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icefall-asr-spgispeech-pruned-transducer-stateless2

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add pretrained model

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  1. .gitattributes +1 -0
  2. README.md +31 -0
  3. data/lang_bpe_500/L.pt +3 -0
  4. data/lang_bpe_500/L_disambig.pt +3 -0
  5. data/lang_bpe_500/Linv.pt +3 -0
  6. data/lang_bpe_500/bpe.model +3 -0
  7. data/lang_bpe_500/lexicon.txt +3 -0
  8. data/lang_bpe_500/lexicon_disambig.txt +3 -0
  9. data/lang_bpe_500/tokens.txt +3 -0
  10. data/lang_bpe_500/unigram_500.model +3 -0
  11. data/lang_bpe_500/unigram_500.vocab +500 -0
  12. data/lang_bpe_500/words.txt +3 -0
  13. data/lm/G_3_gram.pt +3 -0
  14. exp/pretrained.pt +3 -0
  15. log/beam_search/errs-dev-beam_size_4-epoch-28-avg-15-beam-4.txt +3 -0
  16. log/beam_search/errs-val-beam_size_4-epoch-28-avg-15-beam-4.txt +3 -0
  17. log/beam_search/log-decode-epoch-28-avg-15-beam-4-2022-05-11-08-17-51 +429 -0
  18. log/beam_search/recogs-dev-beam_size_4-epoch-28-avg-15-beam-4.txt +3 -0
  19. log/beam_search/recogs-val-beam_size_4-epoch-28-avg-15-beam-4.txt +3 -0
  20. log/beam_search/wer-summary-dev-beam_size_4-epoch-28-avg-15-beam-4.txt +3 -0
  21. log/beam_search/wer-summary-val-beam_size_4-epoch-28-avg-15-beam-4.txt +3 -0
  22. log/fast_beam_search/errs-dev-beam_4.0_max_contexts_4_max_states_8-epoch-28-avg-15-beam-4.0-max-contexts-4-max-states-8.txt +3 -0
  23. log/fast_beam_search/errs-val-beam_4.0_max_contexts_4_max_states_8-epoch-28-avg-15-beam-4.0-max-contexts-4-max-states-8.txt +3 -0
  24. log/fast_beam_search/log-decode-epoch-28-avg-15-beam-4.0-max-contexts-4-max-states-8-2022-05-10-21-01-44 +429 -0
  25. log/fast_beam_search/recogs-dev-beam_4.0_max_contexts_4_max_states_8-epoch-28-avg-15-beam-4.0-max-contexts-4-max-states-8.txt +3 -0
  26. log/fast_beam_search/recogs-val-beam_4.0_max_contexts_4_max_states_8-epoch-28-avg-15-beam-4.0-max-contexts-4-max-states-8.txt +3 -0
  27. log/fast_beam_search/wer-summary-dev-beam_4.0_max_contexts_4_max_states_8-epoch-28-avg-15-beam-4.0-max-contexts-4-max-states-8.txt +3 -0
  28. log/fast_beam_search/wer-summary-val-beam_4.0_max_contexts_4_max_states_8-epoch-28-avg-15-beam-4.0-max-contexts-4-max-states-8.txt +3 -0
  29. log/greedy_search/errs-dev-greedy_search-epoch-28-avg-15-context-2-max-sym-per-frame-1.txt +3 -0
  30. log/greedy_search/errs-val-greedy_search-epoch-28-avg-15-context-2-max-sym-per-frame-1.txt +3 -0
  31. log/greedy_search/log-decode-epoch-28-avg-15-context-2-max-sym-per-frame-1-2022-05-11-08-06-04 +32 -0
  32. log/greedy_search/recogs-dev-greedy_search-epoch-28-avg-15-context-2-max-sym-per-frame-1.txt +3 -0
  33. log/greedy_search/recogs-val-greedy_search-epoch-28-avg-15-context-2-max-sym-per-frame-1.txt +3 -0
  34. log/greedy_search/wer-summary-dev-greedy_search-epoch-28-avg-15-context-2-max-sym-per-frame-1.txt +3 -0
  35. log/greedy_search/wer-summary-val-greedy_search-epoch-28-avg-15-context-2-max-sym-per-frame-1.txt +3 -0
  36. log/log-train-2022-05-03-11-40-27-0 +0 -0
  37. log/log-train-2022-05-03-11-40-27-1 +0 -0
  38. log/log-train-2022-05-03-11-40-27-2 +0 -0
  39. log/log-train-2022-05-03-11-40-27-3 +0 -0
  40. log/log-train-2022-05-03-11-40-27-4 +0 -0
  41. log/log-train-2022-05-03-11-40-27-5 +0 -0
  42. log/log-train-2022-05-03-11-40-27-6 +0 -0
