/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")
2023-10-11 21:13:49 | WARNING | root | Pytorch pre-release version 2.1.0.dev20230831+cu118 - assuming intent to test it
/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.original0', 'encoder.pos_conv_embed.conv.parametrizations.weight.original1']
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
mert_330M_encode {'model_config': None, 'refresh': False}
using suno's k-means clusters: mert_330M_encode

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:  13%|█▎        | 464/3515 [00:00<00:00, 4638.43it/s]

word -> phonemes:  26%|██▋       | 928/3515 [00:00<00:00, 4435.83it/s]

word -> phonemes:  40%|███▉      | 1391/3515 [00:00<00:00, 4520.75it/s]

word -> phonemes:  52%|█████▏    | 1844/3515 [00:00<00:00, 4500.98it/s]

word -> phonemes:  66%|██████▌   | 2316/3515 [00:00<00:00, 4578.43it/s]

word -> phonemes:  79%|███████▉  | 2775/3515 [00:00<00:00, 4440.00it/s]

word -> phonemes:  92%|█████████▏| 3238/3515 [00:00<00:00, 4499.91it/s]
word -> phonemes: 100%|██████████| 3515/3515 [00:00<00:00, 4492.12it/s]


train:   0%|          | 0/3515 [00:00<?, ?it/s]
overall:   0%|          | 1/4000 [00:04<4:29:10,  4.04s/it]

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overall:   0%|          | 2/4000 [00:05<2:37:34,  2.36s/it]

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overall:   0%|          | 3/4000 [00:06<2:01:44,  1.83s/it]

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overall:   0%|          | 4/4000 [00:07<1:45:13,  1.58s/it]

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overall:   0%|          | 5/4000 [00:08<1:36:29,  1.45s/it]

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overall:   0%|          | 6/4000 [00:09<1:28:47,  1.33s/it]

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overall:   0%|          | 7/4000 [00:11<1:29:17,  1.34s/it]

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overall:   0%|          | 8/4000 [00:12<1:26:19,  1.30s/it]

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overall:   0%|          | 9/4000 [00:13<1:26:07,  1.29s/it]

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overall:   0%|          | 10/4000 [00:14<1:08:19,  1.03s/it]

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overall:   0%|          | 11/4000 [00:14<53:03,  1.25it/s]  

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overall:   0%|          | 12/4000 [00:15<1:01:22,  1.08it/s]

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overall:   0%|          | 13/4000 [00:16<1:04:35,  1.03it/s]

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overall:   0%|          | 14/4000 [00:18<1:09:20,  1.04s/it]

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overall:   0%|          | 15/4000 [00:19<1:09:37,  1.05s/it]

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overall:   0%|          | 16/4000 [00:20<1:13:11,  1.10s/it]

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overall:   0%|          | 17/4000 [00:21<1:14:09,  1.12s/it]

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overall:   0%|          | 18/4000 [00:22<1:18:37,  1.18s/it]

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overall:   0%|          | 20/4000 [00:24<1:08:57,  1.04s/it]

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overall:   1%|          | 21/4000 [00:25<1:13:56,  1.11s/it]

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overall:   1%|          | 22/4000 [00:27<1:17:18,  1.17s/it]

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overall:   1%|          | 23/4000 [00:28<1:19:23,  1.20s/it]

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overall:   1%|          | 24/4000 [00:29<1:17:34,  1.17s/it]

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overall:   1%|          | 25/4000 [00:30<1:17:07,  1.16s/it]

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overall:   1%|          | 26/4000 [00:31<1:19:12,  1.20s/it]

train:   1%|          | 26/3515 [00:29<1:09:32,  1.20s/it]
overall:   1%|          | 27/4000 [00:33<1:20:32,  1.22s/it]

train:   1%|          | 27/3515 [00:31<1:10:42,  1.22s/it]
overall:   1%|          | 28/4000 [00:34<1:19:01,  1.19s/it]

train:   1%|          | 28/3515 [00:32<1:09:22,  1.19s/it]
overall:   1%|          | 29/4000 [00:35<1:18:43,  1.19s/it]

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overall:   1%|          | 30/4000 [00:36<1:20:56,  1.22s/it]

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overall:   1%|          | 31/4000 [00:38<1:22:57,  1.25s/it]

train:   1%|          | 31/3515 [00:36<1:12:49,  1.25s/it]
overall:   1%|          | 32/4000 [00:39<1:22:15,  1.24s/it]

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overall:   1%|          | 33/4000 [00:40<1:22:49,  1.25s/it]

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overall:   1%|          | 34/4000 [00:40<1:03:26,  1.04it/s]

train:   1%|          | 34/3515 [00:38<55:40,  1.04it/s]  
overall:   1%|          | 35/4000 [00:42<1:09:37,  1.05s/it]

