/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_g', 'encoder.pos_conv_embed.conv.weight_v']
- 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:  12%|█▏        | 408/3515 [00:00<00:00, 4063.35it/s]

word -> phonemes:  26%|██▌       | 907/3515 [00:00<00:00, 4605.60it/s]

word -> phonemes:  39%|███▉      | 1368/3515 [00:00<00:00, 4538.08it/s]

word -> phonemes:  53%|█████▎    | 1847/3515 [00:00<00:00, 4632.68it/s]

word -> phonemes:  66%|██████▌   | 2328/3515 [00:00<00:00, 4694.54it/s]

word -> phonemes:  80%|███████▉  | 2798/3515 [00:00<00:00, 4693.70it/s]

word -> phonemes:  93%|█████████▎| 3268/3515 [00:00<00:00, 4435.15it/s]
word -> phonemes: 100%|██████████| 3515/3515 [00:00<00:00, 4527.63it/s]


train:   0%|          | 0/3515 [00:00<?, ?it/s]
overall:   0%|          | 1/4000 [00:04<4:44:36,  4.27s/it]

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overall:   0%|          | 2/4000 [00:05<2:43:52,  2.46s/it]

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overall:   0%|          | 3/4000 [00:06<2:09:04,  1.94s/it]

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overall:   0%|          | 4/4000 [00:08<1:50:46,  1.66s/it]

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overall:   0%|          | 5/4000 [00:09<1:40:50,  1.51s/it]

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overall:   0%|          | 6/4000 [00:10<1:32:33,  1.39s/it]

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overall:   0%|          | 7/4000 [00:11<1:33:17,  1.40s/it]

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overall:   0%|          | 8/4000 [00:13<1:29:52,  1.35s/it]

train:   0%|          | 8/3515 [00:11<1:16:03,  1.30s/it]
overall:   0%|          | 9/4000 [00:14<1:27:56,  1.32s/it]

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overall:   0%|          | 11/4000 [00:15<54:10,  1.23it/s]  

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overall:   0%|          | 12/4000 [00:16<1:02:46,  1.06it/s]

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overall:   0%|          | 13/4000 [00:17<1:06:02,  1.01it/s]

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overall:   0%|          | 14/4000 [00:18<1:10:55,  1.07s/it]

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overall:   0%|          | 15/4000 [00:19<1:11:23,  1.08s/it]

train:   0%|          | 15/3515 [00:17<1:02:29,  1.07s/it]
overall:   0%|          | 16/4000 [00:20<1:14:52,  1.13s/it]

train:   0%|          | 16/3515 [00:19<1:05:35,  1.12s/it]
overall:   0%|          | 17/4000 [00:22<1:15:56,  1.14s/it]

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overall:   0%|          | 18/4000 [00:23<1:19:35,  1.20s/it]

train:   1%|          | 18/3515 [00:21<1:09:49,  1.20s/it]
overall:   0%|          | 19/4000 [00:23<1:04:23,  1.03it/s]

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overall:   0%|          | 20/4000 [00:25<1:10:05,  1.06s/it]

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overall:   1%|          | 21/4000 [00:26<1:15:48,  1.14s/it]

train:   1%|          | 21/3515 [00:24<1:06:32,  1.14s/it]
overall:   1%|          | 22/4000 [00:27<1:19:08,  1.19s/it]

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overall:   1%|          | 23/4000 [00:29<1:21:24,  1.23s/it]

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overall:   1%|          | 24/4000 [00:30<1:19:49,  1.20s/it]

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overall:   1%|          | 25/4000 [00:31<1:19:01,  1.19s/it]

train:   1%|          | 25/3515 [00:29<1:09:22,  1.19s/it]
overall:   1%|          | 26/4000 [00:32<1:20:03,  1.21s/it]

train:   1%|          | 26/3515 [00:30<1:10:17,  1.21s/it]
overall:   1%|          | 27/4000 [00:34<1:23:37,  1.26s/it]

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overall:   1%|          | 28/4000 [00:35<1:22:01,  1.24s/it]

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overall:   1%|          | 29/4000 [00:36<1:21:26,  1.23s/it]

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overall:   1%|          | 30/4000 [00:37<1:23:05,  1.26s/it]

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overall:   1%|          | 31/4000 [00:39<1:24:38,  1.28s/it]

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overall:   1%|          | 32/4000 [00:40<1:24:20,  1.28s/it]

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overall:   1%|          | 33/4000 [00:41<1:24:19,  1.28s/it]

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overall:   1%|          | 34/4000 [00:41<1:04:35,  1.02it/s]

train:   1%|          | 34/3515 [00:40<56:41,  1.02it/s]  
overall:   1%|          | 35/4000 [00:43<1:11:03,  1.08s/it]

train:   1%|          | 35/3515 [00:41<1:02:21,  1.08s/it]
overall:   1%|          | 36/4000 [00:44<1:15:33,  1.14s/it]

train:   1%|          | 36/3515 [00:42<1:06:18,  1.14s/it]
overall:   1%|          | 37/4000 [00:45<1:15:56,  1.15s/it]

train:   1%|          | 37/3515 [00:43<1:06:38,  1.15s/it]
overall:   1%|          | 38/4000 [00:46<1:17:14,  1.17s/it]

train:   1%|          | 38/3515 [00:45<1:07:47,  1.17s/it]
overall:   1%|          | 39/4000 [00:48<1:16:12,  1.15s/it]

train:   1%|          | 39/3515 [00:46<1:06:53,  1.15s/it]
overall:   1%|          | 40/4000 [00:48<1:08:42,  1.04s/it]

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overall:   1%|          | 41/4000 [00:50<1:12:00,  1.09s/it]

train:   1%|          | 41/3515 [00:48<1:03:11,  1.09s/it]
overall:   1%|          | 42/4000 [00:51<1:16:17,  1.16s/it]

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overall:   1%|          | 43/4000 [00:52<1:16:55,  1.17s/it]

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overall:   1%|          | 45/4000 [00:54<1:06:57,  1.02s/it]

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overall:   1%|          | 46/4000 [00:54<55:40,  1.18it/s]  

train:   1%|▏         | 46/3515 [00:52<48:51,  1.18it/s]
overall:   1%|          | 47/4000 [00:56<1:03:29,  1.04it/s]

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overall:   1%|          | 48/4000 [00:57<1:04:48,  1.02it/s]

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overall:   1%|          | 49/4000 [00:58<1:11:12,  1.08s/it]

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overall:   1%|▏         | 50/4000 [00:59<1:12:57,  1.11s/it]

train:   1%|▏         | 50/3515 [00:57<1:03:59,  1.11s/it]
overall:   1%|▏         | 51/4000 [01:00<1:15:54,  1.15s/it]

train:   1%|▏         | 51/3515 [00:58<1:06:35,  1.15s/it]
overall:   1%|▏         | 52/4000 [01:02<1:19:00,  1.20s/it]

train:   1%|▏         | 52/3515 [01:00<1:09:18,  1.20s/it]
overall:   1%|▏         | 53/4000 [01:03<1:19:49,  1.21s/it]

train:   2%|▏         | 53/3515 [01:01<1:10:00,  1.21s/it]
overall:   1%|▏         | 54/4000 [01:04<1:19:04,  1.20s/it]

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overall:   1%|▏         | 55/4000 [01:05<1:22:01,  1.25s/it]

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overall:   1%|▏         | 56/4000 [01:07<1:22:07,  1.25s/it]

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overall:   1%|▏         | 57/4000 [01:08<1:23:58,  1.28s/it]

train:   2%|▏         | 57/3515 [01:06<1:13:39,  1.28s/it]
overall:   1%|▏         | 58/4000 [01:09<1:24:48,  1.29s/it]

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overall:   1%|▏         | 59/4000 [01:11<1:23:41,  1.27s/it]

train:   2%|▏         | 59/3515 [01:09<1:13:23,  1.27s/it]
overall:   2%|▏         | 60/4000 [01:12<1:22:42,  1.26s/it]

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overall:   2%|▏         | 61/4000 [01:13<1:20:36,  1.23s/it]

train:   2%|▏         | 61/3515 [01:11<1:10:40,  1.23s/it]
overall:   2%|▏         | 62/4000 [01:14<1:15:15,  1.15s/it]

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overall:   2%|▏         | 63/4000 [01:15<1:16:11,  1.16s/it]

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overall:   2%|▏         | 64/4000 [01:16<1:12:59,  1.11s/it]

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overall:   2%|▏         | 65/4000 [01:17<1:17:08,  1.18s/it]

train:   2%|▏         | 65/3515 [01:16<1:07:38,  1.18s/it]
overall:   2%|▏         | 66/4000 [01:19<1:19:33,  1.21s/it]

train:   2%|▏         | 66/3515 [01:17<1:09:44,  1.21s/it]
overall:   2%|▏         | 67/4000 [01:20<1:19:45,  1.22s/it]

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overall:   2%|▏         | 68/4000 [01:21<1:20:10,  1.22s/it]

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overall:   2%|▏         | 69/4000 [01:22<1:04:25,  1.02it/s]

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overall:   2%|▏         | 70/4000 [01:23<1:08:53,  1.05s/it]

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overall:   2%|▏         | 72/4000 [01:25<1:14:42,  1.14s/it]

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train:   2%|▏         | 73/3515 [01:25<1:04:17,  1.12s/it]
overall:   2%|▏         | 74/4000 [01:28<1:15:40,  1.16s/it]

train:   2%|▏         | 74/3515 [01:26<1:06:19,  1.16s/it]
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overall:  10%|▉         | 390/4000 [07:42<57:22,  1.05it/s]  

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overall:  10%|█         | 404/4000 [07:59<1:11:10,  1.19s/it]

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overall:  10%|█         | 406/4000 [08:01<1:06:18,  1.11s/it]

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overall:  10%|█         | 407/4000 [08:02<1:07:35,  1.13s/it]

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overall:  11%|█         | 426/4000 [08:24<59:25,  1.00it/s]  

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overall:  11%|█         | 427/4000 [08:26<1:05:31,  1.10s/it]

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overall:  11%|█         | 431/4000 [08:30<51:43,  1.15it/s]  

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overall:  11%|█         | 432/4000 [08:31<58:53,  1.01it/s]

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overall:  11%|█▏        | 452/4000 [08:54<1:09:21,  1.17s/it]

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overall:  12%|█▏        | 492/4000 [09:40<56:41,  1.03it/s]  

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train:  15%|█▍        | 515/3515 [10:06<1:00:20,  1.21s/it]
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overall:  13%|█▎        | 531/4000 [10:27<58:04,  1.00s/it]  

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overall:  13%|█▎        | 534/4000 [10:30<58:19,  1.01s/it]  

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overall:  14%|█▎        | 540/4000 [10:37<55:57,  1.03it/s]  

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overall:  14%|█▎        | 549/4000 [10:49<1:13:43,  1.28s/it]

train:  16%|█▌        | 549/3515 [10:47<1:03:22,  1.28s/it]
overall:  14%|█▍        | 550/4000 [10:50<1:16:57,  1.34s/it]

train:  16%|█▌        | 550/3515 [10:48<1:06:08,  1.34s/it]
overall:  14%|█▍        | 551/4000 [10:51<1:15:22,  1.31s/it]

train:  16%|█▌        | 551/3515 [10:50<1:04:46,  1.31s/it]
overall:  14%|█▍        | 552/4000 [10:52<1:06:38,  1.16s/it]

train:  16%|█▌        | 552/3515 [10:50<57:15,  1.16s/it]  
overall:  14%|█▍        | 553/4000 [10:53<1:06:25,  1.16s/it]

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overall:  14%|█▍        | 555/4000 [10:55<55:02,  1.04it/s]  