  43. log/log-train-2022-05-03-11-40-27-7 +0 -0
  44. log/modified_beam_search/errs-dev-beam_size_4-epoch-28-avg-15-beam-4.txt +3 -0
  45. log/modified_beam_search/errs-val-beam_size_4-epoch-28-avg-15-beam-4.txt +3 -0
  46. log/modified_beam_search/log-decode-epoch-28-avg-15-beam-4-2022-05-12-21-03-04 +429 -0
  47. log/modified_beam_search/recogs-dev-beam_size_4-epoch-28-avg-15-beam-4.txt +3 -0
  48. log/modified_beam_search/recogs-val-beam_size_4-epoch-28-avg-15-beam-4.txt +3 -0
  49. log/modified_beam_search/wer-summary-dev-beam_size_4-epoch-28-avg-15-beam-4.txt +3 -0
  50. log/modified_beam_search/wer-summary-val-beam_size_4-epoch-28-avg-15-beam-4.txt +3 -0
.gitattributes CHANGED
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README.md CHANGED
@@ -1,3 +1,34 @@
1
  ---
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  license: mit
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  license: mit
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  ---
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+ # SPGISpeech
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+
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+ SPGISpeech consists of 5,000 hours of recorded company earnings calls and their respective
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+ transcriptions. The original calls were split into slices ranging from 5 to 15 seconds in
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+ length to allow easy training for speech recognition systems. Calls represent a broad
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+ cross-section of international business English; SPGISpeech contains approximately 50,000
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+ speakers, one of the largest numbers of any speech corpus, and offers a variety of L1 and
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+ L2 English accents. The format of each WAV file is single channel, 16kHz, 16 bit audio.
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+
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+ Transcription text represents the output of several stages of manual post-processing.
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+ As such, the text contains polished English orthography following a detailed style guide,
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+ including proper casing, punctuation, and denormalized non-standard words such as numbers
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+ and acronyms, making SPGISpeech suited for training fully formatted end-to-end models.
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+
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+ Official reference:
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+
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+ O’Neill, P.K., Lavrukhin, V., Majumdar, S., Noroozi, V., Zhang, Y., Kuchaiev, O., Balam,
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+ J., Dovzhenko, Y., Freyberg, K., Shulman, M.D., Ginsburg, B., Watanabe, S., & Kucsko, G.
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+ (2021). SPGISpeech: 5, 000 hours of transcribed financial audio for fully formatted
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+ end-to-end speech recognition. ArXiv, abs/2104.02014.
