/home/tony/Work/glockenspiel/s3prl/s3prl/upstream/byol_s/byol_a/common.py:20: UserWarning: torchaudio._backend.set_audio_backend has been deprecated. With dispatcher enabled, this function is no-op. You can remove the function call.
  torchaudio.set_audio_backend("sox_io")
/home/tony/Work/glockenspiel/s3prl/s3prl/run_downstream.py:157: UserWarning: torchaudio._backend.set_audio_backend has been deprecated. With dispatcher enabled, this function is no-op. You can remove the function call.
  torchaudio.set_audio_backend('sox_io')
Some weights of the model checkpoint at m-a-p/MERT-v1-330M were not used when initializing MERTModel: ['encoder.pos_conv_embed.conv.weight_v', 'encoder.pos_conv_embed.conv.weight_g']
- This IS expected if you are initializing MERTModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing MERTModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
Some weights of MERTModel were not initialized from the model checkpoint at m-a-p/MERT-v1-330M and are newly initialized: ['encoder.pos_conv_embed.conv.parametrizations.weight.original1', 'encoder.pos_conv_embed.conv.parametrizations.weight.original0']
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
[Featurizer] - The selected feature hidden_states's downsample rate is 320
[Runner] - Start a new experiment
m-a-p/MERT-v1-330M {'model_config': None, 'refresh': False}

overall:   0%|          | 0/4000 [00:00<?, ?it/s][LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.


word -> phonemes:   0%|          | 0/3515 [00:00<?, ?it/s]

word -> phonemes:   8%|▊         | 295/3515 [00:00<00:01, 2946.55it/s]

word -> phonemes:  19%|█▉        | 660/3515 [00:00<00:00, 3357.51it/s]

word -> phonemes:  28%|██▊       | 996/3515 [00:00<00:00, 2875.29it/s]

word -> phonemes:  39%|███▊      | 1361/3515 [00:00<00:00, 3151.09it/s]

word -> phonemes:  48%|████▊     | 1684/3515 [00:00<00:00, 2967.45it/s]

word -> phonemes:  57%|█████▋    | 2017/3515 [00:00<00:00, 3079.47it/s]

word -> phonemes:  70%|██████▉   | 2447/3515 [00:00<00:00, 3454.02it/s]

word -> phonemes:  80%|███████▉  | 2798/3515 [00:00<00:00, 3181.85it/s]

word -> phonemes:  89%|████████▉ | 3124/3515 [00:01<00:00, 3059.86it/s]

word -> phonemes:  98%|█████████▊| 3456/3515 [00:01<00:00, 3106.14it/s]
word -> phonemes: 100%|██████████| 3515/3515 [00:01<00:00, 3129.59it/s]


train:   0%|          | 0/3515 [00:00<?, ?it/s]
overall:   0%|          | 1/4000 [00:04<5:05:07,  4.58s/it]

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overall:   0%|          | 6/4000 [00:10<1:32:15,  1.39s/it]

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overall:   0%|          | 7/4000 [00:11<1:29:47,  1.35s/it]

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overall:   0%|          | 8/4000 [00:13<1:26:25,  1.30s/it]

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overall:   0%|          | 9/4000 [00:14<1:24:50,  1.28s/it]

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overall:   0%|          | 11/4000 [00:14<52:34,  1.26it/s]  

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overall:   0%|          | 15/4000 [00:19<1:09:23,  1.04s/it]

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overall:   0%|          | 17/4000 [00:21<1:13:32,  1.11s/it]

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overall:   0%|          | 18/4000 [00:23<1:16:33,  1.15s/it]

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overall:   0%|          | 20/4000 [00:24<1:07:41,  1.02s/it]

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overall:   1%|          | 21/4000 [00:26<1:12:31,  1.09s/it]

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overall:   1%|          | 22/4000 [00:27<1:15:51,  1.14s/it]

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overall:   1%|          | 23/4000 [00:28<1:17:57,  1.18s/it]

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overall:   1%|          | 24/4000 [00:29<1:16:29,  1.15s/it]

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overall:   1%|          | 25/4000 [00:30<1:18:23,  1.18s/it]

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overall:   1%|          | 26/4000 [00:32<1:18:27,  1.18s/it]

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overall:   1%|          | 27/4000 [00:33<1:19:33,  1.20s/it]

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overall:   1%|          | 28/4000 [00:34<1:20:21,  1.21s/it]

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overall:   1%|          | 29/4000 [00:35<1:19:34,  1.20s/it]

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overall:   1%|          | 30/4000 [00:37<1:21:00,  1.22s/it]

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overall:   1%|          | 31/4000 [00:38<1:20:48,  1.22s/it]

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overall:   1%|          | 32/4000 [00:39<1:20:57,  1.22s/it]

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overall:   1%|          | 33/4000 [00:40<1:21:15,  1.23s/it]

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overall:   1%|          | 34/4000 [00:41<1:02:15,  1.06it/s]

train:   1%|          | 34/3515 [00:38<54:39,  1.06it/s]  
overall:   1%|          | 35/4000 [00:42<1:08:27,  1.04s/it]

train:   1%|          | 35/3515 [00:40<1:00:05,  1.04s/it]
overall:   1%|          | 36/4000 [00:43<1:12:46,  1.10s/it]

train:   1%|          | 36/3515 [00:41<1:03:51,  1.10s/it]
overall:   1%|          | 37/4000 [00:44<1:13:05,  1.11s/it]

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overall:   1%|          | 38/4000 [00:45<1:14:25,  1.13s/it]

train:   1%|          | 38/3515 [00:43<1:05:18,  1.13s/it]
overall:   1%|          | 39/4000 [00:46<1:13:34,  1.11s/it]

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overall:   1%|          | 40/4000 [00:47<1:06:13,  1.00s/it]

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overall:   1%|          | 41/4000 [00:48<1:09:24,  1.05s/it]

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overall:   1%|          | 43/4000 [00:51<1:13:34,  1.12s/it]

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overall:   1%|          | 46/4000 [00:53<53:13,  1.24it/s]  

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overall:   1%|          | 47/4000 [00:54<1:00:39,  1.09it/s]

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overall:   1%|▏         | 50/4000 [00:58<1:11:14,  1.08s/it]

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overall:   1%|▏         | 52/4000 [01:00<1:16:28,  1.16s/it]

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overall:   1%|▏         | 56/4000 [01:05<1:17:52,  1.18s/it]

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overall:   1%|▏         | 57/4000 [01:06<1:19:45,  1.21s/it]

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overall:   1%|▏         | 58/4000 [01:07<1:21:07,  1.23s/it]

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train:  10%|▉         | 337/3515 [06:24<57:14,  1.08s/it]
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overall:  11%|█▏        | 458/4000 [08:41<1:08:23,  1.16s/it]

train:  13%|█▎        | 458/3515 [08:39<59:01,  1.16s/it]
overall:  11%|█▏        | 459/4000 [08:42<1:07:58,  1.15s/it]

train:  13%|█▎        | 459/3515 [08:40<58:40,  1.15s/it]
overall:  12%|█▏        | 460/4000 [08:43<1:11:16,  1.21s/it]

train:  13%|█▎        | 460/3515 [08:41<1:01:30,  1.21s/it]
overall:  12%|█▏        | 461/4000 [08:45<1:11:13,  1.21s/it]

train:  13%|█▎        | 461/3515 [08:42<1:01:27,  1.21s/it]
overall:  12%|█▏        | 462/4000 [08:46<1:10:33,  1.20s/it]

train:  13%|█▎        | 462/3515 [08:44<1:00:53,  1.20s/it]
overall:  12%|█▏        | 463/4000 [08:47<1:11:14,  1.21s/it]

train:  13%|█▎        | 463/3515 [08:45<1:01:28,  1.21s/it]
overall:  12%|█▏        | 464/4000 [08:48<1:09:12,  1.17s/it]

train:  13%|█▎        | 464/3515 [08:46<59:43,  1.17s/it]  
overall:  12%|█▏        | 465/4000 [08:49<1:07:16,  1.14s/it]

train:  13%|█▎        | 465/3515 [08:47<58:03,  1.14s/it]
overall:  12%|█▏        | 466/4000 [08:50<1:08:08,  1.16s/it]

train:  13%|█▎        | 466/3515 [08:48<58:47,  1.16s/it]
overall:  12%|█▏        | 467/4000 [08:52<1:10:16,  1.19s/it]

train:  13%|█▎        | 467/3515 [08:49<1:00:37,  1.19s/it]
overall:  12%|█▏        | 468/4000 [08:52<59:02,  1.00s/it]  

train:  13%|█▎        | 468/3515 [08:50<50:55,  1.00s/it]  
overall:  12%|█▏        | 469/4000 [08:53<1:02:12,  1.06s/it]

train:  13%|█▎        | 469/3515 [08:51<53:40,  1.06s/it]
overall:  12%|█▏        | 470/4000 [08:55<1:05:12,  1.11s/it]

train:  13%|█▎        | 470/3515 [08:52<56:15,  1.11s/it]
overall:  12%|█▏        | 471/4000 [08:56<1:07:14,  1.14s/it]

train:  13%|█▎        | 471/3515 [08:54<58:00,  1.14s/it]
overall:  12%|█▏        | 472/4000 [08:57<1:08:19,  1.16s/it]

train:  13%|█▎        | 472/3515 [08:55<58:55,  1.16s/it]
overall:  12%|█▏        | 473/4000 [08:58<1:10:07,  1.19s/it]

train:  13%|█▎        | 473/3515 [08:56<1:00:28,  1.19s/it]
overall:  12%|█▏        | 474/4000 [08:59<56:17,  1.04it/s]  

train:  13%|█▎        | 474/3515 [08:56<48:32,  1.04it/s]  
overall:  12%|█▏        | 475/4000 [08:59<53:08,  1.11it/s]

train:  14%|█▎        | 475/3515 [08:57<45:50,  1.11it/s]
overall:  12%|█▏        | 476/4000 [09:01<59:06,  1.01s/it]

train:  14%|█▎        | 476/3515 [08:58<50:58,  1.01s/it]
overall:  12%|█▏        | 477/4000 [09:02<1:03:49,  1.09s/it]

train:  14%|█▎        | 477/3515 [09:00<55:01,  1.09s/it]
overall:  12%|█▏        | 478/4000 [09:03<1:06:17,  1.13s/it]

train:  14%|█▎        | 478/3515 [09:01<57:09,  1.13s/it]
overall:  12%|█▏        | 479/4000 [09:04<1:07:15,  1.15s/it]

train:  14%|█▎        | 479/3515 [09:02<57:59,  1.15s/it]
overall:  12%|█▏        | 480/4000 [09:05<1:04:01,  1.09s/it]

train:  14%|█▎        | 480/3515 [09:03<55:12,  1.09s/it]
overall:  12%|█▏        | 481/4000 [09:07<1:05:36,  1.12s/it]

train:  14%|█▎        | 481/3515 [09:04<56:33,  1.12s/it]
overall:  12%|█▏        | 482/4000 [09:08<1:07:35,  1.15s/it]

train:  14%|█▎        | 482/3515 [09:06<58:16,  1.15s/it]
overall:  12%|█▏        | 483/4000 [09:09<1:06:51,  1.14s/it]

train:  14%|█▎        | 483/3515 [09:07<57:38,  1.14s/it]
overall:  12%|█▏        | 484/4000 [09:10<1:10:06,  1.20s/it]

train:  14%|█▍        | 484/3515 [09:08<1:00:26,  1.20s/it]
overall:  12%|█▏        | 485/4000 [09:11<1:06:08,  1.13s/it]

train:  14%|█▍        | 485/3515 [09:09<57:00,  1.13s/it]  
overall:  12%|█▏        | 486/4000 [09:12<1:08:54,  1.18s/it]

