.74, generator_kl_loss=1.504, generator_dur_loss=1.68, generator_adv_loss=2.132, generator_feat_match_loss=6.581, over 44.00 samples.], tot_loss[discriminator_loss=2.689, discriminator_real_loss=1.356, discriminator_fake_loss=1.333, generator_loss=28.95, generator_mel_loss=18.01, generator_kl_loss=1.456, generator_dur_loss=1.73, generator_adv_loss=1.991, generator_feat_match_loss=5.758, over 2750.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 02:59:17,550 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 02:59:25,701 INFO [train.py:591] (2/6) Epoch 728, validation: discriminator_loss=2.75, discriminator_real_loss=1.473, discriminator_fake_loss=1.277, generator_loss=28.74, generator_mel_loss=18.58, generator_kl_loss=1.261, generator_dur_loss=1.818, generator_adv_loss=1.979, generator_feat_match_loss=5.101, over 100.00 samples.
2024-03-15 02:59:25,702 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 03:01:42,905 INFO [train.py:527] (2/6) Epoch 728, batch 102, global_batch_idx: 90250, batch size: 72, loss[discriminator_loss=2.653, discriminator_real_loss=1.313, discriminator_fake_loss=1.341, generator_loss=28.87, generator_mel_loss=17.96, generator_kl_loss=1.288, generator_dur_loss=1.78, generator_adv_loss=1.996, generator_feat_match_loss=5.852, over 72.00 samples.], tot_loss[discriminator_loss=2.683, discriminator_real_loss=1.355, discriminator_fake_loss=1.328, generator_loss=28.91, generator_mel_loss=17.99, generator_kl_loss=1.429, generator_dur_loss=1.737, generator_adv_loss=1.996, generator_feat_match_loss=5.762, over 5678.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 03:02:43,824 INFO [train.py:919] (2/6) Start epoch 729
2024-03-15 03:04:24,251 INFO [train.py:527] (2/6) Epoch 729, batch 28, global_batch_idx: 90300, batch size: 66, loss[discriminator_loss=2.688, discriminator_real_loss=1.332, discriminator_fake_loss=1.356, generator_loss=29.45, generator_mel_loss=18.18, generator_kl_loss=1.355, generator_dur_loss=1.728, generator_adv_loss=2.032, generator_feat_match_loss=6.152, over 66.00 samples.], tot_loss[discriminator_loss=2.681, discriminator_real_loss=1.359, discriminator_fake_loss=1.322, generator_loss=28.89, generator_mel_loss=17.86, generator_kl_loss=1.434, generator_dur_loss=1.769, generator_adv_loss=2.005, generator_feat_match_loss=5.829, over 1717.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 03:06:43,508 INFO [train.py:527] (2/6) Epoch 729, batch 78, global_batch_idx: 90350, batch size: 56, loss[discriminator_loss=2.684, discriminator_real_loss=1.394, discriminator_fake_loss=1.29, generator_loss=28.75, generator_mel_loss=17.49, generator_kl_loss=1.479, generator_dur_loss=1.687, generator_adv_loss=2.052, generator_feat_match_loss=6.041, over 56.00 samples.], tot_loss[discriminator_loss=2.693, discriminator_real_loss=1.366, discriminator_fake_loss=1.328, generator_loss=28.78, generator_mel_loss=17.87, generator_kl_loss=1.427, generator_dur_loss=1.753, generator_adv_loss=1.988, generator_feat_match_loss=5.749, over 4590.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 03:08:48,256 INFO [train.py:919] (2/6) Start epoch 730
2024-03-15 03:09:24,006 INFO [train.py:527] (2/6) Epoch 730, batch 4, global_batch_idx: 90400, batch size: 48, loss[discriminator_loss=2.664, discriminator_real_loss=1.309, discriminator_fake_loss=1.355, generator_loss=29.23, generator_mel_loss=18.43, generator_kl_loss=1.574, generator_dur_loss=1.596, generator_adv_loss=1.958, generator_feat_match_loss=5.668, over 48.00 samples.], tot_loss[discriminator_loss=2.7, discriminator_real_loss=1.379, discriminator_fake_loss=1.321, generator_loss=28.68, generator_mel_loss=17.86, generator_kl_loss=1.423, generator_dur_loss=1.751, generator_adv_loss=1.951, generator_feat_match_loss=5.698, over 298.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 03:09:24,008 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 03:09:31,913 INFO [train.py:591] (2/6) Epoch 730, validation: discriminator_loss=2.701, discriminator_real_loss=1.391, discriminator_fake_loss=1.31, generator_loss=27.51, generator_mel_loss=18.27, generator_kl_loss=1.258, generator_dur_loss=1.811, generator_adv_loss=1.869, generator_feat_match_loss=4.308, over 100.00 samples.
2024-03-15 03:09:31,915 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 03:11:51,554 INFO [train.py:527] (2/6) Epoch 730, batch 54, global_batch_idx: 90450, batch size: 72, loss[discriminator_loss=2.68, discriminator_real_loss=1.339, discriminator_fake_loss=1.341, generator_loss=27.96, generator_mel_loss=17.66, generator_kl_loss=1.243, generator_dur_loss=1.765, generator_adv_loss=1.986, generator_feat_match_loss=5.307, over 72.00 samples.], tot_loss[discriminator_loss=2.686, discriminator_real_loss=1.361, discriminator_fake_loss=1.325, generator_loss=28.76, generator_mel_loss=17.85, generator_kl_loss=1.413, generator_dur_loss=1.743, generator_adv_loss=2.009, generator_feat_match_loss=5.749, over 3085.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 03:14:08,328 INFO [train.py:527] (2/6) Epoch 730, batch 104, global_batch_idx: 90500, batch size: 53, loss[discriminator_loss=2.736, discriminator_real_loss=1.448, discriminator_fake_loss=1.288, generator_loss=28.28, generator_mel_loss=17.67, generator_kl_loss=1.506, generator_dur_loss=1.653, generator_adv_loss=1.912, generator_feat_match_loss=5.532, over 53.00 samples.], tot_loss[discriminator_loss=2.686, discriminator_real_loss=1.358, discriminator_fake_loss=1.328, generator_loss=28.79, generator_mel_loss=17.86, generator_kl_loss=1.42, generator_dur_loss=1.736, generator_adv_loss=2.001, generator_feat_match_loss=5.774, over 5693.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 03:14:58,711 INFO [train.py:919] (2/6) Start epoch 731
2024-03-15 03:16:42,901 INFO [train.py:527] (2/6) Epoch 731, batch 30, global_batch_idx: 90550, batch size: 48, loss[discriminator_loss=2.607, discriminator_real_loss=1.229, discriminator_fake_loss=1.378, generator_loss=31.29, generator_mel_loss=18.73, generator_kl_loss=1.579, generator_dur_loss=1.697, generator_adv_loss=2.131, generator_feat_match_loss=7.155, over 48.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.367, discriminator_fake_loss=1.317, generator_loss=28.86, generator_mel_loss=17.94, generator_kl_loss=1.442, generator_dur_loss=1.734, generator_adv_loss=1.986, generator_feat_match_loss=5.762, over 1628.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 03:18:59,962 INFO [train.py:527] (2/6) Epoch 731, batch 80, global_batch_idx: 90600, batch size: 77, loss[discriminator_loss=2.741, discriminator_real_loss=1.488, discriminator_fake_loss=1.252, generator_loss=28.34, generator_mel_loss=17.72, generator_kl_loss=1.421, generator_dur_loss=1.822, generator_adv_loss=1.764, generator_feat_match_loss=5.613, over 77.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.366, discriminator_fake_loss=1.32, generator_loss=28.91, generator_mel_loss=17.92, generator_kl_loss=1.445, generator_dur_loss=1.734, generator_adv_loss=1.989, generator_feat_match_loss=5.818, over 4296.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 03:18:59,963 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 03:19:08,866 INFO [train.py:591] (2/6) Epoch 731, validation: discriminator_loss=2.754, discriminator_real_loss=1.286, discriminator_fake_loss=1.468, generator_loss=27.33, generator_mel_loss=17.98, generator_kl_loss=1.2, generator_dur_loss=1.825, generator_adv_loss=1.702, generator_feat_match_loss=4.624, over 100.00 samples.
2024-03-15 03:19:08,867 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 03:21:10,312 INFO [train.py:919] (2/6) Start epoch 732
2024-03-15 03:21:47,911 INFO [train.py:527] (2/6) Epoch 732, batch 6, global_batch_idx: 90650, batch size: 36, loss[discriminator_loss=2.685, discriminator_real_loss=1.385, discriminator_fake_loss=1.3, generator_loss=26.97, generator_mel_loss=17.51, generator_kl_loss=1.52, generator_dur_loss=1.724, generator_adv_loss=1.952, generator_feat_match_loss=4.262, over 36.00 samples.], tot_loss[discriminator_loss=2.689, discriminator_real_loss=1.379, discriminator_fake_loss=1.309, generator_loss=28.28, generator_mel_loss=17.69, generator_kl_loss=1.391, generator_dur_loss=1.748, generator_adv_loss=2.026, generator_feat_match_loss=5.427, over 343.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 03:24:06,768 INFO [train.py:527] (2/6) Epoch 732, batch 56, global_batch_idx: 90700, batch size: 13, loss[discriminator_loss=2.78, discriminator_real_loss=1.337, discriminator_fake_loss=1.443, generator_loss=30.95, generator_mel_loss=18.81, generator_kl_loss=1.799, generator_dur_loss=1.585, generator_adv_loss=1.924, generator_feat_match_loss=6.837, over 13.00 samples.], tot_loss[discriminator_loss=2.689, discriminator_real_loss=1.366, discriminator_fake_loss=1.323, generator_loss=28.61, generator_mel_loss=17.83, generator_kl_loss=1.409, generator_dur_loss=1.728, generator_adv_loss=2.009, generator_feat_match_loss=5.631, over 3009.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 03:26:26,682 INFO [train.py:527] (2/6) Epoch 732, batch 106, global_batch_idx: 90750, batch size: 77, loss[discriminator_loss=2.704, discriminator_real_loss=1.381, discriminator_fake_loss=1.323, generator_loss=28.44, generator_mel_loss=17.78, generator_kl_loss=1.447, generator_dur_loss=1.846, generator_adv_loss=1.981, generator_feat_match_loss=5.39, over 77.00 samples.], tot_loss[discriminator_loss=2.691, discriminator_real_loss=1.362, discriminator_fake_loss=1.329, generator_loss=28.67, generator_mel_loss=17.8, generator_kl_loss=1.426, generator_dur_loss=1.729, generator_adv_loss=2.003, generator_feat_match_loss=5.715, over 5711.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 03:27:14,006 INFO [train.py:919] (2/6) Start epoch 733
2024-03-15 03:29:06,649 INFO [train.py:527] (2/6) Epoch 733, batch 32, global_batch_idx: 90800, batch size: 96, loss[discriminator_loss=2.658, discriminator_real_loss=1.343, discriminator_fake_loss=1.315, generator_loss=28.54, generator_mel_loss=18, generator_kl_loss=1.336, generator_dur_loss=1.844, generator_adv_loss=1.895, generator_feat_match_loss=5.472, over 96.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.363, discriminator_fake_loss=1.321, generator_loss=28.82, generator_mel_loss=17.91, generator_kl_loss=1.435, generator_dur_loss=1.76, generator_adv_loss=1.995, generator_feat_match_loss=5.723, over 1925.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 03:29:06,651 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 03:29:14,669 INFO [train.py:591] (2/6) Epoch 733, validation: discriminator_loss=2.702, discriminator_real_loss=1.341, discriminator_fake_loss=1.361, generator_loss=27.22, generator_mel_loss=17.85, generator_kl_loss=1.268, generator_dur_loss=1.817, generator_adv_loss=1.856, generator_feat_match_loss=4.433, over 100.00 samples.
2024-03-15 03:29:14,669 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 03:31:35,927 INFO [train.py:527] (2/6) Epoch 733, batch 82, global_batch_idx: 90850, batch size: 47, loss[discriminator_loss=2.676, discriminator_real_loss=1.402, discriminator_fake_loss=1.274, generator_loss=28.76, generator_mel_loss=17.76, generator_kl_loss=1.522, generator_dur_loss=1.693, generator_adv_loss=1.892, generator_feat_match_loss=5.89, over 47.00 samples.], tot_loss[discriminator_loss=2.687, discriminator_real_loss=1.363, discriminator_fake_loss=1.324, generator_loss=28.72, generator_mel_loss=17.84, generator_kl_loss=1.427, generator_dur_loss=1.751, generator_adv_loss=1.995, generator_feat_match_loss=5.705, over 4818.00 samples.], cur_lr_g: 1.83e-04, cur_lr_d: 1.83e-04, 
2024-03-15 03:33:27,950 INFO [train.py:919] (2/6) Start epoch 734
2024-03-15 03:34:14,583 INFO [train.py:527] (2/6) Epoch 734, batch 8, global_batch_idx: 90900, batch size: 15, loss[discriminator_loss=2.772, discriminator_real_loss=1.301, discriminator_fake_loss=1.471, generator_loss=29.97, generator_mel_loss=18.76, generator_kl_loss=1.881, generator_dur_loss=1.499, generator_adv_loss=1.802, generator_feat_match_loss=6.035, over 15.00 samples.], tot_loss[discriminator_loss=2.657, discriminator_real_loss=1.302, discriminator_fake_loss=1.355, generator_loss=29.18, generator_mel_loss=18.04, generator_kl_loss=1.444, generator_dur_loss=1.746, generator_adv_loss=1.978, generator_feat_match_loss=5.969, over 523.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 03:36:32,438 INFO [train.py:527] (2/6) Epoch 734, batch 58, global_batch_idx: 90950, batch size: 47, loss[discriminator_loss=2.677, discriminator_real_loss=1.318, discriminator_fake_loss=1.359, generator_loss=30.07, generator_mel_loss=18.08, generator_kl_loss=1.527, generator_dur_loss=1.612, generator_adv_loss=2.205, generator_feat_match_loss=6.641, over 47.00 samples.], tot_loss[discriminator_loss=2.678, discriminator_real_loss=1.344, discriminator_fake_loss=1.333, generator_loss=29.04, generator_mel_loss=17.9, generator_kl_loss=1.421, generator_dur_loss=1.747, generator_adv_loss=2.003, generator_feat_match_loss=5.964, over 3442.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 03:38:52,239 INFO [train.py:527] (2/6) Epoch 734, batch 108, global_batch_idx: 91000, batch size: 72, loss[discriminator_loss=2.668, discriminator_real_loss=1.302, discriminator_fake_loss=1.366, generator_loss=28.88, generator_mel_loss=18.13, generator_kl_loss=1.201, generator_dur_loss=1.823, generator_adv_loss=1.931, generator_feat_match_loss=5.801, over 72.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.351, discriminator_fake_loss=1.325, generator_loss=28.93, generator_mel_loss=17.89, generator_kl_loss=1.434, generator_dur_loss=1.748, generator_adv_loss=1.999, generator_feat_match_loss=5.858, over 6330.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 03:38:52,240 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 03:39:01,388 INFO [train.py:591] (2/6) Epoch 734, validation: discriminator_loss=2.736, discriminator_real_loss=1.413, discriminator_fake_loss=1.323, generator_loss=27.26, generator_mel_loss=18.04, generator_kl_loss=1.267, generator_dur_loss=1.818, generator_adv_loss=1.838, generator_feat_match_loss=4.298, over 100.00 samples.
2024-03-15 03:39:01,389 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 03:39:44,230 INFO [train.py:919] (2/6) Start epoch 735
2024-03-15 03:41:43,581 INFO [train.py:527] (2/6) Epoch 735, batch 34, global_batch_idx: 91050, batch size: 44, loss[discriminator_loss=2.66, discriminator_real_loss=1.214, discriminator_fake_loss=1.446, generator_loss=28.76, generator_mel_loss=17.65, generator_kl_loss=1.504, generator_dur_loss=1.684, generator_adv_loss=2.101, generator_feat_match_loss=5.817, over 44.00 samples.], tot_loss[discriminator_loss=2.691, discriminator_real_loss=1.358, discriminator_fake_loss=1.334, generator_loss=28.97, generator_mel_loss=17.99, generator_kl_loss=1.446, generator_dur_loss=1.739, generator_adv_loss=1.991, generator_feat_match_loss=5.809, over 1908.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 03:44:01,029 INFO [train.py:527] (2/6) Epoch 735, batch 84, global_batch_idx: 91100, batch size: 56, loss[discriminator_loss=2.681, discriminator_real_loss=1.337, discriminator_fake_loss=1.344, generator_loss=28.8, generator_mel_loss=18.21, generator_kl_loss=1.28, generator_dur_loss=1.734, generator_adv_loss=2.121, generator_feat_match_loss=5.457, over 56.00 samples.], tot_loss[discriminator_loss=2.691, discriminator_real_loss=1.362, discriminator_fake_loss=1.329, generator_loss=28.96, generator_mel_loss=17.99, generator_kl_loss=1.438, generator_dur_loss=1.737, generator_adv_loss=2.002, generator_feat_match_loss=5.798, over 4714.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 03:45:51,292 INFO [train.py:919] (2/6) Start epoch 736
2024-03-15 03:46:42,799 INFO [train.py:527] (2/6) Epoch 736, batch 10, global_batch_idx: 91150, batch size: 59, loss[discriminator_loss=2.739, discriminator_real_loss=1.441, discriminator_fake_loss=1.298, generator_loss=28.47, generator_mel_loss=17.8, generator_kl_loss=1.443, generator_dur_loss=1.723, generator_adv_loss=1.943, generator_feat_match_loss=5.558, over 59.00 samples.], tot_loss[discriminator_loss=2.706, discriminator_real_loss=1.373, discriminator_fake_loss=1.333, generator_loss=28.73, generator_mel_loss=17.84, generator_kl_loss=1.476, generator_dur_loss=1.706, generator_adv_loss=1.964, generator_feat_match_loss=5.743, over 548.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 03:49:01,671 INFO [train.py:527] (2/6) Epoch 736, batch 60, global_batch_idx: 91200, batch size: 83, loss[discriminator_loss=2.66, discriminator_real_loss=1.318, discriminator_fake_loss=1.342, generator_loss=28.75, generator_mel_loss=17.83, generator_kl_loss=1.303, generator_dur_loss=1.858, generator_adv_loss=2.093, generator_feat_match_loss=5.665, over 83.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.358, discriminator_fake_loss=1.326, generator_loss=28.84, generator_mel_loss=17.91, generator_kl_loss=1.421, generator_dur_loss=1.731, generator_adv_loss=2.009, generator_feat_match_loss=5.77, over 3326.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 03:49:01,672 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 03:49:09,685 INFO [train.py:591] (2/6) Epoch 736, validation: discriminator_loss=2.739, discriminator_real_loss=1.47, discriminator_fake_loss=1.269, generator_loss=27.55, generator_mel_loss=17.91, generator_kl_loss=1.142, generator_dur_loss=1.814, generator_adv_loss=2.003, generator_feat_match_loss=4.68, over 100.00 samples.
2024-03-15 03:49:09,685 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 03:51:27,994 INFO [train.py:527] (2/6) Epoch 736, batch 110, global_batch_idx: 91250, batch size: 96, loss[discriminator_loss=2.696, discriminator_real_loss=1.268, discriminator_fake_loss=1.428, generator_loss=29.43, generator_mel_loss=18.2, generator_kl_loss=1.299, generator_dur_loss=1.859, generator_adv_loss=1.993, generator_feat_match_loss=6.08, over 96.00 samples.], tot_loss[discriminator_loss=2.683, discriminator_real_loss=1.356, discriminator_fake_loss=1.328, generator_loss=28.85, generator_mel_loss=17.93, generator_kl_loss=1.433, generator_dur_loss=1.735, generator_adv_loss=2.001, generator_feat_match_loss=5.752, over 5973.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 03:52:04,267 INFO [train.py:919] (2/6) Start epoch 737
2024-03-15 03:54:10,804 INFO [train.py:527] (2/6) Epoch 737, batch 36, global_batch_idx: 91300, batch size: 88, loss[discriminator_loss=2.667, discriminator_real_loss=1.334, discriminator_fake_loss=1.333, generator_loss=28.29, generator_mel_loss=17.5, generator_kl_loss=1.377, generator_dur_loss=1.839, generator_adv_loss=1.968, generator_feat_match_loss=5.611, over 88.00 samples.], tot_loss[discriminator_loss=2.683, discriminator_real_loss=1.36, discriminator_fake_loss=1.324, generator_loss=28.81, generator_mel_loss=17.85, generator_kl_loss=1.383, generator_dur_loss=1.764, generator_adv_loss=2.004, generator_feat_match_loss=5.809, over 2288.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 03:56:27,579 INFO [train.py:527] (2/6) Epoch 737, batch 86, global_batch_idx: 91350, batch size: 68, loss[discriminator_loss=2.734, discriminator_real_loss=1.521, discriminator_fake_loss=1.213, generator_loss=28.48, generator_mel_loss=18.1, generator_kl_loss=1.356, generator_dur_loss=1.821, generator_adv_loss=1.819, generator_feat_match_loss=5.383, over 68.00 samples.], tot_loss[discriminator_loss=2.686, discriminator_real_loss=1.36, discriminator_fake_loss=1.325, generator_loss=28.85, generator_mel_loss=17.9, generator_kl_loss=1.414, generator_dur_loss=1.753, generator_adv_loss=1.995, generator_feat_match_loss=5.791, over 5010.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 03:58:12,192 INFO [train.py:919] (2/6) Start epoch 738
2024-03-15 03:59:07,739 INFO [train.py:527] (2/6) Epoch 738, batch 12, global_batch_idx: 91400, batch size: 70, loss[discriminator_loss=2.741, discriminator_real_loss=1.467, discriminator_fake_loss=1.274, generator_loss=28.11, generator_mel_loss=17.71, generator_kl_loss=1.375, generator_dur_loss=1.84, generator_adv_loss=1.791, generator_feat_match_loss=5.393, over 70.00 samples.], tot_loss[discriminator_loss=2.677, discriminator_real_loss=1.359, discriminator_fake_loss=1.318, generator_loss=28.61, generator_mel_loss=17.86, generator_kl_loss=1.422, generator_dur_loss=1.73, generator_adv_loss=1.992, generator_feat_match_loss=5.607, over 681.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 03:59:07,742 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 03:59:15,744 INFO [train.py:591] (2/6) Epoch 738, validation: discriminator_loss=2.79, discriminator_real_loss=1.33, discriminator_fake_loss=1.461, generator_loss=27.54, generator_mel_loss=18.02, generator_kl_loss=1.271, generator_dur_loss=1.801, generator_adv_loss=1.711, generator_feat_match_loss=4.737, over 100.00 samples.
2024-03-15 03:59:15,746 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 04:01:31,892 INFO [train.py:527] (2/6) Epoch 738, batch 62, global_batch_idx: 91450, batch size: 80, loss[discriminator_loss=2.684, discriminator_real_loss=1.421, discriminator_fake_loss=1.264, generator_loss=29.35, generator_mel_loss=18.27, generator_kl_loss=1.472, generator_dur_loss=1.777, generator_adv_loss=2.001, generator_feat_match_loss=5.825, over 80.00 samples.], tot_loss[discriminator_loss=2.69, discriminator_real_loss=1.361, discriminator_fake_loss=1.33, generator_loss=28.76, generator_mel_loss=17.88, generator_kl_loss=1.424, generator_dur_loss=1.739, generator_adv_loss=1.989, generator_feat_match_loss=5.731, over 3562.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 04:03:50,093 INFO [train.py:527] (2/6) Epoch 738, batch 112, global_batch_idx: 91500, batch size: 97, loss[discriminator_loss=2.686, discriminator_real_loss=1.366, discriminator_fake_loss=1.32, generator_loss=27.98, generator_mel_loss=17.55, generator_kl_loss=1.343, generator_dur_loss=1.823, generator_adv_loss=1.901, generator_feat_match_loss=5.366, over 97.00 samples.], tot_loss[discriminator_loss=2.691, discriminator_real_loss=1.36, discriminator_fake_loss=1.33, generator_loss=28.75, generator_mel_loss=17.88, generator_kl_loss=1.412, generator_dur_loss=1.738, generator_adv_loss=1.992, generator_feat_match_loss=5.72, over 6404.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 04:04:25,262 INFO [train.py:919] (2/6) Start epoch 739
2024-03-15 04:06:35,957 INFO [train.py:527] (2/6) Epoch 739, batch 38, global_batch_idx: 91550, batch size: 77, loss[discriminator_loss=2.736, discriminator_real_loss=1.393, discriminator_fake_loss=1.343, generator_loss=27.9, generator_mel_loss=17.73, generator_kl_loss=1.257, generator_dur_loss=1.804, generator_adv_loss=1.941, generator_feat_match_loss=5.172, over 77.00 samples.], tot_loss[discriminator_loss=2.706, discriminator_real_loss=1.372, discriminator_fake_loss=1.334, generator_loss=28.6, generator_mel_loss=17.87, generator_kl_loss=1.418, generator_dur_loss=1.749, generator_adv_loss=1.979, generator_feat_match_loss=5.581, over 2382.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 04:08:56,394 INFO [train.py:527] (2/6) Epoch 739, batch 88, global_batch_idx: 91600, batch size: 96, loss[discriminator_loss=2.684, discriminator_real_loss=1.198, discriminator_fake_loss=1.486, generator_loss=28.61, generator_mel_loss=17.92, generator_kl_loss=1.289, generator_dur_loss=1.828, generator_adv_loss=2.008, generator_feat_match_loss=5.56, over 96.00 samples.], tot_loss[discriminator_loss=2.693, discriminator_real_loss=1.363, discriminator_fake_loss=1.33, generator_loss=28.64, generator_mel_loss=17.84, generator_kl_loss=1.434, generator_dur_loss=1.748, generator_adv_loss=1.991, generator_feat_match_loss=5.628, over 5341.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 04:08:56,396 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 04:09:05,236 INFO [train.py:591] (2/6) Epoch 739, validation: discriminator_loss=2.733, discriminator_real_loss=1.412, discriminator_fake_loss=1.321, generator_loss=28.2, generator_mel_loss=17.99, generator_kl_loss=1.303, generator_dur_loss=1.802, generator_adv_loss=1.993, generator_feat_match_loss=5.106, over 100.00 samples.
2024-03-15 04:09:05,237 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 04:10:43,687 INFO [train.py:919] (2/6) Start epoch 740
2024-03-15 04:11:45,676 INFO [train.py:527] (2/6) Epoch 740, batch 14, global_batch_idx: 91650, batch size: 74, loss[discriminator_loss=2.727, discriminator_real_loss=1.372, discriminator_fake_loss=1.354, generator_loss=29.07, generator_mel_loss=18.47, generator_kl_loss=1.405, generator_dur_loss=1.8, generator_adv_loss=1.921, generator_feat_match_loss=5.471, over 74.00 samples.], tot_loss[discriminator_loss=2.693, discriminator_real_loss=1.352, discriminator_fake_loss=1.341, generator_loss=28.89, generator_mel_loss=18.09, generator_kl_loss=1.424, generator_dur_loss=1.741, generator_adv_loss=1.994, generator_feat_match_loss=5.645, over 821.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 04:14:05,799 INFO [train.py:527] (2/6) Epoch 740, batch 64, global_batch_idx: 91700, batch size: 55, loss[discriminator_loss=2.688, discriminator_real_loss=1.358, discriminator_fake_loss=1.33, generator_loss=27.49, generator_mel_loss=17.75, generator_kl_loss=1.307, generator_dur_loss=1.704, generator_adv_loss=1.928, generator_feat_match_loss=4.802, over 55.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.353, discriminator_fake_loss=1.331, generator_loss=28.86, generator_mel_loss=17.93, generator_kl_loss=1.403, generator_dur_loss=1.745, generator_adv_loss=2.003, generator_feat_match_loss=5.772, over 3710.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 04:16:23,869 INFO [train.py:527] (2/6) Epoch 740, batch 114, global_batch_idx: 91750, batch size: 59, loss[discriminator_loss=2.691, discriminator_real_loss=1.398, discriminator_fake_loss=1.293, generator_loss=28.97, generator_mel_loss=17.57, generator_kl_loss=1.516, generator_dur_loss=1.731, generator_adv_loss=2.007, generator_feat_match_loss=6.145, over 59.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.357, discriminator_fake_loss=1.326, generator_loss=28.84, generator_mel_loss=17.91, generator_kl_loss=1.418, generator_dur_loss=1.741, generator_adv_loss=1.994, generator_feat_match_loss=5.78, over 6520.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 04:16:51,417 INFO [train.py:919] (2/6) Start epoch 741
2024-03-15 04:19:12,510 INFO [train.py:527] (2/6) Epoch 741, batch 40, global_batch_idx: 91800, batch size: 15, loss[discriminator_loss=2.721, discriminator_real_loss=1.315, discriminator_fake_loss=1.405, generator_loss=29.93, generator_mel_loss=19.22, generator_kl_loss=1.929, generator_dur_loss=1.507, generator_adv_loss=2.166, generator_feat_match_loss=5.1, over 15.00 samples.], tot_loss[discriminator_loss=2.688, discriminator_real_loss=1.36, discriminator_fake_loss=1.328, generator_loss=28.87, generator_mel_loss=17.93, generator_kl_loss=1.418, generator_dur_loss=1.759, generator_adv_loss=1.999, generator_feat_match_loss=5.768, over 2498.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 04:19:12,511 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 04:19:20,742 INFO [train.py:591] (2/6) Epoch 741, validation: discriminator_loss=2.737, discriminator_real_loss=1.545, discriminator_fake_loss=1.191, generator_loss=28.37, generator_mel_loss=18.29, generator_kl_loss=1.231, generator_dur_loss=1.814, generator_adv_loss=2.147, generator_feat_match_loss=4.895, over 100.00 samples.
2024-03-15 04:19:20,743 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 04:21:40,849 INFO [train.py:527] (2/6) Epoch 741, batch 90, global_batch_idx: 91850, batch size: 96, loss[discriminator_loss=2.707, discriminator_real_loss=1.383, discriminator_fake_loss=1.324, generator_loss=28.14, generator_mel_loss=17.53, generator_kl_loss=1.286, generator_dur_loss=1.812, generator_adv_loss=1.87, generator_feat_match_loss=5.643, over 96.00 samples.], tot_loss[discriminator_loss=2.688, discriminator_real_loss=1.365, discriminator_fake_loss=1.323, generator_loss=28.68, generator_mel_loss=17.86, generator_kl_loss=1.425, generator_dur_loss=1.753, generator_adv_loss=1.986, generator_feat_match_loss=5.649, over 5336.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 04:23:13,979 INFO [train.py:919] (2/6) Start epoch 742
2024-03-15 04:24:23,311 INFO [train.py:527] (2/6) Epoch 742, batch 16, global_batch_idx: 91900, batch size: 66, loss[discriminator_loss=2.633, discriminator_real_loss=1.344, discriminator_fake_loss=1.289, generator_loss=28.22, generator_mel_loss=17.61, generator_kl_loss=1.351, generator_dur_loss=1.763, generator_adv_loss=2.099, generator_feat_match_loss=5.397, over 66.00 samples.], tot_loss[discriminator_loss=2.678, discriminator_real_loss=1.366, discriminator_fake_loss=1.311, generator_loss=28.88, generator_mel_loss=17.98, generator_kl_loss=1.473, generator_dur_loss=1.709, generator_adv_loss=2.017, generator_feat_match_loss=5.702, over 808.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 04:26:43,227 INFO [train.py:527] (2/6) Epoch 742, batch 66, global_batch_idx: 91950, batch size: 45, loss[discriminator_loss=2.718, discriminator_real_loss=1.377, discriminator_fake_loss=1.341, generator_loss=28.82, generator_mel_loss=18.13, generator_kl_loss=1.614, generator_dur_loss=1.661, generator_adv_loss=1.886, generator_feat_match_loss=5.527, over 45.00 samples.], tot_loss[discriminator_loss=2.693, discriminator_real_loss=1.365, discriminator_fake_loss=1.328, generator_loss=28.81, generator_mel_loss=17.9, generator_kl_loss=1.418, generator_dur_loss=1.744, generator_adv_loss=1.986, generator_feat_match_loss=5.765, over 3787.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 04:29:01,503 INFO [train.py:527] (2/6) Epoch 742, batch 116, global_batch_idx: 92000, batch size: 53, loss[discriminator_loss=2.73, discriminator_real_loss=1.373, discriminator_fake_loss=1.357, generator_loss=27.94, generator_mel_loss=17.67, generator_kl_loss=1.463, generator_dur_loss=1.742, generator_adv_loss=1.903, generator_feat_match_loss=5.16, over 53.00 samples.], tot_loss[discriminator_loss=2.692, discriminator_real_loss=1.362, discriminator_fake_loss=1.33, generator_loss=28.83, generator_mel_loss=17.91, generator_kl_loss=1.406, generator_dur_loss=1.752, generator_adv_loss=1.989, generator_feat_match_loss=5.774, over 6663.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 04:29:01,504 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 04:29:10,225 INFO [train.py:591] (2/6) Epoch 742, validation: discriminator_loss=2.768, discriminator_real_loss=1.436, discriminator_fake_loss=1.332, generator_loss=26.91, generator_mel_loss=18.07, generator_kl_loss=1.166, generator_dur_loss=1.816, generator_adv_loss=1.841, generator_feat_match_loss=4.017, over 100.00 samples.
2024-03-15 04:29:10,226 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 04:29:30,067 INFO [train.py:919] (2/6) Start epoch 743
2024-03-15 04:31:51,632 INFO [train.py:527] (2/6) Epoch 743, batch 42, global_batch_idx: 92050, batch size: 47, loss[discriminator_loss=2.639, discriminator_real_loss=1.327, discriminator_fake_loss=1.312, generator_loss=29.35, generator_mel_loss=18.24, generator_kl_loss=1.494, generator_dur_loss=1.695, generator_adv_loss=2.019, generator_feat_match_loss=5.903, over 47.00 samples.], tot_loss[discriminator_loss=2.687, discriminator_real_loss=1.358, discriminator_fake_loss=1.328, generator_loss=28.76, generator_mel_loss=17.84, generator_kl_loss=1.391, generator_dur_loss=1.745, generator_adv_loss=1.987, generator_feat_match_loss=5.802, over 2516.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 04:34:13,568 INFO [train.py:527] (2/6) Epoch 743, batch 92, global_batch_idx: 92100, batch size: 36, loss[discriminator_loss=2.682, discriminator_real_loss=1.303, discriminator_fake_loss=1.379, generator_loss=28.65, generator_mel_loss=17.93, generator_kl_loss=1.481, generator_dur_loss=1.749, generator_adv_loss=1.951, generator_feat_match_loss=5.537, over 36.00 samples.], tot_loss[discriminator_loss=2.687, discriminator_real_loss=1.358, discriminator_fake_loss=1.329, generator_loss=28.83, generator_mel_loss=17.89, generator_kl_loss=1.402, generator_dur_loss=1.74, generator_adv_loss=1.997, generator_feat_match_loss=5.799, over 5256.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 04:35:40,111 INFO [train.py:919] (2/6) Start epoch 744
2024-03-15 04:36:54,277 INFO [train.py:527] (2/6) Epoch 744, batch 18, global_batch_idx: 92150, batch size: 52, loss[discriminator_loss=2.76, discriminator_real_loss=1.352, discriminator_fake_loss=1.408, generator_loss=28.19, generator_mel_loss=17.8, generator_kl_loss=1.408, generator_dur_loss=1.686, generator_adv_loss=1.945, generator_feat_match_loss=5.349, over 52.00 samples.], tot_loss[discriminator_loss=2.693, discriminator_real_loss=1.363, discriminator_fake_loss=1.33, generator_loss=28.64, generator_mel_loss=17.82, generator_kl_loss=1.397, generator_dur_loss=1.75, generator_adv_loss=1.998, generator_feat_match_loss=5.679, over 1098.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 04:39:13,586 INFO [train.py:527] (2/6) Epoch 744, batch 68, global_batch_idx: 92200, batch size: 45, loss[discriminator_loss=2.659, discriminator_real_loss=1.356, discriminator_fake_loss=1.303, generator_loss=29.79, generator_mel_loss=18.21, generator_kl_loss=1.625, generator_dur_loss=1.619, generator_adv_loss=2.098, generator_feat_match_loss=6.237, over 45.00 samples.], tot_loss[discriminator_loss=2.689, discriminator_real_loss=1.365, discriminator_fake_loss=1.324, generator_loss=28.63, generator_mel_loss=17.81, generator_kl_loss=1.404, generator_dur_loss=1.762, generator_adv_loss=1.983, generator_feat_match_loss=5.675, over 4093.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 04:39:13,588 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 04:39:22,314 INFO [train.py:591] (2/6) Epoch 744, validation: discriminator_loss=2.756, discriminator_real_loss=1.355, discriminator_fake_loss=1.401, generator_loss=28.36, generator_mel_loss=18.23, generator_kl_loss=1.309, generator_dur_loss=1.822, generator_adv_loss=1.904, generator_feat_match_loss=5.097, over 100.00 samples.
2024-03-15 04:39:22,315 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 04:41:40,509 INFO [train.py:527] (2/6) Epoch 744, batch 118, global_batch_idx: 92250, batch size: 31, loss[discriminator_loss=2.707, discriminator_real_loss=1.444, discriminator_fake_loss=1.263, generator_loss=29.28, generator_mel_loss=18.11, generator_kl_loss=1.684, generator_dur_loss=1.679, generator_adv_loss=2.04, generator_feat_match_loss=5.758, over 31.00 samples.], tot_loss[discriminator_loss=2.687, discriminator_real_loss=1.364, discriminator_fake_loss=1.324, generator_loss=28.75, generator_mel_loss=17.83, generator_kl_loss=1.425, generator_dur_loss=1.753, generator_adv_loss=1.991, generator_feat_match_loss=5.746, over 6880.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 04:41:54,456 INFO [train.py:919] (2/6) Start epoch 745
2024-03-15 04:44:22,378 INFO [train.py:527] (2/6) Epoch 745, batch 44, global_batch_idx: 92300, batch size: 31, loss[discriminator_loss=2.718, discriminator_real_loss=1.37, discriminator_fake_loss=1.347, generator_loss=27.43, generator_mel_loss=17.48, generator_kl_loss=1.619, generator_dur_loss=1.628, generator_adv_loss=2.023, generator_feat_match_loss=4.682, over 31.00 samples.], tot_loss[discriminator_loss=2.707, discriminator_real_loss=1.373, discriminator_fake_loss=1.334, generator_loss=28.59, generator_mel_loss=17.86, generator_kl_loss=1.396, generator_dur_loss=1.748, generator_adv_loss=1.986, generator_feat_match_loss=5.601, over 2507.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 04:46:40,584 INFO [train.py:527] (2/6) Epoch 745, batch 94, global_batch_idx: 92350, batch size: 64, loss[discriminator_loss=2.733, discriminator_real_loss=1.526, discriminator_fake_loss=1.207, generator_loss=28.67, generator_mel_loss=18.19, generator_kl_loss=1.454, generator_dur_loss=1.785, generator_adv_loss=1.785, generator_feat_match_loss=5.45, over 64.00 samples.], tot_loss[discriminator_loss=2.694, discriminator_real_loss=1.365, discriminator_fake_loss=1.329, generator_loss=28.75, generator_mel_loss=17.86, generator_kl_loss=1.427, generator_dur_loss=1.734, generator_adv_loss=1.994, generator_feat_match_loss=5.732, over 5167.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 04:48:01,828 INFO [train.py:919] (2/6) Start epoch 746
2024-03-15 04:49:24,198 INFO [train.py:527] (2/6) Epoch 746, batch 20, global_batch_idx: 92400, batch size: 42, loss[discriminator_loss=2.571, discriminator_real_loss=1.275, discriminator_fake_loss=1.296, generator_loss=29.27, generator_mel_loss=17.85, generator_kl_loss=1.701, generator_dur_loss=1.656, generator_adv_loss=2.117, generator_feat_match_loss=5.947, over 42.00 samples.], tot_loss[discriminator_loss=2.679, discriminator_real_loss=1.362, discriminator_fake_loss=1.317, generator_loss=28.78, generator_mel_loss=17.88, generator_kl_loss=1.412, generator_dur_loss=1.765, generator_adv_loss=1.994, generator_feat_match_loss=5.727, over 1318.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 04:49:24,199 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 04:49:32,188 INFO [train.py:591] (2/6) Epoch 746, validation: discriminator_loss=2.636, discriminator_real_loss=1.282, discriminator_fake_loss=1.355, generator_loss=28.28, generator_mel_loss=18.31, generator_kl_loss=1.258, generator_dur_loss=1.822, generator_adv_loss=1.904, generator_feat_match_loss=4.993, over 100.00 samples.
2024-03-15 04:49:32,189 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 04:51:51,657 INFO [train.py:527] (2/6) Epoch 746, batch 70, global_batch_idx: 92450, batch size: 80, loss[discriminator_loss=2.744, discriminator_real_loss=1.354, discriminator_fake_loss=1.39, generator_loss=27.64, generator_mel_loss=17.47, generator_kl_loss=1.473, generator_dur_loss=1.848, generator_adv_loss=1.97, generator_feat_match_loss=4.875, over 80.00 samples.], tot_loss[discriminator_loss=2.686, discriminator_real_loss=1.365, discriminator_fake_loss=1.322, generator_loss=28.79, generator_mel_loss=17.83, generator_kl_loss=1.402, generator_dur_loss=1.758, generator_adv_loss=2.018, generator_feat_match_loss=5.78, over 4328.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 04:54:05,624 INFO [train.py:527] (2/6) Epoch 746, batch 120, global_batch_idx: 92500, batch size: 36, loss[discriminator_loss=2.666, discriminator_real_loss=1.387, discriminator_fake_loss=1.279, generator_loss=29.67, generator_mel_loss=18.18, generator_kl_loss=1.493, generator_dur_loss=1.666, generator_adv_loss=2.178, generator_feat_match_loss=6.152, over 36.00 samples.], tot_loss[discriminator_loss=2.689, discriminator_real_loss=1.366, discriminator_fake_loss=1.323, generator_loss=28.8, generator_mel_loss=17.84, generator_kl_loss=1.42, generator_dur_loss=1.744, generator_adv_loss=2.007, generator_feat_match_loss=5.78, over 6994.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 04:54:16,229 INFO [train.py:919] (2/6) Start epoch 747
2024-03-15 04:56:48,731 INFO [train.py:527] (2/6) Epoch 747, batch 46, global_batch_idx: 92550, batch size: 59, loss[discriminator_loss=2.671, discriminator_real_loss=1.362, discriminator_fake_loss=1.309, generator_loss=27.95, generator_mel_loss=17.7, generator_kl_loss=1.289, generator_dur_loss=1.68, generator_adv_loss=2.028, generator_feat_match_loss=5.252, over 59.00 samples.], tot_loss[discriminator_loss=2.698, discriminator_real_loss=1.354, discriminator_fake_loss=1.344, generator_loss=28.76, generator_mel_loss=17.96, generator_kl_loss=1.436, generator_dur_loss=1.734, generator_adv_loss=1.972, generator_feat_match_loss=5.659, over 2533.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 04:59:03,900 INFO [train.py:527] (2/6) Epoch 747, batch 96, global_batch_idx: 92600, batch size: 88, loss[discriminator_loss=2.709, discriminator_real_loss=1.281, discriminator_fake_loss=1.428, generator_loss=28.61, generator_mel_loss=17.73, generator_kl_loss=1.354, generator_dur_loss=1.85, generator_adv_loss=2.113, generator_feat_match_loss=5.559, over 88.00 samples.], tot_loss[discriminator_loss=2.693, discriminator_real_loss=1.359, discriminator_fake_loss=1.334, generator_loss=28.72, generator_mel_loss=17.9, generator_kl_loss=1.424, generator_dur_loss=1.736, generator_adv_loss=1.989, generator_feat_match_loss=5.667, over 5326.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 04:59:03,901 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 04:59:13,111 INFO [train.py:591] (2/6) Epoch 747, validation: discriminator_loss=2.757, discriminator_real_loss=1.545, discriminator_fake_loss=1.213, generator_loss=27.3, generator_mel_loss=18.04, generator_kl_loss=1.274, generator_dur_loss=1.836, generator_adv_loss=2.056, generator_feat_match_loss=4.094, over 100.00 samples.
2024-03-15 04:59:13,113 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 05:00:27,226 INFO [train.py:919] (2/6) Start epoch 748
2024-03-15 05:01:51,884 INFO [train.py:527] (2/6) Epoch 748, batch 22, global_batch_idx: 92650, batch size: 15, loss[discriminator_loss=2.686, discriminator_real_loss=1.311, discriminator_fake_loss=1.375, generator_loss=31.33, generator_mel_loss=18.83, generator_kl_loss=2.009, generator_dur_loss=1.512, generator_adv_loss=2.094, generator_feat_match_loss=6.89, over 15.00 samples.], tot_loss[discriminator_loss=2.692, discriminator_real_loss=1.368, discriminator_fake_loss=1.324, generator_loss=28.87, generator_mel_loss=17.98, generator_kl_loss=1.447, generator_dur_loss=1.705, generator_adv_loss=1.99, generator_feat_match_loss=5.756, over 1074.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 05:04:13,363 INFO [train.py:527] (2/6) Epoch 748, batch 72, global_batch_idx: 92700, batch size: 88, loss[discriminator_loss=2.66, discriminator_real_loss=1.34, discriminator_fake_loss=1.319, generator_loss=29.37, generator_mel_loss=18.15, generator_kl_loss=1.377, generator_dur_loss=1.798, generator_adv_loss=2.025, generator_feat_match_loss=6.021, over 88.00 samples.], tot_loss[discriminator_loss=2.687, discriminator_real_loss=1.364, discriminator_fake_loss=1.323, generator_loss=28.79, generator_mel_loss=17.9, generator_kl_loss=1.411, generator_dur_loss=1.735, generator_adv_loss=1.992, generator_feat_match_loss=5.751, over 3835.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 05:06:30,456 INFO [train.py:527] (2/6) Epoch 748, batch 122, global_batch_idx: 92750, batch size: 52, loss[discriminator_loss=2.733, discriminator_real_loss=1.423, discriminator_fake_loss=1.31, generator_loss=27.63, generator_mel_loss=17.79, generator_kl_loss=1.439, generator_dur_loss=1.721, generator_adv_loss=1.908, generator_feat_match_loss=4.776, over 52.00 samples.], tot_loss[discriminator_loss=2.689, discriminator_real_loss=1.365, discriminator_fake_loss=1.324, generator_loss=28.78, generator_mel_loss=17.88, generator_kl_loss=1.408, generator_dur_loss=1.739, generator_adv_loss=1.991, generator_feat_match_loss=5.765, over 6614.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 05:06:35,358 INFO [train.py:919] (2/6) Start epoch 749
2024-03-15 05:09:10,711 INFO [train.py:527] (2/6) Epoch 749, batch 48, global_batch_idx: 92800, batch size: 77, loss[discriminator_loss=2.693, discriminator_real_loss=1.3, discriminator_fake_loss=1.393, generator_loss=28.74, generator_mel_loss=17.73, generator_kl_loss=1.441, generator_dur_loss=1.85, generator_adv_loss=1.929, generator_feat_match_loss=5.793, over 77.00 samples.], tot_loss[discriminator_loss=2.694, discriminator_real_loss=1.357, discriminator_fake_loss=1.336, generator_loss=28.95, generator_mel_loss=17.88, generator_kl_loss=1.42, generator_dur_loss=1.76, generator_adv_loss=1.99, generator_feat_match_loss=5.895, over 2815.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 05:09:10,712 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 05:09:18,731 INFO [train.py:591] (2/6) Epoch 749, validation: discriminator_loss=2.763, discriminator_real_loss=1.358, discriminator_fake_loss=1.406, generator_loss=27.93, generator_mel_loss=18.16, generator_kl_loss=1.235, generator_dur_loss=1.818, generator_adv_loss=1.757, generator_feat_match_loss=4.961, over 100.00 samples.
2024-03-15 05:09:18,732 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 05:11:40,230 INFO [train.py:527] (2/6) Epoch 749, batch 98, global_batch_idx: 92850, batch size: 31, loss[discriminator_loss=2.729, discriminator_real_loss=1.441, discriminator_fake_loss=1.288, generator_loss=30.22, generator_mel_loss=18.58, generator_kl_loss=1.803, generator_dur_loss=1.592, generator_adv_loss=2.094, generator_feat_match_loss=6.16, over 31.00 samples.], tot_loss[discriminator_loss=2.69, discriminator_real_loss=1.36, discriminator_fake_loss=1.33, generator_loss=28.88, generator_mel_loss=17.88, generator_kl_loss=1.41, generator_dur_loss=1.76, generator_adv_loss=1.995, generator_feat_match_loss=5.834, over 5822.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 05:12:52,638 INFO [train.py:919] (2/6) Start epoch 750
2024-03-15 05:14:21,320 INFO [train.py:527] (2/6) Epoch 750, batch 24, global_batch_idx: 92900, batch size: 44, loss[discriminator_loss=2.658, discriminator_real_loss=1.309, discriminator_fake_loss=1.349, generator_loss=28.74, generator_mel_loss=17.59, generator_kl_loss=1.575, generator_dur_loss=1.691, generator_adv_loss=2.053, generator_feat_match_loss=5.827, over 44.00 samples.], tot_loss[discriminator_loss=2.681, discriminator_real_loss=1.359, discriminator_fake_loss=1.322, generator_loss=28.85, generator_mel_loss=17.9, generator_kl_loss=1.44, generator_dur_loss=1.72, generator_adv_loss=1.994, generator_feat_match_loss=5.79, over 1313.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 05:16:41,117 INFO [train.py:527] (2/6) Epoch 750, batch 74, global_batch_idx: 92950, batch size: 44, loss[discriminator_loss=2.666, discriminator_real_loss=1.382, discriminator_fake_loss=1.284, generator_loss=28.91, generator_mel_loss=18.23, generator_kl_loss=1.419, generator_dur_loss=1.73, generator_adv_loss=1.967, generator_feat_match_loss=5.568, over 44.00 samples.], tot_loss[discriminator_loss=2.682, discriminator_real_loss=1.359, discriminator_fake_loss=1.323, generator_loss=28.83, generator_mel_loss=17.91, generator_kl_loss=1.414, generator_dur_loss=1.741, generator_adv_loss=1.988, generator_feat_match_loss=5.784, over 4276.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 05:18:58,710 INFO [train.py:919] (2/6) Start epoch 751
2024-03-15 05:19:22,958 INFO [train.py:527] (2/6) Epoch 751, batch 0, global_batch_idx: 93000, batch size: 48, loss[discriminator_loss=2.695, discriminator_real_loss=1.36, discriminator_fake_loss=1.334, generator_loss=28.48, generator_mel_loss=17.77, generator_kl_loss=1.467, generator_dur_loss=1.654, generator_adv_loss=1.92, generator_feat_match_loss=5.667, over 48.00 samples.], tot_loss[discriminator_loss=2.695, discriminator_real_loss=1.36, discriminator_fake_loss=1.334, generator_loss=28.48, generator_mel_loss=17.77, generator_kl_loss=1.467, generator_dur_loss=1.654, generator_adv_loss=1.92, generator_feat_match_loss=5.667, over 48.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 05:19:22,961 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 05:19:30,713 INFO [train.py:591] (2/6) Epoch 751, validation: discriminator_loss=2.758, discriminator_real_loss=1.427, discriminator_fake_loss=1.331, generator_loss=27.35, generator_mel_loss=18.12, generator_kl_loss=1.288, generator_dur_loss=1.803, generator_adv_loss=1.841, generator_feat_match_loss=4.294, over 100.00 samples.
2024-03-15 05:19:30,719 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 05:21:47,076 INFO [train.py:527] (2/6) Epoch 751, batch 50, global_batch_idx: 93050, batch size: 64, loss[discriminator_loss=2.741, discriminator_real_loss=1.541, discriminator_fake_loss=1.199, generator_loss=28.2, generator_mel_loss=17.76, generator_kl_loss=1.329, generator_dur_loss=1.738, generator_adv_loss=1.884, generator_feat_match_loss=5.489, over 64.00 samples.], tot_loss[discriminator_loss=2.691, discriminator_real_loss=1.361, discriminator_fake_loss=1.33, generator_loss=28.96, generator_mel_loss=17.91, generator_kl_loss=1.423, generator_dur_loss=1.747, generator_adv_loss=2.005, generator_feat_match_loss=5.875, over 2815.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 05:24:07,021 INFO [train.py:527] (2/6) Epoch 751, batch 100, global_batch_idx: 93100, batch size: 44, loss[discriminator_loss=2.672, discriminator_real_loss=1.38, discriminator_fake_loss=1.292, generator_loss=29.12, generator_mel_loss=18.05, generator_kl_loss=1.441, generator_dur_loss=1.629, generator_adv_loss=1.988, generator_feat_match_loss=6.011, over 44.00 samples.], tot_loss[discriminator_loss=2.691, discriminator_real_loss=1.358, discriminator_fake_loss=1.334, generator_loss=28.96, generator_mel_loss=17.91, generator_kl_loss=1.411, generator_dur_loss=1.746, generator_adv_loss=1.997, generator_feat_match_loss=5.891, over 5728.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 05:25:10,894 INFO [train.py:919] (2/6) Start epoch 752
2024-03-15 05:26:49,744 INFO [train.py:527] (2/6) Epoch 752, batch 26, global_batch_idx: 93150, batch size: 68, loss[discriminator_loss=2.716, discriminator_real_loss=1.336, discriminator_fake_loss=1.38, generator_loss=28.65, generator_mel_loss=17.96, generator_kl_loss=1.39, generator_dur_loss=1.767, generator_adv_loss=2.071, generator_feat_match_loss=5.47, over 68.00 samples.], tot_loss[discriminator_loss=2.693, discriminator_real_loss=1.361, discriminator_fake_loss=1.333, generator_loss=28.71, generator_mel_loss=17.79, generator_kl_loss=1.387, generator_dur_loss=1.767, generator_adv_loss=1.996, generator_feat_match_loss=5.774, over 1698.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 05:29:10,404 INFO [train.py:527] (2/6) Epoch 752, batch 76, global_batch_idx: 93200, batch size: 96, loss[discriminator_loss=2.684, discriminator_real_loss=1.322, discriminator_fake_loss=1.362, generator_loss=29.25, generator_mel_loss=17.93, generator_kl_loss=1.146, generator_dur_loss=1.819, generator_adv_loss=1.99, generator_feat_match_loss=6.371, over 96.00 samples.], tot_loss[discriminator_loss=2.694, discriminator_real_loss=1.361, discriminator_fake_loss=1.333, generator_loss=28.72, generator_mel_loss=17.79, generator_kl_loss=1.42, generator_dur_loss=1.736, generator_adv_loss=1.99, generator_feat_match_loss=5.78, over 4397.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 05:29:10,406 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 05:29:19,323 INFO [train.py:591] (2/6) Epoch 752, validation: discriminator_loss=2.762, discriminator_real_loss=1.426, discriminator_fake_loss=1.336, generator_loss=28.03, generator_mel_loss=18.4, generator_kl_loss=1.133, generator_dur_loss=1.79, generator_adv_loss=1.924, generator_feat_match_loss=4.788, over 100.00 samples.
2024-03-15 05:29:19,324 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 05:31:28,117 INFO [train.py:919] (2/6) Start epoch 753
2024-03-15 05:31:58,223 INFO [train.py:527] (2/6) Epoch 753, batch 2, global_batch_idx: 93250, batch size: 56, loss[discriminator_loss=2.73, discriminator_real_loss=1.306, discriminator_fake_loss=1.425, generator_loss=29.71, generator_mel_loss=18.49, generator_kl_loss=1.447, generator_dur_loss=1.707, generator_adv_loss=2.024, generator_feat_match_loss=6.043, over 56.00 samples.], tot_loss[discriminator_loss=2.725, discriminator_real_loss=1.336, discriminator_fake_loss=1.389, generator_loss=29.21, generator_mel_loss=17.99, generator_kl_loss=1.453, generator_dur_loss=1.764, generator_adv_loss=2.001, generator_feat_match_loss=6.005, over 170.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 05:34:17,892 INFO [train.py:527] (2/6) Epoch 753, batch 52, global_batch_idx: 93300, batch size: 80, loss[discriminator_loss=2.757, discriminator_real_loss=1.428, discriminator_fake_loss=1.33, generator_loss=28.44, generator_mel_loss=17.77, generator_kl_loss=1.333, generator_dur_loss=1.777, generator_adv_loss=1.858, generator_feat_match_loss=5.702, over 80.00 samples.], tot_loss[discriminator_loss=2.693, discriminator_real_loss=1.366, discriminator_fake_loss=1.327, generator_loss=28.8, generator_mel_loss=17.88, generator_kl_loss=1.412, generator_dur_loss=1.728, generator_adv_loss=1.995, generator_feat_match_loss=5.784, over 3121.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 05:36:40,896 INFO [train.py:527] (2/6) Epoch 753, batch 102, global_batch_idx: 93350, batch size: 66, loss[discriminator_loss=2.68, discriminator_real_loss=1.337, discriminator_fake_loss=1.343, generator_loss=29.12, generator_mel_loss=17.95, generator_kl_loss=1.348, generator_dur_loss=1.703, generator_adv_loss=2.034, generator_feat_match_loss=6.077, over 66.00 samples.], tot_loss[discriminator_loss=2.687, discriminator_real_loss=1.36, discriminator_fake_loss=1.327, generator_loss=28.81, generator_mel_loss=17.88, generator_kl_loss=1.414, generator_dur_loss=1.729, generator_adv_loss=1.994, generator_feat_match_loss=5.796, over 6037.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 05:37:38,725 INFO [train.py:919] (2/6) Start epoch 754
2024-03-15 05:39:17,148 INFO [train.py:527] (2/6) Epoch 754, batch 28, global_batch_idx: 93400, batch size: 64, loss[discriminator_loss=2.715, discriminator_real_loss=1.442, discriminator_fake_loss=1.273, generator_loss=28.12, generator_mel_loss=17.66, generator_kl_loss=1.426, generator_dur_loss=1.716, generator_adv_loss=1.957, generator_feat_match_loss=5.358, over 64.00 samples.], tot_loss[discriminator_loss=2.689, discriminator_real_loss=1.366, discriminator_fake_loss=1.323, generator_loss=28.61, generator_mel_loss=17.85, generator_kl_loss=1.4, generator_dur_loss=1.741, generator_adv_loss=1.987, generator_feat_match_loss=5.632, over 1735.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 05:39:17,149 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 05:39:25,181 INFO [train.py:591] (2/6) Epoch 754, validation: discriminator_loss=2.741, discriminator_real_loss=1.343, discriminator_fake_loss=1.398, generator_loss=27.34, generator_mel_loss=18.17, generator_kl_loss=1.323, generator_dur_loss=1.803, generator_adv_loss=1.826, generator_feat_match_loss=4.214, over 100.00 samples.
2024-03-15 05:39:25,183 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 05:41:46,208 INFO [train.py:527] (2/6) Epoch 754, batch 78, global_batch_idx: 93450, batch size: 80, loss[discriminator_loss=2.722, discriminator_real_loss=1.394, discriminator_fake_loss=1.328, generator_loss=27.71, generator_mel_loss=17.61, generator_kl_loss=1.321, generator_dur_loss=1.769, generator_adv_loss=1.96, generator_feat_match_loss=5.052, over 80.00 samples.], tot_loss[discriminator_loss=2.687, discriminator_real_loss=1.356, discriminator_fake_loss=1.331, generator_loss=28.81, generator_mel_loss=17.86, generator_kl_loss=1.428, generator_dur_loss=1.731, generator_adv_loss=2.025, generator_feat_match_loss=5.771, over 4480.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 05:43:50,652 INFO [train.py:919] (2/6) Start epoch 755
2024-03-15 05:44:26,469 INFO [train.py:527] (2/6) Epoch 755, batch 4, global_batch_idx: 93500, batch size: 77, loss[discriminator_loss=2.706, discriminator_real_loss=1.43, discriminator_fake_loss=1.276, generator_loss=28.86, generator_mel_loss=18.03, generator_kl_loss=1.331, generator_dur_loss=1.779, generator_adv_loss=1.914, generator_feat_match_loss=5.804, over 77.00 samples.], tot_loss[discriminator_loss=2.707, discriminator_real_loss=1.378, discriminator_fake_loss=1.329, generator_loss=29.04, generator_mel_loss=18.15, generator_kl_loss=1.349, generator_dur_loss=1.731, generator_adv_loss=2.006, generator_feat_match_loss=5.807, over 319.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 05:46:47,406 INFO [train.py:527] (2/6) Epoch 755, batch 54, global_batch_idx: 93550, batch size: 56, loss[discriminator_loss=2.622, discriminator_real_loss=1.326, discriminator_fake_loss=1.296, generator_loss=29.74, generator_mel_loss=18.46, generator_kl_loss=1.354, generator_dur_loss=1.735, generator_adv_loss=2.039, generator_feat_match_loss=6.156, over 56.00 samples.], tot_loss[discriminator_loss=2.677, discriminator_real_loss=1.356, discriminator_fake_loss=1.321, generator_loss=28.81, generator_mel_loss=17.88, generator_kl_loss=1.403, generator_dur_loss=1.719, generator_adv_loss=1.998, generator_feat_match_loss=5.811, over 3327.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 05:49:04,368 INFO [train.py:527] (2/6) Epoch 755, batch 104, global_batch_idx: 93600, batch size: 45, loss[discriminator_loss=2.701, discriminator_real_loss=1.364, discriminator_fake_loss=1.336, generator_loss=29.32, generator_mel_loss=17.94, generator_kl_loss=1.455, generator_dur_loss=1.615, generator_adv_loss=2.005, generator_feat_match_loss=6.308, over 45.00 samples.], tot_loss[discriminator_loss=2.678, discriminator_real_loss=1.358, discriminator_fake_loss=1.32, generator_loss=28.86, generator_mel_loss=17.88, generator_kl_loss=1.424, generator_dur_loss=1.725, generator_adv_loss=1.997, generator_feat_match_loss=5.828, over 6126.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 05:49:04,370 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 05:49:13,245 INFO [train.py:591] (2/6) Epoch 755, validation: discriminator_loss=2.697, discriminator_real_loss=1.382, discriminator_fake_loss=1.315, generator_loss=28.98, generator_mel_loss=18.98, generator_kl_loss=1.299, generator_dur_loss=1.78, generator_adv_loss=1.937, generator_feat_match_loss=4.986, over 100.00 samples.
2024-03-15 05:49:13,246 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 05:50:07,609 INFO [train.py:919] (2/6) Start epoch 756
2024-03-15 05:51:56,051 INFO [train.py:527] (2/6) Epoch 756, batch 30, global_batch_idx: 93650, batch size: 25, loss[discriminator_loss=2.673, discriminator_real_loss=1.342, discriminator_fake_loss=1.33, generator_loss=29.98, generator_mel_loss=18.8, generator_kl_loss=1.948, generator_dur_loss=1.539, generator_adv_loss=2.106, generator_feat_match_loss=5.589, over 25.00 samples.], tot_loss[discriminator_loss=2.687, discriminator_real_loss=1.356, discriminator_fake_loss=1.331, generator_loss=28.85, generator_mel_loss=17.91, generator_kl_loss=1.453, generator_dur_loss=1.704, generator_adv_loss=1.991, generator_feat_match_loss=5.789, over 1583.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 05:54:15,411 INFO [train.py:527] (2/6) Epoch 756, batch 80, global_batch_idx: 93700, batch size: 14, loss[discriminator_loss=2.749, discriminator_real_loss=1.433, discriminator_fake_loss=1.315, generator_loss=32.26, generator_mel_loss=19.48, generator_kl_loss=1.8, generator_dur_loss=1.53, generator_adv_loss=2.071, generator_feat_match_loss=7.373, over 14.00 samples.], tot_loss[discriminator_loss=2.688, discriminator_real_loss=1.36, discriminator_fake_loss=1.327, generator_loss=28.79, generator_mel_loss=17.88, generator_kl_loss=1.444, generator_dur_loss=1.716, generator_adv_loss=1.989, generator_feat_match_loss=5.762, over 4460.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 05:56:13,075 INFO [train.py:919] (2/6) Start epoch 757
2024-03-15 05:56:54,339 INFO [train.py:527] (2/6) Epoch 757, batch 6, global_batch_idx: 93750, batch size: 25, loss[discriminator_loss=2.633, discriminator_real_loss=1.369, discriminator_fake_loss=1.264, generator_loss=29.83, generator_mel_loss=18.21, generator_kl_loss=1.701, generator_dur_loss=1.58, generator_adv_loss=2.049, generator_feat_match_loss=6.29, over 25.00 samples.], tot_loss[discriminator_loss=2.668, discriminator_real_loss=1.345, discriminator_fake_loss=1.323, generator_loss=28.51, generator_mel_loss=17.86, generator_kl_loss=1.383, generator_dur_loss=1.785, generator_adv_loss=1.97, generator_feat_match_loss=5.517, over 444.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 05:59:17,022 INFO [train.py:527] (2/6) Epoch 757, batch 56, global_batch_idx: 93800, batch size: 70, loss[discriminator_loss=2.716, discriminator_real_loss=1.433, discriminator_fake_loss=1.283, generator_loss=28.05, generator_mel_loss=17.58, generator_kl_loss=1.366, generator_dur_loss=1.764, generator_adv_loss=1.948, generator_feat_match_loss=5.4, over 70.00 samples.], tot_loss[discriminator_loss=2.686, discriminator_real_loss=1.36, discriminator_fake_loss=1.325, generator_loss=28.83, generator_mel_loss=17.9, generator_kl_loss=1.41, generator_dur_loss=1.752, generator_adv_loss=1.991, generator_feat_match_loss=5.776, over 3454.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 05:59:17,023 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 05:59:25,147 INFO [train.py:591] (2/6) Epoch 757, validation: discriminator_loss=2.754, discriminator_real_loss=1.402, discriminator_fake_loss=1.353, generator_loss=28.61, generator_mel_loss=18.39, generator_kl_loss=1.35, generator_dur_loss=1.799, generator_adv_loss=1.918, generator_feat_match_loss=5.149, over 100.00 samples.
2024-03-15 05:59:25,148 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 06:01:45,078 INFO [train.py:527] (2/6) Epoch 757, batch 106, global_batch_idx: 93850, batch size: 47, loss[discriminator_loss=2.729, discriminator_real_loss=1.309, discriminator_fake_loss=1.42, generator_loss=30.57, generator_mel_loss=18.08, generator_kl_loss=1.557, generator_dur_loss=1.623, generator_adv_loss=1.954, generator_feat_match_loss=7.358, over 47.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.355, discriminator_fake_loss=1.329, generator_loss=28.98, generator_mel_loss=17.92, generator_kl_loss=1.424, generator_dur_loss=1.744, generator_adv_loss=2.005, generator_feat_match_loss=5.894, over 6270.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 06:02:29,092 INFO [train.py:919] (2/6) Start epoch 758
2024-03-15 06:04:21,188 INFO [train.py:527] (2/6) Epoch 758, batch 32, global_batch_idx: 93900, batch size: 52, loss[discriminator_loss=2.775, discriminator_real_loss=1.454, discriminator_fake_loss=1.321, generator_loss=29.14, generator_mel_loss=18.46, generator_kl_loss=1.304, generator_dur_loss=1.685, generator_adv_loss=1.983, generator_feat_match_loss=5.705, over 52.00 samples.], tot_loss[discriminator_loss=2.677, discriminator_real_loss=1.351, discriminator_fake_loss=1.326, generator_loss=28.96, generator_mel_loss=17.94, generator_kl_loss=1.416, generator_dur_loss=1.721, generator_adv_loss=2.008, generator_feat_match_loss=5.88, over 1744.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 06:06:40,748 INFO [train.py:527] (2/6) Epoch 758, batch 82, global_batch_idx: 93950, batch size: 96, loss[discriminator_loss=2.709, discriminator_real_loss=1.429, discriminator_fake_loss=1.28, generator_loss=28.85, generator_mel_loss=17.57, generator_kl_loss=1.459, generator_dur_loss=1.857, generator_adv_loss=1.979, generator_feat_match_loss=5.983, over 96.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.358, discriminator_fake_loss=1.326, generator_loss=28.97, generator_mel_loss=17.92, generator_kl_loss=1.423, generator_dur_loss=1.728, generator_adv_loss=2.006, generator_feat_match_loss=5.888, over 4617.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 06:08:35,742 INFO [train.py:919] (2/6) Start epoch 759
2024-03-15 06:09:22,005 INFO [train.py:527] (2/6) Epoch 759, batch 8, global_batch_idx: 94000, batch size: 31, loss[discriminator_loss=2.701, discriminator_real_loss=1.346, discriminator_fake_loss=1.355, generator_loss=29.34, generator_mel_loss=18.09, generator_kl_loss=1.629, generator_dur_loss=1.654, generator_adv_loss=2.087, generator_feat_match_loss=5.879, over 31.00 samples.], tot_loss[discriminator_loss=2.693, discriminator_real_loss=1.339, discriminator_fake_loss=1.354, generator_loss=28.7, generator_mel_loss=17.83, generator_kl_loss=1.371, generator_dur_loss=1.763, generator_adv_loss=1.986, generator_feat_match_loss=5.749, over 576.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 06:09:22,008 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 06:09:29,728 INFO [train.py:591] (2/6) Epoch 759, validation: discriminator_loss=2.756, discriminator_real_loss=1.459, discriminator_fake_loss=1.296, generator_loss=28.04, generator_mel_loss=18.45, generator_kl_loss=1.287, generator_dur_loss=1.769, generator_adv_loss=1.976, generator_feat_match_loss=4.554, over 100.00 samples.
2024-03-15 06:09:29,729 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 06:11:48,959 INFO [train.py:527] (2/6) Epoch 759, batch 58, global_batch_idx: 94050, batch size: 74, loss[discriminator_loss=2.696, discriminator_real_loss=1.333, discriminator_fake_loss=1.364, generator_loss=28.67, generator_mel_loss=17.7, generator_kl_loss=1.38, generator_dur_loss=1.765, generator_adv_loss=2.017, generator_feat_match_loss=5.802, over 74.00 samples.], tot_loss[discriminator_loss=2.682, discriminator_real_loss=1.348, discriminator_fake_loss=1.335, generator_loss=28.85, generator_mel_loss=17.92, generator_kl_loss=1.41, generator_dur_loss=1.734, generator_adv_loss=1.998, generator_feat_match_loss=5.792, over 3463.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 06:14:05,406 INFO [train.py:527] (2/6) Epoch 759, batch 108, global_batch_idx: 94100, batch size: 58, loss[discriminator_loss=2.726, discriminator_real_loss=1.381, discriminator_fake_loss=1.345, generator_loss=29.27, generator_mel_loss=18.19, generator_kl_loss=1.595, generator_dur_loss=1.701, generator_adv_loss=1.776, generator_feat_match_loss=6.01, over 58.00 samples.], tot_loss[discriminator_loss=2.682, discriminator_real_loss=1.349, discriminator_fake_loss=1.333, generator_loss=28.86, generator_mel_loss=17.91, generator_kl_loss=1.42, generator_dur_loss=1.725, generator_adv_loss=1.994, generator_feat_match_loss=5.81, over 6194.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 06:14:46,828 INFO [train.py:919] (2/6) Start epoch 760
2024-03-15 06:16:44,656 INFO [train.py:527] (2/6) Epoch 760, batch 34, global_batch_idx: 94150, batch size: 52, loss[discriminator_loss=2.682, discriminator_real_loss=1.298, discriminator_fake_loss=1.384, generator_loss=30.27, generator_mel_loss=18.3, generator_kl_loss=1.549, generator_dur_loss=1.645, generator_adv_loss=2.124, generator_feat_match_loss=6.646, over 52.00 samples.], tot_loss[discriminator_loss=2.677, discriminator_real_loss=1.357, discriminator_fake_loss=1.32, generator_loss=28.9, generator_mel_loss=17.88, generator_kl_loss=1.432, generator_dur_loss=1.714, generator_adv_loss=1.991, generator_feat_match_loss=5.878, over 1775.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 06:19:03,128 INFO [train.py:527] (2/6) Epoch 760, batch 84, global_batch_idx: 94200, batch size: 72, loss[discriminator_loss=2.667, discriminator_real_loss=1.348, discriminator_fake_loss=1.319, generator_loss=29.09, generator_mel_loss=17.81, generator_kl_loss=1.46, generator_dur_loss=1.784, generator_adv_loss=2.019, generator_feat_match_loss=6.016, over 72.00 samples.], tot_loss[discriminator_loss=2.682, discriminator_real_loss=1.356, discriminator_fake_loss=1.326, generator_loss=28.91, generator_mel_loss=17.9, generator_kl_loss=1.442, generator_dur_loss=1.722, generator_adv_loss=1.99, generator_feat_match_loss=5.862, over 4610.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 06:19:03,130 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 06:19:12,124 INFO [train.py:591] (2/6) Epoch 760, validation: discriminator_loss=2.739, discriminator_real_loss=1.356, discriminator_fake_loss=1.383, generator_loss=27.28, generator_mel_loss=17.93, generator_kl_loss=1.275, generator_dur_loss=1.789, generator_adv_loss=1.87, generator_feat_match_loss=4.417, over 100.00 samples.
2024-03-15 06:19:12,125 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 06:21:03,347 INFO [train.py:919] (2/6) Start epoch 761
2024-03-15 06:22:00,523 INFO [train.py:527] (2/6) Epoch 761, batch 10, global_batch_idx: 94250, batch size: 42, loss[discriminator_loss=2.682, discriminator_real_loss=1.329, discriminator_fake_loss=1.353, generator_loss=29.32, generator_mel_loss=18.73, generator_kl_loss=1.416, generator_dur_loss=1.644, generator_adv_loss=1.895, generator_feat_match_loss=5.635, over 42.00 samples.], tot_loss[discriminator_loss=2.698, discriminator_real_loss=1.363, discriminator_fake_loss=1.336, generator_loss=28.52, generator_mel_loss=17.79, generator_kl_loss=1.366, generator_dur_loss=1.773, generator_adv_loss=1.956, generator_feat_match_loss=5.637, over 705.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 06:24:17,485 INFO [train.py:527] (2/6) Epoch 761, batch 60, global_batch_idx: 94300, batch size: 48, loss[discriminator_loss=2.647, discriminator_real_loss=1.333, discriminator_fake_loss=1.314, generator_loss=28.71, generator_mel_loss=17.71, generator_kl_loss=1.402, generator_dur_loss=1.613, generator_adv_loss=2.004, generator_feat_match_loss=5.982, over 48.00 samples.], tot_loss[discriminator_loss=2.682, discriminator_real_loss=1.352, discriminator_fake_loss=1.33, generator_loss=28.76, generator_mel_loss=17.84, generator_kl_loss=1.384, generator_dur_loss=1.753, generator_adv_loss=1.985, generator_feat_match_loss=5.803, over 3621.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 06:26:33,104 INFO [train.py:527] (2/6) Epoch 761, batch 110, global_batch_idx: 94350, batch size: 64, loss[discriminator_loss=2.654, discriminator_real_loss=1.319, discriminator_fake_loss=1.334, generator_loss=29.05, generator_mel_loss=17.87, generator_kl_loss=1.403, generator_dur_loss=1.734, generator_adv_loss=2.012, generator_feat_match_loss=6.036, over 64.00 samples.], tot_loss[discriminator_loss=2.682, discriminator_real_loss=1.353, discriminator_fake_loss=1.329, generator_loss=28.85, generator_mel_loss=17.87, generator_kl_loss=1.407, generator_dur_loss=1.751, generator_adv_loss=1.989, generator_feat_match_loss=5.826, over 6448.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 06:27:11,828 INFO [train.py:919] (2/6) Start epoch 762
2024-03-15 06:29:16,001 INFO [train.py:527] (2/6) Epoch 762, batch 36, global_batch_idx: 94400, batch size: 55, loss[discriminator_loss=2.709, discriminator_real_loss=1.386, discriminator_fake_loss=1.323, generator_loss=28.48, generator_mel_loss=17.63, generator_kl_loss=1.455, generator_dur_loss=1.727, generator_adv_loss=2.048, generator_feat_match_loss=5.614, over 55.00 samples.], tot_loss[discriminator_loss=2.672, discriminator_real_loss=1.345, discriminator_fake_loss=1.327, generator_loss=28.94, generator_mel_loss=17.79, generator_kl_loss=1.383, generator_dur_loss=1.768, generator_adv_loss=2.021, generator_feat_match_loss=5.976, over 2199.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 06:29:16,002 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 06:29:24,052 INFO [train.py:591] (2/6) Epoch 762, validation: discriminator_loss=2.744, discriminator_real_loss=1.394, discriminator_fake_loss=1.35, generator_loss=27.27, generator_mel_loss=17.94, generator_kl_loss=1.246, generator_dur_loss=1.804, generator_adv_loss=1.849, generator_feat_match_loss=4.43, over 100.00 samples.