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overall:   1%|          | 36/4000 [00:43<1:13:44,  1.12s/it]

train:   1%|          | 36/3515 [00:41<1:04:42,  1.12s/it]
overall:   1%|          | 37/4000 [00:44<1:13:50,  1.12s/it]

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overall:   1%|          | 38/4000 [00:45<1:14:44,  1.13s/it]

train:   1%|          | 38/3515 [00:43<1:05:35,  1.13s/it]
overall:   1%|          | 39/4000 [00:46<1:13:42,  1.12s/it]

train:   1%|          | 39/3515 [00:44<1:04:41,  1.12s/it]
overall:   1%|          | 40/4000 [00:47<1:06:27,  1.01s/it]

train:   1%|          | 40/3515 [00:45<58:18,  1.01s/it]  
overall:   1%|          | 41/4000 [00:48<1:09:38,  1.06s/it]

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overall:   1%|          | 42/4000 [00:49<1:14:16,  1.13s/it]

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overall:   1%|          | 43/4000 [00:51<1:14:43,  1.13s/it]

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overall:   1%|          | 45/4000 [00:52<1:04:45,  1.02it/s]

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overall:   1%|          | 46/4000 [00:53<54:00,  1.22it/s]  

train:   1%|▏         | 46/3515 [00:51<47:23,  1.22it/s]
overall:   1%|          | 47/4000 [00:54<1:01:23,  1.07it/s]

train:   1%|▏         | 47/3515 [00:52<53:51,  1.07it/s]
overall:   1%|          | 48/4000 [00:55<1:02:51,  1.05it/s]

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overall:   1%|▏         | 50/4000 [00:57<1:10:40,  1.07s/it]

train:   1%|▏         | 50/3515 [00:56<1:01:59,  1.07s/it]
overall:   1%|▏         | 51/4000 [00:58<1:11:26,  1.09s/it]

train:   1%|▏         | 51/3515 [00:57<1:02:40,  1.09s/it]
overall:   1%|▏         | 52/4000 [01:00<1:14:33,  1.13s/it]

train:   1%|▏         | 52/3515 [00:58<1:05:23,  1.13s/it]
overall:   1%|▏         | 53/4000 [01:01<1:15:49,  1.15s/it]

train:   2%|▏         | 53/3515 [00:59<1:06:30,  1.15s/it]
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overall:   1%|▏         | 55/4000 [01:03<1:17:44,  1.18s/it]

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overall:   1%|▏         | 56/4000 [01:05<1:18:16,  1.19s/it]

train:   2%|▏         | 56/3515 [01:03<1:08:39,  1.19s/it]
overall:   1%|▏         | 57/4000 [01:06<1:21:21,  1.24s/it]

train:   2%|▏         | 57/3515 [01:04<1:11:21,  1.24s/it]
overall:   1%|▏         | 58/4000 [01:07<1:22:23,  1.25s/it]

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overall:   1%|▏         | 59/4000 [01:08<1:21:27,  1.24s/it]

train:   2%|▏         | 59/3515 [01:07<1:11:26,  1.24s/it]
overall:   2%|▏         | 60/4000 [01:10<1:20:11,  1.22s/it]

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overall:   2%|▏         | 61/4000 [01:11<1:17:59,  1.19s/it]

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overall:   2%|▏         | 63/4000 [01:13<1:13:38,  1.12s/it]

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overall:   2%|▏         | 65/4000 [01:15<1:14:46,  1.14s/it]

train:   2%|▏         | 65/3515 [01:13<1:05:33,  1.14s/it]
overall:   2%|▏         | 66/4000 [01:16<1:17:33,  1.18s/it]

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overall:   2%|▏         | 70/4000 [01:20<1:07:07,  1.02s/it]

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overall:  11%|█         | 427/4000 [08:10<1:03:17,  1.06s/it]

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overall:  12%|█▏        | 497/4000 [09:27<1:06:12,  1.13s/it]

train:  14%|█▍        | 497/3515 [09:25<57:02,  1.13s/it]
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overall:  12%|█▏        | 499/4000 [09:30<1:04:59,  1.11s/it]

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overall:  13%|█▎        | 518/4000 [09:51<57:35,  1.01it/s]  

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train:  15%|█▍        | 527/3515 [10:01<1:01:27,  1.23s/it]
overall:  13%|█▎        | 528/4000 [10:03<54:00,  1.07it/s]  

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overall:  13%|█▎        | 529/4000 [10:04<59:33,  1.03s/it]

