ctc tdnn baseline model

exp_max_duration_100/best-train-loss.pt

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exp_max_duration_100/best-valid-loss.pt

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exp_max_duration_100/epoch-1.pt

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exp_max_duration_100/epoch-3.pt

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exp_max_duration_100/epoch-4.pt

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exp_max_duration_100/epoch-5.pt

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exp_max_duration_100/epoch-6.pt

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exp_max_duration_100/epoch-7.pt

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exp_max_duration_100/epoch-8.pt

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exp_max_duration_100/log/log-train-2023-03-16-15-23-31

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+2023-03-16 15:23:31,867 INFO [train.py:513] Training started
+2023-03-16 15:23:31,867 INFO [train.py:514] {'best_train_loss': inf, 'best_valid_loss': inf, 'best_train_epoch': -1, 'best_valid_epoch': -1, 'batch_idx_train': 0, 'log_interval': 5, 'reset_interval': 200, 'valid_interval': 3000, 'feature_dim': 80, 'number_class': 9, 'wakeup_word': '你好米雅', 'wakeup_word_tokens': [2, 3, 4, 5, 6, 3, 7, 8], 'weight_decay': 1e-06, 'env_info': {'k2-version': '1.23.2', 'k2-build-type': 'Debug', 'k2-with-cuda': True, 'k2-git-sha1': 'a34171ed85605b0926eebbd0463d059431f4f74a', 'k2-git-date': 'Wed Dec 14 00:06:38 2022', 'lhotse-version': '1.13.0.dev+git.e7b4daf.clean', 'torch-version': '1.10.0+cu102', 'torch-cuda-available': True, 'torch-cuda-version': '10.2', 'python-version': '3.8', 'icefall-git-branch': 'himia', 'icefall-git-sha1': 'd5471c5-dirty', 'icefall-git-date': 'Thu Mar 16 14:59:16 2023', 'icefall-path': '/ceph-data3/ly/workspace/bf_ctc/himia_icefall', 'k2-path': '/star-ly/ceph_storages/ceph-data3/self_alignment_mp/k2/k2/python/k2/__init__.py', 'lhotse-path': '/ceph-data3/ly/workspace/bf_ctc/lhotse/lhotse/__init__.py', 'hostname': 'de-74279-k2-train-7-1218101249-5d97868c7c-v8ngc', 'IP address': '10.177.77.18'}, 'world_size': 1, 'master_port': 12354, 'tensorboard': True, 'num_epochs': 20, 'start_epoch': 1, 'exp_dir': PosixPath('ctc_tdnn/exp_max_duration_100'), 'lr_factor': 0.001, 'seed': 42, 'manifest_dir': PosixPath('data/fbank'), 'max_duration': 100, 'bucketing_sampler': False, 'num_buckets': 30, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'on_the_fly_feats': False, 'shuffle': True, 'drop_last': True, 'return_cuts': True, 'num_workers': 2, 'enable_spec_aug': True, 'spec_aug_time_warp_factor': 80, 'enable_musan': True, 'input_strategy': 'PrecomputedFeatures', 'train_channel': '_7_01', 'dev_channel': '_7_01'}
+2023-03-16 15:23:31,871 INFO [train.py:530] About to create model
+2023-03-16 15:23:45,241 INFO [asr_datamodule.py:401] About to get train cuts
+2023-03-16 15:23:45,264 INFO [asr_datamodule.py:226] Enable MUSAN
+2023-03-16 15:23:45,264 INFO [asr_datamodule.py:227] About to get Musan cuts
+2023-03-16 15:23:47,200 INFO [asr_datamodule.py:251] Enable SpecAugment
+2023-03-16 15:23:47,200 INFO [asr_datamodule.py:252] Time warp factor: 80
+2023-03-16 15:23:47,200 INFO [asr_datamodule.py:262] Num frame mask: 10
+2023-03-16 15:23:47,200 INFO [asr_datamodule.py:275] About to create train dataset
+2023-03-16 15:23:47,201 INFO [asr_datamodule.py:311] Using SingleCutSampler.
+2023-03-16 15:23:47,201 INFO [asr_datamodule.py:317] About to create train dataloader
+2023-03-16 15:23:47,204 INFO [asr_datamodule.py:421] About to get dev cuts
+2023-03-16 15:23:47,206 INFO [asr_datamodule.py:348] About to create dev dataset
+2023-03-16 15:23:47,372 INFO [asr_datamodule.py:365] About to create dev dataloader
+2023-03-16 15:23:47,372 INFO [train.py:616] Sanity check -- see if any of the batches in epoch 0 would cause OOM.