2024-03-15 06:29:24,053 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 06:31:41,077 INFO [train.py:527] (2/6) Epoch 762, batch 86, global_batch_idx: 94450, batch size: 31, loss[discriminator_loss=2.694, discriminator_real_loss=1.404, discriminator_fake_loss=1.29, generator_loss=30.06, generator_mel_loss=18.28, generator_kl_loss=1.656, generator_dur_loss=1.603, generator_adv_loss=1.914, generator_feat_match_loss=6.604, over 31.00 samples.], tot_loss[discriminator_loss=2.681, discriminator_real_loss=1.355, discriminator_fake_loss=1.326, generator_loss=28.84, generator_mel_loss=17.85, generator_kl_loss=1.399, generator_dur_loss=1.753, generator_adv_loss=2.012, generator_feat_match_loss=5.831, over 5021.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 06:33:29,263 INFO [train.py:919] (2/6) Start epoch 763
2024-03-15 06:34:26,608 INFO [train.py:527] (2/6) Epoch 763, batch 12, global_batch_idx: 94500, batch size: 74, loss[discriminator_loss=2.592, discriminator_real_loss=1.31, discriminator_fake_loss=1.282, generator_loss=29.18, generator_mel_loss=18.07, generator_kl_loss=1.38, generator_dur_loss=1.762, generator_adv_loss=2.147, generator_feat_match_loss=5.825, over 74.00 samples.], tot_loss[discriminator_loss=2.697, discriminator_real_loss=1.366, discriminator_fake_loss=1.331, generator_loss=28.93, generator_mel_loss=17.93, generator_kl_loss=1.417, generator_dur_loss=1.748, generator_adv_loss=2.009, generator_feat_match_loss=5.833, over 766.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 06:36:48,848 INFO [train.py:527] (2/6) Epoch 763, batch 62, global_batch_idx: 94550, batch size: 16, loss[discriminator_loss=2.724, discriminator_real_loss=1.324, discriminator_fake_loss=1.4, generator_loss=29.63, generator_mel_loss=17.91, generator_kl_loss=2.024, generator_dur_loss=1.527, generator_adv_loss=1.84, generator_feat_match_loss=6.329, over 16.00 samples.], tot_loss[discriminator_loss=2.693, discriminator_real_loss=1.365, discriminator_fake_loss=1.328, generator_loss=28.81, generator_mel_loss=17.86, generator_kl_loss=1.419, generator_dur_loss=1.736, generator_adv_loss=1.997, generator_feat_match_loss=5.797, over 3383.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 06:39:08,292 INFO [train.py:527] (2/6) Epoch 763, batch 112, global_batch_idx: 94600, batch size: 64, loss[discriminator_loss=2.637, discriminator_real_loss=1.384, discriminator_fake_loss=1.254, generator_loss=29.21, generator_mel_loss=18.34, generator_kl_loss=1.38, generator_dur_loss=1.777, generator_adv_loss=2.016, generator_feat_match_loss=5.69, over 64.00 samples.], tot_loss[discriminator_loss=2.693, discriminator_real_loss=1.365, discriminator_fake_loss=1.328, generator_loss=28.81, generator_mel_loss=17.86, generator_kl_loss=1.416, generator_dur_loss=1.753, generator_adv_loss=1.997, generator_feat_match_loss=5.783, over 6484.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 06:39:08,293 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 06:39:17,118 INFO [train.py:591] (2/6) Epoch 763, validation: discriminator_loss=2.725, discriminator_real_loss=1.361, discriminator_fake_loss=1.364, generator_loss=28.29, generator_mel_loss=18.46, generator_kl_loss=1.198, generator_dur_loss=1.825, generator_adv_loss=1.876, generator_feat_match_loss=4.932, over 100.00 samples.
2024-03-15 06:39:17,118 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 06:39:50,550 INFO [train.py:919] (2/6) Start epoch 764
2024-03-15 06:42:01,012 INFO [train.py:527] (2/6) Epoch 764, batch 38, global_batch_idx: 94650, batch size: 36, loss[discriminator_loss=2.715, discriminator_real_loss=1.416, discriminator_fake_loss=1.299, generator_loss=28.72, generator_mel_loss=18.31, generator_kl_loss=1.396, generator_dur_loss=1.708, generator_adv_loss=2.021, generator_feat_match_loss=5.278, over 36.00 samples.], tot_loss[discriminator_loss=2.691, discriminator_real_loss=1.367, discriminator_fake_loss=1.325, generator_loss=28.78, generator_mel_loss=17.88, generator_kl_loss=1.383, generator_dur_loss=1.765, generator_adv_loss=1.997, generator_feat_match_loss=5.76, over 2401.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 06:44:20,427 INFO [train.py:527] (2/6) Epoch 764, batch 88, global_batch_idx: 94700, batch size: 50, loss[discriminator_loss=2.632, discriminator_real_loss=1.337, discriminator_fake_loss=1.296, generator_loss=28.51, generator_mel_loss=17.85, generator_kl_loss=1.321, generator_dur_loss=1.721, generator_adv_loss=1.981, generator_feat_match_loss=5.634, over 50.00 samples.], tot_loss[discriminator_loss=2.693, discriminator_real_loss=1.365, discriminator_fake_loss=1.327, generator_loss=28.9, generator_mel_loss=17.93, generator_kl_loss=1.421, generator_dur_loss=1.751, generator_adv_loss=1.989, generator_feat_match_loss=5.818, over 4977.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 06:45:59,345 INFO [train.py:919] (2/6) Start epoch 765
2024-03-15 06:47:02,915 INFO [train.py:527] (2/6) Epoch 765, batch 14, global_batch_idx: 94750, batch size: 61, loss[discriminator_loss=2.695, discriminator_real_loss=1.372, discriminator_fake_loss=1.323, generator_loss=29.38, generator_mel_loss=18, generator_kl_loss=1.484, generator_dur_loss=1.72, generator_adv_loss=2.112, generator_feat_match_loss=6.063, over 61.00 samples.], tot_loss[discriminator_loss=2.691, discriminator_real_loss=1.356, discriminator_fake_loss=1.335, generator_loss=28.57, generator_mel_loss=17.75, generator_kl_loss=1.408, generator_dur_loss=1.768, generator_adv_loss=1.984, generator_feat_match_loss=5.66, over 872.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 06:49:20,867 INFO [train.py:527] (2/6) Epoch 765, batch 64, global_batch_idx: 94800, batch size: 36, loss[discriminator_loss=2.704, discriminator_real_loss=1.358, discriminator_fake_loss=1.347, generator_loss=28.76, generator_mel_loss=18.05, generator_kl_loss=1.659, generator_dur_loss=1.665, generator_adv_loss=2.01, generator_feat_match_loss=5.373, over 36.00 samples.], tot_loss[discriminator_loss=2.693, discriminator_real_loss=1.367, discriminator_fake_loss=1.325, generator_loss=28.73, generator_mel_loss=17.78, generator_kl_loss=1.426, generator_dur_loss=1.752, generator_adv_loss=1.99, generator_feat_match_loss=5.78, over 3656.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 06:49:20,868 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 06:49:28,787 INFO [train.py:591] (2/6) Epoch 765, validation: discriminator_loss=2.703, discriminator_real_loss=1.356, discriminator_fake_loss=1.347, generator_loss=27.22, generator_mel_loss=18.13, generator_kl_loss=1.24, generator_dur_loss=1.814, generator_adv_loss=1.827, generator_feat_match_loss=4.21, over 100.00 samples.
2024-03-15 06:49:28,788 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 06:51:46,936 INFO [train.py:527] (2/6) Epoch 765, batch 114, global_batch_idx: 94850, batch size: 72, loss[discriminator_loss=2.793, discriminator_real_loss=1.485, discriminator_fake_loss=1.308, generator_loss=28.32, generator_mel_loss=17.72, generator_kl_loss=1.407, generator_dur_loss=1.798, generator_adv_loss=1.794, generator_feat_match_loss=5.603, over 72.00 samples.], tot_loss[discriminator_loss=2.686, discriminator_real_loss=1.36, discriminator_fake_loss=1.326, generator_loss=28.82, generator_mel_loss=17.84, generator_kl_loss=1.424, generator_dur_loss=1.754, generator_adv_loss=1.998, generator_feat_match_loss=5.803, over 6666.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 06:52:15,907 INFO [train.py:919] (2/6) Start epoch 766
2024-03-15 06:54:37,647 INFO [train.py:527] (2/6) Epoch 766, batch 40, global_batch_idx: 94900, batch size: 77, loss[discriminator_loss=2.65, discriminator_real_loss=1.328, discriminator_fake_loss=1.322, generator_loss=29.88, generator_mel_loss=17.99, generator_kl_loss=1.396, generator_dur_loss=1.854, generator_adv_loss=2.06, generator_feat_match_loss=6.585, over 77.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.364, discriminator_fake_loss=1.321, generator_loss=28.88, generator_mel_loss=17.8, generator_kl_loss=1.414, generator_dur_loss=1.754, generator_adv_loss=1.994, generator_feat_match_loss=5.923, over 2390.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 06:56:57,336 INFO [train.py:527] (2/6) Epoch 766, batch 90, global_batch_idx: 94950, batch size: 58, loss[discriminator_loss=2.693, discriminator_real_loss=1.377, discriminator_fake_loss=1.317, generator_loss=28.06, generator_mel_loss=17.8, generator_kl_loss=1.41, generator_dur_loss=1.701, generator_adv_loss=1.943, generator_feat_match_loss=5.204, over 58.00 samples.], tot_loss[discriminator_loss=2.686, discriminator_real_loss=1.362, discriminator_fake_loss=1.324, generator_loss=28.83, generator_mel_loss=17.81, generator_kl_loss=1.412, generator_dur_loss=1.75, generator_adv_loss=1.991, generator_feat_match_loss=5.869, over 5136.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 06:58:29,007 INFO [train.py:919] (2/6) Start epoch 767
2024-03-15 06:59:38,289 INFO [train.py:527] (2/6) Epoch 767, batch 16, global_batch_idx: 95000, batch size: 68, loss[discriminator_loss=2.691, discriminator_real_loss=1.391, discriminator_fake_loss=1.3, generator_loss=28.84, generator_mel_loss=17.92, generator_kl_loss=1.482, generator_dur_loss=1.796, generator_adv_loss=2.003, generator_feat_match_loss=5.638, over 68.00 samples.], tot_loss[discriminator_loss=2.688, discriminator_real_loss=1.358, discriminator_fake_loss=1.33, generator_loss=29.18, generator_mel_loss=17.91, generator_kl_loss=1.463, generator_dur_loss=1.743, generator_adv_loss=1.985, generator_feat_match_loss=6.073, over 887.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 06:59:38,291 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 06:59:46,427 INFO [train.py:591] (2/6) Epoch 767, validation: discriminator_loss=2.728, discriminator_real_loss=1.395, discriminator_fake_loss=1.333, generator_loss=28.28, generator_mel_loss=18.79, generator_kl_loss=1.264, generator_dur_loss=1.824, generator_adv_loss=1.876, generator_feat_match_loss=4.527, over 100.00 samples.
2024-03-15 06:59:46,428 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 07:02:10,556 INFO [train.py:527] (2/6) Epoch 767, batch 66, global_batch_idx: 95050, batch size: 62, loss[discriminator_loss=2.698, discriminator_real_loss=1.298, discriminator_fake_loss=1.401, generator_loss=28.28, generator_mel_loss=17.94, generator_kl_loss=1.242, generator_dur_loss=1.756, generator_adv_loss=1.99, generator_feat_match_loss=5.354, over 62.00 samples.], tot_loss[discriminator_loss=2.682, discriminator_real_loss=1.361, discriminator_fake_loss=1.321, generator_loss=28.94, generator_mel_loss=17.85, generator_kl_loss=1.427, generator_dur_loss=1.747, generator_adv_loss=1.991, generator_feat_match_loss=5.926, over 3725.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 07:04:29,915 INFO [train.py:527] (2/6) Epoch 767, batch 116, global_batch_idx: 95100, batch size: 14, loss[discriminator_loss=2.714, discriminator_real_loss=1.316, discriminator_fake_loss=1.398, generator_loss=30.11, generator_mel_loss=19.11, generator_kl_loss=1.983, generator_dur_loss=1.545, generator_adv_loss=2.169, generator_feat_match_loss=5.302, over 14.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.361, discriminator_fake_loss=1.324, generator_loss=28.88, generator_mel_loss=17.85, generator_kl_loss=1.423, generator_dur_loss=1.749, generator_adv_loss=1.992, generator_feat_match_loss=5.866, over 6525.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 07:04:50,212 INFO [train.py:919] (2/6) Start epoch 768
2024-03-15 07:07:12,329 INFO [train.py:527] (2/6) Epoch 768, batch 42, global_batch_idx: 95150, batch size: 59, loss[discriminator_loss=2.663, discriminator_real_loss=1.362, discriminator_fake_loss=1.301, generator_loss=28.2, generator_mel_loss=17.91, generator_kl_loss=1.312, generator_dur_loss=1.792, generator_adv_loss=2.173, generator_feat_match_loss=5.014, over 59.00 samples.], tot_loss[discriminator_loss=2.686, discriminator_real_loss=1.362, discriminator_fake_loss=1.325, generator_loss=28.78, generator_mel_loss=17.88, generator_kl_loss=1.389, generator_dur_loss=1.748, generator_adv_loss=1.99, generator_feat_match_loss=5.776, over 2585.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 07:09:33,710 INFO [train.py:527] (2/6) Epoch 768, batch 92, global_batch_idx: 95200, batch size: 74, loss[discriminator_loss=2.747, discriminator_real_loss=1.42, discriminator_fake_loss=1.328, generator_loss=28.55, generator_mel_loss=17.78, generator_kl_loss=1.274, generator_dur_loss=1.791, generator_adv_loss=2.103, generator_feat_match_loss=5.607, over 74.00 samples.], tot_loss[discriminator_loss=2.687, discriminator_real_loss=1.359, discriminator_fake_loss=1.328, generator_loss=28.95, generator_mel_loss=17.92, generator_kl_loss=1.409, generator_dur_loss=1.745, generator_adv_loss=2.01, generator_feat_match_loss=5.865, over 5325.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 07:09:33,712 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 07:09:42,415 INFO [train.py:591] (2/6) Epoch 768, validation: discriminator_loss=2.752, discriminator_real_loss=1.483, discriminator_fake_loss=1.269, generator_loss=27.97, generator_mel_loss=18.22, generator_kl_loss=1.299, generator_dur_loss=1.825, generator_adv_loss=2.032, generator_feat_match_loss=4.6, over 100.00 samples.
2024-03-15 07:09:42,416 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 07:11:12,259 INFO [train.py:919] (2/6) Start epoch 769
2024-03-15 07:12:30,309 INFO [train.py:527] (2/6) Epoch 769, batch 18, global_batch_idx: 95250, batch size: 58, loss[discriminator_loss=2.657, discriminator_real_loss=1.271, discriminator_fake_loss=1.386, generator_loss=29.08, generator_mel_loss=17.98, generator_kl_loss=1.451, generator_dur_loss=1.767, generator_adv_loss=2.122, generator_feat_match_loss=5.76, over 58.00 samples.], tot_loss[discriminator_loss=2.677, discriminator_real_loss=1.351, discriminator_fake_loss=1.326, generator_loss=28.82, generator_mel_loss=17.76, generator_kl_loss=1.382, generator_dur_loss=1.776, generator_adv_loss=2.008, generator_feat_match_loss=5.898, over 1219.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 07:14:48,427 INFO [train.py:527] (2/6) Epoch 769, batch 68, global_batch_idx: 95300, batch size: 52, loss[discriminator_loss=2.682, discriminator_real_loss=1.354, discriminator_fake_loss=1.328, generator_loss=28.99, generator_mel_loss=18.14, generator_kl_loss=1.427, generator_dur_loss=1.657, generator_adv_loss=1.801, generator_feat_match_loss=5.959, over 52.00 samples.], tot_loss[discriminator_loss=2.687, discriminator_real_loss=1.358, discriminator_fake_loss=1.329, generator_loss=28.82, generator_mel_loss=17.86, generator_kl_loss=1.409, generator_dur_loss=1.752, generator_adv_loss=1.996, generator_feat_match_loss=5.803, over 4034.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 07:17:09,070 INFO [train.py:527] (2/6) Epoch 769, batch 118, global_batch_idx: 95350, batch size: 15, loss[discriminator_loss=2.749, discriminator_real_loss=1.304, discriminator_fake_loss=1.445, generator_loss=30.78, generator_mel_loss=18.69, generator_kl_loss=2.038, generator_dur_loss=1.579, generator_adv_loss=2.271, generator_feat_match_loss=6.206, over 15.00 samples.], tot_loss[discriminator_loss=2.681, discriminator_real_loss=1.355, discriminator_fake_loss=1.326, generator_loss=28.87, generator_mel_loss=17.88, generator_kl_loss=1.399, generator_dur_loss=1.755, generator_adv_loss=2.001, generator_feat_match_loss=5.839, over 6794.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 07:17:24,515 INFO [train.py:919] (2/6) Start epoch 770
2024-03-15 07:19:54,023 INFO [train.py:527] (2/6) Epoch 770, batch 44, global_batch_idx: 95400, batch size: 47, loss[discriminator_loss=2.727, discriminator_real_loss=1.461, discriminator_fake_loss=1.266, generator_loss=28.44, generator_mel_loss=17.69, generator_kl_loss=1.445, generator_dur_loss=1.713, generator_adv_loss=1.83, generator_feat_match_loss=5.755, over 47.00 samples.], tot_loss[discriminator_loss=2.693, discriminator_real_loss=1.364, discriminator_fake_loss=1.329, generator_loss=28.8, generator_mel_loss=17.9, generator_kl_loss=1.43, generator_dur_loss=1.746, generator_adv_loss=1.98, generator_feat_match_loss=5.741, over 2555.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 07:19:54,024 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 07:20:02,102 INFO [train.py:591] (2/6) Epoch 770, validation: discriminator_loss=2.748, discriminator_real_loss=1.255, discriminator_fake_loss=1.493, generator_loss=27.08, generator_mel_loss=18.05, generator_kl_loss=1.151, generator_dur_loss=1.836, generator_adv_loss=1.717, generator_feat_match_loss=4.324, over 100.00 samples.
2024-03-15 07:20:02,103 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 07:22:21,234 INFO [train.py:527] (2/6) Epoch 770, batch 94, global_batch_idx: 95450, batch size: 55, loss[discriminator_loss=2.62, discriminator_real_loss=1.307, discriminator_fake_loss=1.313, generator_loss=29.97, generator_mel_loss=18.12, generator_kl_loss=1.556, generator_dur_loss=1.737, generator_adv_loss=2.084, generator_feat_match_loss=6.473, over 55.00 samples.], tot_loss[discriminator_loss=2.69, discriminator_real_loss=1.361, discriminator_fake_loss=1.329, generator_loss=28.89, generator_mel_loss=17.92, generator_kl_loss=1.425, generator_dur_loss=1.744, generator_adv_loss=1.984, generator_feat_match_loss=5.819, over 5278.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 07:23:44,026 INFO [train.py:919] (2/6) Start epoch 771
2024-03-15 07:25:07,403 INFO [train.py:527] (2/6) Epoch 771, batch 20, global_batch_idx: 95500, batch size: 45, loss[discriminator_loss=2.684, discriminator_real_loss=1.391, discriminator_fake_loss=1.292, generator_loss=28.6, generator_mel_loss=17.65, generator_kl_loss=1.496, generator_dur_loss=1.657, generator_adv_loss=1.901, generator_feat_match_loss=5.897, over 45.00 samples.], tot_loss[discriminator_loss=2.677, discriminator_real_loss=1.368, discriminator_fake_loss=1.31, generator_loss=28.95, generator_mel_loss=17.88, generator_kl_loss=1.431, generator_dur_loss=1.754, generator_adv_loss=2.019, generator_feat_match_loss=5.865, over 1168.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 07:27:27,450 INFO [train.py:527] (2/6) Epoch 771, batch 70, global_batch_idx: 95550, batch size: 80, loss[discriminator_loss=2.662, discriminator_real_loss=1.334, discriminator_fake_loss=1.328, generator_loss=28.66, generator_mel_loss=17.81, generator_kl_loss=1.438, generator_dur_loss=1.804, generator_adv_loss=1.969, generator_feat_match_loss=5.637, over 80.00 samples.], tot_loss[discriminator_loss=2.691, discriminator_real_loss=1.366, discriminator_fake_loss=1.325, generator_loss=28.82, generator_mel_loss=17.88, generator_kl_loss=1.413, generator_dur_loss=1.754, generator_adv_loss=1.994, generator_feat_match_loss=5.783, over 4073.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 07:29:46,215 INFO [train.py:527] (2/6) Epoch 771, batch 120, global_batch_idx: 95600, batch size: 44, loss[discriminator_loss=2.679, discriminator_real_loss=1.4, discriminator_fake_loss=1.279, generator_loss=30.03, generator_mel_loss=18.2, generator_kl_loss=1.588, generator_dur_loss=1.667, generator_adv_loss=2.038, generator_feat_match_loss=6.541, over 44.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.362, discriminator_fake_loss=1.323, generator_loss=28.85, generator_mel_loss=17.89, generator_kl_loss=1.412, generator_dur_loss=1.753, generator_adv_loss=1.997, generator_feat_match_loss=5.802, over 6901.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 07:29:46,217 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 07:29:54,766 INFO [train.py:591] (2/6) Epoch 771, validation: discriminator_loss=2.72, discriminator_real_loss=1.362, discriminator_fake_loss=1.358, generator_loss=27.5, generator_mel_loss=18, generator_kl_loss=1.266, generator_dur_loss=1.818, generator_adv_loss=1.857, generator_feat_match_loss=4.555, over 100.00 samples.
2024-03-15 07:29:54,767 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 07:30:05,147 INFO [train.py:919] (2/6) Start epoch 772
2024-03-15 07:32:36,061 INFO [train.py:527] (2/6) Epoch 772, batch 46, global_batch_idx: 95650, batch size: 56, loss[discriminator_loss=2.639, discriminator_real_loss=1.374, discriminator_fake_loss=1.264, generator_loss=29.12, generator_mel_loss=17.88, generator_kl_loss=1.457, generator_dur_loss=1.736, generator_adv_loss=2.01, generator_feat_match_loss=6.044, over 56.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.347, discriminator_fake_loss=1.329, generator_loss=29.03, generator_mel_loss=17.89, generator_kl_loss=1.399, generator_dur_loss=1.748, generator_adv_loss=2.017, generator_feat_match_loss=5.969, over 2762.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 07:34:53,279 INFO [train.py:527] (2/6) Epoch 772, batch 96, global_batch_idx: 95700, batch size: 70, loss[discriminator_loss=2.678, discriminator_real_loss=1.337, discriminator_fake_loss=1.341, generator_loss=29.08, generator_mel_loss=17.8, generator_kl_loss=1.457, generator_dur_loss=1.793, generator_adv_loss=2.04, generator_feat_match_loss=5.988, over 70.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.356, discriminator_fake_loss=1.328, generator_loss=28.99, generator_mel_loss=17.93, generator_kl_loss=1.417, generator_dur_loss=1.733, generator_adv_loss=2.006, generator_feat_match_loss=5.902, over 5508.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 07:36:04,804 INFO [train.py:919] (2/6) Start epoch 773
2024-03-15 07:37:30,023 INFO [train.py:527] (2/6) Epoch 773, batch 22, global_batch_idx: 95750, batch size: 64, loss[discriminator_loss=2.655, discriminator_real_loss=1.319, discriminator_fake_loss=1.336, generator_loss=30.02, generator_mel_loss=18.15, generator_kl_loss=1.327, generator_dur_loss=1.797, generator_adv_loss=2.077, generator_feat_match_loss=6.667, over 64.00 samples.], tot_loss[discriminator_loss=2.682, discriminator_real_loss=1.349, discriminator_fake_loss=1.333, generator_loss=29.06, generator_mel_loss=17.97, generator_kl_loss=1.425, generator_dur_loss=1.74, generator_adv_loss=1.991, generator_feat_match_loss=5.942, over 1330.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 07:39:48,036 INFO [train.py:527] (2/6) Epoch 773, batch 72, global_batch_idx: 95800, batch size: 56, loss[discriminator_loss=2.635, discriminator_real_loss=1.358, discriminator_fake_loss=1.277, generator_loss=28.88, generator_mel_loss=17.95, generator_kl_loss=1.453, generator_dur_loss=1.716, generator_adv_loss=2.091, generator_feat_match_loss=5.674, over 56.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.357, discriminator_fake_loss=1.326, generator_loss=28.87, generator_mel_loss=17.88, generator_kl_loss=1.427, generator_dur_loss=1.738, generator_adv_loss=1.987, generator_feat_match_loss=5.844, over 4142.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 07:39:48,038 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 07:39:56,234 INFO [train.py:591] (2/6) Epoch 773, validation: discriminator_loss=2.719, discriminator_real_loss=1.421, discriminator_fake_loss=1.298, generator_loss=27.94, generator_mel_loss=18.55, generator_kl_loss=1.249, generator_dur_loss=1.8, generator_adv_loss=1.939, generator_feat_match_loss=4.4, over 100.00 samples.
2024-03-15 07:39:56,235 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 07:42:19,784 INFO [train.py:527] (2/6) Epoch 773, batch 122, global_batch_idx: 95850, batch size: 15, loss[discriminator_loss=2.709, discriminator_real_loss=1.499, discriminator_fake_loss=1.21, generator_loss=28.34, generator_mel_loss=18.28, generator_kl_loss=1.513, generator_dur_loss=1.633, generator_adv_loss=2.004, generator_feat_match_loss=4.916, over 15.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.358, discriminator_fake_loss=1.327, generator_loss=28.83, generator_mel_loss=17.86, generator_kl_loss=1.43, generator_dur_loss=1.743, generator_adv_loss=1.998, generator_feat_match_loss=5.803, over 6818.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 07:42:24,486 INFO [train.py:919] (2/6) Start epoch 774
2024-03-15 07:45:02,257 INFO [train.py:527] (2/6) Epoch 774, batch 48, global_batch_idx: 95900, batch size: 88, loss[discriminator_loss=2.624, discriminator_real_loss=1.328, discriminator_fake_loss=1.296, generator_loss=29.1, generator_mel_loss=18.07, generator_kl_loss=1.153, generator_dur_loss=1.872, generator_adv_loss=2.033, generator_feat_match_loss=5.966, over 88.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.351, discriminator_fake_loss=1.334, generator_loss=28.7, generator_mel_loss=17.87, generator_kl_loss=1.384, generator_dur_loss=1.743, generator_adv_loss=1.973, generator_feat_match_loss=5.738, over 2857.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 07:47:22,499 INFO [train.py:527] (2/6) Epoch 774, batch 98, global_batch_idx: 95950, batch size: 72, loss[discriminator_loss=2.749, discriminator_real_loss=1.225, discriminator_fake_loss=1.524, generator_loss=29.81, generator_mel_loss=18.12, generator_kl_loss=1.394, generator_dur_loss=1.765, generator_adv_loss=2.215, generator_feat_match_loss=6.316, over 72.00 samples.], tot_loss[discriminator_loss=2.683, discriminator_real_loss=1.351, discriminator_fake_loss=1.331, generator_loss=28.76, generator_mel_loss=17.85, generator_kl_loss=1.385, generator_dur_loss=1.744, generator_adv_loss=1.985, generator_feat_match_loss=5.797, over 5851.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 07:48:32,639 INFO [train.py:919] (2/6) Start epoch 775
2024-03-15 07:50:03,362 INFO [train.py:527] (2/6) Epoch 775, batch 24, global_batch_idx: 96000, batch size: 55, loss[discriminator_loss=2.694, discriminator_real_loss=1.393, discriminator_fake_loss=1.3, generator_loss=28.69, generator_mel_loss=17.76, generator_kl_loss=1.445, generator_dur_loss=1.715, generator_adv_loss=2.084, generator_feat_match_loss=5.68, over 55.00 samples.], tot_loss[discriminator_loss=2.69, discriminator_real_loss=1.349, discriminator_fake_loss=1.341, generator_loss=28.83, generator_mel_loss=17.89, generator_kl_loss=1.403, generator_dur_loss=1.75, generator_adv_loss=1.973, generator_feat_match_loss=5.81, over 1597.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 07:50:03,363 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 07:50:11,377 INFO [train.py:591] (2/6) Epoch 775, validation: discriminator_loss=2.773, discriminator_real_loss=1.462, discriminator_fake_loss=1.31, generator_loss=28.08, generator_mel_loss=18.36, generator_kl_loss=1.192, generator_dur_loss=1.785, generator_adv_loss=1.999, generator_feat_match_loss=4.746, over 100.00 samples.
2024-03-15 07:50:11,377 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 07:52:32,672 INFO [train.py:527] (2/6) Epoch 775, batch 74, global_batch_idx: 96050, batch size: 66, loss[discriminator_loss=2.703, discriminator_real_loss=1.379, discriminator_fake_loss=1.323, generator_loss=27.47, generator_mel_loss=17.66, generator_kl_loss=1.29, generator_dur_loss=1.743, generator_adv_loss=1.86, generator_feat_match_loss=4.921, over 66.00 samples.], tot_loss[discriminator_loss=2.686, discriminator_real_loss=1.361, discriminator_fake_loss=1.325, generator_loss=28.86, generator_mel_loss=17.86, generator_kl_loss=1.396, generator_dur_loss=1.746, generator_adv_loss=1.992, generator_feat_match_loss=5.859, over 4609.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 07:54:46,801 INFO [train.py:919] (2/6) Start epoch 776
2024-03-15 07:55:09,626 INFO [train.py:527] (2/6) Epoch 776, batch 0, global_batch_idx: 96100, batch size: 31, loss[discriminator_loss=2.736, discriminator_real_loss=1.4, discriminator_fake_loss=1.336, generator_loss=29.93, generator_mel_loss=18.13, generator_kl_loss=1.657, generator_dur_loss=1.594, generator_adv_loss=1.912, generator_feat_match_loss=6.639, over 31.00 samples.], tot_loss[discriminator_loss=2.736, discriminator_real_loss=1.4, discriminator_fake_loss=1.336, generator_loss=29.93, generator_mel_loss=18.13, generator_kl_loss=1.657, generator_dur_loss=1.594, generator_adv_loss=1.912, generator_feat_match_loss=6.639, over 31.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 07:57:27,813 INFO [train.py:527] (2/6) Epoch 776, batch 50, global_batch_idx: 96150, batch size: 64, loss[discriminator_loss=2.653, discriminator_real_loss=1.342, discriminator_fake_loss=1.312, generator_loss=30.01, generator_mel_loss=18.22, generator_kl_loss=1.47, generator_dur_loss=1.682, generator_adv_loss=2.046, generator_feat_match_loss=6.594, over 64.00 samples.], tot_loss[discriminator_loss=2.694, discriminator_real_loss=1.359, discriminator_fake_loss=1.334, generator_loss=28.89, generator_mel_loss=17.87, generator_kl_loss=1.445, generator_dur_loss=1.724, generator_adv_loss=1.987, generator_feat_match_loss=5.871, over 2736.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 07:59:46,261 INFO [train.py:527] (2/6) Epoch 776, batch 100, global_batch_idx: 96200, batch size: 66, loss[discriminator_loss=2.734, discriminator_real_loss=1.273, discriminator_fake_loss=1.46, generator_loss=27.77, generator_mel_loss=17.46, generator_kl_loss=1.232, generator_dur_loss=1.77, generator_adv_loss=2.043, generator_feat_match_loss=5.269, over 66.00 samples.], tot_loss[discriminator_loss=2.689, discriminator_real_loss=1.36, discriminator_fake_loss=1.33, generator_loss=28.85, generator_mel_loss=17.84, generator_kl_loss=1.432, generator_dur_loss=1.727, generator_adv_loss=1.985, generator_feat_match_loss=5.862, over 5681.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 07:59:46,263 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 07:59:55,169 INFO [train.py:591] (2/6) Epoch 776, validation: discriminator_loss=2.694, discriminator_real_loss=1.449, discriminator_fake_loss=1.245, generator_loss=27.8, generator_mel_loss=17.95, generator_kl_loss=1.386, generator_dur_loss=1.784, generator_adv_loss=2.037, generator_feat_match_loss=4.642, over 100.00 samples.
2024-03-15 07:59:55,170 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 08:01:00,533 INFO [train.py:919] (2/6) Start epoch 777
2024-03-15 08:02:38,119 INFO [train.py:527] (2/6) Epoch 777, batch 26, global_batch_idx: 96250, batch size: 39, loss[discriminator_loss=2.704, discriminator_real_loss=1.39, discriminator_fake_loss=1.314, generator_loss=29.19, generator_mel_loss=18.01, generator_kl_loss=1.541, generator_dur_loss=1.649, generator_adv_loss=2.085, generator_feat_match_loss=5.912, over 39.00 samples.], tot_loss[discriminator_loss=2.69, discriminator_real_loss=1.359, discriminator_fake_loss=1.332, generator_loss=28.95, generator_mel_loss=17.87, generator_kl_loss=1.404, generator_dur_loss=1.744, generator_adv_loss=2.003, generator_feat_match_loss=5.929, over 1640.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 08:04:57,615 INFO [train.py:527] (2/6) Epoch 777, batch 76, global_batch_idx: 96300, batch size: 15, loss[discriminator_loss=2.692, discriminator_real_loss=1.42, discriminator_fake_loss=1.272, generator_loss=29.15, generator_mel_loss=18.14, generator_kl_loss=1.844, generator_dur_loss=1.543, generator_adv_loss=1.949, generator_feat_match_loss=5.674, over 15.00 samples.], tot_loss[discriminator_loss=2.688, discriminator_real_loss=1.358, discriminator_fake_loss=1.33, generator_loss=28.8, generator_mel_loss=17.82, generator_kl_loss=1.422, generator_dur_loss=1.739, generator_adv_loss=2.009, generator_feat_match_loss=5.805, over 4476.00 samples.], cur_lr_g: 1.82e-04, cur_lr_d: 1.82e-04, 
2024-03-15 08:07:07,601 INFO [train.py:919] (2/6) Start epoch 778
2024-03-15 08:07:37,270 INFO [train.py:527] (2/6) Epoch 778, batch 2, global_batch_idx: 96350, batch size: 88, loss[discriminator_loss=2.687, discriminator_real_loss=1.329, discriminator_fake_loss=1.358, generator_loss=28.57, generator_mel_loss=17.8, generator_kl_loss=1.2, generator_dur_loss=1.856, generator_adv_loss=2.041, generator_feat_match_loss=5.67, over 88.00 samples.], tot_loss[discriminator_loss=2.675, discriminator_real_loss=1.355, discriminator_fake_loss=1.32, generator_loss=28.76, generator_mel_loss=17.94, generator_kl_loss=1.305, generator_dur_loss=1.801, generator_adv_loss=2.015, generator_feat_match_loss=5.701, over 215.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 08:09:57,647 INFO [train.py:527] (2/6) Epoch 778, batch 52, global_batch_idx: 96400, batch size: 68, loss[discriminator_loss=2.739, discriminator_real_loss=1.419, discriminator_fake_loss=1.321, generator_loss=29.24, generator_mel_loss=17.88, generator_kl_loss=1.378, generator_dur_loss=1.746, generator_adv_loss=1.878, generator_feat_match_loss=6.357, over 68.00 samples.], tot_loss[discriminator_loss=2.693, discriminator_real_loss=1.364, discriminator_fake_loss=1.329, generator_loss=28.99, generator_mel_loss=17.94, generator_kl_loss=1.39, generator_dur_loss=1.738, generator_adv_loss=1.999, generator_feat_match_loss=5.922, over 3089.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 08:09:57,649 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 08:10:05,731 INFO [train.py:591] (2/6) Epoch 778, validation: discriminator_loss=2.767, discriminator_real_loss=1.43, discriminator_fake_loss=1.337, generator_loss=26.99, generator_mel_loss=17.76, generator_kl_loss=1.265, generator_dur_loss=1.784, generator_adv_loss=1.821, generator_feat_match_loss=4.354, over 100.00 samples.
2024-03-15 08:10:05,732 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 08:12:23,796 INFO [train.py:527] (2/6) Epoch 778, batch 102, global_batch_idx: 96450, batch size: 36, loss[discriminator_loss=2.734, discriminator_real_loss=1.384, discriminator_fake_loss=1.351, generator_loss=28.5, generator_mel_loss=17.98, generator_kl_loss=1.519, generator_dur_loss=1.579, generator_adv_loss=1.925, generator_feat_match_loss=5.494, over 36.00 samples.], tot_loss[discriminator_loss=2.689, discriminator_real_loss=1.362, discriminator_fake_loss=1.327, generator_loss=28.93, generator_mel_loss=17.92, generator_kl_loss=1.419, generator_dur_loss=1.728, generator_adv_loss=2.002, generator_feat_match_loss=5.859, over 5858.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 08:13:21,446 INFO [train.py:919] (2/6) Start epoch 779
2024-03-15 08:15:01,041 INFO [train.py:527] (2/6) Epoch 779, batch 28, global_batch_idx: 96500, batch size: 48, loss[discriminator_loss=2.706, discriminator_real_loss=1.471, discriminator_fake_loss=1.235, generator_loss=28.57, generator_mel_loss=17.61, generator_kl_loss=1.612, generator_dur_loss=1.655, generator_adv_loss=1.933, generator_feat_match_loss=5.754, over 48.00 samples.], tot_loss[discriminator_loss=2.711, discriminator_real_loss=1.373, discriminator_fake_loss=1.338, generator_loss=28.84, generator_mel_loss=17.92, generator_kl_loss=1.405, generator_dur_loss=1.728, generator_adv_loss=2.001, generator_feat_match_loss=5.782, over 1635.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 08:17:20,626 INFO [train.py:527] (2/6) Epoch 779, batch 78, global_batch_idx: 96550, batch size: 64, loss[discriminator_loss=2.691, discriminator_real_loss=1.394, discriminator_fake_loss=1.298, generator_loss=28.61, generator_mel_loss=17.82, generator_kl_loss=1.398, generator_dur_loss=1.748, generator_adv_loss=1.999, generator_feat_match_loss=5.651, over 64.00 samples.], tot_loss[discriminator_loss=2.692, discriminator_real_loss=1.361, discriminator_fake_loss=1.331, generator_loss=28.83, generator_mel_loss=17.86, generator_kl_loss=1.414, generator_dur_loss=1.728, generator_adv_loss=1.994, generator_feat_match_loss=5.835, over 4538.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 08:19:30,741 INFO [train.py:919] (2/6) Start epoch 780
2024-03-15 08:20:06,474 INFO [train.py:527] (2/6) Epoch 780, batch 4, global_batch_idx: 96600, batch size: 96, loss[discriminator_loss=2.694, discriminator_real_loss=1.379, discriminator_fake_loss=1.315, generator_loss=28.87, generator_mel_loss=17.86, generator_kl_loss=1.417, generator_dur_loss=1.853, generator_adv_loss=1.978, generator_feat_match_loss=5.76, over 96.00 samples.], tot_loss[discriminator_loss=2.693, discriminator_real_loss=1.376, discriminator_fake_loss=1.317, generator_loss=29, generator_mel_loss=17.92, generator_kl_loss=1.398, generator_dur_loss=1.786, generator_adv_loss=1.99, generator_feat_match_loss=5.905, over 337.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 08:20:06,490 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 08:20:14,316 INFO [train.py:591] (2/6) Epoch 780, validation: discriminator_loss=2.714, discriminator_real_loss=1.425, discriminator_fake_loss=1.289, generator_loss=27.68, generator_mel_loss=18.14, generator_kl_loss=1.341, generator_dur_loss=1.807, generator_adv_loss=1.923, generator_feat_match_loss=4.46, over 100.00 samples.
2024-03-15 08:20:14,318 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 08:22:32,365 INFO [train.py:527] (2/6) Epoch 780, batch 54, global_batch_idx: 96650, batch size: 80, loss[discriminator_loss=2.732, discriminator_real_loss=1.421, discriminator_fake_loss=1.311, generator_loss=27.56, generator_mel_loss=17.42, generator_kl_loss=1.317, generator_dur_loss=1.814, generator_adv_loss=1.873, generator_feat_match_loss=5.138, over 80.00 samples.], tot_loss[discriminator_loss=2.674, discriminator_real_loss=1.358, discriminator_fake_loss=1.315, generator_loss=28.81, generator_mel_loss=17.82, generator_kl_loss=1.408, generator_dur_loss=1.751, generator_adv_loss=1.989, generator_feat_match_loss=5.839, over 3284.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 08:24:52,793 INFO [train.py:527] (2/6) Epoch 780, batch 104, global_batch_idx: 96700, batch size: 42, loss[discriminator_loss=2.701, discriminator_real_loss=1.421, discriminator_fake_loss=1.279, generator_loss=28.8, generator_mel_loss=18.07, generator_kl_loss=1.557, generator_dur_loss=1.717, generator_adv_loss=1.961, generator_feat_match_loss=5.495, over 42.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.357, discriminator_fake_loss=1.318, generator_loss=28.82, generator_mel_loss=17.83, generator_kl_loss=1.408, generator_dur_loss=1.752, generator_adv_loss=1.991, generator_feat_match_loss=5.845, over 6227.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 08:25:47,773 INFO [train.py:919] (2/6) Start epoch 781
2024-03-15 08:27:38,888 INFO [train.py:527] (2/6) Epoch 781, batch 30, global_batch_idx: 96750, batch size: 64, loss[discriminator_loss=2.685, discriminator_real_loss=1.328, discriminator_fake_loss=1.357, generator_loss=29.32, generator_mel_loss=17.99, generator_kl_loss=1.4, generator_dur_loss=1.769, generator_adv_loss=2.022, generator_feat_match_loss=6.138, over 64.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.353, discriminator_fake_loss=1.332, generator_loss=28.83, generator_mel_loss=17.94, generator_kl_loss=1.435, generator_dur_loss=1.726, generator_adv_loss=1.999, generator_feat_match_loss=5.731, over 1657.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 08:29:55,338 INFO [train.py:527] (2/6) Epoch 781, batch 80, global_batch_idx: 96800, batch size: 66, loss[discriminator_loss=2.617, discriminator_real_loss=1.243, discriminator_fake_loss=1.374, generator_loss=29.3, generator_mel_loss=17.6, generator_kl_loss=1.41, generator_dur_loss=1.709, generator_adv_loss=2.116, generator_feat_match_loss=6.466, over 66.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.36, discriminator_fake_loss=1.325, generator_loss=28.86, generator_mel_loss=17.91, generator_kl_loss=1.434, generator_dur_loss=1.727, generator_adv_loss=1.993, generator_feat_match_loss=5.795, over 4385.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 08:29:55,340 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 08:30:03,855 INFO [train.py:591] (2/6) Epoch 781, validation: discriminator_loss=2.686, discriminator_real_loss=1.39, discriminator_fake_loss=1.296, generator_loss=28.29, generator_mel_loss=18.24, generator_kl_loss=1.335, generator_dur_loss=1.794, generator_adv_loss=1.944, generator_feat_match_loss=4.978, over 100.00 samples.
2024-03-15 08:30:03,856 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 08:32:07,255 INFO [train.py:919] (2/6) Start epoch 782
2024-03-15 08:32:49,296 INFO [train.py:527] (2/6) Epoch 782, batch 6, global_batch_idx: 96850, batch size: 48, loss[discriminator_loss=2.704, discriminator_real_loss=1.303, discriminator_fake_loss=1.401, generator_loss=29.38, generator_mel_loss=18.16, generator_kl_loss=1.677, generator_dur_loss=1.677, generator_adv_loss=2.013, generator_feat_match_loss=5.849, over 48.00 samples.], tot_loss[discriminator_loss=2.703, discriminator_real_loss=1.381, discriminator_fake_loss=1.322, generator_loss=29.33, generator_mel_loss=17.98, generator_kl_loss=1.498, generator_dur_loss=1.732, generator_adv_loss=2.003, generator_feat_match_loss=6.121, over 429.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 08:35:10,459 INFO [train.py:527] (2/6) Epoch 782, batch 56, global_batch_idx: 96900, batch size: 77, loss[discriminator_loss=2.69, discriminator_real_loss=1.362, discriminator_fake_loss=1.328, generator_loss=28.61, generator_mel_loss=17.74, generator_kl_loss=1.269, generator_dur_loss=1.82, generator_adv_loss=1.911, generator_feat_match_loss=5.865, over 77.00 samples.], tot_loss[discriminator_loss=2.688, discriminator_real_loss=1.357, discriminator_fake_loss=1.331, generator_loss=28.91, generator_mel_loss=17.85, generator_kl_loss=1.407, generator_dur_loss=1.752, generator_adv_loss=1.986, generator_feat_match_loss=5.907, over 3506.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 08:37:28,877 INFO [train.py:527] (2/6) Epoch 782, batch 106, global_batch_idx: 96950, batch size: 50, loss[discriminator_loss=2.692, discriminator_real_loss=1.247, discriminator_fake_loss=1.445, generator_loss=30.36, generator_mel_loss=18.16, generator_kl_loss=1.662, generator_dur_loss=1.674, generator_adv_loss=1.908, generator_feat_match_loss=6.954, over 50.00 samples.], tot_loss[discriminator_loss=2.686, discriminator_real_loss=1.354, discriminator_fake_loss=1.332, generator_loss=28.99, generator_mel_loss=17.89, generator_kl_loss=1.427, generator_dur_loss=1.742, generator_adv_loss=1.99, generator_feat_match_loss=5.941, over 6129.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 08:38:15,171 INFO [train.py:919] (2/6) Start epoch 783
2024-03-15 08:40:07,260 INFO [train.py:527] (2/6) Epoch 783, batch 32, global_batch_idx: 97000, batch size: 83, loss[discriminator_loss=2.652, discriminator_real_loss=1.359, discriminator_fake_loss=1.293, generator_loss=28.42, generator_mel_loss=17.64, generator_kl_loss=1.292, generator_dur_loss=1.825, generator_adv_loss=1.978, generator_feat_match_loss=5.687, over 83.00 samples.], tot_loss[discriminator_loss=2.69, discriminator_real_loss=1.364, discriminator_fake_loss=1.326, generator_loss=28.76, generator_mel_loss=17.85, generator_kl_loss=1.428, generator_dur_loss=1.73, generator_adv_loss=1.977, generator_feat_match_loss=5.776, over 1972.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 08:40:07,261 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 08:40:15,061 INFO [train.py:591] (2/6) Epoch 783, validation: discriminator_loss=2.71, discriminator_real_loss=1.344, discriminator_fake_loss=1.366, generator_loss=27.44, generator_mel_loss=17.68, generator_kl_loss=1.241, generator_dur_loss=1.797, generator_adv_loss=1.822, generator_feat_match_loss=4.905, over 100.00 samples.
2024-03-15 08:40:15,062 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 08:42:36,396 INFO [train.py:527] (2/6) Epoch 783, batch 82, global_batch_idx: 97050, batch size: 66, loss[discriminator_loss=2.691, discriminator_real_loss=1.407, discriminator_fake_loss=1.284, generator_loss=29.75, generator_mel_loss=18.04, generator_kl_loss=1.535, generator_dur_loss=1.729, generator_adv_loss=1.931, generator_feat_match_loss=6.518, over 66.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.359, discriminator_fake_loss=1.325, generator_loss=28.94, generator_mel_loss=17.85, generator_kl_loss=1.427, generator_dur_loss=1.73, generator_adv_loss=1.999, generator_feat_match_loss=5.936, over 4909.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 08:44:28,181 INFO [train.py:919] (2/6) Start epoch 784
2024-03-15 08:45:12,140 INFO [train.py:527] (2/6) Epoch 784, batch 8, global_batch_idx: 97100, batch size: 88, loss[discriminator_loss=2.705, discriminator_real_loss=1.329, discriminator_fake_loss=1.376, generator_loss=28.83, generator_mel_loss=17.92, generator_kl_loss=1.436, generator_dur_loss=1.793, generator_adv_loss=1.934, generator_feat_match_loss=5.756, over 88.00 samples.], tot_loss[discriminator_loss=2.706, discriminator_real_loss=1.366, discriminator_fake_loss=1.34, generator_loss=28.64, generator_mel_loss=17.78, generator_kl_loss=1.414, generator_dur_loss=1.765, generator_adv_loss=1.981, generator_feat_match_loss=5.696, over 672.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 08:47:31,264 INFO [train.py:527] (2/6) Epoch 784, batch 58, global_batch_idx: 97150, batch size: 72, loss[discriminator_loss=2.629, discriminator_real_loss=1.285, discriminator_fake_loss=1.345, generator_loss=28.03, generator_mel_loss=17.83, generator_kl_loss=1.395, generator_dur_loss=1.758, generator_adv_loss=1.888, generator_feat_match_loss=5.162, over 72.00 samples.], tot_loss[discriminator_loss=2.688, discriminator_real_loss=1.362, discriminator_fake_loss=1.326, generator_loss=28.92, generator_mel_loss=17.86, generator_kl_loss=1.453, generator_dur_loss=1.726, generator_adv_loss=2, generator_feat_match_loss=5.879, over 3411.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 08:49:49,969 INFO [train.py:527] (2/6) Epoch 784, batch 108, global_batch_idx: 97200, batch size: 55, loss[discriminator_loss=2.618, discriminator_real_loss=1.344, discriminator_fake_loss=1.274, generator_loss=29.39, generator_mel_loss=17.93, generator_kl_loss=1.494, generator_dur_loss=1.682, generator_adv_loss=1.998, generator_feat_match_loss=6.282, over 55.00 samples.], tot_loss[discriminator_loss=2.689, discriminator_real_loss=1.36, discriminator_fake_loss=1.329, generator_loss=28.9, generator_mel_loss=17.86, generator_kl_loss=1.445, generator_dur_loss=1.729, generator_adv_loss=1.993, generator_feat_match_loss=5.867, over 6083.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 08:49:49,971 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 08:49:58,658 INFO [train.py:591] (2/6) Epoch 784, validation: discriminator_loss=2.705, discriminator_real_loss=1.417, discriminator_fake_loss=1.288, generator_loss=28.02, generator_mel_loss=18.22, generator_kl_loss=1.303, generator_dur_loss=1.803, generator_adv_loss=1.934, generator_feat_match_loss=4.753, over 100.00 samples.
2024-03-15 08:49:58,659 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 08:50:43,575 INFO [train.py:919] (2/6) Start epoch 785
2024-03-15 08:52:39,295 INFO [train.py:527] (2/6) Epoch 785, batch 34, global_batch_idx: 97250, batch size: 50, loss[discriminator_loss=2.714, discriminator_real_loss=1.44, discriminator_fake_loss=1.274, generator_loss=28.65, generator_mel_loss=17.93, generator_kl_loss=1.413, generator_dur_loss=1.73, generator_adv_loss=1.968, generator_feat_match_loss=5.602, over 50.00 samples.], tot_loss[discriminator_loss=2.681, discriminator_real_loss=1.352, discriminator_fake_loss=1.329, generator_loss=29.1, generator_mel_loss=17.95, generator_kl_loss=1.389, generator_dur_loss=1.748, generator_adv_loss=2.019, generator_feat_match_loss=5.991, over 2002.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 08:54:55,350 INFO [train.py:527] (2/6) Epoch 785, batch 84, global_batch_idx: 97300, batch size: 72, loss[discriminator_loss=2.738, discriminator_real_loss=1.393, discriminator_fake_loss=1.345, generator_loss=28.44, generator_mel_loss=17.82, generator_kl_loss=1.449, generator_dur_loss=1.78, generator_adv_loss=1.963, generator_feat_match_loss=5.429, over 72.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.352, discriminator_fake_loss=1.324, generator_loss=28.98, generator_mel_loss=17.89, generator_kl_loss=1.426, generator_dur_loss=1.733, generator_adv_loss=2.014, generator_feat_match_loss=5.926, over 4777.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 08:56:45,592 INFO [train.py:919] (2/6) Start epoch 786
2024-03-15 08:57:37,851 INFO [train.py:527] (2/6) Epoch 786, batch 10, global_batch_idx: 97350, batch size: 53, loss[discriminator_loss=2.69, discriminator_real_loss=1.368, discriminator_fake_loss=1.322, generator_loss=28.91, generator_mel_loss=17.85, generator_kl_loss=1.512, generator_dur_loss=1.727, generator_adv_loss=2.012, generator_feat_match_loss=5.809, over 53.00 samples.], tot_loss[discriminator_loss=2.706, discriminator_real_loss=1.364, discriminator_fake_loss=1.342, generator_loss=29.04, generator_mel_loss=17.95, generator_kl_loss=1.432, generator_dur_loss=1.736, generator_adv_loss=1.948, generator_feat_match_loss=5.975, over 617.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 08:59:57,232 INFO [train.py:527] (2/6) Epoch 786, batch 60, global_batch_idx: 97400, batch size: 44, loss[discriminator_loss=2.735, discriminator_real_loss=1.237, discriminator_fake_loss=1.498, generator_loss=29.16, generator_mel_loss=18.13, generator_kl_loss=1.515, generator_dur_loss=1.688, generator_adv_loss=1.913, generator_feat_match_loss=5.915, over 44.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.356, discriminator_fake_loss=1.329, generator_loss=29.04, generator_mel_loss=17.93, generator_kl_loss=1.423, generator_dur_loss=1.755, generator_adv_loss=2.002, generator_feat_match_loss=5.924, over 3587.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 08:59:57,234 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 09:00:06,019 INFO [train.py:591] (2/6) Epoch 786, validation: discriminator_loss=2.691, discriminator_real_loss=1.437, discriminator_fake_loss=1.254, generator_loss=28.03, generator_mel_loss=18.48, generator_kl_loss=1.179, generator_dur_loss=1.793, generator_adv_loss=1.998, generator_feat_match_loss=4.582, over 100.00 samples.
2024-03-15 09:00:06,020 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 09:02:26,483 INFO [train.py:527] (2/6) Epoch 786, batch 110, global_batch_idx: 97450, batch size: 56, loss[discriminator_loss=2.728, discriminator_real_loss=1.453, discriminator_fake_loss=1.275, generator_loss=28.38, generator_mel_loss=17.63, generator_kl_loss=1.479, generator_dur_loss=1.664, generator_adv_loss=1.878, generator_feat_match_loss=5.724, over 56.00 samples.], tot_loss[discriminator_loss=2.688, discriminator_real_loss=1.361, discriminator_fake_loss=1.327, generator_loss=29.01, generator_mel_loss=17.91, generator_kl_loss=1.424, generator_dur_loss=1.741, generator_adv_loss=2.001, generator_feat_match_loss=5.934, over 6214.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 09:03:04,156 INFO [train.py:919] (2/6) Start epoch 787
2024-03-15 09:05:06,841 INFO [train.py:527] (2/6) Epoch 787, batch 36, global_batch_idx: 97500, batch size: 66, loss[discriminator_loss=2.702, discriminator_real_loss=1.334, discriminator_fake_loss=1.368, generator_loss=29.35, generator_mel_loss=17.82, generator_kl_loss=1.4, generator_dur_loss=1.73, generator_adv_loss=1.962, generator_feat_match_loss=6.432, over 66.00 samples.], tot_loss[discriminator_loss=2.686, discriminator_real_loss=1.357, discriminator_fake_loss=1.329, generator_loss=28.82, generator_mel_loss=17.86, generator_kl_loss=1.412, generator_dur_loss=1.738, generator_adv_loss=2.001, generator_feat_match_loss=5.809, over 2080.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 09:07:26,630 INFO [train.py:527] (2/6) Epoch 787, batch 86, global_batch_idx: 97550, batch size: 77, loss[discriminator_loss=2.72, discriminator_real_loss=1.427, discriminator_fake_loss=1.292, generator_loss=27.94, generator_mel_loss=17.22, generator_kl_loss=1.33, generator_dur_loss=1.847, generator_adv_loss=1.99, generator_feat_match_loss=5.555, over 77.00 samples.], tot_loss[discriminator_loss=2.679, discriminator_real_loss=1.357, discriminator_fake_loss=1.322, generator_loss=28.91, generator_mel_loss=17.85, generator_kl_loss=1.405, generator_dur_loss=1.753, generator_adv_loss=2.014, generator_feat_match_loss=5.884, over 5121.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 09:09:15,549 INFO [train.py:919] (2/6) Start epoch 788
2024-03-15 09:10:14,336 INFO [train.py:527] (2/6) Epoch 788, batch 12, global_batch_idx: 97600, batch size: 88, loss[discriminator_loss=2.684, discriminator_real_loss=1.402, discriminator_fake_loss=1.282, generator_loss=28.54, generator_mel_loss=17.98, generator_kl_loss=1.355, generator_dur_loss=1.832, generator_adv_loss=1.937, generator_feat_match_loss=5.434, over 88.00 samples.], tot_loss[discriminator_loss=2.692, discriminator_real_loss=1.365, discriminator_fake_loss=1.327, generator_loss=29, generator_mel_loss=17.86, generator_kl_loss=1.5, generator_dur_loss=1.702, generator_adv_loss=1.981, generator_feat_match_loss=5.95, over 707.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 09:10:14,338 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 09:10:21,986 INFO [train.py:591] (2/6) Epoch 788, validation: discriminator_loss=2.772, discriminator_real_loss=1.407, discriminator_fake_loss=1.365, generator_loss=27.53, generator_mel_loss=17.92, generator_kl_loss=1.166, generator_dur_loss=1.81, generator_adv_loss=1.816, generator_feat_match_loss=4.82, over 100.00 samples.
2024-03-15 09:10:21,987 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 09:12:41,226 INFO [train.py:527] (2/6) Epoch 788, batch 62, global_batch_idx: 97650, batch size: 53, loss[discriminator_loss=2.693, discriminator_real_loss=1.363, discriminator_fake_loss=1.329, generator_loss=28.04, generator_mel_loss=17.78, generator_kl_loss=1.309, generator_dur_loss=1.692, generator_adv_loss=1.871, generator_feat_match_loss=5.395, over 53.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.361, discriminator_fake_loss=1.324, generator_loss=28.83, generator_mel_loss=17.86, generator_kl_loss=1.449, generator_dur_loss=1.744, generator_adv_loss=1.981, generator_feat_match_loss=5.796, over 3648.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 09:14:58,395 INFO [train.py:527] (2/6) Epoch 788, batch 112, global_batch_idx: 97700, batch size: 68, loss[discriminator_loss=2.721, discriminator_real_loss=1.29, discriminator_fake_loss=1.431, generator_loss=28.86, generator_mel_loss=17.71, generator_kl_loss=1.457, generator_dur_loss=1.774, generator_adv_loss=2.055, generator_feat_match_loss=5.868, over 68.00 samples.], tot_loss[discriminator_loss=2.687, discriminator_real_loss=1.361, discriminator_fake_loss=1.326, generator_loss=28.89, generator_mel_loss=17.87, generator_kl_loss=1.44, generator_dur_loss=1.741, generator_adv_loss=1.986, generator_feat_match_loss=5.846, over 6476.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 09:15:32,836 INFO [train.py:919] (2/6) Start epoch 789
2024-03-15 09:17:42,783 INFO [train.py:527] (2/6) Epoch 789, batch 38, global_batch_idx: 97750, batch size: 80, loss[discriminator_loss=2.691, discriminator_real_loss=1.302, discriminator_fake_loss=1.389, generator_loss=29.31, generator_mel_loss=18.25, generator_kl_loss=1.255, generator_dur_loss=1.813, generator_adv_loss=2.066, generator_feat_match_loss=5.927, over 80.00 samples.], tot_loss[discriminator_loss=2.687, discriminator_real_loss=1.366, discriminator_fake_loss=1.321, generator_loss=28.98, generator_mel_loss=17.82, generator_kl_loss=1.436, generator_dur_loss=1.719, generator_adv_loss=2.045, generator_feat_match_loss=5.954, over 2104.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 09:19:58,618 INFO [train.py:527] (2/6) Epoch 789, batch 88, global_batch_idx: 97800, batch size: 55, loss[discriminator_loss=2.59, discriminator_real_loss=1.31, discriminator_fake_loss=1.28, generator_loss=29.09, generator_mel_loss=17.71, generator_kl_loss=1.42, generator_dur_loss=1.695, generator_adv_loss=2.015, generator_feat_match_loss=6.254, over 55.00 samples.], tot_loss[discriminator_loss=2.678, discriminator_real_loss=1.36, discriminator_fake_loss=1.318, generator_loss=28.93, generator_mel_loss=17.83, generator_kl_loss=1.424, generator_dur_loss=1.73, generator_adv_loss=2.019, generator_feat_match_loss=5.927, over 4882.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 09:19:58,620 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 09:20:07,304 INFO [train.py:591] (2/6) Epoch 789, validation: discriminator_loss=2.722, discriminator_real_loss=1.317, discriminator_fake_loss=1.405, generator_loss=27.95, generator_mel_loss=18.1, generator_kl_loss=1.351, generator_dur_loss=1.794, generator_adv_loss=1.854, generator_feat_match_loss=4.859, over 100.00 samples.
2024-03-15 09:20:07,305 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 09:21:51,136 INFO [train.py:919] (2/6) Start epoch 790
2024-03-15 09:22:54,304 INFO [train.py:527] (2/6) Epoch 790, batch 14, global_batch_idx: 97850, batch size: 80, loss[discriminator_loss=2.668, discriminator_real_loss=1.356, discriminator_fake_loss=1.312, generator_loss=29.02, generator_mel_loss=17.65, generator_kl_loss=1.338, generator_dur_loss=1.772, generator_adv_loss=2.04, generator_feat_match_loss=6.223, over 80.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.353, discriminator_fake_loss=1.332, generator_loss=28.62, generator_mel_loss=17.67, generator_kl_loss=1.375, generator_dur_loss=1.762, generator_adv_loss=1.985, generator_feat_match_loss=5.826, over 978.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 09:25:11,798 INFO [train.py:527] (2/6) Epoch 790, batch 64, global_batch_idx: 97900, batch size: 55, loss[discriminator_loss=2.72, discriminator_real_loss=1.357, discriminator_fake_loss=1.364, generator_loss=29.19, generator_mel_loss=17.99, generator_kl_loss=1.57, generator_dur_loss=1.69, generator_adv_loss=1.985, generator_feat_match_loss=5.956, over 55.00 samples.], tot_loss[discriminator_loss=2.693, discriminator_real_loss=1.361, discriminator_fake_loss=1.333, generator_loss=28.77, generator_mel_loss=17.77, generator_kl_loss=1.403, generator_dur_loss=1.75, generator_adv_loss=1.983, generator_feat_match_loss=5.86, over 3871.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 09:27:31,654 INFO [train.py:527] (2/6) Epoch 790, batch 114, global_batch_idx: 97950, batch size: 31, loss[discriminator_loss=2.697, discriminator_real_loss=1.33, discriminator_fake_loss=1.368, generator_loss=27.8, generator_mel_loss=17.34, generator_kl_loss=1.585, generator_dur_loss=1.559, generator_adv_loss=1.938, generator_feat_match_loss=5.378, over 31.00 samples.], tot_loss[discriminator_loss=2.692, discriminator_real_loss=1.36, discriminator_fake_loss=1.332, generator_loss=28.83, generator_mel_loss=17.82, generator_kl_loss=1.403, generator_dur_loss=1.753, generator_adv_loss=1.989, generator_feat_match_loss=5.862, over 6782.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 09:27:57,220 INFO [train.py:919] (2/6) Start epoch 791
2024-03-15 09:30:13,481 INFO [train.py:527] (2/6) Epoch 791, batch 40, global_batch_idx: 98000, batch size: 44, loss[discriminator_loss=2.68, discriminator_real_loss=1.31, discriminator_fake_loss=1.37, generator_loss=28.33, generator_mel_loss=17.63, generator_kl_loss=1.513, generator_dur_loss=1.669, generator_adv_loss=1.984, generator_feat_match_loss=5.54, over 44.00 samples.], tot_loss[discriminator_loss=2.674, discriminator_real_loss=1.351, discriminator_fake_loss=1.323, generator_loss=29.24, generator_mel_loss=17.95, generator_kl_loss=1.474, generator_dur_loss=1.724, generator_adv_loss=2.015, generator_feat_match_loss=6.075, over 2195.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 09:30:13,483 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 09:30:21,548 INFO [train.py:591] (2/6) Epoch 791, validation: discriminator_loss=2.693, discriminator_real_loss=1.39, discriminator_fake_loss=1.304, generator_loss=27.72, generator_mel_loss=18.37, generator_kl_loss=1.228, generator_dur_loss=1.794, generator_adv_loss=1.917, generator_feat_match_loss=4.414, over 100.00 samples.
2024-03-15 09:30:21,549 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 09:32:39,911 INFO [train.py:527] (2/6) Epoch 791, batch 90, global_batch_idx: 98050, batch size: 66, loss[discriminator_loss=2.652, discriminator_real_loss=1.333, discriminator_fake_loss=1.319, generator_loss=29.54, generator_mel_loss=17.89, generator_kl_loss=1.315, generator_dur_loss=1.773, generator_adv_loss=2.009, generator_feat_match_loss=6.557, over 66.00 samples.], tot_loss[discriminator_loss=2.681, discriminator_real_loss=1.359, discriminator_fake_loss=1.322, generator_loss=29, generator_mel_loss=17.85, generator_kl_loss=1.435, generator_dur_loss=1.738, generator_adv_loss=2.005, generator_feat_match_loss=5.969, over 5295.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 09:34:13,712 INFO [train.py:919] (2/6) Start epoch 792
2024-03-15 09:35:21,538 INFO [train.py:527] (2/6) Epoch 792, batch 16, global_batch_idx: 98100, batch size: 50, loss[discriminator_loss=2.73, discriminator_real_loss=1.378, discriminator_fake_loss=1.352, generator_loss=28.69, generator_mel_loss=17.98, generator_kl_loss=1.368, generator_dur_loss=1.678, generator_adv_loss=2.017, generator_feat_match_loss=5.653, over 50.00 samples.], tot_loss[discriminator_loss=2.687, discriminator_real_loss=1.37, discriminator_fake_loss=1.316, generator_loss=28.76, generator_mel_loss=17.76, generator_kl_loss=1.447, generator_dur_loss=1.732, generator_adv_loss=2.017, generator_feat_match_loss=5.802, over 935.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 09:37:41,140 INFO [train.py:527] (2/6) Epoch 792, batch 66, global_batch_idx: 98150, batch size: 80, loss[discriminator_loss=2.662, discriminator_real_loss=1.32, discriminator_fake_loss=1.342, generator_loss=29.4, generator_mel_loss=17.91, generator_kl_loss=1.397, generator_dur_loss=1.776, generator_adv_loss=1.983, generator_feat_match_loss=6.329, over 80.00 samples.], tot_loss[discriminator_loss=2.681, discriminator_real_loss=1.36, discriminator_fake_loss=1.321, generator_loss=28.97, generator_mel_loss=17.84, generator_kl_loss=1.448, generator_dur_loss=1.73, generator_adv_loss=2.004, generator_feat_match_loss=5.943, over 3828.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 09:39:58,449 INFO [train.py:527] (2/6) Epoch 792, batch 116, global_batch_idx: 98200, batch size: 83, loss[discriminator_loss=2.731, discriminator_real_loss=1.422, discriminator_fake_loss=1.309, generator_loss=28.6, generator_mel_loss=17.59, generator_kl_loss=1.262, generator_dur_loss=1.862, generator_adv_loss=1.968, generator_feat_match_loss=5.917, over 83.00 samples.], tot_loss[discriminator_loss=2.687, discriminator_real_loss=1.359, discriminator_fake_loss=1.328, generator_loss=29, generator_mel_loss=17.87, generator_kl_loss=1.433, generator_dur_loss=1.733, generator_adv_loss=2.002, generator_feat_match_loss=5.958, over 6685.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 09:39:58,451 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 09:40:07,210 INFO [train.py:591] (2/6) Epoch 792, validation: discriminator_loss=2.773, discriminator_real_loss=1.417, discriminator_fake_loss=1.356, generator_loss=28.46, generator_mel_loss=18.35, generator_kl_loss=1.298, generator_dur_loss=1.806, generator_adv_loss=1.904, generator_feat_match_loss=5.105, over 100.00 samples.
2024-03-15 09:40:07,211 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 09:40:29,303 INFO [train.py:919] (2/6) Start epoch 793
2024-03-15 09:42:50,138 INFO [train.py:527] (2/6) Epoch 793, batch 42, global_batch_idx: 98250, batch size: 61, loss[discriminator_loss=2.67, discriminator_real_loss=1.305, discriminator_fake_loss=1.365, generator_loss=28.78, generator_mel_loss=17.67, generator_kl_loss=1.47, generator_dur_loss=1.709, generator_adv_loss=2.071, generator_feat_match_loss=5.86, over 61.00 samples.], tot_loss[discriminator_loss=2.694, discriminator_real_loss=1.36, discriminator_fake_loss=1.334, generator_loss=28.91, generator_mel_loss=17.97, generator_kl_loss=1.422, generator_dur_loss=1.742, generator_adv_loss=1.994, generator_feat_match_loss=5.78, over 2487.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 09:45:08,701 INFO [train.py:527] (2/6) Epoch 793, batch 92, global_batch_idx: 98300, batch size: 66, loss[discriminator_loss=2.713, discriminator_real_loss=1.332, discriminator_fake_loss=1.381, generator_loss=28.79, generator_mel_loss=18.15, generator_kl_loss=1.414, generator_dur_loss=1.737, generator_adv_loss=1.984, generator_feat_match_loss=5.509, over 66.00 samples.], tot_loss[discriminator_loss=2.701, discriminator_real_loss=1.362, discriminator_fake_loss=1.338, generator_loss=28.96, generator_mel_loss=17.98, generator_kl_loss=1.429, generator_dur_loss=1.732, generator_adv_loss=1.996, generator_feat_match_loss=5.823, over 4990.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 09:46:37,726 INFO [train.py:919] (2/6) Start epoch 794
2024-03-15 09:47:52,237 INFO [train.py:527] (2/6) Epoch 794, batch 18, global_batch_idx: 98350, batch size: 80, loss[discriminator_loss=2.727, discriminator_real_loss=1.374, discriminator_fake_loss=1.353, generator_loss=28.56, generator_mel_loss=18.05, generator_kl_loss=1.289, generator_dur_loss=1.814, generator_adv_loss=1.939, generator_feat_match_loss=5.469, over 80.00 samples.], tot_loss[discriminator_loss=2.7, discriminator_real_loss=1.357, discriminator_fake_loss=1.343, generator_loss=28.88, generator_mel_loss=18.07, generator_kl_loss=1.431, generator_dur_loss=1.724, generator_adv_loss=1.97, generator_feat_match_loss=5.686, over 895.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 09:50:10,963 INFO [train.py:527] (2/6) Epoch 794, batch 68, global_batch_idx: 98400, batch size: 70, loss[discriminator_loss=2.625, discriminator_real_loss=1.367, discriminator_fake_loss=1.258, generator_loss=29.39, generator_mel_loss=17.82, generator_kl_loss=1.279, generator_dur_loss=1.787, generator_adv_loss=2.206, generator_feat_match_loss=6.294, over 70.00 samples.], tot_loss[discriminator_loss=2.695, discriminator_real_loss=1.36, discriminator_fake_loss=1.335, generator_loss=28.86, generator_mel_loss=17.87, generator_kl_loss=1.401, generator_dur_loss=1.741, generator_adv_loss=2.005, generator_feat_match_loss=5.841, over 3701.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 09:50:10,965 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 09:50:19,875 INFO [train.py:591] (2/6) Epoch 794, validation: discriminator_loss=2.619, discriminator_real_loss=1.385, discriminator_fake_loss=1.234, generator_loss=28.83, generator_mel_loss=18.56, generator_kl_loss=1.309, generator_dur_loss=1.806, generator_adv_loss=2.049, generator_feat_match_loss=5.114, over 100.00 samples.
2024-03-15 09:50:19,876 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 09:52:39,490 INFO [train.py:527] (2/6) Epoch 794, batch 118, global_batch_idx: 98450, batch size: 55, loss[discriminator_loss=2.704, discriminator_real_loss=1.409, discriminator_fake_loss=1.295, generator_loss=27.91, generator_mel_loss=17.87, generator_kl_loss=1.468, generator_dur_loss=1.706, generator_adv_loss=1.992, generator_feat_match_loss=4.878, over 55.00 samples.], tot_loss[discriminator_loss=2.692, discriminator_real_loss=1.363, discriminator_fake_loss=1.329, generator_loss=28.91, generator_mel_loss=17.85, generator_kl_loss=1.414, generator_dur_loss=1.738, generator_adv_loss=2.014, generator_feat_match_loss=5.89, over 6518.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 09:52:53,350 INFO [train.py:919] (2/6) Start epoch 795
2024-03-15 09:55:22,341 INFO [train.py:527] (2/6) Epoch 795, batch 44, global_batch_idx: 98500, batch size: 14, loss[discriminator_loss=2.659, discriminator_real_loss=1.266, discriminator_fake_loss=1.392, generator_loss=29.31, generator_mel_loss=18.14, generator_kl_loss=1.746, generator_dur_loss=1.612, generator_adv_loss=1.927, generator_feat_match_loss=5.88, over 14.00 samples.], tot_loss[discriminator_loss=2.681, discriminator_real_loss=1.357, discriminator_fake_loss=1.325, generator_loss=28.95, generator_mel_loss=17.91, generator_kl_loss=1.477, generator_dur_loss=1.718, generator_adv_loss=2, generator_feat_match_loss=5.839, over 2389.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 09:57:44,666 INFO [train.py:527] (2/6) Epoch 795, batch 94, global_batch_idx: 98550, batch size: 44, loss[discriminator_loss=2.665, discriminator_real_loss=1.371, discriminator_fake_loss=1.294, generator_loss=28.06, generator_mel_loss=17.73, generator_kl_loss=1.447, generator_dur_loss=1.693, generator_adv_loss=1.914, generator_feat_match_loss=5.276, over 44.00 samples.], tot_loss[discriminator_loss=2.679, discriminator_real_loss=1.353, discriminator_fake_loss=1.326, generator_loss=28.96, generator_mel_loss=17.85, generator_kl_loss=1.437, generator_dur_loss=1.738, generator_adv_loss=2.009, generator_feat_match_loss=5.923, over 5475.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 09:59:04,457 INFO [train.py:919] (2/6) Start epoch 796
2024-03-15 10:00:25,429 INFO [train.py:527] (2/6) Epoch 796, batch 20, global_batch_idx: 98600, batch size: 50, loss[discriminator_loss=2.665, discriminator_real_loss=1.355, discriminator_fake_loss=1.31, generator_loss=29.01, generator_mel_loss=17.94, generator_kl_loss=1.444, generator_dur_loss=1.656, generator_adv_loss=2.02, generator_feat_match_loss=5.95, over 50.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.352, discriminator_fake_loss=1.331, generator_loss=28.77, generator_mel_loss=17.8, generator_kl_loss=1.408, generator_dur_loss=1.736, generator_adv_loss=1.977, generator_feat_match_loss=5.856, over 1210.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 10:00:25,430 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 10:00:33,304 INFO [train.py:591] (2/6) Epoch 796, validation: discriminator_loss=2.735, discriminator_real_loss=1.401, discriminator_fake_loss=1.334, generator_loss=28.03, generator_mel_loss=18.18, generator_kl_loss=1.285, generator_dur_loss=1.801, generator_adv_loss=1.94, generator_feat_match_loss=4.824, over 100.00 samples.