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overall:  14%|█▎        | 545/4000 [10:21<1:06:24,  1.15s/it]

train:  16%|█▌        | 545/3515 [10:19<57:05,  1.15s/it]
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train:  16%|█▌        | 547/3515 [10:22<58:55,  1.19s/it]
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overall:  14%|█▍        | 550/4000 [10:27<1:10:22,  1.22s/it]

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overall:  14%|█▍        | 552/4000 [10:29<1:01:37,  1.07s/it]

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overall:  14%|█▍        | 565/4000 [10:43<54:04,  1.06it/s]  

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overall:  14%|█▍        | 566/4000 [10:44<59:04,  1.03s/it]

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overall:  14%|█▍        | 568/4000 [10:46<48:19,  1.18it/s]  

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train:  16%|█▌        | 570/3515 [10:47<51:50,  1.06s/it]
overall:  14%|█▍        | 571/4000 [10:50<1:04:21,  1.13s/it]

train:  16%|█▌        | 571/3515 [10:48<55:15,  1.13s/it]
overall:  14%|█▍        | 572/4000 [10:51<1:06:02,  1.16s/it]

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overall:  14%|█▍        | 573/4000 [10:52<1:08:28,  1.20s/it]

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overall:  14%|█▍        | 574/4000 [10:53<1:08:44,  1.20s/it]

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overall:  14%|█▍        | 575/4000 [10:55<1:10:03,  1.23s/it]

train:  16%|█▋        | 575/3515 [10:53<1:00:07,  1.23s/it]
overall:  14%|█▍        | 576/4000 [10:56<1:09:55,  1.23s/it]

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overall:  14%|█▍        | 577/4000 [10:57<1:08:34,  1.20s/it]

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overall:  14%|█▍        | 578/4000 [10:58<1:09:46,  1.22s/it]

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overall:  14%|█▍        | 579/4000 [10:59<59:47,  1.05s/it]  

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overall:  14%|█▍        | 580/4000 [11:00<1:02:04,  1.09s/it]

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overall:  15%|█▍        | 581/4000 [11:01<1:01:47,  1.08s/it]

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overall:  15%|█▍        | 582/4000 [11:02<1:02:31,  1.10s/it]

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overall:  15%|█▍        | 583/4000 [11:04<1:07:01,  1.18s/it]

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overall:  15%|█▍        | 584/4000 [11:05<1:04:49,  1.14s/it]

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overall:  15%|█▍        | 585/4000 [11:06<1:07:17,  1.18s/it]

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overall:  15%|█▍        | 586/4000 [11:07<1:08:42,  1.21s/it]

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overall:  15%|█▍        | 588/4000 [11:10<1:09:34,  1.22s/it]

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overall:  15%|█▍        | 589/4000 [11:11<1:07:37,  1.19s/it]

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overall:  15%|█▍        | 590/4000 [11:12<58:14,  1.02s/it]  

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overall:  15%|█▍        | 591/4000 [11:13<1:02:37,  1.10s/it]

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overall:  15%|█▍        | 592/4000 [11:14<1:04:43,  1.14s/it]

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overall:  15%|█▍        | 593/4000 [11:15<1:04:15,  1.13s/it]

train:  17%|█▋        | 593/3515 [11:13<55:06,  1.13s/it]
overall:  15%|█▍        | 594/4000 [11:16<1:06:03,  1.16s/it]

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overall:  15%|█▍        | 595/4000 [11:18<1:06:40,  1.17s/it]

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overall:  15%|█▍        | 597/4000 [11:20<58:10,  1.03s/it]  

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overall:  15%|█▍        | 598/4000 [11:21<1:01:35,  1.09s/it]

train:  17%|█▋        | 598/3515 [11:19<52:48,  1.09s/it]
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overall:  15%|█▌        | 601/4000 [11:24<56:21,  1.01it/s]

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overall:  15%|█▌        | 602/4000 [11:25<1:00:28,  1.07s/it]

train:  17%|█▋        | 602/3515 [11:23<51:50,  1.07s/it]
overall:  15%|█▌        | 603/4000 [11:26<1:02:50,  1.11s/it]

train:  17%|█▋        | 603/3515 [11:24<53:52,  1.11s/it]
overall:  15%|█▌        | 604/4000 [11:27<1:03:55,  1.13s/it]

train:  17%|█▋        | 604/3515 [11:25<54:47,  1.13s/it]
overall:  15%|█▌        | 605/4000 [11:29<1:06:33,  1.18s/it]

train:  17%|█▋        | 605/3515 [11:27<57:02,  1.18s/it]
overall:  15%|█▌        | 606/4000 [11:30<1:04:39,  1.14s/it]

train:  17%|█▋        | 606/3515 [11:28<55:25,  1.14s/it]
overall:  15%|█▌        | 607/4000 [11:31<1:01:10,  1.08s/it]

