import from zenodo
Browse files- README.md +43 -0
- exp/diar_stats_8k/train/feats_stats.npz +0 -0
- exp/diar_train_diar_raw_max_epoch20/19epoch.pth +3 -0
- exp/diar_train_diar_raw_max_epoch20/RESULTS.md +26 -0
- exp/diar_train_diar_raw_max_epoch20/config.yaml +137 -0
- exp/diar_train_diar_raw_max_epoch20/images/acc.png +0 -0
- exp/diar_train_diar_raw_max_epoch20/images/backward_time.png +0 -0
- exp/diar_train_diar_raw_max_epoch20/images/cf.png +0 -0
- exp/diar_train_diar_raw_max_epoch20/images/der.png +0 -0
- exp/diar_train_diar_raw_max_epoch20/images/fa.png +0 -0
- exp/diar_train_diar_raw_max_epoch20/images/forward_time.png +0 -0
- exp/diar_train_diar_raw_max_epoch20/images/gpu_max_cached_mem_GB.png +0 -0
- exp/diar_train_diar_raw_max_epoch20/images/iter_time.png +0 -0
- exp/diar_train_diar_raw_max_epoch20/images/loss.png +0 -0
- exp/diar_train_diar_raw_max_epoch20/images/mi.png +0 -0
- exp/diar_train_diar_raw_max_epoch20/images/optim0_lr0.png +0 -0
- exp/diar_train_diar_raw_max_epoch20/images/optim_step_time.png +0 -0
- exp/diar_train_diar_raw_max_epoch20/images/sad_fr.png +0 -0
- exp/diar_train_diar_raw_max_epoch20/images/sad_mr.png +0 -0
- exp/diar_train_diar_raw_max_epoch20/images/train_time.png +0 -0
- meta.yaml +8 -0
README.md
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---
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tags:
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- espnet
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- audio
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- <add_more_tags>
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language: en
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datasets:
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- mini_librispeech
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license: cc-by-4.0
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---
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## ESPnet2 DIAR pretrained model
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### `Yushi Ueda/mini_librispeech_diar_train_diar_raw_max_epoch20_valid.acc.best`
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♻️ Imported from https://zenodo.org/record/5264020/
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This model was trained by Yushi Ueda using mini_librispeech/diar1 recipe in [espnet](https://github.com/espnet/espnet/).
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### Demo: How to use in ESPnet2
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```python
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# coming soon
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```
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### Citing ESPnet
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```BibTex
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@inproceedings{watanabe2018espnet,
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author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson {Enrique Yalta Soplin} and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
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title={{ESPnet}: End-to-End Speech Processing Toolkit},
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year={2018},
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booktitle={Proceedings of Interspeech},
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pages={2207--2211},
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doi={10.21437/Interspeech.2018-1456},
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url={http://dx.doi.org/10.21437/Interspeech.2018-1456}
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}
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```
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or arXiv:
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```bibtex
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@misc{watanabe2018espnet,
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title={ESPnet: End-to-End Speech Processing Toolkit},
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author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Enrique Yalta Soplin and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
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year={2018},
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eprint={1804.00015},
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archivePrefix={arXiv},
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primaryClass={cs.CL}
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}
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```
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exp/diar_stats_8k/train/feats_stats.npz
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Binary file (1.4 kB). View file
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exp/diar_train_diar_raw_max_epoch20/19epoch.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:c133eb6c494ec800b8be6b6c14aa91e890af7b19488f36423a7d56105987f493
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size 4404388
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exp/diar_train_diar_raw_max_epoch20/RESULTS.md
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<!-- Generated by scripts/utils/show_diar_result.sh -->
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# RESULTS
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## Environments
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- date: `Wed Aug 25 23:29:07 EDT 2021`
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- python version: `3.7.11 (default, Jul 27 2021, 14:32:16) [GCC 7.5.0]`
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- espnet version: `espnet 0.10.2a1`
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- pytorch version: `pytorch 1.9.0+cu102`
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- Git hash: `19bcd34f9395e01e54a97c4db5ecbcedb429dd92`
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- Commit date: `Tue Aug 24 19:50:44 2021 -0400`
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## `diar_train_diar_raw_max_epoch20`
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### DER
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`dev_clean_2_ns2_beta2_500`
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|threshold_median_collar|DER|
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|---|---|
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|result_th0.3_med1_collar0.0|32.42|
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|result_th0.3_med11_collar0.0|32.03|
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|result_th0.4_med1_collar0.0|30.96|
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|result_th0.4_med11_collar0.0|30.26|
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|result_th0.5_med1_collar0.0|30.35|
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|result_th0.5_med11_collar0.0|29.37|
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|result_th0.6_med1_collar0.0|30.77|
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|result_th0.6_med11_collar0.0|29.52|
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|result_th0.7_med1_collar0.0|32.60|
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|result_th0.7_med11_collar0.0|31.03|
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exp/diar_train_diar_raw_max_epoch20/config.yaml
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config: conf/train_diar.yaml
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print_config: false
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log_level: INFO
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dry_run: false
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iterator_type: chunk
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output_dir: exp/diar_train_diar_raw_max_epoch20
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ngpu: 1
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seed: 0
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num_workers: 1
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num_att_plot: 3
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dist_backend: nccl
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dist_init_method: env://
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dist_world_size: null
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dist_rank: null
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local_rank: 0
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dist_master_addr: null
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dist_master_port: null
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dist_launcher: null
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multiprocessing_distributed: false
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unused_parameters: false
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sharded_ddp: false
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cudnn_enabled: true
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cudnn_benchmark: false
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cudnn_deterministic: true
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collect_stats: false
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write_collected_feats: false
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max_epoch: 20
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patience: 3
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val_scheduler_criterion:
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- valid
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- loss
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early_stopping_criterion:
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- valid
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- loss
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- min