2024-03-15 10:00:33,305 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 10:02:53,545 INFO [train.py:527] (2/6) Epoch 796, batch 70, global_batch_idx: 98650, batch size: 25, loss[discriminator_loss=2.64, discriminator_real_loss=1.256, discriminator_fake_loss=1.385, generator_loss=30.58, generator_mel_loss=18.22, generator_kl_loss=1.763, generator_dur_loss=1.526, generator_adv_loss=2.266, generator_feat_match_loss=6.799, over 25.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.352, discriminator_fake_loss=1.324, generator_loss=29.05, generator_mel_loss=17.87, generator_kl_loss=1.42, generator_dur_loss=1.747, generator_adv_loss=2.014, generator_feat_match_loss=6.002, over 4036.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 10:05:10,251 INFO [train.py:527] (2/6) Epoch 796, batch 120, global_batch_idx: 98700, batch size: 70, loss[discriminator_loss=2.69, discriminator_real_loss=1.427, discriminator_fake_loss=1.262, generator_loss=28.06, generator_mel_loss=17.08, generator_kl_loss=1.447, generator_dur_loss=1.814, generator_adv_loss=2.01, generator_feat_match_loss=5.708, over 70.00 samples.], tot_loss[discriminator_loss=2.678, discriminator_real_loss=1.355, discriminator_fake_loss=1.323, generator_loss=28.98, generator_mel_loss=17.85, generator_kl_loss=1.428, generator_dur_loss=1.747, generator_adv_loss=2.001, generator_feat_match_loss=5.946, over 6804.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 10:05:18,934 INFO [train.py:919] (2/6) Start epoch 797
2024-03-15 10:07:52,339 INFO [train.py:527] (2/6) Epoch 797, batch 46, global_batch_idx: 98750, batch size: 55, loss[discriminator_loss=2.692, discriminator_real_loss=1.371, discriminator_fake_loss=1.321, generator_loss=28.64, generator_mel_loss=17.71, generator_kl_loss=1.344, generator_dur_loss=1.644, generator_adv_loss=2.015, generator_feat_match_loss=5.932, over 55.00 samples.], tot_loss[discriminator_loss=2.677, discriminator_real_loss=1.361, discriminator_fake_loss=1.315, generator_loss=28.79, generator_mel_loss=17.82, generator_kl_loss=1.428, generator_dur_loss=1.746, generator_adv_loss=1.998, generator_feat_match_loss=5.798, over 2782.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 10:10:12,914 INFO [train.py:527] (2/6) Epoch 797, batch 96, global_batch_idx: 98800, batch size: 64, loss[discriminator_loss=2.702, discriminator_real_loss=1.397, discriminator_fake_loss=1.305, generator_loss=27.83, generator_mel_loss=17.4, generator_kl_loss=1.51, generator_dur_loss=1.753, generator_adv_loss=1.925, generator_feat_match_loss=5.243, over 64.00 samples.], tot_loss[discriminator_loss=2.682, discriminator_real_loss=1.357, discriminator_fake_loss=1.325, generator_loss=28.81, generator_mel_loss=17.82, generator_kl_loss=1.426, generator_dur_loss=1.742, generator_adv_loss=1.992, generator_feat_match_loss=5.832, over 5600.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 10:10:12,915 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 10:10:21,698 INFO [train.py:591] (2/6) Epoch 797, validation: discriminator_loss=2.68, discriminator_real_loss=1.382, discriminator_fake_loss=1.298, generator_loss=26.95, generator_mel_loss=18.03, generator_kl_loss=1.322, generator_dur_loss=1.8, generator_adv_loss=1.85, generator_feat_match_loss=3.944, over 100.00 samples.
2024-03-15 10:10:21,699 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 10:11:35,731 INFO [train.py:919] (2/6) Start epoch 798
2024-03-15 10:12:59,971 INFO [train.py:527] (2/6) Epoch 798, batch 22, global_batch_idx: 98850, batch size: 50, loss[discriminator_loss=2.69, discriminator_real_loss=1.378, discriminator_fake_loss=1.312, generator_loss=28.56, generator_mel_loss=18.16, generator_kl_loss=1.381, generator_dur_loss=1.691, generator_adv_loss=1.963, generator_feat_match_loss=5.366, over 50.00 samples.], tot_loss[discriminator_loss=2.677, discriminator_real_loss=1.359, discriminator_fake_loss=1.318, generator_loss=28.7, generator_mel_loss=17.89, generator_kl_loss=1.452, generator_dur_loss=1.737, generator_adv_loss=1.998, generator_feat_match_loss=5.626, over 1365.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 10:15:18,228 INFO [train.py:527] (2/6) Epoch 798, batch 72, global_batch_idx: 98900, batch size: 95, loss[discriminator_loss=2.676, discriminator_real_loss=1.336, discriminator_fake_loss=1.339, generator_loss=28.66, generator_mel_loss=17.73, generator_kl_loss=1.45, generator_dur_loss=1.805, generator_adv_loss=2.037, generator_feat_match_loss=5.638, over 95.00 samples.], tot_loss[discriminator_loss=2.675, discriminator_real_loss=1.352, discriminator_fake_loss=1.323, generator_loss=28.89, generator_mel_loss=17.81, generator_kl_loss=1.453, generator_dur_loss=1.732, generator_adv_loss=1.997, generator_feat_match_loss=5.902, over 4186.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 10:17:35,960 INFO [train.py:527] (2/6) Epoch 798, batch 122, global_batch_idx: 98950, batch size: 25, loss[discriminator_loss=2.709, discriminator_real_loss=1.362, discriminator_fake_loss=1.347, generator_loss=29.62, generator_mel_loss=17.65, generator_kl_loss=1.718, generator_dur_loss=1.555, generator_adv_loss=1.946, generator_feat_match_loss=6.745, over 25.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.354, discriminator_fake_loss=1.322, generator_loss=28.92, generator_mel_loss=17.8, generator_kl_loss=1.447, generator_dur_loss=1.734, generator_adv_loss=2.004, generator_feat_match_loss=5.933, over 6879.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 10:17:40,585 INFO [train.py:919] (2/6) Start epoch 799
2024-03-15 10:20:18,132 INFO [train.py:527] (2/6) Epoch 799, batch 48, global_batch_idx: 99000, batch size: 47, loss[discriminator_loss=2.687, discriminator_real_loss=1.257, discriminator_fake_loss=1.429, generator_loss=29.92, generator_mel_loss=18.24, generator_kl_loss=1.484, generator_dur_loss=1.674, generator_adv_loss=2.16, generator_feat_match_loss=6.36, over 47.00 samples.], tot_loss[discriminator_loss=2.695, discriminator_real_loss=1.369, discriminator_fake_loss=1.326, generator_loss=28.83, generator_mel_loss=17.84, generator_kl_loss=1.422, generator_dur_loss=1.742, generator_adv_loss=1.995, generator_feat_match_loss=5.833, over 2779.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 10:20:18,133 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 10:20:26,126 INFO [train.py:591] (2/6) Epoch 799, validation: discriminator_loss=2.793, discriminator_real_loss=1.59, discriminator_fake_loss=1.203, generator_loss=28.54, generator_mel_loss=18.53, generator_kl_loss=1.235, generator_dur_loss=1.793, generator_adv_loss=2.161, generator_feat_match_loss=4.818, over 100.00 samples.
2024-03-15 10:20:26,127 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 10:22:44,005 INFO [train.py:527] (2/6) Epoch 799, batch 98, global_batch_idx: 99050, batch size: 70, loss[discriminator_loss=2.744, discriminator_real_loss=1.312, discriminator_fake_loss=1.432, generator_loss=28.05, generator_mel_loss=17.31, generator_kl_loss=1.305, generator_dur_loss=1.808, generator_adv_loss=1.986, generator_feat_match_loss=5.638, over 70.00 samples.], tot_loss[discriminator_loss=2.69, discriminator_real_loss=1.366, discriminator_fake_loss=1.324, generator_loss=28.88, generator_mel_loss=17.83, generator_kl_loss=1.437, generator_dur_loss=1.734, generator_adv_loss=1.997, generator_feat_match_loss=5.881, over 5439.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 10:23:55,282 INFO [train.py:919] (2/6) Start epoch 800
2024-03-15 10:25:24,151 INFO [train.py:527] (2/6) Epoch 800, batch 24, global_batch_idx: 99100, batch size: 56, loss[discriminator_loss=2.7, discriminator_real_loss=1.407, discriminator_fake_loss=1.293, generator_loss=28.92, generator_mel_loss=17.96, generator_kl_loss=1.479, generator_dur_loss=1.693, generator_adv_loss=1.953, generator_feat_match_loss=5.839, over 56.00 samples.], tot_loss[discriminator_loss=2.688, discriminator_real_loss=1.348, discriminator_fake_loss=1.339, generator_loss=28.79, generator_mel_loss=17.81, generator_kl_loss=1.424, generator_dur_loss=1.734, generator_adv_loss=1.976, generator_feat_match_loss=5.843, over 1351.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 10:27:42,610 INFO [train.py:527] (2/6) Epoch 800, batch 74, global_batch_idx: 99150, batch size: 44, loss[discriminator_loss=2.675, discriminator_real_loss=1.333, discriminator_fake_loss=1.342, generator_loss=30.35, generator_mel_loss=18.01, generator_kl_loss=1.632, generator_dur_loss=1.681, generator_adv_loss=2.104, generator_feat_match_loss=6.926, over 44.00 samples.], tot_loss[discriminator_loss=2.681, discriminator_real_loss=1.351, discriminator_fake_loss=1.33, generator_loss=28.88, generator_mel_loss=17.85, generator_kl_loss=1.402, generator_dur_loss=1.744, generator_adv_loss=1.997, generator_feat_match_loss=5.891, over 4217.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 10:30:01,648 INFO [train.py:919] (2/6) Start epoch 801
2024-03-15 10:30:25,660 INFO [train.py:527] (2/6) Epoch 801, batch 0, global_batch_idx: 99200, batch size: 48, loss[discriminator_loss=2.689, discriminator_real_loss=1.344, discriminator_fake_loss=1.345, generator_loss=28.06, generator_mel_loss=17.65, generator_kl_loss=1.459, generator_dur_loss=1.714, generator_adv_loss=2.046, generator_feat_match_loss=5.191, over 48.00 samples.], tot_loss[discriminator_loss=2.689, discriminator_real_loss=1.344, discriminator_fake_loss=1.345, generator_loss=28.06, generator_mel_loss=17.65, generator_kl_loss=1.459, generator_dur_loss=1.714, generator_adv_loss=2.046, generator_feat_match_loss=5.191, over 48.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 10:30:25,663 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 10:30:33,648 INFO [train.py:591] (2/6) Epoch 801, validation: discriminator_loss=2.725, discriminator_real_loss=1.353, discriminator_fake_loss=1.371, generator_loss=27.21, generator_mel_loss=17.97, generator_kl_loss=1.262, generator_dur_loss=1.796, generator_adv_loss=1.878, generator_feat_match_loss=4.304, over 100.00 samples.
2024-03-15 10:30:33,650 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 10:32:53,919 INFO [train.py:527] (2/6) Epoch 801, batch 50, global_batch_idx: 99250, batch size: 62, loss[discriminator_loss=2.67, discriminator_real_loss=1.409, discriminator_fake_loss=1.26, generator_loss=28.77, generator_mel_loss=17.62, generator_kl_loss=1.358, generator_dur_loss=1.714, generator_adv_loss=2.012, generator_feat_match_loss=6.068, over 62.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.362, discriminator_fake_loss=1.323, generator_loss=28.84, generator_mel_loss=17.75, generator_kl_loss=1.419, generator_dur_loss=1.741, generator_adv_loss=1.994, generator_feat_match_loss=5.941, over 2975.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 10:35:13,725 INFO [train.py:527] (2/6) Epoch 801, batch 100, global_batch_idx: 99300, batch size: 77, loss[discriminator_loss=2.695, discriminator_real_loss=1.35, discriminator_fake_loss=1.345, generator_loss=28.1, generator_mel_loss=17.36, generator_kl_loss=1.459, generator_dur_loss=1.798, generator_adv_loss=2.046, generator_feat_match_loss=5.442, over 77.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.362, discriminator_fake_loss=1.323, generator_loss=28.99, generator_mel_loss=17.79, generator_kl_loss=1.435, generator_dur_loss=1.741, generator_adv_loss=2.024, generator_feat_match_loss=5.991, over 5776.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 10:36:20,106 INFO [train.py:919] (2/6) Start epoch 802
2024-03-15 10:37:54,651 INFO [train.py:527] (2/6) Epoch 802, batch 26, global_batch_idx: 99350, batch size: 25, loss[discriminator_loss=2.633, discriminator_real_loss=1.28, discriminator_fake_loss=1.353, generator_loss=29.56, generator_mel_loss=17.97, generator_kl_loss=1.85, generator_dur_loss=1.558, generator_adv_loss=2.183, generator_feat_match_loss=6.002, over 25.00 samples.], tot_loss[discriminator_loss=2.682, discriminator_real_loss=1.352, discriminator_fake_loss=1.33, generator_loss=28.84, generator_mel_loss=17.86, generator_kl_loss=1.4, generator_dur_loss=1.754, generator_adv_loss=1.992, generator_feat_match_loss=5.84, over 1545.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 10:40:14,278 INFO [train.py:527] (2/6) Epoch 802, batch 76, global_batch_idx: 99400, batch size: 88, loss[discriminator_loss=2.681, discriminator_real_loss=1.356, discriminator_fake_loss=1.324, generator_loss=27.83, generator_mel_loss=17.55, generator_kl_loss=1.43, generator_dur_loss=1.827, generator_adv_loss=1.848, generator_feat_match_loss=5.169, over 88.00 samples.], tot_loss[discriminator_loss=2.681, discriminator_real_loss=1.355, discriminator_fake_loss=1.326, generator_loss=28.92, generator_mel_loss=17.86, generator_kl_loss=1.427, generator_dur_loss=1.754, generator_adv_loss=1.989, generator_feat_match_loss=5.888, over 4309.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 10:40:14,279 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 10:40:23,119 INFO [train.py:591] (2/6) Epoch 802, validation: discriminator_loss=2.677, discriminator_real_loss=1.347, discriminator_fake_loss=1.33, generator_loss=27.8, generator_mel_loss=18.01, generator_kl_loss=1.349, generator_dur_loss=1.825, generator_adv_loss=1.83, generator_feat_match_loss=4.787, over 100.00 samples.
2024-03-15 10:40:23,120 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 10:42:36,581 INFO [train.py:919] (2/6) Start epoch 803
2024-03-15 10:43:07,056 INFO [train.py:527] (2/6) Epoch 803, batch 2, global_batch_idx: 99450, batch size: 62, loss[discriminator_loss=2.697, discriminator_real_loss=1.365, discriminator_fake_loss=1.332, generator_loss=29.16, generator_mel_loss=18.16, generator_kl_loss=1.482, generator_dur_loss=1.766, generator_adv_loss=1.91, generator_feat_match_loss=5.847, over 62.00 samples.], tot_loss[discriminator_loss=2.7, discriminator_real_loss=1.369, discriminator_fake_loss=1.331, generator_loss=28.8, generator_mel_loss=17.8, generator_kl_loss=1.443, generator_dur_loss=1.769, generator_adv_loss=1.975, generator_feat_match_loss=5.809, over 167.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 10:45:25,731 INFO [train.py:527] (2/6) Epoch 803, batch 52, global_batch_idx: 99500, batch size: 66, loss[discriminator_loss=2.707, discriminator_real_loss=1.404, discriminator_fake_loss=1.303, generator_loss=29.17, generator_mel_loss=17.72, generator_kl_loss=1.406, generator_dur_loss=1.76, generator_adv_loss=2.025, generator_feat_match_loss=6.261, over 66.00 samples.], tot_loss[discriminator_loss=2.68, discriminator_real_loss=1.36, discriminator_fake_loss=1.32, generator_loss=28.88, generator_mel_loss=17.82, generator_kl_loss=1.409, generator_dur_loss=1.752, generator_adv_loss=2.012, generator_feat_match_loss=5.886, over 3061.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 10:47:46,025 INFO [train.py:527] (2/6) Epoch 803, batch 102, global_batch_idx: 99550, batch size: 64, loss[discriminator_loss=2.671, discriminator_real_loss=1.386, discriminator_fake_loss=1.285, generator_loss=28.99, generator_mel_loss=17.74, generator_kl_loss=1.278, generator_dur_loss=1.767, generator_adv_loss=1.953, generator_feat_match_loss=6.25, over 64.00 samples.], tot_loss[discriminator_loss=2.683, discriminator_real_loss=1.357, discriminator_fake_loss=1.326, generator_loss=28.94, generator_mel_loss=17.84, generator_kl_loss=1.408, generator_dur_loss=1.749, generator_adv_loss=2.009, generator_feat_match_loss=5.927, over 6014.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 10:48:45,457 INFO [train.py:919] (2/6) Start epoch 804
2024-03-15 10:50:28,489 INFO [train.py:527] (2/6) Epoch 804, batch 28, global_batch_idx: 99600, batch size: 61, loss[discriminator_loss=2.729, discriminator_real_loss=1.436, discriminator_fake_loss=1.293, generator_loss=26.76, generator_mel_loss=17.09, generator_kl_loss=1.374, generator_dur_loss=1.718, generator_adv_loss=1.895, generator_feat_match_loss=4.675, over 61.00 samples.], tot_loss[discriminator_loss=2.674, discriminator_real_loss=1.356, discriminator_fake_loss=1.318, generator_loss=28.59, generator_mel_loss=17.69, generator_kl_loss=1.346, generator_dur_loss=1.783, generator_adv_loss=2.004, generator_feat_match_loss=5.761, over 1908.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 10:50:28,491 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 10:50:36,564 INFO [train.py:591] (2/6) Epoch 804, validation: discriminator_loss=2.731, discriminator_real_loss=1.378, discriminator_fake_loss=1.353, generator_loss=27.59, generator_mel_loss=17.92, generator_kl_loss=1.318, generator_dur_loss=1.816, generator_adv_loss=1.884, generator_feat_match_loss=4.657, over 100.00 samples.
2024-03-15 10:50:36,565 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 10:52:54,894 INFO [train.py:527] (2/6) Epoch 804, batch 78, global_batch_idx: 99650, batch size: 83, loss[discriminator_loss=2.695, discriminator_real_loss=1.442, discriminator_fake_loss=1.253, generator_loss=28.39, generator_mel_loss=17.55, generator_kl_loss=1.35, generator_dur_loss=1.799, generator_adv_loss=1.94, generator_feat_match_loss=5.754, over 83.00 samples.], tot_loss[discriminator_loss=2.686, discriminator_real_loss=1.358, discriminator_fake_loss=1.328, generator_loss=28.79, generator_mel_loss=17.8, generator_kl_loss=1.382, generator_dur_loss=1.766, generator_adv_loss=1.995, generator_feat_match_loss=5.85, over 4780.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 10:54:58,507 INFO [train.py:919] (2/6) Start epoch 805
2024-03-15 10:55:33,834 INFO [train.py:527] (2/6) Epoch 805, batch 4, global_batch_idx: 99700, batch size: 74, loss[discriminator_loss=2.757, discriminator_real_loss=1.418, discriminator_fake_loss=1.339, generator_loss=28.29, generator_mel_loss=17.56, generator_kl_loss=1.484, generator_dur_loss=1.813, generator_adv_loss=2.01, generator_feat_match_loss=5.416, over 74.00 samples.], tot_loss[discriminator_loss=2.749, discriminator_real_loss=1.394, discriminator_fake_loss=1.355, generator_loss=28.37, generator_mel_loss=17.63, generator_kl_loss=1.463, generator_dur_loss=1.775, generator_adv_loss=1.958, generator_feat_match_loss=5.536, over 313.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 10:57:51,562 INFO [train.py:527] (2/6) Epoch 805, batch 54, global_batch_idx: 99750, batch size: 62, loss[discriminator_loss=2.679, discriminator_real_loss=1.445, discriminator_fake_loss=1.234, generator_loss=28.42, generator_mel_loss=17.44, generator_kl_loss=1.301, generator_dur_loss=1.744, generator_adv_loss=2.008, generator_feat_match_loss=5.924, over 62.00 samples.], tot_loss[discriminator_loss=2.677, discriminator_real_loss=1.359, discriminator_fake_loss=1.318, generator_loss=28.93, generator_mel_loss=17.82, generator_kl_loss=1.426, generator_dur_loss=1.73, generator_adv_loss=2.037, generator_feat_match_loss=5.918, over 3017.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 11:00:12,918 INFO [train.py:527] (2/6) Epoch 805, batch 104, global_batch_idx: 99800, batch size: 52, loss[discriminator_loss=2.673, discriminator_real_loss=1.411, discriminator_fake_loss=1.263, generator_loss=29.01, generator_mel_loss=18.29, generator_kl_loss=1.329, generator_dur_loss=1.739, generator_adv_loss=1.831, generator_feat_match_loss=5.822, over 52.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.36, discriminator_fake_loss=1.324, generator_loss=28.94, generator_mel_loss=17.85, generator_kl_loss=1.426, generator_dur_loss=1.737, generator_adv_loss=2.017, generator_feat_match_loss=5.915, over 5916.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 11:00:12,920 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 11:00:21,941 INFO [train.py:591] (2/6) Epoch 805, validation: discriminator_loss=2.746, discriminator_real_loss=1.292, discriminator_fake_loss=1.454, generator_loss=27.25, generator_mel_loss=17.79, generator_kl_loss=1.295, generator_dur_loss=1.805, generator_adv_loss=1.74, generator_feat_match_loss=4.622, over 100.00 samples.
2024-03-15 11:00:21,942 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 11:01:14,583 INFO [train.py:919] (2/6) Start epoch 806
2024-03-15 11:03:00,290 INFO [train.py:527] (2/6) Epoch 806, batch 30, global_batch_idx: 99850, batch size: 36, loss[discriminator_loss=2.761, discriminator_real_loss=1.377, discriminator_fake_loss=1.384, generator_loss=29.54, generator_mel_loss=17.97, generator_kl_loss=1.493, generator_dur_loss=1.661, generator_adv_loss=2.033, generator_feat_match_loss=6.381, over 36.00 samples.], tot_loss[discriminator_loss=2.663, discriminator_real_loss=1.334, discriminator_fake_loss=1.329, generator_loss=29.09, generator_mel_loss=17.93, generator_kl_loss=1.435, generator_dur_loss=1.738, generator_adv_loss=1.991, generator_feat_match_loss=5.999, over 1732.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 11:05:18,944 INFO [train.py:527] (2/6) Epoch 806, batch 80, global_batch_idx: 99900, batch size: 96, loss[discriminator_loss=2.689, discriminator_real_loss=1.518, discriminator_fake_loss=1.171, generator_loss=28.17, generator_mel_loss=17.47, generator_kl_loss=1.362, generator_dur_loss=1.844, generator_adv_loss=1.85, generator_feat_match_loss=5.64, over 96.00 samples.], tot_loss[discriminator_loss=2.669, discriminator_real_loss=1.351, discriminator_fake_loss=1.318, generator_loss=29, generator_mel_loss=17.86, generator_kl_loss=1.429, generator_dur_loss=1.746, generator_adv_loss=1.995, generator_feat_match_loss=5.972, over 4619.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 11:07:20,347 INFO [train.py:919] (2/6) Start epoch 807
2024-03-15 11:08:01,229 INFO [train.py:527] (2/6) Epoch 807, batch 6, global_batch_idx: 99950, batch size: 45, loss[discriminator_loss=2.663, discriminator_real_loss=1.286, discriminator_fake_loss=1.377, generator_loss=30.03, generator_mel_loss=18.27, generator_kl_loss=1.604, generator_dur_loss=1.652, generator_adv_loss=1.971, generator_feat_match_loss=6.536, over 45.00 samples.], tot_loss[discriminator_loss=2.68, discriminator_real_loss=1.357, discriminator_fake_loss=1.323, generator_loss=28.88, generator_mel_loss=17.85, generator_kl_loss=1.451, generator_dur_loss=1.71, generator_adv_loss=2.023, generator_feat_match_loss=5.849, over 402.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 11:10:20,954 INFO [train.py:527] (2/6) Epoch 807, batch 56, global_batch_idx: 100000, batch size: 83, loss[discriminator_loss=2.688, discriminator_real_loss=1.376, discriminator_fake_loss=1.312, generator_loss=27.84, generator_mel_loss=17.46, generator_kl_loss=1.326, generator_dur_loss=1.858, generator_adv_loss=1.978, generator_feat_match_loss=5.216, over 83.00 samples.], tot_loss[discriminator_loss=2.69, discriminator_real_loss=1.362, discriminator_fake_loss=1.328, generator_loss=28.83, generator_mel_loss=17.82, generator_kl_loss=1.416, generator_dur_loss=1.745, generator_adv_loss=1.991, generator_feat_match_loss=5.856, over 3506.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 11:10:20,956 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 11:10:28,931 INFO [train.py:591] (2/6) Epoch 807, validation: discriminator_loss=2.774, discriminator_real_loss=1.429, discriminator_fake_loss=1.345, generator_loss=26.98, generator_mel_loss=18.01, generator_kl_loss=1.191, generator_dur_loss=1.766, generator_adv_loss=1.844, generator_feat_match_loss=4.171, over 100.00 samples.
2024-03-15 11:10:28,932 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 11:12:46,934 INFO [train.py:527] (2/6) Epoch 807, batch 106, global_batch_idx: 100050, batch size: 83, loss[discriminator_loss=2.816, discriminator_real_loss=1.536, discriminator_fake_loss=1.28, generator_loss=29.45, generator_mel_loss=17.92, generator_kl_loss=1.447, generator_dur_loss=1.802, generator_adv_loss=1.847, generator_feat_match_loss=6.426, over 83.00 samples.], tot_loss[discriminator_loss=2.688, discriminator_real_loss=1.361, discriminator_fake_loss=1.327, generator_loss=28.91, generator_mel_loss=17.83, generator_kl_loss=1.426, generator_dur_loss=1.743, generator_adv_loss=1.992, generator_feat_match_loss=5.915, over 6399.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 11:13:36,277 INFO [train.py:919] (2/6) Start epoch 808
2024-03-15 11:15:28,542 INFO [train.py:527] (2/6) Epoch 808, batch 32, global_batch_idx: 100100, batch size: 80, loss[discriminator_loss=2.671, discriminator_real_loss=1.359, discriminator_fake_loss=1.312, generator_loss=28.91, generator_mel_loss=17.84, generator_kl_loss=1.391, generator_dur_loss=1.807, generator_adv_loss=2.148, generator_feat_match_loss=5.72, over 80.00 samples.], tot_loss[discriminator_loss=2.691, discriminator_real_loss=1.368, discriminator_fake_loss=1.323, generator_loss=29.01, generator_mel_loss=17.91, generator_kl_loss=1.455, generator_dur_loss=1.735, generator_adv_loss=2, generator_feat_match_loss=5.91, over 1853.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 11:17:49,527 INFO [train.py:527] (2/6) Epoch 808, batch 82, global_batch_idx: 100150, batch size: 83, loss[discriminator_loss=2.621, discriminator_real_loss=1.374, discriminator_fake_loss=1.247, generator_loss=29.85, generator_mel_loss=17.83, generator_kl_loss=1.486, generator_dur_loss=1.817, generator_adv_loss=2.079, generator_feat_match_loss=6.644, over 83.00 samples.], tot_loss[discriminator_loss=2.697, discriminator_real_loss=1.365, discriminator_fake_loss=1.331, generator_loss=28.87, generator_mel_loss=17.86, generator_kl_loss=1.436, generator_dur_loss=1.735, generator_adv_loss=1.989, generator_feat_match_loss=5.851, over 4716.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 11:19:47,039 INFO [train.py:919] (2/6) Start epoch 809
2024-03-15 11:20:33,776 INFO [train.py:527] (2/6) Epoch 809, batch 8, global_batch_idx: 100200, batch size: 58, loss[discriminator_loss=2.689, discriminator_real_loss=1.371, discriminator_fake_loss=1.318, generator_loss=28.86, generator_mel_loss=17.61, generator_kl_loss=1.472, generator_dur_loss=1.731, generator_adv_loss=2.128, generator_feat_match_loss=5.92, over 58.00 samples.], tot_loss[discriminator_loss=2.675, discriminator_real_loss=1.337, discriminator_fake_loss=1.337, generator_loss=28.74, generator_mel_loss=17.8, generator_kl_loss=1.399, generator_dur_loss=1.748, generator_adv_loss=2.004, generator_feat_match_loss=5.787, over 556.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 11:20:33,779 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 11:20:41,723 INFO [train.py:591] (2/6) Epoch 809, validation: discriminator_loss=2.69, discriminator_real_loss=1.45, discriminator_fake_loss=1.241, generator_loss=27.66, generator_mel_loss=18.09, generator_kl_loss=1.268, generator_dur_loss=1.804, generator_adv_loss=2.02, generator_feat_match_loss=4.477, over 100.00 samples.
2024-03-15 11:20:41,725 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 11:23:00,005 INFO [train.py:527] (2/6) Epoch 809, batch 58, global_batch_idx: 100250, batch size: 64, loss[discriminator_loss=2.638, discriminator_real_loss=1.29, discriminator_fake_loss=1.348, generator_loss=30.21, generator_mel_loss=18.42, generator_kl_loss=1.529, generator_dur_loss=1.734, generator_adv_loss=1.96, generator_feat_match_loss=6.569, over 64.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.354, discriminator_fake_loss=1.322, generator_loss=28.9, generator_mel_loss=17.81, generator_kl_loss=1.406, generator_dur_loss=1.762, generator_adv_loss=2.003, generator_feat_match_loss=5.918, over 3653.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 11:25:18,715 INFO [train.py:527] (2/6) Epoch 809, batch 108, global_batch_idx: 100300, batch size: 15, loss[discriminator_loss=2.547, discriminator_real_loss=1.194, discriminator_fake_loss=1.353, generator_loss=31.1, generator_mel_loss=17.97, generator_kl_loss=1.883, generator_dur_loss=1.535, generator_adv_loss=2.105, generator_feat_match_loss=7.607, over 15.00 samples.], tot_loss[discriminator_loss=2.679, discriminator_real_loss=1.355, discriminator_fake_loss=1.324, generator_loss=28.94, generator_mel_loss=17.84, generator_kl_loss=1.407, generator_dur_loss=1.753, generator_adv_loss=2.002, generator_feat_match_loss=5.939, over 6571.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 11:26:00,661 INFO [train.py:919] (2/6) Start epoch 810
2024-03-15 11:27:58,519 INFO [train.py:527] (2/6) Epoch 810, batch 34, global_batch_idx: 100350, batch size: 95, loss[discriminator_loss=2.722, discriminator_real_loss=1.401, discriminator_fake_loss=1.321, generator_loss=28.81, generator_mel_loss=17.65, generator_kl_loss=1.302, generator_dur_loss=1.83, generator_adv_loss=1.865, generator_feat_match_loss=6.162, over 95.00 samples.], tot_loss[discriminator_loss=2.694, discriminator_real_loss=1.373, discriminator_fake_loss=1.321, generator_loss=28.64, generator_mel_loss=17.76, generator_kl_loss=1.396, generator_dur_loss=1.75, generator_adv_loss=1.986, generator_feat_match_loss=5.747, over 2040.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 11:30:15,709 INFO [train.py:527] (2/6) Epoch 810, batch 84, global_batch_idx: 100400, batch size: 25, loss[discriminator_loss=2.726, discriminator_real_loss=1.467, discriminator_fake_loss=1.259, generator_loss=28.52, generator_mel_loss=18.24, generator_kl_loss=1.671, generator_dur_loss=1.534, generator_adv_loss=2.039, generator_feat_match_loss=5.034, over 25.00 samples.], tot_loss[discriminator_loss=2.683, discriminator_real_loss=1.366, discriminator_fake_loss=1.317, generator_loss=28.69, generator_mel_loss=17.75, generator_kl_loss=1.406, generator_dur_loss=1.745, generator_adv_loss=1.993, generator_feat_match_loss=5.796, over 4674.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 11:30:15,711 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 11:30:24,305 INFO [train.py:591] (2/6) Epoch 810, validation: discriminator_loss=2.77, discriminator_real_loss=1.386, discriminator_fake_loss=1.384, generator_loss=27.57, generator_mel_loss=18.1, generator_kl_loss=1.194, generator_dur_loss=1.808, generator_adv_loss=1.82, generator_feat_match_loss=4.648, over 100.00 samples.
2024-03-15 11:30:24,306 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 11:32:15,805 INFO [train.py:919] (2/6) Start epoch 811
2024-03-15 11:33:08,707 INFO [train.py:527] (2/6) Epoch 811, batch 10, global_batch_idx: 100450, batch size: 48, loss[discriminator_loss=2.702, discriminator_real_loss=1.384, discriminator_fake_loss=1.318, generator_loss=28.1, generator_mel_loss=17.33, generator_kl_loss=1.675, generator_dur_loss=1.669, generator_adv_loss=1.947, generator_feat_match_loss=5.484, over 48.00 samples.], tot_loss[discriminator_loss=2.678, discriminator_real_loss=1.373, discriminator_fake_loss=1.305, generator_loss=28.92, generator_mel_loss=17.72, generator_kl_loss=1.505, generator_dur_loss=1.722, generator_adv_loss=2.042, generator_feat_match_loss=5.926, over 541.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 11:35:26,312 INFO [train.py:527] (2/6) Epoch 811, batch 60, global_batch_idx: 100500, batch size: 15, loss[discriminator_loss=2.656, discriminator_real_loss=1.283, discriminator_fake_loss=1.374, generator_loss=27.5, generator_mel_loss=17.62, generator_kl_loss=1.51, generator_dur_loss=1.627, generator_adv_loss=1.931, generator_feat_match_loss=4.812, over 15.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.356, discriminator_fake_loss=1.32, generator_loss=29.01, generator_mel_loss=17.82, generator_kl_loss=1.451, generator_dur_loss=1.736, generator_adv_loss=1.999, generator_feat_match_loss=5.998, over 3321.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 11:37:43,276 INFO [train.py:527] (2/6) Epoch 811, batch 110, global_batch_idx: 100550, batch size: 95, loss[discriminator_loss=2.638, discriminator_real_loss=1.3, discriminator_fake_loss=1.338, generator_loss=29.32, generator_mel_loss=18.07, generator_kl_loss=1.215, generator_dur_loss=1.855, generator_adv_loss=1.889, generator_feat_match_loss=6.291, over 95.00 samples.], tot_loss[discriminator_loss=2.673, discriminator_real_loss=1.355, discriminator_fake_loss=1.317, generator_loss=28.98, generator_mel_loss=17.81, generator_kl_loss=1.435, generator_dur_loss=1.737, generator_adv_loss=2, generator_feat_match_loss=5.998, over 6188.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 11:38:20,760 INFO [train.py:919] (2/6) Start epoch 812
2024-03-15 11:40:25,071 INFO [train.py:527] (2/6) Epoch 812, batch 36, global_batch_idx: 100600, batch size: 50, loss[discriminator_loss=2.729, discriminator_real_loss=1.402, discriminator_fake_loss=1.328, generator_loss=27.83, generator_mel_loss=17.77, generator_kl_loss=1.362, generator_dur_loss=1.706, generator_adv_loss=1.992, generator_feat_match_loss=4.992, over 50.00 samples.], tot_loss[discriminator_loss=2.694, discriminator_real_loss=1.361, discriminator_fake_loss=1.333, generator_loss=28.96, generator_mel_loss=17.89, generator_kl_loss=1.448, generator_dur_loss=1.729, generator_adv_loss=1.988, generator_feat_match_loss=5.905, over 1934.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 11:40:25,073 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 11:40:33,078 INFO [train.py:591] (2/6) Epoch 812, validation: discriminator_loss=2.719, discriminator_real_loss=1.419, discriminator_fake_loss=1.3, generator_loss=28.17, generator_mel_loss=18.41, generator_kl_loss=1.234, generator_dur_loss=1.801, generator_adv_loss=1.905, generator_feat_match_loss=4.82, over 100.00 samples.
2024-03-15 11:40:33,080 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 11:42:53,704 INFO [train.py:527] (2/6) Epoch 812, batch 86, global_batch_idx: 100650, batch size: 70, loss[discriminator_loss=2.735, discriminator_real_loss=1.453, discriminator_fake_loss=1.282, generator_loss=29.1, generator_mel_loss=17.82, generator_kl_loss=1.494, generator_dur_loss=1.765, generator_adv_loss=1.964, generator_feat_match_loss=6.054, over 70.00 samples.], tot_loss[discriminator_loss=2.679, discriminator_real_loss=1.355, discriminator_fake_loss=1.324, generator_loss=29.06, generator_mel_loss=17.87, generator_kl_loss=1.439, generator_dur_loss=1.739, generator_adv_loss=2.007, generator_feat_match_loss=5.998, over 4840.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 11:44:33,082 INFO [train.py:919] (2/6) Start epoch 813
2024-03-15 11:45:30,623 INFO [train.py:527] (2/6) Epoch 813, batch 12, global_batch_idx: 100700, batch size: 31, loss[discriminator_loss=2.694, discriminator_real_loss=1.445, discriminator_fake_loss=1.249, generator_loss=29.28, generator_mel_loss=18.19, generator_kl_loss=1.551, generator_dur_loss=1.65, generator_adv_loss=2.041, generator_feat_match_loss=5.846, over 31.00 samples.], tot_loss[discriminator_loss=2.68, discriminator_real_loss=1.356, discriminator_fake_loss=1.323, generator_loss=29.26, generator_mel_loss=17.98, generator_kl_loss=1.501, generator_dur_loss=1.703, generator_adv_loss=2.034, generator_feat_match_loss=6.038, over 592.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 11:47:51,313 INFO [train.py:527] (2/6) Epoch 813, batch 62, global_batch_idx: 100750, batch size: 56, loss[discriminator_loss=2.673, discriminator_real_loss=1.416, discriminator_fake_loss=1.257, generator_loss=30.31, generator_mel_loss=18.28, generator_kl_loss=1.483, generator_dur_loss=1.688, generator_adv_loss=2.01, generator_feat_match_loss=6.848, over 56.00 samples.], tot_loss[discriminator_loss=2.691, discriminator_real_loss=1.368, discriminator_fake_loss=1.323, generator_loss=29.02, generator_mel_loss=17.88, generator_kl_loss=1.474, generator_dur_loss=1.725, generator_adv_loss=2.013, generator_feat_match_loss=5.923, over 3358.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 11:50:11,240 INFO [train.py:527] (2/6) Epoch 813, batch 112, global_batch_idx: 100800, batch size: 52, loss[discriminator_loss=2.697, discriminator_real_loss=1.399, discriminator_fake_loss=1.298, generator_loss=28.72, generator_mel_loss=17.68, generator_kl_loss=1.547, generator_dur_loss=1.657, generator_adv_loss=2.072, generator_feat_match_loss=5.761, over 52.00 samples.], tot_loss[discriminator_loss=2.683, discriminator_real_loss=1.357, discriminator_fake_loss=1.325, generator_loss=28.99, generator_mel_loss=17.83, generator_kl_loss=1.464, generator_dur_loss=1.733, generator_adv_loss=2.005, generator_feat_match_loss=5.961, over 6077.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 11:50:11,242 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 11:50:19,987 INFO [train.py:591] (2/6) Epoch 813, validation: discriminator_loss=2.742, discriminator_real_loss=1.424, discriminator_fake_loss=1.318, generator_loss=28.59, generator_mel_loss=18.42, generator_kl_loss=1.395, generator_dur_loss=1.819, generator_adv_loss=2.009, generator_feat_match_loss=4.94, over 100.00 samples.
2024-03-15 11:50:19,988 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 11:50:51,387 INFO [train.py:919] (2/6) Start epoch 814
2024-03-15 11:52:57,917 INFO [train.py:527] (2/6) Epoch 814, batch 38, global_batch_idx: 100850, batch size: 77, loss[discriminator_loss=2.632, discriminator_real_loss=1.31, discriminator_fake_loss=1.323, generator_loss=28.09, generator_mel_loss=17.6, generator_kl_loss=1.229, generator_dur_loss=1.772, generator_adv_loss=2.069, generator_feat_match_loss=5.417, over 77.00 samples.], tot_loss[discriminator_loss=2.693, discriminator_real_loss=1.365, discriminator_fake_loss=1.328, generator_loss=28.9, generator_mel_loss=17.86, generator_kl_loss=1.42, generator_dur_loss=1.724, generator_adv_loss=1.989, generator_feat_match_loss=5.899, over 2137.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 11:55:16,898 INFO [train.py:527] (2/6) Epoch 814, batch 88, global_batch_idx: 100900, batch size: 25, loss[discriminator_loss=2.644, discriminator_real_loss=1.303, discriminator_fake_loss=1.342, generator_loss=31.63, generator_mel_loss=19.26, generator_kl_loss=1.792, generator_dur_loss=1.575, generator_adv_loss=2.204, generator_feat_match_loss=6.801, over 25.00 samples.], tot_loss[discriminator_loss=2.689, discriminator_real_loss=1.358, discriminator_fake_loss=1.33, generator_loss=29.01, generator_mel_loss=17.9, generator_kl_loss=1.443, generator_dur_loss=1.716, generator_adv_loss=2.005, generator_feat_match_loss=5.939, over 4642.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 11:56:58,310 INFO [train.py:919] (2/6) Start epoch 815
2024-03-15 11:58:01,579 INFO [train.py:527] (2/6) Epoch 815, batch 14, global_batch_idx: 100950, batch size: 25, loss[discriminator_loss=2.751, discriminator_real_loss=1.375, discriminator_fake_loss=1.376, generator_loss=30.27, generator_mel_loss=18.95, generator_kl_loss=1.635, generator_dur_loss=1.56, generator_adv_loss=1.88, generator_feat_match_loss=6.239, over 25.00 samples.], tot_loss[discriminator_loss=2.717, discriminator_real_loss=1.387, discriminator_fake_loss=1.33, generator_loss=28.9, generator_mel_loss=17.88, generator_kl_loss=1.501, generator_dur_loss=1.725, generator_adv_loss=1.972, generator_feat_match_loss=5.826, over 764.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 12:00:24,008 INFO [train.py:527] (2/6) Epoch 815, batch 64, global_batch_idx: 101000, batch size: 66, loss[discriminator_loss=2.735, discriminator_real_loss=1.413, discriminator_fake_loss=1.322, generator_loss=28.34, generator_mel_loss=17.36, generator_kl_loss=1.414, generator_dur_loss=1.731, generator_adv_loss=1.916, generator_feat_match_loss=5.921, over 66.00 samples.], tot_loss[discriminator_loss=2.692, discriminator_real_loss=1.364, discriminator_fake_loss=1.328, generator_loss=28.93, generator_mel_loss=17.84, generator_kl_loss=1.436, generator_dur_loss=1.742, generator_adv_loss=2, generator_feat_match_loss=5.913, over 3579.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 12:00:24,010 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 12:00:32,153 INFO [train.py:591] (2/6) Epoch 815, validation: discriminator_loss=2.77, discriminator_real_loss=1.414, discriminator_fake_loss=1.356, generator_loss=27.53, generator_mel_loss=18, generator_kl_loss=1.165, generator_dur_loss=1.81, generator_adv_loss=1.9, generator_feat_match_loss=4.658, over 100.00 samples.
2024-03-15 12:00:32,154 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 12:02:51,584 INFO [train.py:527] (2/6) Epoch 815, batch 114, global_batch_idx: 101050, batch size: 62, loss[discriminator_loss=2.587, discriminator_real_loss=1.378, discriminator_fake_loss=1.208, generator_loss=29.49, generator_mel_loss=17.71, generator_kl_loss=1.451, generator_dur_loss=1.75, generator_adv_loss=2.067, generator_feat_match_loss=6.515, over 62.00 samples.], tot_loss[discriminator_loss=2.686, discriminator_real_loss=1.358, discriminator_fake_loss=1.328, generator_loss=28.89, generator_mel_loss=17.83, generator_kl_loss=1.437, generator_dur_loss=1.738, generator_adv_loss=1.992, generator_feat_match_loss=5.895, over 6456.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 12:03:20,033 INFO [train.py:919] (2/6) Start epoch 816
2024-03-15 12:05:40,873 INFO [train.py:527] (2/6) Epoch 816, batch 40, global_batch_idx: 101100, batch size: 88, loss[discriminator_loss=2.654, discriminator_real_loss=1.315, discriminator_fake_loss=1.339, generator_loss=29.4, generator_mel_loss=18.07, generator_kl_loss=1.396, generator_dur_loss=1.851, generator_adv_loss=1.948, generator_feat_match_loss=6.14, over 88.00 samples.], tot_loss[discriminator_loss=2.7, discriminator_real_loss=1.364, discriminator_fake_loss=1.337, generator_loss=28.84, generator_mel_loss=17.75, generator_kl_loss=1.432, generator_dur_loss=1.754, generator_adv_loss=1.987, generator_feat_match_loss=5.914, over 2402.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 12:07:55,595 INFO [train.py:527] (2/6) Epoch 816, batch 90, global_batch_idx: 101150, batch size: 62, loss[discriminator_loss=2.713, discriminator_real_loss=1.283, discriminator_fake_loss=1.43, generator_loss=29.74, generator_mel_loss=18.13, generator_kl_loss=1.513, generator_dur_loss=1.734, generator_adv_loss=1.996, generator_feat_match_loss=6.375, over 62.00 samples.], tot_loss[discriminator_loss=2.686, discriminator_real_loss=1.359, discriminator_fake_loss=1.327, generator_loss=28.95, generator_mel_loss=17.81, generator_kl_loss=1.44, generator_dur_loss=1.739, generator_adv_loss=2, generator_feat_match_loss=5.968, over 5077.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 12:09:27,750 INFO [train.py:919] (2/6) Start epoch 817
2024-03-15 12:10:35,951 INFO [train.py:527] (2/6) Epoch 817, batch 16, global_batch_idx: 101200, batch size: 77, loss[discriminator_loss=2.737, discriminator_real_loss=1.328, discriminator_fake_loss=1.409, generator_loss=28.55, generator_mel_loss=17.36, generator_kl_loss=1.455, generator_dur_loss=1.776, generator_adv_loss=2.181, generator_feat_match_loss=5.773, over 77.00 samples.], tot_loss[discriminator_loss=2.705, discriminator_real_loss=1.369, discriminator_fake_loss=1.337, generator_loss=28.93, generator_mel_loss=17.78, generator_kl_loss=1.396, generator_dur_loss=1.773, generator_adv_loss=2.009, generator_feat_match_loss=5.971, over 1066.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 12:10:35,952 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 12:10:44,064 INFO [train.py:591] (2/6) Epoch 817, validation: discriminator_loss=2.779, discriminator_real_loss=1.585, discriminator_fake_loss=1.194, generator_loss=27.21, generator_mel_loss=17.83, generator_kl_loss=1.27, generator_dur_loss=1.815, generator_adv_loss=2.099, generator_feat_match_loss=4.199, over 100.00 samples.
2024-03-15 12:10:44,065 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 12:13:03,855 INFO [train.py:527] (2/6) Epoch 817, batch 66, global_batch_idx: 101250, batch size: 83, loss[discriminator_loss=2.684, discriminator_real_loss=1.425, discriminator_fake_loss=1.259, generator_loss=28.99, generator_mel_loss=18.11, generator_kl_loss=1.275, generator_dur_loss=1.804, generator_adv_loss=1.797, generator_feat_match_loss=6.006, over 83.00 samples.], tot_loss[discriminator_loss=2.69, discriminator_real_loss=1.365, discriminator_fake_loss=1.325, generator_loss=28.94, generator_mel_loss=17.84, generator_kl_loss=1.415, generator_dur_loss=1.755, generator_adv_loss=1.997, generator_feat_match_loss=5.928, over 3855.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 12:15:22,546 INFO [train.py:527] (2/6) Epoch 817, batch 116, global_batch_idx: 101300, batch size: 55, loss[discriminator_loss=2.574, discriminator_real_loss=1.319, discriminator_fake_loss=1.256, generator_loss=29.58, generator_mel_loss=17.92, generator_kl_loss=1.31, generator_dur_loss=1.685, generator_adv_loss=2.144, generator_feat_match_loss=6.513, over 55.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.357, discriminator_fake_loss=1.327, generator_loss=28.98, generator_mel_loss=17.85, generator_kl_loss=1.416, generator_dur_loss=1.746, generator_adv_loss=2.003, generator_feat_match_loss=5.965, over 6672.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 12:15:43,995 INFO [train.py:919] (2/6) Start epoch 818
2024-03-15 12:18:05,867 INFO [train.py:527] (2/6) Epoch 818, batch 42, global_batch_idx: 101350, batch size: 42, loss[discriminator_loss=2.643, discriminator_real_loss=1.333, discriminator_fake_loss=1.31, generator_loss=28.46, generator_mel_loss=17.86, generator_kl_loss=1.334, generator_dur_loss=1.682, generator_adv_loss=2.267, generator_feat_match_loss=5.319, over 42.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.355, discriminator_fake_loss=1.33, generator_loss=29.1, generator_mel_loss=17.86, generator_kl_loss=1.418, generator_dur_loss=1.728, generator_adv_loss=2.018, generator_feat_match_loss=6.077, over 2362.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 12:20:26,265 INFO [train.py:527] (2/6) Epoch 818, batch 92, global_batch_idx: 101400, batch size: 88, loss[discriminator_loss=2.677, discriminator_real_loss=1.337, discriminator_fake_loss=1.34, generator_loss=29.23, generator_mel_loss=17.59, generator_kl_loss=1.381, generator_dur_loss=1.849, generator_adv_loss=1.974, generator_feat_match_loss=6.436, over 88.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.355, discriminator_fake_loss=1.328, generator_loss=28.92, generator_mel_loss=17.8, generator_kl_loss=1.401, generator_dur_loss=1.741, generator_adv_loss=2.003, generator_feat_match_loss=5.976, over 5291.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 12:20:26,266 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 12:20:34,993 INFO [train.py:591] (2/6) Epoch 818, validation: discriminator_loss=2.716, discriminator_real_loss=1.288, discriminator_fake_loss=1.428, generator_loss=27.67, generator_mel_loss=18.01, generator_kl_loss=1.323, generator_dur_loss=1.802, generator_adv_loss=1.839, generator_feat_match_loss=4.698, over 100.00 samples.
2024-03-15 12:20:34,994 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 12:22:01,485 INFO [train.py:919] (2/6) Start epoch 819
2024-03-15 12:23:14,845 INFO [train.py:527] (2/6) Epoch 819, batch 18, global_batch_idx: 101450, batch size: 55, loss[discriminator_loss=2.677, discriminator_real_loss=1.415, discriminator_fake_loss=1.262, generator_loss=29.01, generator_mel_loss=17.86, generator_kl_loss=1.327, generator_dur_loss=1.718, generator_adv_loss=1.983, generator_feat_match_loss=6.125, over 55.00 samples.], tot_loss[discriminator_loss=2.68, discriminator_real_loss=1.362, discriminator_fake_loss=1.318, generator_loss=28.98, generator_mel_loss=17.79, generator_kl_loss=1.423, generator_dur_loss=1.733, generator_adv_loss=2.01, generator_feat_match_loss=6.023, over 1015.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 12:25:33,145 INFO [train.py:527] (2/6) Epoch 819, batch 68, global_batch_idx: 101500, batch size: 64, loss[discriminator_loss=2.689, discriminator_real_loss=1.33, discriminator_fake_loss=1.359, generator_loss=28.39, generator_mel_loss=17.48, generator_kl_loss=1.419, generator_dur_loss=1.743, generator_adv_loss=1.997, generator_feat_match_loss=5.747, over 64.00 samples.], tot_loss[discriminator_loss=2.68, discriminator_real_loss=1.359, discriminator_fake_loss=1.321, generator_loss=28.93, generator_mel_loss=17.79, generator_kl_loss=1.441, generator_dur_loss=1.735, generator_adv_loss=2.008, generator_feat_match_loss=5.949, over 3854.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 12:27:51,579 INFO [train.py:527] (2/6) Epoch 819, batch 118, global_batch_idx: 101550, batch size: 47, loss[discriminator_loss=2.705, discriminator_real_loss=1.355, discriminator_fake_loss=1.35, generator_loss=29.11, generator_mel_loss=17.93, generator_kl_loss=1.421, generator_dur_loss=1.725, generator_adv_loss=2.063, generator_feat_match_loss=5.962, over 47.00 samples.], tot_loss[discriminator_loss=2.678, discriminator_real_loss=1.357, discriminator_fake_loss=1.321, generator_loss=28.89, generator_mel_loss=17.79, generator_kl_loss=1.431, generator_dur_loss=1.739, generator_adv_loss=2, generator_feat_match_loss=5.935, over 6790.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 12:28:08,915 INFO [train.py:919] (2/6) Start epoch 820
2024-03-15 12:30:35,351 INFO [train.py:527] (2/6) Epoch 820, batch 44, global_batch_idx: 101600, batch size: 55, loss[discriminator_loss=2.675, discriminator_real_loss=1.338, discriminator_fake_loss=1.337, generator_loss=29.69, generator_mel_loss=18.19, generator_kl_loss=1.53, generator_dur_loss=1.681, generator_adv_loss=2.079, generator_feat_match_loss=6.201, over 55.00 samples.], tot_loss[discriminator_loss=2.677, discriminator_real_loss=1.359, discriminator_fake_loss=1.318, generator_loss=29.12, generator_mel_loss=17.88, generator_kl_loss=1.426, generator_dur_loss=1.752, generator_adv_loss=2.018, generator_feat_match_loss=6.042, over 2614.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 12:30:35,352 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 12:30:43,547 INFO [train.py:591] (2/6) Epoch 820, validation: discriminator_loss=2.753, discriminator_real_loss=1.358, discriminator_fake_loss=1.395, generator_loss=28.18, generator_mel_loss=18.39, generator_kl_loss=1.237, generator_dur_loss=1.813, generator_adv_loss=1.896, generator_feat_match_loss=4.836, over 100.00 samples.
2024-03-15 12:30:43,548 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 12:33:03,588 INFO [train.py:527] (2/6) Epoch 820, batch 94, global_batch_idx: 101650, batch size: 48, loss[discriminator_loss=2.726, discriminator_real_loss=1.431, discriminator_fake_loss=1.295, generator_loss=28.24, generator_mel_loss=17.59, generator_kl_loss=1.454, generator_dur_loss=1.698, generator_adv_loss=1.931, generator_feat_match_loss=5.559, over 48.00 samples.], tot_loss[discriminator_loss=2.675, discriminator_real_loss=1.359, discriminator_fake_loss=1.317, generator_loss=29.09, generator_mel_loss=17.88, generator_kl_loss=1.435, generator_dur_loss=1.753, generator_adv_loss=2.015, generator_feat_match_loss=6, over 5468.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 12:34:23,793 INFO [train.py:919] (2/6) Start epoch 821
2024-03-15 12:35:45,135 INFO [train.py:527] (2/6) Epoch 821, batch 20, global_batch_idx: 101700, batch size: 25, loss[discriminator_loss=2.615, discriminator_real_loss=1.161, discriminator_fake_loss=1.454, generator_loss=30.97, generator_mel_loss=18.29, generator_kl_loss=1.706, generator_dur_loss=1.54, generator_adv_loss=2.052, generator_feat_match_loss=7.385, over 25.00 samples.], tot_loss[discriminator_loss=2.677, discriminator_real_loss=1.339, discriminator_fake_loss=1.339, generator_loss=28.93, generator_mel_loss=17.82, generator_kl_loss=1.456, generator_dur_loss=1.76, generator_adv_loss=1.982, generator_feat_match_loss=5.915, over 1183.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 12:38:06,254 INFO [train.py:527] (2/6) Epoch 821, batch 70, global_batch_idx: 101750, batch size: 48, loss[discriminator_loss=2.748, discriminator_real_loss=1.395, discriminator_fake_loss=1.353, generator_loss=28.16, generator_mel_loss=17.8, generator_kl_loss=1.58, generator_dur_loss=1.685, generator_adv_loss=1.819, generator_feat_match_loss=5.275, over 48.00 samples.], tot_loss[discriminator_loss=2.69, discriminator_real_loss=1.358, discriminator_fake_loss=1.332, generator_loss=29, generator_mel_loss=17.88, generator_kl_loss=1.425, generator_dur_loss=1.761, generator_adv_loss=1.992, generator_feat_match_loss=5.937, over 4173.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 12:40:20,008 INFO [train.py:527] (2/6) Epoch 821, batch 120, global_batch_idx: 101800, batch size: 31, loss[discriminator_loss=2.7, discriminator_real_loss=1.398, discriminator_fake_loss=1.302, generator_loss=28.26, generator_mel_loss=17.65, generator_kl_loss=1.675, generator_dur_loss=1.595, generator_adv_loss=2.039, generator_feat_match_loss=5.306, over 31.00 samples.], tot_loss[discriminator_loss=2.691, discriminator_real_loss=1.356, discriminator_fake_loss=1.334, generator_loss=29.03, generator_mel_loss=17.87, generator_kl_loss=1.417, generator_dur_loss=1.76, generator_adv_loss=1.995, generator_feat_match_loss=5.981, over 7182.00 samples.], cur_lr_g: 1.81e-04, cur_lr_d: 1.81e-04, 
2024-03-15 12:40:20,009 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 12:40:28,989 INFO [train.py:591] (2/6) Epoch 821, validation: discriminator_loss=2.727, discriminator_real_loss=1.443, discriminator_fake_loss=1.284, generator_loss=28.11, generator_mel_loss=18.16, generator_kl_loss=1.341, generator_dur_loss=1.825, generator_adv_loss=1.962, generator_feat_match_loss=4.823, over 100.00 samples.
2024-03-15 12:40:28,990 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 12:40:38,225 INFO [train.py:919] (2/6) Start epoch 822
2024-03-15 12:43:10,197 INFO [train.py:527] (2/6) Epoch 822, batch 46, global_batch_idx: 101850, batch size: 44, loss[discriminator_loss=2.601, discriminator_real_loss=1.3, discriminator_fake_loss=1.301, generator_loss=29.35, generator_mel_loss=18.36, generator_kl_loss=1.516, generator_dur_loss=1.717, generator_adv_loss=1.968, generator_feat_match_loss=5.792, over 44.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.36, discriminator_fake_loss=1.326, generator_loss=28.87, generator_mel_loss=17.84, generator_kl_loss=1.39, generator_dur_loss=1.763, generator_adv_loss=1.991, generator_feat_match_loss=5.886, over 2836.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 12:45:28,316 INFO [train.py:527] (2/6) Epoch 822, batch 96, global_batch_idx: 101900, batch size: 52, loss[discriminator_loss=2.712, discriminator_real_loss=1.303, discriminator_fake_loss=1.41, generator_loss=28.45, generator_mel_loss=17.66, generator_kl_loss=1.399, generator_dur_loss=1.696, generator_adv_loss=1.908, generator_feat_match_loss=5.79, over 52.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.356, discriminator_fake_loss=1.328, generator_loss=28.96, generator_mel_loss=17.83, generator_kl_loss=1.406, generator_dur_loss=1.757, generator_adv_loss=2.002, generator_feat_match_loss=5.964, over 5613.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 12:46:44,410 INFO [train.py:919] (2/6) Start epoch 823
2024-03-15 12:48:11,356 INFO [train.py:527] (2/6) Epoch 823, batch 22, global_batch_idx: 101950, batch size: 39, loss[discriminator_loss=2.722, discriminator_real_loss=1.357, discriminator_fake_loss=1.365, generator_loss=29.14, generator_mel_loss=18.21, generator_kl_loss=1.538, generator_dur_loss=1.745, generator_adv_loss=1.954, generator_feat_match_loss=5.693, over 39.00 samples.], tot_loss[discriminator_loss=2.692, discriminator_real_loss=1.355, discriminator_fake_loss=1.336, generator_loss=29.08, generator_mel_loss=17.87, generator_kl_loss=1.461, generator_dur_loss=1.745, generator_adv_loss=1.991, generator_feat_match_loss=6.018, over 1275.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 12:50:31,075 INFO [train.py:527] (2/6) Epoch 823, batch 72, global_batch_idx: 102000, batch size: 16, loss[discriminator_loss=2.72, discriminator_real_loss=1.259, discriminator_fake_loss=1.461, generator_loss=30.22, generator_mel_loss=17.67, generator_kl_loss=1.771, generator_dur_loss=1.529, generator_adv_loss=2.003, generator_feat_match_loss=7.247, over 16.00 samples.], tot_loss[discriminator_loss=2.686, discriminator_real_loss=1.359, discriminator_fake_loss=1.327, generator_loss=28.83, generator_mel_loss=17.78, generator_kl_loss=1.414, generator_dur_loss=1.747, generator_adv_loss=2.003, generator_feat_match_loss=5.88, over 4181.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 12:50:31,076 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 12:50:39,871 INFO [train.py:591] (2/6) Epoch 823, validation: discriminator_loss=2.758, discriminator_real_loss=1.426, discriminator_fake_loss=1.331, generator_loss=27.91, generator_mel_loss=18.15, generator_kl_loss=1.312, generator_dur_loss=1.814, generator_adv_loss=1.929, generator_feat_match_loss=4.703, over 100.00 samples.
2024-03-15 12:50:39,872 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 12:52:57,032 INFO [train.py:527] (2/6) Epoch 823, batch 122, global_batch_idx: 102050, batch size: 16, loss[discriminator_loss=2.74, discriminator_real_loss=1.45, discriminator_fake_loss=1.29, generator_loss=28.24, generator_mel_loss=17.83, generator_kl_loss=1.564, generator_dur_loss=1.519, generator_adv_loss=2.02, generator_feat_match_loss=5.309, over 16.00 samples.], tot_loss[discriminator_loss=2.68, discriminator_real_loss=1.355, discriminator_fake_loss=1.325, generator_loss=28.92, generator_mel_loss=17.8, generator_kl_loss=1.432, generator_dur_loss=1.742, generator_adv_loss=2.005, generator_feat_match_loss=5.941, over 6892.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 12:53:02,120 INFO [train.py:919] (2/6) Start epoch 824
2024-03-15 12:55:40,395 INFO [train.py:527] (2/6) Epoch 824, batch 48, global_batch_idx: 102100, batch size: 80, loss[discriminator_loss=2.669, discriminator_real_loss=1.353, discriminator_fake_loss=1.316, generator_loss=29.46, generator_mel_loss=17.84, generator_kl_loss=1.399, generator_dur_loss=1.817, generator_adv_loss=1.865, generator_feat_match_loss=6.533, over 80.00 samples.], tot_loss[discriminator_loss=2.686, discriminator_real_loss=1.354, discriminator_fake_loss=1.332, generator_loss=28.97, generator_mel_loss=17.81, generator_kl_loss=1.412, generator_dur_loss=1.742, generator_adv_loss=1.991, generator_feat_match_loss=6.013, over 2796.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 12:57:58,894 INFO [train.py:527] (2/6) Epoch 824, batch 98, global_batch_idx: 102150, batch size: 53, loss[discriminator_loss=2.65, discriminator_real_loss=1.25, discriminator_fake_loss=1.4, generator_loss=30.06, generator_mel_loss=18.34, generator_kl_loss=1.66, generator_dur_loss=1.704, generator_adv_loss=2.128, generator_feat_match_loss=6.225, over 53.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.352, discriminator_fake_loss=1.324, generator_loss=28.98, generator_mel_loss=17.8, generator_kl_loss=1.429, generator_dur_loss=1.738, generator_adv_loss=2.006, generator_feat_match_loss=6.008, over 5694.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 12:59:05,447 INFO [train.py:919] (2/6) Start epoch 825
2024-03-15 13:00:36,450 INFO [train.py:527] (2/6) Epoch 825, batch 24, global_batch_idx: 102200, batch size: 61, loss[discriminator_loss=2.695, discriminator_real_loss=1.4, discriminator_fake_loss=1.296, generator_loss=28.92, generator_mel_loss=17.75, generator_kl_loss=1.444, generator_dur_loss=1.748, generator_adv_loss=1.869, generator_feat_match_loss=6.111, over 61.00 samples.], tot_loss[discriminator_loss=2.674, discriminator_real_loss=1.354, discriminator_fake_loss=1.321, generator_loss=29.1, generator_mel_loss=17.84, generator_kl_loss=1.448, generator_dur_loss=1.726, generator_adv_loss=1.988, generator_feat_match_loss=6.1, over 1327.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 13:00:36,452 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 13:00:44,503 INFO [train.py:591] (2/6) Epoch 825, validation: discriminator_loss=2.737, discriminator_real_loss=1.38, discriminator_fake_loss=1.358, generator_loss=28.58, generator_mel_loss=18.35, generator_kl_loss=1.403, generator_dur_loss=1.801, generator_adv_loss=1.848, generator_feat_match_loss=5.17, over 100.00 samples.
2024-03-15 13:00:44,504 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 13:03:03,007 INFO [train.py:527] (2/6) Epoch 825, batch 74, global_batch_idx: 102250, batch size: 53, loss[discriminator_loss=2.706, discriminator_real_loss=1.425, discriminator_fake_loss=1.281, generator_loss=28.57, generator_mel_loss=18.08, generator_kl_loss=1.441, generator_dur_loss=1.682, generator_adv_loss=1.888, generator_feat_match_loss=5.473, over 53.00 samples.], tot_loss[discriminator_loss=2.68, discriminator_real_loss=1.354, discriminator_fake_loss=1.326, generator_loss=29.05, generator_mel_loss=17.83, generator_kl_loss=1.435, generator_dur_loss=1.736, generator_adv_loss=2.001, generator_feat_match_loss=6.05, over 4186.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 13:05:20,305 INFO [train.py:919] (2/6) Start epoch 826
2024-03-15 13:05:44,603 INFO [train.py:527] (2/6) Epoch 826, batch 0, global_batch_idx: 102300, batch size: 56, loss[discriminator_loss=2.692, discriminator_real_loss=1.374, discriminator_fake_loss=1.317, generator_loss=28.74, generator_mel_loss=17.89, generator_kl_loss=1.326, generator_dur_loss=1.69, generator_adv_loss=1.865, generator_feat_match_loss=5.961, over 56.00 samples.], tot_loss[discriminator_loss=2.692, discriminator_real_loss=1.374, discriminator_fake_loss=1.317, generator_loss=28.74, generator_mel_loss=17.89, generator_kl_loss=1.326, generator_dur_loss=1.69, generator_adv_loss=1.865, generator_feat_match_loss=5.961, over 56.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 13:08:00,697 INFO [train.py:527] (2/6) Epoch 826, batch 50, global_batch_idx: 102350, batch size: 48, loss[discriminator_loss=2.695, discriminator_real_loss=1.308, discriminator_fake_loss=1.387, generator_loss=28.82, generator_mel_loss=17.43, generator_kl_loss=1.602, generator_dur_loss=1.668, generator_adv_loss=2.122, generator_feat_match_loss=6.006, over 48.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.356, discriminator_fake_loss=1.329, generator_loss=28.76, generator_mel_loss=17.75, generator_kl_loss=1.448, generator_dur_loss=1.751, generator_adv_loss=1.986, generator_feat_match_loss=5.825, over 3004.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 13:10:20,750 INFO [train.py:527] (2/6) Epoch 826, batch 100, global_batch_idx: 102400, batch size: 50, loss[discriminator_loss=2.84, discriminator_real_loss=1.335, discriminator_fake_loss=1.505, generator_loss=29.31, generator_mel_loss=17.92, generator_kl_loss=1.507, generator_dur_loss=1.7, generator_adv_loss=1.881, generator_feat_match_loss=6.3, over 50.00 samples.], tot_loss[discriminator_loss=2.689, discriminator_real_loss=1.359, discriminator_fake_loss=1.329, generator_loss=28.88, generator_mel_loss=17.78, generator_kl_loss=1.449, generator_dur_loss=1.744, generator_adv_loss=2, generator_feat_match_loss=5.905, over 5766.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 13:10:20,752 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 13:10:29,554 INFO [train.py:591] (2/6) Epoch 826, validation: discriminator_loss=2.782, discriminator_real_loss=1.428, discriminator_fake_loss=1.355, generator_loss=27.5, generator_mel_loss=18.04, generator_kl_loss=1.325, generator_dur_loss=1.814, generator_adv_loss=1.874, generator_feat_match_loss=4.452, over 100.00 samples.
2024-03-15 13:10:29,555 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 13:11:33,752 INFO [train.py:919] (2/6) Start epoch 827
2024-03-15 13:13:08,414 INFO [train.py:527] (2/6) Epoch 827, batch 26, global_batch_idx: 102450, batch size: 39, loss[discriminator_loss=2.72, discriminator_real_loss=1.418, discriminator_fake_loss=1.302, generator_loss=29.24, generator_mel_loss=18.04, generator_kl_loss=1.468, generator_dur_loss=1.726, generator_adv_loss=1.985, generator_feat_match_loss=6.018, over 39.00 samples.], tot_loss[discriminator_loss=2.689, discriminator_real_loss=1.376, discriminator_fake_loss=1.313, generator_loss=28.83, generator_mel_loss=17.77, generator_kl_loss=1.418, generator_dur_loss=1.736, generator_adv_loss=2.014, generator_feat_match_loss=5.896, over 1535.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 13:15:26,066 INFO [train.py:527] (2/6) Epoch 827, batch 76, global_batch_idx: 102500, batch size: 58, loss[discriminator_loss=2.67, discriminator_real_loss=1.326, discriminator_fake_loss=1.344, generator_loss=29.46, generator_mel_loss=18.04, generator_kl_loss=1.352, generator_dur_loss=1.721, generator_adv_loss=2.078, generator_feat_match_loss=6.262, over 58.00 samples.], tot_loss[discriminator_loss=2.675, discriminator_real_loss=1.354, discriminator_fake_loss=1.321, generator_loss=28.91, generator_mel_loss=17.79, generator_kl_loss=1.414, generator_dur_loss=1.748, generator_adv_loss=2.003, generator_feat_match_loss=5.96, over 4521.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 13:17:40,962 INFO [train.py:919] (2/6) Start epoch 828
2024-03-15 13:18:09,400 INFO [train.py:527] (2/6) Epoch 828, batch 2, global_batch_idx: 102550, batch size: 62, loss[discriminator_loss=2.691, discriminator_real_loss=1.317, discriminator_fake_loss=1.375, generator_loss=29.36, generator_mel_loss=17.9, generator_kl_loss=1.446, generator_dur_loss=1.787, generator_adv_loss=2.05, generator_feat_match_loss=6.182, over 62.00 samples.], tot_loss[discriminator_loss=2.667, discriminator_real_loss=1.327, discriminator_fake_loss=1.341, generator_loss=28.98, generator_mel_loss=17.73, generator_kl_loss=1.344, generator_dur_loss=1.78, generator_adv_loss=1.999, generator_feat_match_loss=6.124, over 211.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 13:20:27,727 INFO [train.py:527] (2/6) Epoch 828, batch 52, global_batch_idx: 102600, batch size: 72, loss[discriminator_loss=2.693, discriminator_real_loss=1.475, discriminator_fake_loss=1.218, generator_loss=28.81, generator_mel_loss=17.53, generator_kl_loss=1.331, generator_dur_loss=1.782, generator_adv_loss=1.887, generator_feat_match_loss=6.277, over 72.00 samples.], tot_loss[discriminator_loss=2.68, discriminator_real_loss=1.357, discriminator_fake_loss=1.323, generator_loss=29.01, generator_mel_loss=17.85, generator_kl_loss=1.425, generator_dur_loss=1.743, generator_adv_loss=2.007, generator_feat_match_loss=5.984, over 2915.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 13:20:27,729 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 13:20:35,763 INFO [train.py:591] (2/6) Epoch 828, validation: discriminator_loss=2.727, discriminator_real_loss=1.372, discriminator_fake_loss=1.355, generator_loss=27.59, generator_mel_loss=17.59, generator_kl_loss=1.329, generator_dur_loss=1.814, generator_adv_loss=1.834, generator_feat_match_loss=5.023, over 100.00 samples.
2024-03-15 13:20:35,764 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 13:22:54,497 INFO [train.py:527] (2/6) Epoch 828, batch 102, global_batch_idx: 102650, batch size: 45, loss[discriminator_loss=2.689, discriminator_real_loss=1.367, discriminator_fake_loss=1.321, generator_loss=28.1, generator_mel_loss=17.51, generator_kl_loss=1.516, generator_dur_loss=1.671, generator_adv_loss=1.935, generator_feat_match_loss=5.468, over 45.00 samples.], tot_loss[discriminator_loss=2.68, discriminator_real_loss=1.359, discriminator_fake_loss=1.321, generator_loss=28.94, generator_mel_loss=17.8, generator_kl_loss=1.409, generator_dur_loss=1.752, generator_adv_loss=2, generator_feat_match_loss=5.977, over 6042.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 13:23:55,262 INFO [train.py:919] (2/6) Start epoch 829
2024-03-15 13:25:38,715 INFO [train.py:527] (2/6) Epoch 829, batch 28, global_batch_idx: 102700, batch size: 52, loss[discriminator_loss=2.679, discriminator_real_loss=1.327, discriminator_fake_loss=1.352, generator_loss=28.08, generator_mel_loss=17.59, generator_kl_loss=1.437, generator_dur_loss=1.681, generator_adv_loss=2.076, generator_feat_match_loss=5.3, over 52.00 samples.], tot_loss[discriminator_loss=2.678, discriminator_real_loss=1.359, discriminator_fake_loss=1.319, generator_loss=28.76, generator_mel_loss=17.69, generator_kl_loss=1.451, generator_dur_loss=1.743, generator_adv_loss=1.993, generator_feat_match_loss=5.886, over 1668.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 13:27:57,160 INFO [train.py:527] (2/6) Epoch 829, batch 78, global_batch_idx: 102750, batch size: 39, loss[discriminator_loss=2.701, discriminator_real_loss=1.385, discriminator_fake_loss=1.316, generator_loss=27.61, generator_mel_loss=17.35, generator_kl_loss=1.615, generator_dur_loss=1.636, generator_adv_loss=1.975, generator_feat_match_loss=5.039, over 39.00 samples.], tot_loss[discriminator_loss=2.674, discriminator_real_loss=1.356, discriminator_fake_loss=1.318, generator_loss=28.93, generator_mel_loss=17.77, generator_kl_loss=1.464, generator_dur_loss=1.731, generator_adv_loss=2, generator_feat_match_loss=5.962, over 4384.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 13:30:03,518 INFO [train.py:919] (2/6) Start epoch 830
2024-03-15 13:30:37,858 INFO [train.py:527] (2/6) Epoch 830, batch 4, global_batch_idx: 102800, batch size: 53, loss[discriminator_loss=2.777, discriminator_real_loss=1.444, discriminator_fake_loss=1.332, generator_loss=28.35, generator_mel_loss=17.65, generator_kl_loss=1.508, generator_dur_loss=1.673, generator_adv_loss=1.937, generator_feat_match_loss=5.586, over 53.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.351, discriminator_fake_loss=1.333, generator_loss=29.04, generator_mel_loss=17.78, generator_kl_loss=1.468, generator_dur_loss=1.691, generator_adv_loss=2.163, generator_feat_match_loss=5.945, over 246.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 13:30:37,862 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 13:30:45,667 INFO [train.py:591] (2/6) Epoch 830, validation: discriminator_loss=2.748, discriminator_real_loss=1.426, discriminator_fake_loss=1.322, generator_loss=27.94, generator_mel_loss=17.7, generator_kl_loss=1.346, generator_dur_loss=1.804, generator_adv_loss=2.109, generator_feat_match_loss=4.984, over 100.00 samples.