train:  14%|█▍        | 486/3515 [09:10<59:24,  1.18s/it]
overall:  12%|█▏        | 487/4000 [09:14<1:11:02,  1.21s/it]

train:  14%|█▍        | 487/3515 [09:12<1:01:13,  1.21s/it]
overall:  12%|█▏        | 488/4000 [09:14<56:17,  1.04it/s]  

train:  14%|█▍        | 488/3515 [09:12<48:31,  1.04it/s]  
overall:  12%|█▏        | 489/4000 [09:15<55:05,  1.06it/s]

train:  14%|█▍        | 489/3515 [09:13<47:29,  1.06it/s]
overall:  12%|█▏        | 490/4000 [09:16<1:00:10,  1.03s/it]

train:  14%|█▍        | 490/3515 [09:14<51:51,  1.03s/it]
overall:  12%|█▏        | 491/4000 [09:17<1:02:07,  1.06s/it]

train:  14%|█▍        | 491/3515 [09:15<53:32,  1.06s/it]
overall:  12%|█▏        | 492/4000 [09:18<53:00,  1.10it/s]  

train:  14%|█▍        | 492/3515 [09:16<45:40,  1.10it/s]
overall:  12%|█▏        | 493/4000 [09:19<57:41,  1.01it/s]

train:  14%|█▍        | 493/3515 [09:17<49:42,  1.01it/s]
overall:  12%|█▏        | 494/4000 [09:20<1:02:17,  1.07s/it]

train:  14%|█▍        | 494/3515 [09:18<53:40,  1.07s/it]
overall:  12%|█▏        | 495/4000 [09:22<1:04:07,  1.10s/it]

train:  14%|█▍        | 495/3515 [09:19<55:15,  1.10s/it]
overall:  12%|█▏        | 496/4000 [09:23<1:04:50,  1.11s/it]

train:  14%|█▍        | 496/3515 [09:20<55:52,  1.11s/it]
overall:  12%|█▏        | 497/4000 [09:24<1:06:29,  1.14s/it]

train:  14%|█▍        | 497/3515 [09:22<57:17,  1.14s/it]
overall:  12%|█▏        | 498/4000 [09:25<1:06:54,  1.15s/it]

train:  14%|█▍        | 498/3515 [09:23<57:38,  1.15s/it]
overall:  12%|█▏        | 499/4000 [09:26<1:04:29,  1.11s/it]

train:  14%|█▍        | 499/3515 [09:24<55:33,  1.11s/it]
overall:  12%|█▎        | 500/4000 [09:27<55:29,  1.05it/s]  

train:  14%|█▍        | 500/3515 [09:24<47:47,  1.05it/s]
overall:  13%|█▎        | 501/4000 [09:28<1:00:30,  1.04s/it]

train:  14%|█▍        | 501/3515 [09:26<52:07,  1.04s/it]
overall:  13%|█▎        | 502/4000 [09:29<1:03:40,  1.09s/it]

train:  14%|█▍        | 502/3515 [09:27<54:50,  1.09s/it]
overall:  13%|█▎        | 503/4000 [09:30<1:06:22,  1.14s/it]

train:  14%|█▍        | 503/3515 [09:28<57:10,  1.14s/it]
overall:  13%|█▎        | 504/4000 [09:32<1:07:46,  1.16s/it]

train:  14%|█▍        | 504/3515 [09:29<58:21,  1.16s/it]
overall:  13%|█▎        | 505/4000 [09:33<1:11:53,  1.23s/it]

train:  14%|█▍        | 505/3515 [09:31<1:01:54,  1.23s/it]
overall:  13%|█▎        | 506/4000 [09:34<1:07:56,  1.17s/it]

train:  14%|█▍        | 506/3515 [09:32<58:30,  1.17s/it]  
overall:  13%|█▎        | 507/4000 [09:35<1:08:43,  1.18s/it]

train:  14%|█▍        | 507/3515 [09:33<59:11,  1.18s/it]
overall:  13%|█▎        | 508/4000 [09:37<1:12:36,  1.25s/it]

train:  14%|█▍        | 508/3515 [09:34<1:02:31,  1.25s/it]
overall:  13%|█▎        | 509/4000 [09:38<1:13:16,  1.26s/it]

train:  14%|█▍        | 509/3515 [09:36<1:03:05,  1.26s/it]
overall:  13%|█▎        | 510/4000 [09:39<1:12:50,  1.25s/it]

train:  15%|█▍        | 510/3515 [09:37<1:02:42,  1.25s/it]
overall:  13%|█▎        | 511/4000 [09:40<1:10:57,  1.22s/it]

train:  15%|█▍        | 511/3515 [09:38<1:01:05,  1.22s/it]
overall:  13%|█▎        | 512/4000 [09:41<1:09:36,  1.20s/it]

train:  15%|█▍        | 512/3515 [09:39<59:55,  1.20s/it]  
overall:  13%|█▎        | 513/4000 [09:43<1:09:31,  1.20s/it]

train:  15%|█▍        | 513/3515 [09:40<59:51,  1.20s/it]
overall:  13%|█▎        | 514/4000 [09:44<1:08:05,  1.17s/it]

train:  15%|█▍        | 514/3515 [09:42<58:37,  1.17s/it]
overall:  13%|█▎        | 515/4000 [09:45<1:06:40,  1.15s/it]

train:  15%|█▍        | 515/3515 [09:43<57:23,  1.15s/it]
overall:  13%|█▎        | 516/4000 [09:46<1:09:00,  1.19s/it]

train:  15%|█▍        | 516/3515 [09:44<59:24,  1.19s/it]
overall:  13%|█▎        | 517/4000 [09:47<1:08:40,  1.18s/it]

train:  15%|█▍        | 517/3515 [09:45<59:07,  1.18s/it]
overall:  13%|█▎        | 518/4000 [09:48<59:17,  1.02s/it]  

train:  15%|█▍        | 518/3515 [09:46<51:02,  1.02s/it]
overall:  13%|█▎        | 519/4000 [09:49<1:04:05,  1.10s/it]

train:  15%|█▍        | 519/3515 [09:47<55:09,  1.10s/it]
overall:  13%|█▎        | 520/4000 [09:50<1:05:31,  1.13s/it]

train:  15%|█▍        | 520/3515 [09:48<56:23,  1.13s/it]
overall:  13%|█▎        | 521/4000 [09:52<1:07:31,  1.16s/it]

train:  15%|█▍        | 521/3515 [09:49<58:06,  1.16s/it]
overall:  13%|█▎        | 522/4000 [09:53<1:08:35,  1.18s/it]

train:  15%|█▍        | 522/3515 [09:51<59:01,  1.18s/it]
overall:  13%|█▎        | 523/4000 [09:54<1:09:37,  1.20s/it]

train:  15%|█▍        | 523/3515 [09:52<59:54,  1.20s/it]
overall:  13%|█▎        | 524/4000 [09:55<1:10:04,  1.21s/it]

train:  15%|█▍        | 524/3515 [09:53<1:00:17,  1.21s/it]
overall:  13%|█▎        | 525/4000 [09:57<1:11:16,  1.23s/it]

train:  15%|█▍        | 525/3515 [09:54<1:01:19,  1.23s/it]
overall:  13%|█▎        | 526/4000 [09:58<1:11:54,  1.24s/it]

train:  15%|█▍        | 526/3515 [09:56<1:01:52,  1.24s/it]
overall:  13%|█▎        | 527/4000 [09:59<1:11:18,  1.23s/it]

train:  15%|█▍        | 527/3515 [09:57<1:01:20,  1.23s/it]
overall:  13%|█▎        | 528/4000 [09:59<53:53,  1.07it/s]  

train:  15%|█▌        | 528/3515 [09:57<46:21,  1.07it/s]  
overall:  13%|█▎        | 529/4000 [10:01<1:00:26,  1.04s/it]

train:  15%|█▌        | 529/3515 [09:58<52:00,  1.04s/it]
overall:  13%|█▎        | 530/4000 [10:02<1:03:57,  1.11s/it]

train:  15%|█▌        | 530/3515 [10:00<55:01,  1.11s/it]
overall:  13%|█▎        | 531/4000 [10:02<54:53,  1.05it/s]  

train:  15%|█▌        | 531/3515 [10:00<47:12,  1.05it/s]
overall:  13%|█▎        | 532/4000 [10:04<1:02:05,  1.07s/it]

train:  15%|█▌        | 532/3515 [10:02<53:24,  1.07s/it]
overall:  13%|█▎        | 533/4000 [10:05<1:03:59,  1.11s/it]

train:  15%|█▌        | 533/3515 [10:03<55:02,  1.11s/it]
overall:  13%|█▎        | 534/4000 [10:06<56:10,  1.03it/s]  

train:  15%|█▌        | 534/3515 [10:03<48:18,  1.03it/s]
overall:  13%|█▎        | 535/4000 [10:07<1:00:30,  1.05s/it]

train:  15%|█▌        | 535/3515 [10:05<52:02,  1.05s/it]
overall:  13%|█▎        | 536/4000 [10:08<1:02:21,  1.08s/it]

train:  15%|█▌        | 536/3515 [10:06<53:37,  1.08s/it]
overall:  13%|█▎        | 537/4000 [10:09<1:05:53,  1.14s/it]

train:  15%|█▌        | 537/3515 [10:07<56:39,  1.14s/it]
overall:  13%|█▎        | 538/4000 [10:11<1:08:20,  1.18s/it]

train:  15%|█▌        | 538/3515 [10:08<58:46,  1.18s/it]
overall:  13%|█▎        | 539/4000 [10:11<1:00:59,  1.06s/it]

train:  15%|█▌        | 539/3515 [10:09<52:26,  1.06s/it]
overall:  14%|█▎        | 540/4000 [10:12<52:22,  1.10it/s]  

train:  15%|█▌        | 540/3515 [10:10<45:02,  1.10it/s]
overall:  14%|█▎        | 541/4000 [10:13<59:08,  1.03s/it]

train:  15%|█▌        | 541/3515 [10:11<50:50,  1.03s/it]
overall:  14%|█▎        | 542/4000 [10:15<1:03:59,  1.11s/it]

train:  15%|█▌        | 542/3515 [10:12<55:01,  1.11s/it]
overall:  14%|█▎        | 543/4000 [10:16<1:06:07,  1.15s/it]

train:  15%|█▌        | 543/3515 [10:14<56:50,  1.15s/it]
overall:  14%|█▎        | 544/4000 [10:17<1:05:58,  1.15s/it]

train:  15%|█▌        | 544/3515 [10:15<56:43,  1.15s/it]
overall:  14%|█▎        | 545/4000 [10:18<1:07:21,  1.17s/it]

train:  16%|█▌        | 545/3515 [10:16<57:54,  1.17s/it]
overall:  14%|█▎        | 546/4000 [10:19<1:07:05,  1.17s/it]

train:  16%|█▌        | 546/3515 [10:17<57:40,  1.17s/it]
overall:  14%|█▎        | 547/4000 [10:21<1:08:24,  1.19s/it]

train:  16%|█▌        | 547/3515 [10:18<58:47,  1.19s/it]
overall:  14%|█▎        | 548/4000 [10:22<1:07:46,  1.18s/it]

train:  16%|█▌        | 548/3515 [10:20<58:15,  1.18s/it]
overall:  14%|█▎        | 549/4000 [10:23<1:09:30,  1.21s/it]

train:  16%|█▌        | 549/3515 [10:21<59:44,  1.21s/it]
overall:  14%|█▍        | 550/4000 [10:24<1:10:03,  1.22s/it]

train:  16%|█▌        | 550/3515 [10:22<1:00:12,  1.22s/it]
overall:  14%|█▍        | 551/4000 [10:26<1:12:54,  1.27s/it]