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+
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+ ArXiv link: https://arxiv.org/abs/2104.02014
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+
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+ ## Performance Record
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+
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+ | Decoding method | val |
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+ |---------------------------|------------|
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+ | greedy search | 2.40 |
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+ | beam search | 2.24 |
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+ | modified beam search | 2.30 |
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+ | fast beam search | 2.35 |
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1
+ 2022-05-11 08:17:51,501 INFO [decode.py:459] Decoding started
2
+ 2022-05-11 08:17:51,501 INFO [decode.py:465] Device: cuda:0
3
+ 2022-05-11 08:17:51,519 INFO [decode.py:474] {'best_train_loss': inf, 'best_valid_loss': inf, 'best_train_epoch': -1, 'best_valid_epoch': -1, 'batch_idx_train': 0, 'log_interval': 50, 'reset_interval': 200, 'valid_interval': 3000, 'feature_dim': 80, 'subsampling_factor': 4, 'encoder_dim': 512, 'nhead': 8, 'dim_feedforward': 2048, 'num_encoder_layers': 12, 'decoder_dim': 512, 'joiner_dim': 512, 'model_warm_step': 3000, 'env_info': {'k2-version': '1.14', 'k2-build-type': 'Debug', 'k2-with-cuda': True, 'k2-git-sha1': '1b29f0a946f50186aaa82df46a59f492ade9692b', 'k2-git-date': 'Tue Apr 12 20:46:49 2022', 'lhotse-version': '1.1.0', 'torch-version': '1.10.1+cu111', 'torch-cuda-available': True, 'torch-cuda-version': '11.1', 'python-version': '3.8', 'icefall-git-branch': 'spgi', 'icefall-git-sha1': '4e1205a-dirty', 'icefall-git-date': 'Tue May 10 20:51:30 2022', 'icefall-path': '/exp/draj/mini_scale_2022/icefall', 'k2-path': '/exp/draj/mini_scale_2022/k2/k2/python/k2/__init__.py', 'lhotse-path': '/exp/draj/mini_scale_2022/lhotse/lhotse/__init__.py', 'hostname': 'r8n03', 'IP address': '10.1.8.3'}, 'epoch': 28, 'avg': 15, 'avg_last_n': 10, 'exp_dir': PosixPath('pruned_transducer_stateless2/exp/v2'), 'bpe_model': 'data/lang_bpe_500/bpe.model', 'decoding_method': 'beam_search', 'beam_size': 4, 'beam': 4, 'max_contexts': 4, 'max_states': 8, 'context_size': 2, 'max_sym_per_frame': 1, 'manifest_dir': PosixPath('data/manifests'), 'enable_musan': True, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'max_duration': 500, 'num_buckets': 30, 'on_the_fly_feats': False, 'shuffle': True, 'num_workers': 8, 'enable_spec_aug': True, 'spec_aug_time_warp_factor': 80, 'res_dir': PosixPath('pruned_transducer_stateless2/exp/v2/beam_search'), 'suffix': 'epoch-28-avg-15-beam-4', 'blank_id': 0, 'vocab_size': 500}
4
+ 2022-05-11 08:17:51,519 INFO [decode.py:476] About to create model
5
+ 2022-05-11 08:17:52,200 INFO [decode.py:481] averaging ['pruned_transducer_stateless2/exp/v2/checkpoint-696000.pt', 'pruned_transducer_stateless2/exp/v2/checkpoint-688000.pt', 'pruned_transducer_stateless2/exp/v2/checkpoint-680000.pt', 'pruned_transducer_stateless2/exp/v2/checkpoint-672000.pt', 'pruned_transducer_stateless2/exp/v2/checkpoint-664000.pt', 'pruned_transducer_stateless2/exp/v2/checkpoint-656000.pt', 'pruned_transducer_stateless2/exp/v2/checkpoint-648000.pt', 'pruned_transducer_stateless2/exp/v2/checkpoint-640000.pt', 'pruned_transducer_stateless2/exp/v2/checkpoint-632000.pt', 'pruned_transducer_stateless2/exp/v2/checkpoint-624000.pt']
6
+ 2022-05-11 08:19:24,865 INFO [decode.py:506] Number of model parameters: 78648040
7
+ 2022-05-11 08:19:24,866 INFO [asr_datamodule.py:326] About to get SPGISpeech dev cuts
8
+ 2022-05-11 08:19:24,889 INFO [asr_datamodule.py:331] About to get SPGISpeech val cuts
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+ 2022-05-11 08:20:59,119 INFO [decode.py:382] batch 0/?, cuts processed until now is 45