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train:  16%|█▌        | 557/3515 [10:56<56:03,  1.14s/it]
overall:  14%|█▍        | 558/4000 [10:59<1:07:48,  1.18s/it]

train:  16%|█▌        | 558/3515 [10:57<58:15,  1.18s/it]
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overall:  14%|█▍        | 560/4000 [11:01<1:07:29,  1.18s/it]

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overall:  14%|█▍        | 561/4000 [11:03<1:08:08,  1.19s/it]

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overall:  14%|█▍        | 562/4000 [11:04<1:03:51,  1.11s/it]

train:  16%|█▌        | 562/3515 [11:02<54:51,  1.11s/it]
overall:  14%|█▍        | 563/4000 [11:05<1:07:04,  1.17s/it]

train:  16%|█▌        | 563/3515 [11:03<57:36,  1.17s/it]
overall:  14%|█▍        | 564/4000 [11:06<1:10:23,  1.23s/it]

train:  16%|█▌        | 564/3515 [11:04<1:00:27,  1.23s/it]
overall:  14%|█▍        | 565/4000 [11:07<57:03,  1.00it/s]  

train:  16%|█▌        | 565/3515 [11:05<48:59,  1.00it/s]  
overall:  14%|█▍        | 566/4000 [11:08<1:05:40,  1.15s/it]

train:  16%|█▌        | 566/3515 [11:06<56:23,  1.15s/it]
overall:  14%|█▍        | 567/4000 [11:09<1:08:12,  1.19s/it]

train:  16%|█▌        | 567/3515 [11:08<58:34,  1.19s/it]
overall:  14%|█▍        | 568/4000 [11:10<52:39,  1.09it/s]  

train:  16%|█▌        | 568/3515 [11:08<45:12,  1.09it/s]
overall:  14%|█▍        | 569/4000 [11:11<59:03,  1.03s/it]

train:  16%|█▌        | 569/3515 [11:09<50:42,  1.03s/it]
overall:  14%|█▍        | 570/4000 [11:12<1:03:16,  1.11s/it]

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overall:  14%|█▍        | 571/4000 [11:14<1:07:43,  1.18s/it]

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overall:  14%|█▍        | 572/4000 [11:15<1:09:27,  1.22s/it]

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overall:  14%|█▍        | 573/4000 [11:16<1:11:45,  1.26s/it]

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overall:  14%|█▍        | 574/4000 [11:18<1:14:41,  1.31s/it]

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overall:  14%|█▍        | 575/4000 [11:19<1:15:33,  1.32s/it]

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overall:  14%|█▍        | 576/4000 [11:20<1:15:05,  1.32s/it]

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overall:  14%|█▍        | 577/4000 [11:22<1:12:28,  1.27s/it]

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overall:  14%|█▍        | 578/4000 [11:23<1:12:48,  1.28s/it]

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overall:  14%|█▍        | 579/4000 [11:24<1:02:30,  1.10s/it]

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overall:  14%|█▍        | 580/4000 [11:25<1:05:06,  1.14s/it]

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overall:  15%|█▍        | 581/4000 [11:26<1:04:52,  1.14s/it]

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overall:  15%|█▍        | 582/4000 [11:27<1:05:59,  1.16s/it]

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overall:  15%|█▍        | 583/4000 [11:29<1:10:21,  1.24s/it]

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overall:  15%|█▍        | 584/4000 [11:30<1:08:07,  1.20s/it]

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overall:  15%|█▍        | 585/4000 [11:31<1:09:46,  1.23s/it]

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overall:  15%|█▍        | 594/4000 [11:42<1:09:04,  1.22s/it]

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overall:  15%|█▍        | 595/4000 [11:43<1:09:51,  1.23s/it]

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overall:  15%|█▍        | 597/4000 [11:45<1:01:01,  1.08s/it]

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overall:  15%|█▍        | 598/4000 [11:47<1:07:33,  1.19s/it]

train:  17%|█▋        | 598/3515 [11:45<57:55,  1.19s/it]
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overall:  15%|█▌        | 600/4000 [11:50<1:30:21,  1.59s/it]

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overall:  15%|█▌        | 602/4000 [11:53<1:15:58,  1.34s/it]

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train:  17%|█▋        | 603/3515 [11:52<1:01:49,  1.27s/it]
overall:  15%|█▌        | 604/4000 [11:55<1:12:53,  1.29s/it]

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overall:  15%|█▌        | 605/4000 [11:56<1:13:57,  1.31s/it]

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overall:  15%|█▌        | 606/4000 [11:58<1:10:48,  1.25s/it]

train:  17%|█▋        | 606/3515 [11:56<59:54,  1.24s/it]  
overall:  15%|█▌        | 607/4000 [11:59<1:05:18,  1.15s/it]

train:  17%|█▋        | 607/3515 [11:57<55:25,  1.14s/it]
overall:  15%|█▌        | 608/4000 [12:00<1:07:33,  1.19s/it]

train:  17%|█▋        | 608/3515 [11:58<57:30,  1.19s/it]
overall:  15%|█▌        | 609/4000 [12:01<1:07:34,  1.20s/it]

train:  17%|█▋        | 609/3515 [11:59<57:38,  1.19s/it]
overall:  15%|█▌        | 610/4000 [12:02<1:09:05,  1.22s/it]

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overall:  15%|█▌        | 611/4000 [12:03<56:22,  1.00it/s]  

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overall:  15%|█▌        | 612/4000 [12:03<50:36,  1.12it/s]

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overall:  15%|█▌        | 613/4000 [12:05<57:10,  1.01s/it]

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overall:  15%|█▌        | 614/4000 [12:06<1:05:30,  1.16s/it]

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overall:  15%|█▌        | 616/4000 [12:09<1:07:17,  1.19s/it]

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overall:  15%|█▌        | 617/4000 [12:10<1:09:59,  1.24s/it]

train:  18%|█▊        | 617/3515 [12:08<59:56,  1.24s/it]
overall:  15%|█▌        | 618/4000 [12:11<1:10:41,  1.25s/it]

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overall:  15%|█▌        | 619/4000 [12:13<1:10:32,  1.25s/it]

train:  18%|█▊        | 619/3515 [12:11<1:00:24,  1.25s/it]
overall:  16%|█▌        | 620/4000 [12:14<1:11:12,  1.26s/it]

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overall:  16%|█▌        | 621/4000 [12:15<1:11:40,  1.27s/it]

train:  18%|█▊        | 621/3515 [12:13<1:01:22,  1.27s/it]
overall:  16%|█▌        | 622/4000 [12:17<1:14:11,  1.32s/it]

train:  18%|█▊        | 622/3515 [12:15<1:03:32,  1.32s/it]
overall:  16%|█▌        | 623/4000 [12:18<1:14:01,  1.32s/it]

train:  18%|█▊        | 623/3515 [12:16<1:03:23,  1.32s/it]
overall:  16%|█▌        | 624/4000 [12:19<1:13:38,  1.31s/it]

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overall:  16%|█▌        | 625/4000 [12:20<1:11:28,  1.27s/it]

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overall:  16%|█▌        | 626/4000 [12:22<1:10:48,  1.26s/it]

train:  18%|█▊        | 626/3515 [12:20<1:00:38,  1.26s/it]
overall:  16%|█▌        | 627/4000 [12:23<1:10:53,  1.26s/it]

train:  18%|█▊        | 627/3515 [12:21<1:00:42,  1.26s/it]
overall:  16%|█▌        | 628/4000 [12:24<1:11:17,  1.27s/it]

train:  18%|█▊        | 628/3515 [12:22<1:01:02,  1.27s/it]
overall:  16%|█▌        | 629/4000 [12:25<1:12:00,  1.28s/it]

train:  18%|█▊        | 629/3515 [12:24<1:01:38,  1.28s/it]
overall:  16%|█▌        | 630/4000 [12:26<1:07:34,  1.20s/it]

train:  18%|█▊        | 630/3515 [12:25<57:50,  1.20s/it]  
overall:  16%|█▌        | 631/4000 [12:28<1:08:22,  1.22s/it]

train:  18%|█▊        | 631/3515 [12:26<58:32,  1.22s/it]
overall:  16%|█▌        | 632/4000 [12:29<1:08:37,  1.22s/it]

train:  18%|█▊        | 632/3515 [12:27<58:44,  1.22s/it]
overall:  16%|█▌        | 633/4000 [12:30<1:10:43,  1.26s/it]

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overall:  16%|█▌        | 634/4000 [12:32<1:12:13,  1.29s/it]

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overall:  16%|█▌        | 635/4000 [12:32<57:48,  1.03s/it]  

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overall:  16%|█▌        | 636/4000 [12:33<59:41,  1.06s/it]

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overall:  16%|█▌        | 637/4000 [12:35<1:03:39,  1.14s/it]

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overall:  16%|█▌        | 638/4000 [12:35<53:49,  1.04it/s]  

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overall:  16%|█▌        | 639/4000 [12:36<1:00:28,  1.08s/it]

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overall:  16%|█▌        | 640/4000 [12:38<1:00:19,  1.08s/it]

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overall:  16%|█▌        | 641/4000 [12:39<1:03:21,  1.13s/it]

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overall:  16%|█▌        | 642/4000 [12:40<1:04:55,  1.16s/it]

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overall:  16%|█▌        | 643/4000 [12:41<1:07:55,  1.21s/it]

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overall:  16%|█▌        | 645/4000 [12:43<59:15,  1.06s/it]  

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overall:  16%|█▌        | 646/4000 [12:45<1:05:57,  1.18s/it]

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overall:  16%|█▌        | 648/4000 [12:47<1:06:31,  1.19s/it]

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overall:  16%|█▋        | 650/4000 [12:49<1:05:24,  1.17s/it]

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overall:  16%|█▋        | 651/4000 [12:51<1:08:22,  1.22s/it]

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overall:  16%|█▋        | 652/4000 [12:52<1:10:35,  1.27s/it]

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overall:  16%|█▋        | 653/4000 [12:53<1:11:47,  1.29s/it]

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overall:  16%|█▋        | 654/4000 [12:55<1:12:09,  1.29s/it]

train:  19%|█▊        | 654/3515 [12:53<1:01:42,  1.29s/it]
overall:  16%|█▋        | 655/4000 [12:56<1:07:34,  1.21s/it]

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overall:  16%|█▋        | 656/4000 [12:57<1:08:51,  1.24s/it]

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overall:  16%|█▋        | 657/4000 [12:58<1:08:09,  1.22s/it]

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overall:  16%|█▋        | 658/4000 [12:59<1:06:28,  1.19s/it]

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overall:  16%|█▋        | 659/4000 [13:00<56:37,  1.02s/it]  

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overall:  16%|█▋        | 660/4000 [13:01<1:02:37,  1.13s/it]

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overall:  17%|█▋        | 662/4000 [13:04<1:07:34,  1.21s/it]

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overall:  17%|█▋        | 667/4000 [13:10<1:05:35,  1.18s/it]

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overall:  17%|█▋        | 668/4000 [13:11<1:06:17,  1.19s/it]

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overall:  17%|█▋        | 669/4000 [13:12<1:03:18,  1.14s/it]

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overall:  17%|█▋        | 670/4000 [13:13<56:32,  1.02s/it]  

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overall:  17%|█▋        | 671/4000 [13:14<51:04,  1.09it/s]

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overall:  17%|█▋        | 672/4000 [13:15<55:34,  1.00s/it]

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overall:  17%|█▋        | 673/4000 [13:16<1:01:01,  1.10s/it]

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overall:  17%|█▋        | 674/4000 [13:16<47:48,  1.16it/s]  

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overall:  17%|█▋        | 675/4000 [13:18<54:40,  1.01it/s]