2024-03-15 13:30:45,669 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 13:33:07,754 INFO [train.py:527] (2/6) Epoch 830, batch 54, global_batch_idx: 102850, batch size: 96, loss[discriminator_loss=2.66, discriminator_real_loss=1.318, discriminator_fake_loss=1.341, generator_loss=28.43, generator_mel_loss=17.69, generator_kl_loss=1.258, generator_dur_loss=1.875, generator_adv_loss=2.02, generator_feat_match_loss=5.587, over 96.00 samples.], tot_loss[discriminator_loss=2.692, discriminator_real_loss=1.374, discriminator_fake_loss=1.318, generator_loss=28.69, generator_mel_loss=17.7, generator_kl_loss=1.43, generator_dur_loss=1.732, generator_adv_loss=2.02, generator_feat_match_loss=5.815, over 3132.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 13:35:25,286 INFO [train.py:527] (2/6) Epoch 830, batch 104, global_batch_idx: 102900, batch size: 31, loss[discriminator_loss=2.623, discriminator_real_loss=1.389, discriminator_fake_loss=1.234, generator_loss=28.89, generator_mel_loss=17.54, generator_kl_loss=1.603, generator_dur_loss=1.625, generator_adv_loss=1.94, generator_feat_match_loss=6.181, over 31.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.365, discriminator_fake_loss=1.32, generator_loss=28.86, generator_mel_loss=17.74, generator_kl_loss=1.441, generator_dur_loss=1.737, generator_adv_loss=2.015, generator_feat_match_loss=5.927, over 6017.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 13:36:16,611 INFO [train.py:919] (2/6) Start epoch 831
2024-03-15 13:38:02,944 INFO [train.py:527] (2/6) Epoch 831, batch 30, global_batch_idx: 102950, batch size: 88, loss[discriminator_loss=2.62, discriminator_real_loss=1.325, discriminator_fake_loss=1.294, generator_loss=28.81, generator_mel_loss=17.44, generator_kl_loss=1.34, generator_dur_loss=1.848, generator_adv_loss=2.076, generator_feat_match_loss=6.1, over 88.00 samples.], tot_loss[discriminator_loss=2.691, discriminator_real_loss=1.361, discriminator_fake_loss=1.329, generator_loss=29.06, generator_mel_loss=17.96, generator_kl_loss=1.44, generator_dur_loss=1.728, generator_adv_loss=2.001, generator_feat_match_loss=5.935, over 1665.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 13:40:21,245 INFO [train.py:527] (2/6) Epoch 831, batch 80, global_batch_idx: 103000, batch size: 36, loss[discriminator_loss=2.636, discriminator_real_loss=1.344, discriminator_fake_loss=1.293, generator_loss=30.8, generator_mel_loss=18.45, generator_kl_loss=1.685, generator_dur_loss=1.647, generator_adv_loss=2.104, generator_feat_match_loss=6.92, over 36.00 samples.], tot_loss[discriminator_loss=2.687, discriminator_real_loss=1.358, discriminator_fake_loss=1.329, generator_loss=29.01, generator_mel_loss=17.88, generator_kl_loss=1.407, generator_dur_loss=1.745, generator_adv_loss=2.004, generator_feat_match_loss=5.983, over 4660.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 13:40:21,246 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 13:40:30,036 INFO [train.py:591] (2/6) Epoch 831, validation: discriminator_loss=2.713, discriminator_real_loss=1.441, discriminator_fake_loss=1.271, generator_loss=27.33, generator_mel_loss=17.78, generator_kl_loss=1.316, generator_dur_loss=1.814, generator_adv_loss=1.989, generator_feat_match_loss=4.432, over 100.00 samples.
2024-03-15 13:40:30,037 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 13:42:31,800 INFO [train.py:919] (2/6) Start epoch 832
2024-03-15 13:43:12,283 INFO [train.py:527] (2/6) Epoch 832, batch 6, global_batch_idx: 103050, batch size: 49, loss[discriminator_loss=2.672, discriminator_real_loss=1.358, discriminator_fake_loss=1.314, generator_loss=28.65, generator_mel_loss=17.98, generator_kl_loss=1.388, generator_dur_loss=1.648, generator_adv_loss=1.858, generator_feat_match_loss=5.779, over 49.00 samples.], tot_loss[discriminator_loss=2.675, discriminator_real_loss=1.344, discriminator_fake_loss=1.331, generator_loss=28.97, generator_mel_loss=17.96, generator_kl_loss=1.471, generator_dur_loss=1.731, generator_adv_loss=1.984, generator_feat_match_loss=5.818, over 361.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 13:45:31,514 INFO [train.py:527] (2/6) Epoch 832, batch 56, global_batch_idx: 103100, batch size: 77, loss[discriminator_loss=2.694, discriminator_real_loss=1.385, discriminator_fake_loss=1.309, generator_loss=28.39, generator_mel_loss=17.49, generator_kl_loss=1.438, generator_dur_loss=1.774, generator_adv_loss=1.976, generator_feat_match_loss=5.715, over 77.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.359, discriminator_fake_loss=1.326, generator_loss=28.95, generator_mel_loss=17.81, generator_kl_loss=1.436, generator_dur_loss=1.749, generator_adv_loss=2.006, generator_feat_match_loss=5.944, over 3291.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 13:47:51,740 INFO [train.py:527] (2/6) Epoch 832, batch 106, global_batch_idx: 103150, batch size: 56, loss[discriminator_loss=2.702, discriminator_real_loss=1.438, discriminator_fake_loss=1.264, generator_loss=28.74, generator_mel_loss=17.63, generator_kl_loss=1.528, generator_dur_loss=1.682, generator_adv_loss=1.976, generator_feat_match_loss=5.931, over 56.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.361, discriminator_fake_loss=1.324, generator_loss=29.03, generator_mel_loss=17.85, generator_kl_loss=1.449, generator_dur_loss=1.742, generator_adv_loss=2.017, generator_feat_match_loss=5.974, over 5927.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 13:48:36,676 INFO [train.py:919] (2/6) Start epoch 833
2024-03-15 13:50:31,977 INFO [train.py:527] (2/6) Epoch 833, batch 32, global_batch_idx: 103200, batch size: 68, loss[discriminator_loss=2.676, discriminator_real_loss=1.326, discriminator_fake_loss=1.35, generator_loss=29.72, generator_mel_loss=18.14, generator_kl_loss=1.412, generator_dur_loss=1.755, generator_adv_loss=2.019, generator_feat_match_loss=6.395, over 68.00 samples.], tot_loss[discriminator_loss=2.675, discriminator_real_loss=1.353, discriminator_fake_loss=1.322, generator_loss=28.95, generator_mel_loss=17.82, generator_kl_loss=1.413, generator_dur_loss=1.742, generator_adv_loss=2.008, generator_feat_match_loss=5.967, over 2020.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 13:50:31,978 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 13:50:39,868 INFO [train.py:591] (2/6) Epoch 833, validation: discriminator_loss=2.712, discriminator_real_loss=1.41, discriminator_fake_loss=1.302, generator_loss=28.64, generator_mel_loss=18.45, generator_kl_loss=1.419, generator_dur_loss=1.795, generator_adv_loss=1.966, generator_feat_match_loss=5.01, over 100.00 samples.
2024-03-15 13:50:39,869 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 13:53:00,000 INFO [train.py:527] (2/6) Epoch 833, batch 82, global_batch_idx: 103250, batch size: 39, loss[discriminator_loss=2.695, discriminator_real_loss=1.351, discriminator_fake_loss=1.344, generator_loss=26.7, generator_mel_loss=17.3, generator_kl_loss=1.55, generator_dur_loss=1.701, generator_adv_loss=1.884, generator_feat_match_loss=4.266, over 39.00 samples.], tot_loss[discriminator_loss=2.678, discriminator_real_loss=1.357, discriminator_fake_loss=1.321, generator_loss=29.09, generator_mel_loss=17.82, generator_kl_loss=1.43, generator_dur_loss=1.74, generator_adv_loss=2.011, generator_feat_match_loss=6.085, over 4825.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 13:54:51,831 INFO [train.py:919] (2/6) Start epoch 834
2024-03-15 13:55:35,744 INFO [train.py:527] (2/6) Epoch 834, batch 8, global_batch_idx: 103300, batch size: 44, loss[discriminator_loss=2.643, discriminator_real_loss=1.245, discriminator_fake_loss=1.398, generator_loss=28.41, generator_mel_loss=17.66, generator_kl_loss=1.36, generator_dur_loss=1.68, generator_adv_loss=2.138, generator_feat_match_loss=5.572, over 44.00 samples.], tot_loss[discriminator_loss=2.671, discriminator_real_loss=1.345, discriminator_fake_loss=1.327, generator_loss=28.82, generator_mel_loss=17.79, generator_kl_loss=1.406, generator_dur_loss=1.686, generator_adv_loss=2.006, generator_feat_match_loss=5.927, over 448.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 13:57:53,731 INFO [train.py:527] (2/6) Epoch 834, batch 58, global_batch_idx: 103350, batch size: 50, loss[discriminator_loss=2.649, discriminator_real_loss=1.391, discriminator_fake_loss=1.258, generator_loss=28.82, generator_mel_loss=17.56, generator_kl_loss=1.536, generator_dur_loss=1.685, generator_adv_loss=2.019, generator_feat_match_loss=6.022, over 50.00 samples.], tot_loss[discriminator_loss=2.681, discriminator_real_loss=1.354, discriminator_fake_loss=1.327, generator_loss=28.92, generator_mel_loss=17.76, generator_kl_loss=1.417, generator_dur_loss=1.732, generator_adv_loss=2.003, generator_feat_match_loss=6.007, over 3336.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 14:00:12,081 INFO [train.py:527] (2/6) Epoch 834, batch 108, global_batch_idx: 103400, batch size: 83, loss[discriminator_loss=2.715, discriminator_real_loss=1.317, discriminator_fake_loss=1.398, generator_loss=29.09, generator_mel_loss=17.75, generator_kl_loss=1.445, generator_dur_loss=1.787, generator_adv_loss=1.929, generator_feat_match_loss=6.177, over 83.00 samples.], tot_loss[discriminator_loss=2.682, discriminator_real_loss=1.358, discriminator_fake_loss=1.324, generator_loss=28.9, generator_mel_loss=17.77, generator_kl_loss=1.411, generator_dur_loss=1.741, generator_adv_loss=2.016, generator_feat_match_loss=5.967, over 6388.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 14:00:12,083 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 14:00:20,873 INFO [train.py:591] (2/6) Epoch 834, validation: discriminator_loss=2.701, discriminator_real_loss=1.406, discriminator_fake_loss=1.295, generator_loss=28.53, generator_mel_loss=18.59, generator_kl_loss=1.318, generator_dur_loss=1.791, generator_adv_loss=1.891, generator_feat_match_loss=4.939, over 100.00 samples.
2024-03-15 14:00:20,873 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 14:01:05,596 INFO [train.py:919] (2/6) Start epoch 835
2024-03-15 14:03:05,101 INFO [train.py:527] (2/6) Epoch 835, batch 34, global_batch_idx: 103450, batch size: 50, loss[discriminator_loss=2.703, discriminator_real_loss=1.256, discriminator_fake_loss=1.447, generator_loss=28.96, generator_mel_loss=18.03, generator_kl_loss=1.454, generator_dur_loss=1.651, generator_adv_loss=1.997, generator_feat_match_loss=5.832, over 50.00 samples.], tot_loss[discriminator_loss=2.671, discriminator_real_loss=1.346, discriminator_fake_loss=1.325, generator_loss=29.05, generator_mel_loss=17.83, generator_kl_loss=1.416, generator_dur_loss=1.736, generator_adv_loss=1.995, generator_feat_match_loss=6.075, over 2005.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 14:05:22,196 INFO [train.py:527] (2/6) Epoch 835, batch 84, global_batch_idx: 103500, batch size: 45, loss[discriminator_loss=2.748, discriminator_real_loss=1.24, discriminator_fake_loss=1.507, generator_loss=28.65, generator_mel_loss=17.69, generator_kl_loss=1.437, generator_dur_loss=1.641, generator_adv_loss=1.944, generator_feat_match_loss=5.939, over 45.00 samples.], tot_loss[discriminator_loss=2.679, discriminator_real_loss=1.353, discriminator_fake_loss=1.325, generator_loss=28.94, generator_mel_loss=17.79, generator_kl_loss=1.423, generator_dur_loss=1.742, generator_adv_loss=1.993, generator_feat_match_loss=5.997, over 4902.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 14:07:11,014 INFO [train.py:919] (2/6) Start epoch 836
2024-03-15 14:08:02,098 INFO [train.py:527] (2/6) Epoch 836, batch 10, global_batch_idx: 103550, batch size: 59, loss[discriminator_loss=2.627, discriminator_real_loss=1.293, discriminator_fake_loss=1.335, generator_loss=29.15, generator_mel_loss=18, generator_kl_loss=1.378, generator_dur_loss=1.723, generator_adv_loss=2.103, generator_feat_match_loss=5.946, over 59.00 samples.], tot_loss[discriminator_loss=2.691, discriminator_real_loss=1.363, discriminator_fake_loss=1.329, generator_loss=28.98, generator_mel_loss=17.83, generator_kl_loss=1.387, generator_dur_loss=1.765, generator_adv_loss=1.989, generator_feat_match_loss=6.005, over 654.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 14:10:26,493 INFO [train.py:527] (2/6) Epoch 836, batch 60, global_batch_idx: 103600, batch size: 80, loss[discriminator_loss=2.639, discriminator_real_loss=1.243, discriminator_fake_loss=1.396, generator_loss=29.45, generator_mel_loss=17.83, generator_kl_loss=1.431, generator_dur_loss=1.814, generator_adv_loss=1.956, generator_feat_match_loss=6.423, over 80.00 samples.], tot_loss[discriminator_loss=2.678, discriminator_real_loss=1.352, discriminator_fake_loss=1.327, generator_loss=29.03, generator_mel_loss=17.77, generator_kl_loss=1.419, generator_dur_loss=1.762, generator_adv_loss=1.999, generator_feat_match_loss=6.083, over 3624.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 14:10:26,494 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 14:10:34,774 INFO [train.py:591] (2/6) Epoch 836, validation: discriminator_loss=2.731, discriminator_real_loss=1.39, discriminator_fake_loss=1.341, generator_loss=28.17, generator_mel_loss=18.22, generator_kl_loss=1.235, generator_dur_loss=1.796, generator_adv_loss=1.845, generator_feat_match_loss=5.078, over 100.00 samples.
2024-03-15 14:10:34,775 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 14:12:51,399 INFO [train.py:527] (2/6) Epoch 836, batch 110, global_batch_idx: 103650, batch size: 52, loss[discriminator_loss=2.679, discriminator_real_loss=1.357, discriminator_fake_loss=1.321, generator_loss=29.86, generator_mel_loss=18.12, generator_kl_loss=1.426, generator_dur_loss=1.658, generator_adv_loss=2.025, generator_feat_match_loss=6.633, over 52.00 samples.], tot_loss[discriminator_loss=2.679, discriminator_real_loss=1.355, discriminator_fake_loss=1.324, generator_loss=28.92, generator_mel_loss=17.76, generator_kl_loss=1.422, generator_dur_loss=1.757, generator_adv_loss=2, generator_feat_match_loss=5.988, over 6733.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 14:13:25,182 INFO [train.py:919] (2/6) Start epoch 837
2024-03-15 14:15:31,705 INFO [train.py:527] (2/6) Epoch 837, batch 36, global_batch_idx: 103700, batch size: 42, loss[discriminator_loss=2.657, discriminator_real_loss=1.358, discriminator_fake_loss=1.299, generator_loss=29.33, generator_mel_loss=18.2, generator_kl_loss=1.503, generator_dur_loss=1.624, generator_adv_loss=2.079, generator_feat_match_loss=5.93, over 42.00 samples.], tot_loss[discriminator_loss=2.67, discriminator_real_loss=1.345, discriminator_fake_loss=1.326, generator_loss=29.27, generator_mel_loss=17.85, generator_kl_loss=1.458, generator_dur_loss=1.72, generator_adv_loss=2.045, generator_feat_match_loss=6.196, over 1924.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 14:17:48,982 INFO [train.py:527] (2/6) Epoch 837, batch 86, global_batch_idx: 103750, batch size: 31, loss[discriminator_loss=2.71, discriminator_real_loss=1.302, discriminator_fake_loss=1.409, generator_loss=29.19, generator_mel_loss=17.84, generator_kl_loss=1.579, generator_dur_loss=1.615, generator_adv_loss=1.915, generator_feat_match_loss=6.24, over 31.00 samples.], tot_loss[discriminator_loss=2.672, discriminator_real_loss=1.353, discriminator_fake_loss=1.319, generator_loss=29.21, generator_mel_loss=17.86, generator_kl_loss=1.451, generator_dur_loss=1.723, generator_adv_loss=2.024, generator_feat_match_loss=6.153, over 4574.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 14:19:30,370 INFO [train.py:919] (2/6) Start epoch 838
2024-03-15 14:20:25,544 INFO [train.py:527] (2/6) Epoch 838, batch 12, global_batch_idx: 103800, batch size: 50, loss[discriminator_loss=2.691, discriminator_real_loss=1.297, discriminator_fake_loss=1.395, generator_loss=29.74, generator_mel_loss=18.14, generator_kl_loss=1.475, generator_dur_loss=1.68, generator_adv_loss=1.91, generator_feat_match_loss=6.532, over 50.00 samples.], tot_loss[discriminator_loss=2.677, discriminator_real_loss=1.367, discriminator_fake_loss=1.31, generator_loss=28.74, generator_mel_loss=17.74, generator_kl_loss=1.456, generator_dur_loss=1.709, generator_adv_loss=2.024, generator_feat_match_loss=5.812, over 720.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 14:20:25,547 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 14:20:33,316 INFO [train.py:591] (2/6) Epoch 838, validation: discriminator_loss=2.724, discriminator_real_loss=1.304, discriminator_fake_loss=1.42, generator_loss=27.89, generator_mel_loss=18.08, generator_kl_loss=1.151, generator_dur_loss=1.8, generator_adv_loss=1.83, generator_feat_match_loss=5.03, over 100.00 samples.
2024-03-15 14:20:33,317 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 14:22:51,890 INFO [train.py:527] (2/6) Epoch 838, batch 62, global_batch_idx: 103850, batch size: 88, loss[discriminator_loss=2.68, discriminator_real_loss=1.318, discriminator_fake_loss=1.362, generator_loss=28.92, generator_mel_loss=18.26, generator_kl_loss=1.127, generator_dur_loss=1.816, generator_adv_loss=1.952, generator_feat_match_loss=5.756, over 88.00 samples.], tot_loss[discriminator_loss=2.679, discriminator_real_loss=1.358, discriminator_fake_loss=1.321, generator_loss=28.95, generator_mel_loss=17.8, generator_kl_loss=1.42, generator_dur_loss=1.735, generator_adv_loss=2.001, generator_feat_match_loss=5.988, over 3709.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 14:25:14,116 INFO [train.py:527] (2/6) Epoch 838, batch 112, global_batch_idx: 103900, batch size: 50, loss[discriminator_loss=2.597, discriminator_real_loss=1.285, discriminator_fake_loss=1.312, generator_loss=29.84, generator_mel_loss=18.08, generator_kl_loss=1.507, generator_dur_loss=1.708, generator_adv_loss=1.978, generator_feat_match_loss=6.564, over 50.00 samples.], tot_loss[discriminator_loss=2.678, discriminator_real_loss=1.358, discriminator_fake_loss=1.32, generator_loss=29.01, generator_mel_loss=17.81, generator_kl_loss=1.416, generator_dur_loss=1.743, generator_adv_loss=2.002, generator_feat_match_loss=6.037, over 6637.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 14:25:44,320 INFO [train.py:919] (2/6) Start epoch 839
2024-03-15 14:27:55,786 INFO [train.py:527] (2/6) Epoch 839, batch 38, global_batch_idx: 103950, batch size: 64, loss[discriminator_loss=2.631, discriminator_real_loss=1.411, discriminator_fake_loss=1.22, generator_loss=29.02, generator_mel_loss=17.76, generator_kl_loss=1.246, generator_dur_loss=1.748, generator_adv_loss=1.915, generator_feat_match_loss=6.351, over 64.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.358, discriminator_fake_loss=1.327, generator_loss=28.92, generator_mel_loss=17.8, generator_kl_loss=1.408, generator_dur_loss=1.759, generator_adv_loss=1.994, generator_feat_match_loss=5.962, over 2248.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 14:30:14,704 INFO [train.py:527] (2/6) Epoch 839, batch 88, global_batch_idx: 104000, batch size: 55, loss[discriminator_loss=2.71, discriminator_real_loss=1.315, discriminator_fake_loss=1.395, generator_loss=28.72, generator_mel_loss=18.34, generator_kl_loss=1.561, generator_dur_loss=1.73, generator_adv_loss=1.919, generator_feat_match_loss=5.163, over 55.00 samples.], tot_loss[discriminator_loss=2.681, discriminator_real_loss=1.354, discriminator_fake_loss=1.327, generator_loss=29.05, generator_mel_loss=17.87, generator_kl_loss=1.406, generator_dur_loss=1.764, generator_adv_loss=1.999, generator_feat_match_loss=6.009, over 5179.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 14:30:14,705 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 14:30:23,581 INFO [train.py:591] (2/6) Epoch 839, validation: discriminator_loss=2.717, discriminator_real_loss=1.366, discriminator_fake_loss=1.351, generator_loss=28.05, generator_mel_loss=18.16, generator_kl_loss=1.27, generator_dur_loss=1.817, generator_adv_loss=1.861, generator_feat_match_loss=4.934, over 100.00 samples.
2024-03-15 14:30:23,582 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 14:31:59,414 INFO [train.py:919] (2/6) Start epoch 840
2024-03-15 14:33:02,572 INFO [train.py:527] (2/6) Epoch 840, batch 14, global_batch_idx: 104050, batch size: 66, loss[discriminator_loss=2.71, discriminator_real_loss=1.401, discriminator_fake_loss=1.309, generator_loss=29.08, generator_mel_loss=18.01, generator_kl_loss=1.291, generator_dur_loss=1.75, generator_adv_loss=2.057, generator_feat_match_loss=5.969, over 66.00 samples.], tot_loss[discriminator_loss=2.691, discriminator_real_loss=1.356, discriminator_fake_loss=1.335, generator_loss=29.36, generator_mel_loss=17.92, generator_kl_loss=1.4, generator_dur_loss=1.735, generator_adv_loss=2.038, generator_feat_match_loss=6.273, over 817.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 14:35:22,488 INFO [train.py:527] (2/6) Epoch 840, batch 64, global_batch_idx: 104100, batch size: 45, loss[discriminator_loss=2.701, discriminator_real_loss=1.399, discriminator_fake_loss=1.303, generator_loss=28.62, generator_mel_loss=17.93, generator_kl_loss=1.653, generator_dur_loss=1.638, generator_adv_loss=2.011, generator_feat_match_loss=5.383, over 45.00 samples.], tot_loss[discriminator_loss=2.689, discriminator_real_loss=1.36, discriminator_fake_loss=1.329, generator_loss=29.11, generator_mel_loss=17.85, generator_kl_loss=1.415, generator_dur_loss=1.749, generator_adv_loss=2.015, generator_feat_match_loss=6.081, over 3789.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 14:37:43,219 INFO [train.py:527] (2/6) Epoch 840, batch 114, global_batch_idx: 104150, batch size: 55, loss[discriminator_loss=2.731, discriminator_real_loss=1.383, discriminator_fake_loss=1.348, generator_loss=28.81, generator_mel_loss=17.57, generator_kl_loss=1.396, generator_dur_loss=1.687, generator_adv_loss=2.015, generator_feat_match_loss=6.137, over 55.00 samples.], tot_loss[discriminator_loss=2.69, discriminator_real_loss=1.36, discriminator_fake_loss=1.33, generator_loss=29.03, generator_mel_loss=17.83, generator_kl_loss=1.414, generator_dur_loss=1.757, generator_adv_loss=2.004, generator_feat_match_loss=6.022, over 6786.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 14:38:10,550 INFO [train.py:919] (2/6) Start epoch 841
2024-03-15 14:40:29,581 INFO [train.py:527] (2/6) Epoch 841, batch 40, global_batch_idx: 104200, batch size: 36, loss[discriminator_loss=2.655, discriminator_real_loss=1.371, discriminator_fake_loss=1.284, generator_loss=30.27, generator_mel_loss=18.31, generator_kl_loss=1.653, generator_dur_loss=1.638, generator_adv_loss=1.837, generator_feat_match_loss=6.832, over 36.00 samples.], tot_loss[discriminator_loss=2.68, discriminator_real_loss=1.354, discriminator_fake_loss=1.326, generator_loss=29.11, generator_mel_loss=17.87, generator_kl_loss=1.406, generator_dur_loss=1.766, generator_adv_loss=1.997, generator_feat_match_loss=6.066, over 2505.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 14:40:29,582 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 14:40:37,611 INFO [train.py:591] (2/6) Epoch 841, validation: discriminator_loss=2.768, discriminator_real_loss=1.355, discriminator_fake_loss=1.413, generator_loss=28.2, generator_mel_loss=18.32, generator_kl_loss=1.233, generator_dur_loss=1.813, generator_adv_loss=1.759, generator_feat_match_loss=5.072, over 100.00 samples.
2024-03-15 14:40:37,612 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 14:42:54,702 INFO [train.py:527] (2/6) Epoch 841, batch 90, global_batch_idx: 104250, batch size: 53, loss[discriminator_loss=2.693, discriminator_real_loss=1.352, discriminator_fake_loss=1.341, generator_loss=28.84, generator_mel_loss=18.11, generator_kl_loss=1.442, generator_dur_loss=1.722, generator_adv_loss=1.907, generator_feat_match_loss=5.656, over 53.00 samples.], tot_loss[discriminator_loss=2.674, discriminator_real_loss=1.355, discriminator_fake_loss=1.319, generator_loss=29, generator_mel_loss=17.83, generator_kl_loss=1.425, generator_dur_loss=1.759, generator_adv_loss=1.997, generator_feat_match_loss=5.994, over 5331.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 14:44:26,673 INFO [train.py:919] (2/6) Start epoch 842
2024-03-15 14:45:35,183 INFO [train.py:527] (2/6) Epoch 842, batch 16, global_batch_idx: 104300, batch size: 66, loss[discriminator_loss=2.656, discriminator_real_loss=1.298, discriminator_fake_loss=1.358, generator_loss=28.87, generator_mel_loss=17.81, generator_kl_loss=1.43, generator_dur_loss=1.724, generator_adv_loss=2.046, generator_feat_match_loss=5.859, over 66.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.368, discriminator_fake_loss=1.308, generator_loss=29, generator_mel_loss=17.8, generator_kl_loss=1.47, generator_dur_loss=1.73, generator_adv_loss=2.011, generator_feat_match_loss=5.989, over 975.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 14:47:53,224 INFO [train.py:527] (2/6) Epoch 842, batch 66, global_batch_idx: 104350, batch size: 42, loss[discriminator_loss=2.652, discriminator_real_loss=1.208, discriminator_fake_loss=1.445, generator_loss=29.93, generator_mel_loss=17.69, generator_kl_loss=1.668, generator_dur_loss=1.677, generator_adv_loss=2.054, generator_feat_match_loss=6.838, over 42.00 samples.], tot_loss[discriminator_loss=2.677, discriminator_real_loss=1.359, discriminator_fake_loss=1.318, generator_loss=29.04, generator_mel_loss=17.81, generator_kl_loss=1.443, generator_dur_loss=1.749, generator_adv_loss=1.989, generator_feat_match_loss=6.046, over 3818.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 14:50:14,366 INFO [train.py:527] (2/6) Epoch 842, batch 116, global_batch_idx: 104400, batch size: 45, loss[discriminator_loss=2.74, discriminator_real_loss=1.416, discriminator_fake_loss=1.325, generator_loss=28.41, generator_mel_loss=17.7, generator_kl_loss=1.46, generator_dur_loss=1.694, generator_adv_loss=2.102, generator_feat_match_loss=5.458, over 45.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.358, discriminator_fake_loss=1.318, generator_loss=29.03, generator_mel_loss=17.77, generator_kl_loss=1.429, generator_dur_loss=1.754, generator_adv_loss=2.001, generator_feat_match_loss=6.07, over 6864.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 14:50:14,367 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 14:50:23,187 INFO [train.py:591] (2/6) Epoch 842, validation: discriminator_loss=2.706, discriminator_real_loss=1.497, discriminator_fake_loss=1.209, generator_loss=28.94, generator_mel_loss=18.29, generator_kl_loss=1.225, generator_dur_loss=1.809, generator_adv_loss=2.086, generator_feat_match_loss=5.528, over 100.00 samples.
2024-03-15 14:50:23,188 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 14:50:44,150 INFO [train.py:919] (2/6) Start epoch 843
2024-03-15 14:53:01,726 INFO [train.py:527] (2/6) Epoch 843, batch 42, global_batch_idx: 104450, batch size: 66, loss[discriminator_loss=2.726, discriminator_real_loss=1.398, discriminator_fake_loss=1.328, generator_loss=28.82, generator_mel_loss=17.93, generator_kl_loss=1.504, generator_dur_loss=1.714, generator_adv_loss=1.936, generator_feat_match_loss=5.738, over 66.00 samples.], tot_loss[discriminator_loss=2.703, discriminator_real_loss=1.371, discriminator_fake_loss=1.332, generator_loss=28.74, generator_mel_loss=17.74, generator_kl_loss=1.41, generator_dur_loss=1.754, generator_adv_loss=1.99, generator_feat_match_loss=5.846, over 2544.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 14:55:21,125 INFO [train.py:527] (2/6) Epoch 843, batch 92, global_batch_idx: 104500, batch size: 64, loss[discriminator_loss=2.67, discriminator_real_loss=1.425, discriminator_fake_loss=1.245, generator_loss=29.78, generator_mel_loss=17.99, generator_kl_loss=1.33, generator_dur_loss=1.758, generator_adv_loss=1.983, generator_feat_match_loss=6.712, over 64.00 samples.], tot_loss[discriminator_loss=2.695, discriminator_real_loss=1.365, discriminator_fake_loss=1.33, generator_loss=28.83, generator_mel_loss=17.79, generator_kl_loss=1.416, generator_dur_loss=1.755, generator_adv_loss=1.997, generator_feat_match_loss=5.875, over 5484.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 14:56:46,866 INFO [train.py:919] (2/6) Start epoch 844
2024-03-15 14:58:00,521 INFO [train.py:527] (2/6) Epoch 844, batch 18, global_batch_idx: 104550, batch size: 53, loss[discriminator_loss=2.717, discriminator_real_loss=1.331, discriminator_fake_loss=1.386, generator_loss=28.6, generator_mel_loss=18, generator_kl_loss=1.454, generator_dur_loss=1.639, generator_adv_loss=1.856, generator_feat_match_loss=5.644, over 53.00 samples.], tot_loss[discriminator_loss=2.663, discriminator_real_loss=1.335, discriminator_fake_loss=1.327, generator_loss=29.34, generator_mel_loss=17.83, generator_kl_loss=1.46, generator_dur_loss=1.714, generator_adv_loss=2.067, generator_feat_match_loss=6.263, over 1055.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 15:00:22,358 INFO [train.py:527] (2/6) Epoch 844, batch 68, global_batch_idx: 104600, batch size: 74, loss[discriminator_loss=2.684, discriminator_real_loss=1.344, discriminator_fake_loss=1.341, generator_loss=29.47, generator_mel_loss=17.54, generator_kl_loss=1.456, generator_dur_loss=1.784, generator_adv_loss=2.087, generator_feat_match_loss=6.603, over 74.00 samples.], tot_loss[discriminator_loss=2.683, discriminator_real_loss=1.355, discriminator_fake_loss=1.327, generator_loss=29.02, generator_mel_loss=17.77, generator_kl_loss=1.444, generator_dur_loss=1.741, generator_adv_loss=2.027, generator_feat_match_loss=6.033, over 3969.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 15:00:22,359 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 15:00:31,249 INFO [train.py:591] (2/6) Epoch 844, validation: discriminator_loss=2.775, discriminator_real_loss=1.483, discriminator_fake_loss=1.292, generator_loss=27.8, generator_mel_loss=18, generator_kl_loss=1.25, generator_dur_loss=1.795, generator_adv_loss=2.016, generator_feat_match_loss=4.74, over 100.00 samples.
2024-03-15 15:00:31,253 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 15:02:49,506 INFO [train.py:527] (2/6) Epoch 844, batch 118, global_batch_idx: 104650, batch size: 64, loss[discriminator_loss=2.702, discriminator_real_loss=1.41, discriminator_fake_loss=1.291, generator_loss=28.62, generator_mel_loss=17.62, generator_kl_loss=1.431, generator_dur_loss=1.756, generator_adv_loss=2.028, generator_feat_match_loss=5.79, over 64.00 samples.], tot_loss[discriminator_loss=2.683, discriminator_real_loss=1.36, discriminator_fake_loss=1.323, generator_loss=28.95, generator_mel_loss=17.77, generator_kl_loss=1.444, generator_dur_loss=1.736, generator_adv_loss=2.015, generator_feat_match_loss=5.987, over 6707.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 15:03:04,546 INFO [train.py:919] (2/6) Start epoch 845
2024-03-15 15:05:32,942 INFO [train.py:527] (2/6) Epoch 845, batch 44, global_batch_idx: 104700, batch size: 80, loss[discriminator_loss=2.687, discriminator_real_loss=1.406, discriminator_fake_loss=1.281, generator_loss=28.08, generator_mel_loss=17.42, generator_kl_loss=1.335, generator_dur_loss=1.802, generator_adv_loss=1.969, generator_feat_match_loss=5.554, over 80.00 samples.], tot_loss[discriminator_loss=2.689, discriminator_real_loss=1.37, discriminator_fake_loss=1.319, generator_loss=29.02, generator_mel_loss=17.87, generator_kl_loss=1.383, generator_dur_loss=1.747, generator_adv_loss=2.006, generator_feat_match_loss=6.01, over 2594.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 15:07:50,468 INFO [train.py:527] (2/6) Epoch 845, batch 94, global_batch_idx: 104750, batch size: 70, loss[discriminator_loss=2.683, discriminator_real_loss=1.329, discriminator_fake_loss=1.354, generator_loss=28.94, generator_mel_loss=17.8, generator_kl_loss=1.337, generator_dur_loss=1.805, generator_adv_loss=2.009, generator_feat_match_loss=5.992, over 70.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.36, discriminator_fake_loss=1.326, generator_loss=29.03, generator_mel_loss=17.85, generator_kl_loss=1.412, generator_dur_loss=1.74, generator_adv_loss=2.003, generator_feat_match_loss=6.031, over 5256.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 15:09:11,263 INFO [train.py:919] (2/6) Start epoch 846
2024-03-15 15:10:31,969 INFO [train.py:527] (2/6) Epoch 846, batch 20, global_batch_idx: 104800, batch size: 36, loss[discriminator_loss=2.644, discriminator_real_loss=1.314, discriminator_fake_loss=1.33, generator_loss=30.21, generator_mel_loss=18.3, generator_kl_loss=1.692, generator_dur_loss=1.67, generator_adv_loss=1.971, generator_feat_match_loss=6.573, over 36.00 samples.], tot_loss[discriminator_loss=2.682, discriminator_real_loss=1.374, discriminator_fake_loss=1.309, generator_loss=29.06, generator_mel_loss=17.79, generator_kl_loss=1.45, generator_dur_loss=1.714, generator_adv_loss=2.007, generator_feat_match_loss=6.103, over 1012.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 15:10:31,971 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 15:10:40,201 INFO [train.py:591] (2/6) Epoch 846, validation: discriminator_loss=2.711, discriminator_real_loss=1.363, discriminator_fake_loss=1.349, generator_loss=27.95, generator_mel_loss=18.45, generator_kl_loss=1.275, generator_dur_loss=1.793, generator_adv_loss=1.845, generator_feat_match_loss=4.584, over 100.00 samples.
2024-03-15 15:10:40,202 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 15:12:56,244 INFO [train.py:527] (2/6) Epoch 846, batch 70, global_batch_idx: 104850, batch size: 42, loss[discriminator_loss=2.613, discriminator_real_loss=1.25, discriminator_fake_loss=1.363, generator_loss=30.29, generator_mel_loss=17.65, generator_kl_loss=1.535, generator_dur_loss=1.682, generator_adv_loss=2.27, generator_feat_match_loss=7.16, over 42.00 samples.], tot_loss[discriminator_loss=2.68, discriminator_real_loss=1.362, discriminator_fake_loss=1.318, generator_loss=28.98, generator_mel_loss=17.8, generator_kl_loss=1.447, generator_dur_loss=1.718, generator_adv_loss=2.005, generator_feat_match_loss=6.002, over 3746.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 15:15:15,436 INFO [train.py:527] (2/6) Epoch 846, batch 120, global_batch_idx: 104900, batch size: 31, loss[discriminator_loss=2.69, discriminator_real_loss=1.423, discriminator_fake_loss=1.266, generator_loss=30.06, generator_mel_loss=18.32, generator_kl_loss=1.69, generator_dur_loss=1.654, generator_adv_loss=1.969, generator_feat_match_loss=6.426, over 31.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.362, discriminator_fake_loss=1.321, generator_loss=28.97, generator_mel_loss=17.8, generator_kl_loss=1.433, generator_dur_loss=1.737, generator_adv_loss=2.004, generator_feat_match_loss=5.996, over 6833.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 15:15:25,774 INFO [train.py:919] (2/6) Start epoch 847
2024-03-15 15:17:57,157 INFO [train.py:527] (2/6) Epoch 847, batch 46, global_batch_idx: 104950, batch size: 68, loss[discriminator_loss=2.697, discriminator_real_loss=1.38, discriminator_fake_loss=1.317, generator_loss=28.04, generator_mel_loss=17.71, generator_kl_loss=1.412, generator_dur_loss=1.755, generator_adv_loss=1.881, generator_feat_match_loss=5.28, over 68.00 samples.], tot_loss[discriminator_loss=2.673, discriminator_real_loss=1.356, discriminator_fake_loss=1.316, generator_loss=29, generator_mel_loss=17.78, generator_kl_loss=1.434, generator_dur_loss=1.727, generator_adv_loss=2.037, generator_feat_match_loss=6.027, over 2675.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 15:20:17,242 INFO [train.py:527] (2/6) Epoch 847, batch 96, global_batch_idx: 105000, batch size: 47, loss[discriminator_loss=2.678, discriminator_real_loss=1.405, discriminator_fake_loss=1.272, generator_loss=27.72, generator_mel_loss=17.37, generator_kl_loss=1.476, generator_dur_loss=1.692, generator_adv_loss=1.953, generator_feat_match_loss=5.227, over 47.00 samples.], tot_loss[discriminator_loss=2.674, discriminator_real_loss=1.354, discriminator_fake_loss=1.32, generator_loss=28.94, generator_mel_loss=17.76, generator_kl_loss=1.422, generator_dur_loss=1.742, generator_adv_loss=2.016, generator_feat_match_loss=5.995, over 5724.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 15:20:17,245 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 15:20:26,204 INFO [train.py:591] (2/6) Epoch 847, validation: discriminator_loss=2.724, discriminator_real_loss=1.358, discriminator_fake_loss=1.366, generator_loss=27.32, generator_mel_loss=17.85, generator_kl_loss=1.251, generator_dur_loss=1.793, generator_adv_loss=1.83, generator_feat_match_loss=4.59, over 100.00 samples.
2024-03-15 15:20:26,205 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 15:21:42,671 INFO [train.py:919] (2/6) Start epoch 848
2024-03-15 15:23:07,303 INFO [train.py:527] (2/6) Epoch 848, batch 22, global_batch_idx: 105050, batch size: 96, loss[discriminator_loss=2.664, discriminator_real_loss=1.359, discriminator_fake_loss=1.305, generator_loss=29.58, generator_mel_loss=17.87, generator_kl_loss=1.28, generator_dur_loss=1.869, generator_adv_loss=2.054, generator_feat_match_loss=6.512, over 96.00 samples.], tot_loss[discriminator_loss=2.671, discriminator_real_loss=1.35, discriminator_fake_loss=1.322, generator_loss=29.02, generator_mel_loss=17.76, generator_kl_loss=1.396, generator_dur_loss=1.769, generator_adv_loss=2.011, generator_feat_match_loss=6.078, over 1420.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 15:25:25,222 INFO [train.py:527] (2/6) Epoch 848, batch 72, global_batch_idx: 105100, batch size: 45, loss[discriminator_loss=2.647, discriminator_real_loss=1.376, discriminator_fake_loss=1.271, generator_loss=28.96, generator_mel_loss=17.72, generator_kl_loss=1.591, generator_dur_loss=1.668, generator_adv_loss=2.017, generator_feat_match_loss=5.968, over 45.00 samples.], tot_loss[discriminator_loss=2.674, discriminator_real_loss=1.352, discriminator_fake_loss=1.322, generator_loss=29.1, generator_mel_loss=17.77, generator_kl_loss=1.407, generator_dur_loss=1.752, generator_adv_loss=2.01, generator_feat_match_loss=6.156, over 4168.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 15:27:45,026 INFO [train.py:527] (2/6) Epoch 848, batch 122, global_batch_idx: 105150, batch size: 55, loss[discriminator_loss=2.681, discriminator_real_loss=1.39, discriminator_fake_loss=1.29, generator_loss=29.48, generator_mel_loss=18.29, generator_kl_loss=1.543, generator_dur_loss=1.722, generator_adv_loss=2.012, generator_feat_match_loss=5.914, over 55.00 samples.], tot_loss[discriminator_loss=2.677, discriminator_real_loss=1.356, discriminator_fake_loss=1.322, generator_loss=29.09, generator_mel_loss=17.83, generator_kl_loss=1.416, generator_dur_loss=1.754, generator_adv_loss=2.01, generator_feat_match_loss=6.089, over 6934.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 15:27:50,177 INFO [train.py:919] (2/6) Start epoch 849
2024-03-15 15:30:29,675 INFO [train.py:527] (2/6) Epoch 849, batch 48, global_batch_idx: 105200, batch size: 47, loss[discriminator_loss=2.721, discriminator_real_loss=1.426, discriminator_fake_loss=1.296, generator_loss=28.1, generator_mel_loss=17.84, generator_kl_loss=1.499, generator_dur_loss=1.69, generator_adv_loss=1.807, generator_feat_match_loss=5.26, over 47.00 samples.], tot_loss[discriminator_loss=2.675, discriminator_real_loss=1.347, discriminator_fake_loss=1.329, generator_loss=29, generator_mel_loss=17.74, generator_kl_loss=1.409, generator_dur_loss=1.758, generator_adv_loss=2.002, generator_feat_match_loss=6.089, over 2901.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 15:30:29,676 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 15:30:37,817 INFO [train.py:591] (2/6) Epoch 849, validation: discriminator_loss=2.723, discriminator_real_loss=1.264, discriminator_fake_loss=1.459, generator_loss=27.64, generator_mel_loss=18.21, generator_kl_loss=1.177, generator_dur_loss=1.8, generator_adv_loss=1.75, generator_feat_match_loss=4.702, over 100.00 samples.
2024-03-15 15:30:37,819 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 15:32:57,497 INFO [train.py:527] (2/6) Epoch 849, batch 98, global_batch_idx: 105250, batch size: 44, loss[discriminator_loss=2.688, discriminator_real_loss=1.264, discriminator_fake_loss=1.424, generator_loss=29.38, generator_mel_loss=17.88, generator_kl_loss=1.55, generator_dur_loss=1.652, generator_adv_loss=1.931, generator_feat_match_loss=6.365, over 44.00 samples.], tot_loss[discriminator_loss=2.672, discriminator_real_loss=1.346, discriminator_fake_loss=1.326, generator_loss=28.95, generator_mel_loss=17.73, generator_kl_loss=1.402, generator_dur_loss=1.754, generator_adv_loss=2.001, generator_feat_match_loss=6.055, over 5972.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 15:34:06,048 INFO [train.py:919] (2/6) Start epoch 850
2024-03-15 15:35:36,281 INFO [train.py:527] (2/6) Epoch 850, batch 24, global_batch_idx: 105300, batch size: 48, loss[discriminator_loss=2.646, discriminator_real_loss=1.375, discriminator_fake_loss=1.271, generator_loss=30.23, generator_mel_loss=18.21, generator_kl_loss=1.581, generator_dur_loss=1.628, generator_adv_loss=2.121, generator_feat_match_loss=6.688, over 48.00 samples.], tot_loss[discriminator_loss=2.681, discriminator_real_loss=1.355, discriminator_fake_loss=1.326, generator_loss=29.06, generator_mel_loss=17.89, generator_kl_loss=1.422, generator_dur_loss=1.698, generator_adv_loss=2.01, generator_feat_match_loss=6.045, over 1328.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 15:37:54,327 INFO [train.py:527] (2/6) Epoch 850, batch 74, global_batch_idx: 105350, batch size: 96, loss[discriminator_loss=2.668, discriminator_real_loss=1.38, discriminator_fake_loss=1.288, generator_loss=28.53, generator_mel_loss=17.58, generator_kl_loss=1.325, generator_dur_loss=1.831, generator_adv_loss=1.947, generator_feat_match_loss=5.848, over 96.00 samples.], tot_loss[discriminator_loss=2.675, discriminator_real_loss=1.348, discriminator_fake_loss=1.327, generator_loss=29.17, generator_mel_loss=17.91, generator_kl_loss=1.438, generator_dur_loss=1.715, generator_adv_loss=2.004, generator_feat_match_loss=6.096, over 4138.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 15:40:12,481 INFO [train.py:919] (2/6) Start epoch 851
2024-03-15 15:40:36,994 INFO [train.py:527] (2/6) Epoch 851, batch 0, global_batch_idx: 105400, batch size: 58, loss[discriminator_loss=2.729, discriminator_real_loss=1.321, discriminator_fake_loss=1.408, generator_loss=27.99, generator_mel_loss=17.39, generator_kl_loss=1.31, generator_dur_loss=1.734, generator_adv_loss=2.211, generator_feat_match_loss=5.345, over 58.00 samples.], tot_loss[discriminator_loss=2.729, discriminator_real_loss=1.321, discriminator_fake_loss=1.408, generator_loss=27.99, generator_mel_loss=17.39, generator_kl_loss=1.31, generator_dur_loss=1.734, generator_adv_loss=2.211, generator_feat_match_loss=5.345, over 58.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 15:40:37,001 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 15:40:45,135 INFO [train.py:591] (2/6) Epoch 851, validation: discriminator_loss=2.755, discriminator_real_loss=1.525, discriminator_fake_loss=1.23, generator_loss=28.27, generator_mel_loss=18.03, generator_kl_loss=1.212, generator_dur_loss=1.799, generator_adv_loss=2.133, generator_feat_match_loss=5.092, over 100.00 samples.
2024-03-15 15:40:45,137 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 15:43:05,042 INFO [train.py:527] (2/6) Epoch 851, batch 50, global_batch_idx: 105450, batch size: 44, loss[discriminator_loss=2.645, discriminator_real_loss=1.272, discriminator_fake_loss=1.373, generator_loss=29.58, generator_mel_loss=18.04, generator_kl_loss=1.496, generator_dur_loss=1.668, generator_adv_loss=1.982, generator_feat_match_loss=6.389, over 44.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.357, discriminator_fake_loss=1.328, generator_loss=28.9, generator_mel_loss=17.79, generator_kl_loss=1.426, generator_dur_loss=1.733, generator_adv_loss=1.998, generator_feat_match_loss=5.956, over 2917.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 15:45:30,081 INFO [train.py:527] (2/6) Epoch 851, batch 100, global_batch_idx: 105500, batch size: 62, loss[discriminator_loss=2.694, discriminator_real_loss=1.41, discriminator_fake_loss=1.284, generator_loss=28, generator_mel_loss=17.44, generator_kl_loss=1.334, generator_dur_loss=1.755, generator_adv_loss=2.032, generator_feat_match_loss=5.447, over 62.00 samples.], tot_loss[discriminator_loss=2.682, discriminator_real_loss=1.355, discriminator_fake_loss=1.327, generator_loss=28.99, generator_mel_loss=17.82, generator_kl_loss=1.428, generator_dur_loss=1.743, generator_adv_loss=2.004, generator_feat_match_loss=5.991, over 6052.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 15:46:30,770 INFO [train.py:919] (2/6) Start epoch 852
2024-03-15 15:48:06,133 INFO [train.py:527] (2/6) Epoch 852, batch 26, global_batch_idx: 105550, batch size: 77, loss[discriminator_loss=2.638, discriminator_real_loss=1.275, discriminator_fake_loss=1.363, generator_loss=29.16, generator_mel_loss=17.65, generator_kl_loss=1.549, generator_dur_loss=1.802, generator_adv_loss=1.967, generator_feat_match_loss=6.194, over 77.00 samples.], tot_loss[discriminator_loss=2.678, discriminator_real_loss=1.353, discriminator_fake_loss=1.325, generator_loss=29.12, generator_mel_loss=17.84, generator_kl_loss=1.425, generator_dur_loss=1.74, generator_adv_loss=2.017, generator_feat_match_loss=6.097, over 1562.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 15:50:24,310 INFO [train.py:527] (2/6) Epoch 852, batch 76, global_batch_idx: 105600, batch size: 88, loss[discriminator_loss=2.679, discriminator_real_loss=1.344, discriminator_fake_loss=1.335, generator_loss=28.48, generator_mel_loss=18.25, generator_kl_loss=1.463, generator_dur_loss=1.83, generator_adv_loss=1.929, generator_feat_match_loss=5.005, over 88.00 samples.], tot_loss[discriminator_loss=2.677, discriminator_real_loss=1.351, discriminator_fake_loss=1.326, generator_loss=29.14, generator_mel_loss=17.85, generator_kl_loss=1.434, generator_dur_loss=1.74, generator_adv_loss=2.024, generator_feat_match_loss=6.093, over 4410.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 15:50:24,312 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 15:50:33,123 INFO [train.py:591] (2/6) Epoch 852, validation: discriminator_loss=2.749, discriminator_real_loss=1.44, discriminator_fake_loss=1.309, generator_loss=27.58, generator_mel_loss=17.73, generator_kl_loss=1.299, generator_dur_loss=1.807, generator_adv_loss=1.974, generator_feat_match_loss=4.766, over 100.00 samples.
2024-03-15 15:50:33,124 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 15:52:44,617 INFO [train.py:919] (2/6) Start epoch 853
2024-03-15 15:53:14,665 INFO [train.py:527] (2/6) Epoch 853, batch 2, global_batch_idx: 105650, batch size: 74, loss[discriminator_loss=2.692, discriminator_real_loss=1.329, discriminator_fake_loss=1.363, generator_loss=28.67, generator_mel_loss=17.79, generator_kl_loss=1.261, generator_dur_loss=1.807, generator_adv_loss=2.075, generator_feat_match_loss=5.74, over 74.00 samples.], tot_loss[discriminator_loss=2.701, discriminator_real_loss=1.344, discriminator_fake_loss=1.356, generator_loss=29.13, generator_mel_loss=17.95, generator_kl_loss=1.415, generator_dur_loss=1.74, generator_adv_loss=2.019, generator_feat_match_loss=6.001, over 165.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 15:55:34,531 INFO [train.py:527] (2/6) Epoch 853, batch 52, global_batch_idx: 105700, batch size: 80, loss[discriminator_loss=2.663, discriminator_real_loss=1.384, discriminator_fake_loss=1.279, generator_loss=29.79, generator_mel_loss=17.92, generator_kl_loss=1.396, generator_dur_loss=1.76, generator_adv_loss=2.125, generator_feat_match_loss=6.582, over 80.00 samples.], tot_loss[discriminator_loss=2.677, discriminator_real_loss=1.354, discriminator_fake_loss=1.323, generator_loss=28.98, generator_mel_loss=17.78, generator_kl_loss=1.423, generator_dur_loss=1.747, generator_adv_loss=2.003, generator_feat_match_loss=6.023, over 3201.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 15:57:55,578 INFO [train.py:527] (2/6) Epoch 853, batch 102, global_batch_idx: 105750, batch size: 47, loss[discriminator_loss=2.623, discriminator_real_loss=1.349, discriminator_fake_loss=1.274, generator_loss=30.57, generator_mel_loss=18.03, generator_kl_loss=1.627, generator_dur_loss=1.642, generator_adv_loss=2.033, generator_feat_match_loss=7.232, over 47.00 samples.], tot_loss[discriminator_loss=2.682, discriminator_real_loss=1.355, discriminator_fake_loss=1.326, generator_loss=29.04, generator_mel_loss=17.81, generator_kl_loss=1.44, generator_dur_loss=1.74, generator_adv_loss=1.999, generator_feat_match_loss=6.049, over 5870.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 15:58:51,278 INFO [train.py:919] (2/6) Start epoch 854
2024-03-15 16:00:31,940 INFO [train.py:527] (2/6) Epoch 854, batch 28, global_batch_idx: 105800, batch size: 88, loss[discriminator_loss=2.717, discriminator_real_loss=1.378, discriminator_fake_loss=1.339, generator_loss=28.44, generator_mel_loss=17.46, generator_kl_loss=1.189, generator_dur_loss=1.813, generator_adv_loss=1.884, generator_feat_match_loss=6.089, over 88.00 samples.], tot_loss[discriminator_loss=2.678, discriminator_real_loss=1.355, discriminator_fake_loss=1.323, generator_loss=28.83, generator_mel_loss=17.78, generator_kl_loss=1.409, generator_dur_loss=1.73, generator_adv_loss=1.994, generator_feat_match_loss=5.925, over 1683.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 16:00:31,941 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 16:00:40,055 INFO [train.py:591] (2/6) Epoch 854, validation: discriminator_loss=2.732, discriminator_real_loss=1.335, discriminator_fake_loss=1.397, generator_loss=27.9, generator_mel_loss=17.91, generator_kl_loss=1.349, generator_dur_loss=1.796, generator_adv_loss=1.837, generator_feat_match_loss=5.006, over 100.00 samples.
2024-03-15 16:00:40,056 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 16:03:01,604 INFO [train.py:527] (2/6) Epoch 854, batch 78, global_batch_idx: 105850, batch size: 45, loss[discriminator_loss=2.675, discriminator_real_loss=1.362, discriminator_fake_loss=1.313, generator_loss=28.91, generator_mel_loss=18.12, generator_kl_loss=1.542, generator_dur_loss=1.657, generator_adv_loss=2.059, generator_feat_match_loss=5.528, over 45.00 samples.], tot_loss[discriminator_loss=2.675, discriminator_real_loss=1.358, discriminator_fake_loss=1.317, generator_loss=29, generator_mel_loss=17.79, generator_kl_loss=1.434, generator_dur_loss=1.715, generator_adv_loss=2.004, generator_feat_match_loss=6.049, over 4180.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 16:05:08,975 INFO [train.py:919] (2/6) Start epoch 855
2024-03-15 16:05:42,814 INFO [train.py:527] (2/6) Epoch 855, batch 4, global_batch_idx: 105900, batch size: 80, loss[discriminator_loss=2.698, discriminator_real_loss=1.379, discriminator_fake_loss=1.319, generator_loss=28.48, generator_mel_loss=17.56, generator_kl_loss=1.276, generator_dur_loss=1.855, generator_adv_loss=1.945, generator_feat_match_loss=5.838, over 80.00 samples.], tot_loss[discriminator_loss=2.695, discriminator_real_loss=1.404, discriminator_fake_loss=1.291, generator_loss=29.1, generator_mel_loss=17.81, generator_kl_loss=1.401, generator_dur_loss=1.758, generator_adv_loss=2.036, generator_feat_match_loss=6.094, over 302.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 16:08:01,106 INFO [train.py:527] (2/6) Epoch 855, batch 54, global_batch_idx: 105950, batch size: 12, loss[discriminator_loss=2.658, discriminator_real_loss=1.341, discriminator_fake_loss=1.317, generator_loss=28.15, generator_mel_loss=17.72, generator_kl_loss=1.811, generator_dur_loss=1.582, generator_adv_loss=1.96, generator_feat_match_loss=5.079, over 12.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.36, discriminator_fake_loss=1.316, generator_loss=28.99, generator_mel_loss=17.77, generator_kl_loss=1.439, generator_dur_loss=1.735, generator_adv_loss=2.004, generator_feat_match_loss=6.042, over 3086.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 16:10:21,475 INFO [train.py:527] (2/6) Epoch 855, batch 104, global_batch_idx: 106000, batch size: 45, loss[discriminator_loss=2.661, discriminator_real_loss=1.319, discriminator_fake_loss=1.342, generator_loss=28.56, generator_mel_loss=17.62, generator_kl_loss=1.644, generator_dur_loss=1.654, generator_adv_loss=1.971, generator_feat_match_loss=5.671, over 45.00 samples.], tot_loss[discriminator_loss=2.679, discriminator_real_loss=1.358, discriminator_fake_loss=1.321, generator_loss=29.04, generator_mel_loss=17.8, generator_kl_loss=1.44, generator_dur_loss=1.738, generator_adv_loss=2.004, generator_feat_match_loss=6.061, over 5840.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 16:10:21,477 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 16:10:30,231 INFO [train.py:591] (2/6) Epoch 855, validation: discriminator_loss=2.738, discriminator_real_loss=1.342, discriminator_fake_loss=1.397, generator_loss=27.76, generator_mel_loss=18.26, generator_kl_loss=1.239, generator_dur_loss=1.803, generator_adv_loss=1.871, generator_feat_match_loss=4.589, over 100.00 samples.
2024-03-15 16:10:30,232 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 16:11:22,494 INFO [train.py:919] (2/6) Start epoch 856
2024-03-15 16:13:09,371 INFO [train.py:527] (2/6) Epoch 856, batch 30, global_batch_idx: 106050, batch size: 72, loss[discriminator_loss=2.701, discriminator_real_loss=1.405, discriminator_fake_loss=1.296, generator_loss=29.09, generator_mel_loss=17.89, generator_kl_loss=1.433, generator_dur_loss=1.796, generator_adv_loss=2.01, generator_feat_match_loss=5.96, over 72.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.353, discriminator_fake_loss=1.323, generator_loss=29.15, generator_mel_loss=17.87, generator_kl_loss=1.413, generator_dur_loss=1.748, generator_adv_loss=2.042, generator_feat_match_loss=6.076, over 1841.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 16:15:28,336 INFO [train.py:527] (2/6) Epoch 856, batch 80, global_batch_idx: 106100, batch size: 72, loss[discriminator_loss=2.724, discriminator_real_loss=1.34, discriminator_fake_loss=1.384, generator_loss=28.21, generator_mel_loss=17.45, generator_kl_loss=1.393, generator_dur_loss=1.778, generator_adv_loss=2.06, generator_feat_match_loss=5.537, over 72.00 samples.], tot_loss[discriminator_loss=2.681, discriminator_real_loss=1.355, discriminator_fake_loss=1.326, generator_loss=29.07, generator_mel_loss=17.84, generator_kl_loss=1.409, generator_dur_loss=1.742, generator_adv_loss=2.021, generator_feat_match_loss=6.06, over 4815.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 16:17:28,763 INFO [train.py:919] (2/6) Start epoch 857
2024-03-15 16:18:09,589 INFO [train.py:527] (2/6) Epoch 857, batch 6, global_batch_idx: 106150, batch size: 74, loss[discriminator_loss=2.651, discriminator_real_loss=1.307, discriminator_fake_loss=1.344, generator_loss=29.3, generator_mel_loss=17.73, generator_kl_loss=1.203, generator_dur_loss=1.795, generator_adv_loss=2.097, generator_feat_match_loss=6.474, over 74.00 samples.], tot_loss[discriminator_loss=2.665, discriminator_real_loss=1.345, discriminator_fake_loss=1.319, generator_loss=29.06, generator_mel_loss=17.88, generator_kl_loss=1.394, generator_dur_loss=1.717, generator_adv_loss=1.994, generator_feat_match_loss=6.08, over 393.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 16:20:27,313 INFO [train.py:527] (2/6) Epoch 857, batch 56, global_batch_idx: 106200, batch size: 64, loss[discriminator_loss=2.684, discriminator_real_loss=1.319, discriminator_fake_loss=1.365, generator_loss=29.59, generator_mel_loss=18.2, generator_kl_loss=1.412, generator_dur_loss=1.726, generator_adv_loss=1.99, generator_feat_match_loss=6.26, over 64.00 samples.], tot_loss[discriminator_loss=2.674, discriminator_real_loss=1.349, discriminator_fake_loss=1.325, generator_loss=29.13, generator_mel_loss=17.77, generator_kl_loss=1.419, generator_dur_loss=1.741, generator_adv_loss=2.006, generator_feat_match_loss=6.193, over 3191.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 16:20:27,315 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 16:20:35,562 INFO [train.py:591] (2/6) Epoch 857, validation: discriminator_loss=2.751, discriminator_real_loss=1.439, discriminator_fake_loss=1.312, generator_loss=28.33, generator_mel_loss=18.37, generator_kl_loss=1.277, generator_dur_loss=1.797, generator_adv_loss=1.949, generator_feat_match_loss=4.945, over 100.00 samples.
2024-03-15 16:20:35,564 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 16:22:55,696 INFO [train.py:527] (2/6) Epoch 857, batch 106, global_batch_idx: 106250, batch size: 44, loss[discriminator_loss=2.656, discriminator_real_loss=1.371, discriminator_fake_loss=1.285, generator_loss=28.18, generator_mel_loss=17.1, generator_kl_loss=1.582, generator_dur_loss=1.682, generator_adv_loss=2.027, generator_feat_match_loss=5.787, over 44.00 samples.], tot_loss[discriminator_loss=2.673, discriminator_real_loss=1.35, discriminator_fake_loss=1.323, generator_loss=29.1, generator_mel_loss=17.78, generator_kl_loss=1.432, generator_dur_loss=1.739, generator_adv_loss=2.008, generator_feat_match_loss=6.145, over 6011.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 16:23:43,090 INFO [train.py:919] (2/6) Start epoch 858
2024-03-15 16:25:35,212 INFO [train.py:527] (2/6) Epoch 858, batch 32, global_batch_idx: 106300, batch size: 59, loss[discriminator_loss=2.688, discriminator_real_loss=1.386, discriminator_fake_loss=1.302, generator_loss=28.96, generator_mel_loss=17.67, generator_kl_loss=1.433, generator_dur_loss=1.72, generator_adv_loss=1.997, generator_feat_match_loss=6.145, over 59.00 samples.], tot_loss[discriminator_loss=2.689, discriminator_real_loss=1.368, discriminator_fake_loss=1.32, generator_loss=29.13, generator_mel_loss=17.86, generator_kl_loss=1.454, generator_dur_loss=1.729, generator_adv_loss=2.016, generator_feat_match_loss=6.069, over 1699.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 16:27:50,744 INFO [train.py:527] (2/6) Epoch 858, batch 82, global_batch_idx: 106350, batch size: 66, loss[discriminator_loss=2.659, discriminator_real_loss=1.322, discriminator_fake_loss=1.337, generator_loss=28.89, generator_mel_loss=17.45, generator_kl_loss=1.448, generator_dur_loss=1.731, generator_adv_loss=1.981, generator_feat_match_loss=6.275, over 66.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.361, discriminator_fake_loss=1.325, generator_loss=29.16, generator_mel_loss=17.89, generator_kl_loss=1.449, generator_dur_loss=1.728, generator_adv_loss=2.002, generator_feat_match_loss=6.092, over 4341.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 16:29:48,942 INFO [train.py:919] (2/6) Start epoch 859
2024-03-15 16:30:36,520 INFO [train.py:527] (2/6) Epoch 859, batch 8, global_batch_idx: 106400, batch size: 31, loss[discriminator_loss=2.778, discriminator_real_loss=1.375, discriminator_fake_loss=1.403, generator_loss=27.95, generator_mel_loss=17.71, generator_kl_loss=1.511, generator_dur_loss=1.664, generator_adv_loss=1.888, generator_feat_match_loss=5.176, over 31.00 samples.], tot_loss[discriminator_loss=2.68, discriminator_real_loss=1.35, discriminator_fake_loss=1.33, generator_loss=29.08, generator_mel_loss=17.84, generator_kl_loss=1.48, generator_dur_loss=1.736, generator_adv_loss=2, generator_feat_match_loss=6.017, over 497.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 16:30:36,523 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 16:30:44,310 INFO [train.py:591] (2/6) Epoch 859, validation: discriminator_loss=2.728, discriminator_real_loss=1.436, discriminator_fake_loss=1.292, generator_loss=29.1, generator_mel_loss=18.67, generator_kl_loss=1.303, generator_dur_loss=1.801, generator_adv_loss=1.93, generator_feat_match_loss=5.4, over 100.00 samples.
2024-03-15 16:30:44,312 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 16:33:02,137 INFO [train.py:527] (2/6) Epoch 859, batch 58, global_batch_idx: 106450, batch size: 53, loss[discriminator_loss=2.702, discriminator_real_loss=1.344, discriminator_fake_loss=1.358, generator_loss=28.45, generator_mel_loss=17.83, generator_kl_loss=1.564, generator_dur_loss=1.649, generator_adv_loss=1.969, generator_feat_match_loss=5.436, over 53.00 samples.], tot_loss[discriminator_loss=2.67, discriminator_real_loss=1.349, discriminator_fake_loss=1.321, generator_loss=29.11, generator_mel_loss=17.82, generator_kl_loss=1.432, generator_dur_loss=1.746, generator_adv_loss=2.014, generator_feat_match_loss=6.102, over 3438.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 16:35:20,853 INFO [train.py:527] (2/6) Epoch 859, batch 108, global_batch_idx: 106500, batch size: 53, loss[discriminator_loss=2.662, discriminator_real_loss=1.418, discriminator_fake_loss=1.243, generator_loss=29.74, generator_mel_loss=17.85, generator_kl_loss=1.604, generator_dur_loss=1.637, generator_adv_loss=1.897, generator_feat_match_loss=6.746, over 53.00 samples.], tot_loss[discriminator_loss=2.67, discriminator_real_loss=1.35, discriminator_fake_loss=1.32, generator_loss=29.08, generator_mel_loss=17.82, generator_kl_loss=1.425, generator_dur_loss=1.741, generator_adv_loss=2.011, generator_feat_match_loss=6.084, over 6477.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 16:36:03,306 INFO [train.py:919] (2/6) Start epoch 860
2024-03-15 16:38:00,650 INFO [train.py:527] (2/6) Epoch 860, batch 34, global_batch_idx: 106550, batch size: 68, loss[discriminator_loss=2.698, discriminator_real_loss=1.465, discriminator_fake_loss=1.233, generator_loss=28.25, generator_mel_loss=17.54, generator_kl_loss=1.364, generator_dur_loss=1.785, generator_adv_loss=1.923, generator_feat_match_loss=5.64, over 68.00 samples.], tot_loss[discriminator_loss=2.669, discriminator_real_loss=1.353, discriminator_fake_loss=1.316, generator_loss=28.94, generator_mel_loss=17.78, generator_kl_loss=1.449, generator_dur_loss=1.728, generator_adv_loss=2.013, generator_feat_match_loss=5.968, over 1954.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 16:40:16,767 INFO [train.py:527] (2/6) Epoch 860, batch 84, global_batch_idx: 106600, batch size: 96, loss[discriminator_loss=2.663, discriminator_real_loss=1.318, discriminator_fake_loss=1.345, generator_loss=29.07, generator_mel_loss=18.03, generator_kl_loss=1.409, generator_dur_loss=1.884, generator_adv_loss=2.009, generator_feat_match_loss=5.74, over 96.00 samples.], tot_loss[discriminator_loss=2.668, discriminator_real_loss=1.345, discriminator_fake_loss=1.323, generator_loss=29.13, generator_mel_loss=17.83, generator_kl_loss=1.445, generator_dur_loss=1.744, generator_adv_loss=2.017, generator_feat_match_loss=6.098, over 4892.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 16:40:16,769 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 16:40:25,518 INFO [train.py:591] (2/6) Epoch 860, validation: discriminator_loss=2.708, discriminator_real_loss=1.478, discriminator_fake_loss=1.23, generator_loss=28.1, generator_mel_loss=17.94, generator_kl_loss=1.235, generator_dur_loss=1.818, generator_adv_loss=2.011, generator_feat_match_loss=5.09, over 100.00 samples.
2024-03-15 16:40:25,519 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 16:42:19,536 INFO [train.py:919] (2/6) Start epoch 861
2024-03-15 16:43:12,715 INFO [train.py:527] (2/6) Epoch 861, batch 10, global_batch_idx: 106650, batch size: 61, loss[discriminator_loss=2.657, discriminator_real_loss=1.321, discriminator_fake_loss=1.336, generator_loss=29.36, generator_mel_loss=17.82, generator_kl_loss=1.487, generator_dur_loss=1.721, generator_adv_loss=1.998, generator_feat_match_loss=6.333, over 61.00 samples.], tot_loss[discriminator_loss=2.671, discriminator_real_loss=1.362, discriminator_fake_loss=1.31, generator_loss=29.34, generator_mel_loss=17.82, generator_kl_loss=1.482, generator_dur_loss=1.734, generator_adv_loss=2.032, generator_feat_match_loss=6.268, over 637.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 16:45:32,203 INFO [train.py:527] (2/6) Epoch 861, batch 60, global_batch_idx: 106700, batch size: 62, loss[discriminator_loss=2.669, discriminator_real_loss=1.339, discriminator_fake_loss=1.33, generator_loss=28.96, generator_mel_loss=17.95, generator_kl_loss=1.427, generator_dur_loss=1.761, generator_adv_loss=2.002, generator_feat_match_loss=5.822, over 62.00 samples.], tot_loss[discriminator_loss=2.674, discriminator_real_loss=1.358, discriminator_fake_loss=1.316, generator_loss=29.23, generator_mel_loss=17.82, generator_kl_loss=1.447, generator_dur_loss=1.751, generator_adv_loss=2.02, generator_feat_match_loss=6.189, over 3653.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 16:47:49,916 INFO [train.py:527] (2/6) Epoch 861, batch 110, global_batch_idx: 106750, batch size: 56, loss[discriminator_loss=2.713, discriminator_real_loss=1.44, discriminator_fake_loss=1.273, generator_loss=28.82, generator_mel_loss=17.58, generator_kl_loss=1.372, generator_dur_loss=1.667, generator_adv_loss=1.979, generator_feat_match_loss=6.222, over 56.00 samples.], tot_loss[discriminator_loss=2.679, discriminator_real_loss=1.36, discriminator_fake_loss=1.319, generator_loss=29.08, generator_mel_loss=17.78, generator_kl_loss=1.442, generator_dur_loss=1.75, generator_adv_loss=2.017, generator_feat_match_loss=6.095, over 6590.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 16:48:28,759 INFO [train.py:919] (2/6) Start epoch 862
2024-03-15 16:50:33,816 INFO [train.py:527] (2/6) Epoch 862, batch 36, global_batch_idx: 106800, batch size: 52, loss[discriminator_loss=2.6, discriminator_real_loss=1.392, discriminator_fake_loss=1.208, generator_loss=29.99, generator_mel_loss=18.05, generator_kl_loss=1.514, generator_dur_loss=1.683, generator_adv_loss=1.991, generator_feat_match_loss=6.747, over 52.00 samples.], tot_loss[discriminator_loss=2.683, discriminator_real_loss=1.353, discriminator_fake_loss=1.33, generator_loss=29.1, generator_mel_loss=17.83, generator_kl_loss=1.45, generator_dur_loss=1.745, generator_adv_loss=2.011, generator_feat_match_loss=6.068, over 2193.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 16:50:33,817 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 16:50:41,933 INFO [train.py:591] (2/6) Epoch 862, validation: discriminator_loss=2.686, discriminator_real_loss=1.377, discriminator_fake_loss=1.309, generator_loss=26.97, generator_mel_loss=17.55, generator_kl_loss=1.282, generator_dur_loss=1.803, generator_adv_loss=1.825, generator_feat_match_loss=4.515, over 100.00 samples.
2024-03-15 16:50:41,934 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 16:53:01,182 INFO [train.py:527] (2/6) Epoch 862, batch 86, global_batch_idx: 106850, batch size: 56, loss[discriminator_loss=2.734, discriminator_real_loss=1.364, discriminator_fake_loss=1.37, generator_loss=29.46, generator_mel_loss=17.94, generator_kl_loss=1.333, generator_dur_loss=1.718, generator_adv_loss=2.095, generator_feat_match_loss=6.374, over 56.00 samples.], tot_loss[discriminator_loss=2.68, discriminator_real_loss=1.351, discriminator_fake_loss=1.329, generator_loss=29.13, generator_mel_loss=17.8, generator_kl_loss=1.448, generator_dur_loss=1.748, generator_adv_loss=2.009, generator_feat_match_loss=6.125, over 5159.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 16:54:43,384 INFO [train.py:919] (2/6) Start epoch 863
2024-03-15 16:55:40,722 INFO [train.py:527] (2/6) Epoch 863, batch 12, global_batch_idx: 106900, batch size: 52, loss[discriminator_loss=2.646, discriminator_real_loss=1.293, discriminator_fake_loss=1.352, generator_loss=28.92, generator_mel_loss=17.56, generator_kl_loss=1.467, generator_dur_loss=1.678, generator_adv_loss=2.001, generator_feat_match_loss=6.21, over 52.00 samples.], tot_loss[discriminator_loss=2.653, discriminator_real_loss=1.343, discriminator_fake_loss=1.311, generator_loss=29.21, generator_mel_loss=17.93, generator_kl_loss=1.449, generator_dur_loss=1.699, generator_adv_loss=2.007, generator_feat_match_loss=6.127, over 633.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 16:58:01,696 INFO [train.py:527] (2/6) Epoch 863, batch 62, global_batch_idx: 106950, batch size: 83, loss[discriminator_loss=2.666, discriminator_real_loss=1.365, discriminator_fake_loss=1.301, generator_loss=28.14, generator_mel_loss=17.69, generator_kl_loss=1.349, generator_dur_loss=1.847, generator_adv_loss=2.011, generator_feat_match_loss=5.238, over 83.00 samples.], tot_loss[discriminator_loss=2.681, discriminator_real_loss=1.356, discriminator_fake_loss=1.324, generator_loss=28.87, generator_mel_loss=17.77, generator_kl_loss=1.431, generator_dur_loss=1.743, generator_adv_loss=2.003, generator_feat_match_loss=5.923, over 3471.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 17:00:22,772 INFO [train.py:527] (2/6) Epoch 863, batch 112, global_batch_idx: 107000, batch size: 36, loss[discriminator_loss=2.592, discriminator_real_loss=1.288, discriminator_fake_loss=1.303, generator_loss=30.26, generator_mel_loss=18.33, generator_kl_loss=1.68, generator_dur_loss=1.594, generator_adv_loss=2.039, generator_feat_match_loss=6.622, over 36.00 samples.], tot_loss[discriminator_loss=2.679, discriminator_real_loss=1.356, discriminator_fake_loss=1.323, generator_loss=28.95, generator_mel_loss=17.76, generator_kl_loss=1.449, generator_dur_loss=1.738, generator_adv_loss=2.007, generator_feat_match_loss=5.996, over 6201.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 17:00:22,774 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 17:00:31,750 INFO [train.py:591] (2/6) Epoch 863, validation: discriminator_loss=2.749, discriminator_real_loss=1.467, discriminator_fake_loss=1.282, generator_loss=27.81, generator_mel_loss=17.96, generator_kl_loss=1.232, generator_dur_loss=1.805, generator_adv_loss=1.926, generator_feat_match_loss=4.884, over 100.00 samples.