exp_max_duration_100/log/log-train-2023-03-16-15-24-30

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+2023-03-16 15:24:30,734 INFO [train.py:513] Training started
+2023-03-16 15:24:30,734 INFO [train.py:514] {'best_train_loss': inf, 'best_valid_loss': inf, 'best_train_epoch': -1, 'best_valid_epoch': -1, 'batch_idx_train': 0, 'log_interval': 5, 'reset_interval': 200, 'valid_interval': 3000, 'feature_dim': 80, 'number_class': 9, 'wakeup_word': '你好米雅', 'wakeup_word_tokens': [2, 3, 4, 5, 6, 3, 7, 8], 'weight_decay': 1e-06, 'env_info': {'k2-version': '1.23.2', 'k2-build-type': 'Debug', 'k2-with-cuda': True, 'k2-git-sha1': 'a34171ed85605b0926eebbd0463d059431f4f74a', 'k2-git-date': 'Wed Dec 14 00:06:38 2022', 'lhotse-version': '1.13.0.dev+git.e7b4daf.clean', 'torch-version': '1.10.0+cu102', 'torch-cuda-available': True, 'torch-cuda-version': '10.2', 'python-version': '3.8', 'icefall-git-branch': 'himia', 'icefall-git-sha1': 'd5471c5-dirty', 'icefall-git-date': 'Thu Mar 16 14:59:16 2023', 'icefall-path': '/ceph-data3/ly/workspace/bf_ctc/himia_icefall', 'k2-path': '/star-ly/ceph_storages/ceph-data3/self_alignment_mp/k2/k2/python/k2/__init__.py', 'lhotse-path': '/ceph-data3/ly/workspace/bf_ctc/lhotse/lhotse/__init__.py', 'hostname': 'de-74279-k2-train-7-1218101249-5d97868c7c-v8ngc', 'IP address': '10.177.77.18'}, 'world_size': 1, 'master_port': 12354, 'tensorboard': True, 'num_epochs': 20, 'start_epoch': 1, 'exp_dir': PosixPath('ctc_tdnn/exp_max_duration_100'), 'lr_factor': 0.001, 'seed': 42, 'manifest_dir': PosixPath('data/fbank'), 'max_duration': 100, 'bucketing_sampler': False, 'num_buckets': 30, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'on_the_fly_feats': False, 'shuffle': True, 'drop_last': True, 'return_cuts': True, 'num_workers': 2, 'enable_spec_aug': True, 'spec_aug_time_warp_factor': 80, 'enable_musan': True, 'input_strategy': 'PrecomputedFeatures', 'train_channel': '_7_01', 'dev_channel': '_7_01'}
+2023-03-16 15:24:30,737 INFO [train.py:530] About to create model
+2023-03-16 15:24:40,283 INFO [asr_datamodule.py:401] About to get train cuts
+2023-03-16 15:24:40,327 INFO [asr_datamodule.py:226] Enable MUSAN
+2023-03-16 15:24:40,327 INFO [asr_datamodule.py:227] About to get Musan cuts
+2023-03-16 15:24:42,288 INFO [asr_datamodule.py:251] Enable SpecAugment
+2023-03-16 15:24:42,288 INFO [asr_datamodule.py:252] Time warp factor: 80
+2023-03-16 15:24:42,288 INFO [asr_datamodule.py:262] Num frame mask: 10
+2023-03-16 15:24:42,288 INFO [asr_datamodule.py:275] About to create train dataset
+2023-03-16 15:24:42,288 INFO [asr_datamodule.py:311] Using SingleCutSampler.
+2023-03-16 15:24:42,289 INFO [asr_datamodule.py:317] About to create train dataloader
+2023-03-16 15:24:42,300 INFO [asr_datamodule.py:421] About to get dev cuts
+2023-03-16 15:24:42,301 INFO [asr_datamodule.py:348] About to create dev dataset
+2023-03-16 15:24:42,463 INFO [asr_datamodule.py:365] About to create dev dataloader
+2023-03-16 15:24:42,463 INFO [train.py:616] Sanity check -- see if any of the batches in epoch 0 would cause OOM.
+2023-03-16 15:24:55,329 INFO [train.py:578] epoch 1, learning rate 0.001
+2023-03-16 15:24:56,544 INFO [train.py:456] Epoch 1, batch 0, loss[loss=0.6068, number_positive_cuts_ratio=0.1, over 4781.00 frames. utt_duration=478.1 frames, utt_pad_proportion=0.2928, over 10.00 utterances.], tot_loss[loss=0.6068, number_positive_cuts_ratio=0.1, over 4781.00 frames. utt_duration=478.1 frames, utt_pad_proportion=0.2928, over 10.00 utterances.], batch size: 10
+2023-03-16 15:24:56,799 INFO [train.py:456] Epoch 1, batch 5, loss[loss=0.3454, number_positive_cuts_ratio=0.2143, over 5783.00 frames. utt_duration=413.1 frames, utt_pad_proportion=0.4207, over 14.00 utterances.], tot_loss[loss=0.4133, number_positive_cuts_ratio=0.1158, over 32935.47 frames. utt_duration=456.5 frames, utt_pad_proportion=0.3905, over 72.16 utterances.], batch size: 14
+2023-03-16 15:24:57,082 INFO [train.py:456] Epoch 1, batch 10, loss[loss=0.6306, number_positive_cuts_ratio=0.3333, over 5982.00 frames. utt_duration=332.3 frames, utt_pad_proportion=0.4001, over 18.00 utterances.], tot_loss[loss=0.4103, number_positive_cuts_ratio=0.1287, over 59108.64 frames. utt_duration=423.1 frames, utt_pad_proportion=0.3996, over 139.71 utterances.], batch size: 18
+2023-03-16 15:24:57,460 INFO [train.py:456] Epoch 1, batch 15, loss[loss=0.424, number_positive_cuts_ratio=0.1538, over 6028.00 frames. utt_duration=463.7 frames, utt_pad_proportion=0.3017, over 13.00 utterances.], tot_loss[loss=0.4219, number_positive_cuts_ratio=0.1578, over 84843.98 frames. utt_duration=410.8 frames, utt_pad_proportion=0.4068, over 206.53 utterances.], batch size: 13
+2023-03-16 15:24:57,683 INFO [train.py:456] Epoch 1, batch 20, loss[loss=0.334, number_positive_cuts_ratio=0.25, over 4824.00 frames. utt_duration=402 frames, utt_pad_proportion=0.4892, over 12.00 utterances.], tot_loss[loss=0.413, number_positive_cuts_ratio=0.1685, over 107258.69 frames. utt_duration=408.1 frames, utt_pad_proportion=0.4209, over 262.82 utterances.], batch size: 12
+2023-03-16 15:24:57,939 INFO [train.py:456] Epoch 1, batch 25, loss[loss=0.3867, number_positive_cuts_ratio=0.1875, over 5913.00 frames. utt_duration=369.6 frames, utt_pad_proportion=0.3562, over 16.00 utterances.], tot_loss[loss=0.4007, number_positive_cuts_ratio=0.1713, over 130434.15 frames. utt_duration=401.8 frames, utt_pad_proportion=0.4222, over 324.66 utterances.], batch size: 16
+2023-03-16 15:24:58,195 INFO [train.py:456] Epoch 1, batch 30, loss[loss=0.2279, number_positive_cuts_ratio=0.1429, over 5433.00 frames. utt_duration=388.1 frames, utt_pad_proportion=0.4225, over 14.00 utterances.], tot_loss[loss=0.3838, number_positive_cuts_ratio=0.172, over 155612.66 frames. utt_duration=400.1 frames, utt_pad_proportion=0.4175, over 388.92 utterances.], batch size: 14
+2023-03-16 15:24:58,416 INFO [train.py:456] Epoch 1, batch 35, loss[loss=0.3012, number_positive_cuts_ratio=0.2143, over 5468.00 frames. utt_duration=390.6 frames, utt_pad_proportion=0.4499, over 14.00 utterances.], tot_loss[loss=0.3614, number_positive_cuts_ratio=0.1667, over 179388.46 frames. utt_duration=400.8 frames, utt_pad_proportion=0.4171, over 447.60 utterances.], batch size: 14
+2023-03-16 15:24:58,640 INFO [train.py:456] Epoch 1, batch 40, loss[loss=0.3446, number_positive_cuts_ratio=0.2667, over 5315.00 frames. utt_duration=354.3 frames, utt_pad_proportion=0.4489, over 15.00 utterances.], tot_loss[loss=0.3544, number_positive_cuts_ratio=0.1627, over 203603.30 frames. utt_duration=403.3 frames, utt_pad_proportion=0.4146, over 504.84 utterances.], batch size: 15
+2023-03-16 15:24:58,895 INFO [train.py:456] Epoch 1, batch 45, loss[loss=0.1757, number_positive_cuts_ratio=0, over 6586.00 frames. utt_duration=439.1 frames, utt_pad_proportion=0.302, over 15.00 utterances.], tot_loss[loss=0.3411, number_positive_cuts_ratio=0.1545, over 227782.78 frames. utt_duration=402 frames, utt_pad_proportion=0.4099, over 566.61 utterances.], batch size: 15
+2023-03-16 15:24:59,173 INFO [train.py:456] Epoch 1, batch 50, loss[loss=0.1886, number_positive_cuts_ratio=0.07143, over 6272.00 frames. utt_duration=448 frames, utt_pad_proportion=0.3591, over 14.00 utterances.], tot_loss[loss=0.3285, number_positive_cuts_ratio=0.1545, over 249600.21 frames. utt_duration=402 frames, utt_pad_proportion=0.4105, over 620.92 utterances.], batch size: 14
+2023-03-16 15:24:59,439 INFO [train.py:456] Epoch 1, batch 55, loss[loss=0.3458, number_positive_cuts_ratio=0.1538, over 5197.00 frames. utt_duration=399.8 frames, utt_pad_proportion=0.4455, over 13.00 utterances.], tot_loss[loss=0.3197, number_positive_cuts_ratio=0.152, over 270258.48 frames. utt_duration=403.4 frames, utt_pad_proportion=0.4113, over 669.87 utterances.], batch size: 13
+2023-03-16 15:24:59,742 INFO [train.py:456] Epoch 1, batch 60, loss[loss=0.1577, number_positive_cuts_ratio=0.07143, over 5941.00 frames. utt_duration=424.4 frames, utt_pad_proportion=0.359, over 14.00 utterances.], tot_loss[loss=0.3146, number_positive_cuts_ratio=0.1503, over 291900.20 frames. utt_duration=403.4 frames, utt_pad_proportion=0.4097, over 723.56 utterances.], batch size: 14
+2023-03-16 15:24:59,972 INFO [train.py:456] Epoch 1, batch 65, loss[loss=0.3604, number_positive_cuts_ratio=0.3333, over 4916.00 frames. utt_duration=327.7 frames, utt_pad_proportion=0.4189, over 15.00 utterances.], tot_loss[loss=0.3031, number_positive_cuts_ratio=0.1496, over 312088.63 frames. utt_duration=404.3 frames, utt_pad_proportion=0.4094, over 771.98 utterances.], batch size: 15
+2023-03-16 15:25:00,191 INFO [train.py:456] Epoch 1, batch 70, loss[loss=0.0723, number_positive_cuts_ratio=0.1818, over 5711.00 frames. utt_duration=519.2 frames, utt_pad_proportion=0.3856, over 11.00 utterances.], tot_loss[loss=0.2904, number_positive_cuts_ratio=0.1446, over 333421.51 frames. utt_duration=408.5 frames, utt_pad_proportion=0.4064, over 816.22 utterances.], batch size: 11
+2023-03-16 15:25:00,409 INFO [train.py:456] Epoch 1, batch 75, loss[loss=0.151, number_positive_cuts_ratio=0.08333, over 5726.00 frames. utt_duration=477.2 frames, utt_pad_proportion=0.4102, over 12.00 utterances.], tot_loss[loss=0.2819, number_positive_cuts_ratio=0.138, over 353464.76 frames. utt_duration=410.8 frames, utt_pad_proportion=0.4053, over 860.37 utterances.], batch size: 12
+2023-03-16 15:25:00,680 INFO [train.py:456] Epoch 1, batch 80, loss[loss=0.2195, number_positive_cuts_ratio=0.2, over 5772.00 frames. utt_duration=384.8 frames, utt_pad_proportion=0.4025, over 15.00 utterances.], tot_loss[loss=0.2791, number_positive_cuts_ratio=0.1381, over 373773.98 frames. utt_duration=410.6 frames, utt_pad_proportion=0.4043, over 910.33 utterances.], batch size: 15
+2023-03-16 15:25:00,909 INFO [train.py:456] Epoch 1, batch 85, loss[loss=0.3132, number_positive_cuts_ratio=0.3, over 4328.00 frames. utt_duration=432.8 frames, utt_pad_proportion=0.5326, over 10.00 utterances.], tot_loss[loss=0.2745, number_positive_cuts_ratio=0.1383, over 391305.81 frames. utt_duration=411.9 frames, utt_pad_proportion=0.4043, over 950.11 utterances.], batch size: 10
+2023-03-16 15:25:01,164 INFO [train.py:456] Epoch 1, batch 90, loss[loss=0.1886, number_positive_cuts_ratio=0.2308, over 4815.00 frames. utt_duration=370.4 frames, utt_pad_proportion=0.3997, over 13.00 utterances.], tot_loss[loss=0.2743, number_positive_cuts_ratio=0.1412, over 406833.81 frames. utt_duration=409.3 frames, utt_pad_proportion=0.4055, over 993.87 utterances.], batch size: 13
+2023-03-16 15:25:01,442 INFO [train.py:456] Epoch 1, batch 95, loss[loss=0.127, number_positive_cuts_ratio=0.06667, over 6253.00 frames. utt_duration=416.9 frames, utt_pad_proportion=0.3703, over 15.00 utterances.], tot_loss[loss=0.2712, number_positive_cuts_ratio=0.1412, over 424916.86 frames. utt_duration=409.5 frames, utt_pad_proportion=0.4063, over 1037.58 utterances.], batch size: 15
+2023-03-16 15:25:01,668 INFO [train.py:456] Epoch 1, batch 100, loss[loss=0.144, number_positive_cuts_ratio=0.07692, over 5856.00 frames. utt_duration=450.5 frames, utt_pad_proportion=0.4026, over 13.00 utterances.], tot_loss[loss=0.2698, number_positive_cuts_ratio=0.142, over 441044.49 frames. utt_duration=409.4 frames, utt_pad_proportion=0.4078, over 1077.26 utterances.], batch size: 13
+2023-03-16 15:25:01,913 INFO [train.py:456] Epoch 1, batch 105, loss[loss=0.1409, number_positive_cuts_ratio=0.0625, over 6303.00 frames. utt_duration=393.9 frames, utt_pad_proportion=0.3605, over 16.00 utterances.], tot_loss[loss=0.2606, number_positive_cuts_ratio=0.1373, over 459684.56 frames. utt_duration=409.7 frames, utt_pad_proportion=0.4062, over 1121.92 utterances.], batch size: 16
+2023-03-16 15:25:02,118 INFO [train.py:456] Epoch 1, batch 110, loss[loss=0.2042, number_positive_cuts_ratio=0.1429, over 5818.00 frames. utt_duration=415.6 frames, utt_pad_proportion=0.4089, over 14.00 utterances.], tot_loss[loss=0.2574, number_positive_cuts_ratio=0.1354, over 475976.49 frames. utt_duration=410.8 frames, utt_pad_proportion=0.4061, over 1158.56 utterances.], batch size: 14
+2023-03-16 15:25:02,429 INFO [train.py:456] Epoch 1, batch 115, loss[loss=0.04598, number_positive_cuts_ratio=0.09091, over 4751.00 frames. utt_duration=431.9 frames, utt_pad_proportion=0.4895, over 11.00 utterances.], tot_loss[loss=0.2536, number_positive_cuts_ratio=0.1354, over 490507.28 frames. utt_duration=411.1 frames, utt_pad_proportion=0.408, over 1193.25 utterances.], batch size: 11
+2023-03-16 15:25:02,682 INFO [train.py:456] Epoch 1, batch 120, loss[loss=0.4016, number_positive_cuts_ratio=0.25, over 5290.00 frames. utt_duration=330.6 frames, utt_pad_proportion=0.3945, over 16.00 utterances.], tot_loss[loss=0.2512, number_positive_cuts_ratio=0.1358, over 506682.93 frames. utt_duration=409.3 frames, utt_pad_proportion=0.4073, over 1237.94 utterances.], batch size: 16
+2023-03-16 15:25:02,854 INFO [train.py:456] Epoch 1, batch 125, loss[loss=0.1582, number_positive_cuts_ratio=0.2143, over 5367.00 frames. utt_duration=383.4 frames, utt_pad_proportion=0.4601, over 14.00 utterances.], tot_loss[loss=0.2478, number_positive_cuts_ratio=0.1362, over 519570.58 frames. utt_duration=409.9 frames, utt_pad_proportion=0.4089, over 1267.71 utterances.], batch size: 14
+2023-03-16 15:25:03,083 INFO [train.py:456] Epoch 1, batch 130, loss[loss=0.367, number_positive_cuts_ratio=0.2308, over 4955.00 frames. utt_duration=381.2 frames, utt_pad_proportion=0.2928, over 13.00 utterances.], tot_loss[loss=0.2504, number_positive_cuts_ratio=0.1376, over 534020.81 frames. utt_duration=410.3 frames, utt_pad_proportion=0.4077, over 1301.68 utterances.], batch size: 13
+2023-03-16 15:25:03,316 INFO [train.py:456] Epoch 1, batch 135, loss[loss=0.5325, number_positive_cuts_ratio=0.3571, over 4178.00 frames. utt_duration=298.4 frames, utt_pad_proportion=0.5803, over 14.00 utterances.], tot_loss[loss=0.2534, number_positive_cuts_ratio=0.1416, over 545173.57 frames. utt_duration=409.3 frames, utt_pad_proportion=0.4099, over 1331.88 utterances.], batch size: 14