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+ 2022-05-11 08:23:55,089 INFO [decode.py:382] batch 2/?, cuts processed until now is 177
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+ 2022-05-11 10:04:53,708 INFO [decode.py:382] batch 70/?, cuts processed until now is 3783
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+ 2022-05-11 10:06:34,020 INFO [decode.py:382] batch 72/?, cuts processed until now is 3829
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+ 2022-05-11 10:07:59,587 INFO [decode.py:382] batch 74/?, cuts processed until now is 3885
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+ 2022-05-11 10:09:23,115 INFO [decode.py:382] batch 76/?, cuts processed until now is 3934
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+ 2022-05-11 10:10:42,779 INFO [decode.py:382] batch 78/?, cuts processed until now is 3985
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+ 2022-05-11 10:11:22,305 INFO [decode.py:397] The transcripts are stored in pruned_transducer_stateless2/exp/v2/beam_search/recogs-dev-beam_size_4-epoch-28-avg-15-beam-4.txt
50
+ 2022-05-11 10:11:22,418 INFO [utils.py:405] [dev-beam_size_4] %WER 2.27% [2207 / 97304, 458 ins, 441 del, 1308 sub ]
51
+ 2022-05-11 10:11:22,665 INFO [decode.py:410] Wrote detailed error stats to pruned_transducer_stateless2/exp/v2/beam_search/errs-dev-beam_size_4-epoch-28-avg-15-beam-4.txt
52
+ 2022-05-11 10:11:22,666 INFO [decode.py:426]
53
+ For dev, WER of different settings are:
54
+ beam_size_4 2.27 best for dev
55
+
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+ 2022-05-11 10:12:54,398 INFO [decode.py:382] batch 0/?, cuts processed until now is 45
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+ 2022-05-12 04:28:35,684 INFO [decode.py:397] The transcripts are stored in pruned_transducer_stateless2/exp/v2/beam_search/recogs-val-beam_size_4-epoch-28-avg-15-beam-4.txt
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+ 2022-05-12 04:28:36,954 INFO [utils.py:405] [val-beam_size_4] %WER 2.24% [21179 / 946469, 4365 ins, 4129 del, 12685 sub ]
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+ 2022-05-12 04:28:39,267 INFO [decode.py:410] Wrote detailed error stats to pruned_transducer_stateless2/exp/v2/beam_search/errs-val-beam_size_4-epoch-28-avg-15-beam-4.txt
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+ 2022-05-12 04:28:39,268 INFO [decode.py:426]
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+ For val, WER of different settings are:
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+ beam_size_4 2.24 best for val
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+
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+ 2022-05-12 04:28:39,268 INFO [decode.py:534] Done!
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+ 2022-05-10 21:01:44,677 INFO [decode.py:459] Decoding started
2
+ 2022-05-10 21:01:44,677 INFO [decode.py:465] Device: cuda:0
3
+ 2022-05-10 21:01:44,680 INFO [decode.py:474] {'best_train_loss': inf, 'best_valid_loss': inf, 'best_train_epoch': -1, 'best_valid_epoch': -1, 'batch_idx_train': 0, 'log_interval': 50, 'reset_interval': 200, 'valid_interval': 3000, 'feature_dim': 80, 'subsampling_factor': 4, 'encoder_dim': 512, 'nhead': 8, 'dim_feedforward': 2048, 'num_encoder_layers': 12, 'decoder_dim': 512, 'joiner_dim': 512, 'model_warm_step': 3000, 'env_info': {'k2-version': '1.14', 'k2-build-type': 'Debug', 'k2-with-cuda': True, 'k2-git-sha1': '1b29f0a946f50186aaa82df46a59f492ade9692b', 'k2-git-date': 'Tue Apr 12 20:46:49 2022', 'lhotse-version': '1.1.0', 'torch-version': '1.10.1+cu111', 'torch-cuda-available': True, 'torch-cuda-version': '11.1', 'python-version': '3.8', 'icefall-git-branch': 'spgi', 'icefall-git-sha1': '4e1205a-dirty', 'icefall-git-date': 'Tue May 10 20:51:30 2022', 'icefall-path': '/exp/draj/mini_scale_2022/icefall', 'k2-path': '/exp/draj/mini_scale_2022/k2/k2/python/k2/__init__.py', 