2024-03-15 17:00:31,751 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 17:01:03,443 INFO [train.py:919] (2/6) Start epoch 864
2024-03-15 17:03:14,802 INFO [train.py:527] (2/6) Epoch 864, batch 38, global_batch_idx: 107050, batch size: 45, loss[discriminator_loss=2.669, discriminator_real_loss=1.267, discriminator_fake_loss=1.402, generator_loss=29.58, generator_mel_loss=17.8, generator_kl_loss=1.522, generator_dur_loss=1.675, generator_adv_loss=2.037, generator_feat_match_loss=6.546, over 45.00 samples.], tot_loss[discriminator_loss=2.68, discriminator_real_loss=1.353, discriminator_fake_loss=1.326, generator_loss=29.06, generator_mel_loss=17.8, generator_kl_loss=1.461, generator_dur_loss=1.747, generator_adv_loss=2.001, generator_feat_match_loss=6.048, over 2226.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 17:05:35,931 INFO [train.py:527] (2/6) Epoch 864, batch 88, global_batch_idx: 107100, batch size: 50, loss[discriminator_loss=2.686, discriminator_real_loss=1.348, discriminator_fake_loss=1.338, generator_loss=28.32, generator_mel_loss=17.55, generator_kl_loss=1.403, generator_dur_loss=1.68, generator_adv_loss=2.097, generator_feat_match_loss=5.593, over 50.00 samples.], tot_loss[discriminator_loss=2.681, discriminator_real_loss=1.358, discriminator_fake_loss=1.322, generator_loss=29.02, generator_mel_loss=17.79, generator_kl_loss=1.438, generator_dur_loss=1.744, generator_adv_loss=2.01, generator_feat_match_loss=6.036, over 5235.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 17:07:16,189 INFO [train.py:919] (2/6) Start epoch 865
2024-03-15 17:08:19,488 INFO [train.py:527] (2/6) Epoch 865, batch 14, global_batch_idx: 107150, batch size: 96, loss[discriminator_loss=2.72, discriminator_real_loss=1.376, discriminator_fake_loss=1.344, generator_loss=27.84, generator_mel_loss=17.36, generator_kl_loss=1.375, generator_dur_loss=1.786, generator_adv_loss=1.848, generator_feat_match_loss=5.472, over 96.00 samples.], tot_loss[discriminator_loss=2.701, discriminator_real_loss=1.365, discriminator_fake_loss=1.336, generator_loss=28.79, generator_mel_loss=17.76, generator_kl_loss=1.392, generator_dur_loss=1.725, generator_adv_loss=1.996, generator_feat_match_loss=5.913, over 869.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 17:10:41,859 INFO [train.py:527] (2/6) Epoch 865, batch 64, global_batch_idx: 107200, batch size: 36, loss[discriminator_loss=2.686, discriminator_real_loss=1.351, discriminator_fake_loss=1.336, generator_loss=28.63, generator_mel_loss=17.61, generator_kl_loss=1.647, generator_dur_loss=1.714, generator_adv_loss=2.061, generator_feat_match_loss=5.598, over 36.00 samples.], tot_loss[discriminator_loss=2.679, discriminator_real_loss=1.353, discriminator_fake_loss=1.326, generator_loss=28.99, generator_mel_loss=17.75, generator_kl_loss=1.427, generator_dur_loss=1.731, generator_adv_loss=2.013, generator_feat_match_loss=6.068, over 3562.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 17:10:41,861 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 17:10:49,761 INFO [train.py:591] (2/6) Epoch 865, validation: discriminator_loss=2.681, discriminator_real_loss=1.411, discriminator_fake_loss=1.27, generator_loss=27.54, generator_mel_loss=18.04, generator_kl_loss=1.312, generator_dur_loss=1.8, generator_adv_loss=1.97, generator_feat_match_loss=4.413, over 100.00 samples.
2024-03-15 17:10:49,762 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 17:13:13,611 INFO [train.py:527] (2/6) Epoch 865, batch 114, global_batch_idx: 107250, batch size: 31, loss[discriminator_loss=2.623, discriminator_real_loss=1.344, discriminator_fake_loss=1.279, generator_loss=29.89, generator_mel_loss=17.87, generator_kl_loss=1.709, generator_dur_loss=1.635, generator_adv_loss=2.032, generator_feat_match_loss=6.649, over 31.00 samples.], tot_loss[discriminator_loss=2.68, discriminator_real_loss=1.355, discriminator_fake_loss=1.325, generator_loss=29.04, generator_mel_loss=17.77, generator_kl_loss=1.438, generator_dur_loss=1.735, generator_adv_loss=2.013, generator_feat_match_loss=6.076, over 6510.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 17:13:40,472 INFO [train.py:919] (2/6) Start epoch 866
2024-03-15 17:15:59,882 INFO [train.py:527] (2/6) Epoch 866, batch 40, global_batch_idx: 107300, batch size: 74, loss[discriminator_loss=2.681, discriminator_real_loss=1.383, discriminator_fake_loss=1.299, generator_loss=28.24, generator_mel_loss=17.17, generator_kl_loss=1.396, generator_dur_loss=1.733, generator_adv_loss=1.922, generator_feat_match_loss=6.02, over 74.00 samples.], tot_loss[discriminator_loss=2.669, discriminator_real_loss=1.354, discriminator_fake_loss=1.315, generator_loss=28.99, generator_mel_loss=17.76, generator_kl_loss=1.403, generator_dur_loss=1.739, generator_adv_loss=2.009, generator_feat_match_loss=6.079, over 2390.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 17:18:21,277 INFO [train.py:527] (2/6) Epoch 866, batch 90, global_batch_idx: 107350, batch size: 77, loss[discriminator_loss=2.658, discriminator_real_loss=1.282, discriminator_fake_loss=1.376, generator_loss=29.29, generator_mel_loss=17.64, generator_kl_loss=1.411, generator_dur_loss=1.819, generator_adv_loss=2.046, generator_feat_match_loss=6.374, over 77.00 samples.], tot_loss[discriminator_loss=2.669, discriminator_real_loss=1.347, discriminator_fake_loss=1.322, generator_loss=29.01, generator_mel_loss=17.76, generator_kl_loss=1.423, generator_dur_loss=1.743, generator_adv_loss=2.003, generator_feat_match_loss=6.076, over 5345.00 samples.], cur_lr_g: 1.80e-04, cur_lr_d: 1.80e-04, 
2024-03-15 17:19:51,095 INFO [train.py:919] (2/6) Start epoch 867
2024-03-15 17:20:58,845 INFO [train.py:527] (2/6) Epoch 867, batch 16, global_batch_idx: 107400, batch size: 62, loss[discriminator_loss=2.621, discriminator_real_loss=1.371, discriminator_fake_loss=1.25, generator_loss=28.83, generator_mel_loss=17.94, generator_kl_loss=1.243, generator_dur_loss=1.733, generator_adv_loss=1.995, generator_feat_match_loss=5.922, over 62.00 samples.], tot_loss[discriminator_loss=2.692, discriminator_real_loss=1.369, discriminator_fake_loss=1.323, generator_loss=28.74, generator_mel_loss=17.74, generator_kl_loss=1.406, generator_dur_loss=1.738, generator_adv_loss=1.979, generator_feat_match_loss=5.88, over 958.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 17:20:58,847 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 17:21:06,797 INFO [train.py:591] (2/6) Epoch 867, validation: discriminator_loss=2.686, discriminator_real_loss=1.307, discriminator_fake_loss=1.379, generator_loss=27.67, generator_mel_loss=17.74, generator_kl_loss=1.298, generator_dur_loss=1.802, generator_adv_loss=1.89, generator_feat_match_loss=4.94, over 100.00 samples.
2024-03-15 17:21:06,798 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 17:23:24,382 INFO [train.py:527] (2/6) Epoch 867, batch 66, global_batch_idx: 107450, batch size: 61, loss[discriminator_loss=2.703, discriminator_real_loss=1.317, discriminator_fake_loss=1.387, generator_loss=29.55, generator_mel_loss=17.78, generator_kl_loss=1.598, generator_dur_loss=1.742, generator_adv_loss=2.15, generator_feat_match_loss=6.278, over 61.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.359, discriminator_fake_loss=1.325, generator_loss=28.92, generator_mel_loss=17.78, generator_kl_loss=1.433, generator_dur_loss=1.736, generator_adv_loss=1.996, generator_feat_match_loss=5.973, over 3829.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 17:25:42,111 INFO [train.py:527] (2/6) Epoch 867, batch 116, global_batch_idx: 107500, batch size: 49, loss[discriminator_loss=2.708, discriminator_real_loss=1.358, discriminator_fake_loss=1.35, generator_loss=30.2, generator_mel_loss=18.25, generator_kl_loss=1.502, generator_dur_loss=1.677, generator_adv_loss=2.153, generator_feat_match_loss=6.614, over 49.00 samples.], tot_loss[discriminator_loss=2.675, discriminator_real_loss=1.354, discriminator_fake_loss=1.321, generator_loss=29.09, generator_mel_loss=17.8, generator_kl_loss=1.437, generator_dur_loss=1.742, generator_adv_loss=2.006, generator_feat_match_loss=6.102, over 6675.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 17:26:04,941 INFO [train.py:919] (2/6) Start epoch 868
2024-03-15 17:28:24,431 INFO [train.py:527] (2/6) Epoch 868, batch 42, global_batch_idx: 107550, batch size: 48, loss[discriminator_loss=2.735, discriminator_real_loss=1.272, discriminator_fake_loss=1.463, generator_loss=29.67, generator_mel_loss=17.97, generator_kl_loss=1.391, generator_dur_loss=1.703, generator_adv_loss=2.053, generator_feat_match_loss=6.551, over 48.00 samples.], tot_loss[discriminator_loss=2.669, discriminator_real_loss=1.351, discriminator_fake_loss=1.318, generator_loss=29.01, generator_mel_loss=17.77, generator_kl_loss=1.462, generator_dur_loss=1.735, generator_adv_loss=2.005, generator_feat_match_loss=6.04, over 2213.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 17:30:41,042 INFO [train.py:527] (2/6) Epoch 868, batch 92, global_batch_idx: 107600, batch size: 83, loss[discriminator_loss=2.659, discriminator_real_loss=1.368, discriminator_fake_loss=1.291, generator_loss=29.23, generator_mel_loss=17.88, generator_kl_loss=1.327, generator_dur_loss=1.828, generator_adv_loss=2.029, generator_feat_match_loss=6.158, over 83.00 samples.], tot_loss[discriminator_loss=2.673, discriminator_real_loss=1.35, discriminator_fake_loss=1.323, generator_loss=29.1, generator_mel_loss=17.85, generator_kl_loss=1.437, generator_dur_loss=1.734, generator_adv_loss=2.01, generator_feat_match_loss=6.068, over 4978.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 17:30:41,044 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 17:30:49,715 INFO [train.py:591] (2/6) Epoch 868, validation: discriminator_loss=2.713, discriminator_real_loss=1.39, discriminator_fake_loss=1.323, generator_loss=28.26, generator_mel_loss=18.19, generator_kl_loss=1.222, generator_dur_loss=1.804, generator_adv_loss=1.966, generator_feat_match_loss=5.076, over 100.00 samples.
2024-03-15 17:30:49,716 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 17:32:19,776 INFO [train.py:919] (2/6) Start epoch 869
2024-03-15 17:33:34,649 INFO [train.py:527] (2/6) Epoch 869, batch 18, global_batch_idx: 107650, batch size: 31, loss[discriminator_loss=2.686, discriminator_real_loss=1.308, discriminator_fake_loss=1.378, generator_loss=28.39, generator_mel_loss=17.68, generator_kl_loss=1.492, generator_dur_loss=1.629, generator_adv_loss=1.928, generator_feat_match_loss=5.663, over 31.00 samples.], tot_loss[discriminator_loss=2.667, discriminator_real_loss=1.357, discriminator_fake_loss=1.311, generator_loss=29.07, generator_mel_loss=17.88, generator_kl_loss=1.432, generator_dur_loss=1.703, generator_adv_loss=1.997, generator_feat_match_loss=6.057, over 957.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 17:35:53,009 INFO [train.py:527] (2/6) Epoch 869, batch 68, global_batch_idx: 107700, batch size: 88, loss[discriminator_loss=2.651, discriminator_real_loss=1.254, discriminator_fake_loss=1.397, generator_loss=28.91, generator_mel_loss=17.84, generator_kl_loss=1.355, generator_dur_loss=1.836, generator_adv_loss=1.916, generator_feat_match_loss=5.959, over 88.00 samples.], tot_loss[discriminator_loss=2.673, discriminator_real_loss=1.355, discriminator_fake_loss=1.317, generator_loss=29.11, generator_mel_loss=17.83, generator_kl_loss=1.46, generator_dur_loss=1.719, generator_adv_loss=2.011, generator_feat_match_loss=6.089, over 3709.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 17:38:10,289 INFO [train.py:527] (2/6) Epoch 869, batch 118, global_batch_idx: 107750, batch size: 62, loss[discriminator_loss=2.63, discriminator_real_loss=1.364, discriminator_fake_loss=1.266, generator_loss=30.09, generator_mel_loss=17.91, generator_kl_loss=1.698, generator_dur_loss=1.713, generator_adv_loss=1.973, generator_feat_match_loss=6.791, over 62.00 samples.], tot_loss[discriminator_loss=2.675, discriminator_real_loss=1.357, discriminator_fake_loss=1.318, generator_loss=29.08, generator_mel_loss=17.78, generator_kl_loss=1.466, generator_dur_loss=1.732, generator_adv_loss=2.01, generator_feat_match_loss=6.097, over 6629.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 17:38:25,862 INFO [train.py:919] (2/6) Start epoch 870
2024-03-15 17:40:55,590 INFO [train.py:527] (2/6) Epoch 870, batch 44, global_batch_idx: 107800, batch size: 48, loss[discriminator_loss=2.687, discriminator_real_loss=1.331, discriminator_fake_loss=1.357, generator_loss=28.77, generator_mel_loss=17.71, generator_kl_loss=1.383, generator_dur_loss=1.666, generator_adv_loss=1.968, generator_feat_match_loss=6.035, over 48.00 samples.], tot_loss[discriminator_loss=2.668, discriminator_real_loss=1.343, discriminator_fake_loss=1.324, generator_loss=29.02, generator_mel_loss=17.8, generator_kl_loss=1.429, generator_dur_loss=1.759, generator_adv_loss=2.006, generator_feat_match_loss=6.022, over 2756.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 17:40:55,592 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 17:41:03,898 INFO [train.py:591] (2/6) Epoch 870, validation: discriminator_loss=2.776, discriminator_real_loss=1.387, discriminator_fake_loss=1.389, generator_loss=28, generator_mel_loss=18.17, generator_kl_loss=1.305, generator_dur_loss=1.815, generator_adv_loss=1.815, generator_feat_match_loss=4.895, over 100.00 samples.
2024-03-15 17:41:03,899 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 17:43:23,783 INFO [train.py:527] (2/6) Epoch 870, batch 94, global_batch_idx: 107850, batch size: 61, loss[discriminator_loss=2.651, discriminator_real_loss=1.274, discriminator_fake_loss=1.377, generator_loss=29.25, generator_mel_loss=17.91, generator_kl_loss=1.421, generator_dur_loss=1.712, generator_adv_loss=2.131, generator_feat_match_loss=6.075, over 61.00 samples.], tot_loss[discriminator_loss=2.68, discriminator_real_loss=1.355, discriminator_fake_loss=1.325, generator_loss=28.93, generator_mel_loss=17.75, generator_kl_loss=1.414, generator_dur_loss=1.757, generator_adv_loss=1.998, generator_feat_match_loss=6.011, over 5692.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 17:44:43,469 INFO [train.py:919] (2/6) Start epoch 871
2024-03-15 17:46:03,816 INFO [train.py:527] (2/6) Epoch 871, batch 20, global_batch_idx: 107900, batch size: 66, loss[discriminator_loss=2.704, discriminator_real_loss=1.346, discriminator_fake_loss=1.358, generator_loss=28.83, generator_mel_loss=17.5, generator_kl_loss=1.321, generator_dur_loss=1.76, generator_adv_loss=1.797, generator_feat_match_loss=6.457, over 66.00 samples.], tot_loss[discriminator_loss=2.673, discriminator_real_loss=1.365, discriminator_fake_loss=1.309, generator_loss=28.85, generator_mel_loss=17.65, generator_kl_loss=1.395, generator_dur_loss=1.762, generator_adv_loss=2.011, generator_feat_match_loss=6.028, over 1318.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 17:48:24,322 INFO [train.py:527] (2/6) Epoch 871, batch 70, global_batch_idx: 107950, batch size: 53, loss[discriminator_loss=2.748, discriminator_real_loss=1.402, discriminator_fake_loss=1.346, generator_loss=29.31, generator_mel_loss=18.23, generator_kl_loss=1.446, generator_dur_loss=1.656, generator_adv_loss=1.875, generator_feat_match_loss=6.099, over 53.00 samples.], tot_loss[discriminator_loss=2.681, discriminator_real_loss=1.362, discriminator_fake_loss=1.319, generator_loss=29.01, generator_mel_loss=17.75, generator_kl_loss=1.436, generator_dur_loss=1.751, generator_adv_loss=2.008, generator_feat_match_loss=6.066, over 4175.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 17:50:40,121 INFO [train.py:527] (2/6) Epoch 871, batch 120, global_batch_idx: 108000, batch size: 66, loss[discriminator_loss=2.69, discriminator_real_loss=1.31, discriminator_fake_loss=1.38, generator_loss=29.6, generator_mel_loss=17.61, generator_kl_loss=1.528, generator_dur_loss=1.741, generator_adv_loss=2.007, generator_feat_match_loss=6.71, over 66.00 samples.], tot_loss[discriminator_loss=2.679, discriminator_real_loss=1.36, discriminator_fake_loss=1.32, generator_loss=29.05, generator_mel_loss=17.78, generator_kl_loss=1.444, generator_dur_loss=1.745, generator_adv_loss=2.01, generator_feat_match_loss=6.071, over 6906.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 17:50:40,122 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 17:50:49,221 INFO [train.py:591] (2/6) Epoch 871, validation: discriminator_loss=2.693, discriminator_real_loss=1.437, discriminator_fake_loss=1.256, generator_loss=27.69, generator_mel_loss=17.98, generator_kl_loss=1.284, generator_dur_loss=1.814, generator_adv_loss=1.927, generator_feat_match_loss=4.692, over 100.00 samples.
2024-03-15 17:50:49,222 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 17:50:59,265 INFO [train.py:919] (2/6) Start epoch 872
2024-03-15 17:53:28,738 INFO [train.py:527] (2/6) Epoch 872, batch 46, global_batch_idx: 108050, batch size: 80, loss[discriminator_loss=2.705, discriminator_real_loss=1.467, discriminator_fake_loss=1.239, generator_loss=30.28, generator_mel_loss=18.04, generator_kl_loss=1.516, generator_dur_loss=1.781, generator_adv_loss=1.908, generator_feat_match_loss=7.034, over 80.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.37, discriminator_fake_loss=1.313, generator_loss=29.06, generator_mel_loss=17.82, generator_kl_loss=1.443, generator_dur_loss=1.746, generator_adv_loss=2.011, generator_feat_match_loss=6.039, over 2642.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 17:55:49,377 INFO [train.py:527] (2/6) Epoch 872, batch 96, global_batch_idx: 108100, batch size: 53, loss[discriminator_loss=2.64, discriminator_real_loss=1.36, discriminator_fake_loss=1.28, generator_loss=29.34, generator_mel_loss=17.63, generator_kl_loss=1.666, generator_dur_loss=1.722, generator_adv_loss=1.991, generator_feat_match_loss=6.337, over 53.00 samples.], tot_loss[discriminator_loss=2.679, discriminator_real_loss=1.361, discriminator_fake_loss=1.318, generator_loss=29.01, generator_mel_loss=17.78, generator_kl_loss=1.451, generator_dur_loss=1.745, generator_adv_loss=1.999, generator_feat_match_loss=6.043, over 5415.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 17:57:05,190 INFO [train.py:919] (2/6) Start epoch 873
2024-03-15 17:58:29,763 INFO [train.py:527] (2/6) Epoch 873, batch 22, global_batch_idx: 108150, batch size: 55, loss[discriminator_loss=2.661, discriminator_real_loss=1.392, discriminator_fake_loss=1.269, generator_loss=28.74, generator_mel_loss=17.78, generator_kl_loss=1.401, generator_dur_loss=1.679, generator_adv_loss=2.104, generator_feat_match_loss=5.777, over 55.00 samples.], tot_loss[discriminator_loss=2.678, discriminator_real_loss=1.354, discriminator_fake_loss=1.324, generator_loss=29.27, generator_mel_loss=17.78, generator_kl_loss=1.468, generator_dur_loss=1.74, generator_adv_loss=2.077, generator_feat_match_loss=6.207, over 1415.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 18:00:46,063 INFO [train.py:527] (2/6) Epoch 873, batch 72, global_batch_idx: 108200, batch size: 31, loss[discriminator_loss=2.741, discriminator_real_loss=1.467, discriminator_fake_loss=1.275, generator_loss=28.71, generator_mel_loss=17.61, generator_kl_loss=1.609, generator_dur_loss=1.558, generator_adv_loss=2.01, generator_feat_match_loss=5.92, over 31.00 samples.], tot_loss[discriminator_loss=2.67, discriminator_real_loss=1.35, discriminator_fake_loss=1.32, generator_loss=29.17, generator_mel_loss=17.77, generator_kl_loss=1.453, generator_dur_loss=1.743, generator_adv_loss=2.039, generator_feat_match_loss=6.171, over 4251.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 18:00:46,064 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 18:00:54,110 INFO [train.py:591] (2/6) Epoch 873, validation: discriminator_loss=2.741, discriminator_real_loss=1.426, discriminator_fake_loss=1.315, generator_loss=27.49, generator_mel_loss=17.82, generator_kl_loss=1.225, generator_dur_loss=1.815, generator_adv_loss=1.95, generator_feat_match_loss=4.677, over 100.00 samples.
2024-03-15 18:00:54,111 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 18:03:12,109 INFO [train.py:527] (2/6) Epoch 873, batch 122, global_batch_idx: 108250, batch size: 25, loss[discriminator_loss=2.677, discriminator_real_loss=1.411, discriminator_fake_loss=1.266, generator_loss=29.79, generator_mel_loss=18.08, generator_kl_loss=1.81, generator_dur_loss=1.526, generator_adv_loss=2.09, generator_feat_match_loss=6.288, over 25.00 samples.], tot_loss[discriminator_loss=2.672, discriminator_real_loss=1.354, discriminator_fake_loss=1.318, generator_loss=29.12, generator_mel_loss=17.77, generator_kl_loss=1.447, generator_dur_loss=1.74, generator_adv_loss=2.026, generator_feat_match_loss=6.141, over 7058.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 18:03:16,777 INFO [train.py:919] (2/6) Start epoch 874
2024-03-15 18:05:52,495 INFO [train.py:527] (2/6) Epoch 874, batch 48, global_batch_idx: 108300, batch size: 36, loss[discriminator_loss=2.693, discriminator_real_loss=1.329, discriminator_fake_loss=1.364, generator_loss=29.44, generator_mel_loss=17.8, generator_kl_loss=1.432, generator_dur_loss=1.657, generator_adv_loss=2.087, generator_feat_match_loss=6.465, over 36.00 samples.], tot_loss[discriminator_loss=2.672, discriminator_real_loss=1.349, discriminator_fake_loss=1.323, generator_loss=29.08, generator_mel_loss=17.81, generator_kl_loss=1.449, generator_dur_loss=1.739, generator_adv_loss=2.001, generator_feat_match_loss=6.084, over 2810.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 18:08:12,157 INFO [train.py:527] (2/6) Epoch 874, batch 98, global_batch_idx: 108350, batch size: 62, loss[discriminator_loss=2.697, discriminator_real_loss=1.265, discriminator_fake_loss=1.432, generator_loss=29.62, generator_mel_loss=17.75, generator_kl_loss=1.467, generator_dur_loss=1.721, generator_adv_loss=2.226, generator_feat_match_loss=6.46, over 62.00 samples.], tot_loss[discriminator_loss=2.678, discriminator_real_loss=1.35, discriminator_fake_loss=1.328, generator_loss=29.05, generator_mel_loss=17.76, generator_kl_loss=1.451, generator_dur_loss=1.742, generator_adv_loss=2.001, generator_feat_match_loss=6.098, over 5623.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 18:09:22,336 INFO [train.py:919] (2/6) Start epoch 875
2024-03-15 18:10:53,811 INFO [train.py:527] (2/6) Epoch 875, batch 24, global_batch_idx: 108400, batch size: 83, loss[discriminator_loss=2.65, discriminator_real_loss=1.326, discriminator_fake_loss=1.324, generator_loss=28.36, generator_mel_loss=17.76, generator_kl_loss=1.354, generator_dur_loss=1.841, generator_adv_loss=1.944, generator_feat_match_loss=5.464, over 83.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.351, discriminator_fake_loss=1.325, generator_loss=28.93, generator_mel_loss=17.87, generator_kl_loss=1.39, generator_dur_loss=1.746, generator_adv_loss=2.013, generator_feat_match_loss=5.91, over 1432.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 18:10:53,812 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 18:11:01,727 INFO [train.py:591] (2/6) Epoch 875, validation: discriminator_loss=2.644, discriminator_real_loss=1.344, discriminator_fake_loss=1.3, generator_loss=27.54, generator_mel_loss=17.71, generator_kl_loss=1.262, generator_dur_loss=1.802, generator_adv_loss=1.912, generator_feat_match_loss=4.86, over 100.00 samples.
2024-03-15 18:11:01,728 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 18:13:20,860 INFO [train.py:527] (2/6) Epoch 875, batch 74, global_batch_idx: 108450, batch size: 31, loss[discriminator_loss=2.708, discriminator_real_loss=1.289, discriminator_fake_loss=1.419, generator_loss=29.49, generator_mel_loss=18.16, generator_kl_loss=1.495, generator_dur_loss=1.606, generator_adv_loss=1.932, generator_feat_match_loss=6.3, over 31.00 samples.], tot_loss[discriminator_loss=2.674, discriminator_real_loss=1.349, discriminator_fake_loss=1.325, generator_loss=29.17, generator_mel_loss=17.88, generator_kl_loss=1.433, generator_dur_loss=1.738, generator_adv_loss=2.009, generator_feat_match_loss=6.105, over 4286.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 18:15:38,566 INFO [train.py:919] (2/6) Start epoch 876
2024-03-15 18:16:02,417 INFO [train.py:527] (2/6) Epoch 876, batch 0, global_batch_idx: 108500, batch size: 40, loss[discriminator_loss=2.652, discriminator_real_loss=1.379, discriminator_fake_loss=1.273, generator_loss=29.18, generator_mel_loss=18.21, generator_kl_loss=1.538, generator_dur_loss=1.685, generator_adv_loss=1.96, generator_feat_match_loss=5.784, over 40.00 samples.], tot_loss[discriminator_loss=2.652, discriminator_real_loss=1.379, discriminator_fake_loss=1.273, generator_loss=29.18, generator_mel_loss=18.21, generator_kl_loss=1.538, generator_dur_loss=1.685, generator_adv_loss=1.96, generator_feat_match_loss=5.784, over 40.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 18:18:19,655 INFO [train.py:527] (2/6) Epoch 876, batch 50, global_batch_idx: 108550, batch size: 53, loss[discriminator_loss=2.701, discriminator_real_loss=1.331, discriminator_fake_loss=1.37, generator_loss=28.28, generator_mel_loss=17.88, generator_kl_loss=1.503, generator_dur_loss=1.672, generator_adv_loss=1.968, generator_feat_match_loss=5.256, over 53.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.361, discriminator_fake_loss=1.324, generator_loss=29.18, generator_mel_loss=17.83, generator_kl_loss=1.447, generator_dur_loss=1.729, generator_adv_loss=2.025, generator_feat_match_loss=6.15, over 2866.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 18:20:40,464 INFO [train.py:527] (2/6) Epoch 876, batch 100, global_batch_idx: 108600, batch size: 39, loss[discriminator_loss=2.688, discriminator_real_loss=1.448, discriminator_fake_loss=1.24, generator_loss=29.27, generator_mel_loss=17.54, generator_kl_loss=1.494, generator_dur_loss=1.65, generator_adv_loss=1.971, generator_feat_match_loss=6.614, over 39.00 samples.], tot_loss[discriminator_loss=2.683, discriminator_real_loss=1.362, discriminator_fake_loss=1.321, generator_loss=29.12, generator_mel_loss=17.79, generator_kl_loss=1.42, generator_dur_loss=1.737, generator_adv_loss=2.028, generator_feat_match_loss=6.144, over 5906.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 18:20:40,465 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 18:20:49,299 INFO [train.py:591] (2/6) Epoch 876, validation: discriminator_loss=2.681, discriminator_real_loss=1.37, discriminator_fake_loss=1.31, generator_loss=27.59, generator_mel_loss=17.93, generator_kl_loss=1.287, generator_dur_loss=1.799, generator_adv_loss=1.908, generator_feat_match_loss=4.673, over 100.00 samples.
2024-03-15 18:20:49,300 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 18:21:52,369 INFO [train.py:919] (2/6) Start epoch 877
2024-03-15 18:23:24,970 INFO [train.py:527] (2/6) Epoch 877, batch 26, global_batch_idx: 108650, batch size: 68, loss[discriminator_loss=2.703, discriminator_real_loss=1.306, discriminator_fake_loss=1.397, generator_loss=28.71, generator_mel_loss=17.81, generator_kl_loss=1.329, generator_dur_loss=1.791, generator_adv_loss=2.016, generator_feat_match_loss=5.76, over 68.00 samples.], tot_loss[discriminator_loss=2.697, discriminator_real_loss=1.368, discriminator_fake_loss=1.329, generator_loss=29.02, generator_mel_loss=17.82, generator_kl_loss=1.415, generator_dur_loss=1.752, generator_adv_loss=1.982, generator_feat_match_loss=6.056, over 1614.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 18:25:44,626 INFO [train.py:527] (2/6) Epoch 877, batch 76, global_batch_idx: 108700, batch size: 68, loss[discriminator_loss=2.665, discriminator_real_loss=1.378, discriminator_fake_loss=1.287, generator_loss=28.83, generator_mel_loss=17.77, generator_kl_loss=1.233, generator_dur_loss=1.755, generator_adv_loss=2.004, generator_feat_match_loss=6.07, over 68.00 samples.], tot_loss[discriminator_loss=2.675, discriminator_real_loss=1.354, discriminator_fake_loss=1.321, generator_loss=29.04, generator_mel_loss=17.8, generator_kl_loss=1.401, generator_dur_loss=1.749, generator_adv_loss=2.003, generator_feat_match_loss=6.087, over 4674.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 18:27:55,776 INFO [train.py:919] (2/6) Start epoch 878
2024-03-15 18:28:20,873 INFO [train.py:527] (2/6) Epoch 878, batch 2, global_batch_idx: 108750, batch size: 72, loss[discriminator_loss=2.674, discriminator_real_loss=1.407, discriminator_fake_loss=1.267, generator_loss=28.72, generator_mel_loss=17.36, generator_kl_loss=1.419, generator_dur_loss=1.776, generator_adv_loss=1.936, generator_feat_match_loss=6.228, over 72.00 samples.], tot_loss[discriminator_loss=2.699, discriminator_real_loss=1.405, discriminator_fake_loss=1.294, generator_loss=28.47, generator_mel_loss=17.54, generator_kl_loss=1.444, generator_dur_loss=1.729, generator_adv_loss=1.976, generator_feat_match_loss=5.785, over 167.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 18:30:42,787 INFO [train.py:527] (2/6) Epoch 878, batch 52, global_batch_idx: 108800, batch size: 48, loss[discriminator_loss=2.654, discriminator_real_loss=1.38, discriminator_fake_loss=1.274, generator_loss=29.2, generator_mel_loss=17.6, generator_kl_loss=1.585, generator_dur_loss=1.652, generator_adv_loss=2.16, generator_feat_match_loss=6.197, over 48.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.36, discriminator_fake_loss=1.324, generator_loss=29.09, generator_mel_loss=17.71, generator_kl_loss=1.47, generator_dur_loss=1.723, generator_adv_loss=2.015, generator_feat_match_loss=6.166, over 2849.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 18:30:42,788 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 18:30:51,152 INFO [train.py:591] (2/6) Epoch 878, validation: discriminator_loss=2.73, discriminator_real_loss=1.464, discriminator_fake_loss=1.267, generator_loss=27.14, generator_mel_loss=17.6, generator_kl_loss=1.343, generator_dur_loss=1.804, generator_adv_loss=2.048, generator_feat_match_loss=4.35, over 100.00 samples.
2024-03-15 18:30:51,153 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 18:33:07,825 INFO [train.py:527] (2/6) Epoch 878, batch 102, global_batch_idx: 108850, batch size: 72, loss[discriminator_loss=2.614, discriminator_real_loss=1.328, discriminator_fake_loss=1.286, generator_loss=29.41, generator_mel_loss=17.64, generator_kl_loss=1.302, generator_dur_loss=1.774, generator_adv_loss=2.155, generator_feat_match_loss=6.542, over 72.00 samples.], tot_loss[discriminator_loss=2.677, discriminator_real_loss=1.352, discriminator_fake_loss=1.325, generator_loss=29.14, generator_mel_loss=17.74, generator_kl_loss=1.445, generator_dur_loss=1.728, generator_adv_loss=2.025, generator_feat_match_loss=6.204, over 5744.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 18:34:08,410 INFO [train.py:919] (2/6) Start epoch 879
2024-03-15 18:35:51,406 INFO [train.py:527] (2/6) Epoch 879, batch 28, global_batch_idx: 108900, batch size: 36, loss[discriminator_loss=2.65, discriminator_real_loss=1.367, discriminator_fake_loss=1.283, generator_loss=29.46, generator_mel_loss=17.56, generator_kl_loss=1.463, generator_dur_loss=1.674, generator_adv_loss=2.105, generator_feat_match_loss=6.666, over 36.00 samples.], tot_loss[discriminator_loss=2.681, discriminator_real_loss=1.357, discriminator_fake_loss=1.324, generator_loss=29.13, generator_mel_loss=17.83, generator_kl_loss=1.397, generator_dur_loss=1.749, generator_adv_loss=1.996, generator_feat_match_loss=6.155, over 1659.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 18:38:13,268 INFO [train.py:527] (2/6) Epoch 879, batch 78, global_batch_idx: 108950, batch size: 74, loss[discriminator_loss=2.647, discriminator_real_loss=1.334, discriminator_fake_loss=1.313, generator_loss=29.45, generator_mel_loss=17.8, generator_kl_loss=1.28, generator_dur_loss=1.802, generator_adv_loss=1.993, generator_feat_match_loss=6.576, over 74.00 samples.], tot_loss[discriminator_loss=2.677, discriminator_real_loss=1.353, discriminator_fake_loss=1.324, generator_loss=29.1, generator_mel_loss=17.82, generator_kl_loss=1.42, generator_dur_loss=1.751, generator_adv_loss=1.996, generator_feat_match_loss=6.117, over 4684.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 18:40:18,545 INFO [train.py:919] (2/6) Start epoch 880
2024-03-15 18:40:52,060 INFO [train.py:527] (2/6) Epoch 880, batch 4, global_batch_idx: 109000, batch size: 47, loss[discriminator_loss=2.726, discriminator_real_loss=1.351, discriminator_fake_loss=1.375, generator_loss=28.98, generator_mel_loss=17.66, generator_kl_loss=1.514, generator_dur_loss=1.637, generator_adv_loss=2.16, generator_feat_match_loss=6.008, over 47.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.339, discriminator_fake_loss=1.337, generator_loss=29.43, generator_mel_loss=17.87, generator_kl_loss=1.447, generator_dur_loss=1.714, generator_adv_loss=2.01, generator_feat_match_loss=6.393, over 265.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 18:40:52,063 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 18:40:59,968 INFO [train.py:591] (2/6) Epoch 880, validation: discriminator_loss=2.772, discriminator_real_loss=1.501, discriminator_fake_loss=1.271, generator_loss=27.81, generator_mel_loss=17.71, generator_kl_loss=1.226, generator_dur_loss=1.799, generator_adv_loss=2.008, generator_feat_match_loss=5.066, over 100.00 samples.
2024-03-15 18:40:59,970 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 18:43:19,239 INFO [train.py:527] (2/6) Epoch 880, batch 54, global_batch_idx: 109050, batch size: 64, loss[discriminator_loss=2.647, discriminator_real_loss=1.367, discriminator_fake_loss=1.279, generator_loss=28.77, generator_mel_loss=17.52, generator_kl_loss=1.301, generator_dur_loss=1.776, generator_adv_loss=1.935, generator_feat_match_loss=6.243, over 64.00 samples.], tot_loss[discriminator_loss=2.678, discriminator_real_loss=1.357, discriminator_fake_loss=1.322, generator_loss=29.05, generator_mel_loss=17.79, generator_kl_loss=1.421, generator_dur_loss=1.733, generator_adv_loss=2.007, generator_feat_match_loss=6.097, over 3067.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 18:45:38,306 INFO [train.py:527] (2/6) Epoch 880, batch 104, global_batch_idx: 109100, batch size: 48, loss[discriminator_loss=2.684, discriminator_real_loss=1.33, discriminator_fake_loss=1.354, generator_loss=28.6, generator_mel_loss=17.52, generator_kl_loss=1.56, generator_dur_loss=1.653, generator_adv_loss=1.958, generator_feat_match_loss=5.915, over 48.00 samples.], tot_loss[discriminator_loss=2.669, discriminator_real_loss=1.352, discriminator_fake_loss=1.318, generator_loss=29.16, generator_mel_loss=17.81, generator_kl_loss=1.435, generator_dur_loss=1.733, generator_adv_loss=2.016, generator_feat_match_loss=6.168, over 5839.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 18:46:32,279 INFO [train.py:919] (2/6) Start epoch 881
2024-03-15 18:48:21,165 INFO [train.py:527] (2/6) Epoch 881, batch 30, global_batch_idx: 109150, batch size: 15, loss[discriminator_loss=2.837, discriminator_real_loss=1.325, discriminator_fake_loss=1.513, generator_loss=29.76, generator_mel_loss=18.01, generator_kl_loss=1.896, generator_dur_loss=1.64, generator_adv_loss=1.845, generator_feat_match_loss=6.37, over 15.00 samples.], tot_loss[discriminator_loss=2.686, discriminator_real_loss=1.363, discriminator_fake_loss=1.323, generator_loss=28.88, generator_mel_loss=17.72, generator_kl_loss=1.399, generator_dur_loss=1.772, generator_adv_loss=2.007, generator_feat_match_loss=5.989, over 1989.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 18:50:40,775 INFO [train.py:527] (2/6) Epoch 881, batch 80, global_batch_idx: 109200, batch size: 64, loss[discriminator_loss=2.697, discriminator_real_loss=1.351, discriminator_fake_loss=1.346, generator_loss=28.3, generator_mel_loss=17.41, generator_kl_loss=1.549, generator_dur_loss=1.753, generator_adv_loss=1.874, generator_feat_match_loss=5.713, over 64.00 samples.], tot_loss[discriminator_loss=2.683, discriminator_real_loss=1.355, discriminator_fake_loss=1.328, generator_loss=28.97, generator_mel_loss=17.78, generator_kl_loss=1.427, generator_dur_loss=1.747, generator_adv_loss=1.999, generator_feat_match_loss=6.023, over 4720.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 18:50:40,777 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 18:50:49,494 INFO [train.py:591] (2/6) Epoch 881, validation: discriminator_loss=2.706, discriminator_real_loss=1.309, discriminator_fake_loss=1.397, generator_loss=27.62, generator_mel_loss=18.22, generator_kl_loss=1.217, generator_dur_loss=1.809, generator_adv_loss=1.813, generator_feat_match_loss=4.559, over 100.00 samples.
2024-03-15 18:50:49,495 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 18:52:50,286 INFO [train.py:919] (2/6) Start epoch 882
2024-03-15 18:53:31,115 INFO [train.py:527] (2/6) Epoch 882, batch 6, global_batch_idx: 109250, batch size: 31, loss[discriminator_loss=2.662, discriminator_real_loss=1.293, discriminator_fake_loss=1.369, generator_loss=30.73, generator_mel_loss=18.43, generator_kl_loss=1.712, generator_dur_loss=1.598, generator_adv_loss=2.099, generator_feat_match_loss=6.892, over 31.00 samples.], tot_loss[discriminator_loss=2.688, discriminator_real_loss=1.358, discriminator_fake_loss=1.33, generator_loss=29.21, generator_mel_loss=17.83, generator_kl_loss=1.432, generator_dur_loss=1.742, generator_adv_loss=2.039, generator_feat_match_loss=6.169, over 407.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 18:55:50,504 INFO [train.py:527] (2/6) Epoch 882, batch 56, global_batch_idx: 109300, batch size: 72, loss[discriminator_loss=2.687, discriminator_real_loss=1.411, discriminator_fake_loss=1.276, generator_loss=28.6, generator_mel_loss=17.43, generator_kl_loss=1.218, generator_dur_loss=1.819, generator_adv_loss=2.06, generator_feat_match_loss=6.074, over 72.00 samples.], tot_loss[discriminator_loss=2.663, discriminator_real_loss=1.347, discriminator_fake_loss=1.316, generator_loss=29.09, generator_mel_loss=17.73, generator_kl_loss=1.429, generator_dur_loss=1.745, generator_adv_loss=2.025, generator_feat_match_loss=6.167, over 3230.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 18:58:09,377 INFO [train.py:527] (2/6) Epoch 882, batch 106, global_batch_idx: 109350, batch size: 44, loss[discriminator_loss=2.679, discriminator_real_loss=1.341, discriminator_fake_loss=1.338, generator_loss=27.72, generator_mel_loss=17.5, generator_kl_loss=1.457, generator_dur_loss=1.703, generator_adv_loss=1.938, generator_feat_match_loss=5.118, over 44.00 samples.], tot_loss[discriminator_loss=2.67, discriminator_real_loss=1.351, discriminator_fake_loss=1.319, generator_loss=29.07, generator_mel_loss=17.74, generator_kl_loss=1.438, generator_dur_loss=1.731, generator_adv_loss=2.012, generator_feat_match_loss=6.154, over 5987.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 18:58:57,714 INFO [train.py:919] (2/6) Start epoch 883
2024-03-15 19:00:51,708 INFO [train.py:527] (2/6) Epoch 883, batch 32, global_batch_idx: 109400, batch size: 55, loss[discriminator_loss=2.694, discriminator_real_loss=1.326, discriminator_fake_loss=1.368, generator_loss=29.13, generator_mel_loss=17.93, generator_kl_loss=1.269, generator_dur_loss=1.712, generator_adv_loss=2.115, generator_feat_match_loss=6.108, over 55.00 samples.], tot_loss[discriminator_loss=2.66, discriminator_real_loss=1.349, discriminator_fake_loss=1.311, generator_loss=29.11, generator_mel_loss=17.8, generator_kl_loss=1.428, generator_dur_loss=1.718, generator_adv_loss=2.04, generator_feat_match_loss=6.124, over 1923.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 19:00:51,709 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 19:00:59,683 INFO [train.py:591] (2/6) Epoch 883, validation: discriminator_loss=2.722, discriminator_real_loss=1.435, discriminator_fake_loss=1.287, generator_loss=28.51, generator_mel_loss=17.87, generator_kl_loss=1.288, generator_dur_loss=1.781, generator_adv_loss=2.111, generator_feat_match_loss=5.462, over 100.00 samples.
2024-03-15 19:00:59,684 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 19:03:19,541 INFO [train.py:527] (2/6) Epoch 883, batch 82, global_batch_idx: 109450, batch size: 45, loss[discriminator_loss=2.687, discriminator_real_loss=1.251, discriminator_fake_loss=1.437, generator_loss=28.99, generator_mel_loss=17.61, generator_kl_loss=1.478, generator_dur_loss=1.638, generator_adv_loss=1.981, generator_feat_match_loss=6.285, over 45.00 samples.], tot_loss[discriminator_loss=2.663, discriminator_real_loss=1.35, discriminator_fake_loss=1.313, generator_loss=29.05, generator_mel_loss=17.78, generator_kl_loss=1.421, generator_dur_loss=1.716, generator_adv_loss=2.021, generator_feat_match_loss=6.114, over 4749.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 19:05:12,753 INFO [train.py:919] (2/6) Start epoch 884
2024-03-15 19:05:58,835 INFO [train.py:527] (2/6) Epoch 884, batch 8, global_batch_idx: 109500, batch size: 39, loss[discriminator_loss=2.634, discriminator_real_loss=1.335, discriminator_fake_loss=1.298, generator_loss=29.88, generator_mel_loss=17.45, generator_kl_loss=1.594, generator_dur_loss=1.663, generator_adv_loss=2.181, generator_feat_match_loss=6.994, over 39.00 samples.], tot_loss[discriminator_loss=2.667, discriminator_real_loss=1.347, discriminator_fake_loss=1.32, generator_loss=28.89, generator_mel_loss=17.71, generator_kl_loss=1.569, generator_dur_loss=1.678, generator_adv_loss=1.991, generator_feat_match_loss=5.94, over 441.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 19:08:17,071 INFO [train.py:527] (2/6) Epoch 884, batch 58, global_batch_idx: 109550, batch size: 13, loss[discriminator_loss=2.756, discriminator_real_loss=1.431, discriminator_fake_loss=1.325, generator_loss=30.07, generator_mel_loss=18.65, generator_kl_loss=1.753, generator_dur_loss=1.63, generator_adv_loss=1.955, generator_feat_match_loss=6.084, over 13.00 samples.], tot_loss[discriminator_loss=2.664, discriminator_real_loss=1.346, discriminator_fake_loss=1.318, generator_loss=28.94, generator_mel_loss=17.72, generator_kl_loss=1.453, generator_dur_loss=1.717, generator_adv_loss=2.015, generator_feat_match_loss=6.03, over 3093.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 19:10:35,929 INFO [train.py:527] (2/6) Epoch 884, batch 108, global_batch_idx: 109600, batch size: 68, loss[discriminator_loss=2.706, discriminator_real_loss=1.307, discriminator_fake_loss=1.4, generator_loss=28.49, generator_mel_loss=17.54, generator_kl_loss=1.403, generator_dur_loss=1.739, generator_adv_loss=2.034, generator_feat_match_loss=5.772, over 68.00 samples.], tot_loss[discriminator_loss=2.67, discriminator_real_loss=1.348, discriminator_fake_loss=1.321, generator_loss=29.05, generator_mel_loss=17.76, generator_kl_loss=1.444, generator_dur_loss=1.73, generator_adv_loss=2.01, generator_feat_match_loss=6.112, over 5991.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 19:10:35,931 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 19:10:44,693 INFO [train.py:591] (2/6) Epoch 884, validation: discriminator_loss=2.719, discriminator_real_loss=1.486, discriminator_fake_loss=1.233, generator_loss=28.43, generator_mel_loss=18.2, generator_kl_loss=1.247, generator_dur_loss=1.776, generator_adv_loss=2.09, generator_feat_match_loss=5.123, over 100.00 samples.
2024-03-15 19:10:44,693 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 19:11:27,514 INFO [train.py:919] (2/6) Start epoch 885
2024-03-15 19:13:25,316 INFO [train.py:527] (2/6) Epoch 885, batch 34, global_batch_idx: 109650, batch size: 70, loss[discriminator_loss=2.736, discriminator_real_loss=1.416, discriminator_fake_loss=1.319, generator_loss=28.76, generator_mel_loss=17.62, generator_kl_loss=1.407, generator_dur_loss=1.74, generator_adv_loss=1.898, generator_feat_match_loss=6.101, over 70.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.362, discriminator_fake_loss=1.323, generator_loss=29.14, generator_mel_loss=17.83, generator_kl_loss=1.434, generator_dur_loss=1.731, generator_adv_loss=2.013, generator_feat_match_loss=6.134, over 2011.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 19:15:43,308 INFO [train.py:527] (2/6) Epoch 885, batch 84, global_batch_idx: 109700, batch size: 47, loss[discriminator_loss=2.705, discriminator_real_loss=1.361, discriminator_fake_loss=1.344, generator_loss=29.51, generator_mel_loss=17.92, generator_kl_loss=1.582, generator_dur_loss=1.64, generator_adv_loss=2.036, generator_feat_match_loss=6.338, over 47.00 samples.], tot_loss[discriminator_loss=2.691, discriminator_real_loss=1.361, discriminator_fake_loss=1.33, generator_loss=29.09, generator_mel_loss=17.78, generator_kl_loss=1.448, generator_dur_loss=1.738, generator_adv_loss=2.013, generator_feat_match_loss=6.11, over 4935.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 19:17:31,606 INFO [train.py:919] (2/6) Start epoch 886
2024-03-15 19:18:22,965 INFO [train.py:527] (2/6) Epoch 886, batch 10, global_batch_idx: 109750, batch size: 83, loss[discriminator_loss=2.715, discriminator_real_loss=1.397, discriminator_fake_loss=1.318, generator_loss=28.99, generator_mel_loss=17.77, generator_kl_loss=1.317, generator_dur_loss=1.825, generator_adv_loss=1.933, generator_feat_match_loss=6.147, over 83.00 samples.], tot_loss[discriminator_loss=2.683, discriminator_real_loss=1.372, discriminator_fake_loss=1.311, generator_loss=29.15, generator_mel_loss=17.77, generator_kl_loss=1.456, generator_dur_loss=1.753, generator_adv_loss=2.023, generator_feat_match_loss=6.145, over 657.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 19:20:43,204 INFO [train.py:527] (2/6) Epoch 886, batch 60, global_batch_idx: 109800, batch size: 96, loss[discriminator_loss=2.67, discriminator_real_loss=1.343, discriminator_fake_loss=1.328, generator_loss=28.6, generator_mel_loss=17.61, generator_kl_loss=1.409, generator_dur_loss=1.88, generator_adv_loss=1.981, generator_feat_match_loss=5.719, over 96.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.357, discriminator_fake_loss=1.327, generator_loss=29.09, generator_mel_loss=17.74, generator_kl_loss=1.461, generator_dur_loss=1.74, generator_adv_loss=2.007, generator_feat_match_loss=6.14, over 3333.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 19:20:43,205 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 19:20:51,344 INFO [train.py:591] (2/6) Epoch 886, validation: discriminator_loss=2.7, discriminator_real_loss=1.398, discriminator_fake_loss=1.302, generator_loss=27.26, generator_mel_loss=17.68, generator_kl_loss=1.296, generator_dur_loss=1.808, generator_adv_loss=1.922, generator_feat_match_loss=4.554, over 100.00 samples.
2024-03-15 19:20:51,345 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 19:23:09,750 INFO [train.py:527] (2/6) Epoch 886, batch 110, global_batch_idx: 109850, batch size: 70, loss[discriminator_loss=2.686, discriminator_real_loss=1.362, discriminator_fake_loss=1.324, generator_loss=28.37, generator_mel_loss=17.34, generator_kl_loss=1.384, generator_dur_loss=1.82, generator_adv_loss=2.011, generator_feat_match_loss=5.818, over 70.00 samples.], tot_loss[discriminator_loss=2.681, discriminator_real_loss=1.359, discriminator_fake_loss=1.322, generator_loss=29.04, generator_mel_loss=17.72, generator_kl_loss=1.445, generator_dur_loss=1.741, generator_adv_loss=2.01, generator_feat_match_loss=6.125, over 6113.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 19:23:43,489 INFO [train.py:919] (2/6) Start epoch 887
2024-03-15 19:25:52,473 INFO [train.py:527] (2/6) Epoch 887, batch 36, global_batch_idx: 109900, batch size: 83, loss[discriminator_loss=2.644, discriminator_real_loss=1.332, discriminator_fake_loss=1.312, generator_loss=30.12, generator_mel_loss=18.21, generator_kl_loss=1.202, generator_dur_loss=1.857, generator_adv_loss=2.127, generator_feat_match_loss=6.723, over 83.00 samples.], tot_loss[discriminator_loss=2.674, discriminator_real_loss=1.345, discriminator_fake_loss=1.329, generator_loss=29.24, generator_mel_loss=17.81, generator_kl_loss=1.414, generator_dur_loss=1.757, generator_adv_loss=2.017, generator_feat_match_loss=6.241, over 2170.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 19:28:10,920 INFO [train.py:527] (2/6) Epoch 887, batch 86, global_batch_idx: 109950, batch size: 45, loss[discriminator_loss=2.731, discriminator_real_loss=1.308, discriminator_fake_loss=1.423, generator_loss=28.57, generator_mel_loss=17.18, generator_kl_loss=1.532, generator_dur_loss=1.669, generator_adv_loss=2.111, generator_feat_match_loss=6.076, over 45.00 samples.], tot_loss[discriminator_loss=2.675, discriminator_real_loss=1.354, discriminator_fake_loss=1.32, generator_loss=29.13, generator_mel_loss=17.8, generator_kl_loss=1.427, generator_dur_loss=1.74, generator_adv_loss=2.011, generator_feat_match_loss=6.149, over 4850.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 19:29:50,634 INFO [train.py:919] (2/6) Start epoch 888
2024-03-15 19:30:46,964 INFO [train.py:527] (2/6) Epoch 888, batch 12, global_batch_idx: 110000, batch size: 55, loss[discriminator_loss=2.773, discriminator_real_loss=1.387, discriminator_fake_loss=1.386, generator_loss=29.44, generator_mel_loss=18.17, generator_kl_loss=1.572, generator_dur_loss=1.707, generator_adv_loss=1.874, generator_feat_match_loss=6.123, over 55.00 samples.], tot_loss[discriminator_loss=2.67, discriminator_real_loss=1.349, discriminator_fake_loss=1.321, generator_loss=29.08, generator_mel_loss=17.81, generator_kl_loss=1.374, generator_dur_loss=1.762, generator_adv_loss=2.019, generator_feat_match_loss=6.12, over 829.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 19:30:46,967 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 19:30:54,875 INFO [train.py:591] (2/6) Epoch 888, validation: discriminator_loss=2.734, discriminator_real_loss=1.375, discriminator_fake_loss=1.358, generator_loss=27.63, generator_mel_loss=18.08, generator_kl_loss=1.163, generator_dur_loss=1.791, generator_adv_loss=1.857, generator_feat_match_loss=4.732, over 100.00 samples.
2024-03-15 19:30:54,876 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 19:33:14,043 INFO [train.py:527] (2/6) Epoch 888, batch 62, global_batch_idx: 110050, batch size: 47, loss[discriminator_loss=2.65, discriminator_real_loss=1.289, discriminator_fake_loss=1.361, generator_loss=29.04, generator_mel_loss=17.69, generator_kl_loss=1.591, generator_dur_loss=1.685, generator_adv_loss=2.085, generator_feat_match_loss=5.987, over 47.00 samples.], tot_loss[discriminator_loss=2.682, discriminator_real_loss=1.356, discriminator_fake_loss=1.326, generator_loss=29.02, generator_mel_loss=17.79, generator_kl_loss=1.445, generator_dur_loss=1.734, generator_adv_loss=2.008, generator_feat_match_loss=6.036, over 3550.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 19:35:33,591 INFO [train.py:527] (2/6) Epoch 888, batch 112, global_batch_idx: 110100, batch size: 59, loss[discriminator_loss=2.634, discriminator_real_loss=1.295, discriminator_fake_loss=1.34, generator_loss=29.39, generator_mel_loss=18.23, generator_kl_loss=1.443, generator_dur_loss=1.737, generator_adv_loss=1.994, generator_feat_match_loss=5.99, over 59.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.36, discriminator_fake_loss=1.326, generator_loss=29.09, generator_mel_loss=17.79, generator_kl_loss=1.433, generator_dur_loss=1.745, generator_adv_loss=2.008, generator_feat_match_loss=6.108, over 6601.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 19:36:04,790 INFO [train.py:919] (2/6) Start epoch 889
2024-03-15 19:38:16,334 INFO [train.py:527] (2/6) Epoch 889, batch 38, global_batch_idx: 110150, batch size: 39, loss[discriminator_loss=2.607, discriminator_real_loss=1.287, discriminator_fake_loss=1.32, generator_loss=28.99, generator_mel_loss=17.43, generator_kl_loss=1.603, generator_dur_loss=1.619, generator_adv_loss=2.104, generator_feat_match_loss=6.237, over 39.00 samples.], tot_loss[discriminator_loss=2.69, discriminator_real_loss=1.352, discriminator_fake_loss=1.338, generator_loss=29.08, generator_mel_loss=17.82, generator_kl_loss=1.423, generator_dur_loss=1.739, generator_adv_loss=1.988, generator_feat_match_loss=6.109, over 2350.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 19:40:33,956 INFO [train.py:527] (2/6) Epoch 889, batch 88, global_batch_idx: 110200, batch size: 61, loss[discriminator_loss=2.688, discriminator_real_loss=1.346, discriminator_fake_loss=1.342, generator_loss=28.41, generator_mel_loss=17.8, generator_kl_loss=1.549, generator_dur_loss=1.736, generator_adv_loss=1.992, generator_feat_match_loss=5.33, over 61.00 samples.], tot_loss[discriminator_loss=2.693, discriminator_real_loss=1.359, discriminator_fake_loss=1.334, generator_loss=29.05, generator_mel_loss=17.86, generator_kl_loss=1.432, generator_dur_loss=1.728, generator_adv_loss=1.997, generator_feat_match_loss=6.032, over 5042.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 19:40:33,957 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 19:40:42,833 INFO [train.py:591] (2/6) Epoch 889, validation: discriminator_loss=2.754, discriminator_real_loss=1.343, discriminator_fake_loss=1.411, generator_loss=28.45, generator_mel_loss=18.43, generator_kl_loss=1.235, generator_dur_loss=1.779, generator_adv_loss=1.929, generator_feat_match_loss=5.07, over 100.00 samples.
2024-03-15 19:40:42,834 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 19:42:21,639 INFO [train.py:919] (2/6) Start epoch 890
2024-03-15 19:43:21,698 INFO [train.py:527] (2/6) Epoch 890, batch 14, global_batch_idx: 110250, batch size: 72, loss[discriminator_loss=2.722, discriminator_real_loss=1.359, discriminator_fake_loss=1.363, generator_loss=29.75, generator_mel_loss=17.83, generator_kl_loss=1.453, generator_dur_loss=1.788, generator_adv_loss=2.035, generator_feat_match_loss=6.642, over 72.00 samples.], tot_loss[discriminator_loss=2.671, discriminator_real_loss=1.337, discriminator_fake_loss=1.334, generator_loss=29.22, generator_mel_loss=17.85, generator_kl_loss=1.482, generator_dur_loss=1.726, generator_adv_loss=1.992, generator_feat_match_loss=6.173, over 848.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 19:45:41,015 INFO [train.py:527] (2/6) Epoch 890, batch 64, global_batch_idx: 110300, batch size: 59, loss[discriminator_loss=2.655, discriminator_real_loss=1.349, discriminator_fake_loss=1.306, generator_loss=29.75, generator_mel_loss=17.84, generator_kl_loss=1.362, generator_dur_loss=1.752, generator_adv_loss=1.971, generator_feat_match_loss=6.824, over 59.00 samples.], tot_loss[discriminator_loss=2.679, discriminator_real_loss=1.353, discriminator_fake_loss=1.326, generator_loss=29.11, generator_mel_loss=17.82, generator_kl_loss=1.47, generator_dur_loss=1.727, generator_adv_loss=1.996, generator_feat_match_loss=6.092, over 3568.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 19:48:00,211 INFO [train.py:527] (2/6) Epoch 890, batch 114, global_batch_idx: 110350, batch size: 32, loss[discriminator_loss=2.634, discriminator_real_loss=1.319, discriminator_fake_loss=1.316, generator_loss=29.57, generator_mel_loss=18.37, generator_kl_loss=1.679, generator_dur_loss=1.571, generator_adv_loss=2.099, generator_feat_match_loss=5.856, over 32.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.351, discriminator_fake_loss=1.325, generator_loss=29.08, generator_mel_loss=17.81, generator_kl_loss=1.439, generator_dur_loss=1.734, generator_adv_loss=2, generator_feat_match_loss=6.098, over 6394.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 19:48:25,083 INFO [train.py:919] (2/6) Start epoch 891
2024-03-15 19:50:39,186 INFO [train.py:527] (2/6) Epoch 891, batch 40, global_batch_idx: 110400, batch size: 64, loss[discriminator_loss=2.715, discriminator_real_loss=1.408, discriminator_fake_loss=1.306, generator_loss=29.1, generator_mel_loss=17.11, generator_kl_loss=1.367, generator_dur_loss=1.738, generator_adv_loss=1.988, generator_feat_match_loss=6.896, over 64.00 samples.], tot_loss[discriminator_loss=2.664, discriminator_real_loss=1.345, discriminator_fake_loss=1.318, generator_loss=29.02, generator_mel_loss=17.69, generator_kl_loss=1.405, generator_dur_loss=1.744, generator_adv_loss=2.022, generator_feat_match_loss=6.154, over 2502.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 19:50:39,187 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 19:50:47,088 INFO [train.py:591] (2/6) Epoch 891, validation: discriminator_loss=2.732, discriminator_real_loss=1.373, discriminator_fake_loss=1.359, generator_loss=27.53, generator_mel_loss=17.92, generator_kl_loss=1.284, generator_dur_loss=1.802, generator_adv_loss=1.847, generator_feat_match_loss=4.682, over 100.00 samples.
2024-03-15 19:50:47,089 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 19:53:05,757 INFO [train.py:527] (2/6) Epoch 891, batch 90, global_batch_idx: 110450, batch size: 83, loss[discriminator_loss=2.685, discriminator_real_loss=1.339, discriminator_fake_loss=1.346, generator_loss=28.98, generator_mel_loss=17.84, generator_kl_loss=1.449, generator_dur_loss=1.837, generator_adv_loss=1.982, generator_feat_match_loss=5.868, over 83.00 samples.], tot_loss[discriminator_loss=2.667, discriminator_real_loss=1.353, discriminator_fake_loss=1.314, generator_loss=29.05, generator_mel_loss=17.75, generator_kl_loss=1.421, generator_dur_loss=1.734, generator_adv_loss=2.024, generator_feat_match_loss=6.125, over 5246.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 19:54:37,590 INFO [train.py:919] (2/6) Start epoch 892
2024-03-15 19:55:47,486 INFO [train.py:527] (2/6) Epoch 892, batch 16, global_batch_idx: 110500, batch size: 59, loss[discriminator_loss=2.66, discriminator_real_loss=1.321, discriminator_fake_loss=1.339, generator_loss=29.4, generator_mel_loss=17.79, generator_kl_loss=1.464, generator_dur_loss=1.752, generator_adv_loss=2.079, generator_feat_match_loss=6.317, over 59.00 samples.], tot_loss[discriminator_loss=2.668, discriminator_real_loss=1.363, discriminator_fake_loss=1.305, generator_loss=29.04, generator_mel_loss=17.68, generator_kl_loss=1.415, generator_dur_loss=1.756, generator_adv_loss=2.022, generator_feat_match_loss=6.168, over 1051.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 19:58:05,731 INFO [train.py:527] (2/6) Epoch 892, batch 66, global_batch_idx: 110550, batch size: 50, loss[discriminator_loss=2.651, discriminator_real_loss=1.365, discriminator_fake_loss=1.286, generator_loss=29.13, generator_mel_loss=17.97, generator_kl_loss=1.44, generator_dur_loss=1.703, generator_adv_loss=2.155, generator_feat_match_loss=5.865, over 50.00 samples.], tot_loss[discriminator_loss=2.671, discriminator_real_loss=1.358, discriminator_fake_loss=1.313, generator_loss=29.07, generator_mel_loss=17.72, generator_kl_loss=1.44, generator_dur_loss=1.731, generator_adv_loss=2.016, generator_feat_match_loss=6.164, over 3802.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 20:00:25,583 INFO [train.py:527] (2/6) Epoch 892, batch 116, global_batch_idx: 110600, batch size: 55, loss[discriminator_loss=2.685, discriminator_real_loss=1.321, discriminator_fake_loss=1.363, generator_loss=28.97, generator_mel_loss=17.74, generator_kl_loss=1.423, generator_dur_loss=1.7, generator_adv_loss=2.062, generator_feat_match_loss=6.052, over 55.00 samples.], tot_loss[discriminator_loss=2.679, discriminator_real_loss=1.36, discriminator_fake_loss=1.319, generator_loss=29.03, generator_mel_loss=17.74, generator_kl_loss=1.446, generator_dur_loss=1.743, generator_adv_loss=2.004, generator_feat_match_loss=6.093, over 6922.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 20:00:25,585 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 20:00:34,390 INFO [train.py:591] (2/6) Epoch 892, validation: discriminator_loss=2.773, discriminator_real_loss=1.453, discriminator_fake_loss=1.32, generator_loss=27.71, generator_mel_loss=17.94, generator_kl_loss=1.333, generator_dur_loss=1.809, generator_adv_loss=1.964, generator_feat_match_loss=4.661, over 100.00 samples.
2024-03-15 20:00:34,390 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 20:00:55,593 INFO [train.py:919] (2/6) Start epoch 893
2024-03-15 20:03:17,306 INFO [train.py:527] (2/6) Epoch 893, batch 42, global_batch_idx: 110650, batch size: 25, loss[discriminator_loss=2.749, discriminator_real_loss=1.272, discriminator_fake_loss=1.477, generator_loss=29, generator_mel_loss=18.14, generator_kl_loss=1.473, generator_dur_loss=1.587, generator_adv_loss=2.082, generator_feat_match_loss=5.712, over 25.00 samples.], tot_loss[discriminator_loss=2.683, discriminator_real_loss=1.354, discriminator_fake_loss=1.329, generator_loss=28.99, generator_mel_loss=17.76, generator_kl_loss=1.465, generator_dur_loss=1.745, generator_adv_loss=2.003, generator_feat_match_loss=6.014, over 2448.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 20:05:36,790 INFO [train.py:527] (2/6) Epoch 893, batch 92, global_batch_idx: 110700, batch size: 96, loss[discriminator_loss=2.668, discriminator_real_loss=1.362, discriminator_fake_loss=1.306, generator_loss=28.73, generator_mel_loss=17.5, generator_kl_loss=1.436, generator_dur_loss=1.844, generator_adv_loss=1.953, generator_feat_match_loss=5.996, over 96.00 samples.], tot_loss[discriminator_loss=2.677, discriminator_real_loss=1.355, discriminator_fake_loss=1.323, generator_loss=29.11, generator_mel_loss=17.78, generator_kl_loss=1.47, generator_dur_loss=1.739, generator_adv_loss=2.027, generator_feat_match_loss=6.096, over 4980.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 20:07:02,473 INFO [train.py:919] (2/6) Start epoch 894
2024-03-15 20:08:15,003 INFO [train.py:527] (2/6) Epoch 894, batch 18, global_batch_idx: 110750, batch size: 62, loss[discriminator_loss=2.698, discriminator_real_loss=1.369, discriminator_fake_loss=1.329, generator_loss=28.68, generator_mel_loss=17.78, generator_kl_loss=1.225, generator_dur_loss=1.75, generator_adv_loss=1.961, generator_feat_match_loss=5.969, over 62.00 samples.], tot_loss[discriminator_loss=2.675, discriminator_real_loss=1.356, discriminator_fake_loss=1.32, generator_loss=29.09, generator_mel_loss=17.75, generator_kl_loss=1.45, generator_dur_loss=1.728, generator_adv_loss=1.998, generator_feat_match_loss=6.165, over 1068.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 20:10:34,293 INFO [train.py:527] (2/6) Epoch 894, batch 68, global_batch_idx: 110800, batch size: 58, loss[discriminator_loss=2.674, discriminator_real_loss=1.422, discriminator_fake_loss=1.252, generator_loss=28.46, generator_mel_loss=17.27, generator_kl_loss=1.508, generator_dur_loss=1.731, generator_adv_loss=1.974, generator_feat_match_loss=5.979, over 58.00 samples.], tot_loss[discriminator_loss=2.68, discriminator_real_loss=1.359, discriminator_fake_loss=1.321, generator_loss=28.99, generator_mel_loss=17.72, generator_kl_loss=1.455, generator_dur_loss=1.728, generator_adv_loss=2.003, generator_feat_match_loss=6.086, over 3808.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 20:10:34,294 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 20:10:42,208 INFO [train.py:591] (2/6) Epoch 894, validation: discriminator_loss=2.762, discriminator_real_loss=1.361, discriminator_fake_loss=1.402, generator_loss=26.94, generator_mel_loss=17.53, generator_kl_loss=1.314, generator_dur_loss=1.805, generator_adv_loss=1.797, generator_feat_match_loss=4.494, over 100.00 samples.
2024-03-15 20:10:42,209 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 20:12:59,063 INFO [train.py:527] (2/6) Epoch 894, batch 118, global_batch_idx: 110850, batch size: 83, loss[discriminator_loss=2.699, discriminator_real_loss=1.337, discriminator_fake_loss=1.361, generator_loss=28.95, generator_mel_loss=17.66, generator_kl_loss=1.381, generator_dur_loss=1.823, generator_adv_loss=1.998, generator_feat_match_loss=6.082, over 83.00 samples.], tot_loss[discriminator_loss=2.68, discriminator_real_loss=1.357, discriminator_fake_loss=1.322, generator_loss=29, generator_mel_loss=17.72, generator_kl_loss=1.459, generator_dur_loss=1.734, generator_adv_loss=2.005, generator_feat_match_loss=6.084, over 6653.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 20:13:16,842 INFO [train.py:919] (2/6) Start epoch 895
2024-03-15 20:15:43,914 INFO [train.py:527] (2/6) Epoch 895, batch 44, global_batch_idx: 110900, batch size: 39, loss[discriminator_loss=2.67, discriminator_real_loss=1.357, discriminator_fake_loss=1.313, generator_loss=29.71, generator_mel_loss=18.22, generator_kl_loss=1.628, generator_dur_loss=1.709, generator_adv_loss=2.119, generator_feat_match_loss=6.028, over 39.00 samples.], tot_loss[discriminator_loss=2.683, discriminator_real_loss=1.352, discriminator_fake_loss=1.331, generator_loss=29.11, generator_mel_loss=17.8, generator_kl_loss=1.433, generator_dur_loss=1.755, generator_adv_loss=2.006, generator_feat_match_loss=6.121, over 2628.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 20:18:04,675 INFO [train.py:527] (2/6) Epoch 895, batch 94, global_batch_idx: 110950, batch size: 70, loss[discriminator_loss=2.672, discriminator_real_loss=1.247, discriminator_fake_loss=1.425, generator_loss=29.52, generator_mel_loss=17.89, generator_kl_loss=1.247, generator_dur_loss=1.751, generator_adv_loss=2.075, generator_feat_match_loss=6.557, over 70.00 samples.], tot_loss[discriminator_loss=2.68, discriminator_real_loss=1.353, discriminator_fake_loss=1.327, generator_loss=29.09, generator_mel_loss=17.79, generator_kl_loss=1.422, generator_dur_loss=1.751, generator_adv_loss=2.011, generator_feat_match_loss=6.114, over 5553.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 20:19:26,006 INFO [train.py:919] (2/6) Start epoch 896
2024-03-15 20:20:46,837 INFO [train.py:527] (2/6) Epoch 896, batch 20, global_batch_idx: 111000, batch size: 50, loss[discriminator_loss=2.634, discriminator_real_loss=1.334, discriminator_fake_loss=1.3, generator_loss=29.97, generator_mel_loss=18.01, generator_kl_loss=1.415, generator_dur_loss=1.665, generator_adv_loss=2.091, generator_feat_match_loss=6.791, over 50.00 samples.], tot_loss[discriminator_loss=2.69, discriminator_real_loss=1.354, discriminator_fake_loss=1.335, generator_loss=29.04, generator_mel_loss=17.84, generator_kl_loss=1.373, generator_dur_loss=1.757, generator_adv_loss=2.01, generator_feat_match_loss=6.056, over 1275.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 20:20:46,839 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 20:20:54,707 INFO [train.py:591] (2/6) Epoch 896, validation: discriminator_loss=2.71, discriminator_real_loss=1.454, discriminator_fake_loss=1.256, generator_loss=27.7, generator_mel_loss=17.73, generator_kl_loss=1.333, generator_dur_loss=1.819, generator_adv_loss=1.953, generator_feat_match_loss=4.868, over 100.00 samples.
2024-03-15 20:20:54,708 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 20:23:10,962 INFO [train.py:527] (2/6) Epoch 896, batch 70, global_batch_idx: 111050, batch size: 25, loss[discriminator_loss=2.714, discriminator_real_loss=1.423, discriminator_fake_loss=1.29, generator_loss=28.49, generator_mel_loss=17.95, generator_kl_loss=1.703, generator_dur_loss=1.578, generator_adv_loss=2.045, generator_feat_match_loss=5.21, over 25.00 samples.], tot_loss[discriminator_loss=2.677, discriminator_real_loss=1.351, discriminator_fake_loss=1.325, generator_loss=29.04, generator_mel_loss=17.81, generator_kl_loss=1.4, generator_dur_loss=1.75, generator_adv_loss=2.009, generator_feat_match_loss=6.071, over 4172.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 20:25:30,773 INFO [train.py:527] (2/6) Epoch 896, batch 120, global_batch_idx: 111100, batch size: 52, loss[discriminator_loss=2.607, discriminator_real_loss=1.313, discriminator_fake_loss=1.294, generator_loss=29.18, generator_mel_loss=17.76, generator_kl_loss=1.297, generator_dur_loss=1.741, generator_adv_loss=2.018, generator_feat_match_loss=6.361, over 52.00 samples.], tot_loss[discriminator_loss=2.675, discriminator_real_loss=1.354, discriminator_fake_loss=1.32, generator_loss=29.06, generator_mel_loss=17.79, generator_kl_loss=1.411, generator_dur_loss=1.746, generator_adv_loss=2.015, generator_feat_match_loss=6.096, over 6962.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 20:25:41,203 INFO [train.py:919] (2/6) Start epoch 897
2024-03-15 20:28:12,071 INFO [train.py:527] (2/6) Epoch 897, batch 46, global_batch_idx: 111150, batch size: 52, loss[discriminator_loss=2.678, discriminator_real_loss=1.321, discriminator_fake_loss=1.356, generator_loss=29.13, generator_mel_loss=17.6, generator_kl_loss=1.544, generator_dur_loss=1.67, generator_adv_loss=1.916, generator_feat_match_loss=6.406, over 52.00 samples.], tot_loss[discriminator_loss=2.694, discriminator_real_loss=1.364, discriminator_fake_loss=1.33, generator_loss=29.04, generator_mel_loss=17.81, generator_kl_loss=1.427, generator_dur_loss=1.731, generator_adv_loss=2.004, generator_feat_match_loss=6.068, over 2611.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 20:30:31,869 INFO [train.py:527] (2/6) Epoch 897, batch 96, global_batch_idx: 111200, batch size: 56, loss[discriminator_loss=2.68, discriminator_real_loss=1.226, discriminator_fake_loss=1.454, generator_loss=31.68, generator_mel_loss=18.66, generator_kl_loss=1.602, generator_dur_loss=1.68, generator_adv_loss=2.115, generator_feat_match_loss=7.618, over 56.00 samples.], tot_loss[discriminator_loss=2.688, discriminator_real_loss=1.36, discriminator_fake_loss=1.327, generator_loss=29, generator_mel_loss=17.77, generator_kl_loss=1.427, generator_dur_loss=1.745, generator_adv_loss=2.007, generator_feat_match_loss=6.059, over 5596.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 20:30:31,870 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 20:30:40,686 INFO [train.py:591] (2/6) Epoch 897, validation: discriminator_loss=2.755, discriminator_real_loss=1.525, discriminator_fake_loss=1.23, generator_loss=28.06, generator_mel_loss=18, generator_kl_loss=1.329, generator_dur_loss=1.795, generator_adv_loss=2.099, generator_feat_match_loss=4.839, over 100.00 samples.