+2023-03-16 15:25:03,579 INFO [train.py:456] Epoch 1, batch 140, loss[loss=0.2075, number_positive_cuts_ratio=0.06667, over 6036.00 frames. utt_duration=402.4 frames, utt_pad_proportion=0.3133, over 15.00 utterances.], tot_loss[loss=0.2549, number_positive_cuts_ratio=0.1424, over 558288.13 frames. utt_duration=408.3 frames, utt_pad_proportion=0.4109, over 1367.24 utterances.], batch size: 15
+2023-03-16 15:25:03,866 INFO [train.py:456] Epoch 1, batch 145, loss[loss=0.2778, number_positive_cuts_ratio=0.2308, over 5245.00 frames. utt_duration=403.5 frames, utt_pad_proportion=0.474, over 13.00 utterances.], tot_loss[loss=0.2558, number_positive_cuts_ratio=0.1436, over 570725.35 frames. utt_duration=408.3 frames, utt_pad_proportion=0.412, over 1397.77 utterances.], batch size: 13
+2023-03-16 15:25:04,163 INFO [train.py:456] Epoch 1, batch 150, loss[loss=0.2165, number_positive_cuts_ratio=0.08333, over 5670.00 frames. utt_duration=472.5 frames, utt_pad_proportion=0.3864, over 12.00 utterances.], tot_loss[loss=0.2583, number_positive_cuts_ratio=0.1444, over 583041.89 frames. utt_duration=408.7 frames, utt_pad_proportion=0.4127, over 1426.54 utterances.], batch size: 12
+2023-03-16 15:25:04,389 INFO [train.py:456] Epoch 1, batch 155, loss[loss=0.1111, number_positive_cuts_ratio=0.05882, over 6515.00 frames. utt_duration=383.2 frames, utt_pad_proportion=0.3107, over 17.00 utterances.], tot_loss[loss=0.255, number_positive_cuts_ratio=0.1429, over 596522.51 frames. utt_duration=408.4 frames, utt_pad_proportion=0.4116, over 1460.59 utterances.], batch size: 17
+2023-03-16 15:25:04,703 INFO [train.py:456] Epoch 1, batch 160, loss[loss=0.114, number_positive_cuts_ratio=0.07692, over 6075.00 frames. utt_duration=467.3 frames, utt_pad_proportion=0.3899, over 13.00 utterances.], tot_loss[loss=0.2541, number_positive_cuts_ratio=0.1447, over 608593.69 frames. utt_duration=407.7 frames, utt_pad_proportion=0.4125, over 1492.75 utterances.], batch size: 13
+2023-03-16 15:25:04,914 INFO [train.py:456] Epoch 1, batch 165, loss[loss=0.1577, number_positive_cuts_ratio=0.06667, over 6049.00 frames. utt_duration=403.3 frames, utt_pad_proportion=0.3589, over 15.00 utterances.], tot_loss[loss=0.2537, number_positive_cuts_ratio=0.1452, over 624107.89 frames. utt_duration=407.9 frames, utt_pad_proportion=0.4098, over 1530.07 utterances.], batch size: 15
+2023-03-16 15:25:05,170 INFO [train.py:456] Epoch 1, batch 170, loss[loss=0.2002, number_positive_cuts_ratio=0.1333, over 6479.00 frames. utt_duration=431.9 frames, utt_pad_proportion=0.3122, over 15.00 utterances.], tot_loss[loss=0.2487, number_positive_cuts_ratio=0.1426, over 637068.41 frames. utt_duration=408.2 frames, utt_pad_proportion=0.4091, over 1560.55 utterances.], batch size: 15
+2023-03-16 15:25:05,402 INFO [train.py:456] Epoch 1, batch 175, loss[loss=0.1414, number_positive_cuts_ratio=0.08333, over 6196.00 frames. utt_duration=516.3 frames, utt_pad_proportion=0.3346, over 12.00 utterances.], tot_loss[loss=0.2486, number_positive_cuts_ratio=0.143, over 650255.57 frames. utt_duration=407.6 frames, utt_pad_proportion=0.4077, over 1595.16 utterances.], batch size: 12
+2023-03-16 15:25:05,657 INFO [train.py:456] Epoch 1, batch 180, loss[loss=0.1116, number_positive_cuts_ratio=0.1, over 4316.00 frames. utt_duration=431.6 frames, utt_pad_proportion=0.5319, over 10.00 utterances.], tot_loss[loss=0.2451, number_positive_cuts_ratio=0.1429, over 662869.33 frames. utt_duration=407.9 frames, utt_pad_proportion=0.4069, over 1624.92 utterances.], batch size: 10
+2023-03-16 15:25:05,860 INFO [train.py:456] Epoch 1, batch 185, loss[loss=0.1811, number_positive_cuts_ratio=0.1333, over 5922.00 frames. utt_duration=394.8 frames, utt_pad_proportion=0.3917, over 15.00 utterances.], tot_loss[loss=0.2434, number_positive_cuts_ratio=0.1416, over 676162.35 frames. utt_duration=408.6 frames, utt_pad_proportion=0.4052, over 1655.00 utterances.], batch size: 15
+2023-03-16 15:25:06,121 INFO [train.py:456] Epoch 1, batch 190, loss[loss=0.2998, number_positive_cuts_ratio=0.1667, over 4313.00 frames. utt_duration=359.4 frames, utt_pad_proportion=0.5374, over 12.00 utterances.], tot_loss[loss=0.2418, number_positive_cuts_ratio=0.1408, over 687280.69 frames. utt_duration=407.8 frames, utt_pad_proportion=0.4056, over 1685.32 utterances.], batch size: 12
+2023-03-16 15:25:06,339 INFO [train.py:456] Epoch 1, batch 195, loss[loss=0.1856, number_positive_cuts_ratio=0.1818, over 4514.00 frames. utt_duration=410.4 frames, utt_pad_proportion=0.5115, over 11.00 utterances.], tot_loss[loss=0.2432, number_positive_cuts_ratio=0.1432, over 694303.73 frames. utt_duration=406.8 frames, utt_pad_proportion=0.4071, over 1706.91 utterances.], batch size: 11
+2023-03-16 15:25:06,584 INFO [train.py:456] Epoch 1, batch 200, loss[loss=0.3767, number_positive_cuts_ratio=0.2667, over 5998.00 frames. utt_duration=399.9 frames, utt_pad_proportion=0.3941, over 15.00 utterances.], tot_loss[loss=0.2447, number_positive_cuts_ratio=0.1462, over 704417.45 frames. utt_duration=406.9 frames, utt_pad_proportion=0.4075, over 1731.00 utterances.], batch size: 15
+2023-03-16 15:25:06,846 INFO [train.py:456] Epoch 1, batch 205, loss[loss=0.3597, number_positive_cuts_ratio=0.3333, over 5733.00 frames. utt_duration=318.5 frames, utt_pad_proportion=0.4134, over 18.00 utterances.], tot_loss[loss=0.2432, number_positive_cuts_ratio=0.1456, over 716028.11 frames. utt_duration=405.4 frames, utt_pad_proportion=0.4061, over 1766.35 utterances.], batch size: 18
+2023-03-16 15:25:07,055 INFO [train.py:456] Epoch 1, batch 210, loss[loss=0.08984, number_positive_cuts_ratio=0.1818, over 5037.00 frames. utt_duration=457.9 frames, utt_pad_proportion=0.4536, over 11.00 utterances.], tot_loss[loss=0.2405, number_positive_cuts_ratio=0.1452, over 725940.71 frames. utt_duration=405.6 frames, utt_pad_proportion=0.4062, over 1789.92 utterances.], batch size: 11
+2023-03-16 15:25:07,280 INFO [train.py:456] Epoch 1, batch 215, loss[loss=0.09093, number_positive_cuts_ratio=0.09091, over 5203.00 frames. utt_duration=473 frames, utt_pad_proportion=0.4625, over 11.00 utterances.], tot_loss[loss=0.2417, number_positive_cuts_ratio=0.1467, over 732096.80 frames. utt_duration=405.8 frames, utt_pad_proportion=0.4079, over 1803.98 utterances.], batch size: 11
+2023-03-16 15:25:07,525 INFO [train.py:456] Epoch 1, batch 220, loss[loss=0.4267, number_positive_cuts_ratio=0.4167, over 4163.00 frames. utt_duration=346.9 frames, utt_pad_proportion=0.5495, over 12.00 utterances.], tot_loss[loss=0.242, number_positive_cuts_ratio=0.1487, over 740457.48 frames. utt_duration=404.1 frames, utt_pad_proportion=0.409, over 1832.56 utterances.], batch size: 12
+2023-03-16 15:25:07,812 INFO [train.py:456] Epoch 1, batch 225, loss[loss=0.304, number_positive_cuts_ratio=0.2308, over 4984.00 frames. utt_duration=383.4 frames, utt_pad_proportion=0.4915, over 13.00 utterances.], tot_loss[loss=0.242, number_positive_cuts_ratio=0.1511, over 747208.30 frames. utt_duration=403.1 frames, utt_pad_proportion=0.4114, over 1853.52 utterances.], batch size: 13
+2023-03-16 15:25:08,027 INFO [train.py:456] Epoch 1, batch 230, loss[loss=0.08339, number_positive_cuts_ratio=0.09091, over 4628.00 frames. utt_duration=420.7 frames, utt_pad_proportion=0.5009, over 11.00 utterances.], tot_loss[loss=0.2407, number_positive_cuts_ratio=0.1484, over 755988.24 frames. utt_duration=404.9 frames, utt_pad_proportion=0.4105, over 1867.02 utterances.], batch size: 11
+2023-03-16 15:25:08,263 INFO [train.py:456] Epoch 1, batch 235, loss[loss=0.06467, number_positive_cuts_ratio=0.09091, over 4903.00 frames. utt_duration=445.7 frames, utt_pad_proportion=0.5014, over 11.00 utterances.], tot_loss[loss=0.2389, number_positive_cuts_ratio=0.1476, over 762849.98 frames. utt_duration=405.3 frames, utt_pad_proportion=0.4113, over 1882.14 utterances.], batch size: 11
+2023-03-16 15:25:08,453 INFO [train.py:456] Epoch 1, batch 240, loss[loss=0.1056, number_positive_cuts_ratio=0.09091, over 4963.00 frames. utt_duration=451.2 frames, utt_pad_proportion=0.3185, over 11.00 utterances.], tot_loss[loss=0.2381, number_positive_cuts_ratio=0.1465, over 772555.79 frames. utt_duration=405.2 frames, utt_pad_proportion=0.4099, over 1906.78 utterances.], batch size: 11
+2023-03-16 15:25:08,694 INFO [train.py:456] Epoch 1, batch 245, loss[loss=0.1533, number_positive_cuts_ratio=0.07143, over 6001.00 frames. utt_duration=428.6 frames, utt_pad_proportion=0.3602, over 14.00 utterances.], tot_loss[loss=0.2351, number_positive_cuts_ratio=0.144, over 780984.49 frames. utt_duration=405.7 frames, utt_pad_proportion=0.4095, over 1924.93 utterances.], batch size: 14
+2023-03-16 15:25:08,954 INFO [train.py:456] Epoch 1, batch 250, loss[loss=0.2552, number_positive_cuts_ratio=0.1818, over 4753.00 frames. utt_duration=432.1 frames, utt_pad_proportion=0.5167, over 11.00 utterances.], tot_loss[loss=0.2349, number_positive_cuts_ratio=0.1433, over 789643.68 frames. utt_duration=406.3 frames, utt_pad_proportion=0.4094, over 1943.58 utterances.], batch size: 11
+2023-03-16 15:25:09,197 INFO [train.py:456] Epoch 1, batch 255, loss[loss=0.06657, number_positive_cuts_ratio=0, over 5400.00 frames. utt_duration=385.7 frames, utt_pad_proportion=0.4537, over 14.00 utterances.], tot_loss[loss=0.2331, number_positive_cuts_ratio=0.1421, over 796959.79 frames. utt_duration=405.8 frames, utt_pad_proportion=0.4104, over 1963.78 utterances.], batch size: 14
+2023-03-16 15:25:09,399 INFO [train.py:456] Epoch 1, batch 260, loss[loss=0.1613, number_positive_cuts_ratio=0.07143, over 5616.00 frames. utt_duration=401.1 frames, utt_pad_proportion=0.3848, over 14.00 utterances.], tot_loss[loss=0.231, number_positive_cuts_ratio=0.141, over 804588.80 frames. utt_duration=406.9 frames, utt_pad_proportion=0.4105, over 1977.57 utterances.], batch size: 14
+2023-03-16 15:25:09,663 INFO [train.py:456] Epoch 1, batch 265, loss[loss=0.2365, number_positive_cuts_ratio=0.1667, over 5032.00 frames. utt_duration=419.3 frames, utt_pad_proportion=0.4771, over 12.00 utterances.], tot_loss[loss=0.2303, number_positive_cuts_ratio=0.1406, over 812498.03 frames. utt_duration=407.5 frames, utt_pad_proportion=0.4101, over 1994.00 utterances.], batch size: 12
+2023-03-16 15:25:09,904 INFO [train.py:456] Epoch 1, batch 270, loss[loss=0.1715, number_positive_cuts_ratio=0, over 6431.00 frames. utt_duration=494.7 frames, utt_pad_proportion=0.3499, over 13.00 utterances.], tot_loss[loss=0.2304, number_positive_cuts_ratio=0.1408, over 818328.44 frames. utt_duration=407.1 frames, utt_pad_proportion=0.4108, over 2009.97 utterances.], batch size: 13
+2023-03-16 15:25:10,208 INFO [train.py:456] Epoch 1, batch 275, loss[loss=0.1708, number_positive_cuts_ratio=0.08333, over 5909.00 frames. utt_duration=492.4 frames, utt_pad_proportion=0.386, over 12.00 utterances.], tot_loss[loss=0.232, number_positive_cuts_ratio=0.1424, over 823585.46 frames. utt_duration=406.8 frames, utt_pad_proportion=0.4115, over 2024.59 utterances.], batch size: 12
+2023-03-16 15:25:10,412 INFO [train.py:456] Epoch 1, batch 280, loss[loss=0.2756, number_positive_cuts_ratio=0.2667, over 5403.00 frames. utt_duration=360.2 frames, utt_pad_proportion=0.4592, over 15.00 utterances.], tot_loss[loss=0.2304, number_positive_cuts_ratio=0.1438, over 828187.90 frames. utt_duration=406.4 frames, utt_pad_proportion=0.4137, over 2037.85 utterances.], batch size: 15
+2023-03-16 15:25:10,675 INFO [train.py:456] Epoch 1, batch 285, loss[loss=0.1791, number_positive_cuts_ratio=0.1667, over 4408.00 frames. utt_duration=367.3 frames, utt_pad_proportion=0.3948, over 12.00 utterances.], tot_loss[loss=0.2284, number_positive_cuts_ratio=0.1434, over 835063.92 frames. utt_duration=407.2 frames, utt_pad_proportion=0.4131, over 2050.79 utterances.], batch size: 12
+2023-03-16 15:25:10,876 INFO [train.py:456] Epoch 1, batch 290, loss[loss=0.4158, number_positive_cuts_ratio=0.2308, over 4762.00 frames. utt_duration=366.3 frames, utt_pad_proportion=0.5077, over 13.00 utterances.], tot_loss[loss=0.2284, number_positive_cuts_ratio=0.1438, over 839408.96 frames. utt_duration=406.8 frames, utt_pad_proportion=0.4147, over 2063.39 utterances.], batch size: 13
+2023-03-16 15:25:11,104 INFO [train.py:456] Epoch 1, batch 295, loss[loss=0.2952, number_positive_cuts_ratio=0.25, over 5763.00 frames. utt_duration=360.2 frames, utt_pad_proportion=0.4172, over 16.00 utterances.], tot_loss[loss=0.2274, number_positive_cuts_ratio=0.1438, over 844791.73 frames. utt_duration=406.4 frames, utt_pad_proportion=0.4153, over 2078.70 utterances.], batch size: 16
+2023-03-16 15:25:11,322 INFO [train.py:456] Epoch 1, batch 300, loss[loss=0.2302, number_positive_cuts_ratio=0.25, over 5085.00 frames. utt_duration=423.8 frames, utt_pad_proportion=0.4756, over 12.00 utterances.], tot_loss[loss=0.2258, number_positive_cuts_ratio=0.1435, over 852437.62 frames. utt_duration=406.8 frames, utt_pad_proportion=0.4148, over 2095.52 utterances.], batch size: 12
+2023-03-16 15:25:11,594 INFO [train.py:456] Epoch 1, batch 305, loss[loss=0.1598, number_positive_cuts_ratio=0.07143, over 5971.00 frames. utt_duration=426.5 frames, utt_pad_proportion=0.3765, over 14.00 utterances.], tot_loss[loss=0.2242, number_positive_cuts_ratio=0.142, over 858597.05 frames. utt_duration=406.7 frames, utt_pad_proportion=0.415, over 2110.98 utterances.], batch size: 14
+2023-03-16 15:25:11,806 INFO [train.py:456] Epoch 1, batch 310, loss[loss=0.2209, number_positive_cuts_ratio=0.125, over 6671.00 frames. utt_duration=416.9 frames, utt_pad_proportion=0.3086, over 16.00 utterances.], tot_loss[loss=0.2229, number_positive_cuts_ratio=0.1418, over 866769.92 frames. utt_duration=406.5 frames, utt_pad_proportion=0.4139, over 2132.04 utterances.], batch size: 16
