log/fast_beam_search/log-decode-epoch-15-avg-8-beam-4-max-contexts-4-max-states-8-2022-12-09-00-04-39

2022-12-09 00:04:39,800 INFO [decode.py:551] Decoding started
2022-12-09 00:04:39,801 INFO [decode.py:557] Device: cuda:0
2022-12-09 00:04:39,862 INFO [lexicon.py:168] Loading pre-compiled data/lang_char/Linv.pt
2022-12-09 00:04:39,872 INFO [decode.py:563] {'best_train_loss': inf, 'best_valid_loss': inf, 'best_train_epoch': -1, 'best_valid_epoch': -1, 'batch_idx_train': 0, 'log_interval': 100, 'reset_interval': 200, 'valid_interval': 3000, 'feature_dim': 80, 'subsampling_factor': 4, 'warm_step': 2000, 'env_info': {'k2-version': '1.23', 'k2-build-type': 'Release', 'k2-with-cuda': True, 'k2-git-sha1': 'b2ce63f3940018e7b433c43fd802fc50ab006a76', 'k2-git-date': 'Wed Nov 23 08:43:43 2022', 'lhotse-version': '1.9.0.dev+git.97bf4b0.dirty', 'torch-version': '1.10.0+cu102', 'torch-cuda-available': True, 'torch-cuda-version': '10.2', 'python-version': '3.8', 'icefall-git-branch': 'ali_meeting', 'icefall-git-sha1': 'f13cf61-dirty', 'icefall-git-date': 'Tue Dec 6 03:34:27 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': 'r7n08', 'IP address': '10.1.7.8'}, 'epoch': 15, 'iter': 0, 'avg': 8, 'use_averaged_model': True, 'exp_dir': PosixPath('pruned_transducer_stateless7/exp/v1'), 'lang_dir': 'data/lang_char', 'decoding_method': 'fast_beam_search', 'beam_size': 4, 'beam': 4, 'ngram_lm_scale': 0.01, 'max_contexts': 4, 'max_states': 8, 'context_size': 2, 'max_sym_per_frame': 1, 'num_paths': 200, 'nbest_scale': 0.5, 'num_encoder_layers': '2,4,3,2,4', 'feedforward_dims': '1024,1024,2048,2048,1024', 'nhead': '8,8,8,8,8', 'encoder_dims': '384,384,384,384,384', 'attention_dims': '192,192,192,192,192', 'encoder_unmasked_dims': '256,256,256,256,256', 'zipformer_downsampling_factors': '1,2,4,8,2', 'cnn_module_kernels': '31,31,31,31,31', 'decoder_dim': 512, 'joiner_dim': 512, 'manifest_dir': PosixPath('data/manifests'), 'enable_musan': True, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'max_duration': 500, 'max_cuts': None, 'num_buckets': 50, '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_stateless7/exp/v1/fast_beam_search'), 'suffix': 'epoch-15-avg-8-beam-4-max-contexts-4-max-states-8', 'blank_id': 0, 'vocab_size': 3290}
2022-12-09 00:04:39,872 INFO [decode.py:565] About to create model
2022-12-09 00:04:40,318 INFO [zipformer.py:179] At encoder stack 4, which has downsampling_factor=2, we will combine the outputs of layers 1 and 3, with downsampling_factors=2 and 8.