2024-03-15 20:30:40,687 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 20:31:58,501 INFO [train.py:919] (2/6) Start epoch 898
2024-03-15 20:33:24,442 INFO [train.py:527] (2/6) Epoch 898, batch 22, global_batch_idx: 111250, batch size: 50, loss[discriminator_loss=2.7, discriminator_real_loss=1.36, discriminator_fake_loss=1.341, generator_loss=29.04, generator_mel_loss=18.09, generator_kl_loss=1.386, generator_dur_loss=1.716, generator_adv_loss=2.145, generator_feat_match_loss=5.707, over 50.00 samples.], tot_loss[discriminator_loss=2.677, discriminator_real_loss=1.352, discriminator_fake_loss=1.325, generator_loss=29.06, generator_mel_loss=17.86, generator_kl_loss=1.438, generator_dur_loss=1.734, generator_adv_loss=2.009, generator_feat_match_loss=6.014, over 1310.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 20:35:45,787 INFO [train.py:527] (2/6) Epoch 898, batch 72, global_batch_idx: 111300, batch size: 45, loss[discriminator_loss=2.644, discriminator_real_loss=1.311, discriminator_fake_loss=1.333, generator_loss=30.23, generator_mel_loss=18.24, generator_kl_loss=1.637, generator_dur_loss=1.654, generator_adv_loss=2.051, generator_feat_match_loss=6.651, over 45.00 samples.], tot_loss[discriminator_loss=2.679, discriminator_real_loss=1.353, discriminator_fake_loss=1.326, generator_loss=29.04, generator_mel_loss=17.74, generator_kl_loss=1.435, generator_dur_loss=1.745, generator_adv_loss=2.015, generator_feat_match_loss=6.102, over 4287.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 20:38:00,106 INFO [train.py:527] (2/6) Epoch 898, batch 122, global_batch_idx: 111350, batch size: 66, loss[discriminator_loss=2.695, discriminator_real_loss=1.4, discriminator_fake_loss=1.295, generator_loss=28.42, generator_mel_loss=17.7, generator_kl_loss=1.441, generator_dur_loss=1.747, generator_adv_loss=1.91, generator_feat_match_loss=5.615, over 66.00 samples.], tot_loss[discriminator_loss=2.675, discriminator_real_loss=1.355, discriminator_fake_loss=1.321, generator_loss=29.04, generator_mel_loss=17.75, generator_kl_loss=1.437, generator_dur_loss=1.744, generator_adv_loss=2.014, generator_feat_match_loss=6.105, over 7176.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 20:38:04,399 INFO [train.py:919] (2/6) Start epoch 899
2024-03-15 20:40:44,593 INFO [train.py:527] (2/6) Epoch 899, batch 48, global_batch_idx: 111400, batch size: 77, loss[discriminator_loss=2.716, discriminator_real_loss=1.365, discriminator_fake_loss=1.351, generator_loss=27.86, generator_mel_loss=17.46, generator_kl_loss=1.322, generator_dur_loss=1.806, generator_adv_loss=1.978, generator_feat_match_loss=5.293, over 77.00 samples.], tot_loss[discriminator_loss=2.681, discriminator_real_loss=1.358, discriminator_fake_loss=1.324, generator_loss=28.99, generator_mel_loss=17.71, generator_kl_loss=1.46, generator_dur_loss=1.736, generator_adv_loss=2.004, generator_feat_match_loss=6.078, over 2799.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 20:40:44,595 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 20:40:52,598 INFO [train.py:591] (2/6) Epoch 899, validation: discriminator_loss=2.78, discriminator_real_loss=1.487, discriminator_fake_loss=1.293, generator_loss=27.47, generator_mel_loss=17.89, generator_kl_loss=1.261, generator_dur_loss=1.794, generator_adv_loss=1.97, generator_feat_match_loss=4.565, over 100.00 samples.
2024-03-15 20:40:52,598 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 20:43:09,908 INFO [train.py:527] (2/6) Epoch 899, batch 98, global_batch_idx: 111450, batch size: 96, loss[discriminator_loss=2.656, discriminator_real_loss=1.301, discriminator_fake_loss=1.355, generator_loss=28.67, generator_mel_loss=17.45, generator_kl_loss=1.414, generator_dur_loss=1.867, generator_adv_loss=1.941, generator_feat_match_loss=5.996, over 96.00 samples.], tot_loss[discriminator_loss=2.681, discriminator_real_loss=1.358, discriminator_fake_loss=1.323, generator_loss=29.05, generator_mel_loss=17.74, generator_kl_loss=1.468, generator_dur_loss=1.738, generator_adv_loss=2, generator_feat_match_loss=6.104, over 5603.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 20:44:18,386 INFO [train.py:919] (2/6) Start epoch 900
2024-03-15 20:45:47,524 INFO [train.py:527] (2/6) Epoch 900, batch 24, global_batch_idx: 111500, batch size: 39, loss[discriminator_loss=2.735, discriminator_real_loss=1.398, discriminator_fake_loss=1.337, generator_loss=29.59, generator_mel_loss=17.89, generator_kl_loss=1.558, generator_dur_loss=1.655, generator_adv_loss=1.95, generator_feat_match_loss=6.539, over 39.00 samples.], tot_loss[discriminator_loss=2.661, discriminator_real_loss=1.338, discriminator_fake_loss=1.324, generator_loss=29.07, generator_mel_loss=17.77, generator_kl_loss=1.478, generator_dur_loss=1.713, generator_adv_loss=2.011, generator_feat_match_loss=6.095, over 1360.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 20:48:02,738 INFO [train.py:527] (2/6) Epoch 900, batch 74, global_batch_idx: 111550, batch size: 47, loss[discriminator_loss=2.638, discriminator_real_loss=1.343, discriminator_fake_loss=1.295, generator_loss=30.29, generator_mel_loss=17.88, generator_kl_loss=1.355, generator_dur_loss=1.68, generator_adv_loss=2.165, generator_feat_match_loss=7.211, over 47.00 samples.], tot_loss[discriminator_loss=2.678, discriminator_real_loss=1.352, discriminator_fake_loss=1.326, generator_loss=29.04, generator_mel_loss=17.82, generator_kl_loss=1.475, generator_dur_loss=1.726, generator_adv_loss=2.009, generator_feat_match_loss=6.009, over 4039.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 20:50:22,427 INFO [train.py:919] (2/6) Start epoch 901
2024-03-15 20:50:46,725 INFO [train.py:527] (2/6) Epoch 901, batch 0, global_batch_idx: 111600, batch size: 53, loss[discriminator_loss=2.683, discriminator_real_loss=1.392, discriminator_fake_loss=1.291, generator_loss=29.02, generator_mel_loss=17.72, generator_kl_loss=1.448, generator_dur_loss=1.695, generator_adv_loss=1.969, generator_feat_match_loss=6.188, over 53.00 samples.], tot_loss[discriminator_loss=2.683, discriminator_real_loss=1.392, discriminator_fake_loss=1.291, generator_loss=29.02, generator_mel_loss=17.72, generator_kl_loss=1.448, generator_dur_loss=1.695, generator_adv_loss=1.969, generator_feat_match_loss=6.188, over 53.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 20:50:46,728 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 20:50:54,868 INFO [train.py:591] (2/6) Epoch 901, validation: discriminator_loss=2.681, discriminator_real_loss=1.361, discriminator_fake_loss=1.32, generator_loss=28.28, generator_mel_loss=17.82, generator_kl_loss=1.409, generator_dur_loss=1.8, generator_adv_loss=1.931, generator_feat_match_loss=5.321, over 100.00 samples.
2024-03-15 20:50:54,870 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 20:53:15,352 INFO [train.py:527] (2/6) Epoch 901, batch 50, global_batch_idx: 111650, batch size: 59, loss[discriminator_loss=2.726, discriminator_real_loss=1.479, discriminator_fake_loss=1.246, generator_loss=28.2, generator_mel_loss=17.23, generator_kl_loss=1.509, generator_dur_loss=1.734, generator_adv_loss=1.857, generator_feat_match_loss=5.866, over 59.00 samples.], tot_loss[discriminator_loss=2.681, discriminator_real_loss=1.363, discriminator_fake_loss=1.318, generator_loss=29.13, generator_mel_loss=17.73, generator_kl_loss=1.463, generator_dur_loss=1.742, generator_adv_loss=2.004, generator_feat_match_loss=6.191, over 2938.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 20:55:32,949 INFO [train.py:527] (2/6) Epoch 901, batch 100, global_batch_idx: 111700, batch size: 80, loss[discriminator_loss=2.61, discriminator_real_loss=1.277, discriminator_fake_loss=1.332, generator_loss=29.99, generator_mel_loss=17.73, generator_kl_loss=1.448, generator_dur_loss=1.77, generator_adv_loss=2.193, generator_feat_match_loss=6.848, over 80.00 samples.], tot_loss[discriminator_loss=2.678, discriminator_real_loss=1.355, discriminator_fake_loss=1.322, generator_loss=29.1, generator_mel_loss=17.72, generator_kl_loss=1.448, generator_dur_loss=1.743, generator_adv_loss=2.008, generator_feat_match_loss=6.181, over 5805.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 20:56:39,877 INFO [train.py:919] (2/6) Start epoch 902
2024-03-15 20:58:14,250 INFO [train.py:527] (2/6) Epoch 902, batch 26, global_batch_idx: 111750, batch size: 36, loss[discriminator_loss=2.63, discriminator_real_loss=1.329, discriminator_fake_loss=1.3, generator_loss=29.57, generator_mel_loss=17.8, generator_kl_loss=1.472, generator_dur_loss=1.617, generator_adv_loss=2.109, generator_feat_match_loss=6.561, over 36.00 samples.], tot_loss[discriminator_loss=2.673, discriminator_real_loss=1.353, discriminator_fake_loss=1.319, generator_loss=29.07, generator_mel_loss=17.79, generator_kl_loss=1.448, generator_dur_loss=1.729, generator_adv_loss=2.027, generator_feat_match_loss=6.078, over 1483.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 21:00:32,681 INFO [train.py:527] (2/6) Epoch 902, batch 76, global_batch_idx: 111800, batch size: 64, loss[discriminator_loss=2.715, discriminator_real_loss=1.3, discriminator_fake_loss=1.415, generator_loss=30.26, generator_mel_loss=18.09, generator_kl_loss=1.596, generator_dur_loss=1.737, generator_adv_loss=2.134, generator_feat_match_loss=6.705, over 64.00 samples.], tot_loss[discriminator_loss=2.673, discriminator_real_loss=1.355, discriminator_fake_loss=1.318, generator_loss=29.04, generator_mel_loss=17.72, generator_kl_loss=1.434, generator_dur_loss=1.742, generator_adv_loss=2.021, generator_feat_match_loss=6.12, over 4436.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 21:00:32,682 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 21:00:41,438 INFO [train.py:591] (2/6) Epoch 902, validation: discriminator_loss=2.754, discriminator_real_loss=1.503, discriminator_fake_loss=1.252, generator_loss=28.64, generator_mel_loss=18.16, generator_kl_loss=1.335, generator_dur_loss=1.797, generator_adv_loss=2.019, generator_feat_match_loss=5.327, over 100.00 samples.
2024-03-15 21:00:41,439 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 21:02:53,421 INFO [train.py:919] (2/6) Start epoch 903
2024-03-15 21:03:24,032 INFO [train.py:527] (2/6) Epoch 903, batch 2, global_batch_idx: 111850, batch size: 47, loss[discriminator_loss=2.715, discriminator_real_loss=1.33, discriminator_fake_loss=1.385, generator_loss=29.92, generator_mel_loss=18.37, generator_kl_loss=1.506, generator_dur_loss=1.705, generator_adv_loss=2.018, generator_feat_match_loss=6.326, over 47.00 samples.], tot_loss[discriminator_loss=2.716, discriminator_real_loss=1.381, discriminator_fake_loss=1.336, generator_loss=29.49, generator_mel_loss=17.9, generator_kl_loss=1.42, generator_dur_loss=1.769, generator_adv_loss=2.013, generator_feat_match_loss=6.384, over 166.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 21:05:40,707 INFO [train.py:527] (2/6) Epoch 903, batch 52, global_batch_idx: 111900, batch size: 64, loss[discriminator_loss=2.728, discriminator_real_loss=1.324, discriminator_fake_loss=1.404, generator_loss=27.83, generator_mel_loss=17.64, generator_kl_loss=1.329, generator_dur_loss=1.727, generator_adv_loss=1.918, generator_feat_match_loss=5.218, over 64.00 samples.], tot_loss[discriminator_loss=2.682, discriminator_real_loss=1.356, discriminator_fake_loss=1.326, generator_loss=29.08, generator_mel_loss=17.8, generator_kl_loss=1.442, generator_dur_loss=1.741, generator_adv_loss=2.014, generator_feat_match_loss=6.081, over 3064.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 21:08:00,033 INFO [train.py:527] (2/6) Epoch 903, batch 102, global_batch_idx: 111950, batch size: 80, loss[discriminator_loss=2.686, discriminator_real_loss=1.451, discriminator_fake_loss=1.235, generator_loss=28.52, generator_mel_loss=17.93, generator_kl_loss=1.446, generator_dur_loss=1.791, generator_adv_loss=1.889, generator_feat_match_loss=5.461, over 80.00 samples.], tot_loss[discriminator_loss=2.682, discriminator_real_loss=1.358, discriminator_fake_loss=1.325, generator_loss=29.09, generator_mel_loss=17.8, generator_kl_loss=1.444, generator_dur_loss=1.731, generator_adv_loss=2.009, generator_feat_match_loss=6.105, over 5721.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 21:08:59,224 INFO [train.py:919] (2/6) Start epoch 904
2024-03-15 21:10:44,455 INFO [train.py:527] (2/6) Epoch 904, batch 28, global_batch_idx: 112000, batch size: 44, loss[discriminator_loss=2.678, discriminator_real_loss=1.396, discriminator_fake_loss=1.282, generator_loss=28.72, generator_mel_loss=17.36, generator_kl_loss=1.401, generator_dur_loss=1.686, generator_adv_loss=2.021, generator_feat_match_loss=6.25, over 44.00 samples.], tot_loss[discriminator_loss=2.681, discriminator_real_loss=1.356, discriminator_fake_loss=1.325, generator_loss=29.1, generator_mel_loss=17.65, generator_kl_loss=1.454, generator_dur_loss=1.739, generator_adv_loss=2.005, generator_feat_match_loss=6.251, over 1730.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 21:10:44,456 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 21:10:52,259 INFO [train.py:591] (2/6) Epoch 904, validation: discriminator_loss=2.746, discriminator_real_loss=1.417, discriminator_fake_loss=1.329, generator_loss=28.33, generator_mel_loss=17.63, generator_kl_loss=1.195, generator_dur_loss=1.788, generator_adv_loss=1.936, generator_feat_match_loss=5.781, over 100.00 samples.
2024-03-15 21:10:52,259 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 21:13:12,945 INFO [train.py:527] (2/6) Epoch 904, batch 78, global_batch_idx: 112050, batch size: 61, loss[discriminator_loss=2.701, discriminator_real_loss=1.387, discriminator_fake_loss=1.314, generator_loss=28.85, generator_mel_loss=17.93, generator_kl_loss=1.469, generator_dur_loss=1.766, generator_adv_loss=2.039, generator_feat_match_loss=5.649, over 61.00 samples.], tot_loss[discriminator_loss=2.678, discriminator_real_loss=1.355, discriminator_fake_loss=1.323, generator_loss=29.15, generator_mel_loss=17.78, generator_kl_loss=1.439, generator_dur_loss=1.733, generator_adv_loss=2.014, generator_feat_match_loss=6.192, over 4494.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 21:15:17,391 INFO [train.py:919] (2/6) Start epoch 905
2024-03-15 21:15:52,514 INFO [train.py:527] (2/6) Epoch 905, batch 4, global_batch_idx: 112100, batch size: 58, loss[discriminator_loss=2.732, discriminator_real_loss=1.313, discriminator_fake_loss=1.42, generator_loss=27.75, generator_mel_loss=16.9, generator_kl_loss=1.33, generator_dur_loss=1.742, generator_adv_loss=2.104, generator_feat_match_loss=5.674, over 58.00 samples.], tot_loss[discriminator_loss=2.714, discriminator_real_loss=1.364, discriminator_fake_loss=1.35, generator_loss=28.64, generator_mel_loss=17.57, generator_kl_loss=1.35, generator_dur_loss=1.727, generator_adv_loss=1.994, generator_feat_match_loss=5.993, over 296.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 21:18:11,892 INFO [train.py:527] (2/6) Epoch 905, batch 54, global_batch_idx: 112150, batch size: 36, loss[discriminator_loss=2.648, discriminator_real_loss=1.31, discriminator_fake_loss=1.338, generator_loss=30.39, generator_mel_loss=18.25, generator_kl_loss=1.526, generator_dur_loss=1.68, generator_adv_loss=2.048, generator_feat_match_loss=6.887, over 36.00 samples.], tot_loss[discriminator_loss=2.677, discriminator_real_loss=1.357, discriminator_fake_loss=1.32, generator_loss=29.12, generator_mel_loss=17.73, generator_kl_loss=1.423, generator_dur_loss=1.748, generator_adv_loss=2.012, generator_feat_match_loss=6.201, over 3321.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 21:20:30,317 INFO [train.py:527] (2/6) Epoch 905, batch 104, global_batch_idx: 112200, batch size: 52, loss[discriminator_loss=2.676, discriminator_real_loss=1.28, discriminator_fake_loss=1.397, generator_loss=29.47, generator_mel_loss=17.65, generator_kl_loss=1.412, generator_dur_loss=1.703, generator_adv_loss=2.169, generator_feat_match_loss=6.533, over 52.00 samples.], tot_loss[discriminator_loss=2.675, discriminator_real_loss=1.354, discriminator_fake_loss=1.321, generator_loss=29.07, generator_mel_loss=17.73, generator_kl_loss=1.433, generator_dur_loss=1.742, generator_adv_loss=2.014, generator_feat_match_loss=6.152, over 6076.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 21:20:30,319 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 21:20:39,139 INFO [train.py:591] (2/6) Epoch 905, validation: discriminator_loss=2.711, discriminator_real_loss=1.395, discriminator_fake_loss=1.316, generator_loss=28.24, generator_mel_loss=18.03, generator_kl_loss=1.283, generator_dur_loss=1.802, generator_adv_loss=1.967, generator_feat_match_loss=5.154, over 100.00 samples.
2024-03-15 21:20:39,140 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 21:21:31,633 INFO [train.py:919] (2/6) Start epoch 906
2024-03-15 21:23:20,333 INFO [train.py:527] (2/6) Epoch 906, batch 30, global_batch_idx: 112250, batch size: 50, loss[discriminator_loss=2.649, discriminator_real_loss=1.4, discriminator_fake_loss=1.249, generator_loss=29.04, generator_mel_loss=17.9, generator_kl_loss=1.377, generator_dur_loss=1.658, generator_adv_loss=2.047, generator_feat_match_loss=6.058, over 50.00 samples.], tot_loss[discriminator_loss=2.683, discriminator_real_loss=1.357, discriminator_fake_loss=1.326, generator_loss=29.01, generator_mel_loss=17.73, generator_kl_loss=1.427, generator_dur_loss=1.737, generator_adv_loss=2.016, generator_feat_match_loss=6.098, over 1733.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 21:25:40,523 INFO [train.py:527] (2/6) Epoch 906, batch 80, global_batch_idx: 112300, batch size: 96, loss[discriminator_loss=2.68, discriminator_real_loss=1.395, discriminator_fake_loss=1.285, generator_loss=28.83, generator_mel_loss=17.79, generator_kl_loss=1.398, generator_dur_loss=1.855, generator_adv_loss=2.018, generator_feat_match_loss=5.771, over 96.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.36, discriminator_fake_loss=1.324, generator_loss=29.04, generator_mel_loss=17.75, generator_kl_loss=1.441, generator_dur_loss=1.739, generator_adv_loss=2.012, generator_feat_match_loss=6.095, over 4570.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 21:27:38,190 INFO [train.py:919] (2/6) Start epoch 907
2024-03-15 21:28:22,232 INFO [train.py:527] (2/6) Epoch 907, batch 6, global_batch_idx: 112350, batch size: 55, loss[discriminator_loss=2.679, discriminator_real_loss=1.385, discriminator_fake_loss=1.294, generator_loss=29.46, generator_mel_loss=17.61, generator_kl_loss=1.397, generator_dur_loss=1.709, generator_adv_loss=2.141, generator_feat_match_loss=6.605, over 55.00 samples.], tot_loss[discriminator_loss=2.688, discriminator_real_loss=1.349, discriminator_fake_loss=1.339, generator_loss=29.05, generator_mel_loss=17.74, generator_kl_loss=1.431, generator_dur_loss=1.761, generator_adv_loss=2.049, generator_feat_match_loss=6.077, over 444.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 21:30:38,175 INFO [train.py:527] (2/6) Epoch 907, batch 56, global_batch_idx: 112400, batch size: 80, loss[discriminator_loss=2.626, discriminator_real_loss=1.29, discriminator_fake_loss=1.336, generator_loss=29.71, generator_mel_loss=17.94, generator_kl_loss=1.382, generator_dur_loss=1.776, generator_adv_loss=2.039, generator_feat_match_loss=6.573, over 80.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.349, discriminator_fake_loss=1.326, generator_loss=29.03, generator_mel_loss=17.71, generator_kl_loss=1.448, generator_dur_loss=1.74, generator_adv_loss=2.008, generator_feat_match_loss=6.133, over 3372.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 21:30:38,176 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 21:30:45,988 INFO [train.py:591] (2/6) Epoch 907, validation: discriminator_loss=2.664, discriminator_real_loss=1.416, discriminator_fake_loss=1.248, generator_loss=27.56, generator_mel_loss=17.79, generator_kl_loss=1.266, generator_dur_loss=1.794, generator_adv_loss=1.994, generator_feat_match_loss=4.718, over 100.00 samples.
2024-03-15 21:30:45,989 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 21:33:05,444 INFO [train.py:527] (2/6) Epoch 907, batch 106, global_batch_idx: 112450, batch size: 42, loss[discriminator_loss=2.626, discriminator_real_loss=1.292, discriminator_fake_loss=1.334, generator_loss=29.21, generator_mel_loss=17.61, generator_kl_loss=1.474, generator_dur_loss=1.652, generator_adv_loss=2.016, generator_feat_match_loss=6.463, over 42.00 samples.], tot_loss[discriminator_loss=2.673, discriminator_real_loss=1.349, discriminator_fake_loss=1.323, generator_loss=29.06, generator_mel_loss=17.74, generator_kl_loss=1.442, generator_dur_loss=1.73, generator_adv_loss=2.012, generator_feat_match_loss=6.131, over 5986.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 21:33:55,966 INFO [train.py:919] (2/6) Start epoch 908
2024-03-15 21:35:50,182 INFO [train.py:527] (2/6) Epoch 908, batch 32, global_batch_idx: 112500, batch size: 88, loss[discriminator_loss=2.68, discriminator_real_loss=1.344, discriminator_fake_loss=1.337, generator_loss=29.09, generator_mel_loss=17.69, generator_kl_loss=1.382, generator_dur_loss=1.833, generator_adv_loss=2.099, generator_feat_match_loss=6.079, over 88.00 samples.], tot_loss[discriminator_loss=2.67, discriminator_real_loss=1.353, discriminator_fake_loss=1.317, generator_loss=29.17, generator_mel_loss=17.8, generator_kl_loss=1.452, generator_dur_loss=1.728, generator_adv_loss=2.008, generator_feat_match_loss=6.182, over 1948.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 21:38:12,198 INFO [train.py:527] (2/6) Epoch 908, batch 82, global_batch_idx: 112550, batch size: 53, loss[discriminator_loss=2.632, discriminator_real_loss=1.347, discriminator_fake_loss=1.285, generator_loss=30.04, generator_mel_loss=18.34, generator_kl_loss=1.525, generator_dur_loss=1.665, generator_adv_loss=2.118, generator_feat_match_loss=6.388, over 53.00 samples.], tot_loss[discriminator_loss=2.679, discriminator_real_loss=1.359, discriminator_fake_loss=1.32, generator_loss=29.04, generator_mel_loss=17.76, generator_kl_loss=1.431, generator_dur_loss=1.734, generator_adv_loss=2.013, generator_feat_match_loss=6.098, over 4926.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 21:40:05,293 INFO [train.py:919] (2/6) Start epoch 909
2024-03-15 21:40:51,664 INFO [train.py:527] (2/6) Epoch 909, batch 8, global_batch_idx: 112600, batch size: 55, loss[discriminator_loss=2.676, discriminator_real_loss=1.347, discriminator_fake_loss=1.329, generator_loss=28.98, generator_mel_loss=17.75, generator_kl_loss=1.528, generator_dur_loss=1.695, generator_adv_loss=1.977, generator_feat_match_loss=6.024, over 55.00 samples.], tot_loss[discriminator_loss=2.653, discriminator_real_loss=1.344, discriminator_fake_loss=1.309, generator_loss=29.15, generator_mel_loss=17.91, generator_kl_loss=1.497, generator_dur_loss=1.684, generator_adv_loss=2.016, generator_feat_match_loss=6.048, over 429.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 21:40:51,666 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 21:40:59,652 INFO [train.py:591] (2/6) Epoch 909, validation: discriminator_loss=2.692, discriminator_real_loss=1.392, discriminator_fake_loss=1.3, generator_loss=28.19, generator_mel_loss=18.39, generator_kl_loss=1.205, generator_dur_loss=1.783, generator_adv_loss=1.917, generator_feat_match_loss=4.895, over 100.00 samples.
2024-03-15 21:40:59,654 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 21:43:17,123 INFO [train.py:527] (2/6) Epoch 909, batch 58, global_batch_idx: 112650, batch size: 74, loss[discriminator_loss=2.705, discriminator_real_loss=1.358, discriminator_fake_loss=1.347, generator_loss=28.19, generator_mel_loss=17.29, generator_kl_loss=1.371, generator_dur_loss=1.79, generator_adv_loss=2.065, generator_feat_match_loss=5.678, over 74.00 samples.], tot_loss[discriminator_loss=2.665, discriminator_real_loss=1.349, discriminator_fake_loss=1.316, generator_loss=29.1, generator_mel_loss=17.78, generator_kl_loss=1.43, generator_dur_loss=1.734, generator_adv_loss=2.007, generator_feat_match_loss=6.146, over 3370.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 21:45:36,638 INFO [train.py:527] (2/6) Epoch 909, batch 108, global_batch_idx: 112700, batch size: 64, loss[discriminator_loss=2.605, discriminator_real_loss=1.28, discriminator_fake_loss=1.325, generator_loss=29.75, generator_mel_loss=17.88, generator_kl_loss=1.435, generator_dur_loss=1.743, generator_adv_loss=2.139, generator_feat_match_loss=6.552, over 64.00 samples.], tot_loss[discriminator_loss=2.668, discriminator_real_loss=1.347, discriminator_fake_loss=1.321, generator_loss=29.09, generator_mel_loss=17.78, generator_kl_loss=1.435, generator_dur_loss=1.736, generator_adv_loss=2.009, generator_feat_match_loss=6.129, over 6379.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 21:46:19,225 INFO [train.py:919] (2/6) Start epoch 910
2024-03-15 21:48:18,740 INFO [train.py:527] (2/6) Epoch 910, batch 34, global_batch_idx: 112750, batch size: 42, loss[discriminator_loss=2.698, discriminator_real_loss=1.372, discriminator_fake_loss=1.326, generator_loss=29.11, generator_mel_loss=17.53, generator_kl_loss=1.57, generator_dur_loss=1.68, generator_adv_loss=2.177, generator_feat_match_loss=6.155, over 42.00 samples.], tot_loss[discriminator_loss=2.68, discriminator_real_loss=1.353, discriminator_fake_loss=1.326, generator_loss=29, generator_mel_loss=17.74, generator_kl_loss=1.433, generator_dur_loss=1.724, generator_adv_loss=2.008, generator_feat_match_loss=6.095, over 1955.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 21:50:36,706 INFO [train.py:527] (2/6) Epoch 910, batch 84, global_batch_idx: 112800, batch size: 36, loss[discriminator_loss=2.632, discriminator_real_loss=1.387, discriminator_fake_loss=1.245, generator_loss=28.81, generator_mel_loss=17.79, generator_kl_loss=1.486, generator_dur_loss=1.68, generator_adv_loss=1.966, generator_feat_match_loss=5.885, over 36.00 samples.], tot_loss[discriminator_loss=2.678, discriminator_real_loss=1.355, discriminator_fake_loss=1.324, generator_loss=28.93, generator_mel_loss=17.67, generator_kl_loss=1.418, generator_dur_loss=1.733, generator_adv_loss=2.007, generator_feat_match_loss=6.1, over 4981.00 samples.], cur_lr_g: 1.79e-04, cur_lr_d: 1.79e-04, 
2024-03-15 21:50:36,707 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 21:50:45,551 INFO [train.py:591] (2/6) Epoch 910, validation: discriminator_loss=2.684, discriminator_real_loss=1.36, discriminator_fake_loss=1.324, generator_loss=28.2, generator_mel_loss=18.04, generator_kl_loss=1.346, generator_dur_loss=1.793, generator_adv_loss=1.908, generator_feat_match_loss=5.107, over 100.00 samples.
2024-03-15 21:50:45,552 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 21:52:33,530 INFO [train.py:919] (2/6) Start epoch 911
2024-03-15 21:53:21,778 INFO [train.py:527] (2/6) Epoch 911, batch 10, global_batch_idx: 112850, batch size: 55, loss[discriminator_loss=2.73, discriminator_real_loss=1.39, discriminator_fake_loss=1.341, generator_loss=29.16, generator_mel_loss=17.9, generator_kl_loss=1.496, generator_dur_loss=1.753, generator_adv_loss=2.068, generator_feat_match_loss=5.937, over 55.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.355, discriminator_fake_loss=1.33, generator_loss=29.18, generator_mel_loss=17.8, generator_kl_loss=1.496, generator_dur_loss=1.752, generator_adv_loss=2.003, generator_feat_match_loss=6.133, over 632.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 21:55:41,990 INFO [train.py:527] (2/6) Epoch 911, batch 60, global_batch_idx: 112900, batch size: 68, loss[discriminator_loss=2.638, discriminator_real_loss=1.318, discriminator_fake_loss=1.32, generator_loss=29.21, generator_mel_loss=17.79, generator_kl_loss=1.356, generator_dur_loss=1.773, generator_adv_loss=2.002, generator_feat_match_loss=6.287, over 68.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.357, discriminator_fake_loss=1.327, generator_loss=29.08, generator_mel_loss=17.76, generator_kl_loss=1.444, generator_dur_loss=1.734, generator_adv_loss=2.012, generator_feat_match_loss=6.129, over 3437.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 21:58:01,559 INFO [train.py:527] (2/6) Epoch 911, batch 110, global_batch_idx: 112950, batch size: 56, loss[discriminator_loss=2.635, discriminator_real_loss=1.403, discriminator_fake_loss=1.232, generator_loss=29.9, generator_mel_loss=17.62, generator_kl_loss=1.37, generator_dur_loss=1.708, generator_adv_loss=1.99, generator_feat_match_loss=7.208, over 56.00 samples.], tot_loss[discriminator_loss=2.678, discriminator_real_loss=1.355, discriminator_fake_loss=1.322, generator_loss=29.11, generator_mel_loss=17.76, generator_kl_loss=1.446, generator_dur_loss=1.734, generator_adv_loss=2.014, generator_feat_match_loss=6.159, over 6334.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 21:58:38,060 INFO [train.py:919] (2/6) Start epoch 912
2024-03-15 22:00:41,240 INFO [train.py:527] (2/6) Epoch 912, batch 36, global_batch_idx: 113000, batch size: 31, loss[discriminator_loss=2.615, discriminator_real_loss=1.367, discriminator_fake_loss=1.249, generator_loss=29.8, generator_mel_loss=18.25, generator_kl_loss=1.574, generator_dur_loss=1.676, generator_adv_loss=2.025, generator_feat_match_loss=6.274, over 31.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.36, discriminator_fake_loss=1.325, generator_loss=28.84, generator_mel_loss=17.71, generator_kl_loss=1.453, generator_dur_loss=1.744, generator_adv_loss=1.996, generator_feat_match_loss=5.939, over 1979.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 22:00:41,243 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 22:00:49,100 INFO [train.py:591] (2/6) Epoch 912, validation: discriminator_loss=2.746, discriminator_real_loss=1.38, discriminator_fake_loss=1.366, generator_loss=27.78, generator_mel_loss=18.16, generator_kl_loss=1.293, generator_dur_loss=1.821, generator_adv_loss=1.836, generator_feat_match_loss=4.669, over 100.00 samples.
2024-03-15 22:00:49,101 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 22:03:06,552 INFO [train.py:527] (2/6) Epoch 912, batch 86, global_batch_idx: 113050, batch size: 25, loss[discriminator_loss=2.614, discriminator_real_loss=1.298, discriminator_fake_loss=1.315, generator_loss=32.62, generator_mel_loss=18.07, generator_kl_loss=1.967, generator_dur_loss=1.502, generator_adv_loss=2.167, generator_feat_match_loss=8.912, over 25.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.356, discriminator_fake_loss=1.32, generator_loss=28.9, generator_mel_loss=17.7, generator_kl_loss=1.45, generator_dur_loss=1.743, generator_adv_loss=2.005, generator_feat_match_loss=6.001, over 4725.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 22:04:50,267 INFO [train.py:919] (2/6) Start epoch 913
2024-03-15 22:05:47,810 INFO [train.py:527] (2/6) Epoch 913, batch 12, global_batch_idx: 113100, batch size: 83, loss[discriminator_loss=2.715, discriminator_real_loss=1.344, discriminator_fake_loss=1.371, generator_loss=29, generator_mel_loss=18.05, generator_kl_loss=1.348, generator_dur_loss=1.828, generator_adv_loss=1.936, generator_feat_match_loss=5.842, over 83.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.348, discriminator_fake_loss=1.328, generator_loss=28.94, generator_mel_loss=17.64, generator_kl_loss=1.411, generator_dur_loss=1.752, generator_adv_loss=2.001, generator_feat_match_loss=6.133, over 840.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 22:08:07,178 INFO [train.py:527] (2/6) Epoch 913, batch 62, global_batch_idx: 113150, batch size: 61, loss[discriminator_loss=2.638, discriminator_real_loss=1.368, discriminator_fake_loss=1.271, generator_loss=29.04, generator_mel_loss=17.78, generator_kl_loss=1.421, generator_dur_loss=1.758, generator_adv_loss=2.161, generator_feat_match_loss=5.92, over 61.00 samples.], tot_loss[discriminator_loss=2.671, discriminator_real_loss=1.359, discriminator_fake_loss=1.312, generator_loss=29.14, generator_mel_loss=17.73, generator_kl_loss=1.438, generator_dur_loss=1.744, generator_adv_loss=2.048, generator_feat_match_loss=6.185, over 3641.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 22:10:23,143 INFO [train.py:527] (2/6) Epoch 913, batch 112, global_batch_idx: 113200, batch size: 53, loss[discriminator_loss=2.66, discriminator_real_loss=1.349, discriminator_fake_loss=1.311, generator_loss=29.32, generator_mel_loss=17.74, generator_kl_loss=1.456, generator_dur_loss=1.68, generator_adv_loss=2.085, generator_feat_match_loss=6.355, over 53.00 samples.], tot_loss[discriminator_loss=2.671, discriminator_real_loss=1.354, discriminator_fake_loss=1.317, generator_loss=29.12, generator_mel_loss=17.75, generator_kl_loss=1.448, generator_dur_loss=1.734, generator_adv_loss=2.032, generator_feat_match_loss=6.16, over 6289.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 22:10:23,144 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 22:10:32,024 INFO [train.py:591] (2/6) Epoch 913, validation: discriminator_loss=2.712, discriminator_real_loss=1.412, discriminator_fake_loss=1.3, generator_loss=27.69, generator_mel_loss=17.83, generator_kl_loss=1.352, generator_dur_loss=1.812, generator_adv_loss=1.869, generator_feat_match_loss=4.819, over 100.00 samples.
2024-03-15 22:10:32,025 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 22:11:03,008 INFO [train.py:919] (2/6) Start epoch 914
2024-03-15 22:13:12,197 INFO [train.py:527] (2/6) Epoch 914, batch 38, global_batch_idx: 113250, batch size: 31, loss[discriminator_loss=2.603, discriminator_real_loss=1.231, discriminator_fake_loss=1.373, generator_loss=31.84, generator_mel_loss=18.83, generator_kl_loss=1.677, generator_dur_loss=1.621, generator_adv_loss=2.046, generator_feat_match_loss=7.661, over 31.00 samples.], tot_loss[discriminator_loss=2.675, discriminator_real_loss=1.351, discriminator_fake_loss=1.325, generator_loss=29.08, generator_mel_loss=17.75, generator_kl_loss=1.442, generator_dur_loss=1.742, generator_adv_loss=2, generator_feat_match_loss=6.146, over 2287.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 22:15:32,632 INFO [train.py:527] (2/6) Epoch 914, batch 88, global_batch_idx: 113300, batch size: 47, loss[discriminator_loss=2.681, discriminator_real_loss=1.336, discriminator_fake_loss=1.345, generator_loss=29.35, generator_mel_loss=18.11, generator_kl_loss=1.526, generator_dur_loss=1.717, generator_adv_loss=2.117, generator_feat_match_loss=5.876, over 47.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.355, discriminator_fake_loss=1.321, generator_loss=29.11, generator_mel_loss=17.75, generator_kl_loss=1.449, generator_dur_loss=1.738, generator_adv_loss=2.009, generator_feat_match_loss=6.164, over 5131.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 22:17:09,774 INFO [train.py:919] (2/6) Start epoch 915
2024-03-15 22:18:12,882 INFO [train.py:527] (2/6) Epoch 915, batch 14, global_batch_idx: 113350, batch size: 61, loss[discriminator_loss=2.636, discriminator_real_loss=1.297, discriminator_fake_loss=1.339, generator_loss=29.18, generator_mel_loss=17.45, generator_kl_loss=1.437, generator_dur_loss=1.784, generator_adv_loss=2.124, generator_feat_match_loss=6.387, over 61.00 samples.], tot_loss[discriminator_loss=2.664, discriminator_real_loss=1.354, discriminator_fake_loss=1.31, generator_loss=29.02, generator_mel_loss=17.71, generator_kl_loss=1.516, generator_dur_loss=1.75, generator_adv_loss=2.004, generator_feat_match_loss=6.043, over 880.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 22:20:30,748 INFO [train.py:527] (2/6) Epoch 915, batch 64, global_batch_idx: 113400, batch size: 88, loss[discriminator_loss=2.606, discriminator_real_loss=1.279, discriminator_fake_loss=1.327, generator_loss=30.14, generator_mel_loss=18.14, generator_kl_loss=1.388, generator_dur_loss=1.843, generator_adv_loss=1.964, generator_feat_match_loss=6.81, over 88.00 samples.], tot_loss[discriminator_loss=2.661, discriminator_real_loss=1.348, discriminator_fake_loss=1.313, generator_loss=29.12, generator_mel_loss=17.73, generator_kl_loss=1.523, generator_dur_loss=1.737, generator_adv_loss=2, generator_feat_match_loss=6.126, over 3644.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 22:20:30,749 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 22:20:38,829 INFO [train.py:591] (2/6) Epoch 915, validation: discriminator_loss=2.713, discriminator_real_loss=1.421, discriminator_fake_loss=1.292, generator_loss=28.16, generator_mel_loss=18.15, generator_kl_loss=1.297, generator_dur_loss=1.807, generator_adv_loss=1.971, generator_feat_match_loss=4.934, over 100.00 samples.
2024-03-15 22:20:38,830 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 22:22:59,020 INFO [train.py:527] (2/6) Epoch 915, batch 114, global_batch_idx: 113450, batch size: 55, loss[discriminator_loss=2.715, discriminator_real_loss=1.385, discriminator_fake_loss=1.33, generator_loss=28.85, generator_mel_loss=17.46, generator_kl_loss=1.524, generator_dur_loss=1.699, generator_adv_loss=2.102, generator_feat_match_loss=6.072, over 55.00 samples.], tot_loss[discriminator_loss=2.664, discriminator_real_loss=1.349, discriminator_fake_loss=1.316, generator_loss=29.12, generator_mel_loss=17.73, generator_kl_loss=1.489, generator_dur_loss=1.743, generator_adv_loss=2.011, generator_feat_match_loss=6.148, over 6676.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 22:23:24,992 INFO [train.py:919] (2/6) Start epoch 916
2024-03-15 22:25:38,668 INFO [train.py:527] (2/6) Epoch 916, batch 40, global_batch_idx: 113500, batch size: 66, loss[discriminator_loss=2.593, discriminator_real_loss=1.219, discriminator_fake_loss=1.375, generator_loss=29.67, generator_mel_loss=18.04, generator_kl_loss=1.458, generator_dur_loss=1.751, generator_adv_loss=1.982, generator_feat_match_loss=6.432, over 66.00 samples.], tot_loss[discriminator_loss=2.668, discriminator_real_loss=1.351, discriminator_fake_loss=1.317, generator_loss=29.08, generator_mel_loss=17.76, generator_kl_loss=1.475, generator_dur_loss=1.723, generator_adv_loss=2.014, generator_feat_match_loss=6.112, over 2213.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 22:27:58,864 INFO [train.py:527] (2/6) Epoch 916, batch 90, global_batch_idx: 113550, batch size: 96, loss[discriminator_loss=2.651, discriminator_real_loss=1.303, discriminator_fake_loss=1.348, generator_loss=28.42, generator_mel_loss=17.38, generator_kl_loss=1.304, generator_dur_loss=1.838, generator_adv_loss=1.955, generator_feat_match_loss=5.944, over 96.00 samples.], tot_loss[discriminator_loss=2.673, discriminator_real_loss=1.353, discriminator_fake_loss=1.32, generator_loss=29.16, generator_mel_loss=17.77, generator_kl_loss=1.454, generator_dur_loss=1.73, generator_adv_loss=2.009, generator_feat_match_loss=6.201, over 5098.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 22:29:32,347 INFO [train.py:919] (2/6) Start epoch 917
2024-03-15 22:30:40,770 INFO [train.py:527] (2/6) Epoch 917, batch 16, global_batch_idx: 113600, batch size: 61, loss[discriminator_loss=2.718, discriminator_real_loss=1.418, discriminator_fake_loss=1.299, generator_loss=27.56, generator_mel_loss=17.26, generator_kl_loss=1.386, generator_dur_loss=1.732, generator_adv_loss=1.865, generator_feat_match_loss=5.323, over 61.00 samples.], tot_loss[discriminator_loss=2.649, discriminator_real_loss=1.338, discriminator_fake_loss=1.31, generator_loss=29.01, generator_mel_loss=17.67, generator_kl_loss=1.425, generator_dur_loss=1.747, generator_adv_loss=2.03, generator_feat_match_loss=6.137, over 1000.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 22:30:40,771 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 22:30:48,826 INFO [train.py:591] (2/6) Epoch 917, validation: discriminator_loss=2.752, discriminator_real_loss=1.322, discriminator_fake_loss=1.43, generator_loss=28, generator_mel_loss=17.95, generator_kl_loss=1.406, generator_dur_loss=1.809, generator_adv_loss=1.827, generator_feat_match_loss=5.009, over 100.00 samples.
2024-03-15 22:30:48,827 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 22:33:08,166 INFO [train.py:527] (2/6) Epoch 917, batch 66, global_batch_idx: 113650, batch size: 68, loss[discriminator_loss=2.673, discriminator_real_loss=1.359, discriminator_fake_loss=1.314, generator_loss=29.08, generator_mel_loss=17.86, generator_kl_loss=1.363, generator_dur_loss=1.796, generator_adv_loss=1.908, generator_feat_match_loss=6.16, over 68.00 samples.], tot_loss[discriminator_loss=2.678, discriminator_real_loss=1.354, discriminator_fake_loss=1.324, generator_loss=29.09, generator_mel_loss=17.74, generator_kl_loss=1.427, generator_dur_loss=1.746, generator_adv_loss=2.006, generator_feat_match_loss=6.166, over 3856.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 22:35:24,395 INFO [train.py:527] (2/6) Epoch 917, batch 116, global_batch_idx: 113700, batch size: 72, loss[discriminator_loss=2.672, discriminator_real_loss=1.28, discriminator_fake_loss=1.392, generator_loss=28.79, generator_mel_loss=17.5, generator_kl_loss=1.203, generator_dur_loss=1.776, generator_adv_loss=1.952, generator_feat_match_loss=6.361, over 72.00 samples.], tot_loss[discriminator_loss=2.673, discriminator_real_loss=1.35, discriminator_fake_loss=1.324, generator_loss=29.16, generator_mel_loss=17.73, generator_kl_loss=1.441, generator_dur_loss=1.741, generator_adv_loss=2.008, generator_feat_match_loss=6.236, over 6776.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 22:35:45,727 INFO [train.py:919] (2/6) Start epoch 918
2024-03-15 22:38:06,172 INFO [train.py:527] (2/6) Epoch 918, batch 42, global_batch_idx: 113750, batch size: 72, loss[discriminator_loss=2.674, discriminator_real_loss=1.359, discriminator_fake_loss=1.315, generator_loss=28.86, generator_mel_loss=17.69, generator_kl_loss=1.463, generator_dur_loss=1.781, generator_adv_loss=1.876, generator_feat_match_loss=6.045, over 72.00 samples.], tot_loss[discriminator_loss=2.668, discriminator_real_loss=1.347, discriminator_fake_loss=1.322, generator_loss=29.34, generator_mel_loss=17.77, generator_kl_loss=1.446, generator_dur_loss=1.745, generator_adv_loss=2.009, generator_feat_match_loss=6.37, over 2572.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 22:40:23,941 INFO [train.py:527] (2/6) Epoch 918, batch 92, global_batch_idx: 113800, batch size: 66, loss[discriminator_loss=2.697, discriminator_real_loss=1.397, discriminator_fake_loss=1.3, generator_loss=28.45, generator_mel_loss=17.58, generator_kl_loss=1.356, generator_dur_loss=1.779, generator_adv_loss=1.995, generator_feat_match_loss=5.731, over 66.00 samples.], tot_loss[discriminator_loss=2.672, discriminator_real_loss=1.353, discriminator_fake_loss=1.319, generator_loss=29.31, generator_mel_loss=17.76, generator_kl_loss=1.473, generator_dur_loss=1.74, generator_adv_loss=2.019, generator_feat_match_loss=6.311, over 5229.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 22:40:23,943 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 22:40:32,678 INFO [train.py:591] (2/6) Epoch 918, validation: discriminator_loss=2.722, discriminator_real_loss=1.411, discriminator_fake_loss=1.31, generator_loss=27.73, generator_mel_loss=18.28, generator_kl_loss=1.329, generator_dur_loss=1.804, generator_adv_loss=1.903, generator_feat_match_loss=4.414, over 100.00 samples.
2024-03-15 22:40:32,679 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 22:42:01,873 INFO [train.py:919] (2/6) Start epoch 919
2024-03-15 22:43:15,193 INFO [train.py:527] (2/6) Epoch 919, batch 18, global_batch_idx: 113850, batch size: 39, loss[discriminator_loss=2.732, discriminator_real_loss=1.28, discriminator_fake_loss=1.452, generator_loss=29.54, generator_mel_loss=17.82, generator_kl_loss=1.616, generator_dur_loss=1.637, generator_adv_loss=2.039, generator_feat_match_loss=6.425, over 39.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.35, discriminator_fake_loss=1.335, generator_loss=29.4, generator_mel_loss=17.81, generator_kl_loss=1.522, generator_dur_loss=1.717, generator_adv_loss=2.021, generator_feat_match_loss=6.332, over 961.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 22:45:35,733 INFO [train.py:527] (2/6) Epoch 919, batch 68, global_batch_idx: 113900, batch size: 59, loss[discriminator_loss=2.727, discriminator_real_loss=1.38, discriminator_fake_loss=1.348, generator_loss=29.22, generator_mel_loss=18.27, generator_kl_loss=1.377, generator_dur_loss=1.747, generator_adv_loss=2.021, generator_feat_match_loss=5.799, over 59.00 samples.], tot_loss[discriminator_loss=2.679, discriminator_real_loss=1.355, discriminator_fake_loss=1.324, generator_loss=29.18, generator_mel_loss=17.74, generator_kl_loss=1.49, generator_dur_loss=1.722, generator_adv_loss=2.011, generator_feat_match_loss=6.22, over 3724.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 22:47:55,618 INFO [train.py:527] (2/6) Epoch 919, batch 118, global_batch_idx: 113950, batch size: 66, loss[discriminator_loss=2.637, discriminator_real_loss=1.297, discriminator_fake_loss=1.339, generator_loss=29.51, generator_mel_loss=17.83, generator_kl_loss=1.353, generator_dur_loss=1.791, generator_adv_loss=2.079, generator_feat_match_loss=6.461, over 66.00 samples.], tot_loss[discriminator_loss=2.68, discriminator_real_loss=1.355, discriminator_fake_loss=1.324, generator_loss=29.16, generator_mel_loss=17.76, generator_kl_loss=1.486, generator_dur_loss=1.727, generator_adv_loss=2.008, generator_feat_match_loss=6.188, over 6459.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 22:48:11,530 INFO [train.py:919] (2/6) Start epoch 920
2024-03-15 22:50:39,340 INFO [train.py:527] (2/6) Epoch 920, batch 44, global_batch_idx: 114000, batch size: 96, loss[discriminator_loss=2.687, discriminator_real_loss=1.322, discriminator_fake_loss=1.365, generator_loss=28.49, generator_mel_loss=17.67, generator_kl_loss=1.377, generator_dur_loss=1.861, generator_adv_loss=1.968, generator_feat_match_loss=5.606, over 96.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.354, discriminator_fake_loss=1.33, generator_loss=29.18, generator_mel_loss=17.83, generator_kl_loss=1.428, generator_dur_loss=1.753, generator_adv_loss=2.009, generator_feat_match_loss=6.164, over 2636.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 22:50:39,342 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 22:50:47,287 INFO [train.py:591] (2/6) Epoch 920, validation: discriminator_loss=2.653, discriminator_real_loss=1.397, discriminator_fake_loss=1.255, generator_loss=28.07, generator_mel_loss=17.81, generator_kl_loss=1.25, generator_dur_loss=1.811, generator_adv_loss=2.03, generator_feat_match_loss=5.167, over 100.00 samples.
2024-03-15 22:50:47,288 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 22:53:07,371 INFO [train.py:527] (2/6) Epoch 920, batch 94, global_batch_idx: 114050, batch size: 74, loss[discriminator_loss=2.666, discriminator_real_loss=1.378, discriminator_fake_loss=1.288, generator_loss=28.56, generator_mel_loss=17.97, generator_kl_loss=1.253, generator_dur_loss=1.796, generator_adv_loss=1.975, generator_feat_match_loss=5.568, over 74.00 samples.], tot_loss[discriminator_loss=2.678, discriminator_real_loss=1.352, discriminator_fake_loss=1.326, generator_loss=29.14, generator_mel_loss=17.78, generator_kl_loss=1.441, generator_dur_loss=1.743, generator_adv_loss=2.007, generator_feat_match_loss=6.165, over 5371.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 22:54:26,083 INFO [train.py:919] (2/6) Start epoch 921
2024-03-15 22:55:45,845 INFO [train.py:527] (2/6) Epoch 921, batch 20, global_batch_idx: 114100, batch size: 31, loss[discriminator_loss=2.673, discriminator_real_loss=1.35, discriminator_fake_loss=1.323, generator_loss=29.1, generator_mel_loss=18.04, generator_kl_loss=1.545, generator_dur_loss=1.631, generator_adv_loss=2.08, generator_feat_match_loss=5.806, over 31.00 samples.], tot_loss[discriminator_loss=2.693, discriminator_real_loss=1.365, discriminator_fake_loss=1.328, generator_loss=29.17, generator_mel_loss=17.92, generator_kl_loss=1.415, generator_dur_loss=1.752, generator_adv_loss=2.002, generator_feat_match_loss=6.074, over 1164.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 22:58:02,012 INFO [train.py:527] (2/6) Epoch 921, batch 70, global_batch_idx: 114150, batch size: 68, loss[discriminator_loss=2.698, discriminator_real_loss=1.344, discriminator_fake_loss=1.355, generator_loss=29.28, generator_mel_loss=17.54, generator_kl_loss=1.376, generator_dur_loss=1.788, generator_adv_loss=2.115, generator_feat_match_loss=6.466, over 68.00 samples.], tot_loss[discriminator_loss=2.69, discriminator_real_loss=1.361, discriminator_fake_loss=1.329, generator_loss=29.14, generator_mel_loss=17.86, generator_kl_loss=1.417, generator_dur_loss=1.742, generator_adv_loss=2.002, generator_feat_match_loss=6.12, over 3941.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 23:00:22,604 INFO [train.py:527] (2/6) Epoch 921, batch 120, global_batch_idx: 114200, batch size: 96, loss[discriminator_loss=2.701, discriminator_real_loss=1.404, discriminator_fake_loss=1.296, generator_loss=29, generator_mel_loss=17.36, generator_kl_loss=1.234, generator_dur_loss=1.809, generator_adv_loss=2.072, generator_feat_match_loss=6.523, over 96.00 samples.], tot_loss[discriminator_loss=2.688, discriminator_real_loss=1.358, discriminator_fake_loss=1.33, generator_loss=29.18, generator_mel_loss=17.84, generator_kl_loss=1.422, generator_dur_loss=1.742, generator_adv_loss=2.01, generator_feat_match_loss=6.157, over 6689.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 23:00:22,606 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 23:00:31,611 INFO [train.py:591] (2/6) Epoch 921, validation: discriminator_loss=2.693, discriminator_real_loss=1.445, discriminator_fake_loss=1.247, generator_loss=27.78, generator_mel_loss=17.8, generator_kl_loss=1.218, generator_dur_loss=1.817, generator_adv_loss=2.007, generator_feat_match_loss=4.93, over 100.00 samples.
2024-03-15 23:00:31,612 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 23:00:40,782 INFO [train.py:919] (2/6) Start epoch 922
2024-03-15 23:03:11,670 INFO [train.py:527] (2/6) Epoch 922, batch 46, global_batch_idx: 114250, batch size: 72, loss[discriminator_loss=2.655, discriminator_real_loss=1.393, discriminator_fake_loss=1.262, generator_loss=28.94, generator_mel_loss=17.49, generator_kl_loss=1.478, generator_dur_loss=1.802, generator_adv_loss=2.09, generator_feat_match_loss=6.08, over 72.00 samples.], tot_loss[discriminator_loss=2.665, discriminator_real_loss=1.345, discriminator_fake_loss=1.319, generator_loss=29.13, generator_mel_loss=17.72, generator_kl_loss=1.451, generator_dur_loss=1.74, generator_adv_loss=2.017, generator_feat_match_loss=6.204, over 2687.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 23:05:29,935 INFO [train.py:527] (2/6) Epoch 922, batch 96, global_batch_idx: 114300, batch size: 64, loss[discriminator_loss=2.66, discriminator_real_loss=1.332, discriminator_fake_loss=1.329, generator_loss=28.37, generator_mel_loss=17.3, generator_kl_loss=1.419, generator_dur_loss=1.751, generator_adv_loss=2.159, generator_feat_match_loss=5.738, over 64.00 samples.], tot_loss[discriminator_loss=2.673, discriminator_real_loss=1.357, discriminator_fake_loss=1.316, generator_loss=29.03, generator_mel_loss=17.71, generator_kl_loss=1.435, generator_dur_loss=1.739, generator_adv_loss=2.013, generator_feat_match_loss=6.135, over 5460.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 23:06:47,833 INFO [train.py:919] (2/6) Start epoch 923
2024-03-15 23:08:16,172 INFO [train.py:527] (2/6) Epoch 923, batch 22, global_batch_idx: 114350, batch size: 48, loss[discriminator_loss=2.707, discriminator_real_loss=1.355, discriminator_fake_loss=1.352, generator_loss=29.5, generator_mel_loss=17.96, generator_kl_loss=1.401, generator_dur_loss=1.615, generator_adv_loss=2.044, generator_feat_match_loss=6.479, over 48.00 samples.], tot_loss[discriminator_loss=2.687, discriminator_real_loss=1.353, discriminator_fake_loss=1.334, generator_loss=29.16, generator_mel_loss=17.79, generator_kl_loss=1.433, generator_dur_loss=1.741, generator_adv_loss=2.034, generator_feat_match_loss=6.158, over 1410.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 23:10:38,450 INFO [train.py:527] (2/6) Epoch 923, batch 72, global_batch_idx: 114400, batch size: 96, loss[discriminator_loss=2.704, discriminator_real_loss=1.308, discriminator_fake_loss=1.396, generator_loss=28.38, generator_mel_loss=18, generator_kl_loss=1.304, generator_dur_loss=1.819, generator_adv_loss=1.982, generator_feat_match_loss=5.278, over 96.00 samples.], tot_loss[discriminator_loss=2.673, discriminator_real_loss=1.349, discriminator_fake_loss=1.325, generator_loss=29.11, generator_mel_loss=17.75, generator_kl_loss=1.432, generator_dur_loss=1.733, generator_adv_loss=2.027, generator_feat_match_loss=6.165, over 4364.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 23:10:38,452 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 23:10:47,329 INFO [train.py:591] (2/6) Epoch 923, validation: discriminator_loss=2.766, discriminator_real_loss=1.488, discriminator_fake_loss=1.277, generator_loss=28.54, generator_mel_loss=18.39, generator_kl_loss=1.281, generator_dur_loss=1.764, generator_adv_loss=1.994, generator_feat_match_loss=5.106, over 100.00 samples.
2024-03-15 23:10:47,330 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 23:13:02,691 INFO [train.py:527] (2/6) Epoch 923, batch 122, global_batch_idx: 114450, batch size: 36, loss[discriminator_loss=2.7, discriminator_real_loss=1.406, discriminator_fake_loss=1.293, generator_loss=28.8, generator_mel_loss=17.78, generator_kl_loss=1.67, generator_dur_loss=1.671, generator_adv_loss=1.781, generator_feat_match_loss=5.896, over 36.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.354, discriminator_fake_loss=1.322, generator_loss=29.09, generator_mel_loss=17.75, generator_kl_loss=1.431, generator_dur_loss=1.731, generator_adv_loss=2.019, generator_feat_match_loss=6.16, over 7310.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 23:13:07,963 INFO [train.py:919] (2/6) Start epoch 924
2024-03-15 23:15:46,464 INFO [train.py:527] (2/6) Epoch 924, batch 48, global_batch_idx: 114500, batch size: 53, loss[discriminator_loss=2.643, discriminator_real_loss=1.29, discriminator_fake_loss=1.352, generator_loss=29.25, generator_mel_loss=17.64, generator_kl_loss=1.447, generator_dur_loss=1.603, generator_adv_loss=2.03, generator_feat_match_loss=6.534, over 53.00 samples.], tot_loss[discriminator_loss=2.664, discriminator_real_loss=1.35, discriminator_fake_loss=1.314, generator_loss=29.1, generator_mel_loss=17.78, generator_kl_loss=1.422, generator_dur_loss=1.72, generator_adv_loss=2.018, generator_feat_match_loss=6.166, over 2725.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 23:18:06,614 INFO [train.py:527] (2/6) Epoch 924, batch 98, global_batch_idx: 114550, batch size: 25, loss[discriminator_loss=2.66, discriminator_real_loss=1.335, discriminator_fake_loss=1.325, generator_loss=29.9, generator_mel_loss=17.97, generator_kl_loss=1.714, generator_dur_loss=1.566, generator_adv_loss=2.085, generator_feat_match_loss=6.571, over 25.00 samples.], tot_loss[discriminator_loss=2.666, discriminator_real_loss=1.349, discriminator_fake_loss=1.317, generator_loss=29.12, generator_mel_loss=17.76, generator_kl_loss=1.434, generator_dur_loss=1.725, generator_adv_loss=2.012, generator_feat_match_loss=6.187, over 5566.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 23:19:16,058 INFO [train.py:919] (2/6) Start epoch 925
2024-03-15 23:20:43,872 INFO [train.py:527] (2/6) Epoch 925, batch 24, global_batch_idx: 114600, batch size: 55, loss[discriminator_loss=2.678, discriminator_real_loss=1.372, discriminator_fake_loss=1.305, generator_loss=28.79, generator_mel_loss=17.7, generator_kl_loss=1.334, generator_dur_loss=1.674, generator_adv_loss=1.977, generator_feat_match_loss=6.104, over 55.00 samples.], tot_loss[discriminator_loss=2.687, discriminator_real_loss=1.366, discriminator_fake_loss=1.321, generator_loss=29.05, generator_mel_loss=17.7, generator_kl_loss=1.427, generator_dur_loss=1.736, generator_adv_loss=2.004, generator_feat_match_loss=6.19, over 1492.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 23:20:43,874 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 23:20:52,330 INFO [train.py:591] (2/6) Epoch 925, validation: discriminator_loss=2.675, discriminator_real_loss=1.297, discriminator_fake_loss=1.378, generator_loss=27.34, generator_mel_loss=17.87, generator_kl_loss=1.345, generator_dur_loss=1.785, generator_adv_loss=1.806, generator_feat_match_loss=4.529, over 100.00 samples.
2024-03-15 23:20:52,331 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 23:23:12,814 INFO [train.py:527] (2/6) Epoch 925, batch 74, global_batch_idx: 114650, batch size: 62, loss[discriminator_loss=2.734, discriminator_real_loss=1.386, discriminator_fake_loss=1.348, generator_loss=28.02, generator_mel_loss=17.53, generator_kl_loss=1.399, generator_dur_loss=1.704, generator_adv_loss=2.018, generator_feat_match_loss=5.371, over 62.00 samples.], tot_loss[discriminator_loss=2.682, discriminator_real_loss=1.364, discriminator_fake_loss=1.319, generator_loss=29.12, generator_mel_loss=17.74, generator_kl_loss=1.44, generator_dur_loss=1.727, generator_adv_loss=2.009, generator_feat_match_loss=6.199, over 4270.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 23:25:30,347 INFO [train.py:919] (2/6) Start epoch 926
2024-03-15 23:25:55,259 INFO [train.py:527] (2/6) Epoch 926, batch 0, global_batch_idx: 114700, batch size: 50, loss[discriminator_loss=2.612, discriminator_real_loss=1.363, discriminator_fake_loss=1.248, generator_loss=29.21, generator_mel_loss=17.69, generator_kl_loss=1.469, generator_dur_loss=1.686, generator_adv_loss=1.983, generator_feat_match_loss=6.382, over 50.00 samples.], tot_loss[discriminator_loss=2.612, discriminator_real_loss=1.363, discriminator_fake_loss=1.248, generator_loss=29.21, generator_mel_loss=17.69, generator_kl_loss=1.469, generator_dur_loss=1.686, generator_adv_loss=1.983, generator_feat_match_loss=6.382, over 50.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 23:28:12,624 INFO [train.py:527] (2/6) Epoch 926, batch 50, global_batch_idx: 114750, batch size: 16, loss[discriminator_loss=2.661, discriminator_real_loss=1.379, discriminator_fake_loss=1.282, generator_loss=30.54, generator_mel_loss=17.99, generator_kl_loss=1.88, generator_dur_loss=1.55, generator_adv_loss=2.058, generator_feat_match_loss=7.063, over 16.00 samples.], tot_loss[discriminator_loss=2.668, discriminator_real_loss=1.36, discriminator_fake_loss=1.308, generator_loss=29.14, generator_mel_loss=17.69, generator_kl_loss=1.46, generator_dur_loss=1.732, generator_adv_loss=2.029, generator_feat_match_loss=6.232, over 2827.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 23:30:32,404 INFO [train.py:527] (2/6) Epoch 926, batch 100, global_batch_idx: 114800, batch size: 55, loss[discriminator_loss=2.742, discriminator_real_loss=1.398, discriminator_fake_loss=1.344, generator_loss=28.32, generator_mel_loss=17.78, generator_kl_loss=1.479, generator_dur_loss=1.658, generator_adv_loss=1.95, generator_feat_match_loss=5.458, over 55.00 samples.], tot_loss[discriminator_loss=2.678, discriminator_real_loss=1.36, discriminator_fake_loss=1.318, generator_loss=29.08, generator_mel_loss=17.69, generator_kl_loss=1.442, generator_dur_loss=1.73, generator_adv_loss=2.017, generator_feat_match_loss=6.197, over 5835.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 23:30:32,405 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 23:30:41,176 INFO [train.py:591] (2/6) Epoch 926, validation: discriminator_loss=2.776, discriminator_real_loss=1.398, discriminator_fake_loss=1.378, generator_loss=28.2, generator_mel_loss=18.08, generator_kl_loss=1.284, generator_dur_loss=1.779, generator_adv_loss=1.868, generator_feat_match_loss=5.192, over 100.00 samples.
2024-03-15 23:30:41,177 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 23:31:47,057 INFO [train.py:919] (2/6) Start epoch 927
2024-03-15 23:33:20,823 INFO [train.py:527] (2/6) Epoch 927, batch 26, global_batch_idx: 114850, batch size: 14, loss[discriminator_loss=2.602, discriminator_real_loss=1.161, discriminator_fake_loss=1.441, generator_loss=33.26, generator_mel_loss=19.19, generator_kl_loss=1.797, generator_dur_loss=1.571, generator_adv_loss=2.097, generator_feat_match_loss=8.598, over 14.00 samples.], tot_loss[discriminator_loss=2.679, discriminator_real_loss=1.346, discriminator_fake_loss=1.333, generator_loss=29.4, generator_mel_loss=17.81, generator_kl_loss=1.462, generator_dur_loss=1.742, generator_adv_loss=2.024, generator_feat_match_loss=6.365, over 1567.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 23:35:40,888 INFO [train.py:527] (2/6) Epoch 927, batch 76, global_batch_idx: 114900, batch size: 59, loss[discriminator_loss=2.69, discriminator_real_loss=1.346, discriminator_fake_loss=1.344, generator_loss=28.08, generator_mel_loss=17.02, generator_kl_loss=1.442, generator_dur_loss=1.815, generator_adv_loss=2.002, generator_feat_match_loss=5.8, over 59.00 samples.], tot_loss[discriminator_loss=2.673, discriminator_real_loss=1.35, discriminator_fake_loss=1.323, generator_loss=29.25, generator_mel_loss=17.76, generator_kl_loss=1.425, generator_dur_loss=1.752, generator_adv_loss=2.018, generator_feat_match_loss=6.295, over 4586.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 23:37:53,073 INFO [train.py:919] (2/6) Start epoch 928
2024-03-15 23:38:21,873 INFO [train.py:527] (2/6) Epoch 928, batch 2, global_batch_idx: 114950, batch size: 77, loss[discriminator_loss=2.687, discriminator_real_loss=1.418, discriminator_fake_loss=1.269, generator_loss=28.06, generator_mel_loss=17.5, generator_kl_loss=1.405, generator_dur_loss=1.814, generator_adv_loss=1.918, generator_feat_match_loss=5.416, over 77.00 samples.], tot_loss[discriminator_loss=2.651, discriminator_real_loss=1.369, discriminator_fake_loss=1.282, generator_loss=28.87, generator_mel_loss=17.61, generator_kl_loss=1.447, generator_dur_loss=1.785, generator_adv_loss=2.002, generator_feat_match_loss=6.033, over 190.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 23:40:44,053 INFO [train.py:527] (2/6) Epoch 928, batch 52, global_batch_idx: 115000, batch size: 56, loss[discriminator_loss=2.683, discriminator_real_loss=1.463, discriminator_fake_loss=1.22, generator_loss=28.91, generator_mel_loss=17.79, generator_kl_loss=1.544, generator_dur_loss=1.689, generator_adv_loss=2.04, generator_feat_match_loss=5.848, over 56.00 samples.], tot_loss[discriminator_loss=2.673, discriminator_real_loss=1.358, discriminator_fake_loss=1.315, generator_loss=29.08, generator_mel_loss=17.72, generator_kl_loss=1.434, generator_dur_loss=1.752, generator_adv_loss=2.016, generator_feat_match_loss=6.16, over 3119.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 23:40:44,055 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 23:40:52,365 INFO [train.py:591] (2/6) Epoch 928, validation: discriminator_loss=2.757, discriminator_real_loss=1.4, discriminator_fake_loss=1.357, generator_loss=27.1, generator_mel_loss=17.86, generator_kl_loss=1.265, generator_dur_loss=1.808, generator_adv_loss=1.835, generator_feat_match_loss=4.331, over 100.00 samples.
2024-03-15 23:40:52,366 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 23:43:11,610 INFO [train.py:527] (2/6) Epoch 928, batch 102, global_batch_idx: 115050, batch size: 80, loss[discriminator_loss=2.664, discriminator_real_loss=1.345, discriminator_fake_loss=1.319, generator_loss=28.69, generator_mel_loss=17.79, generator_kl_loss=1.287, generator_dur_loss=1.819, generator_adv_loss=1.9, generator_feat_match_loss=5.897, over 80.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.357, discriminator_fake_loss=1.32, generator_loss=29.1, generator_mel_loss=17.73, generator_kl_loss=1.427, generator_dur_loss=1.753, generator_adv_loss=2.028, generator_feat_match_loss=6.169, over 6108.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 23:44:09,500 INFO [train.py:919] (2/6) Start epoch 929
2024-03-15 23:45:49,462 INFO [train.py:527] (2/6) Epoch 929, batch 28, global_batch_idx: 115100, batch size: 61, loss[discriminator_loss=2.697, discriminator_real_loss=1.334, discriminator_fake_loss=1.362, generator_loss=28.75, generator_mel_loss=17.21, generator_kl_loss=1.355, generator_dur_loss=1.714, generator_adv_loss=2.133, generator_feat_match_loss=6.338, over 61.00 samples.], tot_loss[discriminator_loss=2.664, discriminator_real_loss=1.344, discriminator_fake_loss=1.32, generator_loss=29.24, generator_mel_loss=17.75, generator_kl_loss=1.477, generator_dur_loss=1.716, generator_adv_loss=2.024, generator_feat_match_loss=6.265, over 1543.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 23:48:09,923 INFO [train.py:527] (2/6) Epoch 929, batch 78, global_batch_idx: 115150, batch size: 68, loss[discriminator_loss=2.661, discriminator_real_loss=1.355, discriminator_fake_loss=1.306, generator_loss=29.19, generator_mel_loss=18.05, generator_kl_loss=1.424, generator_dur_loss=1.75, generator_adv_loss=1.965, generator_feat_match_loss=5.998, over 68.00 samples.], tot_loss[discriminator_loss=2.669, discriminator_real_loss=1.353, discriminator_fake_loss=1.316, generator_loss=29.07, generator_mel_loss=17.7, generator_kl_loss=1.44, generator_dur_loss=1.735, generator_adv_loss=2.009, generator_feat_match_loss=6.188, over 4418.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 23:50:17,635 INFO [train.py:919] (2/6) Start epoch 930
2024-03-15 23:50:51,615 INFO [train.py:527] (2/6) Epoch 930, batch 4, global_batch_idx: 115200, batch size: 62, loss[discriminator_loss=2.75, discriminator_real_loss=1.446, discriminator_fake_loss=1.304, generator_loss=29.65, generator_mel_loss=17.93, generator_kl_loss=1.441, generator_dur_loss=1.757, generator_adv_loss=1.912, generator_feat_match_loss=6.607, over 62.00 samples.], tot_loss[discriminator_loss=2.699, discriminator_real_loss=1.327, discriminator_fake_loss=1.372, generator_loss=29.16, generator_mel_loss=17.6, generator_kl_loss=1.47, generator_dur_loss=1.73, generator_adv_loss=2.002, generator_feat_match_loss=6.354, over 279.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 23:50:51,617 INFO [train.py:581] (2/6) Computing validation loss
2024-03-15 23:50:59,572 INFO [train.py:591] (2/6) Epoch 930, validation: discriminator_loss=2.644, discriminator_real_loss=1.352, discriminator_fake_loss=1.292, generator_loss=28.36, generator_mel_loss=18.17, generator_kl_loss=1.304, generator_dur_loss=1.819, generator_adv_loss=1.924, generator_feat_match_loss=5.15, over 100.00 samples.
2024-03-15 23:50:59,573 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-15 23:53:20,109 INFO [train.py:527] (2/6) Epoch 930, batch 54, global_batch_idx: 115250, batch size: 58, loss[discriminator_loss=2.651, discriminator_real_loss=1.332, discriminator_fake_loss=1.319, generator_loss=29.57, generator_mel_loss=17.91, generator_kl_loss=1.454, generator_dur_loss=1.715, generator_adv_loss=2.077, generator_feat_match_loss=6.42, over 58.00 samples.], tot_loss[discriminator_loss=2.658, discriminator_real_loss=1.332, discriminator_fake_loss=1.326, generator_loss=29.3, generator_mel_loss=17.77, generator_kl_loss=1.456, generator_dur_loss=1.745, generator_adv_loss=2.03, generator_feat_match_loss=6.295, over 3336.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 23:55:39,477 INFO [train.py:527] (2/6) Epoch 930, batch 104, global_batch_idx: 115300, batch size: 55, loss[discriminator_loss=2.631, discriminator_real_loss=1.306, discriminator_fake_loss=1.324, generator_loss=28.85, generator_mel_loss=17.74, generator_kl_loss=1.395, generator_dur_loss=1.707, generator_adv_loss=2.108, generator_feat_match_loss=5.904, over 55.00 samples.], tot_loss[discriminator_loss=2.661, discriminator_real_loss=1.338, discriminator_fake_loss=1.324, generator_loss=29.28, generator_mel_loss=17.77, generator_kl_loss=1.454, generator_dur_loss=1.741, generator_adv_loss=2.018, generator_feat_match_loss=6.292, over 6349.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-15 23:56:31,643 INFO [train.py:919] (2/6) Start epoch 931
2024-03-15 23:58:20,369 INFO [train.py:527] (2/6) Epoch 931, batch 30, global_batch_idx: 115350, batch size: 45, loss[discriminator_loss=2.711, discriminator_real_loss=1.407, discriminator_fake_loss=1.304, generator_loss=28.53, generator_mel_loss=17.62, generator_kl_loss=1.344, generator_dur_loss=1.675, generator_adv_loss=2.07, generator_feat_match_loss=5.818, over 45.00 samples.], tot_loss[discriminator_loss=2.664, discriminator_real_loss=1.349, discriminator_fake_loss=1.315, generator_loss=29.18, generator_mel_loss=17.73, generator_kl_loss=1.467, generator_dur_loss=1.728, generator_adv_loss=2.019, generator_feat_match_loss=6.236, over 1696.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 00:00:41,225 INFO [train.py:527] (2/6) Epoch 931, batch 80, global_batch_idx: 115400, batch size: 66, loss[discriminator_loss=2.683, discriminator_real_loss=1.413, discriminator_fake_loss=1.27, generator_loss=28.51, generator_mel_loss=17.67, generator_kl_loss=1.432, generator_dur_loss=1.763, generator_adv_loss=2.008, generator_feat_match_loss=5.642, over 66.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.354, discriminator_fake_loss=1.322, generator_loss=29.07, generator_mel_loss=17.72, generator_kl_loss=1.457, generator_dur_loss=1.729, generator_adv_loss=2.006, generator_feat_match_loss=6.156, over 4548.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 00:00:41,226 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 00:00:50,266 INFO [train.py:591] (2/6) Epoch 931, validation: discriminator_loss=2.687, discriminator_real_loss=1.389, discriminator_fake_loss=1.298, generator_loss=27.94, generator_mel_loss=17.9, generator_kl_loss=1.323, generator_dur_loss=1.792, generator_adv_loss=1.908, generator_feat_match_loss=5.023, over 100.00 samples.
2024-03-16 00:00:50,267 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 00:02:49,556 INFO [train.py:919] (2/6) Start epoch 932
2024-03-16 00:03:29,998 INFO [train.py:527] (2/6) Epoch 932, batch 6, global_batch_idx: 115450, batch size: 39, loss[discriminator_loss=2.721, discriminator_real_loss=1.391, discriminator_fake_loss=1.331, generator_loss=28.52, generator_mel_loss=18.1, generator_kl_loss=1.354, generator_dur_loss=1.733, generator_adv_loss=1.894, generator_feat_match_loss=5.439, over 39.00 samples.], tot_loss[discriminator_loss=2.686, discriminator_real_loss=1.391, discriminator_fake_loss=1.294, generator_loss=28.93, generator_mel_loss=17.65, generator_kl_loss=1.502, generator_dur_loss=1.743, generator_adv_loss=2.022, generator_feat_match_loss=6.015, over 343.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 00:05:49,185 INFO [train.py:527] (2/6) Epoch 932, batch 56, global_batch_idx: 115500, batch size: 36, loss[discriminator_loss=2.676, discriminator_real_loss=1.438, discriminator_fake_loss=1.238, generator_loss=29.83, generator_mel_loss=18.08, generator_kl_loss=1.631, generator_dur_loss=1.658, generator_adv_loss=2.078, generator_feat_match_loss=6.385, over 36.00 samples.], tot_loss[discriminator_loss=2.673, discriminator_real_loss=1.355, discriminator_fake_loss=1.318, generator_loss=29.23, generator_mel_loss=17.74, generator_kl_loss=1.469, generator_dur_loss=1.736, generator_adv_loss=2.024, generator_feat_match_loss=6.253, over 3157.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 00:08:05,235 INFO [train.py:527] (2/6) Epoch 932, batch 106, global_batch_idx: 115550, batch size: 45, loss[discriminator_loss=2.756, discriminator_real_loss=1.425, discriminator_fake_loss=1.331, generator_loss=29.48, generator_mel_loss=18.31, generator_kl_loss=1.338, generator_dur_loss=1.68, generator_adv_loss=1.958, generator_feat_match_loss=6.194, over 45.00 samples.], tot_loss[discriminator_loss=2.679, discriminator_real_loss=1.356, discriminator_fake_loss=1.323, generator_loss=29.24, generator_mel_loss=17.75, generator_kl_loss=1.458, generator_dur_loss=1.729, generator_adv_loss=2.017, generator_feat_match_loss=6.281, over 5868.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 00:08:55,170 INFO [train.py:919] (2/6) Start epoch 933
2024-03-16 00:10:46,914 INFO [train.py:527] (2/6) Epoch 933, batch 32, global_batch_idx: 115600, batch size: 62, loss[discriminator_loss=2.695, discriminator_real_loss=1.371, discriminator_fake_loss=1.324, generator_loss=28.32, generator_mel_loss=17.99, generator_kl_loss=1.335, generator_dur_loss=1.731, generator_adv_loss=1.98, generator_feat_match_loss=5.286, over 62.00 samples.], tot_loss[discriminator_loss=2.673, discriminator_real_loss=1.347, discriminator_fake_loss=1.325, generator_loss=28.96, generator_mel_loss=17.65, generator_kl_loss=1.413, generator_dur_loss=1.738, generator_adv_loss=2.013, generator_feat_match_loss=6.138, over 1875.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 00:10:46,915 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 00:10:55,125 INFO [train.py:591] (2/6) Epoch 933, validation: discriminator_loss=2.75, discriminator_real_loss=1.426, discriminator_fake_loss=1.324, generator_loss=28.26, generator_mel_loss=18.06, generator_kl_loss=1.33, generator_dur_loss=1.797, generator_adv_loss=1.905, generator_feat_match_loss=5.164, over 100.00 samples.