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overall:  17%|█▋        | 676/4000 [13:19<59:27,  1.07s/it]

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overall:  17%|█▋        | 677/4000 [13:20<1:03:49,  1.15s/it]

train:  19%|█▉        | 677/3515 [13:18<54:30,  1.15s/it]
overall:  17%|█▋        | 678/4000 [13:22<1:06:07,  1.19s/it]

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overall:  17%|█▋        | 679/4000 [13:23<1:09:47,  1.26s/it]

train:  19%|█▉        | 679/3515 [13:21<59:35,  1.26s/it]
overall:  17%|█▋        | 680/4000 [13:24<1:11:23,  1.29s/it]

train:  19%|█▉        | 680/3515 [13:23<1:00:57,  1.29s/it]
overall:  17%|█▋        | 681/4000 [13:26<1:11:34,  1.29s/it]

train:  19%|█▉        | 681/3515 [13:24<1:01:06,  1.29s/it]
overall:  17%|█▋        | 682/4000 [13:27<1:11:33,  1.29s/it]

train:  19%|█▉        | 682/3515 [13:25<1:01:06,  1.29s/it]
overall:  17%|█▋        | 683/4000 [13:28<1:11:47,  1.30s/it]

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train:  28%|██▊       | 994/3515 [19:34<42:57,  1.02s/it]
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train:  28%|██▊       | 995/3515 [19:36<47:06,  1.12s/it]
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train:  28%|██▊       | 997/3515 [19:38<51:03,  1.22s/it]
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train:  28%|██▊       | 998/3515 [19:40<53:10,  1.27s/it]
overall:  25%|██▍       | 999/4000 [19:43<1:04:35,  1.29s/it]

train:  28%|██▊       | 999/3515 [19:41<54:09,  1.29s/it]train loss: 242.1951141357422
train per: 1.0936367697423934
train loss: 185.15032958984375
train per: 1.0332495458052313
train loss: 76.72183990478516
train per: 0.9835828469931489
train loss: 50.491416931152344
train per: 0.9190255104587889
train loss: 35.45976638793945
train per: 0.9274100540467198
train loss: 26.001461029052734
train per: 0.8987446707721459
train loss: 25.463483810424805
train per: 0.9624486872193294
train loss: 19.078859329223633
train per: 0.9248222524349745
train loss: 16.52552604675293
train per: 0.8880942809385778
train loss: 17.283710479736328
train per: 0.9572465646875811
train loss: 16.879854202270508
train per: 0.904022450888681
train loss: 15.45995044708252
train per: 0.9100220374636883
train loss: 14.59375286102295
train per: 0.9460275669815704
train loss: 12.15442180633545
train per: 0.9567170464648356
train loss: 13.106809616088867
train per: 0.9205089783585939
train loss: 14.638811111450195
train per: 0.9668842667230488
train loss: 16.554439544677734
train per: 0.9067707234760599
train loss: 18.80117416381836
train per: 0.9943889801592316
train loss: 17.943912506103516
train per: 0.9130312699425654
train loss: 17.403072357177734
train per: 0.9163017973342364
train loss: 18.163623809814453
train per: 0.9430334266669971
train loss: 16.58308982849121
train per: 0.9864052005502657
train loss: 16.984973907470703
train per: 1.0431530202025343
train loss: 11.845836639404297
train per: 0.9165283853773822
train loss: 13.76551342010498
train per: 0.8729400650781988
train loss: 10.99620246887207
train per: 0.8760324777125208
train loss: 11.099772453308105
train per: 0.9162822605445556
train loss: 10.152046203613281
train per: 0.8672238602305125
train loss: 12.310506820678711
train per: 0.8902779186530074
train loss: 9.12534236907959
train per: 0.8264804693376122
train loss: 8.915460586547852
train per: 0.8313597490005566
train loss: 7.92313289642334
train per: 0.779220130810325
train loss: 8.458342552185059
train per: 0.8123207043228806
train loss: 9.665212631225586
train per: 0.832645525629887
train loss: 9.214542388916016
train per: 0.817763875065169
train loss: 9.747652053833008
train per: 0.7937425783468429
train loss: 8.063305854797363
train per: 0.8368224539719326
train loss: 8.59192943572998
train per: 0.7921943654691135
train loss: 13.213653564453125
train per: 0.8685401641382741
train loss: 10.005888938903809
train per: 0.8418278541835209
train loss: 9.624734878540039
train per: 0.9005634415882765
train loss: 8.309030532836914
train per: 0.7984311389137126
train loss: 6.295302867889404
train per: 0.7587198429025622
train loss: 7.034416198730469
train per: 0.7837907395709038
train loss: 7.749137878417969
train per: 0.7886254078005551
train loss: 9.007953643798828
train per: 0.8328796016972015
train loss: 8.149508476257324
train per: 0.8193530887638164
train loss: 8.875866889953613
train per: 0.8153434201632611
train loss: 10.555749893188477
train per: 0.8120496345048256
train loss: 10.128580093383789
train per: 0.7599848121692494
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  18%|█▊        | 491/2703 [00:00<00:00, 4818.34it/s]


word -> phonemes:  39%|███▉      | 1057/2703 [00:00<00:00, 5263.56it/s]


word -> phonemes:  59%|█████▊    | 1584/2703 [00:00<00:00, 4978.16it/s]


word -> phonemes:  79%|███████▉  | 2135/2703 [00:00<00:00, 5178.34it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 5240.11it/s]



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


dev:   0%|          | 1/2703 [00:00<40:42,  1.11it/s]


dev:   0%|          | 2/2703 [00:01<22:32,  2.00it/s]


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dev:   0%|          | 5/2703 [00:01<12:25,  3.62it/s]


dev:   0%|          | 6/2703 [00:01<11:36,  3.87it/s]


dev:   0%|          | 7/2703 [00:02<11:04,  4.06it/s]


dev:   0%|          | 8/2703 [00:02<10:23,  4.32it/s]


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overall:  47%|████▋     | 1884/4000 [39:54<43:48,  1.24s/it]

train:  54%|█████▎    | 1884/3515 [39:52<33:45,  1.24s/it]
overall:  47%|████▋     | 1885/4000 [39:55<43:34,  1.24s/it]

train:  54%|█████▎    | 1885/3515 [39:54<33:35,  1.24s/it]
overall:  47%|████▋     | 1886/4000 [39:57<42:36,  1.21s/it]

train:  54%|█████▎    | 1886/3515 [39:55<32:50,  1.21s/it]
overall:  47%|████▋     | 1887/4000 [39:58<43:51,  1.25s/it]

train:  54%|█████▎    | 1887/3515 [39:56<33:47,  1.25s/it]
overall:  47%|████▋     | 1888/4000 [39:59<40:02,  1.14s/it]

train:  54%|█████▎    | 1888/3515 [39:57<30:50,  1.14s/it]
overall:  47%|████▋     | 1889/4000 [40:00<40:14,  1.14s/it]

train:  54%|█████▎    | 1889/3515 [39:58<30:59,  1.14s/it]
overall:  47%|████▋     | 1890/4000 [40:01<42:24,  1.21s/it]

train:  54%|█████▍    | 1890/3515 [39:59<32:39,  1.21s/it]
overall:  47%|████▋     | 1891/4000 [40:03<43:21,  1.23s/it]

train:  54%|█████▍    | 1891/3515 [40:01<33:22,  1.23s/it]
overall:  47%|████▋     | 1892/4000 [40:04<44:28,  1.27s/it]

train:  54%|█████▍    | 1892/3515 [40:02<34:14,  1.27s/it]
overall:  47%|████▋     | 1893/4000 [40:05<42:46,  1.22s/it]

train:  54%|█████▍    | 1893/3515 [40:03<32:56,  1.22s/it]
overall:  47%|████▋     | 1894/4000 [40:07<45:19,  1.29s/it]

train:  54%|█████▍    | 1894/3515 [40:05<34:53,  1.29s/it]
overall:  47%|████▋     | 1895/4000 [40:08<45:10,  1.29s/it]

train:  54%|█████▍    | 1895/3515 [40:06<34:46,  1.29s/it]
overall:  47%|████▋     | 1896/4000 [40:08<34:40,  1.01it/s]

train:  54%|█████▍    | 1896/3515 [40:06<26:41,  1.01it/s]
overall:  47%|████▋     | 1897/4000 [40:09<36:52,  1.05s/it]

train:  54%|█████▍    | 1897/3515 [40:07<28:22,  1.05s/it]
overall:  47%|████▋     | 1898/4000 [40:11<39:17,  1.12s/it]

train:  54%|█████▍    | 1898/3515 [40:09<30:13,  1.12s/it]
overall:  47%|████▋     | 1899/4000 [40:11<32:01,  1.09it/s]

train:  54%|█████▍    | 1899/3515 [40:09<24:38,  1.09it/s]
overall:  48%|████▊     | 1900/4000 [40:12<36:04,  1.03s/it]

train:  54%|█████▍    | 1900/3515 [40:10<27:44,  1.03s/it]
overall:  48%|████▊     | 1901/4000 [40:14<39:08,  1.12s/it]

train:  54%|█████▍    | 1901/3515 [40:12<30:06,  1.12s/it]
overall:  48%|████▊     | 1902/4000 [40:15<42:57,  1.23s/it]

train:  54%|█████▍    | 1902/3515 [40:13<33:01,  1.23s/it]
overall:  48%|████▊     | 1903/4000 [40:16<44:06,  1.26s/it]

train:  54%|█████▍    | 1903/3515 [40:15<33:54,  1.26s/it]
overall:  48%|████▊     | 1904/4000 [40:18<44:30,  1.27s/it]

train:  54%|█████▍    | 1904/3515 [40:16<34:12,  1.27s/it]
overall:  48%|████▊     | 1905/4000 [40:19<45:33,  1.30s/it]

train:  54%|█████▍    | 1905/3515 [40:17<35:00,  1.30s/it]
overall:  48%|████▊     | 1906/4000 [40:20<44:59,  1.29s/it]

train:  54%|█████▍    | 1906/3515 [40:19<34:34,  1.29s/it]
overall:  48%|████▊     | 1907/4000 [40:22<44:31,  1.28s/it]

train:  54%|█████▍    | 1907/3515 [40:20<34:12,  1.28s/it]
overall:  48%|████▊     | 1908/4000 [40:22<37:12,  1.07s/it]

train:  54%|█████▍    | 1908/3515 [40:20<28:34,  1.07s/it]
overall:  48%|████▊     | 1909/4000 [40:24<39:35,  1.14s/it]

train:  54%|█████▍    | 1909/3515 [40:22<30:24,  1.14s/it]
overall:  48%|████▊     | 1910/4000 [40:25<41:43,  1.20s/it]

train:  54%|█████▍    | 1910/3515 [40:23<32:02,  1.20s/it]
overall:  48%|████▊     | 1911/4000 [40:25<35:05,  1.01s/it]

train:  54%|█████▍    | 1911/3515 [40:24<26:56,  1.01s/it]
overall:  48%|████▊     | 1912/4000 [40:27<36:57,  1.06s/it]

train:  54%|█████▍    | 1912/3515 [40:25<28:22,  1.06s/it]
overall:  48%|████▊     | 1913/4000 [40:28<38:22,  1.10s/it]

train:  54%|█████▍    | 1913/3515 [40:26<29:27,  1.10s/it]
overall:  48%|████▊     | 1914/4000 [40:29<37:22,  1.07s/it]

train:  54%|█████▍    | 1914/3515 [40:27<28:40,  1.07s/it]
overall:  48%|████▊     | 1915/4000 [40:30<36:42,  1.06s/it]