+2023-03-16 15:25:12,079 INFO [train.py:456] Epoch 1, batch 315, loss[loss=0.3037, number_positive_cuts_ratio=0.2857, over 5244.00 frames. utt_duration=374.6 frames, utt_pad_proportion=0.4702, over 14.00 utterances.], tot_loss[loss=0.2214, number_positive_cuts_ratio=0.1412, over 874285.80 frames. utt_duration=407.3 frames, utt_pad_proportion=0.4135, over 2146.59 utterances.], batch size: 14
+2023-03-16 15:25:12,268 INFO [train.py:456] Epoch 1, batch 320, loss[loss=0.03584, number_positive_cuts_ratio=0.09091, over 5079.00 frames. utt_duration=461.7 frames, utt_pad_proportion=0.4858, over 11.00 utterances.], tot_loss[loss=0.2211, number_positive_cuts_ratio=0.1429, over 880375.01 frames. utt_duration=407.1 frames, utt_pad_proportion=0.4133, over 2162.69 utterances.], batch size: 11
+2023-03-16 15:25:12,494 INFO [train.py:456] Epoch 1, batch 325, loss[loss=0.1647, number_positive_cuts_ratio=0.07692, over 5898.00 frames. utt_duration=453.7 frames, utt_pad_proportion=0.3785, over 13.00 utterances.], tot_loss[loss=0.2236, number_positive_cuts_ratio=0.1457, over 884114.21 frames. utt_duration=406 frames, utt_pad_proportion=0.4141, over 2177.44 utterances.], batch size: 13
+2023-03-16 15:25:12,736 INFO [train.py:456] Epoch 1, batch 330, loss[loss=0.1392, number_positive_cuts_ratio=0.07692, over 5278.00 frames. utt_duration=406 frames, utt_pad_proportion=0.47, over 13.00 utterances.], tot_loss[loss=0.223, number_positive_cuts_ratio=0.1442, over 889133.04 frames. utt_duration=407.1 frames, utt_pad_proportion=0.4146, over 2183.91 utterances.], batch size: 13
+2023-03-16 15:25:12,959 INFO [train.py:456] Epoch 1, batch 335, loss[loss=0.08205, number_positive_cuts_ratio=0, over 5998.00 frames. utt_duration=499.8 frames, utt_pad_proportion=0.3713, over 12.00 utterances.], tot_loss[loss=0.2207, number_positive_cuts_ratio=0.1418, over 895010.39 frames. utt_duration=407.7 frames, utt_pad_proportion=0.4139, over 2195.17 utterances.], batch size: 12
+2023-03-16 15:25:13,215 INFO [train.py:456] Epoch 1, batch 340, loss[loss=0.2535, number_positive_cuts_ratio=0.1333, over 5865.00 frames. utt_duration=391 frames, utt_pad_proportion=0.3744, over 15.00 utterances.], tot_loss[loss=0.2204, number_positive_cuts_ratio=0.1409, over 901590.15 frames. utt_duration=407.9 frames, utt_pad_proportion=0.4127, over 2210.13 utterances.], batch size: 15
+2023-03-16 15:25:13,434 INFO [train.py:456] Epoch 1, batch 345, loss[loss=0.07813, number_positive_cuts_ratio=0.06667, over 6024.00 frames. utt_duration=401.6 frames, utt_pad_proportion=0.385, over 15.00 utterances.], tot_loss[loss=0.219, number_positive_cuts_ratio=0.1405, over 907185.94 frames. utt_duration=407.9 frames, utt_pad_proportion=0.4126, over 2223.79 utterances.], batch size: 15
+2023-03-16 15:25:13,718 INFO [train.py:456] Epoch 1, batch 350, loss[loss=0.1657, number_positive_cuts_ratio=0.1333, over 5890.00 frames. utt_duration=392.7 frames, utt_pad_proportion=0.3845, over 15.00 utterances.], tot_loss[loss=0.2174, number_positive_cuts_ratio=0.1398, over 914558.11 frames. utt_duration=406.8 frames, utt_pad_proportion=0.4112, over 2247.95 utterances.], batch size: 15
+2023-03-16 15:25:13,964 INFO [train.py:456] Epoch 1, batch 355, loss[loss=0.2678, number_positive_cuts_ratio=0.2308, over 4925.00 frames. utt_duration=378.8 frames, utt_pad_proportion=0.5028, over 13.00 utterances.], tot_loss[loss=0.217, number_positive_cuts_ratio=0.1406, over 918356.01 frames. utt_duration=407 frames, utt_pad_proportion=0.4117, over 2256.66 utterances.], batch size: 13
+2023-03-16 15:25:14,210 INFO [train.py:456] Epoch 1, batch 360, loss[loss=0.2097, number_positive_cuts_ratio=0.1176, over 6625.00 frames. utt_duration=389.7 frames, utt_pad_proportion=0.3246, over 17.00 utterances.], tot_loss[loss=0.2175, number_positive_cuts_ratio=0.1403, over 923070.61 frames. utt_duration=407.1 frames, utt_pad_proportion=0.4116, over 2267.19 utterances.], batch size: 17
+2023-03-16 15:25:14,394 INFO [train.py:456] Epoch 1, batch 365, loss[loss=0.2137, number_positive_cuts_ratio=0.1667, over 5510.00 frames. utt_duration=459.2 frames, utt_pad_proportion=0.4136, over 12.00 utterances.], tot_loss[loss=0.2185, number_positive_cuts_ratio=0.1427, over 925703.79 frames. utt_duration=406.8 frames, utt_pad_proportion=0.4121, over 2275.39 utterances.], batch size: 12
+2023-03-16 15:25:14,687 INFO [train.py:456] Epoch 1, batch 370, loss[loss=0.2348, number_positive_cuts_ratio=0.2143, over 5044.00 frames. utt_duration=360.3 frames, utt_pad_proportion=0.4353, over 14.00 utterances.], tot_loss[loss=0.2187, number_positive_cuts_ratio=0.1442, over 930332.84 frames. utt_duration=406.4 frames, utt_pad_proportion=0.4121, over 2289.38 utterances.], batch size: 14
+2023-03-16 15:25:14,939 INFO [train.py:456] Epoch 1, batch 375, loss[loss=0.04474, number_positive_cuts_ratio=0, over 5561.00 frames. utt_duration=505.5 frames, utt_pad_proportion=0.4169, over 11.00 utterances.], tot_loss[loss=0.2163, number_positive_cuts_ratio=0.1424, over 935945.68 frames. utt_duration=406.9 frames, utt_pad_proportion=0.4116, over 2300.00 utterances.], batch size: 11
+2023-03-16 15:25:15,244 INFO [train.py:456] Epoch 1, batch 380, loss[loss=0.08222, number_positive_cuts_ratio=0, over 6132.00 frames. utt_duration=438 frames, utt_pad_proportion=0.3414, over 14.00 utterances.], tot_loss[loss=0.2133, number_positive_cuts_ratio=0.1409, over 940166.11 frames. utt_duration=407.5 frames, utt_pad_proportion=0.4117, over 2307.42 utterances.], batch size: 14
+2023-03-16 15:25:15,450 INFO [train.py:456] Epoch 1, batch 385, loss[loss=0.3026, number_positive_cuts_ratio=0.2857, over 5762.00 frames. utt_duration=411.6 frames, utt_pad_proportion=0.4052, over 14.00 utterances.], tot_loss[loss=0.2116, number_positive_cuts_ratio=0.1405, over 945113.66 frames. utt_duration=408.1 frames, utt_pad_proportion=0.4115, over 2315.65 utterances.], batch size: 14
+2023-03-16 15:25:15,779 INFO [train.py:456] Epoch 1, batch 390, loss[loss=0.205, number_positive_cuts_ratio=0.125, over 6322.00 frames. utt_duration=395.1 frames, utt_pad_proportion=0.3359, over 16.00 utterances.], tot_loss[loss=0.2112, number_positive_cuts_ratio=0.1402, over 951390.20 frames. utt_duration=407.7 frames, utt_pad_proportion=0.4105, over 2333.58 utterances.], batch size: 16
+2023-03-16 15:25:15,987 INFO [train.py:456] Epoch 1, batch 395, loss[loss=0.2927, number_positive_cuts_ratio=0.25, over 5008.00 frames. utt_duration=417.3 frames, utt_pad_proportion=0.4744, over 12.00 utterances.], tot_loss[loss=0.2094, number_positive_cuts_ratio=0.1393, over 954532.77 frames. utt_duration=407.9 frames, utt_pad_proportion=0.4106, over 2340.15 utterances.], batch size: 12
+2023-03-16 15:25:16,224 INFO [train.py:456] Epoch 1, batch 400, loss[loss=0.2554, number_positive_cuts_ratio=0.1818, over 4357.00 frames. utt_duration=396.1 frames, utt_pad_proportion=0.3343, over 11.00 utterances.], tot_loss[loss=0.2078, number_positive_cuts_ratio=0.1391, over 956497.46 frames. utt_duration=408.5 frames, utt_pad_proportion=0.4108, over 2341.63 utterances.], batch size: 11
+2023-03-16 15:25:16,426 INFO [train.py:456] Epoch 1, batch 405, loss[loss=0.1173, number_positive_cuts_ratio=0.1667, over 5349.00 frames. utt_duration=445.8 frames, utt_pad_proportion=0.4504, over 12.00 utterances.], tot_loss[loss=0.2073, number_positive_cuts_ratio=0.1398, over 960065.03 frames. utt_duration=408.5 frames, utt_pad_proportion=0.411, over 2350.03 utterances.], batch size: 12
+2023-03-16 15:25:16,711 INFO [train.py:456] Epoch 1, batch 410, loss[loss=0.2311, number_positive_cuts_ratio=0.125, over 6211.00 frames. utt_duration=388.2 frames, utt_pad_proportion=0.3769, over 16.00 utterances.], tot_loss[loss=0.2096, number_positive_cuts_ratio=0.1413, over 963586.33 frames. utt_duration=408.1 frames, utt_pad_proportion=0.4113, over 2361.19 utterances.], batch size: 16
+2023-03-16 15:25:17,239 INFO [train.py:456] Epoch 1, batch 415, loss[loss=0.2793, number_positive_cuts_ratio=0.1538, over 4326.00 frames. utt_duration=332.8 frames, utt_pad_proportion=0.2828, over 13.00 utterances.], tot_loss[loss=0.2116, number_positive_cuts_ratio=0.1434, over 964504.21 frames. utt_duration=408.1 frames, utt_pad_proportion=0.4114, over 2363.18 utterances.], batch size: 13
+2023-03-16 15:25:17,506 INFO [train.py:456] Epoch 1, batch 420, loss[loss=0.2044, number_positive_cuts_ratio=0.25, over 4622.00 frames. utt_duration=385.2 frames, utt_pad_proportion=0.5081, over 12.00 utterances.], tot_loss[loss=0.2115, number_positive_cuts_ratio=0.1439, over 964502.17 frames. utt_duration=408.3 frames, utt_pad_proportion=0.413, over 2362.10 utterances.], batch size: 12
+2023-03-16 15:25:17,726 INFO [train.py:456] Epoch 1, batch 425, loss[loss=0.1003, number_positive_cuts_ratio=0, over 6108.00 frames. utt_duration=469.8 frames, utt_pad_proportion=0.3564, over 13.00 utterances.], tot_loss[loss=0.2116, number_positive_cuts_ratio=0.1444, over 967577.12 frames. utt_duration=407.8 frames, utt_pad_proportion=0.4133, over 2372.94 utterances.], batch size: 13
+2023-03-16 15:25:17,977 INFO [train.py:456] Epoch 1, batch 430, loss[loss=0.1375, number_positive_cuts_ratio=0.2, over 6411.00 frames. utt_duration=427.4 frames, utt_pad_proportion=0.3363, over 15.00 utterances.], tot_loss[loss=0.2107, number_positive_cuts_ratio=0.1453, over 971483.10 frames. utt_duration=407.4 frames, utt_pad_proportion=0.4133, over 2384.51 utterances.], batch size: 15
+2023-03-16 15:25:18,246 INFO [train.py:456] Epoch 1, batch 435, loss[loss=0.2601, number_positive_cuts_ratio=0.1429, over 4927.00 frames. utt_duration=351.9 frames, utt_pad_proportion=0.3932, over 14.00 utterances.], tot_loss[loss=0.2111, number_positive_cuts_ratio=0.146, over 974288.32 frames. utt_duration=407.2 frames, utt_pad_proportion=0.4131, over 2392.83 utterances.], batch size: 14
+2023-03-16 15:25:18,503 INFO [train.py:456] Epoch 1, batch 440, loss[loss=0.2282, number_positive_cuts_ratio=0.125, over 6129.00 frames. utt_duration=383.1 frames, utt_pad_proportion=0.3573, over 16.00 utterances.], tot_loss[loss=0.2111, number_positive_cuts_ratio=0.1467, over 976286.19 frames. utt_duration=406.5 frames, utt_pad_proportion=0.414, over 2401.97 utterances.], batch size: 16
+2023-03-16 15:25:18,726 INFO [train.py:456] Epoch 1, batch 445, loss[loss=0.2776, number_positive_cuts_ratio=0.2667, over 6721.00 frames. utt_duration=448.1 frames, utt_pad_proportion=0.3053, over 15.00 utterances.], tot_loss[loss=0.2105, number_positive_cuts_ratio=0.1452, over 980271.30 frames. utt_duration=407.3 frames, utt_pad_proportion=0.413, over 2406.86 utterances.], batch size: 15
+2023-03-16 15:25:19,031 INFO [train.py:456] Epoch 1, batch 450, loss[loss=0.2233, number_positive_cuts_ratio=0.1429, over 5535.00 frames. utt_duration=395.4 frames, utt_pad_proportion=0.4194, over 14.00 utterances.], tot_loss[loss=0.2076, number_positive_cuts_ratio=0.1426, over 984177.48 frames. utt_duration=407.8 frames, utt_pad_proportion=0.4126, over 2413.63 utterances.], batch size: 14
+2023-03-16 15:25:19,426 INFO [train.py:456] Epoch 1, batch 455, loss[loss=0.4031, number_positive_cuts_ratio=0.2308, over 4703.00 frames. utt_duration=361.8 frames, utt_pad_proportion=0.5265, over 13.00 utterances.], tot_loss[loss=0.2056, number_positive_cuts_ratio=0.1399, over 989279.83 frames. utt_duration=407.9 frames, utt_pad_proportion=0.4113, over 2425.16 utterances.], batch size: 13
+2023-03-16 15:25:19,728 INFO [train.py:456] Epoch 1, batch 460, loss[loss=0.2074, number_positive_cuts_ratio=0.08333, over 5360.00 frames. utt_duration=446.7 frames, utt_pad_proportion=0.4592, over 12.00 utterances.], tot_loss[loss=0.2099, number_positive_cuts_ratio=0.1417, over 989706.92 frames. utt_duration=407.5 frames, utt_pad_proportion=0.4121, over 2428.51 utterances.], batch size: 12
+2023-03-16 15:25:19,956 INFO [train.py:456] Epoch 1, batch 465, loss[loss=0.1151, number_positive_cuts_ratio=0, over 6004.00 frames. utt_duration=545.8 frames, utt_pad_proportion=0.3962, over 11.00 utterances.], tot_loss[loss=0.2111, number_positive_cuts_ratio=0.1418, over 993157.69 frames. utt_duration=408.4 frames, utt_pad_proportion=0.4123, over 2431.74 utterances.], batch size: 11
+2023-03-16 15:25:20,329 INFO [train.py:456] Epoch 1, batch 470, loss[loss=0.6716, number_positive_cuts_ratio=0.4118, over 5145.00 frames. utt_duration=302.6 frames, utt_pad_proportion=0.4615, over 17.00 utterances.], tot_loss[loss=0.2149, number_positive_cuts_ratio=0.1435, over 996710.87 frames. utt_duration=406.7 frames, utt_pad_proportion=0.4123, over 2450.75 utterances.], batch size: 17
+2023-03-16 15:25:20,545 INFO [train.py:456] Epoch 1, batch 475, loss[loss=0.261, number_positive_cuts_ratio=0.2143, over 5823.00 frames. utt_duration=415.9 frames, utt_pad_proportion=0.3811, over 14.00 utterances.], tot_loss[loss=0.2179, number_positive_cuts_ratio=0.1467, over 998976.46 frames. utt_duration=405.9 frames, utt_pad_proportion=0.4129, over 2461.37 utterances.], batch size: 14
+2023-03-16 15:25:20,816 INFO [train.py:456] Epoch 1, batch 480, loss[loss=0.2195, number_positive_cuts_ratio=0.2143, over 5772.00 frames. utt_duration=412.3 frames, utt_pad_proportion=0.3846, over 14.00 utterances.], tot_loss[loss=0.2181, number_positive_cuts_ratio=0.1472, over 1001919.98 frames. utt_duration=405.5 frames, utt_pad_proportion=0.4121, over 2470.78 utterances.], batch size: 14
+2023-03-16 15:25:21,004 INFO [train.py:456] Epoch 1, batch 485, loss[loss=0.1276, number_positive_cuts_ratio=0, over 6482.00 frames. utt_duration=498.6 frames, utt_pad_proportion=0.317, over 13.00 utterances.], tot_loss[loss=0.2175, number_positive_cuts_ratio=0.1469, over 1002573.29 frames. utt_duration=406.1 frames, utt_pad_proportion=0.4123, over 2469.03 utterances.], batch size: 13
+2023-03-16 15:25:21,256 INFO [train.py:456] Epoch 1, batch 490, loss[loss=0.3197, number_positive_cuts_ratio=0.2308, over 5284.00 frames. utt_duration=406.5 frames, utt_pad_proportion=0.4417, over 13.00 utterances.], tot_loss[loss=0.2178, number_positive_cuts_ratio=0.1476, over 1004402.40 frames. utt_duration=405.6 frames, utt_pad_proportion=0.4131, over 2476.23 utterances.], batch size: 13