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best_model_criterion:
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- - valid
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- acc
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- max
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keep_nbest_models: 3
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grad_clip: 5
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grad_clip_type: 2.0
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grad_noise: false
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accum_grad: 2
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no_forward_run: false
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resume: true
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train_dtype: float32
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use_amp: false
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log_interval: null
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use_tensorboard: true
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use_wandb: false
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wandb_project: null
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wandb_id: null
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wandb_entity: null
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wandb_name: null
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wandb_model_log_interval: -1
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detect_anomaly: false
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pretrain_path: null
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init_param: []
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ignore_init_mismatch: false
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freeze_param: []
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num_iters_per_epoch: null
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batch_size: 16
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valid_batch_size: null
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batch_bins: 1000000
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valid_batch_bins: null
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train_shape_file:
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- exp/diar_stats_8k/train/speech_shape
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- exp/diar_stats_8k/train/spk_labels_shape
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valid_shape_file:
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- exp/diar_stats_8k/valid/speech_shape
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- exp/diar_stats_8k/valid/spk_labels_shape
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batch_type: folded
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valid_batch_type: null
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fold_length:
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- 80000
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- 800
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sort_in_batch: descending
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sort_batch: descending
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multiple_iterator: false
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chunk_length: 200000
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chunk_shift_ratio: 0.5
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num_cache_chunks: 64
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train_data_path_and_name_and_type:
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- - dump/raw/simu/data/train_clean_5_ns2_beta2_500/wav.scp
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- speech
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- sound
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- - dump/raw/simu/data/train_clean_5_ns2_beta2_500/espnet_rttm
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- spk_labels
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- rttm
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valid_data_path_and_name_and_type:
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- - dump/raw/simu/data/dev_clean_2_ns2_beta2_500/wav.scp
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- speech
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- sound
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- - dump/raw/simu/data/dev_clean_2_ns2_beta2_500/espnet_rttm
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- spk_labels
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- rttm
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allow_variable_data_keys: false
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max_cache_size: 0.0
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max_cache_fd: 32
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valid_max_cache_size: null
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optim: adam
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optim_conf:
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lr: 0.01
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scheduler: noamlr
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scheduler_conf:
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warmup_steps: 1000
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num_spk: 2
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init: xavier_uniform
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input_size: null
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model_conf:
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loss_type: pit
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use_preprocessor: true
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frontend: default
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frontend_conf:
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fs: 8k
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hop_length: 128
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normalize: global_mvn
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normalize_conf:
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stats_file: exp/diar_stats_8k/train/feats_stats.npz
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encoder: transformer
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encoder_conf:
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input_layer: linear
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num_blocks: 2
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linear_units: 512
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dropout_rate: 0.1
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output_size: 256
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attention_heads: 4
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attention_dropout_rate: 0.0
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decoder: linear
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decoder_conf: {}
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label_aggregator: label_aggregator
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label_aggregator_conf: {}
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required:
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- output_dir
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version: 0.10.2a1
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distributed: false
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exp/diar_train_diar_raw_max_epoch20/images/acc.png
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exp/diar_train_diar_raw_max_epoch20/images/backward_time.png
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exp/diar_train_diar_raw_max_epoch20/images/cf.png
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exp/diar_train_diar_raw_max_epoch20/images/der.png
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exp/diar_train_diar_raw_max_epoch20/images/fa.png
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exp/diar_train_diar_raw_max_epoch20/images/forward_time.png
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exp/diar_train_diar_raw_max_epoch20/images/gpu_max_cached_mem_GB.png
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exp/diar_train_diar_raw_max_epoch20/images/iter_time.png
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exp/diar_train_diar_raw_max_epoch20/images/loss.png
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exp/diar_train_diar_raw_max_epoch20/images/mi.png
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exp/diar_train_diar_raw_max_epoch20/images/optim0_lr0.png
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exp/diar_train_diar_raw_max_epoch20/images/optim_step_time.png
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exp/diar_train_diar_raw_max_epoch20/images/sad_fr.png
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exp/diar_train_diar_raw_max_epoch20/images/sad_mr.png
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exp/diar_train_diar_raw_max_epoch20/images/train_time.png
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meta.yaml
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espnet: 0.10.2a1
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files:
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model_file: exp/diar_train_diar_raw_max_epoch20/19epoch.pth
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python: "3.7.11 (default, Jul 27 2021, 14:32:16) \n[GCC 7.5.0]"
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timestamp: 1629948586.911716
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torch: 1.9.0+cu102
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yaml_files:
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train_config: exp/diar_train_diar_raw_max_epoch20/config.yaml
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