train:  54%|█████▍    | 1915/3515 [40:28<28:09,  1.06s/it]
overall:  48%|████▊     | 1916/4000 [40:30<28:50,  1.20it/s]

train:  55%|█████▍    | 1916/3515 [40:28<22:08,  1.20it/s]
overall:  48%|████▊     | 1917/4000 [40:31<33:24,  1.04it/s]

train:  55%|█████▍    | 1917/3515 [40:30<25:38,  1.04it/s]
overall:  48%|████▊     | 1918/4000 [40:33<38:00,  1.10s/it]

train:  55%|█████▍    | 1918/3515 [40:31<29:09,  1.10s/it]
overall:  48%|████▊     | 1919/4000 [40:34<39:22,  1.14s/it]

train:  55%|█████▍    | 1919/3515 [40:32<30:12,  1.14s/it]
overall:  48%|████▊     | 1920/4000 [40:35<40:33,  1.17s/it]

train:  55%|█████▍    | 1920/3515 [40:33<31:05,  1.17s/it]
overall:  48%|████▊     | 1921/4000 [40:37<41:35,  1.20s/it]

train:  55%|█████▍    | 1921/3515 [40:35<31:53,  1.20s/it]
overall:  48%|████▊     | 1922/4000 [40:38<40:44,  1.18s/it]

train:  55%|█████▍    | 1922/3515 [40:36<31:13,  1.18s/it]
overall:  48%|████▊     | 1923/4000 [40:39<42:18,  1.22s/it]

train:  55%|█████▍    | 1923/3515 [40:37<32:26,  1.22s/it]
overall:  48%|████▊     | 1924/4000 [40:40<42:43,  1.23s/it]

train:  55%|█████▍    | 1924/3515 [40:38<32:44,  1.23s/it]
overall:  48%|████▊     | 1925/4000 [40:42<43:51,  1.27s/it]

train:  55%|█████▍    | 1925/3515 [40:40<33:36,  1.27s/it]
overall:  48%|████▊     | 1926/4000 [40:43<45:37,  1.32s/it]

train:  55%|█████▍    | 1926/3515 [40:41<34:57,  1.32s/it]
overall:  48%|████▊     | 1927/4000 [40:43<35:01,  1.01s/it]

train:  55%|█████▍    | 1927/3515 [40:41<26:49,  1.01s/it]
overall:  48%|████▊     | 1928/4000 [40:45<37:56,  1.10s/it]

train:  55%|█████▍    | 1928/3515 [40:43<29:03,  1.10s/it]
overall:  48%|████▊     | 1929/4000 [40:46<39:45,  1.15s/it]

train:  55%|█████▍    | 1929/3515 [40:44<30:26,  1.15s/it]
overall:  48%|████▊     | 1930/4000 [40:47<40:45,  1.18s/it]

train:  55%|█████▍    | 1930/3515 [40:45<31:12,  1.18s/it]
overall:  48%|████▊     | 1931/4000 [40:48<41:11,  1.19s/it]

train:  55%|█████▍    | 1931/3515 [40:47<31:32,  1.19s/it]
overall:  48%|████▊     | 1932/4000 [40:50<42:05,  1.22s/it]

train:  55%|█████▍    | 1932/3515 [40:48<32:13,  1.22s/it]
overall:  48%|████▊     | 1933/4000 [40:51<41:28,  1.20s/it]

train:  55%|█████▍    | 1933/3515 [40:49<31:44,  1.20s/it]
overall:  48%|████▊     | 1934/4000 [40:52<41:56,  1.22s/it]

train:  55%|█████▌    | 1934/3515 [40:50<32:05,  1.22s/it]
overall:  48%|████▊     | 1935/4000 [40:53<43:13,  1.26s/it]

train:  55%|█████▌    | 1935/3515 [40:52<33:04,  1.26s/it]
overall:  48%|████▊     | 1936/4000 [40:55<43:28,  1.26s/it]

train:  55%|█████▌    | 1936/3515 [40:53<33:15,  1.26s/it]
overall:  48%|████▊     | 1937/4000 [40:56<43:17,  1.26s/it]

train:  55%|█████▌    | 1937/3515 [40:54<33:07,  1.26s/it]
overall:  48%|████▊     | 1938/4000 [40:57<43:24,  1.26s/it]

train:  55%|█████▌    | 1938/3515 [40:55<33:11,  1.26s/it]
overall:  48%|████▊     | 1939/4000 [40:59<43:21,  1.26s/it]

train:  55%|█████▌    | 1939/3515 [40:57<33:09,  1.26s/it]
overall:  48%|████▊     | 1940/4000 [41:00<41:51,  1.22s/it]

train:  55%|█████▌    | 1940/3515 [40:58<32:00,  1.22s/it]
overall:  49%|████▊     | 1941/4000 [41:01<41:59,  1.22s/it]

train:  55%|█████▌    | 1941/3515 [40:59<32:06,  1.22s/it]
overall:  49%|████▊     | 1942/4000 [41:02<43:52,  1.28s/it]

train:  55%|█████▌    | 1942/3515 [41:00<33:32,  1.28s/it]
overall:  49%|████▊     | 1943/4000 [41:04<43:31,  1.27s/it]

train:  55%|█████▌    | 1943/3515 [41:02<33:15,  1.27s/it]
overall:  49%|████▊     | 1944/4000 [41:05<42:43,  1.25s/it]

train:  55%|█████▌    | 1944/3515 [41:03<32:38,  1.25s/it]
overall:  49%|████▊     | 1945/4000 [41:06<42:57,  1.25s/it]

train:  55%|█████▌    | 1945/3515 [41:04<32:48,  1.25s/it]
overall:  49%|████▊     | 1946/4000 [41:07<43:19,  1.27s/it]

train:  55%|█████▌    | 1946/3515 [41:05<33:05,  1.27s/it]
overall:  49%|████▊     | 1947/4000 [41:09<43:35,  1.27s/it]

train:  55%|█████▌    | 1947/3515 [41:07<33:17,  1.27s/it]
overall:  49%|████▊     | 1948/4000 [41:10<40:00,  1.17s/it]

train:  55%|█████▌    | 1948/3515 [41:08<30:33,  1.17s/it]
overall:  49%|████▊     | 1949/4000 [41:11<40:13,  1.18s/it]

train:  55%|█████▌    | 1949/3515 [41:09<30:43,  1.18s/it]
overall:  49%|████▉     | 1950/4000 [41:12<43:03,  1.26s/it]

train:  55%|█████▌    | 1950/3515 [41:10<32:52,  1.26s/it]
overall:  49%|████▉     | 1951/4000 [41:13<43:13,  1.27s/it]

train:  56%|█████▌    | 1951/3515 [41:12<32:59,  1.27s/it]
overall:  49%|████▉     | 1952/4000 [41:14<40:29,  1.19s/it]

train:  56%|█████▌    | 1952/3515 [41:13<30:53,  1.19s/it]
overall:  49%|████▉     | 1953/4000 [41:16<42:56,  1.26s/it]

train:  56%|█████▌    | 1953/3515 [41:14<32:45,  1.26s/it]
overall:  49%|████▉     | 1954/4000 [41:17<42:59,  1.26s/it]

train:  56%|█████▌    | 1954/3515 [41:15<32:48,  1.26s/it]
overall:  49%|████▉     | 1955/4000 [41:18<41:58,  1.23s/it]

train:  56%|█████▌    | 1955/3515 [41:16<32:01,  1.23s/it]
overall:  49%|████▉     | 1956/4000 [41:19<41:27,  1.22s/it]

train:  56%|█████▌    | 1956/3515 [41:18<31:37,  1.22s/it]
overall:  49%|████▉     | 1957/4000 [41:21<41:31,  1.22s/it]

train:  56%|█████▌    | 1957/3515 [41:19<31:39,  1.22s/it]
overall:  49%|████▉     | 1958/4000 [41:22<41:42,  1.23s/it]

train:  56%|█████▌    | 1958/3515 [41:20<31:48,  1.23s/it]
overall:  49%|████▉     | 1959/4000 [41:23<42:10,  1.24s/it]

train:  56%|█████▌    | 1959/3515 [41:21<32:09,  1.24s/it]
overall:  49%|████▉     | 1960/4000 [41:25<42:52,  1.26s/it]

train:  56%|█████▌    | 1960/3515 [41:23<32:40,  1.26s/it]
overall:  49%|████▉     | 1961/4000 [41:26<43:45,  1.29s/it]

train:  56%|█████▌    | 1961/3515 [41:24<33:21,  1.29s/it]
overall:  49%|████▉     | 1962/4000 [41:27<43:45,  1.29s/it]

train:  56%|█████▌    | 1962/3515 [41:25<33:20,  1.29s/it]
overall:  49%|████▉     | 1963/4000 [41:28<42:43,  1.26s/it]

train:  56%|█████▌    | 1963/3515 [41:26<32:32,  1.26s/it]
overall:  49%|████▉     | 1964/4000 [41:30<43:00,  1.27s/it]

train:  56%|█████▌    | 1964/3515 [41:28<32:46,  1.27s/it]
overall:  49%|████▉     | 1965/4000 [41:31<40:04,  1.18s/it]

train:  56%|█████▌    | 1965/3515 [41:29<30:31,  1.18s/it]
overall:  49%|████▉     | 1966/4000 [41:32<42:38,  1.26s/it]

train:  56%|█████▌    | 1966/3515 [41:30<32:28,  1.26s/it]
overall:  49%|████▉     | 1967/4000 [41:33<41:48,  1.23s/it]

train:  56%|█████▌    | 1967/3515 [41:31<31:49,  1.23s/it]
overall:  49%|████▉     | 1968/4000 [41:34<34:43,  1.03s/it]

train:  56%|█████▌    | 1968/3515 [41:32<26:26,  1.03s/it]
overall:  49%|████▉     | 1969/4000 [41:35<36:29,  1.08s/it]

train:  56%|█████▌    | 1969/3515 [41:33<27:46,  1.08s/it]
overall:  49%|████▉     | 1970/4000 [41:36<38:32,  1.14s/it]

train:  56%|█████▌    | 1970/3515 [41:34<29:20,  1.14s/it]
overall:  49%|████▉     | 1971/4000 [41:37<39:29,  1.17s/it]

train:  56%|█████▌    | 1971/3515 [41:36<30:03,  1.17s/it]
overall:  49%|████▉     | 1972/4000 [41:39<40:34,  1.20s/it]

train:  56%|█████▌    | 1972/3515 [41:37<30:52,  1.20s/it]
overall:  49%|████▉     | 1973/4000 [41:40<41:48,  1.24s/it]

train:  56%|█████▌    | 1973/3515 [41:38<31:48,  1.24s/it]
overall:  49%|████▉     | 1974/4000 [41:41<43:24,  1.29s/it]

train:  56%|█████▌    | 1974/3515 [41:40<33:00,  1.29s/it]
overall:  49%|████▉     | 1975/4000 [41:42<34:52,  1.03s/it]

train:  56%|█████▌    | 1975/3515 [41:40<26:31,  1.03s/it]
overall:  49%|████▉     | 1976/4000 [41:43<37:24,  1.11s/it]

train:  56%|█████▌    | 1976/3515 [41:41<28:26,  1.11s/it]
overall:  49%|████▉     | 1977/4000 [41:45<39:59,  1.19s/it]

train:  56%|█████▌    | 1977/3515 [41:43<30:23,  1.19s/it]
overall:  49%|████▉     | 1978/4000 [41:46<40:18,  1.20s/it]

train:  56%|█████▋    | 1978/3515 [41:44<30:38,  1.20s/it]
overall:  49%|████▉     | 1979/4000 [41:47<41:02,  1.22s/it]