2022-12-09 00:04:40,367 INFO [decode.py:632] Calculating the averaged model over epoch range from 7 (excluded) to 15
2022-12-09 00:04:56,153 INFO [decode.py:655] Number of model parameters: 75734561
2022-12-09 00:04:56,153 INFO [asr_datamodule.py:381] About to get AliMeeting IHM eval cuts
2022-12-09 00:04:56,156 INFO [asr_datamodule.py:402] About to get AliMeeting IHM test cuts
2022-12-09 00:04:56,158 INFO [asr_datamodule.py:387] About to get AliMeeting SDM eval cuts
2022-12-09 00:04:56,159 INFO [asr_datamodule.py:408] About to get AliMeeting SDM test cuts
2022-12-09 00:04:56,161 INFO [asr_datamodule.py:396] About to get AliMeeting GSS-enhanced eval cuts
2022-12-09 00:04:56,163 INFO [asr_datamodule.py:417] About to get AliMeeting GSS-enhanced test cuts
2022-12-09 00:04:57,914 INFO [decode.py:687] Decoding eval_ihm
2022-12-09 00:05:00,542 INFO [decode.py:463] batch 0/?, cuts processed until now is 58
2022-12-09 00:05:02,549 INFO [zipformer.py:1414] attn_weights_entropy = tensor([3.0737, 1.5896, 3.0429, 1.9527, 3.1868, 3.0717, 2.1364, 3.2050],
       device='cuda:0'), covar=tensor([0.0130, 0.1163, 0.0235, 0.0949, 0.0167, 0.0218, 0.0828, 0.0144],
       device='cuda:0'), in_proj_covar=tensor([0.0160, 0.0151, 0.0146, 0.0161, 0.0155, 0.0161, 0.0120, 0.0130],
       device='cuda:0'), out_proj_covar=tensor([0.0003, 0.0004, 0.0003, 0.0004, 0.0004, 0.0004, 0.0003, 0.0003],
       device='cuda:0')
2022-12-09 00:05:03,160 INFO [decode.py:463] batch 2/?, cuts processed until now is 512
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2022-12-09 00:05:44,872 INFO [decode.py:463] batch 42/?, cuts processed until now is 6171
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2022-12-09 00:05:48,661 INFO [decode.py:463] batch 46/?, cuts processed until now is 6456
2022-12-09 00:05:49,043 INFO [decode.py:479] The transcripts are stored in pruned_transducer_stateless7/exp/v1/fast_beam_search/recogs-eval_ihm-beam_4_max_contexts_4_max_states_8-epoch-15-avg-8-beam-4-max-contexts-4-max-states-8.txt
2022-12-09 00:05:49,145 INFO [utils.py:536] [eval_ihm-beam_4_max_contexts_4_max_states_8] %WER 9.92% [8049 / 81111, 835 ins, 2146 del, 5068 sub ]
2022-12-09 00:05:49,383 INFO [decode.py:492] Wrote detailed error stats to pruned_transducer_stateless7/exp/v1/fast_beam_search/errs-eval_ihm-beam_4_max_contexts_4_max_states_8-epoch-15-avg-8-beam-4-max-contexts-4-max-states-8.txt
2022-12-09 00:05:49,386 INFO [decode.py:508] 
For eval_ihm, WER of different settings are:
beam_4_max_contexts_4_max_states_8	9.92	best for eval_ihm

2022-12-09 00:05:49,386 INFO [decode.py:687] Decoding test_ihm
2022-12-09 00:05:52,047 INFO [decode.py:463] batch 0/?, cuts processed until now is 49
2022-12-09 00:05:54,386 INFO [decode.py:463] batch 2/?, cuts processed until now is 433
2022-12-09 00:05:57,029 INFO [decode.py:463] batch 4/?, cuts processed until now is 545
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2022-12-09 00:06:26,248 INFO [zipformer.py:1414] attn_weights_entropy = tensor([1.7884, 1.7374, 1.7931, 1.6476, 1.5451, 1.3756, 1.2392, 0.9835],
       device='cuda:0'), covar=tensor([0.0257, 0.0477, 0.0302, 0.0285, 0.0391, 0.0372, 0.0391, 0.0706],