train:  16%|█▌        | 551/3515 [10:23<1:02:39,  1.27s/it]
overall:  14%|█▍        | 552/4000 [10:26<1:04:06,  1.12s/it]

train:  16%|█▌        | 552/3515 [10:24<55:05,  1.12s/it]  
overall:  14%|█▍        | 553/4000 [10:27<1:03:37,  1.11s/it]

train:  16%|█▌        | 553/3515 [10:25<54:40,  1.11s/it]
overall:  14%|█▍        | 554/4000 [10:29<1:05:58,  1.15s/it]

train:  16%|█▌        | 554/3515 [10:27<56:41,  1.15s/it]
overall:  14%|█▍        | 555/4000 [10:29<52:44,  1.09it/s]  

train:  16%|█▌        | 555/3515 [10:27<45:18,  1.09it/s]
overall:  14%|█▍        | 556/4000 [10:30<58:05,  1.01s/it]

train:  16%|█▌        | 556/3515 [10:28<49:54,  1.01s/it]
overall:  14%|█▍        | 557/4000 [10:32<1:02:10,  1.08s/it]

train:  16%|█▌        | 557/3515 [10:29<53:24,  1.08s/it]
overall:  14%|█▍        | 558/4000 [10:33<1:04:21,  1.12s/it]

train:  16%|█▌        | 558/3515 [10:31<55:17,  1.12s/it]
overall:  14%|█▍        | 559/4000 [10:34<1:06:17,  1.16s/it]

train:  16%|█▌        | 559/3515 [10:32<56:57,  1.16s/it]
overall:  14%|█▍        | 560/4000 [10:35<1:03:42,  1.11s/it]

train:  16%|█▌        | 560/3515 [10:33<54:43,  1.11s/it]
overall:  14%|█▍        | 561/4000 [10:36<1:04:36,  1.13s/it]

train:  16%|█▌        | 561/3515 [10:34<55:29,  1.13s/it]
overall:  14%|█▍        | 562/4000 [10:37<1:00:23,  1.05s/it]

train:  16%|█▌        | 562/3515 [10:35<51:52,  1.05s/it]
overall:  14%|█▍        | 563/4000 [10:38<1:03:30,  1.11s/it]

train:  16%|█▌        | 563/3515 [10:36<54:32,  1.11s/it]
overall:  14%|█▍        | 564/4000 [10:40<1:06:45,  1.17s/it]

train:  16%|█▌        | 564/3515 [10:37<57:20,  1.17s/it]
overall:  14%|█▍        | 565/4000 [10:40<54:10,  1.06it/s]  

train:  16%|█▌        | 565/3515 [10:38<46:31,  1.06it/s]
overall:  14%|█▍        | 566/4000 [10:41<1:01:32,  1.08s/it]

train:  16%|█▌        | 566/3515 [10:39<52:51,  1.08s/it]
overall:  14%|█▍        | 567/4000 [10:43<1:04:11,  1.12s/it]

train:  16%|█▌        | 567/3515 [10:40<55:07,  1.12s/it]
overall:  14%|█▍        | 568/4000 [10:43<49:54,  1.15it/s]  

train:  16%|█▌        | 568/3515 [10:41<42:51,  1.15it/s]
overall:  14%|█▍        | 569/4000 [10:44<56:04,  1.02it/s]

train:  16%|█▌        | 569/3515 [10:42<48:08,  1.02it/s]
overall:  14%|█▍        | 570/4000 [10:45<1:00:18,  1.05s/it]

train:  16%|█▌        | 570/3515 [10:43<51:46,  1.05s/it]
overall:  14%|█▍        | 571/4000 [10:47<1:04:20,  1.13s/it]

train:  16%|█▌        | 571/3515 [10:44<55:14,  1.13s/it]
overall:  14%|█▍        | 572/4000 [10:48<1:06:05,  1.16s/it]

train:  16%|█▋        | 572/3515 [10:46<56:44,  1.16s/it]
overall:  14%|█▍        | 573/4000 [10:49<1:08:54,  1.21s/it]

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overall:  14%|█▍        | 575/4000 [10:52<1:13:31,  1.29s/it]

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overall:  14%|█▍        | 577/4000 [10:54<1:09:32,  1.22s/it]

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overall:  14%|█▍        | 578/4000 [10:55<1:09:36,  1.22s/it]

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overall:  14%|█▍        | 579/4000 [10:56<59:37,  1.05s/it]  

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overall:  15%|█▍        | 581/4000 [10:58<1:02:16,  1.09s/it]

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overall:  15%|█▍        | 597/4000 [11:17<58:01,  1.02s/it]  

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overall:  15%|█▌        | 603/4000 [11:23<1:02:53,  1.11s/it]

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overall:  15%|█▌        | 605/4000 [11:26<1:07:01,  1.18s/it]

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overall:  15%|█▌        | 607/4000 [11:28<1:00:01,  1.06s/it]

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overall:  15%|█▌        | 608/4000 [11:29<1:02:45,  1.11s/it]

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overall:  15%|█▌        | 609/4000 [11:30<1:03:22,  1.12s/it]

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overall:  15%|█▌        | 610/4000 [11:31<1:05:08,  1.15s/it]

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overall:  15%|█▌        | 611/4000 [11:32<53:16,  1.06it/s]  

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overall:  15%|█▌        | 612/4000 [11:33<47:51,  1.18it/s]

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overall:  15%|█▌        | 613/4000 [11:34<54:06,  1.04it/s]

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overall:  15%|█▌        | 614/4000 [11:35<1:01:22,  1.09s/it]

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overall:  15%|█▌        | 615/4000 [11:36<1:03:30,  1.13s/it]

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overall:  15%|█▌        | 616/4000 [11:38<1:03:37,  1.13s/it]

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overall:  15%|█▌        | 617/4000 [11:39<1:06:17,  1.18s/it]

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overall:  15%|█▌        | 618/4000 [11:40<1:07:02,  1.19s/it]

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overall:  15%|█▌        | 619/4000 [11:41<1:06:54,  1.19s/it]

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overall:  16%|█▌        | 620/4000 [11:42<1:07:30,  1.20s/it]

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overall:  16%|█▌        | 621/4000 [11:44<1:08:06,  1.21s/it]

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overall:  16%|█▌        | 623/4000 [11:46<1:11:46,  1.28s/it]

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overall:  16%|█▌        | 624/4000 [11:48<1:10:56,  1.26s/it]

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overall:  16%|█▌        | 625/4000 [11:49<1:08:35,  1.22s/it]

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overall:  16%|█▌        | 626/4000 [11:50<1:07:51,  1.21s/it]

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overall:  16%|█▌        | 627/4000 [11:51<1:07:55,  1.21s/it]

train:  18%|█▊        | 627/3515 [11:49<58:09,  1.21s/it]
overall:  16%|█▌        | 628/4000 [11:52<1:08:43,  1.22s/it]

train:  18%|█▊        | 628/3515 [11:50<58:50,  1.22s/it]
overall:  16%|█▌        | 629/4000 [11:54<1:09:01,  1.23s/it]

train:  18%|█▊        | 629/3515 [11:51<59:05,  1.23s/it]
overall:  16%|█▌        | 630/4000 [11:55<1:04:39,  1.15s/it]

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overall:  16%|█▌        | 631/4000 [11:56<1:04:47,  1.15s/it]

train:  18%|█▊        | 631/3515 [11:53<55:27,  1.15s/it]
overall:  16%|█▌        | 632/4000 [11:57<1:05:00,  1.16s/it]

train:  18%|█▊        | 632/3515 [11:55<55:39,  1.16s/it]
overall:  16%|█▌        | 633/4000 [11:58<1:07:07,  1.20s/it]

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overall:  16%|█▌        | 634/4000 [11:59<1:08:30,  1.22s/it]

train:  18%|█▊        | 634/3515 [11:57<58:38,  1.22s/it]
overall:  16%|█▌        | 635/4000 [12:00<54:50,  1.02it/s]  

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overall:  16%|█▌        | 636/4000 [12:01<56:44,  1.01s/it]

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overall:  16%|█▌        | 637/4000 [12:02<1:00:27,  1.08s/it]

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overall:  16%|█▌        | 638/4000 [12:03<50:14,  1.12it/s]  

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overall:  16%|█▌        | 639/4000 [12:04<56:49,  1.01s/it]

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overall:  16%|█▌        | 640/4000 [12:05<56:46,  1.01s/it]

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overall:  16%|█▌        | 641/4000 [12:06<59:47,  1.07s/it]

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overall:  16%|█▌        | 642/4000 [12:07<1:01:26,  1.10s/it]

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overall:  16%|█▌        | 644/4000 [12:10<1:05:20,  1.17s/it]

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overall:  16%|█▌        | 645/4000 [12:10<56:36,  1.01s/it]  

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overall:  16%|█▌        | 646/4000 [12:12<1:00:12,  1.08s/it]

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overall:  16%|█▌        | 647/4000 [12:13<1:03:08,  1.13s/it]

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overall:  16%|█▌        | 648/4000 [12:14<1:04:07,  1.15s/it]

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overall:  16%|█▌        | 649/4000 [12:15<1:05:34,  1.17s/it]

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overall:  16%|█▋        | 650/4000 [12:16<1:03:05,  1.13s/it]

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overall:  16%|█▋        | 651/4000 [12:18<1:05:29,  1.17s/it]

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overall:  16%|█▋        | 652/4000 [12:19<1:08:13,  1.22s/it]

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overall:  16%|█▋        | 654/4000 [12:21<1:09:11,  1.24s/it]

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overall:  16%|█▋        | 655/4000 [12:22<1:04:08,  1.15s/it]

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overall:  16%|█▋        | 656/4000 [12:24<1:05:28,  1.17s/it]

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overall:  16%|█▋        | 657/4000 [12:25<1:05:01,  1.17s/it]

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overall:  16%|█▋        | 658/4000 [12:26<1:03:25,  1.14s/it]

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overall:  16%|█▋        | 659/4000 [12:26<54:04,  1.03it/s]  

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overall:  16%|█▋        | 660/4000 [12:28<59:48,  1.07s/it]

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overall:  17%|█▋        | 661/4000 [12:29<1:03:11,  1.14s/it]

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overall:  17%|█▋        | 662/4000 [12:30<1:03:56,  1.15s/it]

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overall:  17%|█▋        | 663/4000 [12:31<1:03:45,  1.15s/it]

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overall:  17%|█▋        | 665/4000 [12:34<1:05:01,  1.17s/it]

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overall:  17%|█▋        | 667/4000 [12:36<1:02:23,  1.12s/it]

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overall:  17%|█▋        | 668/4000 [12:37<1:03:12,  1.14s/it]

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overall:  17%|█▋        | 669/4000 [12:38<1:00:23,  1.09s/it]

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overall:  17%|█▋        | 670/4000 [12:39<52:01,  1.07it/s]  

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overall:  17%|█▋        | 672/4000 [12:41<53:54,  1.03it/s]

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overall:  17%|█▋        | 673/4000 [12:42<58:59,  1.06s/it]

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overall:  17%|█▋        | 679/4000 [12:48<1:05:59,  1.19s/it]

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overall:  17%|█▋        | 686/4000 [12:57<1:06:11,  1.20s/it]