+2023-03-16 15:25:21,468 INFO [train.py:456] Epoch 1, batch 495, loss[loss=0.09606, number_positive_cuts_ratio=0.1429, over 5088.00 frames. utt_duration=363.4 frames, utt_pad_proportion=0.4608, over 14.00 utterances.], tot_loss[loss=0.2145, number_positive_cuts_ratio=0.1461, over 1009125.51 frames. utt_duration=406 frames, utt_pad_proportion=0.4122, over 2485.27 utterances.], batch size: 14
+2023-03-16 15:25:21,751 INFO [train.py:456] Epoch 1, batch 500, loss[loss=0.1599, number_positive_cuts_ratio=0.1538, over 5508.00 frames. utt_duration=423.7 frames, utt_pad_proportion=0.4469, over 13.00 utterances.], tot_loss[loss=0.2139, number_positive_cuts_ratio=0.147, over 1013068.75 frames. utt_duration=406 frames, utt_pad_proportion=0.4113, over 2495.01 utterances.], batch size: 13
+2023-03-16 15:25:21,970 INFO [train.py:456] Epoch 1, batch 505, loss[loss=0.1983, number_positive_cuts_ratio=0.2, over 5610.00 frames. utt_duration=374 frames, utt_pad_proportion=0.4073, over 15.00 utterances.], tot_loss[loss=0.2117, number_positive_cuts_ratio=0.1457, over 1017201.56 frames. utt_duration=406.8 frames, utt_pad_proportion=0.4106, over 2500.58 utterances.], batch size: 15
+2023-03-16 15:25:22,260 INFO [train.py:456] Epoch 1, batch 510, loss[loss=0.1245, number_positive_cuts_ratio=0.1429, over 6143.00 frames. utt_duration=438.8 frames, utt_pad_proportion=0.3767, over 14.00 utterances.], tot_loss[loss=0.209, number_positive_cuts_ratio=0.1447, over 1020500.69 frames. utt_duration=407.1 frames, utt_pad_proportion=0.4101, over 2507.00 utterances.], batch size: 14
+2023-03-16 15:25:22,457 INFO [train.py:456] Epoch 1, batch 515, loss[loss=0.2129, number_positive_cuts_ratio=0.1667, over 5525.00 frames. utt_duration=460.4 frames, utt_pad_proportion=0.4172, over 12.00 utterances.], tot_loss[loss=0.2084, number_positive_cuts_ratio=0.145, over 1021956.18 frames. utt_duration=406.8 frames, utt_pad_proportion=0.4106, over 2512.23 utterances.], batch size: 12
+2023-03-16 15:25:22,773 INFO [train.py:456] Epoch 1, batch 520, loss[loss=0.1748, number_positive_cuts_ratio=0.2222, over 6377.00 frames. utt_duration=354.3 frames, utt_pad_proportion=0.3451, over 18.00 utterances.], tot_loss[loss=0.2091, number_positive_cuts_ratio=0.1466, over 1023429.61 frames. utt_duration=406.1 frames, utt_pad_proportion=0.4112, over 2520.39 utterances.], batch size: 18
+2023-03-16 15:25:23,009 INFO [train.py:456] Epoch 1, batch 525, loss[loss=0.1642, number_positive_cuts_ratio=0, over 6506.00 frames. utt_duration=433.7 frames, utt_pad_proportion=0.3418, over 15.00 utterances.], tot_loss[loss=0.2079, number_positive_cuts_ratio=0.1451, over 1027639.28 frames. utt_duration=406.8 frames, utt_pad_proportion=0.4104, over 2526.36 utterances.], batch size: 15
+2023-03-16 15:25:23,291 INFO [train.py:456] Epoch 1, batch 530, loss[loss=0.123, number_positive_cuts_ratio=0.1429, over 5473.00 frames. utt_duration=390.9 frames, utt_pad_proportion=0.4174, over 14.00 utterances.], tot_loss[loss=0.206, number_positive_cuts_ratio=0.1451, over 1027847.05 frames. utt_duration=406.6 frames, utt_pad_proportion=0.4108, over 2528.18 utterances.], batch size: 14
+2023-03-16 15:25:23,627 INFO [train.py:456] Epoch 1, batch 535, loss[loss=0.08163, number_positive_cuts_ratio=0.06667, over 6115.00 frames. utt_duration=407.7 frames, utt_pad_proportion=0.3689, over 15.00 utterances.], tot_loss[loss=0.2054, number_positive_cuts_ratio=0.145, over 1030346.20 frames. utt_duration=406.5 frames, utt_pad_proportion=0.4106, over 2534.92 utterances.], batch size: 15
+2023-03-16 15:25:23,929 INFO [train.py:456] Epoch 1, batch 540, loss[loss=0.105, number_positive_cuts_ratio=0.1333, over 5880.00 frames. utt_duration=392 frames, utt_pad_proportion=0.3758, over 15.00 utterances.], tot_loss[loss=0.203, number_positive_cuts_ratio=0.1438, over 1035480.61 frames. utt_duration=406.6 frames, utt_pad_proportion=0.4087, over 2546.44 utterances.], batch size: 15
+2023-03-16 15:25:24,252 INFO [train.py:456] Epoch 1, batch 545, loss[loss=0.3396, number_positive_cuts_ratio=0.3333, over 4780.00 frames. utt_duration=318.7 frames, utt_pad_proportion=0.4909, over 15.00 utterances.], tot_loss[loss=0.2068, number_positive_cuts_ratio=0.1478, over 1035776.00 frames. utt_duration=405 frames, utt_pad_proportion=0.4096, over 2557.71 utterances.], batch size: 15
+2023-03-16 15:25:24,567 INFO [train.py:456] Epoch 1, batch 550, loss[loss=0.121, number_positive_cuts_ratio=0.1429, over 5723.00 frames. utt_duration=408.8 frames, utt_pad_proportion=0.411, over 14.00 utterances.], tot_loss[loss=0.2059, number_positive_cuts_ratio=0.1476, over 1039287.57 frames. utt_duration=404.5 frames, utt_pad_proportion=0.4084, over 2569.61 utterances.], batch size: 14
+2023-03-16 15:25:24,764 INFO [train.py:456] Epoch 1, batch 555, loss[loss=0.1955, number_positive_cuts_ratio=0.1333, over 6323.00 frames. utt_duration=421.5 frames, utt_pad_proportion=0.3574, over 15.00 utterances.], tot_loss[loss=0.2059, number_positive_cuts_ratio=0.1477, over 1041681.87 frames. utt_duration=404.2 frames, utt_pad_proportion=0.4084, over 2577.28 utterances.], batch size: 15
+2023-03-16 15:25:25,043 INFO [train.py:456] Epoch 1, batch 560, loss[loss=0.1164, number_positive_cuts_ratio=0, over 6236.00 frames. utt_duration=479.7 frames, utt_pad_proportion=0.2787, over 13.00 utterances.], tot_loss[loss=0.2046, number_positive_cuts_ratio=0.1455, over 1045437.52 frames. utt_duration=404.8 frames, utt_pad_proportion=0.4057, over 2582.73 utterances.], batch size: 13
+2023-03-16 15:25:25,258 INFO [train.py:456] Epoch 1, batch 565, loss[loss=0.09753, number_positive_cuts_ratio=0.09091, over 5107.00 frames. utt_duration=464.3 frames, utt_pad_proportion=0.47, over 11.00 utterances.], tot_loss[loss=0.2036, number_positive_cuts_ratio=0.1438, over 1047401.22 frames. utt_duration=405.2 frames, utt_pad_proportion=0.4055, over 2585.13 utterances.], batch size: 11
+2023-03-16 15:25:25,538 INFO [train.py:456] Epoch 1, batch 570, loss[loss=0.4685, number_positive_cuts_ratio=0.2778, over 5854.00 frames. utt_duration=325.2 frames, utt_pad_proportion=0.4119, over 18.00 utterances.], tot_loss[loss=0.2058, number_positive_cuts_ratio=0.1448, over 1049534.29 frames. utt_duration=405 frames, utt_pad_proportion=0.4051, over 2591.48 utterances.], batch size: 18
+2023-03-16 15:25:25,712 INFO [train.py:456] Epoch 1, batch 575, loss[loss=0.2995, number_positive_cuts_ratio=0.2667, over 5026.00 frames. utt_duration=335.1 frames, utt_pad_proportion=0.4969, over 15.00 utterances.], tot_loss[loss=0.2048, number_positive_cuts_ratio=0.145, over 1048309.13 frames. utt_duration=405.1 frames, utt_pad_proportion=0.4067, over 2587.78 utterances.], batch size: 15
+2023-03-16 15:25:25,938 INFO [train.py:456] Epoch 1, batch 580, loss[loss=0.1649, number_positive_cuts_ratio=0.25, over 4248.00 frames. utt_duration=354 frames, utt_pad_proportion=0.5409, over 12.00 utterances.], tot_loss[loss=0.204, number_positive_cuts_ratio=0.1454, over 1047709.96 frames. utt_duration=404.7 frames, utt_pad_proportion=0.4078, over 2589.08 utterances.], batch size: 12
+2023-03-16 15:25:26,162 INFO [train.py:456] Epoch 1, batch 585, loss[loss=0.08935, number_positive_cuts_ratio=0.1818, over 4505.00 frames. utt_duration=409.5 frames, utt_pad_proportion=0.5221, over 11.00 utterances.], tot_loss[loss=0.2021, number_positive_cuts_ratio=0.1445, over 1051884.12 frames. utt_duration=405.5 frames, utt_pad_proportion=0.4065, over 2594.27 utterances.], batch size: 11
+2023-03-16 15:25:26,428 INFO [train.py:456] Epoch 1, batch 590, loss[loss=0.1693, number_positive_cuts_ratio=0, over 6839.00 frames. utt_duration=488.5 frames, utt_pad_proportion=0.2941, over 14.00 utterances.], tot_loss[loss=0.201, number_positive_cuts_ratio=0.1433, over 1055629.21 frames. utt_duration=406 frames, utt_pad_proportion=0.4058, over 2600.35 utterances.], batch size: 14
+2023-03-16 15:25:26,677 INFO [train.py:456] Epoch 1, batch 595, loss[loss=0.116, number_positive_cuts_ratio=0.1765, over 6060.00 frames. utt_duration=356.5 frames, utt_pad_proportion=0.36, over 17.00 utterances.], tot_loss[loss=0.1992, number_positive_cuts_ratio=0.143, over 1056917.82 frames. utt_duration=406.1 frames, utt_pad_proportion=0.4057, over 2602.39 utterances.], batch size: 17
+2023-03-16 15:25:26,944 INFO [train.py:456] Epoch 1, batch 600, loss[loss=0.1418, number_positive_cuts_ratio=0.0625, over 6224.00 frames. utt_duration=389 frames, utt_pad_proportion=0.3644, over 16.00 utterances.], tot_loss[loss=0.1986, number_positive_cuts_ratio=0.1419, over 1058808.53 frames. utt_duration=406.2 frames, utt_pad_proportion=0.4058, over 2606.32 utterances.], batch size: 16
+2023-03-16 15:25:27,153 INFO [train.py:456] Epoch 1, batch 605, loss[loss=0.1744, number_positive_cuts_ratio=0.1667, over 5062.00 frames. utt_duration=421.8 frames, utt_pad_proportion=0.4799, over 12.00 utterances.], tot_loss[loss=0.1997, number_positive_cuts_ratio=0.1427, over 1059522.80 frames. utt_duration=406.2 frames, utt_pad_proportion=0.4066, over 2608.13 utterances.], batch size: 12
+2023-03-16 15:25:27,394 INFO [train.py:456] Epoch 1, batch 610, loss[loss=0.2287, number_positive_cuts_ratio=0.1111, over 4121.00 frames. utt_duration=457.9 frames, utt_pad_proportion=0.5444, over 9.00 utterances.], tot_loss[loss=0.1993, number_positive_cuts_ratio=0.1428, over 1055760.57 frames. utt_duration=406.7 frames, utt_pad_proportion=0.4083, over 2596.01 utterances.], batch size: 9
+2023-03-16 15:25:27,610 INFO [train.py:456] Epoch 1, batch 615, loss[loss=0.08986, number_positive_cuts_ratio=0, over 5431.00 frames. utt_duration=452.6 frames, utt_pad_proportion=0.4242, over 12.00 utterances.], tot_loss[loss=0.1976, number_positive_cuts_ratio=0.1413, over 1058319.85 frames. utt_duration=407.3 frames, utt_pad_proportion=0.4079, over 2598.07 utterances.], batch size: 12
+2023-03-16 15:25:27,865 INFO [train.py:456] Epoch 1, batch 620, loss[loss=0.2473, number_positive_cuts_ratio=0.1667, over 5580.00 frames. utt_duration=465 frames, utt_pad_proportion=0.3984, over 12.00 utterances.], tot_loss[loss=0.198, number_positive_cuts_ratio=0.1415, over 1062002.85 frames. utt_duration=407.7 frames, utt_pad_proportion=0.4068, over 2605.04 utterances.], batch size: 12
+2023-03-16 15:25:28,138 INFO [train.py:456] Epoch 1, batch 625, loss[loss=0.07051, number_positive_cuts_ratio=0, over 6294.00 frames. utt_duration=524.5 frames, utt_pad_proportion=0.3549, over 12.00 utterances.], tot_loss[loss=0.1957, number_positive_cuts_ratio=0.1395, over 1064912.21 frames. utt_duration=408.5 frames, utt_pad_proportion=0.4063, over 2606.87 utterances.], batch size: 12
+2023-03-16 15:25:28,412 INFO [train.py:456] Epoch 1, batch 630, loss[loss=0.3064, number_positive_cuts_ratio=0.2143, over 5444.00 frames. utt_duration=388.9 frames, utt_pad_proportion=0.4179, over 14.00 utterances.], tot_loss[loss=0.1938, number_positive_cuts_ratio=0.1378, over 1068515.38 frames. utt_duration=409.3 frames, utt_pad_proportion=0.4052, over 2610.66 utterances.], batch size: 14
+2023-03-16 15:25:28,675 INFO [train.py:456] Epoch 1, batch 635, loss[loss=0.2164, number_positive_cuts_ratio=0.1333, over 6230.00 frames. utt_duration=415.3 frames, utt_pad_proportion=0.3449, over 15.00 utterances.], tot_loss[loss=0.1922, number_positive_cuts_ratio=0.1359, over 1071165.72 frames. utt_duration=409.9 frames, utt_pad_proportion=0.4043, over 2613.36 utterances.], batch size: 15
+2023-03-16 15:25:28,939 INFO [train.py:456] Epoch 1, batch 640, loss[loss=0.1101, number_positive_cuts_ratio=0.08333, over 5373.00 frames. utt_duration=447.8 frames, utt_pad_proportion=0.4506, over 12.00 utterances.], tot_loss[loss=0.1927, number_positive_cuts_ratio=0.1365, over 1069173.73 frames. utt_duration=409.3 frames, utt_pad_proportion=0.4053, over 2612.05 utterances.], batch size: 12
+2023-03-16 15:25:29,420 INFO [train.py:456] Epoch 1, batch 645, loss[loss=0.2023, number_positive_cuts_ratio=0.1875, over 6762.00 frames. utt_duration=422.6 frames, utt_pad_proportion=0.3003, over 16.00 utterances.], tot_loss[loss=0.1935, number_positive_cuts_ratio=0.1373, over 1070724.25 frames. utt_duration=409.5 frames, utt_pad_proportion=0.4054, over 2614.72 utterances.], batch size: 16
+2023-03-16 15:25:29,630 INFO [train.py:456] Epoch 1, batch 650, loss[loss=0.217, number_positive_cuts_ratio=0.1875, over 6350.00 frames. utt_duration=396.9 frames, utt_pad_proportion=0.3472, over 16.00 utterances.], tot_loss[loss=0.1938, number_positive_cuts_ratio=0.1374, over 1074423.18 frames. utt_duration=410.2 frames, utt_pad_proportion=0.4043, over 2619.32 utterances.], batch size: 16
+2023-03-16 15:25:30,074 INFO [train.py:456] Epoch 1, batch 655, loss[loss=0.09117, number_positive_cuts_ratio=0, over 5605.00 frames. utt_duration=467.1 frames, utt_pad_proportion=0.4065, over 12.00 utterances.], tot_loss[loss=0.1923, number_positive_cuts_ratio=0.1367, over 1074914.07 frames. utt_duration=409.7 frames, utt_pad_proportion=0.4049, over 2623.80 utterances.], batch size: 12
+2023-03-16 15:25:30,282 INFO [train.py:456] Epoch 1, batch 660, loss[loss=0.06198, number_positive_cuts_ratio=0, over 5642.00 frames. utt_duration=434 frames, utt_pad_proportion=0.4119, over 13.00 utterances.], tot_loss[loss=0.1907, number_positive_cuts_ratio=0.1352, over 1077264.55 frames. utt_duration=410.1 frames, utt_pad_proportion=0.4044, over 2627.14 utterances.], batch size: 13
+2023-03-16 15:25:30,570 INFO [train.py:456] Epoch 1, batch 665, loss[loss=0.09573, number_positive_cuts_ratio=0, over 6756.00 frames. utt_duration=397.4 frames, utt_pad_proportion=0.2865, over 17.00 utterances.], tot_loss[loss=0.1908, number_positive_cuts_ratio=0.1361, over 1078601.10 frames. utt_duration=409.4 frames, utt_pad_proportion=0.4043, over 2634.43 utterances.], batch size: 17