'lhotse-path': '/exp/draj/mini_scale_2022/lhotse/lhotse/__init__.py', 'hostname': 'r7n03', 'IP address': '10.1.7.3'}, 'epoch': 28, 'avg': 15, 'avg_last_n': 10, 'exp_dir': PosixPath('pruned_transducer_stateless2/exp/v2'), 'bpe_model': 'data/lang_bpe_500/bpe.model', 'decoding_method': 'fast_beam_search', 'beam_size': 4, 'beam': 4.0, 'max_contexts': 4, 'max_states': 8, 'context_size': 2, 'max_sym_per_frame': 1, 'manifest_dir': PosixPath('data/manifests'), 'enable_musan': True, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'max_duration': 500, 'num_buckets': 30, 'on_the_fly_feats': False, 'shuffle': True, 'num_workers': 8, 'enable_spec_aug': True, 'spec_aug_time_warp_factor': 80, 'res_dir': PosixPath('pruned_transducer_stateless2/exp/v2/fast_beam_search'), 'suffix': 'epoch-28-avg-15-beam-4.0-max-contexts-4-max-states-8', 'blank_id': 0, 'vocab_size': 500}
4
+ 2022-05-10 21:01:44,680 INFO [decode.py:476] About to create model
5
+ 2022-05-10 21:01:45,018 INFO [decode.py:481] averaging ['pruned_transducer_stateless2/exp/v2/checkpoint-696000.pt', 'pruned_transducer_stateless2/exp/v2/checkpoint-688000.pt', 'pruned_transducer_stateless2/exp/v2/checkpoint-680000.pt', 'pruned_transducer_stateless2/exp/v2/checkpoint-672000.pt', 'pruned_transducer_stateless2/exp/v2/checkpoint-664000.pt', 'pruned_transducer_stateless2/exp/v2/checkpoint-656000.pt', 'pruned_transducer_stateless2/exp/v2/checkpoint-648000.pt', 'pruned_transducer_stateless2/exp/v2/checkpoint-640000.pt', 'pruned_transducer_stateless2/exp/v2/checkpoint-632000.pt', 'pruned_transducer_stateless2/exp/v2/checkpoint-624000.pt']
6
+ 2022-05-10 21:01:56,791 INFO [decode.py:506] Number of model parameters: 78648040
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+ 2022-05-10 21:01:56,791 INFO [asr_datamodule.py:326] About to get SPGISpeech dev cuts
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+ 2022-05-10 21:01:56,793 INFO [asr_datamodule.py:331] About to get SPGISpeech val cuts
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+ 2022-05-10 21:02:00,648 INFO [decode.py:382] batch 0/?, cuts processed until now is 45
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+ 2022-05-10 21:04:46,259 INFO [decode.py:397] The transcripts are stored in pruned_transducer_stateless2/exp/v2/fast_beam_search/recogs-dev-beam_4.0_max_contexts_4_max_states_8-epoch-28-avg-15-beam-4.0-max-contexts-4-max-states-8.txt
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+ 2022-05-10 21:04:46,382 INFO [utils.py:405] [dev-beam_4.0_max_contexts_4_max_states_8] %WER 2.38% [2313 / 97304, 425 ins, 560 del, 1328 sub ]
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+ 2022-05-10 21:04:46,625 INFO [decode.py:410] Wrote detailed error stats to pruned_transducer_stateless2/exp/v2/fast_beam_search/errs-dev-beam_4.0_max_contexts_4_max_states_8-epoch-28-avg-15-beam-4.0-max-contexts-4-max-states-8.txt
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+ 2022-05-10 21:04:46,626 INFO [decode.py:426]
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+ For dev, WER of different settings are:
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+ beam_4.0_max_contexts_4_max_states_8 2.38 best for dev
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+
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+ 2022-05-10 21:30:45,777 INFO [decode.py:397] The transcripts are stored in pruned_transducer_stateless2/exp/v2/fast_beam_search/recogs-val-beam_4.0_max_contexts_4_max_states_8-epoch-28-avg-15-beam-4.0-max-contexts-4-max-states-8.txt
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+ 2022-05-10 21:30:47,050 INFO [utils.py:405] [val-beam_4.0_max_contexts_4_max_states_8] %WER 2.35% [22214 / 946469, 3948 ins, 5314 del, 12952 sub ]
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+ 2022-05-10 21:30:49,406 INFO [decode.py:410] Wrote detailed error stats to pruned_transducer_stateless2/exp/v2/fast_beam_search/errs-val-beam_4.0_max_contexts_4_max_states_8-epoch-28-avg-15-beam-4.0-max-contexts-4-max-states-8.txt