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train:  28%|██▊       | 999/3515 [18:49<50:57,  1.22s/it]train loss: 303.31488037109375
train per: 1.117486474413064
train loss: 241.372802734375
train per: 1.053308777780543
train loss: 62.061866760253906
train per: 0.9863993910175083
train loss: 45.661441802978516
train per: 0.9560930557635665
train loss: 38.56212615966797
train per: 1.0477601139729993
train loss: 30.43500328063965
train per: 1.0031975367124586
train loss: 28.942829132080078
train per: 0.981348320797862
train loss: 24.160804748535156
train per: 1.0180756457975795
train loss: 31.57489013671875
train per: 1.0322027801874616
train loss: 23.819164276123047
train per: 1.0575836142079336
train loss: 25.34316635131836
train per: 1.0087231057062676
train loss: 20.256589889526367
train per: 0.9764599819693479
train loss: 20.16159439086914
train per: 0.9705229466728615
train loss: 21.26446533203125
train per: 0.9937298207851761
train loss: 17.326818466186523
train per: 0.9419047385099119
train loss: 17.502685546875
train per: 0.945582366466686
train loss: 22.787954330444336
train per: 1.0736658932714618
train loss: 20.100061416625977
train per: 0.9153292051055225
train loss: 20.341320037841797
train per: 0.9750350989151244
train loss: 16.51902198791504
train per: 0.986888894264496
train loss: 19.346454620361328
train per: 1.002923904155413
train loss: 18.184770584106445
train per: 0.9347773312113937
train loss: 15.956652641296387
train per: 0.9399776092819704
train loss: 17.254329681396484
train per: 1.016493186503746
train loss: 16.327457427978516
train per: 0.971554529232707
train loss: 16.294618606567383
train per: 0.9583967054308913
train loss: 14.937487602233887
train per: 1.0674662314006576
train loss: 15.052729606628418
train per: 0.9547016252832672
train loss: 15.609415054321289
train per: 0.8992544882848159
train loss: 15.063142776489258
train per: 1.047284761570476
train loss: 14.509737968444824
train per: 0.9831233237184352
train loss: 14.73144245147705
train per: 0.9617554545908433
train loss: 16.79488754272461
train per: 0.9950044514788802
train loss: 16.88132095336914
train per: 0.9851216333622936
train loss: 15.584222793579102
train per: 0.9629129342622873
train loss: 15.214475631713867
train per: 0.9680933450358821
train loss: 13.389886856079102
train per: 0.967065791167761
train loss: 15.5114164352417
train per: 0.9947273197208581
train loss: 15.778200149536133
train per: 1.0242725690126835
train loss: 16.322330474853516
train per: 0.9287342796205045
train loss: 14.304712295532227
train per: 0.9375377844412739
train loss: 17.0736026763916
train per: 1.0344801906464105
train loss: 16.053571701049805
train per: 0.9886618664671779
train loss: 14.359519958496094
train per: 1.0051706792073185
train loss: 16.50177001953125
train per: 1.0186736134781127
train loss: 18.118019104003906
train per: 0.9924214553748805
train loss: 14.734796524047852
train per: 0.9526005289211364
train loss: 15.979377746582031
train per: 0.9825040295325742
train loss: 11.328141212463379
train per: 0.9950053328477407
train loss: 14.38252067565918
train per: 0.9656138019411946
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



word -> phonemes:   0%|          | 0/2703 [00:00<?, ?it/s]


word -> phonemes:  21%|██        | 557/2703 [00:00<00:00, 5420.29it/s]


word -> phonemes:  42%|████▏     | 1130/2703 [00:00<00:00, 5595.74it/s]


word -> phonemes:  64%|██████▎   | 1717/2703 [00:00<00:00, 5716.13it/s]


word -> phonemes:  85%|████████▌ | 2304/2703 [00:00<00:00, 5775.11it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 5690.38it/s]



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overall:  25%|██▍       | 999/4000 [21:36<1:00:46,  1.22s/it]

train:  28%|██▊       | 999/3515 [21:34<50:57,  1.22s/it]
                                                             

                                                         

overall:  25%|██▍       | 999/4000 [21:36<1:00:46,  1.22s/it]

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overall:  25%|██▌       | 1001/4000 [21:37<29:30:28, 35.42s/it]

train:  28%|██▊       | 1001/3515 [21:35<24:44:09, 35.42s/it]
overall:  25%|██▌       | 1002/4000 [21:38<20:57:21, 25.16s/it]

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overall:  48%|████▊     | 1913/4000 [38:45<36:47,  1.06s/it]

train:  54%|█████▍    | 1913/3515 [38:43<28:14,  1.06s/it]
overall:  48%|████▊     | 1914/4000 [38:46<35:46,  1.03s/it]

train:  54%|█████▍    | 1914/3515 [38:44<27:27,  1.03s/it]
overall:  48%|████▊     | 1915/4000 [38:47<35:08,  1.01s/it]

train:  54%|█████▍    | 1915/3515 [38:45<26:58,  1.01s/it]
overall:  48%|████▊     | 1916/4000 [38:48<27:41,  1.25it/s]

train:  55%|█████▍    | 1916/3515 [38:45<21:14,  1.25it/s]
overall:  48%|████▊     | 1917/4000 [38:49<31:58,  1.09it/s]

train:  55%|█████▍    | 1917/3515 [38:47<24:31,  1.09it/s]
overall:  48%|████▊     | 1918/4000 [38:50<35:05,  1.01s/it]

train:  55%|█████▍    | 1918/3515 [38:48<26:55,  1.01s/it]
overall:  48%|████▊     | 1919/4000 [38:51<36:48,  1.06s/it]

train:  55%|█████▍    | 1919/3515 [38:49<28:13,  1.06s/it]
overall:  48%|████▊     | 1920/4000 [38:52<38:10,  1.10s/it]

train:  55%|█████▍    | 1920/3515 [38:50<29:16,  1.10s/it]
overall:  48%|████▊     | 1921/4000 [38:54<39:21,  1.14s/it]

train:  55%|█████▍    | 1921/3515 [38:51<30:10,  1.14s/it]
overall:  48%|████▊     | 1922/4000 [38:55<42:52,  1.24s/it]

train:  55%|█████▍    | 1922/3515 [38:53<32:51,  1.24s/it]
overall:  48%|████▊     | 1923/4000 [38:56<43:13,  1.25s/it]

train:  55%|█████▍    | 1923/3515 [38:54<33:08,  1.25s/it]
overall:  48%|████▊     | 1924/4000 [38:58<42:48,  1.24s/it]

train:  55%|█████▍    | 1924/3515 [38:55<32:48,  1.24s/it]
overall:  48%|████▊     | 1925/4000 [38:59<43:12,  1.25s/it]

train:  55%|█████▍    | 1925/3515 [38:57<33:06,  1.25s/it]
overall:  48%|████▊     | 1926/4000 [39:00<43:18,  1.25s/it]

train:  55%|█████▍    | 1926/3515 [38:58<33:10,  1.25s/it]
overall:  48%|████▊     | 1927/4000 [39:00<33:16,  1.04it/s]

train:  55%|█████▍    | 1927/3515 [38:58<25:29,  1.04it/s]
overall:  48%|████▊     | 1928/4000 [39:02<36:17,  1.05s/it]

train:  55%|█████▍    | 1928/3515 [38:59<27:47,  1.05s/it]
overall:  48%|████▊     | 1929/4000 [39:03<37:18,  1.08s/it]

train:  55%|█████▍    | 1929/3515 [39:01<28:34,  1.08s/it]
overall:  48%|████▊     | 1930/4000 [39:04<38:33,  1.12s/it]

train:  55%|█████▍    | 1930/3515 [39:02<29:31,  1.12s/it]
overall:  48%|████▊     | 1931/4000 [39:05<39:03,  1.13s/it]

train:  55%|█████▍    | 1931/3515 [39:03<29:54,  1.13s/it]
overall:  48%|████▊     | 1932/4000 [39:06<40:02,  1.16s/it]

train:  55%|█████▍    | 1932/3515 [39:04<30:39,  1.16s/it]
overall:  48%|████▊     | 1933/4000 [39:08<39:33,  1.15s/it]

train:  55%|█████▍    | 1933/3515 [39:05<30:16,  1.15s/it]
overall:  48%|████▊     | 1934/4000 [39:09<40:04,  1.16s/it]

train:  55%|█████▌    | 1934/3515 [39:07<30:39,  1.16s/it]
overall:  48%|████▊     | 1935/4000 [39:10<41:16,  1.20s/it]

train:  55%|█████▌    | 1935/3515 [39:08<31:34,  1.20s/it]
overall:  48%|████▊     | 1936/4000 [39:11<41:32,  1.21s/it]

train:  55%|█████▌    | 1936/3515 [39:09<31:46,  1.21s/it]
overall:  48%|████▊     | 1937/4000 [39:12<41:22,  1.20s/it]

train:  55%|█████▌    | 1937/3515 [39:10<31:39,  1.20s/it]
overall:  48%|████▊     | 1938/4000 [39:14<41:25,  1.21s/it]

train:  55%|█████▌    | 1938/3515 [39:11<31:41,  1.21s/it]
overall:  48%|████▊     | 1939/4000 [39:15<41:22,  1.20s/it]

train:  55%|█████▌    | 1939/3515 [39:13<31:38,  1.20s/it]
overall:  48%|████▊     | 1940/4000 [39:16<40:06,  1.17s/it]

train:  55%|█████▌    | 1940/3515 [39:14<30:40,  1.17s/it]
overall:  49%|████▊     | 1941/4000 [39:17<40:17,  1.17s/it]

train:  55%|█████▌    | 1941/3515 [39:15<30:48,  1.17s/it]
overall:  49%|████▊     | 1942/4000 [39:18<40:49,  1.19s/it]

train:  55%|█████▌    | 1942/3515 [39:16<31:11,  1.19s/it]
overall:  49%|████▊     | 1943/4000 [39:20<40:54,  1.19s/it]

train:  55%|█████▌    | 1943/3515 [39:17<31:15,  1.19s/it]
overall:  49%|████▊     | 1944/4000 [39:21<40:18,  1.18s/it]

train:  55%|█████▌    | 1944/3515 [39:19<30:47,  1.18s/it]
overall:  49%|████▊     | 1945/4000 [39:22<40:43,  1.19s/it]

train:  55%|█████▌    | 1945/3515 [39:20<31:06,  1.19s/it]
overall:  49%|████▊     | 1946/4000 [39:24<45:26,  1.33s/it]

train:  55%|█████▌    | 1946/3515 [39:21<34:42,  1.33s/it]
overall:  49%|████▊     | 1947/4000 [39:25<44:29,  1.30s/it]

train:  55%|█████▌    | 1947/3515 [39:23<33:58,  1.30s/it]
overall:  49%|████▊     | 1948/4000 [39:26<40:10,  1.17s/it]

train:  55%|█████▌    | 1948/3515 [39:23<30:41,  1.17s/it]
overall:  49%|████▊     | 1949/4000 [39:27<39:46,  1.16s/it]

train:  55%|█████▌    | 1949/3515 [39:25<30:22,  1.16s/it]
overall:  49%|████▉     | 1950/4000 [39:28<40:56,  1.20s/it]

train:  55%|█████▌    | 1950/3515 [39:26<31:15,  1.20s/it]
overall:  49%|████▉     | 1951/4000 [39:29<41:07,  1.20s/it]

train:  56%|█████▌    | 1951/3515 [39:27<31:23,  1.20s/it]
overall:  49%|████▉     | 1952/4000 [39:30<38:30,  1.13s/it]

train:  56%|█████▌    | 1952/3515 [39:28<29:23,  1.13s/it]
overall:  49%|████▉     | 1953/4000 [39:32<40:01,  1.17s/it]

train:  56%|█████▌    | 1953/3515 [39:29<30:32,  1.17s/it]
overall:  49%|████▉     | 1954/4000 [39:33<40:30,  1.19s/it]

train:  56%|█████▌    | 1954/3515 [39:31<30:54,  1.19s/it]
overall:  49%|████▉     | 1955/4000 [39:34<39:49,  1.17s/it]