train:  56%|█████▋    | 1979/3515 [41:45<31:11,  1.22s/it]
overall:  50%|████▉     | 1980/4000 [41:48<40:55,  1.22s/it]

train:  56%|█████▋    | 1980/3515 [41:46<31:05,  1.22s/it]
overall:  50%|████▉     | 1981/4000 [41:49<39:50,  1.18s/it]

train:  56%|█████▋    | 1981/3515 [41:48<30:15,  1.18s/it]
overall:  50%|████▉     | 1982/4000 [41:51<40:47,  1.21s/it]

train:  56%|█████▋    | 1982/3515 [41:49<30:59,  1.21s/it]
overall:  50%|████▉     | 1983/4000 [41:52<42:15,  1.26s/it]

train:  56%|█████▋    | 1983/3515 [41:50<32:05,  1.26s/it]
overall:  50%|████▉     | 1984/4000 [41:53<43:04,  1.28s/it]

train:  56%|█████▋    | 1984/3515 [41:51<32:42,  1.28s/it]
overall:  50%|████▉     | 1985/4000 [41:55<43:04,  1.28s/it]

train:  56%|█████▋    | 1985/3515 [41:53<32:42,  1.28s/it]
overall:  50%|████▉     | 1986/4000 [41:56<43:03,  1.28s/it]

train:  57%|█████▋    | 1986/3515 [41:54<32:41,  1.28s/it]
overall:  50%|████▉     | 1987/4000 [41:57<42:59,  1.28s/it]

train:  57%|█████▋    | 1987/3515 [41:55<32:37,  1.28s/it]
overall:  50%|████▉     | 1988/4000 [41:58<41:59,  1.25s/it]

train:  57%|█████▋    | 1988/3515 [41:57<31:52,  1.25s/it]
overall:  50%|████▉     | 1989/4000 [42:00<41:50,  1.25s/it]

train:  57%|█████▋    | 1989/3515 [41:58<31:45,  1.25s/it]
overall:  50%|████▉     | 1990/4000 [42:01<42:57,  1.28s/it]

train:  57%|█████▋    | 1990/3515 [41:59<32:35,  1.28s/it]
overall:  50%|████▉     | 1991/4000 [42:02<42:32,  1.27s/it]

train:  57%|█████▋    | 1991/3515 [42:00<32:16,  1.27s/it]
overall:  50%|████▉     | 1992/4000 [42:04<42:49,  1.28s/it]

train:  57%|█████▋    | 1992/3515 [42:02<32:28,  1.28s/it]
overall:  50%|████▉     | 1993/4000 [42:05<43:20,  1.30s/it]

train:  57%|█████▋    | 1993/3515 [42:03<32:52,  1.30s/it]
overall:  50%|████▉     | 1994/4000 [42:06<41:11,  1.23s/it]

train:  57%|█████▋    | 1994/3515 [42:04<31:14,  1.23s/it]
overall:  50%|████▉     | 1995/4000 [42:07<40:51,  1.22s/it]

train:  57%|█████▋    | 1995/3515 [42:05<30:58,  1.22s/it]
overall:  50%|████▉     | 1996/4000 [42:08<41:02,  1.23s/it]

train:  57%|█████▋    | 1996/3515 [42:07<31:06,  1.23s/it]
overall:  50%|████▉     | 1997/4000 [42:10<42:13,  1.26s/it]

train:  57%|█████▋    | 1997/3515 [42:08<31:59,  1.26s/it]
overall:  50%|████▉     | 1998/4000 [42:11<43:39,  1.31s/it]

train:  57%|█████▋    | 1998/3515 [42:09<33:04,  1.31s/it]
overall:  50%|████▉     | 1999/4000 [42:12<42:51,  1.28s/it]

train:  57%|█████▋    | 1999/3515 [42:11<32:27,  1.28s/it]dev loss: 9.65188980102539
dev per: 0.7367533818938605
[Runner] - Save the checkpoint to:
1. result/downstream/grid/dev-best.ckpt
train loss: 7.868017673492432
train per: 0.779903381642512
train loss: 7.268309593200684
train per: 0.7479263011084196
train loss: 7.315498352050781
train per: 0.7890625
train loss: 8.204626083374023
train per: 0.7843509320236633
train loss: 8.076959609985352
train per: 0.752230743259538
train loss: 6.958444118499756
train per: 0.7581107188062087
train loss: 6.204858303070068
train per: 0.7352522575579112
train loss: 6.904335975646973
train per: 0.7349132211666047
train loss: 7.238006591796875
train per: 0.7499102680913333
train loss: 7.625144958496094
train per: 0.7701988012258957
train loss: 7.151181221008301
train per: 0.7656791963207523
train loss: 12.810407638549805
train per: 0.8809825635628692
train loss: 14.4881010055542
train per: 0.8044823351596448
train loss: 8.51575756072998
train per: 0.7382176315157338
train loss: 7.158905029296875
train per: 0.732067758381693
train loss: 8.543375015258789
train per: 0.79303152039555
train loss: 7.929386138916016
train per: 0.7408844714947792
train loss: 7.588204860687256
train per: 0.7479172469676635
train loss: 8.607918739318848
train per: 0.7679422686928811
train loss: 8.085383415222168
train per: 0.7632391241439183
train loss: 6.498797416687012
train per: 0.7136391935252143
train loss: 6.671891689300537
train per: 0.6998889440230618
train loss: 6.250877380371094
train per: 0.7077137223059969
train loss: 6.08719539642334
train per: 0.6983708856550983
train loss: 8.071213722229004
train per: 0.7515121116454725
train loss: 9.160406112670898
train per: 0.75390064133244
train loss: 12.437488555908203
train per: 0.781105743424584
train loss: 9.47365951538086
train per: 0.7367283329981902
train loss: 7.405472755432129
train per: 0.7183671582451112
train loss: 6.821091651916504
train per: 0.7619678817231711
train loss: 6.563823699951172
train per: 0.691088250724208
train loss: 6.795048713684082
train per: 0.7120979368042918
train loss: 7.565618991851807
train per: 0.7567238892502616
train loss: 6.431858062744141
train per: 0.6908116111086186
train loss: 5.901472568511963
train per: 0.6980343278543792
train loss: 5.376524925231934
train per: 0.6878573005864024
train loss: 7.900738716125488
train per: 0.7571757952192735
train loss: 10.58122730255127
train per: 0.8305735360529881
train loss: 11.307113647460938
train per: 0.8144995526322153
train loss: 7.277417182922363
train per: 0.6981254201000772
train loss: 7.950059413909912
train per: 0.7482161815174184
train loss: 10.044113159179688
train per: 0.8165502986918055
train loss: 10.015969276428223
train per: 0.7602342107897108
train loss: 7.432560920715332
train per: 0.7066164865849217
train loss: 7.000540733337402
train per: 0.7594232544216329
train loss: 8.344874382019043
train per: 0.8169061488673139
train loss: 8.869750022888184
train per: 0.7440425732316097
train loss: 6.317042350769043
train per: 0.6804109070251846
train loss: 5.84105920791626
train per: 0.7185883176285336
train loss: 7.234063625335693
train per: 0.7629223413175009
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  21%|██        | 558/2703 [00:00<00:00, 5572.23it/s]


word -> phonemes:  41%|████▏     | 1116/2703 [00:00<00:00, 5536.14it/s]


word -> phonemes:  62%|██████▏   | 1670/2703 [00:00<00:00, 4972.63it/s]


word -> phonemes:  81%|████████▏ | 2199/2703 [00:00<00:00, 4988.38it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 5138.27it/s]



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overall:  75%|███████▍  | 2995/4000 [1:04:27<19:05,  1.14s/it]

train:  85%|████████▌ | 2995/3515 [1:04:25<09:52,  1.14s/it]
overall:  75%|███████▍  | 2996/4000 [1:04:28<20:04,  1.20s/it]

train:  85%|████████▌ | 2996/3515 [1:04:26<10:22,  1.20s/it]
overall:  75%|███████▍  | 2997/4000 [1:04:30<20:16,  1.21s/it]

train:  85%|████████▌ | 2997/3515 [1:04:28<10:28,  1.21s/it]
overall:  75%|███████▍  | 2998/4000 [1:04:31<20:52,  1.25s/it]

train:  85%|████████▌ | 2998/3515 [1:04:29<10:46,  1.25s/it]
overall:  75%|███████▍  | 2999/4000 [1:04:32<19:32,  1.17s/it]

train:  85%|████████▌ | 2999/3515 [1:04:30<10:04,  1.17s/it]dev loss: 8.758675575256348
dev per: 0.7184495317377732
[Runner] - Save the checkpoint to:
1. result/downstream/grid/dev-best.ckpt
train loss: 12.540705680847168
train per: 0.7875940313232211
train loss: 6.58031702041626
train per: 0.66705827642754
train loss: 5.505916595458984
train per: 0.6711615004221445
train loss: 5.7045135498046875
train per: 0.6837445133948842
train loss: 6.732480049133301
train per: 0.7268204544329488
train loss: 6.713479042053223
train per: 0.6827527519284087
train loss: 11.052663803100586
train per: 0.8414098215602418
train loss: 8.414125442504883
train per: 0.7162944010326625
train loss: 8.603696823120117
train per: 0.758167757287329
train loss: 5.948455810546875
train per: 0.6715721386555534
train loss: 6.165183067321777
train per: 0.7055902383654937
train loss: 9.75506591796875
train per: 0.7473601877199844
train loss: 12.989166259765625
train per: 0.7882649873803633
train loss: 12.616166114807129
train per: 0.7442267489912003
train loss: 10.110878944396973
train per: 0.72939630629973
train loss: 7.387693881988525
train per: 0.6938445717643602
train loss: 7.391116142272949
train per: 0.7317626527050611
train loss: 9.54180908203125
train per: 0.7722154465779845
train loss: 9.35703182220459
train per: 0.7360179483070443
train loss: 15.386087417602539
train per: 0.886961972419557
train loss: 7.901973724365234
train per: 0.6665508081134089
train loss: 6.7956743240356445
train per: 0.6962933118452861
train loss: 8.474491119384766
train per: 0.7149753858593546
train loss: 7.89249324798584
train per: 0.7149177136789948
train loss: 10.311918258666992
train per: 0.7449109783680334
train loss: 11.519693374633789
train per: 0.7733519567006709
train loss: 8.088207244873047
train per: 0.681566505701211
train loss: 6.545437812805176
train per: 0.666971637694419
train loss: 5.810267925262451
train per: 0.6755823180693648
train loss: 6.600437164306641
train per: 0.7005873246012828
train loss: 6.310605049133301
train per: 0.6879526627218935
train loss: 7.874015808105469
train per: 0.708626531144123
train loss: 9.866050720214844
train per: 0.7162395694465018
train loss: 8.99462604522705
train per: 0.7185648971870003
train loss: 7.6874494552612305
train per: 0.7371909661900308
train loss: 8.680027961730957
train per: 0.7745859906747414
train loss: 7.210211277008057
train per: 0.7375247474491091
train loss: 7.578935146331787
train per: 0.720636992559718
train loss: 9.073995590209961
train per: 0.7530179277752094
train loss: 7.628399848937988
train per: 0.7326262773015643
train loss: 6.052826404571533
train per: 0.6653673235125311
train loss: 6.264293670654297
train per: 0.7342015648964101
train loss: 8.10335636138916
train per: 0.7383590299837297
train loss: 10.893450736999512
train per: 0.7942829339496411
train loss: 11.27110481262207
train per: 0.7745972115664436
train loss: 9.119420051574707
train per: 0.7021772553687448
train loss: 7.1356377601623535
train per: 0.6782663794195919
train loss: 6.043717384338379
train per: 0.687734743187962
train loss: 6.312063694000244
train per: 0.70322925006672
train loss: 7.6926984786987305
train per: 0.7209192358615472
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  15%|█▍        | 404/2703 [00:00<00:00, 3975.52it/s]


word -> phonemes:  30%|██▉       | 804/2703 [00:00<00:00, 3847.32it/s]


word -> phonemes:  47%|████▋     | 1274/2703 [00:00<00:00, 4226.50it/s]


word -> phonemes:  65%|██████▍   | 1750/2703 [00:00<00:00, 4432.11it/s]


word -> phonemes:  83%|████████▎ | 2236/2703 [00:00<00:00, 4582.24it/s]


word -> phonemes: 100%|█████████▉| 2702/2703 [00:00<00:00, 4607.34it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 4440.16it/s]