       device='cuda:0'), in_proj_covar=tensor([0.0013, 0.0014, 0.0012, 0.0013, 0.0013, 0.0022, 0.0018, 0.0023],
       device='cuda:0'), out_proj_covar=tensor([1.0210e-04, 1.1124e-04, 9.6061e-05, 1.0387e-04, 1.0128e-04, 1.6022e-04,
        1.3170e-04, 1.5378e-04], device='cuda:0')
2022-12-09 00:06:26,881 INFO [decode.py:463] batch 28/?, cuts processed until now is 2546
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2022-12-09 00:06:59,037 INFO [decode.py:463] batch 54/?, cuts processed until now is 5219
2022-12-09 00:06:59,308 INFO [zipformer.py:1414] attn_weights_entropy = tensor([3.0441, 2.9961, 2.5706, 3.2930, 3.2433, 3.2067, 2.9979, 2.6837],
       device='cuda:0'), covar=tensor([0.0658, 0.0330, 0.1699, 0.0248, 0.0410, 0.0486, 0.0532, 0.0554],
       device='cuda:0'), in_proj_covar=tensor([0.0237, 0.0272, 0.0252, 0.0220, 0.0279, 0.0268, 0.0232, 0.0237],
       device='cuda:0'), out_proj_covar=tensor([0.0003, 0.0004, 0.0004, 0.0003, 0.0004, 0.0003, 0.0003, 0.0003],
       device='cuda:0')
2022-12-09 00:07:00,786 INFO [decode.py:463] batch 56/?, cuts processed until now is 5892
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2022-12-09 00:08:05,950 INFO [decode.py:479] The transcripts are stored in pruned_transducer_stateless7/exp/v1/fast_beam_search/recogs-test_ihm-beam_4_max_contexts_4_max_states_8-epoch-15-avg-8-beam-4-max-contexts-4-max-states-8.txt
2022-12-09 00:08:06,244 INFO [utils.py:536] [test_ihm-beam_4_max_contexts_4_max_states_8] %WER 12.07% [25334 / 209845, 2035 ins, 7940 del, 15359 sub ]
2022-12-09 00:08:06,874 INFO [decode.py:492] Wrote detailed error stats to pruned_transducer_stateless7/exp/v1/fast_beam_search/errs-test_ihm-beam_4_max_contexts_4_max_states_8-epoch-15-avg-8-beam-4-max-contexts-4-max-states-8.txt
2022-12-09 00:08:06,875 INFO [decode.py:508] 
For test_ihm, WER of different settings are:
beam_4_max_contexts_4_max_states_8	12.07	best for test_ihm

2022-12-09 00:08:06,876 INFO [decode.py:687] Decoding eval_sdm
2022-12-09 00:08:09,951 INFO [decode.py:463] batch 0/?, cuts processed until now is 58
2022-12-09 00:08:12,839 INFO [decode.py:463] batch 2/?, cuts processed until now is 512
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2022-12-09 00:09:01,542 INFO [decode.py:463] batch 46/?, cuts processed until now is 6456
2022-12-09 00:09:01,956 INFO [decode.py:479] The transcripts are stored in pruned_transducer_stateless7/exp/v1/fast_beam_search/recogs-eval_sdm-beam_4_max_contexts_4_max_states_8-epoch-15-avg-8-beam-4-max-contexts-4-max-states-8.txt
2022-12-09 00:09:02,058 INFO [utils.py:536] [eval_sdm-beam_4_max_contexts_4_max_states_8] %WER 23.60% [19139 / 81111, 1582 ins, 6591 del, 10966 sub ]
2022-12-09 00:09:02,314 INFO [decode.py:492] Wrote detailed error stats to pruned_transducer_stateless7/exp/v1/fast_beam_search/errs-eval_sdm-beam_4_max_contexts_4_max_states_8-epoch-15-avg-8-beam-4-max-contexts-4-max-states-8.txt
2022-12-09 00:09:02,315 INFO [decode.py:508] 
For eval_sdm, WER of different settings are:
beam_4_max_contexts_4_max_states_8	23.6	best for eval_sdm

2022-12-09 00:09:02,315 INFO [decode.py:687] Decoding test_sdm
2022-12-09 00:09:05,263 INFO [decode.py:463] batch 0/?, cuts processed until now is 49