2024-03-16 00:10:55,126 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 00:13:11,340 INFO [train.py:527] (2/6) Epoch 933, batch 82, global_batch_idx: 115650, batch size: 44, loss[discriminator_loss=2.719, discriminator_real_loss=1.512, discriminator_fake_loss=1.207, generator_loss=29.4, generator_mel_loss=17.58, generator_kl_loss=1.781, generator_dur_loss=1.683, generator_adv_loss=1.986, generator_feat_match_loss=6.37, over 44.00 samples.], tot_loss[discriminator_loss=2.681, discriminator_real_loss=1.359, discriminator_fake_loss=1.322, generator_loss=29.16, generator_mel_loss=17.71, generator_kl_loss=1.449, generator_dur_loss=1.725, generator_adv_loss=2.017, generator_feat_match_loss=6.258, over 4448.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 00:15:07,548 INFO [train.py:919] (2/6) Start epoch 934
2024-03-16 00:15:53,481 INFO [train.py:527] (2/6) Epoch 934, batch 8, global_batch_idx: 115700, batch size: 48, loss[discriminator_loss=2.685, discriminator_real_loss=1.374, discriminator_fake_loss=1.311, generator_loss=28.77, generator_mel_loss=17.8, generator_kl_loss=1.476, generator_dur_loss=1.676, generator_adv_loss=2.169, generator_feat_match_loss=5.643, over 48.00 samples.], tot_loss[discriminator_loss=2.731, discriminator_real_loss=1.411, discriminator_fake_loss=1.32, generator_loss=29.17, generator_mel_loss=17.84, generator_kl_loss=1.415, generator_dur_loss=1.768, generator_adv_loss=2.058, generator_feat_match_loss=6.095, over 589.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 00:18:14,926 INFO [train.py:527] (2/6) Epoch 934, batch 58, global_batch_idx: 115750, batch size: 77, loss[discriminator_loss=2.684, discriminator_real_loss=1.332, discriminator_fake_loss=1.351, generator_loss=29.54, generator_mel_loss=17.65, generator_kl_loss=1.469, generator_dur_loss=1.839, generator_adv_loss=2.034, generator_feat_match_loss=6.546, over 77.00 samples.], tot_loss[discriminator_loss=2.673, discriminator_real_loss=1.36, discriminator_fake_loss=1.313, generator_loss=29.1, generator_mel_loss=17.68, generator_kl_loss=1.434, generator_dur_loss=1.752, generator_adv_loss=2.021, generator_feat_match_loss=6.212, over 3545.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 00:20:34,063 INFO [train.py:527] (2/6) Epoch 934, batch 108, global_batch_idx: 115800, batch size: 62, loss[discriminator_loss=2.748, discriminator_real_loss=1.346, discriminator_fake_loss=1.402, generator_loss=28.6, generator_mel_loss=17.84, generator_kl_loss=1.492, generator_dur_loss=1.729, generator_adv_loss=1.985, generator_feat_match_loss=5.553, over 62.00 samples.], tot_loss[discriminator_loss=2.68, discriminator_real_loss=1.357, discriminator_fake_loss=1.323, generator_loss=29.11, generator_mel_loss=17.7, generator_kl_loss=1.443, generator_dur_loss=1.756, generator_adv_loss=2.011, generator_feat_match_loss=6.205, over 6589.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 00:20:34,065 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 00:20:42,783 INFO [train.py:591] (2/6) Epoch 934, validation: discriminator_loss=2.725, discriminator_real_loss=1.444, discriminator_fake_loss=1.281, generator_loss=27.39, generator_mel_loss=17.48, generator_kl_loss=1.291, generator_dur_loss=1.817, generator_adv_loss=1.973, generator_feat_match_loss=4.825, over 100.00 samples.
2024-03-16 00:20:42,784 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 00:21:20,632 INFO [train.py:919] (2/6) Start epoch 935
2024-03-16 00:23:20,360 INFO [train.py:527] (2/6) Epoch 935, batch 34, global_batch_idx: 115850, batch size: 52, loss[discriminator_loss=2.65, discriminator_real_loss=1.365, discriminator_fake_loss=1.285, generator_loss=29.7, generator_mel_loss=17.85, generator_kl_loss=1.633, generator_dur_loss=1.685, generator_adv_loss=1.996, generator_feat_match_loss=6.542, over 52.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.347, discriminator_fake_loss=1.33, generator_loss=29.06, generator_mel_loss=17.66, generator_kl_loss=1.474, generator_dur_loss=1.733, generator_adv_loss=2.001, generator_feat_match_loss=6.201, over 1910.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 00:25:38,966 INFO [train.py:527] (2/6) Epoch 935, batch 84, global_batch_idx: 115900, batch size: 17, loss[discriminator_loss=2.65, discriminator_real_loss=1.246, discriminator_fake_loss=1.404, generator_loss=30.95, generator_mel_loss=18.72, generator_kl_loss=1.901, generator_dur_loss=1.5, generator_adv_loss=2.063, generator_feat_match_loss=6.762, over 17.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.348, discriminator_fake_loss=1.328, generator_loss=29.38, generator_mel_loss=17.75, generator_kl_loss=1.456, generator_dur_loss=1.741, generator_adv_loss=2.038, generator_feat_match_loss=6.397, over 4793.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 00:27:27,349 INFO [train.py:919] (2/6) Start epoch 936
2024-03-16 00:28:19,996 INFO [train.py:527] (2/6) Epoch 936, batch 10, global_batch_idx: 115950, batch size: 25, loss[discriminator_loss=2.671, discriminator_real_loss=1.315, discriminator_fake_loss=1.356, generator_loss=30.3, generator_mel_loss=18.07, generator_kl_loss=1.637, generator_dur_loss=1.59, generator_adv_loss=2.022, generator_feat_match_loss=6.986, over 25.00 samples.], tot_loss[discriminator_loss=2.695, discriminator_real_loss=1.351, discriminator_fake_loss=1.344, generator_loss=29.55, generator_mel_loss=17.98, generator_kl_loss=1.478, generator_dur_loss=1.74, generator_adv_loss=2.007, generator_feat_match_loss=6.347, over 610.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 00:30:39,196 INFO [train.py:527] (2/6) Epoch 936, batch 60, global_batch_idx: 116000, batch size: 45, loss[discriminator_loss=2.739, discriminator_real_loss=1.455, discriminator_fake_loss=1.284, generator_loss=28.41, generator_mel_loss=17.42, generator_kl_loss=1.579, generator_dur_loss=1.616, generator_adv_loss=1.882, generator_feat_match_loss=5.912, over 45.00 samples.], tot_loss[discriminator_loss=2.687, discriminator_real_loss=1.362, discriminator_fake_loss=1.326, generator_loss=29.03, generator_mel_loss=17.71, generator_kl_loss=1.462, generator_dur_loss=1.732, generator_adv_loss=1.999, generator_feat_match_loss=6.119, over 3399.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 00:30:39,197 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 00:30:47,171 INFO [train.py:591] (2/6) Epoch 936, validation: discriminator_loss=2.758, discriminator_real_loss=1.362, discriminator_fake_loss=1.396, generator_loss=29.14, generator_mel_loss=18.57, generator_kl_loss=1.275, generator_dur_loss=1.804, generator_adv_loss=1.909, generator_feat_match_loss=5.584, over 100.00 samples.
2024-03-16 00:30:47,172 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 00:33:05,019 INFO [train.py:527] (2/6) Epoch 936, batch 110, global_batch_idx: 116050, batch size: 74, loss[discriminator_loss=2.642, discriminator_real_loss=1.351, discriminator_fake_loss=1.292, generator_loss=30.01, generator_mel_loss=17.68, generator_kl_loss=1.552, generator_dur_loss=1.765, generator_adv_loss=2.048, generator_feat_match_loss=6.962, over 74.00 samples.], tot_loss[discriminator_loss=2.683, discriminator_real_loss=1.357, discriminator_fake_loss=1.326, generator_loss=29.2, generator_mel_loss=17.74, generator_kl_loss=1.471, generator_dur_loss=1.734, generator_adv_loss=2.006, generator_feat_match_loss=6.244, over 6164.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 00:33:40,154 INFO [train.py:919] (2/6) Start epoch 937
2024-03-16 00:35:43,945 INFO [train.py:527] (2/6) Epoch 937, batch 36, global_batch_idx: 116100, batch size: 61, loss[discriminator_loss=2.655, discriminator_real_loss=1.303, discriminator_fake_loss=1.352, generator_loss=28.74, generator_mel_loss=17.66, generator_kl_loss=1.335, generator_dur_loss=1.757, generator_adv_loss=1.913, generator_feat_match_loss=6.074, over 61.00 samples.], tot_loss[discriminator_loss=2.653, discriminator_real_loss=1.338, discriminator_fake_loss=1.315, generator_loss=29.24, generator_mel_loss=17.69, generator_kl_loss=1.468, generator_dur_loss=1.741, generator_adv_loss=2.018, generator_feat_match_loss=6.328, over 2208.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 00:38:02,922 INFO [train.py:527] (2/6) Epoch 937, batch 86, global_batch_idx: 116150, batch size: 66, loss[discriminator_loss=2.657, discriminator_real_loss=1.365, discriminator_fake_loss=1.291, generator_loss=29.06, generator_mel_loss=17.92, generator_kl_loss=1.393, generator_dur_loss=1.751, generator_adv_loss=1.846, generator_feat_match_loss=6.156, over 66.00 samples.], tot_loss[discriminator_loss=2.668, discriminator_real_loss=1.348, discriminator_fake_loss=1.32, generator_loss=29.14, generator_mel_loss=17.71, generator_kl_loss=1.457, generator_dur_loss=1.741, generator_adv_loss=2.018, generator_feat_match_loss=6.217, over 5110.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 00:39:46,189 INFO [train.py:919] (2/6) Start epoch 938
2024-03-16 00:40:43,587 INFO [train.py:527] (2/6) Epoch 938, batch 12, global_batch_idx: 116200, batch size: 14, loss[discriminator_loss=2.584, discriminator_real_loss=1.372, discriminator_fake_loss=1.212, generator_loss=28.94, generator_mel_loss=16.85, generator_kl_loss=1.777, generator_dur_loss=1.612, generator_adv_loss=2.158, generator_feat_match_loss=6.547, over 14.00 samples.], tot_loss[discriminator_loss=2.647, discriminator_real_loss=1.333, discriminator_fake_loss=1.314, generator_loss=29.16, generator_mel_loss=17.67, generator_kl_loss=1.473, generator_dur_loss=1.713, generator_adv_loss=2.025, generator_feat_match_loss=6.275, over 681.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 00:40:43,618 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 00:40:51,534 INFO [train.py:591] (2/6) Epoch 938, validation: discriminator_loss=2.751, discriminator_real_loss=1.432, discriminator_fake_loss=1.319, generator_loss=27.89, generator_mel_loss=18.17, generator_kl_loss=1.323, generator_dur_loss=1.794, generator_adv_loss=1.896, generator_feat_match_loss=4.709, over 100.00 samples.
2024-03-16 00:40:51,535 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 00:43:09,088 INFO [train.py:527] (2/6) Epoch 938, batch 62, global_batch_idx: 116250, batch size: 25, loss[discriminator_loss=2.539, discriminator_real_loss=1.19, discriminator_fake_loss=1.349, generator_loss=30.88, generator_mel_loss=18.22, generator_kl_loss=1.956, generator_dur_loss=1.548, generator_adv_loss=2.036, generator_feat_match_loss=7.118, over 25.00 samples.], tot_loss[discriminator_loss=2.672, discriminator_real_loss=1.348, discriminator_fake_loss=1.324, generator_loss=29.08, generator_mel_loss=17.74, generator_kl_loss=1.434, generator_dur_loss=1.734, generator_adv_loss=2.002, generator_feat_match_loss=6.168, over 3665.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 00:45:29,107 INFO [train.py:527] (2/6) Epoch 938, batch 112, global_batch_idx: 116300, batch size: 45, loss[discriminator_loss=2.755, discriminator_real_loss=1.392, discriminator_fake_loss=1.364, generator_loss=28.03, generator_mel_loss=17.42, generator_kl_loss=1.498, generator_dur_loss=1.675, generator_adv_loss=1.998, generator_feat_match_loss=5.433, over 45.00 samples.], tot_loss[discriminator_loss=2.674, discriminator_real_loss=1.351, discriminator_fake_loss=1.323, generator_loss=29.08, generator_mel_loss=17.71, generator_kl_loss=1.428, generator_dur_loss=1.744, generator_adv_loss=2.008, generator_feat_match_loss=6.191, over 6825.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 00:46:00,922 INFO [train.py:919] (2/6) Start epoch 939
2024-03-16 00:48:11,731 INFO [train.py:527] (2/6) Epoch 939, batch 38, global_batch_idx: 116350, batch size: 55, loss[discriminator_loss=2.587, discriminator_real_loss=1.277, discriminator_fake_loss=1.31, generator_loss=29.82, generator_mel_loss=17.87, generator_kl_loss=1.616, generator_dur_loss=1.657, generator_adv_loss=2.146, generator_feat_match_loss=6.527, over 55.00 samples.], tot_loss[discriminator_loss=2.672, discriminator_real_loss=1.353, discriminator_fake_loss=1.319, generator_loss=28.98, generator_mel_loss=17.63, generator_kl_loss=1.449, generator_dur_loss=1.749, generator_adv_loss=2.012, generator_feat_match_loss=6.134, over 2344.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 00:50:30,539 INFO [train.py:527] (2/6) Epoch 939, batch 88, global_batch_idx: 116400, batch size: 42, loss[discriminator_loss=2.743, discriminator_real_loss=1.393, discriminator_fake_loss=1.35, generator_loss=28.94, generator_mel_loss=18, generator_kl_loss=1.51, generator_dur_loss=1.686, generator_adv_loss=2.011, generator_feat_match_loss=5.74, over 42.00 samples.], tot_loss[discriminator_loss=2.675, discriminator_real_loss=1.354, discriminator_fake_loss=1.321, generator_loss=29.08, generator_mel_loss=17.7, generator_kl_loss=1.434, generator_dur_loss=1.744, generator_adv_loss=2.013, generator_feat_match_loss=6.186, over 5269.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 00:50:30,541 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 00:50:39,489 INFO [train.py:591] (2/6) Epoch 939, validation: discriminator_loss=2.745, discriminator_real_loss=1.466, discriminator_fake_loss=1.279, generator_loss=28.39, generator_mel_loss=18.45, generator_kl_loss=1.304, generator_dur_loss=1.8, generator_adv_loss=1.906, generator_feat_match_loss=4.93, over 100.00 samples.
2024-03-16 00:50:39,490 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 00:52:14,773 INFO [train.py:919] (2/6) Start epoch 940
2024-03-16 00:53:18,587 INFO [train.py:527] (2/6) Epoch 940, batch 14, global_batch_idx: 116450, batch size: 53, loss[discriminator_loss=2.639, discriminator_real_loss=1.303, discriminator_fake_loss=1.335, generator_loss=29.17, generator_mel_loss=18.01, generator_kl_loss=1.431, generator_dur_loss=1.699, generator_adv_loss=2.079, generator_feat_match_loss=5.944, over 53.00 samples.], tot_loss[discriminator_loss=2.671, discriminator_real_loss=1.35, discriminator_fake_loss=1.32, generator_loss=28.87, generator_mel_loss=17.62, generator_kl_loss=1.429, generator_dur_loss=1.709, generator_adv_loss=2.066, generator_feat_match_loss=6.044, over 794.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 00:55:37,649 INFO [train.py:527] (2/6) Epoch 940, batch 64, global_batch_idx: 116500, batch size: 77, loss[discriminator_loss=2.673, discriminator_real_loss=1.348, discriminator_fake_loss=1.325, generator_loss=29.6, generator_mel_loss=17.65, generator_kl_loss=1.473, generator_dur_loss=1.801, generator_adv_loss=2.045, generator_feat_match_loss=6.628, over 77.00 samples.], tot_loss[discriminator_loss=2.666, discriminator_real_loss=1.346, discriminator_fake_loss=1.32, generator_loss=29.13, generator_mel_loss=17.68, generator_kl_loss=1.432, generator_dur_loss=1.741, generator_adv_loss=2.029, generator_feat_match_loss=6.246, over 3674.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 00:57:56,285 INFO [train.py:527] (2/6) Epoch 940, batch 114, global_batch_idx: 116550, batch size: 47, loss[discriminator_loss=2.676, discriminator_real_loss=1.365, discriminator_fake_loss=1.311, generator_loss=29.81, generator_mel_loss=17.5, generator_kl_loss=1.478, generator_dur_loss=1.662, generator_adv_loss=2, generator_feat_match_loss=7.166, over 47.00 samples.], tot_loss[discriminator_loss=2.673, discriminator_real_loss=1.352, discriminator_fake_loss=1.321, generator_loss=29.14, generator_mel_loss=17.68, generator_kl_loss=1.443, generator_dur_loss=1.74, generator_adv_loss=2.028, generator_feat_match_loss=6.245, over 6555.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 00:58:23,721 INFO [train.py:919] (2/6) Start epoch 941
2024-03-16 01:00:37,599 INFO [train.py:527] (2/6) Epoch 941, batch 40, global_batch_idx: 116600, batch size: 58, loss[discriminator_loss=2.703, discriminator_real_loss=1.322, discriminator_fake_loss=1.382, generator_loss=28.88, generator_mel_loss=17.79, generator_kl_loss=1.53, generator_dur_loss=1.718, generator_adv_loss=2.157, generator_feat_match_loss=5.685, over 58.00 samples.], tot_loss[discriminator_loss=2.671, discriminator_real_loss=1.355, discriminator_fake_loss=1.316, generator_loss=29.08, generator_mel_loss=17.72, generator_kl_loss=1.46, generator_dur_loss=1.729, generator_adv_loss=2.012, generator_feat_match_loss=6.159, over 2237.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 01:00:37,601 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 01:00:45,811 INFO [train.py:591] (2/6) Epoch 941, validation: discriminator_loss=2.752, discriminator_real_loss=1.539, discriminator_fake_loss=1.214, generator_loss=28.52, generator_mel_loss=17.67, generator_kl_loss=1.372, generator_dur_loss=1.795, generator_adv_loss=2.107, generator_feat_match_loss=5.573, over 100.00 samples.
2024-03-16 01:00:45,812 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 01:03:04,719 INFO [train.py:527] (2/6) Epoch 941, batch 90, global_batch_idx: 116650, batch size: 31, loss[discriminator_loss=2.672, discriminator_real_loss=1.348, discriminator_fake_loss=1.324, generator_loss=29.51, generator_mel_loss=18.13, generator_kl_loss=1.496, generator_dur_loss=1.63, generator_adv_loss=2.158, generator_feat_match_loss=6.099, over 31.00 samples.], tot_loss[discriminator_loss=2.678, discriminator_real_loss=1.358, discriminator_fake_loss=1.32, generator_loss=29.06, generator_mel_loss=17.71, generator_kl_loss=1.437, generator_dur_loss=1.732, generator_adv_loss=2.009, generator_feat_match_loss=6.173, over 5135.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 01:04:36,284 INFO [train.py:919] (2/6) Start epoch 942
2024-03-16 01:05:45,323 INFO [train.py:527] (2/6) Epoch 942, batch 16, global_batch_idx: 116700, batch size: 88, loss[discriminator_loss=2.64, discriminator_real_loss=1.361, discriminator_fake_loss=1.279, generator_loss=29.77, generator_mel_loss=17.82, generator_kl_loss=1.244, generator_dur_loss=1.842, generator_adv_loss=1.912, generator_feat_match_loss=6.949, over 88.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.347, discriminator_fake_loss=1.329, generator_loss=28.97, generator_mel_loss=17.73, generator_kl_loss=1.402, generator_dur_loss=1.761, generator_adv_loss=1.989, generator_feat_match_loss=6.089, over 1142.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 01:08:05,282 INFO [train.py:527] (2/6) Epoch 942, batch 66, global_batch_idx: 116750, batch size: 62, loss[discriminator_loss=2.667, discriminator_real_loss=1.391, discriminator_fake_loss=1.276, generator_loss=29.67, generator_mel_loss=17.76, generator_kl_loss=1.456, generator_dur_loss=1.755, generator_adv_loss=1.848, generator_feat_match_loss=6.853, over 62.00 samples.], tot_loss[discriminator_loss=2.672, discriminator_real_loss=1.353, discriminator_fake_loss=1.32, generator_loss=29.21, generator_mel_loss=17.77, generator_kl_loss=1.426, generator_dur_loss=1.742, generator_adv_loss=2.006, generator_feat_match_loss=6.267, over 4035.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 01:10:21,041 INFO [train.py:527] (2/6) Epoch 942, batch 116, global_batch_idx: 116800, batch size: 95, loss[discriminator_loss=2.61, discriminator_real_loss=1.347, discriminator_fake_loss=1.263, generator_loss=28.96, generator_mel_loss=17.63, generator_kl_loss=1.226, generator_dur_loss=1.827, generator_adv_loss=1.984, generator_feat_match_loss=6.292, over 95.00 samples.], tot_loss[discriminator_loss=2.672, discriminator_real_loss=1.349, discriminator_fake_loss=1.323, generator_loss=29.22, generator_mel_loss=17.78, generator_kl_loss=1.432, generator_dur_loss=1.741, generator_adv_loss=2.009, generator_feat_match_loss=6.256, over 6792.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 01:10:21,043 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 01:10:29,980 INFO [train.py:591] (2/6) Epoch 942, validation: discriminator_loss=2.664, discriminator_real_loss=1.33, discriminator_fake_loss=1.334, generator_loss=27.31, generator_mel_loss=17.59, generator_kl_loss=1.23, generator_dur_loss=1.826, generator_adv_loss=1.896, generator_feat_match_loss=4.766, over 100.00 samples.
2024-03-16 01:10:29,981 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 01:10:50,988 INFO [train.py:919] (2/6) Start epoch 943
2024-03-16 01:13:12,564 INFO [train.py:527] (2/6) Epoch 943, batch 42, global_batch_idx: 116850, batch size: 42, loss[discriminator_loss=2.683, discriminator_real_loss=1.324, discriminator_fake_loss=1.358, generator_loss=28.84, generator_mel_loss=17.64, generator_kl_loss=1.415, generator_dur_loss=1.682, generator_adv_loss=2.052, generator_feat_match_loss=6.057, over 42.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.353, discriminator_fake_loss=1.331, generator_loss=29.19, generator_mel_loss=17.75, generator_kl_loss=1.423, generator_dur_loss=1.732, generator_adv_loss=2.013, generator_feat_match_loss=6.273, over 2428.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 01:15:30,954 INFO [train.py:527] (2/6) Epoch 943, batch 92, global_batch_idx: 116900, batch size: 31, loss[discriminator_loss=2.678, discriminator_real_loss=1.394, discriminator_fake_loss=1.284, generator_loss=29.34, generator_mel_loss=17.54, generator_kl_loss=1.585, generator_dur_loss=1.619, generator_adv_loss=2.087, generator_feat_match_loss=6.509, over 31.00 samples.], tot_loss[discriminator_loss=2.687, discriminator_real_loss=1.359, discriminator_fake_loss=1.328, generator_loss=29.15, generator_mel_loss=17.72, generator_kl_loss=1.44, generator_dur_loss=1.737, generator_adv_loss=2.023, generator_feat_match_loss=6.224, over 5238.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 01:16:56,692 INFO [train.py:919] (2/6) Start epoch 944
2024-03-16 01:18:10,330 INFO [train.py:527] (2/6) Epoch 944, batch 18, global_batch_idx: 116950, batch size: 17, loss[discriminator_loss=2.693, discriminator_real_loss=1.436, discriminator_fake_loss=1.256, generator_loss=29.49, generator_mel_loss=18.25, generator_kl_loss=1.738, generator_dur_loss=1.572, generator_adv_loss=2.136, generator_feat_match_loss=5.793, over 17.00 samples.], tot_loss[discriminator_loss=2.661, discriminator_real_loss=1.348, discriminator_fake_loss=1.313, generator_loss=29.3, generator_mel_loss=17.73, generator_kl_loss=1.495, generator_dur_loss=1.718, generator_adv_loss=2.026, generator_feat_match_loss=6.331, over 899.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 01:20:29,934 INFO [train.py:527] (2/6) Epoch 944, batch 68, global_batch_idx: 117000, batch size: 80, loss[discriminator_loss=2.672, discriminator_real_loss=1.295, discriminator_fake_loss=1.377, generator_loss=28.25, generator_mel_loss=17.58, generator_kl_loss=1.377, generator_dur_loss=1.799, generator_adv_loss=1.99, generator_feat_match_loss=5.508, over 80.00 samples.], tot_loss[discriminator_loss=2.672, discriminator_real_loss=1.351, discriminator_fake_loss=1.321, generator_loss=29.16, generator_mel_loss=17.68, generator_kl_loss=1.46, generator_dur_loss=1.748, generator_adv_loss=2.024, generator_feat_match_loss=6.246, over 3916.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 01:20:29,935 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 01:20:38,012 INFO [train.py:591] (2/6) Epoch 944, validation: discriminator_loss=2.674, discriminator_real_loss=1.303, discriminator_fake_loss=1.371, generator_loss=28.81, generator_mel_loss=18.27, generator_kl_loss=1.272, generator_dur_loss=1.814, generator_adv_loss=1.948, generator_feat_match_loss=5.504, over 100.00 samples.
2024-03-16 01:20:38,013 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 01:22:56,777 INFO [train.py:527] (2/6) Epoch 944, batch 118, global_batch_idx: 117050, batch size: 45, loss[discriminator_loss=2.796, discriminator_real_loss=1.484, discriminator_fake_loss=1.312, generator_loss=28.36, generator_mel_loss=17.55, generator_kl_loss=1.593, generator_dur_loss=1.723, generator_adv_loss=1.926, generator_feat_match_loss=5.565, over 45.00 samples.], tot_loss[discriminator_loss=2.674, discriminator_real_loss=1.354, discriminator_fake_loss=1.319, generator_loss=29.21, generator_mel_loss=17.74, generator_kl_loss=1.455, generator_dur_loss=1.747, generator_adv_loss=2.018, generator_feat_match_loss=6.248, over 6723.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 01:23:10,549 INFO [train.py:919] (2/6) Start epoch 945
2024-03-16 01:25:37,117 INFO [train.py:527] (2/6) Epoch 945, batch 44, global_batch_idx: 117100, batch size: 25, loss[discriminator_loss=2.536, discriminator_real_loss=1.323, discriminator_fake_loss=1.213, generator_loss=32.12, generator_mel_loss=18.93, generator_kl_loss=1.976, generator_dur_loss=1.505, generator_adv_loss=2.226, generator_feat_match_loss=7.477, over 25.00 samples.], tot_loss[discriminator_loss=2.681, discriminator_real_loss=1.361, discriminator_fake_loss=1.321, generator_loss=29.37, generator_mel_loss=17.8, generator_kl_loss=1.441, generator_dur_loss=1.741, generator_adv_loss=2.011, generator_feat_match_loss=6.379, over 2635.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 01:27:55,845 INFO [train.py:527] (2/6) Epoch 945, batch 94, global_batch_idx: 117150, batch size: 31, loss[discriminator_loss=2.598, discriminator_real_loss=1.197, discriminator_fake_loss=1.401, generator_loss=29.5, generator_mel_loss=18.1, generator_kl_loss=1.695, generator_dur_loss=1.582, generator_adv_loss=2.287, generator_feat_match_loss=5.838, over 31.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.354, discriminator_fake_loss=1.322, generator_loss=29.26, generator_mel_loss=17.77, generator_kl_loss=1.438, generator_dur_loss=1.739, generator_adv_loss=2.02, generator_feat_match_loss=6.298, over 5406.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 01:29:15,169 INFO [train.py:919] (2/6) Start epoch 946
2024-03-16 01:30:35,127 INFO [train.py:527] (2/6) Epoch 946, batch 20, global_batch_idx: 117200, batch size: 68, loss[discriminator_loss=2.654, discriminator_real_loss=1.336, discriminator_fake_loss=1.318, generator_loss=28.69, generator_mel_loss=17.37, generator_kl_loss=1.452, generator_dur_loss=1.719, generator_adv_loss=2.046, generator_feat_match_loss=6.101, over 68.00 samples.], tot_loss[discriminator_loss=2.669, discriminator_real_loss=1.343, discriminator_fake_loss=1.326, generator_loss=29.06, generator_mel_loss=17.7, generator_kl_loss=1.47, generator_dur_loss=1.728, generator_adv_loss=1.993, generator_feat_match_loss=6.165, over 1214.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 01:30:35,129 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 01:30:43,266 INFO [train.py:591] (2/6) Epoch 946, validation: discriminator_loss=2.702, discriminator_real_loss=1.422, discriminator_fake_loss=1.279, generator_loss=27.95, generator_mel_loss=17.8, generator_kl_loss=1.297, generator_dur_loss=1.79, generator_adv_loss=2.012, generator_feat_match_loss=5.047, over 100.00 samples.
2024-03-16 01:30:43,267 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 01:33:02,976 INFO [train.py:527] (2/6) Epoch 946, batch 70, global_batch_idx: 117250, batch size: 66, loss[discriminator_loss=2.654, discriminator_real_loss=1.343, discriminator_fake_loss=1.31, generator_loss=29.11, generator_mel_loss=17.52, generator_kl_loss=1.449, generator_dur_loss=1.76, generator_adv_loss=1.953, generator_feat_match_loss=6.427, over 66.00 samples.], tot_loss[discriminator_loss=2.674, discriminator_real_loss=1.351, discriminator_fake_loss=1.323, generator_loss=28.98, generator_mel_loss=17.71, generator_kl_loss=1.456, generator_dur_loss=1.738, generator_adv_loss=1.988, generator_feat_match_loss=6.089, over 4270.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 01:35:20,505 INFO [train.py:527] (2/6) Epoch 946, batch 120, global_batch_idx: 117300, batch size: 59, loss[discriminator_loss=2.678, discriminator_real_loss=1.314, discriminator_fake_loss=1.364, generator_loss=29.33, generator_mel_loss=17.95, generator_kl_loss=1.315, generator_dur_loss=1.715, generator_adv_loss=2.012, generator_feat_match_loss=6.335, over 59.00 samples.], tot_loss[discriminator_loss=2.673, discriminator_real_loss=1.352, discriminator_fake_loss=1.321, generator_loss=29.09, generator_mel_loss=17.73, generator_kl_loss=1.456, generator_dur_loss=1.732, generator_adv_loss=2, generator_feat_match_loss=6.164, over 7025.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 01:35:30,385 INFO [train.py:919] (2/6) Start epoch 947
2024-03-16 01:38:02,453 INFO [train.py:527] (2/6) Epoch 947, batch 46, global_batch_idx: 117350, batch size: 36, loss[discriminator_loss=2.696, discriminator_real_loss=1.349, discriminator_fake_loss=1.347, generator_loss=28.11, generator_mel_loss=18.07, generator_kl_loss=1.482, generator_dur_loss=1.661, generator_adv_loss=1.908, generator_feat_match_loss=4.995, over 36.00 samples.], tot_loss[discriminator_loss=2.67, discriminator_real_loss=1.357, discriminator_fake_loss=1.313, generator_loss=29.13, generator_mel_loss=17.73, generator_kl_loss=1.428, generator_dur_loss=1.733, generator_adv_loss=2.014, generator_feat_match_loss=6.226, over 2575.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 01:40:21,639 INFO [train.py:527] (2/6) Epoch 947, batch 96, global_batch_idx: 117400, batch size: 83, loss[discriminator_loss=2.62, discriminator_real_loss=1.349, discriminator_fake_loss=1.272, generator_loss=29.76, generator_mel_loss=17.9, generator_kl_loss=1.336, generator_dur_loss=1.828, generator_adv_loss=2.001, generator_feat_match_loss=6.69, over 83.00 samples.], tot_loss[discriminator_loss=2.669, discriminator_real_loss=1.351, discriminator_fake_loss=1.318, generator_loss=29.21, generator_mel_loss=17.74, generator_kl_loss=1.425, generator_dur_loss=1.749, generator_adv_loss=2.009, generator_feat_match_loss=6.286, over 5541.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 01:40:21,641 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 01:40:30,417 INFO [train.py:591] (2/6) Epoch 947, validation: discriminator_loss=2.748, discriminator_real_loss=1.341, discriminator_fake_loss=1.407, generator_loss=28.92, generator_mel_loss=18.29, generator_kl_loss=1.363, generator_dur_loss=1.822, generator_adv_loss=1.87, generator_feat_match_loss=5.571, over 100.00 samples.
2024-03-16 01:40:30,418 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 01:41:46,453 INFO [train.py:919] (2/6) Start epoch 948
2024-03-16 01:43:10,126 INFO [train.py:527] (2/6) Epoch 948, batch 22, global_batch_idx: 117450, batch size: 39, loss[discriminator_loss=2.703, discriminator_real_loss=1.342, discriminator_fake_loss=1.361, generator_loss=29.12, generator_mel_loss=18.42, generator_kl_loss=1.371, generator_dur_loss=1.667, generator_adv_loss=1.935, generator_feat_match_loss=5.722, over 39.00 samples.], tot_loss[discriminator_loss=2.666, discriminator_real_loss=1.344, discriminator_fake_loss=1.322, generator_loss=29.3, generator_mel_loss=17.74, generator_kl_loss=1.429, generator_dur_loss=1.729, generator_adv_loss=2.028, generator_feat_match_loss=6.371, over 1207.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 01:45:27,518 INFO [train.py:527] (2/6) Epoch 948, batch 72, global_batch_idx: 117500, batch size: 88, loss[discriminator_loss=2.706, discriminator_real_loss=1.4, discriminator_fake_loss=1.306, generator_loss=28.84, generator_mel_loss=17.47, generator_kl_loss=1.474, generator_dur_loss=1.836, generator_adv_loss=1.884, generator_feat_match_loss=6.178, over 88.00 samples.], tot_loss[discriminator_loss=2.665, discriminator_real_loss=1.347, discriminator_fake_loss=1.318, generator_loss=29.2, generator_mel_loss=17.74, generator_kl_loss=1.444, generator_dur_loss=1.74, generator_adv_loss=2.017, generator_feat_match_loss=6.257, over 4086.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 01:47:44,902 INFO [train.py:527] (2/6) Epoch 948, batch 122, global_batch_idx: 117550, batch size: 45, loss[discriminator_loss=2.619, discriminator_real_loss=1.386, discriminator_fake_loss=1.234, generator_loss=29.68, generator_mel_loss=17.93, generator_kl_loss=1.559, generator_dur_loss=1.648, generator_adv_loss=2.013, generator_feat_match_loss=6.531, over 45.00 samples.], tot_loss[discriminator_loss=2.666, discriminator_real_loss=1.348, discriminator_fake_loss=1.317, generator_loss=29.24, generator_mel_loss=17.76, generator_kl_loss=1.456, generator_dur_loss=1.741, generator_adv_loss=2.015, generator_feat_match_loss=6.266, over 6860.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 01:47:50,430 INFO [train.py:919] (2/6) Start epoch 949
2024-03-16 01:50:29,815 INFO [train.py:527] (2/6) Epoch 949, batch 48, global_batch_idx: 117600, batch size: 48, loss[discriminator_loss=2.652, discriminator_real_loss=1.388, discriminator_fake_loss=1.264, generator_loss=30.04, generator_mel_loss=17.77, generator_kl_loss=1.473, generator_dur_loss=1.702, generator_adv_loss=2.036, generator_feat_match_loss=7.058, over 48.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.355, discriminator_fake_loss=1.329, generator_loss=29.05, generator_mel_loss=17.68, generator_kl_loss=1.439, generator_dur_loss=1.739, generator_adv_loss=2.006, generator_feat_match_loss=6.179, over 2835.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 01:50:29,816 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 01:50:37,969 INFO [train.py:591] (2/6) Epoch 949, validation: discriminator_loss=2.697, discriminator_real_loss=1.391, discriminator_fake_loss=1.306, generator_loss=28.1, generator_mel_loss=17.84, generator_kl_loss=1.36, generator_dur_loss=1.799, generator_adv_loss=1.956, generator_feat_match_loss=5.15, over 100.00 samples.
2024-03-16 01:50:37,970 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 01:52:58,051 INFO [train.py:527] (2/6) Epoch 949, batch 98, global_batch_idx: 117650, batch size: 70, loss[discriminator_loss=2.646, discriminator_real_loss=1.327, discriminator_fake_loss=1.319, generator_loss=30.65, generator_mel_loss=18.35, generator_kl_loss=1.237, generator_dur_loss=1.814, generator_adv_loss=2.105, generator_feat_match_loss=7.144, over 70.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.354, discriminator_fake_loss=1.33, generator_loss=29.07, generator_mel_loss=17.71, generator_kl_loss=1.427, generator_dur_loss=1.744, generator_adv_loss=2.004, generator_feat_match_loss=6.185, over 5783.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 01:54:07,039 INFO [train.py:919] (2/6) Start epoch 950
2024-03-16 01:55:37,160 INFO [train.py:527] (2/6) Epoch 950, batch 24, global_batch_idx: 117700, batch size: 47, loss[discriminator_loss=2.73, discriminator_real_loss=1.415, discriminator_fake_loss=1.314, generator_loss=28.22, generator_mel_loss=17.52, generator_kl_loss=1.406, generator_dur_loss=1.66, generator_adv_loss=2.04, generator_feat_match_loss=5.592, over 47.00 samples.], tot_loss[discriminator_loss=2.681, discriminator_real_loss=1.36, discriminator_fake_loss=1.321, generator_loss=29.2, generator_mel_loss=17.68, generator_kl_loss=1.454, generator_dur_loss=1.743, generator_adv_loss=2.007, generator_feat_match_loss=6.312, over 1430.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 01:58:01,000 INFO [train.py:527] (2/6) Epoch 950, batch 74, global_batch_idx: 117750, batch size: 45, loss[discriminator_loss=2.686, discriminator_real_loss=1.317, discriminator_fake_loss=1.369, generator_loss=28.48, generator_mel_loss=17.57, generator_kl_loss=1.341, generator_dur_loss=1.731, generator_adv_loss=2.007, generator_feat_match_loss=5.835, over 45.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.36, discriminator_fake_loss=1.316, generator_loss=29.11, generator_mel_loss=17.66, generator_kl_loss=1.429, generator_dur_loss=1.756, generator_adv_loss=2.01, generator_feat_match_loss=6.258, over 4405.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 02:00:19,518 INFO [train.py:919] (2/6) Start epoch 951
2024-03-16 02:00:44,347 INFO [train.py:527] (2/6) Epoch 951, batch 0, global_batch_idx: 117800, batch size: 36, loss[discriminator_loss=2.619, discriminator_real_loss=1.321, discriminator_fake_loss=1.298, generator_loss=29.01, generator_mel_loss=17.44, generator_kl_loss=1.635, generator_dur_loss=1.653, generator_adv_loss=2.127, generator_feat_match_loss=6.16, over 36.00 samples.], tot_loss[discriminator_loss=2.619, discriminator_real_loss=1.321, discriminator_fake_loss=1.298, generator_loss=29.01, generator_mel_loss=17.44, generator_kl_loss=1.635, generator_dur_loss=1.653, generator_adv_loss=2.127, generator_feat_match_loss=6.16, over 36.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 02:00:44,350 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 02:00:52,409 INFO [train.py:591] (2/6) Epoch 951, validation: discriminator_loss=2.731, discriminator_real_loss=1.498, discriminator_fake_loss=1.232, generator_loss=28.27, generator_mel_loss=18.11, generator_kl_loss=1.324, generator_dur_loss=1.81, generator_adv_loss=2.02, generator_feat_match_loss=5.008, over 100.00 samples.
2024-03-16 02:00:52,450 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 02:03:13,033 INFO [train.py:527] (2/6) Epoch 951, batch 50, global_batch_idx: 117850, batch size: 47, loss[discriminator_loss=2.774, discriminator_real_loss=1.412, discriminator_fake_loss=1.363, generator_loss=29.78, generator_mel_loss=17.93, generator_kl_loss=1.496, generator_dur_loss=1.671, generator_adv_loss=2.13, generator_feat_match_loss=6.546, over 47.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.354, discriminator_fake_loss=1.322, generator_loss=29.32, generator_mel_loss=17.8, generator_kl_loss=1.479, generator_dur_loss=1.72, generator_adv_loss=2.036, generator_feat_match_loss=6.282, over 2721.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 02:05:35,409 INFO [train.py:527] (2/6) Epoch 951, batch 100, global_batch_idx: 117900, batch size: 45, loss[discriminator_loss=2.696, discriminator_real_loss=1.475, discriminator_fake_loss=1.221, generator_loss=28.78, generator_mel_loss=18.13, generator_kl_loss=1.614, generator_dur_loss=1.62, generator_adv_loss=1.977, generator_feat_match_loss=5.434, over 45.00 samples.], tot_loss[discriminator_loss=2.674, discriminator_real_loss=1.354, discriminator_fake_loss=1.32, generator_loss=29.21, generator_mel_loss=17.79, generator_kl_loss=1.461, generator_dur_loss=1.734, generator_adv_loss=2.02, generator_feat_match_loss=6.206, over 5636.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 02:06:41,385 INFO [train.py:919] (2/6) Start epoch 952
2024-03-16 02:08:20,300 INFO [train.py:527] (2/6) Epoch 952, batch 26, global_batch_idx: 117950, batch size: 45, loss[discriminator_loss=2.738, discriminator_real_loss=1.278, discriminator_fake_loss=1.46, generator_loss=29.35, generator_mel_loss=17.91, generator_kl_loss=1.557, generator_dur_loss=1.688, generator_adv_loss=2.157, generator_feat_match_loss=6.044, over 45.00 samples.], tot_loss[discriminator_loss=2.677, discriminator_real_loss=1.367, discriminator_fake_loss=1.31, generator_loss=28.98, generator_mel_loss=17.69, generator_kl_loss=1.435, generator_dur_loss=1.738, generator_adv_loss=2.01, generator_feat_match_loss=6.116, over 1664.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 02:10:40,355 INFO [train.py:527] (2/6) Epoch 952, batch 76, global_batch_idx: 118000, batch size: 74, loss[discriminator_loss=2.647, discriminator_real_loss=1.339, discriminator_fake_loss=1.308, generator_loss=29.82, generator_mel_loss=17.93, generator_kl_loss=1.346, generator_dur_loss=1.785, generator_adv_loss=1.993, generator_feat_match_loss=6.77, over 74.00 samples.], tot_loss[discriminator_loss=2.681, discriminator_real_loss=1.363, discriminator_fake_loss=1.318, generator_loss=29.12, generator_mel_loss=17.73, generator_kl_loss=1.44, generator_dur_loss=1.729, generator_adv_loss=2.015, generator_feat_match_loss=6.204, over 4423.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 02:10:40,357 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 02:10:49,138 INFO [train.py:591] (2/6) Epoch 952, validation: discriminator_loss=2.691, discriminator_real_loss=1.407, discriminator_fake_loss=1.284, generator_loss=28.35, generator_mel_loss=17.98, generator_kl_loss=1.225, generator_dur_loss=1.797, generator_adv_loss=1.939, generator_feat_match_loss=5.41, over 100.00 samples.
2024-03-16 02:10:49,139 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 02:13:02,967 INFO [train.py:919] (2/6) Start epoch 953
2024-03-16 02:13:33,406 INFO [train.py:527] (2/6) Epoch 953, batch 2, global_batch_idx: 118050, batch size: 39, loss[discriminator_loss=2.688, discriminator_real_loss=1.298, discriminator_fake_loss=1.391, generator_loss=31.57, generator_mel_loss=18.23, generator_kl_loss=1.556, generator_dur_loss=1.721, generator_adv_loss=2.031, generator_feat_match_loss=8.025, over 39.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.333, discriminator_fake_loss=1.352, generator_loss=30.42, generator_mel_loss=18.01, generator_kl_loss=1.464, generator_dur_loss=1.765, generator_adv_loss=2.008, generator_feat_match_loss=7.175, over 186.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 02:15:54,579 INFO [train.py:527] (2/6) Epoch 953, batch 52, global_batch_idx: 118100, batch size: 64, loss[discriminator_loss=2.668, discriminator_real_loss=1.267, discriminator_fake_loss=1.401, generator_loss=29.73, generator_mel_loss=17.64, generator_kl_loss=1.371, generator_dur_loss=1.728, generator_adv_loss=2.032, generator_feat_match_loss=6.968, over 64.00 samples.], tot_loss[discriminator_loss=2.669, discriminator_real_loss=1.349, discriminator_fake_loss=1.32, generator_loss=29.36, generator_mel_loss=17.76, generator_kl_loss=1.425, generator_dur_loss=1.748, generator_adv_loss=2.014, generator_feat_match_loss=6.419, over 3227.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 02:18:17,806 INFO [train.py:527] (2/6) Epoch 953, batch 102, global_batch_idx: 118150, batch size: 72, loss[discriminator_loss=2.621, discriminator_real_loss=1.294, discriminator_fake_loss=1.326, generator_loss=29.52, generator_mel_loss=17.81, generator_kl_loss=1.274, generator_dur_loss=1.843, generator_adv_loss=2.142, generator_feat_match_loss=6.454, over 72.00 samples.], tot_loss[discriminator_loss=2.671, discriminator_real_loss=1.35, discriminator_fake_loss=1.322, generator_loss=29.32, generator_mel_loss=17.74, generator_kl_loss=1.43, generator_dur_loss=1.752, generator_adv_loss=2.017, generator_feat_match_loss=6.379, over 6120.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 02:19:16,685 INFO [train.py:919] (2/6) Start epoch 954
2024-03-16 02:21:03,222 INFO [train.py:527] (2/6) Epoch 954, batch 28, global_batch_idx: 118200, batch size: 61, loss[discriminator_loss=2.717, discriminator_real_loss=1.326, discriminator_fake_loss=1.392, generator_loss=29.75, generator_mel_loss=18.24, generator_kl_loss=1.485, generator_dur_loss=1.741, generator_adv_loss=2.033, generator_feat_match_loss=6.25, over 61.00 samples.], tot_loss[discriminator_loss=2.669, discriminator_real_loss=1.359, discriminator_fake_loss=1.31, generator_loss=29.19, generator_mel_loss=17.81, generator_kl_loss=1.468, generator_dur_loss=1.722, generator_adv_loss=2.008, generator_feat_match_loss=6.189, over 1554.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 02:21:03,224 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 02:21:11,359 INFO [train.py:591] (2/6) Epoch 954, validation: discriminator_loss=2.663, discriminator_real_loss=1.387, discriminator_fake_loss=1.276, generator_loss=27.74, generator_mel_loss=17.97, generator_kl_loss=1.348, generator_dur_loss=1.821, generator_adv_loss=1.95, generator_feat_match_loss=4.657, over 100.00 samples.
2024-03-16 02:21:11,360 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 02:23:33,027 INFO [train.py:527] (2/6) Epoch 954, batch 78, global_batch_idx: 118250, batch size: 53, loss[discriminator_loss=2.75, discriminator_real_loss=1.242, discriminator_fake_loss=1.509, generator_loss=29.27, generator_mel_loss=17.84, generator_kl_loss=1.52, generator_dur_loss=1.691, generator_adv_loss=2.204, generator_feat_match_loss=6.01, over 53.00 samples.], tot_loss[discriminator_loss=2.664, discriminator_real_loss=1.352, discriminator_fake_loss=1.312, generator_loss=29.28, generator_mel_loss=17.76, generator_kl_loss=1.464, generator_dur_loss=1.738, generator_adv_loss=2.009, generator_feat_match_loss=6.313, over 4357.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 02:25:41,907 INFO [train.py:919] (2/6) Start epoch 955
2024-03-16 02:26:18,652 INFO [train.py:527] (2/6) Epoch 955, batch 4, global_batch_idx: 118300, batch size: 80, loss[discriminator_loss=2.701, discriminator_real_loss=1.295, discriminator_fake_loss=1.406, generator_loss=29.46, generator_mel_loss=18, generator_kl_loss=1.445, generator_dur_loss=1.803, generator_adv_loss=2.013, generator_feat_match_loss=6.193, over 80.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.341, discriminator_fake_loss=1.343, generator_loss=29.25, generator_mel_loss=17.79, generator_kl_loss=1.446, generator_dur_loss=1.753, generator_adv_loss=1.995, generator_feat_match_loss=6.263, over 301.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 02:28:40,850 INFO [train.py:527] (2/6) Epoch 955, batch 54, global_batch_idx: 118350, batch size: 48, loss[discriminator_loss=2.651, discriminator_real_loss=1.356, discriminator_fake_loss=1.295, generator_loss=29.36, generator_mel_loss=17.63, generator_kl_loss=1.503, generator_dur_loss=1.699, generator_adv_loss=2.139, generator_feat_match_loss=6.398, over 48.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.345, discriminator_fake_loss=1.331, generator_loss=29.19, generator_mel_loss=17.72, generator_kl_loss=1.439, generator_dur_loss=1.752, generator_adv_loss=2.01, generator_feat_match_loss=6.272, over 3289.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 02:31:04,368 INFO [train.py:527] (2/6) Epoch 955, batch 104, global_batch_idx: 118400, batch size: 68, loss[discriminator_loss=2.688, discriminator_real_loss=1.389, discriminator_fake_loss=1.299, generator_loss=29.01, generator_mel_loss=17.8, generator_kl_loss=1.376, generator_dur_loss=1.82, generator_adv_loss=2.005, generator_feat_match_loss=6.011, over 68.00 samples.], tot_loss[discriminator_loss=2.679, discriminator_real_loss=1.349, discriminator_fake_loss=1.33, generator_loss=29.23, generator_mel_loss=17.74, generator_kl_loss=1.447, generator_dur_loss=1.75, generator_adv_loss=2.004, generator_feat_match_loss=6.287, over 6119.00 samples.], cur_lr_g: 1.78e-04, cur_lr_d: 1.78e-04, 
2024-03-16 02:31:04,369 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 02:31:13,205 INFO [train.py:591] (2/6) Epoch 955, validation: discriminator_loss=2.737, discriminator_real_loss=1.437, discriminator_fake_loss=1.3, generator_loss=28.33, generator_mel_loss=17.99, generator_kl_loss=1.248, generator_dur_loss=1.814, generator_adv_loss=2.029, generator_feat_match_loss=5.248, over 100.00 samples.
2024-03-16 02:31:13,205 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 02:32:06,066 INFO [train.py:919] (2/6) Start epoch 956
2024-03-16 02:33:54,962 INFO [train.py:527] (2/6) Epoch 956, batch 30, global_batch_idx: 118450, batch size: 66, loss[discriminator_loss=2.636, discriminator_real_loss=1.356, discriminator_fake_loss=1.28, generator_loss=29.47, generator_mel_loss=18.17, generator_kl_loss=1.496, generator_dur_loss=1.722, generator_adv_loss=2.021, generator_feat_match_loss=6.053, over 66.00 samples.], tot_loss[discriminator_loss=2.669, discriminator_real_loss=1.352, discriminator_fake_loss=1.317, generator_loss=29.38, generator_mel_loss=17.83, generator_kl_loss=1.453, generator_dur_loss=1.742, generator_adv_loss=2.029, generator_feat_match_loss=6.321, over 1719.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 02:36:16,795 INFO [train.py:527] (2/6) Epoch 956, batch 80, global_batch_idx: 118500, batch size: 16, loss[discriminator_loss=2.572, discriminator_real_loss=1.415, discriminator_fake_loss=1.157, generator_loss=30.85, generator_mel_loss=18.15, generator_kl_loss=1.911, generator_dur_loss=1.541, generator_adv_loss=2.138, generator_feat_match_loss=7.106, over 16.00 samples.], tot_loss[discriminator_loss=2.673, discriminator_real_loss=1.353, discriminator_fake_loss=1.32, generator_loss=29.24, generator_mel_loss=17.78, generator_kl_loss=1.456, generator_dur_loss=1.742, generator_adv_loss=2.017, generator_feat_match_loss=6.248, over 4649.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 02:38:19,743 INFO [train.py:919] (2/6) Start epoch 957
2024-03-16 02:39:00,508 INFO [train.py:527] (2/6) Epoch 957, batch 6, global_batch_idx: 118550, batch size: 66, loss[discriminator_loss=2.664, discriminator_real_loss=1.284, discriminator_fake_loss=1.38, generator_loss=28.71, generator_mel_loss=17.81, generator_kl_loss=1.425, generator_dur_loss=1.729, generator_adv_loss=2.031, generator_feat_match_loss=5.713, over 66.00 samples.], tot_loss[discriminator_loss=2.683, discriminator_real_loss=1.354, discriminator_fake_loss=1.329, generator_loss=29, generator_mel_loss=17.74, generator_kl_loss=1.484, generator_dur_loss=1.727, generator_adv_loss=1.988, generator_feat_match_loss=6.063, over 397.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 02:41:20,816 INFO [train.py:527] (2/6) Epoch 957, batch 56, global_batch_idx: 118600, batch size: 66, loss[discriminator_loss=2.67, discriminator_real_loss=1.396, discriminator_fake_loss=1.274, generator_loss=28.67, generator_mel_loss=17.16, generator_kl_loss=1.391, generator_dur_loss=1.775, generator_adv_loss=2.067, generator_feat_match_loss=6.277, over 66.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.363, discriminator_fake_loss=1.313, generator_loss=29.04, generator_mel_loss=17.72, generator_kl_loss=1.443, generator_dur_loss=1.742, generator_adv_loss=2.012, generator_feat_match_loss=6.127, over 3254.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 02:41:20,817 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 02:41:28,896 INFO [train.py:591] (2/6) Epoch 957, validation: discriminator_loss=2.701, discriminator_real_loss=1.379, discriminator_fake_loss=1.321, generator_loss=28.3, generator_mel_loss=18.2, generator_kl_loss=1.215, generator_dur_loss=1.81, generator_adv_loss=1.93, generator_feat_match_loss=5.143, over 100.00 samples.
2024-03-16 02:41:28,897 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 02:43:50,885 INFO [train.py:527] (2/6) Epoch 957, batch 106, global_batch_idx: 118650, batch size: 70, loss[discriminator_loss=2.676, discriminator_real_loss=1.267, discriminator_fake_loss=1.409, generator_loss=29.2, generator_mel_loss=17.53, generator_kl_loss=1.338, generator_dur_loss=1.78, generator_adv_loss=2.004, generator_feat_match_loss=6.545, over 70.00 samples.], tot_loss[discriminator_loss=2.678, discriminator_real_loss=1.359, discriminator_fake_loss=1.319, generator_loss=29.09, generator_mel_loss=17.71, generator_kl_loss=1.457, generator_dur_loss=1.742, generator_adv_loss=2.009, generator_feat_match_loss=6.166, over 6044.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 02:44:40,664 INFO [train.py:919] (2/6) Start epoch 958
2024-03-16 02:46:36,130 INFO [train.py:527] (2/6) Epoch 958, batch 32, global_batch_idx: 118700, batch size: 44, loss[discriminator_loss=2.726, discriminator_real_loss=1.386, discriminator_fake_loss=1.34, generator_loss=27.37, generator_mel_loss=17.15, generator_kl_loss=1.432, generator_dur_loss=1.725, generator_adv_loss=2.023, generator_feat_match_loss=5.046, over 44.00 samples.], tot_loss[discriminator_loss=2.666, discriminator_real_loss=1.347, discriminator_fake_loss=1.32, generator_loss=29.11, generator_mel_loss=17.7, generator_kl_loss=1.425, generator_dur_loss=1.732, generator_adv_loss=2.045, generator_feat_match_loss=6.203, over 1866.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 02:49:02,426 INFO [train.py:527] (2/6) Epoch 958, batch 82, global_batch_idx: 118750, batch size: 66, loss[discriminator_loss=2.718, discriminator_real_loss=1.338, discriminator_fake_loss=1.38, generator_loss=29.3, generator_mel_loss=17.54, generator_kl_loss=1.362, generator_dur_loss=1.769, generator_adv_loss=2.004, generator_feat_match_loss=6.627, over 66.00 samples.], tot_loss[discriminator_loss=2.663, discriminator_real_loss=1.347, discriminator_fake_loss=1.316, generator_loss=29.18, generator_mel_loss=17.69, generator_kl_loss=1.438, generator_dur_loss=1.743, generator_adv_loss=2.032, generator_feat_match_loss=6.28, over 4746.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 02:50:53,988 INFO [train.py:919] (2/6) Start epoch 959
2024-03-16 02:51:42,576 INFO [train.py:527] (2/6) Epoch 959, batch 8, global_batch_idx: 118800, batch size: 58, loss[discriminator_loss=2.685, discriminator_real_loss=1.296, discriminator_fake_loss=1.389, generator_loss=29.88, generator_mel_loss=17.93, generator_kl_loss=1.452, generator_dur_loss=1.704, generator_adv_loss=1.936, generator_feat_match_loss=6.865, over 58.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.368, discriminator_fake_loss=1.316, generator_loss=29.02, generator_mel_loss=17.63, generator_kl_loss=1.416, generator_dur_loss=1.786, generator_adv_loss=1.997, generator_feat_match_loss=6.187, over 578.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 02:51:42,578 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 02:51:50,405 INFO [train.py:591] (2/6) Epoch 959, validation: discriminator_loss=2.75, discriminator_real_loss=1.37, discriminator_fake_loss=1.381, generator_loss=27.2, generator_mel_loss=17.62, generator_kl_loss=1.332, generator_dur_loss=1.811, generator_adv_loss=1.8, generator_feat_match_loss=4.637, over 100.00 samples.
2024-03-16 02:51:50,410 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 02:54:11,265 INFO [train.py:527] (2/6) Epoch 959, batch 58, global_batch_idx: 118850, batch size: 96, loss[discriminator_loss=2.67, discriminator_real_loss=1.385, discriminator_fake_loss=1.285, generator_loss=28.57, generator_mel_loss=17.65, generator_kl_loss=1.49, generator_dur_loss=1.872, generator_adv_loss=1.902, generator_feat_match_loss=5.663, over 96.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.357, discriminator_fake_loss=1.327, generator_loss=29.18, generator_mel_loss=17.75, generator_kl_loss=1.438, generator_dur_loss=1.761, generator_adv_loss=2, generator_feat_match_loss=6.227, over 3542.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 02:56:33,451 INFO [train.py:527] (2/6) Epoch 959, batch 108, global_batch_idx: 118900, batch size: 64, loss[discriminator_loss=2.715, discriminator_real_loss=1.354, discriminator_fake_loss=1.361, generator_loss=29.04, generator_mel_loss=17.64, generator_kl_loss=1.498, generator_dur_loss=1.725, generator_adv_loss=1.958, generator_feat_match_loss=6.217, over 64.00 samples.], tot_loss[discriminator_loss=2.683, discriminator_real_loss=1.358, discriminator_fake_loss=1.325, generator_loss=29.13, generator_mel_loss=17.73, generator_kl_loss=1.445, generator_dur_loss=1.753, generator_adv_loss=2.005, generator_feat_match_loss=6.192, over 6328.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 02:57:14,927 INFO [train.py:919] (2/6) Start epoch 960
2024-03-16 02:59:14,287 INFO [train.py:527] (2/6) Epoch 960, batch 34, global_batch_idx: 118950, batch size: 88, loss[discriminator_loss=2.643, discriminator_real_loss=1.302, discriminator_fake_loss=1.341, generator_loss=29.1, generator_mel_loss=17.57, generator_kl_loss=1.302, generator_dur_loss=1.846, generator_adv_loss=2.029, generator_feat_match_loss=6.351, over 88.00 samples.], tot_loss[discriminator_loss=2.661, discriminator_real_loss=1.354, discriminator_fake_loss=1.307, generator_loss=29.57, generator_mel_loss=17.76, generator_kl_loss=1.477, generator_dur_loss=1.713, generator_adv_loss=2.109, generator_feat_match_loss=6.515, over 1698.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 03:01:36,106 INFO [train.py:527] (2/6) Epoch 960, batch 84, global_batch_idx: 119000, batch size: 25, loss[discriminator_loss=2.624, discriminator_real_loss=1.33, discriminator_fake_loss=1.294, generator_loss=29.67, generator_mel_loss=17.79, generator_kl_loss=1.957, generator_dur_loss=1.567, generator_adv_loss=2.113, generator_feat_match_loss=6.243, over 25.00 samples.], tot_loss[discriminator_loss=2.66, discriminator_real_loss=1.352, discriminator_fake_loss=1.309, generator_loss=29.32, generator_mel_loss=17.69, generator_kl_loss=1.464, generator_dur_loss=1.73, generator_adv_loss=2.05, generator_feat_match_loss=6.389, over 4527.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 03:01:36,107 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 03:01:43,957 INFO [train.py:591] (2/6) Epoch 960, validation: discriminator_loss=2.745, discriminator_real_loss=1.395, discriminator_fake_loss=1.35, generator_loss=28.7, generator_mel_loss=18.48, generator_kl_loss=1.318, generator_dur_loss=1.817, generator_adv_loss=1.916, generator_feat_match_loss=5.172, over 100.00 samples.
2024-03-16 03:01:43,958 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 03:03:35,920 INFO [train.py:919] (2/6) Start epoch 961
2024-03-16 03:04:32,350 INFO [train.py:527] (2/6) Epoch 961, batch 10, global_batch_idx: 119050, batch size: 55, loss[discriminator_loss=2.659, discriminator_real_loss=1.327, discriminator_fake_loss=1.333, generator_loss=30.36, generator_mel_loss=18.17, generator_kl_loss=1.289, generator_dur_loss=1.695, generator_adv_loss=2.073, generator_feat_match_loss=7.13, over 55.00 samples.], tot_loss[discriminator_loss=2.68, discriminator_real_loss=1.369, discriminator_fake_loss=1.312, generator_loss=29.04, generator_mel_loss=17.57, generator_kl_loss=1.417, generator_dur_loss=1.739, generator_adv_loss=2.039, generator_feat_match_loss=6.278, over 618.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 03:06:51,796 INFO [train.py:527] (2/6) Epoch 961, batch 60, global_batch_idx: 119100, batch size: 96, loss[discriminator_loss=2.581, discriminator_real_loss=1.238, discriminator_fake_loss=1.342, generator_loss=30.4, generator_mel_loss=17.91, generator_kl_loss=1.267, generator_dur_loss=1.863, generator_adv_loss=2.219, generator_feat_match_loss=7.142, over 96.00 samples.], tot_loss[discriminator_loss=2.674, discriminator_real_loss=1.355, discriminator_fake_loss=1.319, generator_loss=29.01, generator_mel_loss=17.65, generator_kl_loss=1.412, generator_dur_loss=1.746, generator_adv_loss=2.016, generator_feat_match_loss=6.19, over 3570.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 03:09:12,452 INFO [train.py:527] (2/6) Epoch 961, batch 110, global_batch_idx: 119150, batch size: 52, loss[discriminator_loss=2.675, discriminator_real_loss=1.414, discriminator_fake_loss=1.261, generator_loss=29.95, generator_mel_loss=18.4, generator_kl_loss=1.649, generator_dur_loss=1.661, generator_adv_loss=2.153, generator_feat_match_loss=6.087, over 52.00 samples.], tot_loss[discriminator_loss=2.677, discriminator_real_loss=1.356, discriminator_fake_loss=1.32, generator_loss=29.15, generator_mel_loss=17.71, generator_kl_loss=1.432, generator_dur_loss=1.749, generator_adv_loss=2.013, generator_feat_match_loss=6.24, over 6551.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 03:09:50,800 INFO [train.py:919] (2/6) Start epoch 962
2024-03-16 03:11:56,374 INFO [train.py:527] (2/6) Epoch 962, batch 36, global_batch_idx: 119200, batch size: 74, loss[discriminator_loss=2.689, discriminator_real_loss=1.281, discriminator_fake_loss=1.408, generator_loss=29.18, generator_mel_loss=17.59, generator_kl_loss=1.455, generator_dur_loss=1.751, generator_adv_loss=1.948, generator_feat_match_loss=6.438, over 74.00 samples.], tot_loss[discriminator_loss=2.666, discriminator_real_loss=1.343, discriminator_fake_loss=1.323, generator_loss=29.24, generator_mel_loss=17.69, generator_kl_loss=1.462, generator_dur_loss=1.725, generator_adv_loss=2.019, generator_feat_match_loss=6.345, over 2074.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 03:11:56,376 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 03:12:04,407 INFO [train.py:591] (2/6) Epoch 962, validation: discriminator_loss=2.732, discriminator_real_loss=1.453, discriminator_fake_loss=1.279, generator_loss=27.79, generator_mel_loss=17.87, generator_kl_loss=1.245, generator_dur_loss=1.798, generator_adv_loss=1.95, generator_feat_match_loss=4.929, over 100.00 samples.
2024-03-16 03:12:04,408 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 03:14:22,638 INFO [train.py:527] (2/6) Epoch 962, batch 86, global_batch_idx: 119250, batch size: 64, loss[discriminator_loss=2.738, discriminator_real_loss=1.371, discriminator_fake_loss=1.366, generator_loss=29.17, generator_mel_loss=17.73, generator_kl_loss=1.372, generator_dur_loss=1.755, generator_adv_loss=2.045, generator_feat_match_loss=6.27, over 64.00 samples.], tot_loss[discriminator_loss=2.667, discriminator_real_loss=1.348, discriminator_fake_loss=1.319, generator_loss=29.1, generator_mel_loss=17.69, generator_kl_loss=1.447, generator_dur_loss=1.727, generator_adv_loss=2.024, generator_feat_match_loss=6.213, over 4850.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 03:16:10,030 INFO [train.py:919] (2/6) Start epoch 963
2024-03-16 03:17:08,119 INFO [train.py:527] (2/6) Epoch 963, batch 12, global_batch_idx: 119300, batch size: 31, loss[discriminator_loss=2.72, discriminator_real_loss=1.38, discriminator_fake_loss=1.341, generator_loss=27.64, generator_mel_loss=17.29, generator_kl_loss=1.503, generator_dur_loss=1.64, generator_adv_loss=1.999, generator_feat_match_loss=5.206, over 31.00 samples.], tot_loss[discriminator_loss=2.681, discriminator_real_loss=1.349, discriminator_fake_loss=1.332, generator_loss=29.59, generator_mel_loss=17.76, generator_kl_loss=1.495, generator_dur_loss=1.687, generator_adv_loss=2.01, generator_feat_match_loss=6.633, over 633.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 03:19:29,421 INFO [train.py:527] (2/6) Epoch 963, batch 62, global_batch_idx: 119350, batch size: 48, loss[discriminator_loss=2.65, discriminator_real_loss=1.349, discriminator_fake_loss=1.301, generator_loss=29.12, generator_mel_loss=17.65, generator_kl_loss=1.402, generator_dur_loss=1.681, generator_adv_loss=2.134, generator_feat_match_loss=6.254, over 48.00 samples.], tot_loss[discriminator_loss=2.667, discriminator_real_loss=1.351, discriminator_fake_loss=1.316, generator_loss=29.29, generator_mel_loss=17.67, generator_kl_loss=1.451, generator_dur_loss=1.72, generator_adv_loss=2.025, generator_feat_match_loss=6.421, over 3420.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 03:21:49,917 INFO [train.py:527] (2/6) Epoch 963, batch 112, global_batch_idx: 119400, batch size: 59, loss[discriminator_loss=2.651, discriminator_real_loss=1.459, discriminator_fake_loss=1.191, generator_loss=28.96, generator_mel_loss=17.84, generator_kl_loss=1.415, generator_dur_loss=1.696, generator_adv_loss=2.093, generator_feat_match_loss=5.914, over 59.00 samples.], tot_loss[discriminator_loss=2.669, discriminator_real_loss=1.348, discriminator_fake_loss=1.321, generator_loss=29.29, generator_mel_loss=17.74, generator_kl_loss=1.433, generator_dur_loss=1.727, generator_adv_loss=2.022, generator_feat_match_loss=6.368, over 6361.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 03:21:49,918 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 03:21:59,012 INFO [train.py:591] (2/6) Epoch 963, validation: discriminator_loss=2.679, discriminator_real_loss=1.417, discriminator_fake_loss=1.263, generator_loss=27.53, generator_mel_loss=17.95, generator_kl_loss=1.161, generator_dur_loss=1.807, generator_adv_loss=1.98, generator_feat_match_loss=4.633, over 100.00 samples.
2024-03-16 03:21:59,012 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 03:22:29,963 INFO [train.py:919] (2/6) Start epoch 964
2024-03-16 03:24:45,521 INFO [train.py:527] (2/6) Epoch 964, batch 38, global_batch_idx: 119450, batch size: 62, loss[discriminator_loss=2.721, discriminator_real_loss=1.414, discriminator_fake_loss=1.306, generator_loss=28.8, generator_mel_loss=17.3, generator_kl_loss=1.506, generator_dur_loss=1.764, generator_adv_loss=2.025, generator_feat_match_loss=6.202, over 62.00 samples.], tot_loss[discriminator_loss=2.666, discriminator_real_loss=1.348, discriminator_fake_loss=1.319, generator_loss=29.27, generator_mel_loss=17.79, generator_kl_loss=1.449, generator_dur_loss=1.731, generator_adv_loss=2.011, generator_feat_match_loss=6.285, over 2150.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 03:27:09,274 INFO [train.py:527] (2/6) Epoch 964, batch 88, global_batch_idx: 119500, batch size: 77, loss[discriminator_loss=2.7, discriminator_real_loss=1.354, discriminator_fake_loss=1.345, generator_loss=28.59, generator_mel_loss=17.49, generator_kl_loss=1.358, generator_dur_loss=1.799, generator_adv_loss=2.019, generator_feat_match_loss=5.922, over 77.00 samples.], tot_loss[discriminator_loss=2.673, discriminator_real_loss=1.351, discriminator_fake_loss=1.322, generator_loss=29.31, generator_mel_loss=17.76, generator_kl_loss=1.446, generator_dur_loss=1.737, generator_adv_loss=2.035, generator_feat_match_loss=6.329, over 5114.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 03:28:46,687 INFO [train.py:919] (2/6) Start epoch 965
2024-03-16 03:29:50,756 INFO [train.py:527] (2/6) Epoch 965, batch 14, global_batch_idx: 119550, batch size: 56, loss[discriminator_loss=2.725, discriminator_real_loss=1.39, discriminator_fake_loss=1.335, generator_loss=28.62, generator_mel_loss=17.66, generator_kl_loss=1.316, generator_dur_loss=1.711, generator_adv_loss=2.05, generator_feat_match_loss=5.881, over 56.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.363, discriminator_fake_loss=1.313, generator_loss=29.2, generator_mel_loss=17.7, generator_kl_loss=1.464, generator_dur_loss=1.714, generator_adv_loss=2.029, generator_feat_match_loss=6.29, over 848.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 03:32:10,231 INFO [train.py:527] (2/6) Epoch 965, batch 64, global_batch_idx: 119600, batch size: 68, loss[discriminator_loss=2.684, discriminator_real_loss=1.258, discriminator_fake_loss=1.426, generator_loss=29.61, generator_mel_loss=17.6, generator_kl_loss=1.465, generator_dur_loss=1.753, generator_adv_loss=2.087, generator_feat_match_loss=6.713, over 68.00 samples.], tot_loss[discriminator_loss=2.677, discriminator_real_loss=1.359, discriminator_fake_loss=1.319, generator_loss=29.15, generator_mel_loss=17.71, generator_kl_loss=1.441, generator_dur_loss=1.736, generator_adv_loss=2.008, generator_feat_match_loss=6.25, over 3763.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 03:32:10,233 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 03:32:18,313 INFO [train.py:591] (2/6) Epoch 965, validation: discriminator_loss=2.703, discriminator_real_loss=1.36, discriminator_fake_loss=1.343, generator_loss=27.66, generator_mel_loss=18, generator_kl_loss=1.352, generator_dur_loss=1.796, generator_adv_loss=1.896, generator_feat_match_loss=4.611, over 100.00 samples.
2024-03-16 03:32:18,314 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 03:34:35,891 INFO [train.py:527] (2/6) Epoch 965, batch 114, global_batch_idx: 119650, batch size: 62, loss[discriminator_loss=2.685, discriminator_real_loss=1.416, discriminator_fake_loss=1.268, generator_loss=28.89, generator_mel_loss=17.76, generator_kl_loss=1.495, generator_dur_loss=1.709, generator_adv_loss=1.784, generator_feat_match_loss=6.141, over 62.00 samples.], tot_loss[discriminator_loss=2.677, discriminator_real_loss=1.358, discriminator_fake_loss=1.319, generator_loss=29.17, generator_mel_loss=17.71, generator_kl_loss=1.447, generator_dur_loss=1.732, generator_adv_loss=2.011, generator_feat_match_loss=6.271, over 6622.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 03:35:02,449 INFO [train.py:919] (2/6) Start epoch 966
2024-03-16 03:37:17,003 INFO [train.py:527] (2/6) Epoch 966, batch 40, global_batch_idx: 119700, batch size: 62, loss[discriminator_loss=2.666, discriminator_real_loss=1.431, discriminator_fake_loss=1.236, generator_loss=28.77, generator_mel_loss=17.08, generator_kl_loss=1.461, generator_dur_loss=1.777, generator_adv_loss=2.006, generator_feat_match_loss=6.455, over 62.00 samples.], tot_loss[discriminator_loss=2.679, discriminator_real_loss=1.355, discriminator_fake_loss=1.324, generator_loss=29.15, generator_mel_loss=17.65, generator_kl_loss=1.449, generator_dur_loss=1.737, generator_adv_loss=2.014, generator_feat_match_loss=6.298, over 2336.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 03:39:35,461 INFO [train.py:527] (2/6) Epoch 966, batch 90, global_batch_idx: 119750, batch size: 58, loss[discriminator_loss=2.675, discriminator_real_loss=1.377, discriminator_fake_loss=1.298, generator_loss=30.55, generator_mel_loss=18.11, generator_kl_loss=1.526, generator_dur_loss=1.69, generator_adv_loss=1.921, generator_feat_match_loss=7.299, over 58.00 samples.], tot_loss[discriminator_loss=2.672, discriminator_real_loss=1.35, discriminator_fake_loss=1.322, generator_loss=29.24, generator_mel_loss=17.69, generator_kl_loss=1.456, generator_dur_loss=1.735, generator_adv_loss=2.019, generator_feat_match_loss=6.336, over 5053.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 03:41:10,512 INFO [train.py:919] (2/6) Start epoch 967
2024-03-16 03:42:20,841 INFO [train.py:527] (2/6) Epoch 967, batch 16, global_batch_idx: 119800, batch size: 80, loss[discriminator_loss=2.687, discriminator_real_loss=1.355, discriminator_fake_loss=1.331, generator_loss=28.84, generator_mel_loss=17.76, generator_kl_loss=1.49, generator_dur_loss=1.81, generator_adv_loss=2.03, generator_feat_match_loss=5.75, over 80.00 samples.], tot_loss[discriminator_loss=2.668, discriminator_real_loss=1.34, discriminator_fake_loss=1.328, generator_loss=29.45, generator_mel_loss=17.8, generator_kl_loss=1.474, generator_dur_loss=1.751, generator_adv_loss=2.011, generator_feat_match_loss=6.413, over 952.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 03:42:20,843 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 03:42:29,730 INFO [train.py:591] (2/6) Epoch 967, validation: discriminator_loss=2.732, discriminator_real_loss=1.422, discriminator_fake_loss=1.311, generator_loss=27.33, generator_mel_loss=17.69, generator_kl_loss=1.272, generator_dur_loss=1.813, generator_adv_loss=2, generator_feat_match_loss=4.555, over 100.00 samples.