train:  56%|█████▌    | 1955/3515 [39:32<30:22,  1.17s/it]
overall:  49%|████▉     | 1956/4000 [39:35<39:27,  1.16s/it]

train:  56%|█████▌    | 1956/3515 [39:33<30:05,  1.16s/it]
overall:  49%|████▉     | 1957/4000 [39:36<39:37,  1.16s/it]

train:  56%|█████▌    | 1957/3515 [39:34<30:12,  1.16s/it]
overall:  49%|████▉     | 1958/4000 [39:37<39:57,  1.17s/it]

train:  56%|█████▌    | 1958/3515 [39:35<30:27,  1.17s/it]
overall:  49%|████▉     | 1959/4000 [39:39<40:22,  1.19s/it]

train:  56%|█████▌    | 1959/3515 [39:36<30:47,  1.19s/it]
overall:  49%|████▉     | 1960/4000 [39:40<41:03,  1.21s/it]

train:  56%|█████▌    | 1960/3515 [39:38<31:17,  1.21s/it]
overall:  49%|████▉     | 1961/4000 [39:41<41:56,  1.23s/it]

train:  56%|█████▌    | 1961/3515 [39:39<31:57,  1.23s/it]
overall:  49%|████▉     | 1962/4000 [39:42<42:05,  1.24s/it]

train:  56%|█████▌    | 1962/3515 [39:40<32:04,  1.24s/it]
overall:  49%|████▉     | 1963/4000 [39:44<41:12,  1.21s/it]

train:  56%|█████▌    | 1963/3515 [39:41<31:23,  1.21s/it]
overall:  49%|████▉     | 1964/4000 [39:45<41:26,  1.22s/it]

train:  56%|█████▌    | 1964/3515 [39:43<31:34,  1.22s/it]
overall:  49%|████▉     | 1965/4000 [39:46<38:33,  1.14s/it]

train:  56%|█████▌    | 1965/3515 [39:44<29:22,  1.14s/it]
overall:  49%|████▉     | 1966/4000 [39:47<39:44,  1.17s/it]

train:  56%|█████▌    | 1966/3515 [39:45<30:16,  1.17s/it]
overall:  49%|████▉     | 1967/4000 [39:48<39:19,  1.16s/it]

train:  56%|█████▌    | 1967/3515 [39:46<29:56,  1.16s/it]
overall:  49%|████▉     | 1968/4000 [39:49<32:43,  1.04it/s]

train:  56%|█████▌    | 1968/3515 [39:46<24:54,  1.04it/s]
overall:  49%|████▉     | 1969/4000 [39:50<34:37,  1.02s/it]

train:  56%|█████▌    | 1969/3515 [39:48<26:21,  1.02s/it]
overall:  49%|████▉     | 1970/4000 [39:51<40:44,  1.20s/it]

train:  56%|█████▌    | 1970/3515 [39:49<31:00,  1.20s/it]
overall:  49%|████▉     | 1971/4000 [39:53<40:32,  1.20s/it]

train:  56%|█████▌    | 1971/3515 [39:50<30:51,  1.20s/it]
overall:  49%|████▉     | 1972/4000 [39:54<40:46,  1.21s/it]

train:  56%|█████▌    | 1972/3515 [39:52<31:01,  1.21s/it]
overall:  49%|████▉     | 1973/4000 [39:55<41:26,  1.23s/it]

train:  56%|█████▌    | 1973/3515 [39:53<31:31,  1.23s/it]
overall:  49%|████▉     | 1974/4000 [39:56<41:19,  1.22s/it]

train:  56%|█████▌    | 1974/3515 [39:54<31:25,  1.22s/it]
overall:  49%|████▉     | 1975/4000 [39:57<33:17,  1.01it/s]

train:  56%|█████▌    | 1975/3515 [39:55<25:19,  1.01it/s]
overall:  49%|████▉     | 1976/4000 [39:58<35:45,  1.06s/it]

train:  56%|█████▌    | 1976/3515 [39:56<27:11,  1.06s/it]
overall:  49%|████▉     | 1977/4000 [39:59<37:27,  1.11s/it]

train:  56%|█████▌    | 1977/3515 [39:57<28:28,  1.11s/it]
overall:  49%|████▉     | 1978/4000 [40:00<37:59,  1.13s/it]

train:  56%|█████▋    | 1978/3515 [39:58<28:52,  1.13s/it]
overall:  49%|████▉     | 1979/4000 [40:02<38:52,  1.15s/it]

train:  56%|█████▋    | 1979/3515 [39:59<29:32,  1.15s/it]
overall:  50%|████▉     | 1980/4000 [40:03<38:59,  1.16s/it]

train:  56%|█████▋    | 1980/3515 [40:01<29:37,  1.16s/it]
overall:  50%|████▉     | 1981/4000 [40:04<38:04,  1.13s/it]

train:  56%|█████▋    | 1981/3515 [40:02<28:55,  1.13s/it]
overall:  50%|████▉     | 1982/4000 [40:05<39:02,  1.16s/it]

train:  56%|█████▋    | 1982/3515 [40:03<29:39,  1.16s/it]
overall:  50%|████▉     | 1983/4000 [40:06<40:18,  1.20s/it]

train:  56%|█████▋    | 1983/3515 [40:04<30:37,  1.20s/it]
overall:  50%|████▉     | 1984/4000 [40:08<41:03,  1.22s/it]

train:  56%|█████▋    | 1984/3515 [40:05<31:10,  1.22s/it]
overall:  50%|████▉     | 1985/4000 [40:09<41:04,  1.22s/it]

train:  56%|█████▋    | 1985/3515 [40:07<31:11,  1.22s/it]
overall:  50%|████▉     | 1986/4000 [40:10<41:18,  1.23s/it]

train:  57%|█████▋    | 1986/3515 [40:08<31:21,  1.23s/it]
overall:  50%|████▉     | 1987/4000 [40:11<41:07,  1.23s/it]

train:  57%|█████▋    | 1987/3515 [40:09<31:12,  1.23s/it]
overall:  50%|████▉     | 1988/4000 [40:12<40:09,  1.20s/it]

train:  57%|█████▋    | 1988/3515 [40:10<30:28,  1.20s/it]
overall:  50%|████▉     | 1989/4000 [40:14<40:05,  1.20s/it]

train:  57%|█████▋    | 1989/3515 [40:11<30:25,  1.20s/it]
overall:  50%|████▉     | 1990/4000 [40:15<39:55,  1.19s/it]

train:  57%|█████▋    | 1990/3515 [40:13<30:17,  1.19s/it]
overall:  50%|████▉     | 1991/4000 [40:16<40:00,  1.19s/it]

train:  57%|█████▋    | 1991/3515 [40:14<30:20,  1.19s/it]
overall:  50%|████▉     | 1992/4000 [40:17<40:23,  1.21s/it]

train:  57%|█████▋    | 1992/3515 [40:15<30:38,  1.21s/it]
overall:  50%|████▉     | 1993/4000 [40:19<41:03,  1.23s/it]

train:  57%|█████▋    | 1993/3515 [40:16<31:07,  1.23s/it]
overall:  50%|████▉     | 1994/4000 [40:20<43:02,  1.29s/it]

train:  57%|█████▋    | 1994/3515 [40:18<32:38,  1.29s/it]
overall:  50%|████▉     | 1995/4000 [40:21<41:34,  1.24s/it]

train:  57%|█████▋    | 1995/3515 [40:19<31:30,  1.24s/it]
overall:  50%|████▉     | 1996/4000 [40:22<40:53,  1.22s/it]

train:  57%|█████▋    | 1996/3515 [40:20<30:59,  1.22s/it]
overall:  50%|████▉     | 1997/4000 [40:24<41:28,  1.24s/it]

train:  57%|█████▋    | 1997/3515 [40:21<31:25,  1.24s/it]
overall:  50%|████▉     | 1998/4000 [40:25<41:24,  1.24s/it]

train:  57%|█████▋    | 1998/3515 [40:23<31:22,  1.24s/it]
overall:  50%|████▉     | 1999/4000 [40:26<40:49,  1.22s/it]

train:  57%|█████▋    | 1999/3515 [40:24<30:56,  1.22s/it]dev loss: 16.045307159423828
dev per: 1.1828459937565037
[Runner] - Save the checkpoint to:
1. result/downstream/grid/dev-best.ckpt
train loss: 14.040229797363281
train per: 0.9613768115942029
train loss: 16.094497680664062
train per: 0.9573760062639164
train loss: 16.124095916748047
train per: 0.9415625
train loss: 14.785360336303711
train per: 0.9559939725415783
train loss: 16.672603607177734
train per: 0.9756426952201804
train loss: 16.30428695678711
train per: 0.9596073990184976
train loss: 15.661616325378418
train per: 0.9514134275618374
train loss: 20.080480575561523
train per: 0.959397059604055
train loss: 15.769800186157227
train per: 1.0195477511803197
train loss: 18.722896575927734
train per: 0.9997287841392964
train loss: 16.899677276611328
train per: 0.9651601962950592
train loss: 20.682973861694336
train per: 1.0391781673802292
train loss: 16.706668853759766
train per: 0.9830436425467599
train loss: 16.058063507080078
train per: 0.9983185202978622
train loss: 17.890003204345703
train per: 1.048680779080422
train loss: 16.02897834777832
train per: 1.0020601565718994
train loss: 14.782422065734863
train per: 0.9864314032050924
train loss: 20.21006965637207
train per: 0.9550277278367223
train loss: 18.79443359375
train per: 1.0371092206800285
train loss: 19.152624130249023
train per: 0.9496479212887046
train loss: 13.995416641235352
train per: 1.045950864422202
train loss: 16.476238250732422
train per: 1.0259209375959926
train loss: 16.779071807861328
train per: 0.981069481498666
train loss: 16.109760284423828
train per: 0.9333265133884044
train loss: 15.786076545715332
train per: 1.1461658749594312
train loss: 16.774272918701172
train per: 0.9699674547717048
train loss: 16.69861602783203
train per: 0.9772410091250671
train loss: 16.064544677734375
train per: 0.9669465111602654
train loss: 19.100502014160156
train per: 0.9793352133512089
train loss: 20.710359573364258
train per: 1.0912566913076727
train loss: 17.57035255432129
train per: 0.9871581396409753
train loss: 17.42699432373047
train per: 0.9906411741072484
train loss: 14.672073364257812
train per: 0.9218586498486948
train loss: 14.234369277954102
train per: 0.9653640809367849
train loss: 13.236564636230469
train per: 0.9168289579600634
train loss: 14.376192092895508
train per: 0.9665578918958706
train loss: 16.264631271362305
train per: 0.9484989648033126
train loss: 17.28067970275879
train per: 0.995935571278037
train loss: 17.8723087310791
train per: 0.9787923488017798
train loss: 17.377958297729492
train per: 1.0316911050810327
train loss: 19.13535499572754
train per: 0.9840505641557415
train loss: 17.25309181213379
train per: 0.9317167847150455
train loss: 17.46614646911621
train per: 1.0744419977980182
train loss: 17.513595581054688
train per: 0.9617336408886731
train loss: 15.472921371459961
train per: 0.9989023873076059
train loss: 14.229375839233398
train per: 0.9842071197411003
train loss: 13.321009635925293
train per: 0.9532589243665819
train loss: 16.13434600830078
train per: 1.0263444423404657
train loss: 17.822311401367188
train per: 0.955859931515409
train loss: 20.218978881835938
train per: 1.077205465793469
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



word -> phonemes:   0%|          | 0/2703 [00:00<?, ?it/s]


word -> phonemes:  20%|██        | 552/2703 [00:00<00:00, 5515.85it/s]


word -> phonemes:  41%|████      | 1104/2703 [00:00<00:00, 5275.51it/s]


word -> phonemes:  64%|██████▎   | 1720/2703 [00:00<00:00, 5666.18it/s]


word -> phonemes:  86%|████████▌ | 2328/2703 [00:00<00:00, 5825.04it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 5722.66it/s]



dev:   0%|          | 0/2703 [00:00<?, ?it/s]


dev:   0%|          | 1/2703 [00:01<55:34,  1.23s/it]


dev:   0%|          | 2/2703 [00:01<28:43,  1.57it/s]


dev:   0%|          | 3/2703 [00:01<20:04,  2.24it/s]


dev:   0%|          | 4/2703 [00:01<15:49,  2.84it/s]


dev:   0%|          | 5/2703 [00:02<13:50,  3.25it/s]


dev:   0%|          | 6/2703 [00:02<12:29,  3.60it/s]