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train: 100%|█████████▉| 3509/3515 [1:17:23<00:07,  1.25s/it]
overall:  88%|████████▊ | 3510/4000 [1:17:25<08:38,  1.06s/it]

train: 100%|█████████▉| 3510/3515 [1:17:23<00:05,  1.06s/it]
overall:  88%|████████▊ | 3511/4000 [1:17:26<08:00,  1.02it/s]

train: 100%|█████████▉| 3511/3515 [1:17:24<00:03,  1.02it/s]
overall:  88%|████████▊ | 3512/4000 [1:17:27<08:46,  1.08s/it]

train: 100%|█████████▉| 3512/3515 [1:17:26<00:03,  1.08s/it]
overall:  88%|████████▊ | 3513/4000 [1:17:29<09:05,  1.12s/it]

train: 100%|█████████▉| 3513/3515 [1:17:27<00:02,  1.12s/it]
overall:  88%|████████▊ | 3514/4000 [1:17:30<09:32,  1.18s/it]

train: 100%|█████████▉| 3514/3515 [1:17:28<00:01,  1.18s/it]
overall:  88%|████████▊ | 3515/4000 [1:17:31<09:52,  1.22s/it]

train: 100%|██████████| 3515/3515 [1:17:29<00:00,  1.22s/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 [1:17:30<00:00,  1.32s/it]
dev loss: 7.744774341583252
dev per: 0.7586576482830385
train loss: 7.177020072937012
train per: 0.7049715708848269
train loss: 7.261188507080078
train per: 0.7192908400168848
train loss: 5.701671123504639
train per: 0.6785098798366345
train loss: 9.87331485748291
train per: 0.8016305023239629
train loss: 9.921468734741211
train per: 0.7357833766085542
train loss: 7.781525611877441
train per: 0.7036647286311857
train loss: 13.61902904510498
train per: 0.7995579872247527
train loss: 8.492582321166992
train per: 0.6895021227325357
train loss: 6.833443641662598
train per: 0.6912209376191081
train loss: 6.126591205596924
train per: 0.695337061124577
train loss: 8.500844955444336
train per: 0.7347566586911366
train loss: 9.443456649780273
train per: 0.7947395808694829
train loss: 8.087153434753418
train per: 0.7306619951146093
train loss: 8.646013259887695
train per: 0.7466881834385086
train loss: 6.916787147521973
train per: 0.7015458358298382
train loss: 6.160144329071045
train per: 0.6573796508552283
train loss: 6.733094692230225
train per: 0.695113620838836
train loss: 10.081313133239746
train per: 0.7667831479476327
train loss: 8.527518272399902
train per: 0.7694472111553785
train loss: 9.884318351745605
train per: 0.7110180337405468
train loss: 12.289335250854492
train per: 0.7911842804036112
train loss: 11.55708122253418
train per: 0.7607566271479952
train loss: 9.207250595092773
train per: 0.7319605554037607
train loss: 6.183116436004639
train per: 0.6553648520585448
train loss: 6.692202568054199
train per: 0.7224598312333834
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.


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

word -> phonemes:  10%|█         | 360/3515 [00:00<00:00, 3551.79it/s]

word -> phonemes:  20%|██        | 716/3515 [00:00<00:00, 3375.41it/s]

word -> phonemes:  32%|███▏      | 1123/3515 [00:00<00:00, 3681.81it/s]

word -> phonemes:  42%|████▏     | 1493/3515 [00:00<00:00, 3310.23it/s]

word -> phonemes:  52%|█████▏    | 1830/3515 [00:00<00:00, 3137.37it/s]

word -> phonemes:  66%|██████▋   | 2332/3515 [00:00<00:00, 3717.40it/s]

word -> phonemes:  77%|███████▋  | 2713/3515 [00:00<00:00, 3543.88it/s]

word -> phonemes:  88%|████████▊ | 3101/3515 [00:00<00:00, 3639.84it/s]

word -> phonemes:  99%|█████████▊| 3471/3515 [00:00<00:00, 3494.48it/s]
word -> phonemes: 100%|██████████| 3515/3515 [00:01<00:00, 3507.47it/s]


train:   0%|          | 0/3515 [00:00<?, ?it/s]
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overall:  88%|████████▊ | 3526/4000 [1:17:48<09:44,  1.23s/it]

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overall:  88%|████████▊ | 3527/4000 [1:17:50<09:38,  1.22s/it]

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overall:  88%|████████▊ | 3528/4000 [1:17:51<09:52,  1.26s/it]

train:   0%|          | 13/3515 [00:17<1:12:46,  1.25s/it]
overall:  88%|████████▊ | 3529/4000 [1:17:52<09:52,  1.26s/it]

train:   0%|          | 14/3515 [00:18<1:13:03,  1.25s/it]
overall:  88%|████████▊ | 3530/4000 [1:17:53<09:48,  1.25s/it]

train:   0%|          | 15/3515 [00:19<1:12:43,  1.25s/it]
overall:  88%|████████▊ | 3531/4000 [1:17:55<09:54,  1.27s/it]

train:   0%|          | 16/3515 [00:21<1:13:42,  1.26s/it]
overall:  88%|████████▊ | 3532/4000 [1:17:56<09:59,  1.28s/it]

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train:   1%|          | 18/3515 [00:23<1:14:39,  1.28s/it]
overall:  88%|████████▊ | 3534/4000 [1:17:59<09:59,  1.29s/it]

train:   1%|          | 19/3515 [00:25<1:14:51,  1.28s/it]
overall:  88%|████████▊ | 3535/4000 [1:18:00<10:07,  1.31s/it]

train:   1%|          | 20/3515 [00:26<1:16:02,  1.31s/it]
overall:  88%|████████▊ | 3536/4000 [1:18:01<10:12,  1.32s/it]

train:   1%|          | 21/3515 [00:27<1:16:48,  1.32s/it]
overall:  88%|████████▊ | 3537/4000 [1:18:03<10:13,  1.33s/it]

train:   1%|          | 22/3515 [00:29<1:17:09,  1.33s/it]
overall:  88%|████████▊ | 3538/4000 [1:18:04<10:06,  1.31s/it]

train:   1%|          | 23/3515 [00:30<1:16:27,  1.31s/it]
overall:  88%|████████▊ | 3539/4000 [1:18:05<10:10,  1.32s/it]

train:   1%|          | 24/3515 [00:31<1:17:04,  1.32s/it]
overall:  88%|████████▊ | 3540/4000 [1:18:07<10:15,  1.34s/it]

train:   1%|          | 25/3515 [00:33<1:17:47,  1.34s/it]
overall:  89%|████████▊ | 3541/4000 [1:18:08<10:09,  1.33s/it]

train:   1%|          | 26/3515 [00:34<1:17:14,  1.33s/it]
overall:  89%|████████▊ | 3542/4000 [1:18:09<09:39,  1.26s/it]

train:   1%|          | 27/3515 [00:35<1:13:29,  1.26s/it]
overall:  89%|████████▊ | 3543/4000 [1:18:10<09:41,  1.27s/it]

train:   1%|          | 28/3515 [00:36<1:13:57,  1.27s/it]
overall:  89%|████████▊ | 3544/4000 [1:18:12<09:22,  1.23s/it]

train:   1%|          | 29/3515 [00:37<1:11:38,  1.23s/it]
overall:  89%|████████▊ | 3545/4000 [1:18:13<09:40,  1.28s/it]

train:   1%|          | 30/3515 [00:39<1:14:05,  1.28s/it]
overall:  89%|████████▊ | 3546/4000 [1:18:14<09:26,  1.25s/it]

train:   1%|          | 31/3515 [00:40<1:12:25,  1.25s/it]
overall:  89%|████████▊ | 3547/4000 [1:18:15<07:34,  1.00s/it]

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overall:  89%|████████▊ | 3548/4000 [1:18:16<08:22,  1.11s/it]

train:   1%|          | 33/3515 [00:42<1:04:28,  1.11s/it]
overall:  89%|████████▊ | 3549/4000 [1:18:17<08:52,  1.18s/it]

train:   1%|          | 34/3515 [00:43<1:08:28,  1.18s/it]
overall:  89%|████████▉ | 3550/4000 [1:18:18<09:01,  1.20s/it]

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overall:  89%|████████▉ | 3551/4000 [1:18:20<08:59,  1.20s/it]

train:   1%|          | 36/3515 [00:46<1:09:39,  1.20s/it]
overall:  89%|████████▉ | 3552/4000 [1:18:21<09:11,  1.23s/it]

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overall:  89%|████████▉ | 3553/4000 [1:18:22<09:18,  1.25s/it]

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overall:  89%|████████▉ | 3554/4000 [1:18:24<09:32,  1.28s/it]

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overall:  89%|████████▉ | 3559/4000 [1:18:30<08:57,  1.22s/it]

train:   1%|▏         | 44/3515 [00:56<1:10:31,  1.22s/it]
overall:  89%|████████▉ | 3560/4000 [1:18:31<09:15,  1.26s/it]

train:   1%|▏         | 45/3515 [00:57<1:12:57,  1.26s/it]
overall:  89%|████████▉ | 3561/4000 [1:18:32<09:15,  1.27s/it]

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overall:  89%|████████▉ | 3562/4000 [1:18:33<07:53,  1.08s/it]

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overall:  89%|████████▉ | 3563/4000 [1:18:34<07:28,  1.03s/it]

train:   1%|▏         | 48/3515 [01:00<59:18,  1.03s/it]  
overall:  89%|████████▉ | 3564/4000 [1:18:35<08:15,  1.14s/it]

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overall:  89%|████████▉ | 3565/4000 [1:18:37<08:44,  1.21s/it]

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overall:  89%|████████▉ | 3566/4000 [1:18:38<08:40,  1.20s/it]

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overall:  89%|████████▉ | 3567/4000 [1:18:39<09:00,  1.25s/it]

train:   1%|▏         | 52/3515 [01:05<1:11:59,  1.25s/it]
overall:  89%|████████▉ | 3568/4000 [1:18:40<08:50,  1.23s/it]

train:   2%|▏         | 53/3515 [01:06<1:10:55,  1.23s/it]
overall:  89%|████████▉ | 3569/4000 [1:18:42<09:00,  1.26s/it]

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overall:  89%|████████▉ | 3570/4000 [1:18:43<08:49,  1.23s/it]

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overall:  89%|████████▉ | 3571/4000 [1:18:44<09:02,  1.27s/it]

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overall:  89%|████████▉ | 3572/4000 [1:18:46<09:13,  1.29s/it]

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overall:  89%|████████▉ | 3573/4000 [1:18:47<09:20,  1.31s/it]

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overall:  89%|████████▉ | 3574/4000 [1:18:48<09:25,  1.33s/it]

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overall:  89%|████████▉ | 3575/4000 [1:18:50<09:28,  1.34s/it]

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overall:  89%|████████▉ | 3576/4000 [1:18:51<09:26,  1.34s/it]