2024-03-16 03:42:29,731 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 03:44:48,633 INFO [train.py:527] (2/6) Epoch 967, batch 66, global_batch_idx: 119850, batch size: 59, loss[discriminator_loss=2.671, discriminator_real_loss=1.302, discriminator_fake_loss=1.369, generator_loss=28.6, generator_mel_loss=17.49, generator_kl_loss=1.336, generator_dur_loss=1.765, generator_adv_loss=1.838, generator_feat_match_loss=6.179, over 59.00 samples.], tot_loss[discriminator_loss=2.672, discriminator_real_loss=1.347, discriminator_fake_loss=1.325, generator_loss=29.33, generator_mel_loss=17.78, generator_kl_loss=1.474, generator_dur_loss=1.738, generator_adv_loss=2.014, generator_feat_match_loss=6.324, over 3708.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 03:47:04,614 INFO [train.py:527] (2/6) Epoch 967, batch 116, global_batch_idx: 119900, batch size: 52, loss[discriminator_loss=2.637, discriminator_real_loss=1.396, discriminator_fake_loss=1.241, generator_loss=28.46, generator_mel_loss=17.67, generator_kl_loss=1.442, generator_dur_loss=1.735, generator_adv_loss=1.992, generator_feat_match_loss=5.622, over 52.00 samples.], tot_loss[discriminator_loss=2.672, discriminator_real_loss=1.348, discriminator_fake_loss=1.324, generator_loss=29.28, generator_mel_loss=17.77, generator_kl_loss=1.46, generator_dur_loss=1.736, generator_adv_loss=2.016, generator_feat_match_loss=6.3, over 6372.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 03:47:27,560 INFO [train.py:919] (2/6) Start epoch 968
2024-03-16 03:49:48,400 INFO [train.py:527] (2/6) Epoch 968, batch 42, global_batch_idx: 119950, batch size: 66, loss[discriminator_loss=2.681, discriminator_real_loss=1.384, discriminator_fake_loss=1.297, generator_loss=29.05, generator_mel_loss=17.31, generator_kl_loss=1.385, generator_dur_loss=1.736, generator_adv_loss=1.965, generator_feat_match_loss=6.656, over 66.00 samples.], tot_loss[discriminator_loss=2.673, discriminator_real_loss=1.345, discriminator_fake_loss=1.327, generator_loss=29.31, generator_mel_loss=17.67, generator_kl_loss=1.42, generator_dur_loss=1.746, generator_adv_loss=2.066, generator_feat_match_loss=6.406, over 2507.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 03:52:07,633 INFO [train.py:527] (2/6) Epoch 968, batch 92, global_batch_idx: 120000, batch size: 77, loss[discriminator_loss=2.638, discriminator_real_loss=1.342, discriminator_fake_loss=1.296, generator_loss=28.69, generator_mel_loss=17.49, generator_kl_loss=1.265, generator_dur_loss=1.782, generator_adv_loss=1.963, generator_feat_match_loss=6.185, over 77.00 samples.], tot_loss[discriminator_loss=2.668, discriminator_real_loss=1.35, discriminator_fake_loss=1.317, generator_loss=29.21, generator_mel_loss=17.67, generator_kl_loss=1.436, generator_dur_loss=1.742, generator_adv_loss=2.036, generator_feat_match_loss=6.327, over 5270.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 03:52:07,635 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 03:52:16,506 INFO [train.py:591] (2/6) Epoch 968, validation: discriminator_loss=2.664, discriminator_real_loss=1.324, discriminator_fake_loss=1.34, generator_loss=28.55, generator_mel_loss=18.05, generator_kl_loss=1.228, generator_dur_loss=1.812, generator_adv_loss=1.908, generator_feat_match_loss=5.552, over 100.00 samples.
2024-03-16 03:52:16,507 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 03:53:43,491 INFO [train.py:919] (2/6) Start epoch 969
2024-03-16 03:54:57,280 INFO [train.py:527] (2/6) Epoch 969, batch 18, global_batch_idx: 120050, batch size: 66, loss[discriminator_loss=2.648, discriminator_real_loss=1.316, discriminator_fake_loss=1.331, generator_loss=29.22, generator_mel_loss=17.96, generator_kl_loss=1.392, generator_dur_loss=1.742, generator_adv_loss=1.98, generator_feat_match_loss=6.14, over 66.00 samples.], tot_loss[discriminator_loss=2.679, discriminator_real_loss=1.356, discriminator_fake_loss=1.323, generator_loss=29.46, generator_mel_loss=17.88, generator_kl_loss=1.506, generator_dur_loss=1.707, generator_adv_loss=2.02, generator_feat_match_loss=6.345, over 1003.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 03:57:17,442 INFO [train.py:527] (2/6) Epoch 969, batch 68, global_batch_idx: 120100, batch size: 53, loss[discriminator_loss=2.645, discriminator_real_loss=1.372, discriminator_fake_loss=1.273, generator_loss=28.42, generator_mel_loss=17.73, generator_kl_loss=1.494, generator_dur_loss=1.642, generator_adv_loss=1.925, generator_feat_match_loss=5.63, over 53.00 samples.], tot_loss[discriminator_loss=2.664, discriminator_real_loss=1.342, discriminator_fake_loss=1.322, generator_loss=29.3, generator_mel_loss=17.75, generator_kl_loss=1.455, generator_dur_loss=1.732, generator_adv_loss=2.01, generator_feat_match_loss=6.353, over 3993.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 03:59:34,220 INFO [train.py:527] (2/6) Epoch 969, batch 118, global_batch_idx: 120150, batch size: 62, loss[discriminator_loss=2.677, discriminator_real_loss=1.34, discriminator_fake_loss=1.337, generator_loss=29.78, generator_mel_loss=17.98, generator_kl_loss=1.454, generator_dur_loss=1.739, generator_adv_loss=2.011, generator_feat_match_loss=6.594, over 62.00 samples.], tot_loss[discriminator_loss=2.665, discriminator_real_loss=1.344, discriminator_fake_loss=1.321, generator_loss=29.31, generator_mel_loss=17.77, generator_kl_loss=1.463, generator_dur_loss=1.728, generator_adv_loss=2.014, generator_feat_match_loss=6.338, over 6681.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 03:59:50,077 INFO [train.py:919] (2/6) Start epoch 970
2024-03-16 04:02:16,056 INFO [train.py:527] (2/6) Epoch 970, batch 44, global_batch_idx: 120200, batch size: 36, loss[discriminator_loss=2.706, discriminator_real_loss=1.388, discriminator_fake_loss=1.318, generator_loss=29.67, generator_mel_loss=17.89, generator_kl_loss=1.637, generator_dur_loss=1.65, generator_adv_loss=2.051, generator_feat_match_loss=6.438, over 36.00 samples.], tot_loss[discriminator_loss=2.679, discriminator_real_loss=1.347, discriminator_fake_loss=1.332, generator_loss=29.25, generator_mel_loss=17.75, generator_kl_loss=1.466, generator_dur_loss=1.721, generator_adv_loss=2.014, generator_feat_match_loss=6.3, over 2353.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 04:02:16,057 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 04:02:23,798 INFO [train.py:591] (2/6) Epoch 970, validation: discriminator_loss=2.721, discriminator_real_loss=1.439, discriminator_fake_loss=1.282, generator_loss=27.91, generator_mel_loss=17.65, generator_kl_loss=1.307, generator_dur_loss=1.813, generator_adv_loss=1.951, generator_feat_match_loss=5.194, over 100.00 samples.
2024-03-16 04:02:23,799 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 04:04:41,783 INFO [train.py:527] (2/6) Epoch 970, batch 94, global_batch_idx: 120250, batch size: 25, loss[discriminator_loss=2.684, discriminator_real_loss=1.27, discriminator_fake_loss=1.414, generator_loss=28.58, generator_mel_loss=17.56, generator_kl_loss=1.747, generator_dur_loss=1.539, generator_adv_loss=2.094, generator_feat_match_loss=5.638, over 25.00 samples.], tot_loss[discriminator_loss=2.677, discriminator_real_loss=1.351, discriminator_fake_loss=1.327, generator_loss=29.26, generator_mel_loss=17.74, generator_kl_loss=1.451, generator_dur_loss=1.738, generator_adv_loss=2.013, generator_feat_match_loss=6.311, over 5369.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 04:06:00,731 INFO [train.py:919] (2/6) Start epoch 971
2024-03-16 04:07:16,752 INFO [train.py:527] (2/6) Epoch 971, batch 20, global_batch_idx: 120300, batch size: 48, loss[discriminator_loss=2.711, discriminator_real_loss=1.37, discriminator_fake_loss=1.341, generator_loss=28.26, generator_mel_loss=17.54, generator_kl_loss=1.615, generator_dur_loss=1.666, generator_adv_loss=2.058, generator_feat_match_loss=5.385, over 48.00 samples.], tot_loss[discriminator_loss=2.667, discriminator_real_loss=1.352, discriminator_fake_loss=1.316, generator_loss=28.9, generator_mel_loss=17.47, generator_kl_loss=1.425, generator_dur_loss=1.735, generator_adv_loss=2.025, generator_feat_match_loss=6.237, over 1247.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 04:09:34,927 INFO [train.py:527] (2/6) Epoch 971, batch 70, global_batch_idx: 120350, batch size: 53, loss[discriminator_loss=2.638, discriminator_real_loss=1.358, discriminator_fake_loss=1.28, generator_loss=29.45, generator_mel_loss=17.4, generator_kl_loss=1.562, generator_dur_loss=1.665, generator_adv_loss=2.044, generator_feat_match_loss=6.778, over 53.00 samples.], tot_loss[discriminator_loss=2.661, discriminator_real_loss=1.353, discriminator_fake_loss=1.309, generator_loss=29.02, generator_mel_loss=17.58, generator_kl_loss=1.452, generator_dur_loss=1.741, generator_adv_loss=2.027, generator_feat_match_loss=6.222, over 4034.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 04:11:53,972 INFO [train.py:527] (2/6) Epoch 971, batch 120, global_batch_idx: 120400, batch size: 72, loss[discriminator_loss=2.598, discriminator_real_loss=1.373, discriminator_fake_loss=1.225, generator_loss=29.52, generator_mel_loss=17.46, generator_kl_loss=1.372, generator_dur_loss=1.81, generator_adv_loss=2.125, generator_feat_match_loss=6.748, over 72.00 samples.], tot_loss[discriminator_loss=2.664, discriminator_real_loss=1.349, discriminator_fake_loss=1.316, generator_loss=29.09, generator_mel_loss=17.63, generator_kl_loss=1.445, generator_dur_loss=1.744, generator_adv_loss=2.018, generator_feat_match_loss=6.252, over 6988.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 04:11:53,974 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 04:12:02,758 INFO [train.py:591] (2/6) Epoch 971, validation: discriminator_loss=2.709, discriminator_real_loss=1.367, discriminator_fake_loss=1.342, generator_loss=27.71, generator_mel_loss=17.7, generator_kl_loss=1.189, generator_dur_loss=1.816, generator_adv_loss=1.942, generator_feat_match_loss=5.053, over 100.00 samples.
2024-03-16 04:12:02,759 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 04:12:12,584 INFO [train.py:919] (2/6) Start epoch 972
2024-03-16 04:14:42,815 INFO [train.py:527] (2/6) Epoch 972, batch 46, global_batch_idx: 120450, batch size: 61, loss[discriminator_loss=2.583, discriminator_real_loss=1.329, discriminator_fake_loss=1.254, generator_loss=29.26, generator_mel_loss=17.42, generator_kl_loss=1.399, generator_dur_loss=1.733, generator_adv_loss=2.066, generator_feat_match_loss=6.65, over 61.00 samples.], tot_loss[discriminator_loss=2.657, discriminator_real_loss=1.346, discriminator_fake_loss=1.311, generator_loss=29.3, generator_mel_loss=17.68, generator_kl_loss=1.48, generator_dur_loss=1.717, generator_adv_loss=2.021, generator_feat_match_loss=6.393, over 2518.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 04:17:02,580 INFO [train.py:527] (2/6) Epoch 972, batch 96, global_batch_idx: 120500, batch size: 66, loss[discriminator_loss=2.699, discriminator_real_loss=1.431, discriminator_fake_loss=1.269, generator_loss=29.45, generator_mel_loss=17.73, generator_kl_loss=1.367, generator_dur_loss=1.781, generator_adv_loss=1.944, generator_feat_match_loss=6.634, over 66.00 samples.], tot_loss[discriminator_loss=2.658, discriminator_real_loss=1.346, discriminator_fake_loss=1.311, generator_loss=29.25, generator_mel_loss=17.67, generator_kl_loss=1.463, generator_dur_loss=1.729, generator_adv_loss=2.02, generator_feat_match_loss=6.373, over 5393.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 04:18:19,379 INFO [train.py:919] (2/6) Start epoch 973
2024-03-16 04:19:42,331 INFO [train.py:527] (2/6) Epoch 973, batch 22, global_batch_idx: 120550, batch size: 74, loss[discriminator_loss=2.678, discriminator_real_loss=1.331, discriminator_fake_loss=1.346, generator_loss=28.65, generator_mel_loss=17.25, generator_kl_loss=1.245, generator_dur_loss=1.781, generator_adv_loss=2.276, generator_feat_match_loss=6.092, over 74.00 samples.], tot_loss[discriminator_loss=2.661, discriminator_real_loss=1.341, discriminator_fake_loss=1.32, generator_loss=29.05, generator_mel_loss=17.59, generator_kl_loss=1.423, generator_dur_loss=1.748, generator_adv_loss=2.022, generator_feat_match_loss=6.271, over 1372.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 04:22:01,956 INFO [train.py:527] (2/6) Epoch 973, batch 72, global_batch_idx: 120600, batch size: 64, loss[discriminator_loss=2.61, discriminator_real_loss=1.37, discriminator_fake_loss=1.24, generator_loss=29.98, generator_mel_loss=17.79, generator_kl_loss=1.426, generator_dur_loss=1.772, generator_adv_loss=2.004, generator_feat_match_loss=6.982, over 64.00 samples.], tot_loss[discriminator_loss=2.662, discriminator_real_loss=1.347, discriminator_fake_loss=1.315, generator_loss=29.23, generator_mel_loss=17.66, generator_kl_loss=1.423, generator_dur_loss=1.741, generator_adv_loss=2.022, generator_feat_match_loss=6.383, over 4260.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 04:22:01,957 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 04:22:10,204 INFO [train.py:591] (2/6) Epoch 973, validation: discriminator_loss=2.714, discriminator_real_loss=1.352, discriminator_fake_loss=1.362, generator_loss=28.38, generator_mel_loss=18.37, generator_kl_loss=1.242, generator_dur_loss=1.801, generator_adv_loss=1.845, generator_feat_match_loss=5.118, over 100.00 samples.
2024-03-16 04:22:10,205 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 04:24:28,782 INFO [train.py:527] (2/6) Epoch 973, batch 122, global_batch_idx: 120650, batch size: 58, loss[discriminator_loss=2.659, discriminator_real_loss=1.322, discriminator_fake_loss=1.336, generator_loss=30.14, generator_mel_loss=18.18, generator_kl_loss=1.439, generator_dur_loss=1.709, generator_adv_loss=2.012, generator_feat_match_loss=6.795, over 58.00 samples.], tot_loss[discriminator_loss=2.666, discriminator_real_loss=1.35, discriminator_fake_loss=1.316, generator_loss=29.24, generator_mel_loss=17.69, generator_kl_loss=1.429, generator_dur_loss=1.742, generator_adv_loss=2.021, generator_feat_match_loss=6.356, over 7220.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 04:24:35,377 INFO [train.py:919] (2/6) Start epoch 974
2024-03-16 04:27:14,427 INFO [train.py:527] (2/6) Epoch 974, batch 48, global_batch_idx: 120700, batch size: 83, loss[discriminator_loss=2.589, discriminator_real_loss=1.34, discriminator_fake_loss=1.249, generator_loss=29.63, generator_mel_loss=17.85, generator_kl_loss=1.32, generator_dur_loss=1.817, generator_adv_loss=2.143, generator_feat_match_loss=6.507, over 83.00 samples.], tot_loss[discriminator_loss=2.652, discriminator_real_loss=1.341, discriminator_fake_loss=1.311, generator_loss=29.36, generator_mel_loss=17.68, generator_kl_loss=1.41, generator_dur_loss=1.746, generator_adv_loss=2.037, generator_feat_match_loss=6.484, over 2996.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 04:29:32,821 INFO [train.py:527] (2/6) Epoch 974, batch 98, global_batch_idx: 120750, batch size: 31, loss[discriminator_loss=2.748, discriminator_real_loss=1.426, discriminator_fake_loss=1.322, generator_loss=28.43, generator_mel_loss=17.62, generator_kl_loss=1.522, generator_dur_loss=1.643, generator_adv_loss=2.004, generator_feat_match_loss=5.648, over 31.00 samples.], tot_loss[discriminator_loss=2.665, discriminator_real_loss=1.352, discriminator_fake_loss=1.314, generator_loss=29.24, generator_mel_loss=17.68, generator_kl_loss=1.432, generator_dur_loss=1.734, generator_adv_loss=2.038, generator_feat_match_loss=6.363, over 5535.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 04:30:42,735 INFO [train.py:919] (2/6) Start epoch 975
2024-03-16 04:32:14,179 INFO [train.py:527] (2/6) Epoch 975, batch 24, global_batch_idx: 120800, batch size: 77, loss[discriminator_loss=2.648, discriminator_real_loss=1.286, discriminator_fake_loss=1.362, generator_loss=29.78, generator_mel_loss=18.1, generator_kl_loss=1.358, generator_dur_loss=1.81, generator_adv_loss=2.052, generator_feat_match_loss=6.46, over 77.00 samples.], tot_loss[discriminator_loss=2.672, discriminator_real_loss=1.357, discriminator_fake_loss=1.315, generator_loss=29.07, generator_mel_loss=17.77, generator_kl_loss=1.412, generator_dur_loss=1.73, generator_adv_loss=1.999, generator_feat_match_loss=6.163, over 1399.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 04:32:14,180 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 04:32:22,021 INFO [train.py:591] (2/6) Epoch 975, validation: discriminator_loss=2.764, discriminator_real_loss=1.476, discriminator_fake_loss=1.287, generator_loss=28.07, generator_mel_loss=18.2, generator_kl_loss=1.347, generator_dur_loss=1.808, generator_adv_loss=1.986, generator_feat_match_loss=4.725, over 100.00 samples.
2024-03-16 04:32:22,022 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 04:34:43,146 INFO [train.py:527] (2/6) Epoch 975, batch 74, global_batch_idx: 120850, batch size: 36, loss[discriminator_loss=2.65, discriminator_real_loss=1.375, discriminator_fake_loss=1.274, generator_loss=29.08, generator_mel_loss=17.62, generator_kl_loss=1.65, generator_dur_loss=1.657, generator_adv_loss=2.081, generator_feat_match_loss=6.073, over 36.00 samples.], tot_loss[discriminator_loss=2.668, discriminator_real_loss=1.351, discriminator_fake_loss=1.317, generator_loss=29.17, generator_mel_loss=17.7, generator_kl_loss=1.451, generator_dur_loss=1.733, generator_adv_loss=2.002, generator_feat_match_loss=6.285, over 4185.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 04:36:58,821 INFO [train.py:919] (2/6) Start epoch 976
2024-03-16 04:37:24,080 INFO [train.py:527] (2/6) Epoch 976, batch 0, global_batch_idx: 120900, batch size: 53, loss[discriminator_loss=2.69, discriminator_real_loss=1.368, discriminator_fake_loss=1.322, generator_loss=28.87, generator_mel_loss=17.75, generator_kl_loss=1.561, generator_dur_loss=1.616, generator_adv_loss=2.141, generator_feat_match_loss=5.809, over 53.00 samples.], tot_loss[discriminator_loss=2.69, discriminator_real_loss=1.368, discriminator_fake_loss=1.322, generator_loss=28.87, generator_mel_loss=17.75, generator_kl_loss=1.561, generator_dur_loss=1.616, generator_adv_loss=2.141, generator_feat_match_loss=5.809, over 53.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 04:39:43,134 INFO [train.py:527] (2/6) Epoch 976, batch 50, global_batch_idx: 120950, batch size: 72, loss[discriminator_loss=2.659, discriminator_real_loss=1.397, discriminator_fake_loss=1.262, generator_loss=29.26, generator_mel_loss=17.75, generator_kl_loss=1.304, generator_dur_loss=1.792, generator_adv_loss=1.957, generator_feat_match_loss=6.462, over 72.00 samples.], tot_loss[discriminator_loss=2.671, discriminator_real_loss=1.353, discriminator_fake_loss=1.318, generator_loss=29.41, generator_mel_loss=17.74, generator_kl_loss=1.429, generator_dur_loss=1.74, generator_adv_loss=2.046, generator_feat_match_loss=6.445, over 2790.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 04:42:03,690 INFO [train.py:527] (2/6) Epoch 976, batch 100, global_batch_idx: 121000, batch size: 62, loss[discriminator_loss=2.673, discriminator_real_loss=1.382, discriminator_fake_loss=1.291, generator_loss=29.49, generator_mel_loss=17.69, generator_kl_loss=1.352, generator_dur_loss=1.751, generator_adv_loss=1.944, generator_feat_match_loss=6.754, over 62.00 samples.], tot_loss[discriminator_loss=2.672, discriminator_real_loss=1.356, discriminator_fake_loss=1.316, generator_loss=29.25, generator_mel_loss=17.73, generator_kl_loss=1.425, generator_dur_loss=1.741, generator_adv_loss=2.025, generator_feat_match_loss=6.331, over 5767.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 04:42:03,691 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 04:42:12,325 INFO [train.py:591] (2/6) Epoch 976, validation: discriminator_loss=2.716, discriminator_real_loss=1.315, discriminator_fake_loss=1.401, generator_loss=28.04, generator_mel_loss=18.46, generator_kl_loss=1.27, generator_dur_loss=1.816, generator_adv_loss=1.744, generator_feat_match_loss=4.742, over 100.00 samples.
2024-03-16 04:42:12,326 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 04:43:17,345 INFO [train.py:919] (2/6) Start epoch 977
2024-03-16 04:44:52,760 INFO [train.py:527] (2/6) Epoch 977, batch 26, global_batch_idx: 121050, batch size: 56, loss[discriminator_loss=2.679, discriminator_real_loss=1.331, discriminator_fake_loss=1.347, generator_loss=29.88, generator_mel_loss=17.97, generator_kl_loss=1.733, generator_dur_loss=1.718, generator_adv_loss=1.991, generator_feat_match_loss=6.468, over 56.00 samples.], tot_loss[discriminator_loss=2.673, discriminator_real_loss=1.356, discriminator_fake_loss=1.317, generator_loss=29.34, generator_mel_loss=17.76, generator_kl_loss=1.594, generator_dur_loss=1.741, generator_adv_loss=2.016, generator_feat_match_loss=6.231, over 1573.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 04:47:15,570 INFO [train.py:527] (2/6) Epoch 977, batch 76, global_batch_idx: 121100, batch size: 88, loss[discriminator_loss=2.632, discriminator_real_loss=1.247, discriminator_fake_loss=1.385, generator_loss=28.96, generator_mel_loss=17.72, generator_kl_loss=1.341, generator_dur_loss=1.804, generator_adv_loss=2.023, generator_feat_match_loss=6.075, over 88.00 samples.], tot_loss[discriminator_loss=2.67, discriminator_real_loss=1.351, discriminator_fake_loss=1.32, generator_loss=29.33, generator_mel_loss=17.72, generator_kl_loss=1.525, generator_dur_loss=1.749, generator_adv_loss=2.014, generator_feat_match_loss=6.315, over 4499.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 04:49:23,506 INFO [train.py:919] (2/6) Start epoch 978
2024-03-16 04:49:52,878 INFO [train.py:527] (2/6) Epoch 978, batch 2, global_batch_idx: 121150, batch size: 44, loss[discriminator_loss=2.636, discriminator_real_loss=1.352, discriminator_fake_loss=1.283, generator_loss=29.77, generator_mel_loss=18.12, generator_kl_loss=1.548, generator_dur_loss=1.735, generator_adv_loss=1.987, generator_feat_match_loss=6.378, over 44.00 samples.], tot_loss[discriminator_loss=2.672, discriminator_real_loss=1.34, discriminator_fake_loss=1.331, generator_loss=29.5, generator_mel_loss=17.72, generator_kl_loss=1.469, generator_dur_loss=1.745, generator_adv_loss=2.079, generator_feat_match_loss=6.486, over 154.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 04:52:09,654 INFO [train.py:527] (2/6) Epoch 978, batch 52, global_batch_idx: 121200, batch size: 53, loss[discriminator_loss=2.647, discriminator_real_loss=1.262, discriminator_fake_loss=1.385, generator_loss=29.69, generator_mel_loss=18.14, generator_kl_loss=1.489, generator_dur_loss=1.632, generator_adv_loss=1.976, generator_feat_match_loss=6.455, over 53.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.361, discriminator_fake_loss=1.324, generator_loss=29.29, generator_mel_loss=17.78, generator_kl_loss=1.469, generator_dur_loss=1.737, generator_adv_loss=2.027, generator_feat_match_loss=6.284, over 2862.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 04:52:09,655 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 04:52:17,761 INFO [train.py:591] (2/6) Epoch 978, validation: discriminator_loss=2.684, discriminator_real_loss=1.319, discriminator_fake_loss=1.365, generator_loss=27.33, generator_mel_loss=17.94, generator_kl_loss=1.208, generator_dur_loss=1.801, generator_adv_loss=1.836, generator_feat_match_loss=4.543, over 100.00 samples.
2024-03-16 04:52:17,762 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 04:54:33,301 INFO [train.py:527] (2/6) Epoch 978, batch 102, global_batch_idx: 121250, batch size: 96, loss[discriminator_loss=2.663, discriminator_real_loss=1.369, discriminator_fake_loss=1.294, generator_loss=29.2, generator_mel_loss=17.75, generator_kl_loss=1.394, generator_dur_loss=1.83, generator_adv_loss=1.936, generator_feat_match_loss=6.292, over 96.00 samples.], tot_loss[discriminator_loss=2.673, discriminator_real_loss=1.358, discriminator_fake_loss=1.314, generator_loss=29.33, generator_mel_loss=17.7, generator_kl_loss=1.469, generator_dur_loss=1.726, generator_adv_loss=2.023, generator_feat_match_loss=6.407, over 5458.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 04:55:35,665 INFO [train.py:919] (2/6) Start epoch 979
2024-03-16 04:57:14,793 INFO [train.py:527] (2/6) Epoch 979, batch 28, global_batch_idx: 121300, batch size: 44, loss[discriminator_loss=2.728, discriminator_real_loss=1.35, discriminator_fake_loss=1.378, generator_loss=29.02, generator_mel_loss=17.84, generator_kl_loss=1.554, generator_dur_loss=1.663, generator_adv_loss=1.922, generator_feat_match_loss=6.04, over 44.00 samples.], tot_loss[discriminator_loss=2.682, discriminator_real_loss=1.364, discriminator_fake_loss=1.318, generator_loss=29.24, generator_mel_loss=17.69, generator_kl_loss=1.44, generator_dur_loss=1.733, generator_adv_loss=2.014, generator_feat_match_loss=6.357, over 1692.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 04:59:31,908 INFO [train.py:527] (2/6) Epoch 979, batch 78, global_batch_idx: 121350, batch size: 50, loss[discriminator_loss=2.702, discriminator_real_loss=1.42, discriminator_fake_loss=1.282, generator_loss=28.19, generator_mel_loss=17.82, generator_kl_loss=1.595, generator_dur_loss=1.676, generator_adv_loss=1.888, generator_feat_match_loss=5.209, over 50.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.366, discriminator_fake_loss=1.319, generator_loss=28.99, generator_mel_loss=17.62, generator_kl_loss=1.443, generator_dur_loss=1.731, generator_adv_loss=2.005, generator_feat_match_loss=6.187, over 4529.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 05:01:39,529 INFO [train.py:919] (2/6) Start epoch 980
2024-03-16 05:02:16,026 INFO [train.py:527] (2/6) Epoch 980, batch 4, global_batch_idx: 121400, batch size: 77, loss[discriminator_loss=2.714, discriminator_real_loss=1.413, discriminator_fake_loss=1.3, generator_loss=29.79, generator_mel_loss=17.56, generator_kl_loss=1.424, generator_dur_loss=1.802, generator_adv_loss=1.898, generator_feat_match_loss=7.107, over 77.00 samples.], tot_loss[discriminator_loss=2.685, discriminator_real_loss=1.367, discriminator_fake_loss=1.318, generator_loss=29.47, generator_mel_loss=17.78, generator_kl_loss=1.506, generator_dur_loss=1.726, generator_adv_loss=1.989, generator_feat_match_loss=6.466, over 296.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 05:02:16,029 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 05:02:23,771 INFO [train.py:591] (2/6) Epoch 980, validation: discriminator_loss=2.722, discriminator_real_loss=1.367, discriminator_fake_loss=1.355, generator_loss=27.75, generator_mel_loss=18.1, generator_kl_loss=1.305, generator_dur_loss=1.816, generator_adv_loss=1.841, generator_feat_match_loss=4.69, over 100.00 samples.
2024-03-16 05:02:23,773 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 05:04:44,160 INFO [train.py:527] (2/6) Epoch 980, batch 54, global_batch_idx: 121450, batch size: 72, loss[discriminator_loss=2.665, discriminator_real_loss=1.309, discriminator_fake_loss=1.356, generator_loss=28.13, generator_mel_loss=17.42, generator_kl_loss=1.282, generator_dur_loss=1.792, generator_adv_loss=2.012, generator_feat_match_loss=5.626, over 72.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.358, discriminator_fake_loss=1.317, generator_loss=29.17, generator_mel_loss=17.67, generator_kl_loss=1.432, generator_dur_loss=1.745, generator_adv_loss=2.019, generator_feat_match_loss=6.305, over 3200.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 05:07:02,458 INFO [train.py:527] (2/6) Epoch 980, batch 104, global_batch_idx: 121500, batch size: 42, loss[discriminator_loss=2.654, discriminator_real_loss=1.264, discriminator_fake_loss=1.39, generator_loss=30.52, generator_mel_loss=17.7, generator_kl_loss=1.586, generator_dur_loss=1.678, generator_adv_loss=2.141, generator_feat_match_loss=7.415, over 42.00 samples.], tot_loss[discriminator_loss=2.675, discriminator_real_loss=1.357, discriminator_fake_loss=1.318, generator_loss=29.12, generator_mel_loss=17.67, generator_kl_loss=1.432, generator_dur_loss=1.744, generator_adv_loss=2.015, generator_feat_match_loss=6.26, over 6056.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 05:07:55,266 INFO [train.py:919] (2/6) Start epoch 981
2024-03-16 05:09:42,431 INFO [train.py:527] (2/6) Epoch 981, batch 30, global_batch_idx: 121550, batch size: 36, loss[discriminator_loss=2.639, discriminator_real_loss=1.347, discriminator_fake_loss=1.291, generator_loss=29.44, generator_mel_loss=17.58, generator_kl_loss=1.45, generator_dur_loss=1.64, generator_adv_loss=2.108, generator_feat_match_loss=6.66, over 36.00 samples.], tot_loss[discriminator_loss=2.664, discriminator_real_loss=1.354, discriminator_fake_loss=1.311, generator_loss=29.04, generator_mel_loss=17.64, generator_kl_loss=1.454, generator_dur_loss=1.715, generator_adv_loss=2.021, generator_feat_match_loss=6.208, over 1615.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 05:12:00,819 INFO [train.py:527] (2/6) Epoch 981, batch 80, global_batch_idx: 121600, batch size: 50, loss[discriminator_loss=2.664, discriminator_real_loss=1.236, discriminator_fake_loss=1.428, generator_loss=30.33, generator_mel_loss=17.73, generator_kl_loss=1.679, generator_dur_loss=1.653, generator_adv_loss=2.194, generator_feat_match_loss=7.071, over 50.00 samples.], tot_loss[discriminator_loss=2.666, discriminator_real_loss=1.35, discriminator_fake_loss=1.316, generator_loss=29.15, generator_mel_loss=17.68, generator_kl_loss=1.452, generator_dur_loss=1.726, generator_adv_loss=2.021, generator_feat_match_loss=6.268, over 4458.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 05:12:00,820 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 05:12:09,457 INFO [train.py:591] (2/6) Epoch 981, validation: discriminator_loss=2.757, discriminator_real_loss=1.515, discriminator_fake_loss=1.243, generator_loss=29.08, generator_mel_loss=18.26, generator_kl_loss=1.352, generator_dur_loss=1.792, generator_adv_loss=2.119, generator_feat_match_loss=5.557, over 100.00 samples.
2024-03-16 05:12:09,458 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 05:14:13,167 INFO [train.py:919] (2/6) Start epoch 982
2024-03-16 05:14:52,279 INFO [train.py:527] (2/6) Epoch 982, batch 6, global_batch_idx: 121650, batch size: 72, loss[discriminator_loss=2.709, discriminator_real_loss=1.342, discriminator_fake_loss=1.367, generator_loss=28.25, generator_mel_loss=17.61, generator_kl_loss=1.457, generator_dur_loss=1.786, generator_adv_loss=2, generator_feat_match_loss=5.397, over 72.00 samples.], tot_loss[discriminator_loss=2.678, discriminator_real_loss=1.36, discriminator_fake_loss=1.317, generator_loss=29.22, generator_mel_loss=17.69, generator_kl_loss=1.518, generator_dur_loss=1.739, generator_adv_loss=2.027, generator_feat_match_loss=6.247, over 397.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 05:17:09,864 INFO [train.py:527] (2/6) Epoch 982, batch 56, global_batch_idx: 121700, batch size: 72, loss[discriminator_loss=2.631, discriminator_real_loss=1.293, discriminator_fake_loss=1.338, generator_loss=28.76, generator_mel_loss=17.49, generator_kl_loss=1.285, generator_dur_loss=1.767, generator_adv_loss=2.117, generator_feat_match_loss=6.097, over 72.00 samples.], tot_loss[discriminator_loss=2.675, discriminator_real_loss=1.358, discriminator_fake_loss=1.317, generator_loss=29.2, generator_mel_loss=17.7, generator_kl_loss=1.456, generator_dur_loss=1.727, generator_adv_loss=2.03, generator_feat_match_loss=6.293, over 3205.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 05:19:30,269 INFO [train.py:527] (2/6) Epoch 982, batch 106, global_batch_idx: 121750, batch size: 56, loss[discriminator_loss=2.662, discriminator_real_loss=1.3, discriminator_fake_loss=1.362, generator_loss=30.25, generator_mel_loss=17.85, generator_kl_loss=1.412, generator_dur_loss=1.66, generator_adv_loss=2.148, generator_feat_match_loss=7.176, over 56.00 samples.], tot_loss[discriminator_loss=2.68, discriminator_real_loss=1.358, discriminator_fake_loss=1.322, generator_loss=29.21, generator_mel_loss=17.73, generator_kl_loss=1.446, generator_dur_loss=1.728, generator_adv_loss=2.015, generator_feat_match_loss=6.289, over 6138.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 05:20:20,757 INFO [train.py:919] (2/6) Start epoch 983
2024-03-16 05:22:11,841 INFO [train.py:527] (2/6) Epoch 983, batch 32, global_batch_idx: 121800, batch size: 48, loss[discriminator_loss=2.692, discriminator_real_loss=1.348, discriminator_fake_loss=1.345, generator_loss=28.78, generator_mel_loss=17.53, generator_kl_loss=1.402, generator_dur_loss=1.715, generator_adv_loss=2.139, generator_feat_match_loss=5.988, over 48.00 samples.], tot_loss[discriminator_loss=2.672, discriminator_real_loss=1.352, discriminator_fake_loss=1.321, generator_loss=29.07, generator_mel_loss=17.67, generator_kl_loss=1.434, generator_dur_loss=1.723, generator_adv_loss=2.021, generator_feat_match_loss=6.226, over 1813.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 05:22:11,843 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 05:22:19,998 INFO [train.py:591] (2/6) Epoch 983, validation: discriminator_loss=2.797, discriminator_real_loss=1.532, discriminator_fake_loss=1.265, generator_loss=27.99, generator_mel_loss=17.87, generator_kl_loss=1.185, generator_dur_loss=1.803, generator_adv_loss=2.017, generator_feat_match_loss=5.114, over 100.00 samples.
2024-03-16 05:22:19,998 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 05:24:35,134 INFO [train.py:527] (2/6) Epoch 983, batch 82, global_batch_idx: 121850, batch size: 31, loss[discriminator_loss=2.718, discriminator_real_loss=1.379, discriminator_fake_loss=1.339, generator_loss=28.45, generator_mel_loss=17.14, generator_kl_loss=1.687, generator_dur_loss=1.598, generator_adv_loss=2.006, generator_feat_match_loss=6.021, over 31.00 samples.], tot_loss[discriminator_loss=2.673, discriminator_real_loss=1.351, discriminator_fake_loss=1.322, generator_loss=29.2, generator_mel_loss=17.69, generator_kl_loss=1.448, generator_dur_loss=1.727, generator_adv_loss=2.021, generator_feat_match_loss=6.312, over 4504.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 05:26:29,920 INFO [train.py:919] (2/6) Start epoch 984
2024-03-16 05:27:17,812 INFO [train.py:527] (2/6) Epoch 984, batch 8, global_batch_idx: 121900, batch size: 56, loss[discriminator_loss=2.718, discriminator_real_loss=1.369, discriminator_fake_loss=1.349, generator_loss=28.69, generator_mel_loss=17.63, generator_kl_loss=1.399, generator_dur_loss=1.699, generator_adv_loss=1.888, generator_feat_match_loss=6.081, over 56.00 samples.], tot_loss[discriminator_loss=2.668, discriminator_real_loss=1.355, discriminator_fake_loss=1.313, generator_loss=28.92, generator_mel_loss=17.69, generator_kl_loss=1.457, generator_dur_loss=1.72, generator_adv_loss=2.014, generator_feat_match_loss=6.042, over 440.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 05:29:35,372 INFO [train.py:527] (2/6) Epoch 984, batch 58, global_batch_idx: 121950, batch size: 55, loss[discriminator_loss=2.652, discriminator_real_loss=1.293, discriminator_fake_loss=1.36, generator_loss=29.96, generator_mel_loss=17.88, generator_kl_loss=1.53, generator_dur_loss=1.643, generator_adv_loss=2.067, generator_feat_match_loss=6.841, over 55.00 samples.], tot_loss[discriminator_loss=2.67, discriminator_real_loss=1.355, discriminator_fake_loss=1.315, generator_loss=29.29, generator_mel_loss=17.8, generator_kl_loss=1.443, generator_dur_loss=1.734, generator_adv_loss=2.022, generator_feat_match_loss=6.299, over 3332.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 05:31:53,515 INFO [train.py:527] (2/6) Epoch 984, batch 108, global_batch_idx: 122000, batch size: 42, loss[discriminator_loss=2.688, discriminator_real_loss=1.412, discriminator_fake_loss=1.276, generator_loss=30.18, generator_mel_loss=18.1, generator_kl_loss=1.717, generator_dur_loss=1.644, generator_adv_loss=2.014, generator_feat_match_loss=6.71, over 42.00 samples.], tot_loss[discriminator_loss=2.675, discriminator_real_loss=1.356, discriminator_fake_loss=1.319, generator_loss=29.24, generator_mel_loss=17.76, generator_kl_loss=1.441, generator_dur_loss=1.736, generator_adv_loss=2.019, generator_feat_match_loss=6.28, over 6295.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 05:31:53,516 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 05:32:02,174 INFO [train.py:591] (2/6) Epoch 984, validation: discriminator_loss=2.731, discriminator_real_loss=1.446, discriminator_fake_loss=1.286, generator_loss=27.98, generator_mel_loss=18.09, generator_kl_loss=1.356, generator_dur_loss=1.799, generator_adv_loss=1.933, generator_feat_match_loss=4.807, over 100.00 samples.
2024-03-16 05:32:02,175 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 05:32:45,034 INFO [train.py:919] (2/6) Start epoch 985
2024-03-16 05:34:45,306 INFO [train.py:527] (2/6) Epoch 985, batch 34, global_batch_idx: 122050, batch size: 66, loss[discriminator_loss=2.684, discriminator_real_loss=1.339, discriminator_fake_loss=1.345, generator_loss=30.79, generator_mel_loss=17.93, generator_kl_loss=1.517, generator_dur_loss=1.734, generator_adv_loss=1.913, generator_feat_match_loss=7.701, over 66.00 samples.], tot_loss[discriminator_loss=2.684, discriminator_real_loss=1.363, discriminator_fake_loss=1.321, generator_loss=29.1, generator_mel_loss=17.66, generator_kl_loss=1.445, generator_dur_loss=1.732, generator_adv_loss=2.005, generator_feat_match_loss=6.252, over 2004.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 05:37:03,527 INFO [train.py:527] (2/6) Epoch 985, batch 84, global_batch_idx: 122100, batch size: 16, loss[discriminator_loss=2.636, discriminator_real_loss=1.319, discriminator_fake_loss=1.317, generator_loss=31.55, generator_mel_loss=19.09, generator_kl_loss=1.955, generator_dur_loss=1.554, generator_adv_loss=2.002, generator_feat_match_loss=6.953, over 16.00 samples.], tot_loss[discriminator_loss=2.674, discriminator_real_loss=1.351, discriminator_fake_loss=1.324, generator_loss=29.25, generator_mel_loss=17.71, generator_kl_loss=1.446, generator_dur_loss=1.735, generator_adv_loss=2.009, generator_feat_match_loss=6.351, over 4788.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 05:38:51,384 INFO [train.py:919] (2/6) Start epoch 986
2024-03-16 05:39:43,685 INFO [train.py:527] (2/6) Epoch 986, batch 10, global_batch_idx: 122150, batch size: 55, loss[discriminator_loss=2.675, discriminator_real_loss=1.384, discriminator_fake_loss=1.291, generator_loss=29.27, generator_mel_loss=18.07, generator_kl_loss=1.458, generator_dur_loss=1.713, generator_adv_loss=2.09, generator_feat_match_loss=5.937, over 55.00 samples.], tot_loss[discriminator_loss=2.695, discriminator_real_loss=1.38, discriminator_fake_loss=1.315, generator_loss=29.06, generator_mel_loss=17.7, generator_kl_loss=1.408, generator_dur_loss=1.766, generator_adv_loss=2.004, generator_feat_match_loss=6.176, over 725.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 05:42:01,280 INFO [train.py:527] (2/6) Epoch 986, batch 60, global_batch_idx: 122200, batch size: 39, loss[discriminator_loss=2.733, discriminator_real_loss=1.338, discriminator_fake_loss=1.395, generator_loss=29.6, generator_mel_loss=17.96, generator_kl_loss=1.564, generator_dur_loss=1.688, generator_adv_loss=1.974, generator_feat_match_loss=6.413, over 39.00 samples.], tot_loss[discriminator_loss=2.675, discriminator_real_loss=1.359, discriminator_fake_loss=1.316, generator_loss=29.27, generator_mel_loss=17.73, generator_kl_loss=1.451, generator_dur_loss=1.75, generator_adv_loss=2.009, generator_feat_match_loss=6.335, over 3461.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 05:42:01,281 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 05:42:09,353 INFO [train.py:591] (2/6) Epoch 986, validation: discriminator_loss=2.721, discriminator_real_loss=1.44, discriminator_fake_loss=1.281, generator_loss=28.95, generator_mel_loss=18.18, generator_kl_loss=1.218, generator_dur_loss=1.808, generator_adv_loss=1.993, generator_feat_match_loss=5.746, over 100.00 samples.
2024-03-16 05:42:09,354 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 05:44:30,358 INFO [train.py:527] (2/6) Epoch 986, batch 110, global_batch_idx: 122250, batch size: 36, loss[discriminator_loss=2.719, discriminator_real_loss=1.479, discriminator_fake_loss=1.24, generator_loss=28.78, generator_mel_loss=17.26, generator_kl_loss=1.527, generator_dur_loss=1.715, generator_adv_loss=1.748, generator_feat_match_loss=6.532, over 36.00 samples.], tot_loss[discriminator_loss=2.674, discriminator_real_loss=1.355, discriminator_fake_loss=1.319, generator_loss=29.2, generator_mel_loss=17.69, generator_kl_loss=1.444, generator_dur_loss=1.751, generator_adv_loss=2.007, generator_feat_match_loss=6.312, over 6556.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 05:45:07,672 INFO [train.py:919] (2/6) Start epoch 987
2024-03-16 05:47:13,330 INFO [train.py:527] (2/6) Epoch 987, batch 36, global_batch_idx: 122300, batch size: 39, loss[discriminator_loss=2.637, discriminator_real_loss=1.373, discriminator_fake_loss=1.264, generator_loss=30.02, generator_mel_loss=17.79, generator_kl_loss=1.625, generator_dur_loss=1.665, generator_adv_loss=2.061, generator_feat_match_loss=6.886, over 39.00 samples.], tot_loss[discriminator_loss=2.68, discriminator_real_loss=1.365, discriminator_fake_loss=1.316, generator_loss=29.13, generator_mel_loss=17.7, generator_kl_loss=1.427, generator_dur_loss=1.711, generator_adv_loss=2.034, generator_feat_match_loss=6.26, over 1976.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 05:49:36,687 INFO [train.py:527] (2/6) Epoch 987, batch 86, global_batch_idx: 122350, batch size: 25, loss[discriminator_loss=2.669, discriminator_real_loss=1.328, discriminator_fake_loss=1.341, generator_loss=28.81, generator_mel_loss=17.82, generator_kl_loss=1.752, generator_dur_loss=1.597, generator_adv_loss=2.098, generator_feat_match_loss=5.545, over 25.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.359, discriminator_fake_loss=1.317, generator_loss=29.21, generator_mel_loss=17.69, generator_kl_loss=1.468, generator_dur_loss=1.721, generator_adv_loss=2.029, generator_feat_match_loss=6.306, over 4722.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 05:51:16,834 INFO [train.py:919] (2/6) Start epoch 988
2024-03-16 05:52:15,209 INFO [train.py:527] (2/6) Epoch 988, batch 12, global_batch_idx: 122400, batch size: 64, loss[discriminator_loss=2.63, discriminator_real_loss=1.361, discriminator_fake_loss=1.269, generator_loss=28.51, generator_mel_loss=17.42, generator_kl_loss=1.334, generator_dur_loss=1.717, generator_adv_loss=2.104, generator_feat_match_loss=5.934, over 64.00 samples.], tot_loss[discriminator_loss=2.644, discriminator_real_loss=1.326, discriminator_fake_loss=1.318, generator_loss=29.38, generator_mel_loss=17.81, generator_kl_loss=1.503, generator_dur_loss=1.706, generator_adv_loss=2.032, generator_feat_match_loss=6.333, over 694.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 05:52:15,214 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 05:52:23,024 INFO [train.py:591] (2/6) Epoch 988, validation: discriminator_loss=2.709, discriminator_real_loss=1.433, discriminator_fake_loss=1.275, generator_loss=27.75, generator_mel_loss=17.91, generator_kl_loss=1.349, generator_dur_loss=1.8, generator_adv_loss=1.963, generator_feat_match_loss=4.722, over 100.00 samples.
2024-03-16 05:52:23,025 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 05:54:41,330 INFO [train.py:527] (2/6) Epoch 988, batch 62, global_batch_idx: 122450, batch size: 50, loss[discriminator_loss=2.643, discriminator_real_loss=1.289, discriminator_fake_loss=1.354, generator_loss=29.31, generator_mel_loss=18.09, generator_kl_loss=1.444, generator_dur_loss=1.668, generator_adv_loss=1.921, generator_feat_match_loss=6.195, over 50.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.351, discriminator_fake_loss=1.325, generator_loss=29.18, generator_mel_loss=17.71, generator_kl_loss=1.458, generator_dur_loss=1.72, generator_adv_loss=2.009, generator_feat_match_loss=6.28, over 3527.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 05:57:00,750 INFO [train.py:527] (2/6) Epoch 988, batch 112, global_batch_idx: 122500, batch size: 74, loss[discriminator_loss=2.661, discriminator_real_loss=1.299, discriminator_fake_loss=1.362, generator_loss=30.58, generator_mel_loss=18.27, generator_kl_loss=1.387, generator_dur_loss=1.803, generator_adv_loss=2.186, generator_feat_match_loss=6.935, over 74.00 samples.], tot_loss[discriminator_loss=2.673, discriminator_real_loss=1.352, discriminator_fake_loss=1.32, generator_loss=29.25, generator_mel_loss=17.71, generator_kl_loss=1.452, generator_dur_loss=1.73, generator_adv_loss=2.023, generator_feat_match_loss=6.338, over 6557.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 05:57:31,185 INFO [train.py:919] (2/6) Start epoch 989
2024-03-16 05:59:43,227 INFO [train.py:527] (2/6) Epoch 989, batch 38, global_batch_idx: 122550, batch size: 74, loss[discriminator_loss=2.684, discriminator_real_loss=1.381, discriminator_fake_loss=1.303, generator_loss=28.55, generator_mel_loss=17.23, generator_kl_loss=1.547, generator_dur_loss=1.755, generator_adv_loss=1.949, generator_feat_match_loss=6.068, over 74.00 samples.], tot_loss[discriminator_loss=2.669, discriminator_real_loss=1.354, discriminator_fake_loss=1.315, generator_loss=29.13, generator_mel_loss=17.63, generator_kl_loss=1.47, generator_dur_loss=1.727, generator_adv_loss=2.013, generator_feat_match_loss=6.289, over 2201.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 06:02:03,366 INFO [train.py:527] (2/6) Epoch 989, batch 88, global_batch_idx: 122600, batch size: 52, loss[discriminator_loss=2.676, discriminator_real_loss=1.274, discriminator_fake_loss=1.402, generator_loss=28.92, generator_mel_loss=17.65, generator_kl_loss=1.583, generator_dur_loss=1.628, generator_adv_loss=2.104, generator_feat_match_loss=5.95, over 52.00 samples.], tot_loss[discriminator_loss=2.669, discriminator_real_loss=1.349, discriminator_fake_loss=1.319, generator_loss=29.24, generator_mel_loss=17.69, generator_kl_loss=1.468, generator_dur_loss=1.725, generator_adv_loss=2.005, generator_feat_match_loss=6.359, over 4915.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 06:02:03,367 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 06:02:12,383 INFO [train.py:591] (2/6) Epoch 989, validation: discriminator_loss=2.731, discriminator_real_loss=1.433, discriminator_fake_loss=1.298, generator_loss=28.06, generator_mel_loss=17.94, generator_kl_loss=1.327, generator_dur_loss=1.798, generator_adv_loss=1.954, generator_feat_match_loss=5.038, over 100.00 samples.
2024-03-16 06:02:12,384 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 06:03:48,581 INFO [train.py:919] (2/6) Start epoch 990
2024-03-16 06:04:49,257 INFO [train.py:527] (2/6) Epoch 990, batch 14, global_batch_idx: 122650, batch size: 56, loss[discriminator_loss=2.603, discriminator_real_loss=1.263, discriminator_fake_loss=1.34, generator_loss=29.61, generator_mel_loss=17.89, generator_kl_loss=1.433, generator_dur_loss=1.662, generator_adv_loss=2.211, generator_feat_match_loss=6.416, over 56.00 samples.], tot_loss[discriminator_loss=2.671, discriminator_real_loss=1.347, discriminator_fake_loss=1.325, generator_loss=29.08, generator_mel_loss=17.68, generator_kl_loss=1.465, generator_dur_loss=1.711, generator_adv_loss=2.023, generator_feat_match_loss=6.199, over 828.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 06:07:08,594 INFO [train.py:527] (2/6) Epoch 990, batch 64, global_batch_idx: 122700, batch size: 44, loss[discriminator_loss=2.734, discriminator_real_loss=1.385, discriminator_fake_loss=1.349, generator_loss=29.11, generator_mel_loss=17.68, generator_kl_loss=1.635, generator_dur_loss=1.674, generator_adv_loss=1.975, generator_feat_match_loss=6.142, over 44.00 samples.], tot_loss[discriminator_loss=2.672, discriminator_real_loss=1.353, discriminator_fake_loss=1.32, generator_loss=29.31, generator_mel_loss=17.75, generator_kl_loss=1.464, generator_dur_loss=1.73, generator_adv_loss=2.017, generator_feat_match_loss=6.355, over 3528.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 06:09:27,516 INFO [train.py:527] (2/6) Epoch 990, batch 114, global_batch_idx: 122750, batch size: 58, loss[discriminator_loss=2.632, discriminator_real_loss=1.344, discriminator_fake_loss=1.288, generator_loss=29.15, generator_mel_loss=17.92, generator_kl_loss=1.453, generator_dur_loss=1.705, generator_adv_loss=1.921, generator_feat_match_loss=6.158, over 58.00 samples.], tot_loss[discriminator_loss=2.672, discriminator_real_loss=1.353, discriminator_fake_loss=1.319, generator_loss=29.25, generator_mel_loss=17.7, generator_kl_loss=1.462, generator_dur_loss=1.729, generator_adv_loss=2.017, generator_feat_match_loss=6.342, over 6389.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 06:09:53,070 INFO [train.py:919] (2/6) Start epoch 991
2024-03-16 06:12:07,880 INFO [train.py:527] (2/6) Epoch 991, batch 40, global_batch_idx: 122800, batch size: 44, loss[discriminator_loss=2.678, discriminator_real_loss=1.449, discriminator_fake_loss=1.23, generator_loss=29.81, generator_mel_loss=17.17, generator_kl_loss=1.485, generator_dur_loss=1.677, generator_adv_loss=2.077, generator_feat_match_loss=7.404, over 44.00 samples.], tot_loss[discriminator_loss=2.665, discriminator_real_loss=1.355, discriminator_fake_loss=1.311, generator_loss=29.3, generator_mel_loss=17.72, generator_kl_loss=1.445, generator_dur_loss=1.729, generator_adv_loss=2.016, generator_feat_match_loss=6.388, over 2338.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 06:12:07,881 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 06:12:15,877 INFO [train.py:591] (2/6) Epoch 991, validation: discriminator_loss=2.734, discriminator_real_loss=1.385, discriminator_fake_loss=1.349, generator_loss=28.05, generator_mel_loss=17.76, generator_kl_loss=1.38, generator_dur_loss=1.803, generator_adv_loss=1.889, generator_feat_match_loss=5.217, over 100.00 samples.
2024-03-16 06:12:15,878 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 06:14:34,126 INFO [train.py:527] (2/6) Epoch 991, batch 90, global_batch_idx: 122850, batch size: 62, loss[discriminator_loss=2.661, discriminator_real_loss=1.318, discriminator_fake_loss=1.343, generator_loss=29.27, generator_mel_loss=17.62, generator_kl_loss=1.388, generator_dur_loss=1.745, generator_adv_loss=2.121, generator_feat_match_loss=6.39, over 62.00 samples.], tot_loss[discriminator_loss=2.671, discriminator_real_loss=1.351, discriminator_fake_loss=1.32, generator_loss=29.21, generator_mel_loss=17.73, generator_kl_loss=1.46, generator_dur_loss=1.726, generator_adv_loss=2.007, generator_feat_match_loss=6.287, over 5044.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 06:16:06,298 INFO [train.py:919] (2/6) Start epoch 992
2024-03-16 06:17:12,681 INFO [train.py:527] (2/6) Epoch 992, batch 16, global_batch_idx: 122900, batch size: 48, loss[discriminator_loss=2.712, discriminator_real_loss=1.295, discriminator_fake_loss=1.417, generator_loss=29.57, generator_mel_loss=17.84, generator_kl_loss=1.562, generator_dur_loss=1.666, generator_adv_loss=2.021, generator_feat_match_loss=6.485, over 48.00 samples.], tot_loss[discriminator_loss=2.679, discriminator_real_loss=1.351, discriminator_fake_loss=1.328, generator_loss=29.24, generator_mel_loss=17.69, generator_kl_loss=1.461, generator_dur_loss=1.734, generator_adv_loss=2.012, generator_feat_match_loss=6.34, over 971.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 06:19:33,945 INFO [train.py:527] (2/6) Epoch 992, batch 66, global_batch_idx: 122950, batch size: 88, loss[discriminator_loss=2.661, discriminator_real_loss=1.307, discriminator_fake_loss=1.354, generator_loss=28.11, generator_mel_loss=17.31, generator_kl_loss=1.382, generator_dur_loss=1.813, generator_adv_loss=1.921, generator_feat_match_loss=5.685, over 88.00 samples.], tot_loss[discriminator_loss=2.682, discriminator_real_loss=1.358, discriminator_fake_loss=1.324, generator_loss=29.14, generator_mel_loss=17.72, generator_kl_loss=1.465, generator_dur_loss=1.725, generator_adv_loss=2.009, generator_feat_match_loss=6.218, over 3659.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 06:21:53,199 INFO [train.py:527] (2/6) Epoch 992, batch 116, global_batch_idx: 123000, batch size: 31, loss[discriminator_loss=2.704, discriminator_real_loss=1.307, discriminator_fake_loss=1.398, generator_loss=30.05, generator_mel_loss=17.97, generator_kl_loss=1.5, generator_dur_loss=1.617, generator_adv_loss=2.16, generator_feat_match_loss=6.804, over 31.00 samples.], tot_loss[discriminator_loss=2.675, discriminator_real_loss=1.356, discriminator_fake_loss=1.319, generator_loss=29.21, generator_mel_loss=17.69, generator_kl_loss=1.455, generator_dur_loss=1.733, generator_adv_loss=2.016, generator_feat_match_loss=6.318, over 6532.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 06:21:53,202 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 06:22:02,305 INFO [train.py:591] (2/6) Epoch 992, validation: discriminator_loss=2.774, discriminator_real_loss=1.453, discriminator_fake_loss=1.321, generator_loss=28.94, generator_mel_loss=18.67, generator_kl_loss=1.351, generator_dur_loss=1.807, generator_adv_loss=1.995, generator_feat_match_loss=5.123, over 100.00 samples.
2024-03-16 06:22:02,306 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 06:22:21,436 INFO [train.py:919] (2/6) Start epoch 993
2024-03-16 06:24:43,624 INFO [train.py:527] (2/6) Epoch 993, batch 42, global_batch_idx: 123050, batch size: 25, loss[discriminator_loss=2.66, discriminator_real_loss=1.469, discriminator_fake_loss=1.191, generator_loss=31.19, generator_mel_loss=18.15, generator_kl_loss=2.002, generator_dur_loss=1.567, generator_adv_loss=2.116, generator_feat_match_loss=7.357, over 25.00 samples.], tot_loss[discriminator_loss=2.683, discriminator_real_loss=1.354, discriminator_fake_loss=1.329, generator_loss=29.31, generator_mel_loss=17.76, generator_kl_loss=1.478, generator_dur_loss=1.727, generator_adv_loss=2.012, generator_feat_match_loss=6.329, over 2289.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 06:27:03,485 INFO [train.py:527] (2/6) Epoch 993, batch 92, global_batch_idx: 123100, batch size: 55, loss[discriminator_loss=2.678, discriminator_real_loss=1.343, discriminator_fake_loss=1.335, generator_loss=29.28, generator_mel_loss=18.01, generator_kl_loss=1.401, generator_dur_loss=1.721, generator_adv_loss=1.949, generator_feat_match_loss=6.194, over 55.00 samples.], tot_loss[discriminator_loss=2.67, discriminator_real_loss=1.351, discriminator_fake_loss=1.319, generator_loss=29.35, generator_mel_loss=17.75, generator_kl_loss=1.46, generator_dur_loss=1.741, generator_adv_loss=2.02, generator_feat_match_loss=6.384, over 5263.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 06:28:28,111 INFO [train.py:919] (2/6) Start epoch 994
2024-03-16 06:29:43,567 INFO [train.py:527] (2/6) Epoch 994, batch 18, global_batch_idx: 123150, batch size: 52, loss[discriminator_loss=2.644, discriminator_real_loss=1.333, discriminator_fake_loss=1.311, generator_loss=28.56, generator_mel_loss=17.92, generator_kl_loss=1.529, generator_dur_loss=1.694, generator_adv_loss=2.002, generator_feat_match_loss=5.414, over 52.00 samples.], tot_loss[discriminator_loss=2.67, discriminator_real_loss=1.354, discriminator_fake_loss=1.316, generator_loss=29.02, generator_mel_loss=17.61, generator_kl_loss=1.423, generator_dur_loss=1.754, generator_adv_loss=2.016, generator_feat_match_loss=6.217, over 1105.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 06:32:04,813 INFO [train.py:527] (2/6) Epoch 994, batch 68, global_batch_idx: 123200, batch size: 52, loss[discriminator_loss=2.721, discriminator_real_loss=1.359, discriminator_fake_loss=1.362, generator_loss=29.45, generator_mel_loss=17.81, generator_kl_loss=1.507, generator_dur_loss=1.713, generator_adv_loss=1.909, generator_feat_match_loss=6.507, over 52.00 samples.], tot_loss[discriminator_loss=2.667, discriminator_real_loss=1.348, discriminator_fake_loss=1.319, generator_loss=29.24, generator_mel_loss=17.74, generator_kl_loss=1.424, generator_dur_loss=1.747, generator_adv_loss=2.012, generator_feat_match_loss=6.324, over 3968.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 06:32:04,814 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 06:32:12,730 INFO [train.py:591] (2/6) Epoch 994, validation: discriminator_loss=2.784, discriminator_real_loss=1.422, discriminator_fake_loss=1.362, generator_loss=28.28, generator_mel_loss=18.37, generator_kl_loss=1.264, generator_dur_loss=1.805, generator_adv_loss=1.849, generator_feat_match_loss=4.988, over 100.00 samples.
2024-03-16 06:32:12,731 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 06:34:30,992 INFO [train.py:527] (2/6) Epoch 994, batch 118, global_batch_idx: 123250, batch size: 25, loss[discriminator_loss=2.67, discriminator_real_loss=1.326, discriminator_fake_loss=1.344, generator_loss=30.29, generator_mel_loss=18.14, generator_kl_loss=1.779, generator_dur_loss=1.592, generator_adv_loss=2.199, generator_feat_match_loss=6.573, over 25.00 samples.], tot_loss[discriminator_loss=2.668, discriminator_real_loss=1.35, discriminator_fake_loss=1.318, generator_loss=29.19, generator_mel_loss=17.7, generator_kl_loss=1.426, generator_dur_loss=1.744, generator_adv_loss=2.014, generator_feat_match_loss=6.307, over 6843.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 06:34:46,485 INFO [train.py:919] (2/6) Start epoch 995
2024-03-16 06:37:11,258 INFO [train.py:527] (2/6) Epoch 995, batch 44, global_batch_idx: 123300, batch size: 56, loss[discriminator_loss=2.62, discriminator_real_loss=1.308, discriminator_fake_loss=1.312, generator_loss=28.93, generator_mel_loss=17.55, generator_kl_loss=1.472, generator_dur_loss=1.757, generator_adv_loss=2.031, generator_feat_match_loss=6.119, over 56.00 samples.], tot_loss[discriminator_loss=2.682, discriminator_real_loss=1.359, discriminator_fake_loss=1.322, generator_loss=29.11, generator_mel_loss=17.76, generator_kl_loss=1.437, generator_dur_loss=1.73, generator_adv_loss=2.007, generator_feat_match_loss=6.18, over 2507.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 06:39:29,424 INFO [train.py:527] (2/6) Epoch 995, batch 94, global_batch_idx: 123350, batch size: 39, loss[discriminator_loss=2.668, discriminator_real_loss=1.435, discriminator_fake_loss=1.232, generator_loss=29.82, generator_mel_loss=17.89, generator_kl_loss=1.543, generator_dur_loss=1.612, generator_adv_loss=2.066, generator_feat_match_loss=6.712, over 39.00 samples.], tot_loss[discriminator_loss=2.672, discriminator_real_loss=1.353, discriminator_fake_loss=1.319, generator_loss=29.18, generator_mel_loss=17.67, generator_kl_loss=1.427, generator_dur_loss=1.746, generator_adv_loss=2.023, generator_feat_match_loss=6.306, over 5506.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 06:40:52,509 INFO [train.py:919] (2/6) Start epoch 996
2024-03-16 06:42:12,876 INFO [train.py:527] (2/6) Epoch 996, batch 20, global_batch_idx: 123400, batch size: 66, loss[discriminator_loss=2.703, discriminator_real_loss=1.335, discriminator_fake_loss=1.368, generator_loss=28.08, generator_mel_loss=17.22, generator_kl_loss=1.411, generator_dur_loss=1.755, generator_adv_loss=1.955, generator_feat_match_loss=5.733, over 66.00 samples.], tot_loss[discriminator_loss=2.675, discriminator_real_loss=1.34, discriminator_fake_loss=1.335, generator_loss=29.12, generator_mel_loss=17.61, generator_kl_loss=1.405, generator_dur_loss=1.751, generator_adv_loss=2.012, generator_feat_match_loss=6.34, over 1315.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 06:42:12,878 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 06:42:20,825 INFO [train.py:591] (2/6) Epoch 996, validation: discriminator_loss=2.751, discriminator_real_loss=1.435, discriminator_fake_loss=1.315, generator_loss=27.61, generator_mel_loss=17.61, generator_kl_loss=1.406, generator_dur_loss=1.802, generator_adv_loss=1.891, generator_feat_match_loss=4.899, over 100.00 samples.
2024-03-16 06:42:20,826 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 06:44:41,161 INFO [train.py:527] (2/6) Epoch 996, batch 70, global_batch_idx: 123450, batch size: 16, loss[discriminator_loss=2.72, discriminator_real_loss=1.309, discriminator_fake_loss=1.411, generator_loss=30.65, generator_mel_loss=17.76, generator_kl_loss=1.965, generator_dur_loss=1.546, generator_adv_loss=1.955, generator_feat_match_loss=7.426, over 16.00 samples.], tot_loss[discriminator_loss=2.673, discriminator_real_loss=1.351, discriminator_fake_loss=1.322, generator_loss=29.17, generator_mel_loss=17.66, generator_kl_loss=1.421, generator_dur_loss=1.74, generator_adv_loss=2.011, generator_feat_match_loss=6.336, over 4050.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 06:46:58,114 INFO [train.py:527] (2/6) Epoch 996, batch 120, global_batch_idx: 123500, batch size: 70, loss[discriminator_loss=2.713, discriminator_real_loss=1.382, discriminator_fake_loss=1.331, generator_loss=28.61, generator_mel_loss=17.49, generator_kl_loss=1.373, generator_dur_loss=1.738, generator_adv_loss=1.983, generator_feat_match_loss=6.031, over 70.00 samples.], tot_loss[discriminator_loss=2.676, discriminator_real_loss=1.355, discriminator_fake_loss=1.321, generator_loss=29.19, generator_mel_loss=17.69, generator_kl_loss=1.427, generator_dur_loss=1.738, generator_adv_loss=2.011, generator_feat_match_loss=6.327, over 6969.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 06:47:07,000 INFO [train.py:919] (2/6) Start epoch 997
2024-03-16 06:49:38,287 INFO [train.py:527] (2/6) Epoch 997, batch 46, global_batch_idx: 123550, batch size: 47, loss[discriminator_loss=2.637, discriminator_real_loss=1.366, discriminator_fake_loss=1.272, generator_loss=29.35, generator_mel_loss=17.92, generator_kl_loss=1.511, generator_dur_loss=1.675, generator_adv_loss=1.924, generator_feat_match_loss=6.326, over 47.00 samples.], tot_loss[discriminator_loss=2.688, discriminator_real_loss=1.364, discriminator_fake_loss=1.324, generator_loss=29.04, generator_mel_loss=17.72, generator_kl_loss=1.426, generator_dur_loss=1.724, generator_adv_loss=2.008, generator_feat_match_loss=6.168, over 2521.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 06:51:52,873 INFO [train.py:527] (2/6) Epoch 997, batch 96, global_batch_idx: 123600, batch size: 52, loss[discriminator_loss=2.614, discriminator_real_loss=1.316, discriminator_fake_loss=1.298, generator_loss=29.68, generator_mel_loss=17.57, generator_kl_loss=1.629, generator_dur_loss=1.657, generator_adv_loss=2.144, generator_feat_match_loss=6.68, over 52.00 samples.], tot_loss[discriminator_loss=2.677, discriminator_real_loss=1.357, discriminator_fake_loss=1.32, generator_loss=29.21, generator_mel_loss=17.75, generator_kl_loss=1.438, generator_dur_loss=1.723, generator_adv_loss=2.025, generator_feat_match_loss=6.277, over 5331.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 06:51:52,874 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 06:52:00,767 INFO [train.py:591] (2/6) Epoch 997, validation: discriminator_loss=2.713, discriminator_real_loss=1.463, discriminator_fake_loss=1.25, generator_loss=28.08, generator_mel_loss=18.1, generator_kl_loss=1.252, generator_dur_loss=1.795, generator_adv_loss=2.04, generator_feat_match_loss=4.895, over 100.00 samples.
2024-03-16 06:52:00,768 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 06:53:18,644 INFO [train.py:919] (2/6) Start epoch 998
2024-03-16 06:54:45,909 INFO [train.py:527] (2/6) Epoch 998, batch 22, global_batch_idx: 123650, batch size: 59, loss[discriminator_loss=2.692, discriminator_real_loss=1.316, discriminator_fake_loss=1.377, generator_loss=29.55, generator_mel_loss=17.92, generator_kl_loss=1.479, generator_dur_loss=1.734, generator_adv_loss=2.115, generator_feat_match_loss=6.3, over 59.00 samples.], tot_loss[discriminator_loss=2.681, discriminator_real_loss=1.358, discriminator_fake_loss=1.322, generator_loss=29.04, generator_mel_loss=17.73, generator_kl_loss=1.421, generator_dur_loss=1.761, generator_adv_loss=1.994, generator_feat_match_loss=6.127, over 1505.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 06:57:01,523 INFO [train.py:527] (2/6) Epoch 998, batch 72, global_batch_idx: 123700, batch size: 48, loss[discriminator_loss=2.629, discriminator_real_loss=1.358, discriminator_fake_loss=1.27, generator_loss=29.72, generator_mel_loss=17.78, generator_kl_loss=1.482, generator_dur_loss=1.691, generator_adv_loss=2.131, generator_feat_match_loss=6.638, over 48.00 samples.], tot_loss[discriminator_loss=2.673, discriminator_real_loss=1.357, discriminator_fake_loss=1.316, generator_loss=29.14, generator_mel_loss=17.7, generator_kl_loss=1.448, generator_dur_loss=1.74, generator_adv_loss=2.012, generator_feat_match_loss=6.242, over 4366.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 06:59:20,802 INFO [train.py:527] (2/6) Epoch 998, batch 122, global_batch_idx: 123750, batch size: 77, loss[discriminator_loss=2.712, discriminator_real_loss=1.42, discriminator_fake_loss=1.292, generator_loss=28.03, generator_mel_loss=17.38, generator_kl_loss=1.398, generator_dur_loss=1.805, generator_adv_loss=1.885, generator_feat_match_loss=5.57, over 77.00 samples.], tot_loss[discriminator_loss=2.669, discriminator_real_loss=1.352, discriminator_fake_loss=1.317, generator_loss=29.21, generator_mel_loss=17.68, generator_kl_loss=1.444, generator_dur_loss=1.739, generator_adv_loss=2.013, generator_feat_match_loss=6.325, over 7288.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 06:59:26,587 INFO [train.py:919] (2/6) Start epoch 999
2024-03-16 07:02:04,296 INFO [train.py:527] (2/6) Epoch 999, batch 48, global_batch_idx: 123800, batch size: 83, loss[discriminator_loss=2.674, discriminator_real_loss=1.372, discriminator_fake_loss=1.302, generator_loss=28.81, generator_mel_loss=17.9, generator_kl_loss=1.286, generator_dur_loss=1.794, generator_adv_loss=1.871, generator_feat_match_loss=5.966, over 83.00 samples.], tot_loss[discriminator_loss=2.671, discriminator_real_loss=1.356, discriminator_fake_loss=1.315, generator_loss=29.31, generator_mel_loss=17.75, generator_kl_loss=1.451, generator_dur_loss=1.731, generator_adv_loss=2.026, generator_feat_match_loss=6.35, over 2817.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 07:02:04,297 INFO [train.py:581] (2/6) Computing validation loss
2024-03-16 07:02:12,163 INFO [train.py:591] (2/6) Epoch 999, validation: discriminator_loss=2.747, discriminator_real_loss=1.323, discriminator_fake_loss=1.424, generator_loss=28.31, generator_mel_loss=18.07, generator_kl_loss=1.205, generator_dur_loss=1.805, generator_adv_loss=1.787, generator_feat_match_loss=5.439, over 100.00 samples.
2024-03-16 07:02:12,164 INFO [train.py:592] (2/6) Maximum memory allocated so far is 29117MB
2024-03-16 07:04:29,734 INFO [train.py:527] (2/6) Epoch 999, batch 98, global_batch_idx: 123850, batch size: 44, loss[discriminator_loss=2.676, discriminator_real_loss=1.294, discriminator_fake_loss=1.383, generator_loss=30.61, generator_mel_loss=17.92, generator_kl_loss=1.641, generator_dur_loss=1.639, generator_adv_loss=2.079, generator_feat_match_loss=7.328, over 44.00 samples.], tot_loss[discriminator_loss=2.672, discriminator_real_loss=1.352, discriminator_fake_loss=1.321, generator_loss=29.33, generator_mel_loss=17.75, generator_kl_loss=1.438, generator_dur_loss=1.731, generator_adv_loss=2.02, generator_feat_match_loss=6.397, over 5664.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 07:05:42,783 INFO [train.py:919] (2/6) Start epoch 1000
2024-03-16 07:07:13,379 INFO [train.py:527] (2/6) Epoch 1000, batch 24, global_batch_idx: 123900, batch size: 45, loss[discriminator_loss=2.686, discriminator_real_loss=1.328, discriminator_fake_loss=1.358, generator_loss=29.37, generator_mel_loss=17.82, generator_kl_loss=1.541, generator_dur_loss=1.651, generator_adv_loss=2.169, generator_feat_match_loss=6.196, over 45.00 samples.], tot_loss[discriminator_loss=2.661, discriminator_real_loss=1.338, discriminator_fake_loss=1.324, generator_loss=29.48, generator_mel_loss=17.77, generator_kl_loss=1.451, generator_dur_loss=1.718, generator_adv_loss=2.061, generator_feat_match_loss=6.484, over 1271.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 07:09:33,634 INFO [train.py:527] (2/6) Epoch 1000, batch 74, global_batch_idx: 123950, batch size: 66, loss[discriminator_loss=2.622, discriminator_real_loss=1.347, discriminator_fake_loss=1.275, generator_loss=29.75, generator_mel_loss=17.4, generator_kl_loss=1.562, generator_dur_loss=1.776, generator_adv_loss=2.019, generator_feat_match_loss=6.989, over 66.00 samples.], tot_loss[discriminator_loss=2.668, discriminator_real_loss=1.35, discriminator_fake_loss=1.319, generator_loss=29.32, generator_mel_loss=17.68, generator_kl_loss=1.441, generator_dur_loss=1.742, generator_adv_loss=2.039, generator_feat_match_loss=6.423, over 4364.00 samples.], cur_lr_g: 1.77e-04, cur_lr_d: 1.77e-04, 
2024-03-16 07:11:48,749 INFO [train.py:977] (2/6) Done!