+2023-03-16 15:25:30,812 INFO [train.py:456] Epoch 1, batch 670, loss[loss=0.3035, number_positive_cuts_ratio=0.3333, over 5636.00 frames. utt_duration=375.7 frames, utt_pad_proportion=0.4219, over 15.00 utterances.], tot_loss[loss=0.1913, number_positive_cuts_ratio=0.138, over 1078248.10 frames. utt_duration=408.8 frames, utt_pad_proportion=0.4055, over 2637.56 utterances.], batch size: 15
+2023-03-16 15:25:31,036 INFO [train.py:456] Epoch 1, batch 675, loss[loss=0.09128, number_positive_cuts_ratio=0.07692, over 5394.00 frames. utt_duration=414.9 frames, utt_pad_proportion=0.4355, over 13.00 utterances.], tot_loss[loss=0.1916, number_positive_cuts_ratio=0.1388, over 1079908.36 frames. utt_duration=408.7 frames, utt_pad_proportion=0.4054, over 2642.58 utterances.], batch size: 13
+2023-03-16 15:25:31,267 INFO [train.py:456] Epoch 1, batch 680, loss[loss=0.1158, number_positive_cuts_ratio=0.08333, over 5283.00 frames. utt_duration=440.2 frames, utt_pad_proportion=0.4631, over 12.00 utterances.], tot_loss[loss=0.1901, number_positive_cuts_ratio=0.1377, over 1079713.70 frames. utt_duration=408.7 frames, utt_pad_proportion=0.4053, over 2641.52 utterances.], batch size: 12
+2023-03-16 15:25:31,471 INFO [train.py:456] Epoch 1, batch 685, loss[loss=0.2786, number_positive_cuts_ratio=0.25, over 5845.00 frames. utt_duration=365.3 frames, utt_pad_proportion=0.405, over 16.00 utterances.], tot_loss[loss=0.1897, number_positive_cuts_ratio=0.1379, over 1080843.51 frames. utt_duration=408.9 frames, utt_pad_proportion=0.4049, over 2643.46 utterances.], batch size: 16
+2023-03-16 15:25:31,703 INFO [train.py:456] Epoch 1, batch 690, loss[loss=0.1918, number_positive_cuts_ratio=0.2143, over 5782.00 frames. utt_duration=413 frames, utt_pad_proportion=0.4092, over 14.00 utterances.], tot_loss[loss=0.1885, number_positive_cuts_ratio=0.1387, over 1081521.87 frames. utt_duration=408.8 frames, utt_pad_proportion=0.4043, over 2645.35 utterances.], batch size: 14
+2023-03-16 15:25:31,924 INFO [train.py:456] Epoch 1, batch 695, loss[loss=0.1853, number_positive_cuts_ratio=0.08333, over 4969.00 frames. utt_duration=414.1 frames, utt_pad_proportion=0.4657, over 12.00 utterances.], tot_loss[loss=0.1869, number_positive_cuts_ratio=0.1373, over 1082449.94 frames. utt_duration=408.9 frames, utt_pad_proportion=0.4042, over 2647.18 utterances.], batch size: 12
+2023-03-16 15:25:32,206 INFO [train.py:456] Epoch 1, batch 700, loss[loss=0.1734, number_positive_cuts_ratio=0.1333, over 5678.00 frames. utt_duration=378.5 frames, utt_pad_proportion=0.4076, over 15.00 utterances.], tot_loss[loss=0.1867, number_positive_cuts_ratio=0.1377, over 1083779.14 frames. utt_duration=408.5 frames, utt_pad_proportion=0.4043, over 2652.92 utterances.], batch size: 15
+2023-03-16 15:25:32,392 INFO [train.py:456] Epoch 1, batch 705, loss[loss=0.1556, number_positive_cuts_ratio=0.1818, over 4558.00 frames. utt_duration=414.4 frames, utt_pad_proportion=0.5102, over 11.00 utterances.], tot_loss[loss=0.187, number_positive_cuts_ratio=0.1385, over 1083181.41 frames. utt_duration=408.4 frames, utt_pad_proportion=0.4054, over 2652.56 utterances.], batch size: 11
+2023-03-16 15:25:32,673 INFO [train.py:456] Epoch 1, batch 710, loss[loss=0.1217, number_positive_cuts_ratio=0.1765, over 6304.00 frames. utt_duration=370.8 frames, utt_pad_proportion=0.365, over 17.00 utterances.], tot_loss[loss=0.1861, number_positive_cuts_ratio=0.1373, over 1084100.96 frames. utt_duration=409.4 frames, utt_pad_proportion=0.4053, over 2648.33 utterances.], batch size: 17
+2023-03-16 15:25:32,893 INFO [train.py:456] Epoch 1, batch 715, loss[loss=0.2005, number_positive_cuts_ratio=0.08333, over 4514.00 frames. utt_duration=376.2 frames, utt_pad_proportion=0.3943, over 12.00 utterances.], tot_loss[loss=0.186, number_positive_cuts_ratio=0.136, over 1084471.79 frames. utt_duration=408.9 frames, utt_pad_proportion=0.4043, over 2652.10 utterances.], batch size: 12
+2023-03-16 15:25:33,150 INFO [train.py:456] Epoch 1, batch 720, loss[loss=0.1264, number_positive_cuts_ratio=0.1333, over 6235.00 frames. utt_duration=415.7 frames, utt_pad_proportion=0.3644, over 15.00 utterances.], tot_loss[loss=0.186, number_positive_cuts_ratio=0.1373, over 1083065.59 frames. utt_duration=409 frames, utt_pad_proportion=0.4054, over 2647.90 utterances.], batch size: 15
+2023-03-16 15:25:33,346 INFO [train.py:456] Epoch 1, batch 725, loss[loss=0.05621, number_positive_cuts_ratio=0, over 5382.00 frames. utt_duration=448.5 frames, utt_pad_proportion=0.4596, over 12.00 utterances.], tot_loss[loss=0.1866, number_positive_cuts_ratio=0.1373, over 1084824.55 frames. utt_duration=408.7 frames, utt_pad_proportion=0.4051, over 2654.54 utterances.], batch size: 12
+2023-03-16 15:25:33,620 INFO [train.py:456] Epoch 1, batch 730, loss[loss=0.2202, number_positive_cuts_ratio=0.2857, over 5351.00 frames. utt_duration=382.2 frames, utt_pad_proportion=0.4493, over 14.00 utterances.], tot_loss[loss=0.1858, number_positive_cuts_ratio=0.1377, over 1085963.72 frames. utt_duration=408.6 frames, utt_pad_proportion=0.4052, over 2658.09 utterances.], batch size: 14
+2023-03-16 15:25:33,853 INFO [train.py:456] Epoch 1, batch 735, loss[loss=0.3267, number_positive_cuts_ratio=0.3333, over 5547.00 frames. utt_duration=369.8 frames, utt_pad_proportion=0.4083, over 15.00 utterances.], tot_loss[loss=0.1868, number_positive_cuts_ratio=0.139, over 1084726.74 frames. utt_duration=407.2 frames, utt_pad_proportion=0.4066, over 2663.59 utterances.], batch size: 15
+2023-03-16 15:25:34,109 INFO [train.py:456] Epoch 1, batch 740, loss[loss=0.1989, number_positive_cuts_ratio=0.1538, over 4792.00 frames. utt_duration=368.6 frames, utt_pad_proportion=0.4998, over 13.00 utterances.], tot_loss[loss=0.186, number_positive_cuts_ratio=0.1393, over 1084544.06 frames. utt_duration=407.4 frames, utt_pad_proportion=0.4066, over 2661.97 utterances.], batch size: 13
+2023-03-16 15:25:34,416 INFO [train.py:456] Epoch 1, batch 745, loss[loss=0.3896, number_positive_cuts_ratio=0.2941, over 5320.00 frames. utt_duration=312.9 frames, utt_pad_proportion=0.4461, over 17.00 utterances.], tot_loss[loss=0.187, number_positive_cuts_ratio=0.1409, over 1085977.07 frames. utt_duration=407.1 frames, utt_pad_proportion=0.4066, over 2667.44 utterances.], batch size: 17
+2023-03-16 15:25:34,757 INFO [train.py:456] Epoch 1, batch 750, loss[loss=0.1109, number_positive_cuts_ratio=0, over 6539.00 frames. utt_duration=467.1 frames, utt_pad_proportion=0.3181, over 14.00 utterances.], tot_loss[loss=0.1859, number_positive_cuts_ratio=0.1407, over 1086723.23 frames. utt_duration=406.9 frames, utt_pad_proportion=0.4063, over 2670.72 utterances.], batch size: 14
+2023-03-16 15:25:35,036 INFO [train.py:456] Epoch 1, batch 755, loss[loss=0.2322, number_positive_cuts_ratio=0.2, over 6230.00 frames. utt_duration=415.3 frames, utt_pad_proportion=0.364, over 15.00 utterances.], tot_loss[loss=0.1845, number_positive_cuts_ratio=0.1406, over 1089957.63 frames. utt_duration=407.5 frames, utt_pad_proportion=0.4054, over 2674.90 utterances.], batch size: 15
+2023-03-16 15:25:35,311 INFO [train.py:456] Epoch 1, batch 760, loss[loss=0.1957, number_positive_cuts_ratio=0.2353, over 6053.00 frames. utt_duration=356.1 frames, utt_pad_proportion=0.3818, over 17.00 utterances.], tot_loss[loss=0.1835, number_positive_cuts_ratio=0.141, over 1093691.62 frames. utt_duration=407.5 frames, utt_pad_proportion=0.4044, over 2683.95 utterances.], batch size: 17
+2023-03-16 15:25:35,513 INFO [train.py:456] Epoch 1, batch 765, loss[loss=0.04613, number_positive_cuts_ratio=0, over 6365.00 frames. utt_duration=489.6 frames, utt_pad_proportion=0.3329, over 13.00 utterances.], tot_loss[loss=0.1814, number_positive_cuts_ratio=0.1396, over 1094430.23 frames. utt_duration=407.9 frames, utt_pad_proportion=0.4047, over 2682.85 utterances.], batch size: 13
+2023-03-16 15:25:35,759 INFO [train.py:456] Epoch 1, batch 770, loss[loss=0.1681, number_positive_cuts_ratio=0.1538, over 5064.00 frames. utt_duration=389.5 frames, utt_pad_proportion=0.4806, over 13.00 utterances.], tot_loss[loss=0.1821, number_positive_cuts_ratio=0.141, over 1093738.73 frames. utt_duration=407.4 frames, utt_pad_proportion=0.4057, over 2684.80 utterances.], batch size: 13
+2023-03-16 15:25:35,955 INFO [train.py:456] Epoch 1, batch 775, loss[loss=0.2025, number_positive_cuts_ratio=0.2727, over 4443.00 frames. utt_duration=403.9 frames, utt_pad_proportion=0.5287, over 11.00 utterances.], tot_loss[loss=0.1835, number_positive_cuts_ratio=0.1424, over 1091397.57 frames. utt_duration=407.1 frames, utt_pad_proportion=0.4067, over 2680.73 utterances.], batch size: 11
+2023-03-16 15:25:36,230 INFO [train.py:456] Epoch 1, batch 780, loss[loss=0.4051, number_positive_cuts_ratio=0.25, over 4671.00 frames. utt_duration=389.2 frames, utt_pad_proportion=0.5189, over 12.00 utterances.], tot_loss[loss=0.1839, number_positive_cuts_ratio=0.1419, over 1092383.85 frames. utt_duration=407.2 frames, utt_pad_proportion=0.4067, over 2682.67 utterances.], batch size: 12
+2023-03-16 15:25:36,532 INFO [train.py:456] Epoch 1, batch 785, loss[loss=0.187, number_positive_cuts_ratio=0.1111, over 4754.00 frames. utt_duration=528.2 frames, utt_pad_proportion=0.4786, over 9.00 utterances.], tot_loss[loss=0.184, number_positive_cuts_ratio=0.1422, over 1090248.29 frames. utt_duration=407.2 frames, utt_pad_proportion=0.4082, over 2677.58 utterances.], batch size: 9
+2023-03-16 15:25:36,774 INFO [train.py:456] Epoch 1, batch 790, loss[loss=0.4405, number_positive_cuts_ratio=0.2857, over 5207.00 frames. utt_duration=371.9 frames, utt_pad_proportion=0.4522, over 14.00 utterances.], tot_loss[loss=0.1857, number_positive_cuts_ratio=0.1431, over 1092078.50 frames. utt_duration=407.1 frames, utt_pad_proportion=0.4078, over 2682.58 utterances.], batch size: 14
+2023-03-16 15:25:36,987 INFO [train.py:456] Epoch 1, batch 795, loss[loss=0.06288, number_positive_cuts_ratio=0.06667, over 5478.00 frames. utt_duration=365.2 frames, utt_pad_proportion=0.432, over 15.00 utterances.], tot_loss[loss=0.1859, number_positive_cuts_ratio=0.1434, over 1092666.44 frames. utt_duration=406.7 frames, utt_pad_proportion=0.408, over 2686.52 utterances.], batch size: 15
+2023-03-16 15:25:37,209 INFO [train.py:456] Epoch 1, batch 800, loss[loss=0.1188, number_positive_cuts_ratio=0, over 6677.00 frames. utt_duration=476.9 frames, utt_pad_proportion=0.273, over 14.00 utterances.], tot_loss[loss=0.187, number_positive_cuts_ratio=0.1437, over 1091996.46 frames. utt_duration=406.8 frames, utt_pad_proportion=0.4074, over 2684.40 utterances.], batch size: 14
+2023-03-16 15:25:37,416 INFO [train.py:456] Epoch 1, batch 805, loss[loss=0.8543, number_positive_cuts_ratio=0.5, over 4291.00 frames. utt_duration=306.5 frames, utt_pad_proportion=0.5425, over 14.00 utterances.], tot_loss[loss=0.1883, number_positive_cuts_ratio=0.1436, over 1089740.02 frames. utt_duration=406.7 frames, utt_pad_proportion=0.4076, over 2679.34 utterances.], batch size: 14
+2023-03-16 15:25:37,654 INFO [train.py:456] Epoch 1, batch 810, loss[loss=0.2825, number_positive_cuts_ratio=0.1, over 5083.00 frames. utt_duration=508.3 frames, utt_pad_proportion=0.4621, over 10.00 utterances.], tot_loss[loss=0.1872, number_positive_cuts_ratio=0.1426, over 1090537.04 frames. utt_duration=407.8 frames, utt_pad_proportion=0.4074, over 2674.36 utterances.], batch size: 10
+2023-03-16 15:25:37,866 INFO [train.py:456] Epoch 1, batch 815, loss[loss=0.1071, number_positive_cuts_ratio=0.07143, over 5640.00 frames. utt_duration=402.9 frames, utt_pad_proportion=0.3646, over 14.00 utterances.], tot_loss[loss=0.1859, number_positive_cuts_ratio=0.1416, over 1093156.68 frames. utt_duration=408 frames, utt_pad_proportion=0.4065, over 2679.43 utterances.], batch size: 14
+2023-03-16 15:25:38,075 INFO [train.py:456] Epoch 1, batch 820, loss[loss=0.1659, number_positive_cuts_ratio=0.08333, over 5069.00 frames. utt_duration=422.4 frames, utt_pad_proportion=0.4514, over 12.00 utterances.], tot_loss[loss=0.1848, number_positive_cuts_ratio=0.1407, over 1090747.90 frames. utt_duration=408.6 frames, utt_pad_proportion=0.4074, over 2669.56 utterances.], batch size: 12
+2023-03-16 15:25:38,317 INFO [train.py:456] Epoch 1, batch 825, loss[loss=0.176, number_positive_cuts_ratio=0.08333, over 5452.00 frames. utt_duration=454.3 frames, utt_pad_proportion=0.4168, over 12.00 utterances.], tot_loss[loss=0.1845, number_positive_cuts_ratio=0.1402, over 1091944.67 frames. utt_duration=408.7 frames, utt_pad_proportion=0.4072, over 2671.76 utterances.], batch size: 12
+2023-03-16 15:25:38,588 INFO [train.py:456] Epoch 1, batch 830, loss[loss=0.2646, number_positive_cuts_ratio=0.2143, over 5052.00 frames. utt_duration=360.9 frames, utt_pad_proportion=0.467, over 14.00 utterances.], tot_loss[loss=0.1839, number_positive_cuts_ratio=0.1401, over 1091384.13 frames. utt_duration=408.8 frames, utt_pad_proportion=0.4079, over 2669.99 utterances.], batch size: 14
+2023-03-16 15:25:38,767 INFO [train.py:456] Epoch 1, batch 835, loss[loss=0.05309, number_positive_cuts_ratio=0, over 6551.00 frames. utt_duration=436.7 frames, utt_pad_proportion=0.3187, over 15.00 utterances.], tot_loss[loss=0.1814, number_positive_cuts_ratio=0.1384, over 1094601.19 frames. utt_duration=409.2 frames, utt_pad_proportion=0.4062, over 2675.17 utterances.], batch size: 15
+2023-03-16 15:25:39,070 INFO [train.py:456] Epoch 1, batch 840, loss[loss=0.1228, number_positive_cuts_ratio=0.1667, over 5002.00 frames. utt_duration=416.8 frames, utt_pad_proportion=0.4683, over 12.00 utterances.], tot_loss[loss=0.1799, number_positive_cuts_ratio=0.1379, over 1094576.91 frames. utt_duration=409.6 frames, utt_pad_proportion=0.4063, over 2672.35 utterances.], batch size: 12
+2023-03-16 15:25:39,321 INFO [train.py:456] Epoch 1, batch 845, loss[loss=0.1451, number_positive_cuts_ratio=0.2143, over 5260.00 frames. utt_duration=375.7 frames, utt_pad_proportion=0.4663, over 14.00 utterances.], tot_loss[loss=0.1803, number_positive_cuts_ratio=0.1394, over 1094198.53 frames. utt_duration=409 frames, utt_pad_proportion=0.4071, over 2675.53 utterances.], batch size: 14