2022-12-09 00:09:08,151 INFO [decode.py:463] batch 2/?, cuts processed until now is 433
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2022-12-09 00:09:54,241 INFO [zipformer.py:1414] attn_weights_entropy = tensor([2.7396, 3.1001, 3.0621, 3.0092, 2.4846, 3.1160, 2.9203, 1.5742],
       device='cuda:0'), covar=tensor([0.3222, 0.1240, 0.1216, 0.1279, 0.1173, 0.0968, 0.1290, 0.3379],
       device='cuda:0'), in_proj_covar=tensor([0.0138, 0.0066, 0.0052, 0.0054, 0.0082, 0.0064, 0.0085, 0.0091],
       device='cuda:0'), out_proj_covar=tensor([0.0007, 0.0004, 0.0004, 0.0004, 0.0005, 0.0004, 0.0005, 0.0005],
       device='cuda:0')
2022-12-09 00:09:56,816 INFO [decode.py:463] batch 34/?, cuts processed until now is 2875
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2022-12-09 00:11:23,831 INFO [decode.py:463] batch 110/?, cuts processed until now is 15787
2022-12-09 00:11:24,660 INFO [zipformer.py:1414] attn_weights_entropy = tensor([4.0644, 3.4893, 2.6910, 4.0270, 4.0221, 3.9192, 3.2926, 2.7434],
       device='cuda:0'), covar=tensor([0.0469, 0.1215, 0.3648, 0.0498, 0.0629, 0.1124, 0.1476, 0.4299],
       device='cuda:0'), in_proj_covar=tensor([0.0237, 0.0272, 0.0252, 0.0220, 0.0279, 0.0268, 0.0232, 0.0237],
       device='cuda:0'), out_proj_covar=tensor([0.0003, 0.0004, 0.0004, 0.0003, 0.0004, 0.0003, 0.0003, 0.0003],
       device='cuda:0')
2022-12-09 00:11:24,993 INFO [decode.py:463] batch 112/?, cuts processed until now is 15881
2022-12-09 00:11:27,253 INFO [decode.py:463] batch 114/?, cuts processed until now is 15926
2022-12-09 00:11:28,278 INFO [decode.py:463] batch 116/?, cuts processed until now is 16287
2022-12-09 00:11:30,637 INFO [decode.py:463] batch 118/?, cuts processed until now is 16357
2022-12-09 00:11:30,938 INFO [decode.py:479] The transcripts are stored in pruned_transducer_stateless7/exp/v1/fast_beam_search/recogs-test_sdm-beam_4_max_contexts_4_max_states_8-epoch-15-avg-8-beam-4-max-contexts-4-max-states-8.txt
2022-12-09 00:11:31,232 INFO [utils.py:536] [test_sdm-beam_4_max_contexts_4_max_states_8] %WER 26.38% [55365 / 209845, 4187 ins, 20994 del, 30184 sub ]
2022-12-09 00:11:31,895 INFO [decode.py:492] Wrote detailed error stats to pruned_transducer_stateless7/exp/v1/fast_beam_search/errs-test_sdm-beam_4_max_contexts_4_max_states_8-epoch-15-avg-8-beam-4-max-contexts-4-max-states-8.txt
2022-12-09 00:11:31,896 INFO [decode.py:508] 
For test_sdm, WER of different settings are:
beam_4_max_contexts_4_max_states_8	26.38	best for test_sdm

2022-12-09 00:11:31,896 INFO [decode.py:687] Decoding eval_gss
2022-12-09 00:11:34,643 INFO [decode.py:463] batch 0/?, cuts processed until now is 58
2022-12-09 00:11:37,265 INFO [decode.py:463] batch 2/?, cuts processed until now is 512
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2022-12-09 00:11:42,519 INFO [decode.py:463] batch 6/?, cuts processed until now is 750
2022-12-09 00:11:45,087 INFO [decode.py:463] batch 8/?, cuts processed until now is 883
2022-12-09 00:11:45,431 INFO [zipformer.py:1414] attn_weights_entropy = tensor([4.4707, 2.5249, 4.5708, 2.7089, 4.2849, 2.1961, 3.3505, 4.2979],
       device='cuda:0'), covar=tensor([0.0574, 0.4876, 0.0310, 1.1301, 0.0766, 0.4357, 0.1456, 0.0313],