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overall:  74%|███████▍  | 2973/4000 [1:01:27<18:47,  1.10s/it]

train:  85%|████████▍ | 2973/3515 [1:01:25<09:55,  1.10s/it]
overall:  74%|███████▍  | 2974/4000 [1:01:28<19:28,  1.14s/it]

train:  85%|████████▍ | 2974/3515 [1:01:26<10:16,  1.14s/it]
overall:  74%|███████▍  | 2975/4000 [1:01:30<20:38,  1.21s/it]

train:  85%|████████▍ | 2975/3515 [1:01:27<10:52,  1.21s/it]
overall:  74%|███████▍  | 2976/4000 [1:01:30<16:39,  1.02it/s]

train:  85%|████████▍ | 2976/3515 [1:01:28<08:45,  1.02it/s]
overall:  74%|███████▍  | 2977/4000 [1:01:31<17:54,  1.05s/it]

train:  85%|████████▍ | 2977/3515 [1:01:29<09:24,  1.05s/it]
overall:  74%|███████▍  | 2978/4000 [1:01:33<18:41,  1.10s/it]

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overall:  74%|███████▍  | 2979/4000 [1:01:33<15:55,  1.07it/s]

train:  85%|████████▍ | 2979/3515 [1:01:31<08:21,  1.07it/s]
overall:  74%|███████▍  | 2980/4000 [1:01:34<14:41,  1.16it/s]

train:  85%|████████▍ | 2980/3515 [1:01:32<07:42,  1.16it/s]
overall:  75%|███████▍  | 2981/4000 [1:01:35<16:26,  1.03it/s]

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train:  85%|████████▌ | 2994/3515 [1:01:47<08:54,  1.03s/it]
overall:  75%|███████▍  | 2995/4000 [1:01:51<18:03,  1.08s/it]

train:  85%|████████▌ | 2995/3515 [1:01:48<09:20,  1.08s/it]
overall:  75%|███████▍  | 2996/4000 [1:01:52<19:01,  1.14s/it]

train:  85%|████████▌ | 2996/3515 [1:01:50<09:50,  1.14s/it]
overall:  75%|███████▍  | 2997/4000 [1:01:53<19:18,  1.16s/it]

train:  85%|████████▌ | 2997/3515 [1:01:51<09:58,  1.16s/it]
overall:  75%|███████▍  | 2998/4000 [1:01:54<19:41,  1.18s/it]

train:  85%|████████▌ | 2998/3515 [1:01:52<10:09,  1.18s/it]
overall:  75%|███████▍  | 2999/4000 [1:01:55<18:57,  1.14s/it]

train:  85%|████████▌ | 2999/3515 [1:01:53<09:46,  1.14s/it]dev loss: 20.908292770385742
dev per: 0.9210978147762747
[Runner] - Save the checkpoint to:
1. result/downstream/grid/dev-best.ckpt
train loss: 19.406604766845703
train per: 0.9827598964113947
train loss: 17.74351692199707
train per: 0.9426536456421176
train loss: 17.5385684967041
train per: 0.9841997346520324
train loss: 16.792604446411133
train per: 0.9760859694263659
train loss: 16.245651245117188
train per: 0.9659670313350824
train loss: 16.13015365600586
train per: 0.9437536028987894
train loss: 16.279460906982422
train per: 1.0132723787052058
train loss: 15.376910209655762
train per: 0.9680981029435494
train loss: 15.073591232299805
train per: 0.9583343248066627
train loss: 18.85013198852539
train per: 1.0202296455470903
train loss: 23.2014102935791
train per: 1.021968407113129
train loss: 17.34717559814453
train per: 0.9967810836015764
train loss: 14.586591720581055
train per: 0.9627158457655497
train loss: 15.922111511230469
train per: 0.9884048811318003
train loss: 19.58199119567871
train per: 1.095165097209042
train loss: 21.73771095275879
train per: 0.9618529944664805
train loss: 19.554279327392578
train per: 0.9635751682872101
train loss: 25.520742416381836
train per: 0.9700768641688176
train loss: 20.449871063232422
train per: 0.9434307822623108
train loss: 20.835708618164062
train per: 1.0362254492269118
train loss: 17.81887435913086
train per: 0.9285483750837905
train loss: 17.710468292236328
train per: 1.0385173247381145
train loss: 17.963420867919922
train per: 0.9816642488525292
train loss: 16.94938087463379
train per: 0.9760598629825316
train loss: 15.499425888061523
train per: 0.9614336252392275
train loss: 17.824626922607422
train per: 1.0419275185194423
train loss: 19.111955642700195
train per: 1.0037670973124668
train loss: 16.263086318969727
train per: 0.9259167676368042
train loss: 18.536630630493164
train per: 0.9163982635485226
train loss: 15.426950454711914
train per: 0.9808812326444352
train loss: 15.113232612609863
train per: 0.9746272189349112
train loss: 15.37177562713623
train per: 1.0612197028928851
train loss: 13.362846374511719
train per: 0.939465758159285
train loss: 14.765820503234863
train per: 0.9968469178622104
train loss: 12.99128246307373
train per: 0.9203795269277028
train loss: 12.707898139953613
train per: 0.9535076906586634
train loss: 16.586875915527344
train per: 0.9781714807858267
train loss: 16.90546226501465
train per: 0.9530609580994648
train loss: 14.172523498535156
train per: 0.9471670005650589
train loss: 14.003057479858398
train per: 0.9270666860380647
train loss: 15.692052841186523
train per: 0.9710158790893438
train loss: 15.959310531616211
train per: 1.0079804517923523
train loss: 14.584643363952637
train per: 0.9167376875597221
train loss: 14.775239944458008
train per: 1.009877143899769
train loss: 11.458260536193848
train per: 0.8928278525886928
train loss: 11.446351051330566
train per: 0.8886822397460695
train loss: 11.871800422668457
train per: 0.8895197059941706
train loss: 13.276881217956543
train per: 0.9586134303007106
train loss: 12.699785232543945
train per: 0.9507072324526288
train loss: 11.43303394317627
train per: 0.9322630981653112
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



word -> phonemes:   0%|          | 0/2703 [00:00<?, ?it/s]


word -> phonemes:  21%|██        | 563/2703 [00:00<00:00, 5622.34it/s]


word -> phonemes:  42%|████▏     | 1144/2703 [00:00<00:00, 5732.56it/s]


word -> phonemes:  64%|██████▎   | 1718/2703 [00:00<00:00, 5618.19it/s]


word -> phonemes:  85%|████████▍ | 2292/2703 [00:00<00:00, 5664.54it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 5642.83it/s]



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train: 100%|██████████| 3515/3515 [1:14:24<00:00,  1.17s/it]403-128339-0009 Failed!!!
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/home/victor/glockenspiel/s3prl/data/LibriSpeech/train-clean-100/403/128339/403-128339-0009.flac WTF Failed!!!
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train: 100%|██████████| 3515/3515 [1:14:24<00:00,  1.27s/it]
dev loss: 12.830740928649902
dev per: 1.135936524453694
train loss: 10.40711784362793
train per: 0.9281518725623796
train loss: 11.252723693847656
train per: 0.9206416209371042
train loss: 11.17955493927002
train per: 0.9110460586888265
train loss: 12.53037166595459
train per: 0.8723684537568662
train loss: 13.94251537322998
train per: 0.9738636687876281
train loss: 13.089078903198242
train per: 0.9834784667596222
train loss: 11.243976593017578
train per: 0.9626984340888877
train loss: 10.340818405151367
train per: 0.9244500192975685
train loss: 13.857065200805664
train per: 0.927836361326388
train loss: 13.084478378295898
train per: 0.9045093474765413
train loss: 13.542963981628418
train per: 0.9252754187153261
train loss: 12.963537216186523
train per: 0.9194380055820994
train loss: 12.538820266723633
train per: 0.8908435934762763
train loss: 12.399685859680176
train per: 0.8867238306276796
train loss: 13.91230583190918
train per: 0.9469143199520671
train loss: 11.20698356628418
train per: 0.8838451268357811
train loss: 12.447879791259766
train per: 0.9314404116763059
train loss: 12.32565975189209
train per: 0.9113347770449848
train loss: 11.655102729797363
train per: 0.8875249003984064
train loss: 10.971266746520996
train per: 0.8827690517742873
train loss: 11.825040817260742
train per: 0.8657461497610196
train loss: 13.990461349487305
train per: 0.909471160250433
train loss: 12.61907958984375
train per: 0.8928189969944609
train loss: 10.214366912841797
train per: 0.8790670738127829
train loss: 10.62230110168457
train per: 0.8909721419489076
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.


word -> phonemes:   0%|          | 0/3515 [00:00<?, ?it/s]

word -> phonemes:  10%|█         | 358/3515 [00:00<00:00, 3570.80it/s]

word -> phonemes:  20%|██        | 716/3515 [00:00<00:00, 3348.74it/s]

word -> phonemes:  31%|███       | 1082/3515 [00:00<00:00, 3482.92it/s]

word -> phonemes:  43%|████▎     | 1500/3515 [00:00<00:00, 3750.28it/s]

word -> phonemes:  53%|█████▎    | 1877/3515 [00:00<00:00, 3430.24it/s]

word -> phonemes:  65%|██████▌   | 2296/3515 [00:00<00:00, 3669.97it/s]

word -> phonemes:  76%|███████▌  | 2671/3515 [00:00<00:00, 3694.01it/s]

word -> phonemes:  87%|████████▋ | 3044/3515 [00:00<00:00, 3549.24it/s]

word -> phonemes:  98%|█████████▊| 3433/3515 [00:00<00:00, 3649.95it/s]
word -> phonemes: 100%|██████████| 3515/3515 [00:00<00:00, 3590.38it/s]


train:   0%|          | 0/3515 [00:00<?, ?it/s]
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overall:  88%|████████▊ | 3520/4000 [1:14:36<12:12,  1.53s/it]

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overall:  88%|████████▊ | 3522/4000 [1:14:39<10:58,  1.38s/it]

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overall:  88%|████████▊ | 3523/4000 [1:14:39<08:43,  1.10s/it]

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overall:  88%|████████▊ | 3526/4000 [1:14:43<09:23,  1.19s/it]

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overall:  88%|████████▊ | 3527/4000 [1:14:44<09:13,  1.17s/it]

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overall:  88%|████████▊ | 3528/4000 [1:14:45<09:22,  1.19s/it]

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overall:  88%|████████▊ | 3529/4000 [1:14:46<09:15,  1.18s/it]

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overall:  88%|████████▊ | 3530/4000 [1:14:48<09:25,  1.20s/it]

train:   0%|          | 15/3515 [00:19<1:09:51,  1.20s/it]
overall:  88%|████████▊ | 3531/4000 [1:14:49<09:28,  1.21s/it]

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overall:  88%|████████▊ | 3532/4000 [1:14:50<09:36,  1.23s/it]