exp_max_duration_100/post/epoch_1-avg_1/log/log-auc-himia_aishell-2023-03-16-15-40-07

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+2023-03-16 15:40:07,869 INFO [auc.py:109] About to compute AUC of himia_aishell
+2023-03-16 15:40:07,926 INFO [auc.py:126] AUC of himia_aishell ctc_tdnn/exp_max_duration_100/post/epoch_1-avg_1: 0.9307096888618627

exp_max_duration_100/post/epoch_1-avg_1/log/log-auc-himia_cw-2023-03-16-15-39-53

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+2023-03-16 15:39:53,702 INFO [auc.py:109] About to compute AUC of himia_cw
+2023-03-16 15:39:53,843 INFO [auc.py:126] AUC of himia_cw ctc_tdnn/exp_max_duration_100/post/epoch_1-avg_1: 0.920954498868017

exp_max_duration_100/post/epoch_1-avg_1/log/log-decode-aishell_test-2023-03-16-15-38-38

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+2023-03-16 15:38:38,890 INFO [decode.py:274] About to load aishell_test.
+2023-03-16 15:38:40,218 INFO [decode.py:283] Decoding aishell_test.
+2023-03-16 15:39:02,418 INFO [decode.py:288] Finish decoding aishell_test.

exp_max_duration_100/post/epoch_1-avg_1/log/log-decode-cw_test-2023-03-16-15-39-11

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+2023-03-16 15:39:11,408 INFO [decode.py:274] About to load cw_test.
+2023-03-16 15:39:13,199 INFO [decode.py:283] Decoding cw_test.
+2023-03-16 15:39:28,311 INFO [decode.py:288] Finish decoding cw_test.

exp_max_duration_100/post/epoch_1-avg_1/log/log-decode-test-2023-03-16-15-38-27

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+2023-03-16 15:38:27,748 INFO [decode.py:283] Decoding test.
+2023-03-16 15:38:30,430 INFO [decode.py:288] Finish decoding test.

exp_max_duration_100/post/epoch_1-avg_1/log/log-inference-2023-03-16-15-37-23

@@ -0,0 +1,21 @@
+2023-03-16 15:37:23,951 INFO [inference.py:144] Decoding started
+2023-03-16 15:37:23,951 INFO [inference.py:145] {'env_info': {'k2-version': '1.23.2', 'k2-build-type': 'Debug', 'k2-with-cuda': True, 'k2-git-sha1': 'a34171ed85605b0926eebbd0463d059431f4f74a', 'k2-git-date': 'Wed Dec 14 00:06:38 2022', 'lhotse-version': '1.13.0.dev+git.e7b4daf.clean', 'torch-version': '1.10.0+cu102', 'torch-cuda-available': True, 'torch-cuda-version': '10.2', 'python-version': '3.8', 'icefall-git-branch': 'himia', 'icefall-git-sha1': 'd5471c5-dirty', 'icefall-git-date': 'Thu Mar 16 14:59:16 2023', 'icefall-path': '/ceph-data3/ly/workspace/bf_ctc/himia_icefall', 'k2-path': '/star-ly/ceph_storages/ceph-data3/self_alignment_mp/k2/k2/python/k2/__init__.py', 'lhotse-path': '/ceph-data3/ly/workspace/bf_ctc/lhotse/lhotse/__init__.py', 'hostname': 'de-74279-k2-train-7-1218101249-5d97868c7c-v8ngc', 'IP address': '10.177.77.18'}, 'feature_dim': 80, 'number_class': 9, 'epoch': 1, 'avg': 1, 'exp_dir': PosixPath('ctc_tdnn/exp_max_duration_100'), 'manifest_dir': PosixPath('data/fbank'), 'max_duration': 200.0, 'bucketing_sampler': False, 'num_buckets': 30, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'on_the_fly_feats': False, 'shuffle': True, 'drop_last': True, 'return_cuts': True, 'num_workers': 2, 'enable_spec_aug': True, 'spec_aug_time_warp_factor': 80, 'enable_musan': True, 'input_strategy': 'PrecomputedFeatures', 'train_channel': '_7_01', 'dev_channel': '_7_01', 'out_dir': 'ctc_tdnn/exp_max_duration_100/post/epoch_1-avg_1/'}
+2023-03-16 15:37:23,952 INFO [inference.py:151] device: cuda:0
+2023-03-16 15:37:23,976 INFO [checkpoint.py:112] Loading checkpoint from ctc_tdnn/exp_max_duration_100/epoch-1.pt
+2023-03-16 15:37:35,651 INFO [inference.py:173] Number of model parameters: 1502169
+2023-03-16 15:37:35,652 INFO [asr_datamodule.py:411] About to get aishell test cuts
+2023-03-16 15:37:35,663 INFO [asr_datamodule.py:429] About to get test cuts
+2023-03-16 15:37:35,665 INFO [asr_datamodule.py:416] About to get HI-MIA-CW test cuts
+2023-03-16 15:37:36,630 INFO [inference.py:189] About to inference aishell_test
+2023-03-16 15:37:38,299 INFO [inference.py:127] batch 0/?, cuts processed until now is 20
+2023-03-16 15:37:42,052 INFO [inference.py:127] batch 100/?, cuts processed until now is 2911
+2023-03-16 15:37:47,794 INFO [inference.py:127] batch 200/?, cuts processed until now is 5885
+2023-03-16 15:37:50,226 INFO [inference.py:197] finish inferencing aishell_test
+2023-03-16 15:37:50,227 INFO [inference.py:189] About to inference test
+2023-03-16 15:37:50,887 INFO [inference.py:127] batch 0/?, cuts processed until now is 99
+2023-03-16 15:37:53,141 INFO [inference.py:197] finish inferencing test
+2023-03-16 15:37:53,142 INFO [inference.py:189] About to inference cw_test
+2023-03-16 15:37:54,278 INFO [inference.py:127] batch 0/?, cuts processed until now is 67
+2023-03-16 15:38:00,858 INFO [inference.py:127] batch 100/?, cuts processed until now is 10251
+2023-03-16 15:38:04,887 INFO [inference.py:197] finish inferencing cw_test
+2023-03-16 15:38:04,890 INFO [inference.py:199] Done!