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+ 2022-05-10 21:30:49,407 INFO [decode.py:426]
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+ For val, WER of different settings are:
427
+ beam_4.0_max_contexts_4_max_states_8 2.35 best for val
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+
429
+ 2022-05-10 21:30:49,407 INFO [decode.py:534] Done!
log/fast_beam_search/recogs-dev-beam_4.0_max_contexts_4_max_states_8-epoch-28-avg-15-beam-4.0-max-contexts-4-max-states-8.txt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
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3
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4
+ 2022-05-11 08:06:04,600 INFO [decode.py:476] About to create model
5
+ 2022-05-11 08:06:04,921 INFO [decode.py:481] averaging ['pruned_transducer_stateless2/exp/v2/checkpoint-696000.pt', 'pruned_transducer_stateless2/exp/v2/checkpoint-688000.pt', 'pruned_transducer_stateless2/exp/v2/checkpoint-680000.pt', 'pruned_transducer_stateless2/exp/v2/checkpoint-672000.pt', 'pruned_transducer_stateless2/exp/v2/checkpoint-664000.pt', 'pruned_transducer_stateless2/exp/v2/checkpoint-656000.pt', 'pruned_transducer_stateless2/exp/v2/checkpoint-648000.pt', 'pruned_transducer_stateless2/exp/v2/checkpoint-640000.pt', 'pruned_transducer_stateless2/exp/v2/checkpoint-632000.pt', 'pruned_transducer_stateless2/exp/v2/checkpoint-624000.pt']
6
+ 2022-05-11 08:06:16,567 INFO [decode.py:506] Number of model parameters: 78648040
7
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9
+ 2022-05-11 08:06:18,639 INFO [decode.py:382] batch 0/?, cuts processed until now is 45
10
+ 2022-05-11 08:07:04,413 INFO [decode.py:397] The transcripts are stored in pruned_transducer_stateless2/exp/v2/greedy_search/recogs-dev-greedy_search-epoch-28-avg-15-context-2-max-sym-per-frame-1.txt
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+ 2022-05-11 08:07:04,801 INFO [decode.py:410] Wrote detailed error stats to pruned_transducer_stateless2/exp/v2/greedy_search/errs-dev-greedy_search-epoch-28-avg-15-context-2-max-sym-per-frame-1.txt
13
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+ For dev, WER of different settings are:
15
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16
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17
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22
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25
+ 2022-05-11 08:14:19,738 INFO [decode.py:397] The transcripts are stored in pruned_transducer_stateless2/exp/v2/greedy_search/recogs-val-greedy_search-epoch-28-avg-15-context-2-max-sym-per-frame-1.txt
26
+ 2022-05-11 08:14:20,872 INFO [utils.py:405] [val-greedy_search] %WER 2.40% [22731 / 946469, 3844 ins, 5524 del, 13363 sub ]
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+ 2022-05-11 08:14:23,249 INFO [decode.py:410] Wrote detailed error stats to pruned_transducer_stateless2/exp/v2/greedy_search/errs-val-greedy_search-epoch-28-avg-15-context-2-max-sym-per-frame-1.txt
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31
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+ 2022-05-12 21:03:04,889 INFO [decode.py:459] Decoding started
2
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3
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4
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5
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6
+ 2022-05-12 21:04:52,899 INFO [decode.py:506] Number of model parameters: 78648040
7
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8
+ 2022-05-12 21:04:52,936 INFO [asr_datamodule.py:331] About to get SPGISpeech val cuts
9
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10
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+ 2022-05-12 21:06:20,455 INFO [decode.py:382] batch 18/?, cuts processed until now is 958