       device='cuda:0'), in_proj_covar=tensor([0.0221, 0.0205, 0.0174, 0.0283, 0.0196, 0.0207, 0.0197, 0.0178],
       device='cuda:0'), out_proj_covar=tensor([0.0004, 0.0004, 0.0003, 0.0005, 0.0004, 0.0004, 0.0004, 0.0004],
       device='cuda:0')
2022-12-09 00:11:48,123 INFO [decode.py:463] batch 10/?, cuts processed until now is 1082
2022-12-09 00:11:48,459 INFO [zipformer.py:1414] attn_weights_entropy = tensor([5.2040, 2.9190, 5.3102, 3.1520, 4.9151, 2.4271, 3.8951, 4.8336],
       device='cuda:0'), covar=tensor([0.0427, 0.4875, 0.0264, 1.0490, 0.0479, 0.4513, 0.1411, 0.0262],
       device='cuda:0'), in_proj_covar=tensor([0.0221, 0.0205, 0.0174, 0.0283, 0.0196, 0.0207, 0.0197, 0.0178],
       device='cuda:0'), out_proj_covar=tensor([0.0004, 0.0004, 0.0003, 0.0005, 0.0004, 0.0004, 0.0004, 0.0004],
       device='cuda:0')
2022-12-09 00:11:50,504 INFO [decode.py:463] batch 12/?, cuts processed until now is 1279
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2022-12-09 00:12:25,982 INFO [decode.py:463] batch 46/?, cuts processed until now is 6456
2022-12-09 00:12:26,413 INFO [decode.py:479] The transcripts are stored in pruned_transducer_stateless7/exp/v1/fast_beam_search/recogs-eval_gss-beam_4_max_contexts_4_max_states_8-epoch-15-avg-8-beam-4-max-contexts-4-max-states-8.txt
2022-12-09 00:12:26,516 INFO [utils.py:536] [eval_gss-beam_4_max_contexts_4_max_states_8] %WER 12.30% [9980 / 81111, 904 ins, 2805 del, 6271 sub ]
2022-12-09 00:12:26,761 INFO [decode.py:492] Wrote detailed error stats to pruned_transducer_stateless7/exp/v1/fast_beam_search/errs-eval_gss-beam_4_max_contexts_4_max_states_8-epoch-15-avg-8-beam-4-max-contexts-4-max-states-8.txt
2022-12-09 00:12:26,762 INFO [decode.py:508] 
For eval_gss, WER of different settings are:
beam_4_max_contexts_4_max_states_8	12.3	best for eval_gss

2022-12-09 00:12:26,763 INFO [decode.py:687] Decoding test_gss
2022-12-09 00:12:29,434 INFO [decode.py:463] batch 0/?, cuts processed until now is 49
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2022-12-09 00:14:45,434 INFO [decode.py:463] batch 112/?, cuts processed until now is 15881
2022-12-09 00:14:47,672 INFO [decode.py:463] batch 114/?, cuts processed until now is 15926
2022-12-09 00:14:48,671 INFO [decode.py:463] batch 116/?, cuts processed until now is 16287
2022-12-09 00:14:50,930 INFO [decode.py:463] batch 118/?, cuts processed until now is 16357
2022-12-09 00:14:51,229 INFO [decode.py:479] The transcripts are stored in pruned_transducer_stateless7/exp/v1/fast_beam_search/recogs-test_gss-beam_4_max_contexts_4_max_states_8-epoch-15-avg-8-beam-4-max-contexts-4-max-states-8.txt
2022-12-09 00:14:51,493 INFO [utils.py:536] [test_gss-beam_4_max_contexts_4_max_states_8] %WER 14.98% [31430 / 209845, 2279 ins, 10211 del, 18940 sub ]
2022-12-09 00:14:52,136 INFO [decode.py:492] Wrote detailed error stats to pruned_transducer_stateless7/exp/v1/fast_beam_search/errs-test_gss-beam_4_max_contexts_4_max_states_8-epoch-15-avg-8-beam-4-max-contexts-4-max-states-8.txt
2022-12-09 00:14:52,138 INFO [decode.py:508] 
For test_gss, WER of different settings are:
beam_4_max_contexts_4_max_states_8	14.98	best for test_gss

2022-12-09 00:14:52,138 INFO [decode.py:703] Done!