icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13 / decoding-results /modified_beam_search /log-decode-iter-1224000-avg-14-modified_beam_search-beam-size-4-2022-05-13-11-51-15
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add modified beam search results.
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2022-05-13 11:51:15,903 INFO [decode.py:531] Decoding started
2022-05-13 11:51:15,904 INFO [decode.py:537] Device: cuda:0
2022-05-13 11:51:15,906 INFO [decode.py:547] {'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': '1.15.1', 'k2-build-type': 'Release', 'k2-with-cuda': True, 'k2-git-sha1': 'f8d2dba06c000ffee36aab5b66f24e7c9809f116', 'k2-git-date': 'Thu Apr 21 12:20:34 2022', 'lhotse-version': '1.1.0.dev+missing.version.file', 'torch-version': '1.10.0+cu102', 'torch-cuda-available': True, 'torch-cuda-version': '10.2', 'python-version': '3.8', 'icefall-git-branch': 'modified-conformer-with-multi-datasets', 'icefall-git-sha1': '00fd664-dirty', 'icefall-git-date': 'Fri Apr 29 15:28:42 2022', 'icefall-path': '/ceph-fj/fangjun/open-source-2/icefall-multi-4', 'k2-path': '/ceph-fj/fangjun/open-source-2/k2-multi-22/k2/python/k2/__init__.py', 'lhotse-path': '/ceph-fj/fangjun/open-source-2/lhotse-multi-3/lhotse/__init__.py', 'hostname': 'de-74279-k2-train-2-0307200233-b554c565c-lf9qd', 'IP address': '10.177.74.201'}, 'epoch': 28, 'iter': 1224000, 'avg': 14, 'exp_dir': PosixPath('pruned_transducer_stateless3/exp-0.9'), 'bpe_model': 'data/lang_bpe_500/bpe.model', 'decoding_method': 'modified_beam_search', 'beam_size': 4, 'beam': 4.0, 'max_contexts': 32, 'max_states': 8, 'context_size': 2, 'max_sym_per_frame': 1, 'num_paths': 100, 'nbest_scale': 0.5, 'max_duration': 600, 'bucketing_sampler': True, 'num_buckets': 30, 'shuffle': True, 'return_cuts': True, 'num_workers': 2, 'on_the_fly_num_workers': 0, 'enable_spec_aug': True, 'spec_aug_time_warp_factor': 80, 'enable_musan': True, 'manifest_dir': PosixPath('data/fbank'), 'on_the_fly_feats': False, 'res_dir': PosixPath('pruned_transducer_stateless3/exp-0.9/modified_beam_search'), 'suffix': 'iter-1224000-avg-14-modified_beam_search-beam-size-4', 'blank_id': 0, 'unk_id': 2, 'vocab_size': 500}
2022-05-13 11:51:15,907 INFO [decode.py:549] About to create model
2022-05-13 11:51:16,527 INFO [decode.py:566] averaging ['pruned_transducer_stateless3/exp-0.9/checkpoint-1224000.pt', 'pruned_transducer_stateless3/exp-0.9/checkpoint-1216000.pt', 'pruned_transducer_stateless3/exp-0.9/checkpoint-1208000.pt', 'pruned_transducer_stateless3/exp-0.9/checkpoint-1200000.pt', 'pruned_transducer_stateless3/exp-0.9/checkpoint-1192000.pt', 'pruned_transducer_stateless3/exp-0.9/checkpoint-1184000.pt', 'pruned_transducer_stateless3/exp-0.9/checkpoint-1176000.pt', 'pruned_transducer_stateless3/exp-0.9/checkpoint-1168000.pt', 'pruned_transducer_stateless3/exp-0.9/checkpoint-1160000.pt', 'pruned_transducer_stateless3/exp-0.9/checkpoint-1152000.pt', 'pruned_transducer_stateless3/exp-0.9/checkpoint-1144000.pt', 'pruned_transducer_stateless3/exp-0.9/checkpoint-1136000.pt', 'pruned_transducer_stateless3/exp-0.9/checkpoint-1128000.pt', 'pruned_transducer_stateless3/exp-0.9/checkpoint-1120000.pt']
2022-05-13 11:53:04,387 INFO [decode.py:595] Number of model parameters: 80199888
2022-05-13 11:53:04,388 INFO [librispeech.py:58] About to get test-clean cuts from data/fbank/cuts_test-clean.json.gz
2022-05-13 11:53:04,507 INFO [librispeech.py:63] About to get test-other cuts from data/fbank/cuts_test-other.json.gz
2022-05-13 11:53:37,741 INFO [decode.py:438] batch 0/?, cuts processed until now is 123
2022-05-13 11:58:10,766 INFO [decode.py:438] batch 10/?, cuts processed until now is 945
2022-05-13 12:01:44,946 INFO [decode.py:438] batch 20/?, cuts processed until now is 1558
2022-05-13 12:04:34,252 INFO [decode.py:438] batch 30/?, cuts processed until now is 2383
2022-05-13 12:07:23,218 INFO [decode.py:455] The transcripts are stored in pruned_transducer_stateless3/exp-0.9/modified_beam_search/recogs-test-clean-beam_size_4-iter-1224000-avg-14-modified_beam_search-beam-size-4.txt
2022-05-13 12:07:23,293 INFO [utils.py:405] [test-clean-beam_size_4] %WER 2.00% [1049 / 52576, 111 ins, 85 del, 853 sub ]
2022-05-13 12:07:23,471 INFO [decode.py:468] Wrote detailed error stats to pruned_transducer_stateless3/exp-0.9/modified_beam_search/errs-test-clean-beam_size_4-iter-1224000-avg-14-modified_beam_search-beam-size-4.txt
2022-05-13 12:07:23,472 INFO [decode.py:485]
For test-clean, WER of different settings are:
beam_size_4 2.0 best for test-clean
2022-05-13 12:07:37,469 INFO [decode.py:438] batch 0/?, cuts processed until now is 138
2022-05-13 12:10:52,601 INFO [decode.py:438] batch 10/?, cuts processed until now is 1070
2022-05-13 12:13:58,872 INFO [decode.py:438] batch 20/?, cuts processed until now is 1765
2022-05-13 12:19:26,416 INFO [decode.py:438] batch 30/?, cuts processed until now is 2653
2022-05-13 12:22:25,967 INFO [decode.py:455] The transcripts are stored in pruned_transducer_stateless3/exp-0.9/modified_beam_search/recogs-test-other-beam_size_4-iter-1224000-avg-14-modified_beam_search-beam-size-4.txt
2022-05-13 12:22:26,158 INFO [utils.py:405] [test-other-beam_size_4] %WER 4.63% [2422 / 52343, 247 ins, 197 del, 1978 sub ]
2022-05-13 12:22:26,334 INFO [decode.py:468] Wrote detailed error stats to pruned_transducer_stateless3/exp-0.9/modified_beam_search/errs-test-other-beam_size_4-iter-1224000-avg-14-modified_beam_search-beam-size-4.txt
2022-05-13 12:22:26,335 INFO [decode.py:485]
For test-other, WER of different settings are:
beam_size_4 4.63 best for test-other
2022-05-13 12:22:26,335 INFO [decode.py:624] Done!