exp_max_duration_100/post/epoch_2-avg_1/log/log-auc-himia_aishell-2023-03-16-16-02-56

@@ -0,0 +1,2 @@
+2023-03-16 16:02:56,627 INFO [auc.py:109] About to compute AUC of himia_aishell
+2023-03-16 16:02:56,682 INFO [auc.py:126] AUC of himia_aishell ctc_tdnn/exp_max_duration_100/post/epoch_2-avg_1: 0.9610327512161752

exp_max_duration_100/post/epoch_2-avg_1/log/log-auc-himia_cw-2023-03-16-16-02-43

@@ -0,0 +1,2 @@
+2023-03-16 16:02:43,922 INFO [auc.py:109] About to compute AUC of himia_cw
+2023-03-16 16:02:44,138 INFO [auc.py:126] AUC of himia_cw ctc_tdnn/exp_max_duration_100/post/epoch_2-avg_1: 0.8777777391488155

exp_max_duration_100/post/epoch_2-avg_1/log/log-decode-aishell_test-2023-03-16-16-01-32

@@ -0,0 +1,24 @@
+2023-03-16 16:01:32,761 INFO [decode.py:272] Graph used:
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+2023-03-16 16:01:32,761 INFO [decode.py:274] About to load aishell_test.
+2023-03-16 16:01:33,988 INFO [decode.py:283] Decoding aishell_test.
+2023-03-16 16:01:55,958 INFO [decode.py:288] Finish decoding aishell_test.

exp_max_duration_100/post/epoch_2-avg_1/log/log-decode-cw_test-2023-03-16-16-02-03

@@ -0,0 +1,24 @@
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+2023-03-16 16:02:03,132 INFO [decode.py:274] About to load cw_test.
+2023-03-16 16:02:04,645 INFO [decode.py:283] Decoding cw_test.
+2023-03-16 16:02:19,915 INFO [decode.py:288] Finish decoding cw_test.

exp_max_duration_100/post/epoch_2-avg_1/log/log-decode-test-2023-03-16-16-01-20

@@ -0,0 +1,24 @@
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+2023-03-16 16:01:20,820 INFO [decode.py:274] About to load test.
+2023-03-16 16:01:21,782 INFO [decode.py:283] Decoding test.
+2023-03-16 16:01:24,514 INFO [decode.py:288] Finish decoding test.

exp_max_duration_100/post/epoch_2-avg_1/log/log-inference-2023-03-16-16-00-02

@@ -0,0 +1,21 @@
+2023-03-16 16:00:02,285 INFO [inference.py:144] Decoding started
+2023-03-16 16:00:02,285 INFO [inference.py:145] {'env_info': {'k2-version': '1.23.2', 'k2-build-type': 'Debug', 'k2-with-cuda': True, 'k2-git-sha1': 'a34171ed85605b0926eebbd0463d059431f4f74a', 'k2-git-date': 'Wed Dec 14 00:06:38 2022', 'lhotse-version': '1.13.0.dev+git.e7b4daf.clean', 'torch-version': '1.10.0+cu102', 'torch-cuda-available': True, 'torch-cuda-version': '10.2', 'python-version': '3.8', 'icefall-git-branch': 'himia', 'icefall-git-sha1': 'd5471c5-dirty', 'icefall-git-date': 'Thu Mar 16 14:59:16 2023', 'icefall-path': '/ceph-data3/ly/workspace/bf_ctc/himia_icefall', 'k2-path': '/star-ly/ceph_storages/ceph-data3/self_alignment_mp/k2/k2/python/k2/__init__.py', 'lhotse-path': '/ceph-data3/ly/workspace/bf_ctc/lhotse/lhotse/__init__.py', 'hostname': 'de-74279-k2-train-7-1218101249-5d97868c7c-v8ngc', 'IP address': '10.177.77.18'}, 'feature_dim': 80, 'number_class': 9, 'epoch': 2, 'avg': 1, 'exp_dir': PosixPath('ctc_tdnn/exp_max_duration_100'), 'manifest_dir': PosixPath('data/fbank'), 'max_duration': 200.0, 'bucketing_sampler': False, 'num_buckets': 30, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'on_the_fly_feats': False, 'shuffle': True, 'drop_last': True, 'return_cuts': True, 'num_workers': 2, 'enable_spec_aug': True, 'spec_aug_time_warp_factor': 80, 'enable_musan': True, 'input_strategy': 'PrecomputedFeatures', 'train_channel': '_7_01', 'dev_channel': '_7_01', 'out_dir': 'ctc_tdnn/exp_max_duration_100/post/epoch_2-avg_1/'}
+2023-03-16 16:00:02,285 INFO [inference.py:151] device: cuda:0
+2023-03-16 16:00:02,312 INFO [checkpoint.py:112] Loading checkpoint from ctc_tdnn/exp_max_duration_100/epoch-2.pt
+2023-03-16 16:00:16,632 INFO [inference.py:173] Number of model parameters: 1502169
+2023-03-16 16:00:16,633 INFO [asr_datamodule.py:411] About to get aishell test cuts
+2023-03-16 16:00:16,687 INFO [asr_datamodule.py:429] About to get test cuts
+2023-03-16 16:00:16,688 INFO [asr_datamodule.py:416] About to get HI-MIA-CW test cuts
+2023-03-16 16:00:17,665 INFO [inference.py:189] About to inference aishell_test
+2023-03-16 16:00:19,460 INFO [inference.py:127] batch 0/?, cuts processed until now is 20
+2023-03-16 16:00:24,699 INFO [inference.py:127] batch 100/?, cuts processed until now is 2911
+2023-03-16 16:00:31,724 INFO [inference.py:127] batch 200/?, cuts processed until now is 5885
+2023-03-16 16:00:33,922 INFO [inference.py:197] finish inferencing aishell_test
+2023-03-16 16:00:33,924 INFO [inference.py:189] About to inference test
+2023-03-16 16:00:34,610 INFO [inference.py:127] batch 0/?, cuts processed until now is 99
+2023-03-16 16:00:36,990 INFO [inference.py:197] finish inferencing test
+2023-03-16 16:00:36,992 INFO [inference.py:189] About to inference cw_test
+2023-03-16 16:00:38,073 INFO [inference.py:127] batch 0/?, cuts processed until now is 67
+2023-03-16 16:00:44,719 INFO [inference.py:127] batch 100/?, cuts processed until now is 10251
+2023-03-16 16:00:48,849 INFO [inference.py:197] finish inferencing cw_test
+2023-03-16 16:00:48,851 INFO [inference.py:199] Done!

exp_max_duration_100/post/epoch_3-avg_1/log/log-auc-himia_aishell-2023-03-16-16-06-30

@@ -0,0 +1,2 @@
+2023-03-16 16:06:30,791 INFO [auc.py:109] About to compute AUC of himia_aishell
+2023-03-16 16:06:30,861 INFO [auc.py:126] AUC of himia_aishell ctc_tdnn/exp_max_duration_100/post/epoch_3-avg_1: 0.8215526858784332

exp_max_duration_100/post/epoch_3-avg_1/log/log-auc-himia_cw-2023-03-16-16-06-18

@@ -0,0 +1,2 @@
+2023-03-16 16:06:18,006 INFO [auc.py:109] About to compute AUC of himia_cw
+2023-03-16 16:06:18,163 INFO [auc.py:126] AUC of himia_cw ctc_tdnn/exp_max_duration_100/post/epoch_3-avg_1: 0.8311250333754234

exp_max_duration_100/post/epoch_3-avg_1/log/log-decode-aishell_test-2023-03-16-16-05-06

@@ -0,0 +1,24 @@
+2023-03-16 16:05:06,498 INFO [decode.py:272] Graph used:
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+
+2023-03-16 16:05:06,498 INFO [decode.py:274] About to load aishell_test.
+2023-03-16 16:05:07,632 INFO [decode.py:283] Decoding aishell_test.
+2023-03-16 16:05:29,625 INFO [decode.py:288] Finish decoding aishell_test.

exp_max_duration_100/post/epoch_3-avg_1/log/log-decode-cw_test-2023-03-16-16-05-37

@@ -0,0 +1,24 @@
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+
+2023-03-16 16:05:37,196 INFO [decode.py:274] About to load cw_test.
+2023-03-16 16:05:38,739 INFO [decode.py:283] Decoding cw_test.
+2023-03-16 16:05:54,279 INFO [decode.py:288] Finish decoding cw_test.

exp_max_duration_100/post/epoch_3-avg_1/log/log-decode-test-2023-03-16-16-04-54

@@ -0,0 +1,24 @@
+2023-03-16 16:04:54,611 INFO [decode.py:272] Graph used:
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+
+2023-03-16 16:04:54,611 INFO [decode.py:274] About to load test.
+2023-03-16 16:04:55,722 INFO [decode.py:283] Decoding test.
+2023-03-16 16:04:58,442 INFO [decode.py:288] Finish decoding test.

exp_max_duration_100/post/epoch_3-avg_1/log/log-inference-2023-03-16-16-03-47

@@ -0,0 +1,21 @@
+2023-03-16 16:03:47,394 INFO [inference.py:144] Decoding started
+2023-03-16 16:03:47,394 INFO [inference.py:145] {'env_info': {'k2-version': '1.23.2', 'k2-build-type': 'Debug', 'k2-with-cuda': True, 'k2-git-sha1': 'a34171ed85605b0926eebbd0463d059431f4f74a', 'k2-git-date': 'Wed Dec 14 00:06:38 2022', 'lhotse-version': '1.13.0.dev+git.e7b4daf.clean', 'torch-version': '1.10.0+cu102', 'torch-cuda-available': True, 'torch-cuda-version': '10.2', 'python-version': '3.8', 'icefall-git-branch': 'himia', 'icefall-git-sha1': 'd5471c5-dirty', 'icefall-git-date': 'Thu Mar 16 14:59:16 2023', 'icefall-path': '/ceph-data3/ly/workspace/bf_ctc/himia_icefall', 'k2-path': '/star-ly/ceph_storages/ceph-data3/self_alignment_mp/k2/k2/python/k2/__init__.py', 'lhotse-path': '/ceph-data3/ly/workspace/bf_ctc/lhotse/lhotse/__init__.py', 'hostname': 'de-74279-k2-train-7-1218101249-5d97868c7c-v8ngc', 'IP address': '10.177.77.18'}, 'feature_dim': 80, 'number_class': 9, 'epoch': 3, 'avg': 1, 'exp_dir': PosixPath('ctc_tdnn/exp_max_duration_100'), 'manifest_dir': PosixPath('data/fbank'), 'max_duration': 200.0, 'bucketing_sampler': False, 'num_buckets': 30, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'on_the_fly_feats': False, 'shuffle': True, 'drop_last': True, 'return_cuts': True, 'num_workers': 2, 'enable_spec_aug': True, 'spec_aug_time_warp_factor': 80, 'enable_musan': True, 'input_strategy': 'PrecomputedFeatures', 'train_channel': '_7_01', 'dev_channel': '_7_01', 'out_dir': 'ctc_tdnn/exp_max_duration_100/post/epoch_3-avg_1/'}
+2023-03-16 16:03:47,395 INFO [inference.py:151] device: cuda:0
+2023-03-16 16:03:47,422 INFO [checkpoint.py:112] Loading checkpoint from ctc_tdnn/exp_max_duration_100/epoch-3.pt
+2023-03-16 16:03:59,897 INFO [inference.py:173] Number of model parameters: 1502169
+2023-03-16 16:03:59,898 INFO [asr_datamodule.py:411] About to get aishell test cuts
+2023-03-16 16:03:59,906 INFO [asr_datamodule.py:429] About to get test cuts
+2023-03-16 16:03:59,907 INFO [asr_datamodule.py:416] About to get HI-MIA-CW test cuts
+2023-03-16 16:04:00,856 INFO [inference.py:189] About to inference aishell_test
+2023-03-16 16:04:02,619 INFO [inference.py:127] batch 0/?, cuts processed until now is 20
+2023-03-16 16:04:05,687 INFO [inference.py:127] batch 100/?, cuts processed until now is 2911
+2023-03-16 16:04:09,279 INFO [inference.py:127] batch 200/?, cuts processed until now is 5885
+2023-03-16 16:04:10,951 INFO [inference.py:197] finish inferencing aishell_test
+2023-03-16 16:04:10,953 INFO [inference.py:189] About to inference test
+2023-03-16 16:04:11,581 INFO [inference.py:127] batch 0/?, cuts processed until now is 99
+2023-03-16 16:04:13,948 INFO [inference.py:197] finish inferencing test
+2023-03-16 16:04:13,950 INFO [inference.py:189] About to inference cw_test
+2023-03-16 16:04:15,075 INFO [inference.py:127] batch 0/?, cuts processed until now is 67
+2023-03-16 16:04:22,231 INFO [inference.py:127] batch 100/?, cuts processed until now is 10251
+2023-03-16 16:04:26,453 INFO [inference.py:197] finish inferencing cw_test
+2023-03-16 16:04:26,456 INFO [inference.py:199] Done!