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overall:  88%|████████▊ | 3533/4000 [1:14:51<09:38,  1.24s/it]

train:   1%|          | 18/3515 [00:22<1:12:09,  1.24s/it]
overall:  88%|████████▊ | 3534/4000 [1:14:53<09:37,  1.24s/it]

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overall:  88%|████████▊ | 3535/4000 [1:14:54<09:46,  1.26s/it]

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overall:  88%|████████▊ | 3536/4000 [1:14:55<09:46,  1.26s/it]

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overall:  88%|████████▊ | 3537/4000 [1:14:56<09:51,  1.28s/it]

train:   1%|          | 22/3515 [00:28<1:14:24,  1.28s/it]
overall:  88%|████████▊ | 3538/4000 [1:14:58<09:45,  1.27s/it]

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overall:  88%|████████▊ | 3539/4000 [1:14:59<09:47,  1.27s/it]

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overall:  88%|████████▊ | 3540/4000 [1:15:00<09:53,  1.29s/it]

train:   1%|          | 25/3515 [00:31<1:15:05,  1.29s/it]
overall:  89%|████████▊ | 3541/4000 [1:15:02<09:39,  1.26s/it]

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overall:  89%|████████▊ | 3543/4000 [1:15:04<09:22,  1.23s/it]

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overall:  89%|████████▊ | 3544/4000 [1:15:05<09:05,  1.20s/it]

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overall:  89%|████████▊ | 3545/4000 [1:15:06<09:21,  1.24s/it]

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overall:  89%|████████▊ | 3546/4000 [1:15:08<09:08,  1.21s/it]

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overall:  89%|████████▊ | 3547/4000 [1:15:08<07:22,  1.02it/s]

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overall:  89%|████████▊ | 3548/4000 [1:15:09<08:06,  1.08s/it]

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overall:  89%|████████▊ | 3549/4000 [1:15:11<08:37,  1.15s/it]

train:   1%|          | 34/3515 [00:42<1:06:36,  1.15s/it]
overall:  89%|████████▉ | 3550/4000 [1:15:12<08:44,  1.17s/it]

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overall:  89%|████████▉ | 3551/4000 [1:15:13<08:42,  1.16s/it]

train:   1%|          | 36/3515 [00:44<1:07:25,  1.16s/it]
overall:  89%|████████▉ | 3552/4000 [1:15:14<08:54,  1.19s/it]

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overall:  89%|████████▉ | 3554/4000 [1:15:17<09:14,  1.24s/it]

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overall:  89%|████████▉ | 3555/4000 [1:15:18<09:12,  1.24s/it]

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overall:  89%|████████▉ | 3556/4000 [1:15:19<09:15,  1.25s/it]

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overall:  89%|████████▉ | 3557/4000 [1:15:21<09:16,  1.26s/it]

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overall:  89%|████████▉ | 3558/4000 [1:15:22<08:44,  1.19s/it]

train:   1%|          | 43/3515 [00:53<1:08:39,  1.19s/it]
overall:  89%|████████▉ | 3559/4000 [1:15:23<08:40,  1.18s/it]

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overall:  89%|████████▉ | 3560/4000 [1:15:24<08:57,  1.22s/it]

train:   1%|▏         | 45/3515 [00:55<1:10:40,  1.22s/it]
overall:  89%|████████▉ | 3561/4000 [1:15:25<09:01,  1.23s/it]

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overall:  89%|████████▉ | 3562/4000 [1:15:26<07:41,  1.05s/it]

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overall:  89%|████████▉ | 3563/4000 [1:15:27<07:17,  1.00s/it]

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overall:  89%|████████▉ | 3564/4000 [1:15:28<07:57,  1.10s/it]

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overall:  89%|████████▉ | 3565/4000 [1:15:29<08:18,  1.15s/it]

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overall:  89%|████████▉ | 3566/4000 [1:15:31<08:24,  1.16s/it]

train:   1%|▏         | 51/3515 [01:02<1:07:06,  1.16s/it]
overall:  89%|████████▉ | 3567/4000 [1:15:32<08:39,  1.20s/it]

train:   1%|▏         | 52/3515 [01:03<1:09:14,  1.20s/it]
overall:  89%|████████▉ | 3568/4000 [1:15:33<08:32,  1.19s/it]

train:   2%|▏         | 53/3515 [01:04<1:08:30,  1.19s/it]
overall:  89%|████████▉ | 3569/4000 [1:15:34<08:43,  1.21s/it]

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overall:  89%|████████▉ | 3570/4000 [1:15:35<08:32,  1.19s/it]

train:   2%|▏         | 55/3515 [01:07<1:08:42,  1.19s/it]
overall:  89%|████████▉ | 3571/4000 [1:15:37<08:44,  1.22s/it]

train:   2%|▏         | 56/3515 [01:08<1:10:30,  1.22s/it]
overall:  89%|████████▉ | 3572/4000 [1:15:38<08:55,  1.25s/it]

train:   2%|▏         | 57/3515 [01:09<1:12:09,  1.25s/it]
overall:  89%|████████▉ | 3573/4000 [1:15:39<09:05,  1.28s/it]

train:   2%|▏         | 58/3515 [01:11<1:13:33,  1.28s/it]
overall:  89%|████████▉ | 3574/4000 [1:15:41<09:07,  1.28s/it]

train:   2%|▏         | 59/3515 [01:12<1:13:59,  1.28s/it]
overall:  89%|████████▉ | 3575/4000 [1:15:42<09:07,  1.29s/it]

train:   2%|▏         | 60/3515 [01:13<1:14:08,  1.29s/it]
overall:  89%|████████▉ | 3576/4000 [1:15:43<09:07,  1.29s/it]

train:   2%|▏         | 61/3515 [01:14<1:14:16,  1.29s/it]
overall:  89%|████████▉ | 3577/4000 [1:15:45<08:57,  1.27s/it]

train:   2%|▏         | 62/3515 [01:16<1:13:05,  1.27s/it]
overall:  89%|████████▉ | 3578/4000 [1:15:46<08:55,  1.27s/it]

train:   2%|▏         | 63/3515 [01:17<1:12:59,  1.27s/it]
overall:  89%|████████▉ | 3579/4000 [1:15:47<08:48,  1.26s/it]

train:   2%|▏         | 64/3515 [01:18<1:12:14,  1.26s/it]
overall:  90%|████████▉ | 3580/4000 [1:15:48<08:41,  1.24s/it]

train:   2%|▏         | 65/3515 [01:19<1:11:25,  1.24s/it]
overall:  90%|████████▉ | 3581/4000 [1:15:49<08:29,  1.21s/it]

train:   2%|▏         | 66/3515 [01:21<1:09:49,  1.21s/it]
overall:  90%|████████▉ | 3582/4000 [1:15:51<08:30,  1.22s/it]

train:   2%|▏         | 67/3515 [01:22<1:10:08,  1.22s/it]
overall:  90%|████████▉ | 3583/4000 [1:15:52<08:40,  1.25s/it]

train:   2%|▏         | 68/3515 [01:23<1:11:44,  1.25s/it]
overall:  90%|████████▉ | 3584/4000 [1:15:53<08:29,  1.23s/it]

train:   2%|▏         | 69/3515 [01:24<1:10:22,  1.23s/it]
overall:  90%|████████▉ | 3585/4000 [1:15:54<07:43,  1.12s/it]

train:   2%|▏         | 70/3515 [01:25<1:04:10,  1.12s/it]
overall:  90%|████████▉ | 3586/4000 [1:15:55<07:40,  1.11s/it]

train:   2%|▏         | 71/3515 [01:26<1:03:52,  1.11s/it]
overall:  90%|████████▉ | 3587/4000 [1:15:56<08:02,  1.17s/it]

train:   2%|▏         | 72/3515 [01:27<1:07:03,  1.17s/it]
overall:  90%|████████▉ | 3588/4000 [1:15:58<08:19,  1.21s/it]

train:   2%|▏         | 73/3515 [01:29<1:09:35,  1.21s/it]
overall:  90%|████████▉ | 3589/4000 [1:15:59<08:22,  1.22s/it]

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overall:  90%|████████▉ | 3590/4000 [1:16:00<08:38,  1.27s/it]

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overall:  90%|████████▉ | 3591/4000 [1:16:02<08:39,  1.27s/it]

train:   2%|▏         | 76/3515 [01:33<1:12:44,  1.27s/it]
overall:  90%|████████▉ | 3592/4000 [1:16:03<08:29,  1.25s/it]

train:   2%|▏         | 77/3515 [01:34<1:11:35,  1.25s/it]
overall:  90%|████████▉ | 3593/4000 [1:16:04<08:40,  1.28s/it]

train:   2%|▏         | 78/3515 [01:35<1:13:14,  1.28s/it]
overall:  90%|████████▉ | 3594/4000 [1:16:05<08:18,  1.23s/it]

train:   2%|▏         | 79/3515 [01:36<1:10:22,  1.23s/it]
overall:  90%|████████▉ | 3595/4000 [1:16:06<08:08,  1.21s/it]

train:   2%|▏         | 80/3515 [01:38<1:09:05,  1.21s/it]
overall:  90%|████████▉ | 3596/4000 [1:16:08<08:02,  1.19s/it]

train:   2%|▏         | 81/3515 [01:39<1:08:21,  1.19s/it]
overall:  90%|████████▉ | 3597/4000 [1:16:09<08:13,  1.22s/it]

train:   2%|▏         | 82/3515 [01:40<1:10:02,  1.22s/it]
overall:  90%|████████▉ | 3598/4000 [1:16:10<08:20,  1.25s/it]

train:   2%|▏         | 83/3515 [01:41<1:11:14,  1.25s/it]
overall:  90%|████████▉ | 3599/4000 [1:16:11<08:26,  1.26s/it]

train:   2%|▏         | 84/3515 [01:43<1:12:14,  1.26s/it]
overall:  90%|█████████ | 3600/4000 [1:16:13<08:36,  1.29s/it]

train:   2%|▏         | 85/3515 [01:44<1:13:46,  1.29s/it]
overall:  90%|█████████ | 3601/4000 [1:16:14<08:29,  1.28s/it]

train:   2%|▏         | 86/3515 [01:45<1:12:55,  1.28s/it]
overall:  90%|█████████ | 3602/4000 [1:16:15<08:21,  1.26s/it]

train:   2%|▏         | 87/3515 [01:46<1:11:59,  1.26s/it]
overall:  90%|█████████ | 3603/4000 [1:16:17<08:17,  1.25s/it]

train:   3%|▎         | 88/3515 [01:48<1:11:36,  1.25s/it]
overall:  90%|█████████ | 3604/4000 [1:16:18<08:03,  1.22s/it]

train:   3%|▎         | 89/3515 [01:49<1:09:43,  1.22s/it]
overall:  90%|█████████ | 3605/4000 [1:16:19<07:59,  1.21s/it]

train:   3%|▎         | 90/3515 [01:50<1:09:18,  1.21s/it]
overall:  90%|█████████ | 3606/4000 [1:16:20<07:52,  1.20s/it]

train:   3%|▎         | 91/3515 [01:51<1:08:22,  1.20s/it]
overall:  90%|█████████ | 3607/4000 [1:16:21<07:55,  1.21s/it]

train:   3%|▎         | 92/3515 [01:52<1:09:00,  1.21s/it]
overall:  90%|█████████ | 3608/4000 [1:16:23<08:03,  1.23s/it]

train:   3%|▎         | 93/3515 [01:54<1:10:23,  1.23s/it]
overall:  90%|█████████ | 3609/4000 [1:16:23<06:22,  1.02it/s]

train:   3%|▎         | 94/3515 [01:54<55:46,  1.02it/s]  
overall:  90%|█████████ | 3610/4000 [1:16:24<06:19,  1.03it/s]

train:   3%|▎         | 95/3515 [01:55<55:27,  1.03it/s]
overall:  90%|█████████ | 3611/4000 [1:16:25<06:40,  1.03s/it]

train:   3%|▎         | 96/3515 [01:56<58:36,  1.03s/it]
overall:  90%|█████████ | 3612/4000 [1:16:26<06:52,  1.06s/it]

train:   3%|▎         | 97/3515 [01:57<1:00:32,  1.06s/it]
overall:  90%|█████████ | 3613/4000 [1:16:27<06:55,  1.07s/it]

train:   3%|▎         | 98/3515 [01:58<1:01:11,  1.07s/it]
overall:  90%|█████████ | 3614/4000 [1:16:29<07:13,  1.12s/it]

train:   3%|▎         | 99/3515 [02:00<1:03:58,  1.12s/it]
overall:  90%|█████████ | 3615/4000 [1:16:30<07:20,  1.14s/it]