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overall:  89%|████████▉ | 3577/4000 [1:18:52<09:25,  1.34s/it]

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overall:  89%|████████▉ | 3578/4000 [1:18:54<09:14,  1.31s/it]

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overall:  90%|████████▉ | 3581/4000 [1:18:57<08:47,  1.26s/it]

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overall:  90%|████████▉ | 3584/4000 [1:19:01<08:47,  1.27s/it]

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overall:  90%|████████▉ | 3586/4000 [1:19:03<07:55,  1.15s/it]

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overall:  90%|████████▉ | 3591/4000 [1:19:10<09:01,  1.32s/it]

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overall:  90%|████████▉ | 3599/4000 [1:19:20<08:48,  1.32s/it]

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overall:  90%|█████████ | 3600/4000 [1:19:22<09:03,  1.36s/it]

train:   2%|▏         | 85/3515 [01:48<1:17:43,  1.36s/it]
overall:  90%|█████████ | 3601/4000 [1:19:23<09:01,  1.36s/it]

train:   2%|▏         | 86/3515 [01:49<1:17:32,  1.36s/it]
overall:  90%|█████████ | 3602/4000 [1:19:24<08:40,  1.31s/it]

train:   2%|▏         | 87/3515 [01:50<1:14:40,  1.31s/it]
overall:  90%|█████████ | 3603/4000 [1:19:26<08:39,  1.31s/it]

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train:   3%|▎         | 89/3515 [01:53<1:12:15,  1.27s/it]
overall:  90%|█████████ | 3605/4000 [1:19:28<08:16,  1.26s/it]

train:   3%|▎         | 90/3515 [01:54<1:11:48,  1.26s/it]
overall:  90%|█████████ | 3606/4000 [1:19:29<08:09,  1.24s/it]

train:   3%|▎         | 91/3515 [01:55<1:10:50,  1.24s/it]
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train:   3%|▎         | 92/3515 [01:57<1:11:28,  1.25s/it]
overall:  90%|█████████ | 3608/4000 [1:19:32<08:22,  1.28s/it]

train:   3%|▎         | 93/3515 [01:58<1:13:09,  1.28s/it]
overall:  90%|█████████ | 3609/4000 [1:19:32<06:37,  1.02s/it]

train:   3%|▎         | 94/3515 [01:58<57:58,  1.02s/it]  
overall:  90%|█████████ | 3610/4000 [1:19:33<06:34,  1.01s/it]

train:   3%|▎         | 95/3515 [01:59<57:40,  1.01s/it]
overall:  90%|█████████ | 3611/4000 [1:19:35<06:55,  1.07s/it]

train:   3%|▎         | 96/3515 [02:00<1:00:48,  1.07s/it]
overall:  90%|█████████ | 3612/4000 [1:19:36<07:06,  1.10s/it]

train:   3%|▎         | 97/3515 [02:02<1:02:40,  1.10s/it]
overall:  90%|█████████ | 3613/4000 [1:19:37<07:16,  1.13s/it]

train:   3%|▎         | 98/3515 [02:03<1:04:16,  1.13s/it]
overall:  90%|█████████ | 3614/4000 [1:19:38<07:23,  1.15s/it]

train:   3%|▎         | 99/3515 [02:04<1:05:23,  1.15s/it]
overall:  90%|█████████ | 3615/4000 [1:19:39<07:34,  1.18s/it]

train:   3%|▎         | 100/3515 [02:05<1:07:13,  1.18s/it]
overall:  90%|█████████ | 3616/4000 [1:19:41<07:45,  1.21s/it]

train:   3%|▎         | 101/3515 [02:07<1:09:00,  1.21s/it]
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train:   3%|▎         | 102/3515 [02:08<1:10:39,  1.24s/it]
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train:   3%|▎         | 103/3515 [02:09<1:12:21,  1.27s/it]
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train:   3%|▎         | 104/3515 [02:10<1:01:34,  1.08s/it]
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train:   3%|▎         | 105/3515 [02:10<53:08,  1.07it/s]  
overall:  91%|█████████ | 3621/4000 [1:19:45<04:38,  1.36it/s]

train:   3%|▎         | 106/3515 [02:11<41:45,  1.36it/s]
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train:   3%|▎         | 107/3515 [02:12<50:26,  1.13it/s]
overall:  91%|█████████ | 3623/4000 [1:19:47<06:28,  1.03s/it]

train:   3%|▎         | 108/3515 [02:13<58:32,  1.03s/it]
overall:  91%|█████████ | 3624/4000 [1:19:49<06:47,  1.08s/it]

train:   3%|▎         | 109/3515 [02:15<1:01:29,  1.08s/it]
overall:  91%|█████████ | 3625/4000 [1:19:49<05:40,  1.10it/s]

train:   3%|▎         | 110/3515 [02:15<51:29,  1.10it/s]  
overall:  91%|█████████ | 3626/4000 [1:19:50<06:30,  1.04s/it]

train:   3%|▎         | 111/3515 [02:16<59:12,  1.04s/it]
overall:  91%|█████████ | 3627/4000 [1:19:52<06:48,  1.09s/it]

train:   3%|▎         | 112/3515 [02:18<1:02:03,  1.09s/it]
overall:  91%|█████████ | 3628/4000 [1:19:53<07:16,  1.17s/it]

train:   3%|▎         | 113/3515 [02:19<1:06:28,  1.17s/it]
overall:  91%|█████████ | 3629/4000 [1:19:54<07:27,  1.21s/it]

train:   3%|▎         | 114/3515 [02:20<1:08:26,  1.21s/it]
overall:  91%|█████████ | 3630/4000 [1:19:55<05:46,  1.07it/s]

train:   3%|▎         | 115/3515 [02:21<53:05,  1.07it/s]  
overall:  91%|█████████ | 3631/4000 [1:19:56<06:23,  1.04s/it]

train:   3%|▎         | 116/3515 [02:22<58:56,  1.04s/it]
overall:  91%|█████████ | 3632/4000 [1:19:57<06:45,  1.10s/it]

train:   3%|▎         | 117/3515 [02:23<1:02:28,  1.10s/it]
overall:  91%|█████████ | 3633/4000 [1:19:58<06:30,  1.06s/it]

train:   3%|▎         | 118/3515 [02:24<1:00:10,  1.06s/it]
overall:  91%|█████████ | 3634/4000 [1:19:59<06:49,  1.12s/it]

train:   3%|▎         | 119/3515 [02:25<1:03:16,  1.12s/it]
overall:  91%|█████████ | 3635/4000 [1:20:00<06:36,  1.09s/it]

train:   3%|▎         | 120/3515 [02:26<1:01:29,  1.09s/it]
overall:  91%|█████████ | 3636/4000 [1:20:02<07:02,  1.16s/it]

train:   3%|▎         | 121/3515 [02:28<1:05:38,  1.16s/it]
overall:  91%|█████████ | 3637/4000 [1:20:03<06:55,  1.14s/it]

train:   3%|▎         | 122/3515 [02:29<1:04:43,  1.14s/it]
overall:  91%|█████████ | 3638/4000 [1:20:04<07:04,  1.17s/it]

train:   3%|▎         | 123/3515 [02:30<1:06:20,  1.17s/it]
overall:  91%|█████████ | 3639/4000 [1:20:05<07:23,  1.23s/it]

train:   4%|▎         | 124/3515 [02:31<1:09:30,  1.23s/it]
overall:  91%|█████████ | 3640/4000 [1:20:07<07:10,  1.20s/it]

train:   4%|▎         | 125/3515 [02:32<1:07:38,  1.20s/it]
overall:  91%|█████████ | 3641/4000 [1:20:07<05:49,  1.03it/s]

train:   4%|▎         | 126/3515 [02:33<54:55,  1.03it/s]  
overall:  91%|█████████ | 3642/4000 [1:20:08<06:23,  1.07s/it]

train:   4%|▎         | 127/3515 [02:34<1:00:27,  1.07s/it]
overall:  91%|█████████ | 3643/4000 [1:20:09<06:24,  1.08s/it]

train:   4%|▎         | 128/3515 [02:35<1:00:51,  1.08s/it]
overall:  91%|█████████ | 3644/4000 [1:20:11<06:46,  1.14s/it]

train:   4%|▎         | 129/3515 [02:37<1:04:26,  1.14s/it]
overall:  91%|█████████ | 3645/4000 [1:20:12<06:33,  1.11s/it]

train:   4%|▎         | 130/3515 [02:38<1:02:35,  1.11s/it]
overall:  91%|█████████ | 3646/4000 [1:20:13<06:56,  1.18s/it]

train:   4%|▎         | 131/3515 [02:39<1:06:26,  1.18s/it]
overall:  91%|█████████ | 3647/4000 [1:20:14<06:54,  1.17s/it]

train:   4%|▍         | 132/3515 [02:40<1:06:10,  1.17s/it]
overall:  91%|█████████ | 3648/4000 [1:20:16<07:18,  1.25s/it]

train:   4%|▍         | 133/3515 [02:42<1:10:17,  1.25s/it]
overall:  91%|█████████ | 3649/4000 [1:20:17<07:17,  1.25s/it]

train:   4%|▍         | 134/3515 [02:43<1:10:11,  1.25s/it]
overall:  91%|█████████▏| 3650/4000 [1:20:18<07:16,  1.25s/it]

train:   4%|▍         | 135/3515 [02:44<1:10:16,  1.25s/it]
overall:  91%|█████████▏| 3651/4000 [1:20:19<07:22,  1.27s/it]

train:   4%|▍         | 136/3515 [02:45<1:11:26,  1.27s/it]
overall:  91%|█████████▏| 3652/4000 [1:20:21<07:04,  1.22s/it]

train:   4%|▍         | 137/3515 [02:46<1:08:37,  1.22s/it]
overall:  91%|█████████▏| 3653/4000 [1:20:22<07:11,  1.24s/it]

train:   4%|▍         | 138/3515 [02:48<1:10:01,  1.24s/it]
overall:  91%|█████████▏| 3654/4000 [1:20:23<07:16,  1.26s/it]

train:   4%|▍         | 139/3515 [02:49<1:10:59,  1.26s/it]
overall:  91%|█████████▏| 3655/4000 [1:20:24<07:16,  1.26s/it]

train:   4%|▍         | 140/3515 [02:50<1:11:05,  1.26s/it]
overall:  91%|█████████▏| 3656/4000 [1:20:26<07:07,  1.24s/it]

train:   4%|▍         | 141/3515 [02:52<1:09:52,  1.24s/it]
overall:  91%|█████████▏| 3657/4000 [1:20:27<06:52,  1.20s/it]

train:   4%|▍         | 142/3515 [02:53<1:07:37,  1.20s/it]
overall:  91%|█████████▏| 3658/4000 [1:20:28<07:06,  1.25s/it]

train:   4%|▍         | 143/3515 [02:54<1:10:02,  1.25s/it]
overall:  91%|█████████▏| 3659/4000 [1:20:29<07:05,  1.25s/it]

train:   4%|▍         | 144/3515 [02:55<1:10:02,  1.25s/it]
overall:  92%|█████████▏| 3660/4000 [1:20:31<07:15,  1.28s/it]

train:   4%|▍         | 145/3515 [02:57<1:11:57,  1.28s/it]
overall:  92%|█████████▏| 3661/4000 [1:20:32<07:24,  1.31s/it]

train:   4%|▍         | 146/3515 [02:58<1:13:41,  1.31s/it]
overall:  92%|█████████▏| 3662/4000 [1:20:32<05:40,  1.01s/it]

train:   4%|▍         | 147/3515 [02:58<56:29,  1.01s/it]  
overall:  92%|█████████▏| 3663/4000 [1:20:33<04:38,  1.21it/s]