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+ 2022-05-12 21:06:38,459 INFO [decode.py:382] batch 22/?, cuts processed until now is 1145
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+ 2022-05-12 21:06:56,260 INFO [decode.py:382] batch 26/?, cuts processed until now is 1379
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+ 2022-05-12 21:07:23,224 INFO [decode.py:382] batch 32/?, cuts processed until now is 1664
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+ 2022-05-12 21:07:32,200 INFO [decode.py:382] batch 34/?, cuts processed until now is 1758
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+ 2022-05-12 21:08:16,808 INFO [decode.py:382] batch 44/?, cuts processed until now is 2348
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+ 2022-05-12 21:08:34,191 INFO [decode.py:382] batch 48/?, cuts processed until now is 2542
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+ 2022-05-12 21:08:42,918 INFO [decode.py:382] batch 50/?, cuts processed until now is 2672
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37
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38
+ 2022-05-12 21:09:18,544 INFO [decode.py:382] batch 58/?, cuts processed until now is 3143
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+ 2022-05-12 21:09:27,411 INFO [decode.py:382] batch 60/?, cuts processed until now is 3235
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+ 2022-05-12 21:09:36,142 INFO [decode.py:382] batch 62/?, cuts processed until now is 3376
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+ 2022-05-12 21:09:54,038 INFO [decode.py:382] batch 66/?, cuts processed until now is 3576
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45
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48
+ 2022-05-12 21:10:27,212 INFO [decode.py:382] batch 78/?, cuts processed until now is 3985
49
+ 2022-05-12 21:10:29,668 INFO [decode.py:397] The transcripts are stored in pruned_transducer_stateless2/exp/v2/modified_beam_search/recogs-dev-beam_size_4-epoch-28-avg-15-beam-4.txt
50
+ 2022-05-12 21:10:29,787 INFO [utils.py:405] [dev-beam_size_4] %WER 2.34% [2273 / 97304, 507 ins, 452 del, 1314 sub ]
51
+ 2022-05-12 21:10:30,042 INFO [decode.py:410] Wrote detailed error stats to pruned_transducer_stateless2/exp/v2/modified_beam_search/errs-dev-beam_size_4-epoch-28-avg-15-beam-4.txt
52
+ 2022-05-12 21:10:30,043 INFO [decode.py:426]
53
+ For dev, WER of different settings are:
54
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55
+
56
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57
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58
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59
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60
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64
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65
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+ 2022-05-12 22:04:58,456 INFO [decode.py:397] The transcripts are stored in pruned_transducer_stateless2/exp/v2/modified_beam_search/recogs-val-beam_size_4-epoch-28-avg-15-beam-4.txt
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+ 2022-05-12 22:04:59,671 INFO [utils.py:405] [val-beam_size_4] %WER 2.30% [21738 / 946469, 4782 ins, 4151 del, 12805 sub ]
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+ 2022-05-12 22:05:01,921 INFO [decode.py:410] Wrote detailed error stats to pruned_transducer_stateless2/exp/v2/modified_beam_search/errs-val-beam_size_4-epoch-28-avg-15-beam-4.txt
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+ 2022-05-12 22:05:01,925 INFO [decode.py:426]
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+ For val, WER of different settings are:
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+ beam_size_4 2.3 best for val
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+
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+ 2022-05-12 22:05:01,925 INFO [decode.py:534] Done!
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