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overall:  90%|█████████ | 3616/4000 [1:16:31<07:31,  1.18s/it]

train:   3%|▎         | 101/3515 [02:02<1:06:53,  1.18s/it]
overall:  90%|█████████ | 3617/4000 [1:16:32<07:38,  1.20s/it]

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overall:  90%|█████████ | 3618/4000 [1:16:33<07:46,  1.22s/it]

train:   3%|▎         | 103/3515 [02:05<1:09:29,  1.22s/it]
overall:  90%|█████████ | 3619/4000 [1:16:34<06:37,  1.04s/it]

train:   3%|▎         | 104/3515 [02:05<59:18,  1.04s/it]  
overall:  90%|█████████ | 3620/4000 [1:16:35<05:42,  1.11it/s]

train:   3%|▎         | 105/3515 [02:06<51:13,  1.11it/s]
overall:  91%|█████████ | 3621/4000 [1:16:35<04:29,  1.40it/s]

train:   3%|▎         | 106/3515 [02:06<40:28,  1.40it/s]
overall:  91%|█████████ | 3622/4000 [1:16:36<05:25,  1.16it/s]

train:   3%|▎         | 107/3515 [02:07<48:51,  1.16it/s]
overall:  91%|█████████ | 3623/4000 [1:16:37<06:14,  1.01it/s]

train:   3%|▎         | 108/3515 [02:09<56:22,  1.01it/s]
overall:  91%|█████████ | 3624/4000 [1:16:39<06:31,  1.04s/it]

train:   3%|▎         | 109/3515 [02:10<59:08,  1.04s/it]
overall:  91%|█████████ | 3625/4000 [1:16:39<05:23,  1.16it/s]

train:   3%|▎         | 110/3515 [02:10<48:53,  1.16it/s]
overall:  91%|█████████ | 3626/4000 [1:16:40<06:15,  1.00s/it]

train:   3%|▎         | 111/3515 [02:12<56:57,  1.00s/it]
overall:  91%|█████████ | 3627/4000 [1:16:42<06:31,  1.05s/it]

train:   3%|▎         | 112/3515 [02:13<59:32,  1.05s/it]
overall:  91%|█████████ | 3628/4000 [1:16:43<06:59,  1.13s/it]

train:   3%|▎         | 113/3515 [02:14<1:03:53,  1.13s/it]
overall:  91%|█████████ | 3629/4000 [1:16:44<07:11,  1.16s/it]

train:   3%|▎         | 114/3515 [02:15<1:05:58,  1.16s/it]
overall:  91%|█████████ | 3630/4000 [1:16:44<05:33,  1.11it/s]

train:   3%|▎         | 115/3515 [02:16<51:05,  1.11it/s]  
overall:  91%|█████████ | 3631/4000 [1:16:46<06:10,  1.00s/it]

train:   3%|▎         | 116/3515 [02:17<56:49,  1.00s/it]
overall:  91%|█████████ | 3632/4000 [1:16:47<06:32,  1.07s/it]

train:   3%|▎         | 117/3515 [02:18<1:00:20,  1.07s/it]
overall:  91%|█████████ | 3633/4000 [1:16:48<06:16,  1.02s/it]

train:   3%|▎         | 118/3515 [02:19<58:01,  1.02s/it]  
overall:  91%|█████████ | 3634/4000 [1:16:49<06:33,  1.08s/it]

train:   3%|▎         | 119/3515 [02:20<1:00:54,  1.08s/it]
overall:  91%|█████████ | 3635/4000 [1:16:50<06:22,  1.05s/it]

train:   3%|▎         | 120/3515 [02:21<59:15,  1.05s/it]  
overall:  91%|█████████ | 3636/4000 [1:16:51<06:45,  1.11s/it]

train:   3%|▎         | 121/3515 [02:22<1:02:59,  1.11s/it]
overall:  91%|█████████ | 3637/4000 [1:16:52<06:33,  1.08s/it]

train:   3%|▎         | 122/3515 [02:23<1:01:13,  1.08s/it]
overall:  91%|█████████ | 3638/4000 [1:16:54<06:52,  1.14s/it]

train:   3%|▎         | 123/3515 [02:25<1:04:25,  1.14s/it]
overall:  91%|█████████ | 3639/4000 [1:16:55<07:07,  1.18s/it]

train:   4%|▎         | 124/3515 [02:26<1:06:56,  1.18s/it]
overall:  91%|█████████ | 3640/4000 [1:16:56<06:58,  1.16s/it]

train:   4%|▎         | 125/3515 [02:27<1:05:43,  1.16s/it]
overall:  91%|█████████ | 3641/4000 [1:16:56<05:40,  1.05it/s]

train:   4%|▎         | 126/3515 [02:27<53:38,  1.05it/s]  
overall:  91%|█████████ | 3642/4000 [1:16:58<06:12,  1.04s/it]

train:   4%|▎         | 127/3515 [02:29<58:49,  1.04s/it]
overall:  91%|█████████ | 3643/4000 [1:16:59<06:13,  1.05s/it]

train:   4%|▎         | 128/3515 [02:30<59:06,  1.05s/it]
overall:  91%|█████████ | 3644/4000 [1:17:00<06:33,  1.10s/it]

train:   4%|▎         | 129/3515 [02:31<1:02:18,  1.10s/it]
overall:  91%|█████████ | 3645/4000 [1:17:01<06:20,  1.07s/it]

train:   4%|▎         | 130/3515 [02:32<1:00:29,  1.07s/it]
overall:  91%|█████████ | 3646/4000 [1:17:02<06:42,  1.14s/it]

train:   4%|▎         | 131/3515 [02:33<1:04:05,  1.14s/it]
overall:  91%|█████████ | 3647/4000 [1:17:03<06:39,  1.13s/it]

train:   4%|▍         | 132/3515 [02:34<1:03:44,  1.13s/it]
overall:  91%|█████████ | 3648/4000 [1:17:05<07:02,  1.20s/it]

train:   4%|▍         | 133/3515 [02:36<1:07:43,  1.20s/it]
overall:  91%|█████████ | 3649/4000 [1:17:06<06:56,  1.19s/it]

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overall:  99%|█████████▉| 3976/4000 [1:23:20<00:27,  1.13s/it]

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overall:  99%|█████████▉| 3977/4000 [1:23:21<00:26,  1.15s/it]

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overall:  99%|█████████▉| 3978/4000 [1:23:22<00:24,  1.12s/it]

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overall:  99%|█████████▉| 3979/4000 [1:23:23<00:23,  1.14s/it]

train:  13%|█▎        | 464/3515 [08:55<57:49,  1.14s/it]
overall: 100%|█████████▉| 3980/4000 [1:23:25<00:23,  1.17s/it]

train:  13%|█▎        | 465/3515 [08:56<59:32,  1.17s/it]
overall: 100%|█████████▉| 3981/4000 [1:23:26<00:22,  1.19s/it]

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overall: 100%|█████████▉| 3982/4000 [1:23:27<00:21,  1.19s/it]

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train:  14%|█▎        | 482/3515 [09:15<1:00:50,  1.20s/it]
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overall: 100%|█████████▉| 3999/4000 [1:23:46<00:01,  1.11s/it]

train:  14%|█▍        | 484/3515 [09:17<55:55,  1.11s/it]train loss: 12.469161033630371
train per: 0.9324584174598596
train loss: 10.266958236694336
train per: 0.9137122625711689
train loss: 8.9746675491333
train per: 0.8851000933513121
train loss: 9.772011756896973
train per: 0.8845741512805241
train loss: 10.346471786499023
train per: 0.885092624956309
train loss: 10.201539993286133
train per: 0.8383720001065444
train loss: 11.061568260192871
train per: 0.871447902571042
train loss: 13.665809631347656
train per: 0.9938119108723287
train loss: 11.324913024902344
train per: 0.9102794022092268
train loss: 10.893227577209473
train per: 0.8850571973307912
train loss: 11.773261070251465
train per: 0.8732998294066117
train loss: 11.892802238464355
train per: 0.9413517882400485
train loss: 15.040385246276855
train per: 0.9866504238363535
train loss: 12.517026901245117
train per: 0.8722007071897626
train loss: 12.967300415039062
train per: 0.8744761623034067
train loss: 10.629598617553711
train per: 0.8840832100768167
train loss: 11.19051456451416
train per: 0.878186215235792
train loss: 11.195571899414062
train per: 0.9219796692743711
train loss: 10.041170120239258
train per: 0.9598539151290507
train loss: 10.769424438476562
train per: 1.0000254394667887
train loss: 12.194143295288086
train per: 0.8958046681510019
train loss: 10.849828720092773
train per: 0.9256073907717436
train loss: 13.13957405090332
train per: 0.8888253935269365
train loss: 11.309834480285645
train per: 0.8862670015167715
train loss: 10.366373062133789
train per: 0.8760694908180301
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



word -> phonemes:   0%|          | 0/2703 [00:00<?, ?it/s]


word -> phonemes:  18%|█▊        | 474/2703 [00:00<00:00, 4736.48it/s]


word -> phonemes:  39%|███▉      | 1051/2703 [00:00<00:00, 5341.70it/s]


word -> phonemes:  60%|██████    | 1623/2703 [00:00<00:00, 5510.58it/s]


word -> phonemes:  81%|████████▏ | 2200/2703 [00:00<00:00, 5612.30it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 5472.97it/s]



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overall: 100%|█████████▉| 3999/4000 [1:26:47<00:01,  1.11s/it]

train:  14%|█▍        | 484/3515 [12:18<55:55,  1.11s/it]
                                                              

                                                         

overall: 100%|█████████▉| 3999/4000 [1:26:47<00:01,  1.11s/it]

train:  14%|█▍        | 484/3515 [12:18<55:55,  1.11s/it]
                                                              

                                                         

overall: 100%|█████████▉| 3999/4000 [1:26:47<00:01,  1.11s/it]

train:  14%|█▍        | 484/3515 [12:18<55:55,  1.11s/it]
overall: 100%|██████████| 4000/4000 [1:26:47<00:00, 55.12s/it]

train:  14%|█▍        | 485/3515 [12:18<46:23:30, 55.12s/it]/home/victor/glockenspiel/s3prl/data/LibriSpeech/train-clean-100/403/128339/403-128339-0009.flac WTF Failed!!!
403-128339-0009 Failed!!!

train:  14%|█▍        | 485/3515 [12:18<1:16:55,  1.52s/it] 

overall: 100%|██████████| 4000/4000 [1:26:47<00:00,  1.30s/it]
dev loss: 9.967609405517578
dev per: 0.8647138397502602
[Runner] - Save the checkpoint to:
1. result/downstream/grid/dev-best.ckpt
2. result/downstream/grid/states-4000.ckpt