train:   4%|▍         | 148/3515 [02:59<46:22,  1.21it/s]
overall:  92%|█████████▏| 3664/4000 [1:20:34<05:20,  1.05it/s]

train:   4%|▍         | 149/3515 [03:00<53:27,  1.05it/s]
overall:  92%|█████████▏| 3665/4000 [1:20:35<05:50,  1.05s/it]

train:   4%|▍         | 150/3515 [03:01<58:43,  1.05s/it]
overall:  92%|█████████▏| 3666/4000 [1:20:37<06:20,  1.14s/it]

train:   4%|▍         | 151/3515 [03:03<1:03:48,  1.14s/it]
overall:  92%|█████████▏| 3667/4000 [1:20:38<06:40,  1.20s/it]

train:   4%|▍         | 152/3515 [03:04<1:07:27,  1.20s/it]
overall:  92%|█████████▏| 3668/4000 [1:20:39<06:42,  1.21s/it]

train:   4%|▍         | 153/3515 [03:05<1:08:00,  1.21s/it]
overall:  92%|█████████▏| 3669/4000 [1:20:41<06:55,  1.25s/it]

train:   4%|▍         | 154/3515 [03:07<1:10:17,  1.25s/it]
overall:  92%|█████████▏| 3670/4000 [1:20:42<07:01,  1.28s/it]

train:   4%|▍         | 155/3515 [03:08<1:11:35,  1.28s/it]
overall:  92%|█████████▏| 3671/4000 [1:20:43<07:06,  1.30s/it]

train:   4%|▍         | 156/3515 [03:09<1:12:34,  1.30s/it]
overall:  92%|█████████▏| 3672/4000 [1:20:45<07:09,  1.31s/it]

train:   4%|▍         | 157/3515 [03:11<1:13:12,  1.31s/it]
overall:  92%|█████████▏| 3673/4000 [1:20:46<07:13,  1.32s/it]

train:   4%|▍         | 158/3515 [03:12<1:14:06,  1.32s/it]
overall:  92%|█████████▏| 3674/4000 [1:20:47<07:13,  1.33s/it]

train:   5%|▍         | 159/3515 [03:13<1:14:22,  1.33s/it]
overall:  92%|█████████▏| 3675/4000 [1:20:48<06:57,  1.28s/it]

train:   5%|▍         | 160/3515 [03:14<1:11:45,  1.28s/it]
overall:  92%|█████████▏| 3676/4000 [1:20:50<07:01,  1.30s/it]

train:   5%|▍         | 161/3515 [03:16<1:12:46,  1.30s/it]
overall:  92%|█████████▏| 3677/4000 [1:20:51<06:23,  1.19s/it]

train:   5%|▍         | 162/3515 [03:17<1:06:23,  1.19s/it]
overall:  92%|█████████▏| 3678/4000 [1:20:52<06:20,  1.18s/it]

train:   5%|▍         | 163/3515 [03:18<1:06:05,  1.18s/it]
overall:  92%|█████████▏| 3679/4000 [1:20:53<05:30,  1.03s/it]

train:   5%|▍         | 164/3515 [03:19<57:28,  1.03s/it]  
overall:  92%|█████████▏| 3680/4000 [1:20:54<05:48,  1.09s/it]

train:   5%|▍         | 165/3515 [03:20<1:00:53,  1.09s/it]
overall:  92%|█████████▏| 3681/4000 [1:20:55<06:06,  1.15s/it]

train:   5%|▍         | 166/3515 [03:21<1:04:06,  1.15s/it]
overall:  92%|█████████▏| 3682/4000 [1:20:56<06:10,  1.17s/it]

train:   5%|▍         | 167/3515 [03:22<1:05:05,  1.17s/it]
overall:  92%|█████████▏| 3683/4000 [1:20:58<06:20,  1.20s/it]

train:   5%|▍         | 168/3515 [03:24<1:06:57,  1.20s/it]
overall:  92%|█████████▏| 3684/4000 [1:20:59<06:29,  1.23s/it]

train:   5%|▍         | 169/3515 [03:25<1:08:47,  1.23s/it]
overall:  92%|█████████▏| 3685/4000 [1:21:00<06:38,  1.27s/it]

train:   5%|▍         | 170/3515 [03:26<1:10:32,  1.27s/it]
overall:  92%|█████████▏| 3686/4000 [1:21:02<06:47,  1.30s/it]

train:   5%|▍         | 171/3515 [03:28<1:12:23,  1.30s/it]
overall:  92%|█████████▏| 3687/4000 [1:21:03<06:41,  1.28s/it]

train:   5%|▍         | 172/3515 [03:29<1:11:30,  1.28s/it]
overall:  92%|█████████▏| 3688/4000 [1:21:04<06:41,  1.29s/it]

train:   5%|▍         | 173/3515 [03:30<1:11:44,  1.29s/it]
overall:  92%|█████████▏| 3689/4000 [1:21:05<06:36,  1.27s/it]

train:   5%|▍         | 174/3515 [03:31<1:10:57,  1.27s/it]
overall:  92%|█████████▏| 3690/4000 [1:21:07<06:36,  1.28s/it]

train:   5%|▍         | 175/3515 [03:33<1:11:10,  1.28s/it]
overall:  92%|█████████▏| 3691/4000 [1:21:08<06:35,  1.28s/it]

train:   5%|▌         | 176/3515 [03:34<1:11:13,  1.28s/it]
overall:  92%|█████████▏| 3692/4000 [1:21:09<05:59,  1.17s/it]

train:   5%|▌         | 177/3515 [03:35<1:05:00,  1.17s/it]
overall:  92%|█████████▏| 3693/4000 [1:21:09<04:52,  1.05it/s]

train:   5%|▌         | 178/3515 [03:35<53:02,  1.05it/s]  
overall:  92%|█████████▏| 3694/4000 [1:21:11<05:23,  1.06s/it]

train:   5%|▌         | 179/3515 [03:37<58:47,  1.06s/it]
overall:  92%|█████████▏| 3695/4000 [1:21:12<05:49,  1.14s/it]

train:   5%|▌         | 180/3515 [03:38<1:03:37,  1.14s/it]
overall:  92%|█████████▏| 3696/4000 [1:21:13<06:11,  1.22s/it]

train:   5%|▌         | 181/3515 [03:39<1:07:55,  1.22s/it]
overall:  92%|█████████▏| 3697/4000 [1:21:14<05:13,  1.03s/it]

train:   5%|▌         | 182/3515 [03:40<57:24,  1.03s/it]  
overall:  92%|█████████▏| 3698/4000 [1:21:15<05:26,  1.08s/it]

train:   5%|▌         | 183/3515 [03:41<1:00:01,  1.08s/it]
overall:  92%|█████████▏| 3699/4000 [1:21:16<05:44,  1.14s/it]

train:   5%|▌         | 184/3515 [03:42<1:03:31,  1.14s/it]
overall:  92%|█████████▎| 3700/4000 [1:21:18<05:55,  1.19s/it]

train:   5%|▌         | 185/3515 [03:44<1:05:47,  1.19s/it]
overall:  93%|█████████▎| 3701/4000 [1:21:18<04:45,  1.05it/s]

train:   5%|▌         | 186/3515 [03:44<52:57,  1.05it/s]  
overall:  93%|█████████▎| 3702/4000 [1:21:19<05:10,  1.04s/it]

train:   5%|▌         | 187/3515 [03:45<57:44,  1.04s/it]
overall:  93%|█████████▎| 3703/4000 [1:21:21<05:27,  1.10s/it]

train:   5%|▌         | 188/3515 [03:47<1:01:09,  1.10s/it]
overall:  93%|█████████▎| 3704/4000 [1:21:22<05:27,  1.11s/it]

train:   5%|▌         | 189/3515 [03:48<1:01:15,  1.11s/it]
overall:  93%|█████████▎| 3705/4000 [1:21:23<05:49,  1.18s/it]

train:   5%|▌         | 190/3515 [03:49<1:05:36,  1.18s/it]
overall:  93%|█████████▎| 3706/4000 [1:21:24<05:56,  1.21s/it]

train:   5%|▌         | 191/3515 [03:50<1:07:06,  1.21s/it]
overall:  93%|█████████▎| 3707/4000 [1:21:26<06:05,  1.25s/it]

train:   5%|▌         | 192/3515 [03:52<1:09:10,  1.25s/it]
overall:  93%|█████████▎| 3708/4000 [1:21:27<06:11,  1.27s/it]

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train:  14%|█▍        | 484/3515 [09:39<58:54,  1.17s/it]train loss: 7.355228424072266
train per: 0.731444091914239
train loss: 9.292210578918457
train per: 0.7673556289172767
train loss: 6.1721673011779785
train per: 0.6506327144487086
train loss: 6.312180042266846
train per: 0.6977963073257891
train loss: 4.811734199523926
train per: 0.6470421181405103
train loss: 6.569314479827881
train per: 0.7275390885118398
train loss: 11.811561584472656
train per: 0.7901775053729205
train loss: 9.275663375854492
train per: 0.7018444343175113
train loss: 13.406227111816406
train per: 0.7539961013645224
train loss: 8.824792861938477
train per: 0.688322211630124
train loss: 7.762358665466309
train per: 0.6946839411683342
train loss: 5.7485504150390625
train per: 0.6708173368357244
train loss: 5.549050807952881
train per: 0.6764123648545759
train loss: 5.132309913635254
train per: 0.6804897409376278
train loss: 6.264461517333984
train per: 0.7184341566829364
train loss: 6.134756565093994
train per: 0.6848132067369627
train loss: 5.3713788986206055
train per: 0.6555259975816203
train loss: 6.550406455993652
train per: 0.6844755703377524
train loss: 13.173754692077637
train per: 0.7514104276253032
train loss: 9.885139465332031
train per: 0.6913175099849908
train loss: 6.791400909423828
train per: 0.6660996172416381
train loss: 5.106246471405029
train per: 0.6486065741118824
train loss: 4.875447750091553
train per: 0.6556963998129773
train loss: 4.654454708099365
train per: 0.6615113011910386
train loss: 5.446581840515137
train per: 0.6902650250417363
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  19%|█▊        | 505/2703 [00:00<00:00, 5042.30it/s]


word -> phonemes:  41%|████      | 1113/2703 [00:00<00:00, 5652.19it/s]


word -> phonemes:  62%|██████▏   | 1686/2703 [00:00<00:00, 5624.70it/s]


word -> phonemes:  83%|████████▎ | 2249/2703 [00:00<00:00, 5548.66it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 5559.62it/s]



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overall: 100%|█████████▉| 3999/4000 [1:30:06<00:01,  1.17s/it]

train:  14%|█▍        | 484/3515 [12:32<58:54,  1.17s/it]
                                                              

                                                         

overall: 100%|█████████▉| 3999/4000 [1:30:06<00:01,  1.17s/it]

train:  14%|█▍        | 484/3515 [12:32<58:54,  1.17s/it]
                                                              

                                                         

overall: 100%|█████████▉| 3999/4000 [1:30:06<00:01,  1.17s/it]

train:  14%|█▍        | 484/3515 [12:32<58:54,  1.17s/it]
overall: 100%|██████████| 4000/4000 [1:30:06<00:00, 52.68s/it]

train:  14%|█▍        | 485/3515 [12:32<44:20:14, 52.68s/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 [12:32<1:18:21,  1.55s/it] 

overall: 100%|██████████| 4000/4000 [1:30:06<00:00,  1.35s/it]
dev loss: 6.136473178863525
dev per: 0.6989802289281998
[Runner] - Save the checkpoint to:
1. result/downstream/grid/dev-best.ckpt
2. result/downstream/grid/states-4000.ckpt