train:  17%|█▋        | 607/3515 [11:29<52:25,  1.08s/it]
overall:  15%|█▌        | 608/4000 [11:32<1:03:32,  1.12s/it]

train:  17%|█▋        | 608/3515 [11:30<54:27,  1.12s/it]
overall:  15%|█▌        | 609/4000 [11:33<1:04:36,  1.14s/it]

train:  17%|█▋        | 609/3515 [11:31<55:21,  1.14s/it]
overall:  15%|█▌        | 610/4000 [11:34<1:05:53,  1.17s/it]

train:  17%|█▋        | 610/3515 [11:32<56:27,  1.17s/it]
overall:  15%|█▌        | 611/4000 [11:35<53:51,  1.05it/s]  

train:  17%|█▋        | 611/3515 [11:33<46:09,  1.05it/s]
overall:  15%|█▌        | 612/4000 [11:35<48:10,  1.17it/s]

train:  17%|█▋        | 612/3515 [11:33<41:16,  1.17it/s]
overall:  15%|█▌        | 613/4000 [11:36<54:09,  1.04it/s]

train:  17%|█▋        | 613/3515 [11:35<46:23,  1.04it/s]
overall:  15%|█▌        | 614/4000 [11:38<59:31,  1.05s/it]

train:  17%|█▋        | 614/3515 [11:36<51:00,  1.05s/it]
overall:  15%|█▌        | 615/4000 [11:39<1:02:20,  1.11s/it]

train:  17%|█▋        | 615/3515 [11:37<53:24,  1.11s/it]
overall:  15%|█▌        | 616/4000 [11:40<1:02:42,  1.11s/it]

train:  18%|█▊        | 616/3515 [11:38<53:43,  1.11s/it]
overall:  15%|█▌        | 617/4000 [11:41<1:05:40,  1.16s/it]

train:  18%|█▊        | 617/3515 [11:40<56:15,  1.16s/it]
overall:  15%|█▌        | 618/4000 [11:43<1:08:12,  1.21s/it]

train:  18%|█▊        | 618/3515 [11:41<58:25,  1.21s/it]
overall:  15%|█▌        | 619/4000 [11:44<1:07:27,  1.20s/it]

train:  18%|█▊        | 619/3515 [11:42<57:47,  1.20s/it]
overall:  16%|█▌        | 620/4000 [11:45<1:07:52,  1.20s/it]

train:  18%|█▊        | 620/3515 [11:43<58:08,  1.20s/it]
overall:  16%|█▌        | 621/4000 [11:46<1:08:30,  1.22s/it]

train:  18%|█▊        | 621/3515 [11:45<58:40,  1.22s/it]
overall:  16%|█▌        | 622/4000 [11:48<1:08:21,  1.21s/it]

train:  18%|█▊        | 622/3515 [11:46<58:32,  1.21s/it]
overall:  16%|█▌        | 623/4000 [11:49<1:08:51,  1.22s/it]

train:  18%|█▊        | 623/3515 [11:47<58:58,  1.22s/it]
overall:  16%|█▌        | 624/4000 [11:50<1:08:55,  1.22s/it]

train:  18%|█▊        | 624/3515 [11:48<59:01,  1.22s/it]
overall:  16%|█▌        | 625/4000 [11:51<1:08:01,  1.21s/it]

train:  18%|█▊        | 625/3515 [11:49<58:14,  1.21s/it]
overall:  16%|█▌        | 626/4000 [11:52<1:08:18,  1.21s/it]

train:  18%|█▊        | 626/3515 [11:51<58:29,  1.21s/it]
overall:  16%|█▌        | 627/4000 [11:54<1:08:06,  1.21s/it]

train:  18%|█▊        | 627/3515 [11:52<58:18,  1.21s/it]
overall:  16%|█▌        | 628/4000 [11:55<1:08:20,  1.22s/it]

train:  18%|█▊        | 628/3515 [11:53<58:30,  1.22s/it]
overall:  16%|█▌        | 629/4000 [11:56<1:08:36,  1.22s/it]

train:  18%|█▊        | 629/3515 [11:54<58:44,  1.22s/it]
overall:  16%|█▌        | 630/4000 [11:57<1:04:20,  1.15s/it]

train:  18%|█▊        | 630/3515 [11:55<55:04,  1.15s/it]
overall:  16%|█▌        | 631/4000 [11:58<1:05:32,  1.17s/it]

train:  18%|█▊        | 631/3515 [11:56<56:06,  1.17s/it]
overall:  16%|█▌        | 632/4000 [11:59<1:05:26,  1.17s/it]

train:  18%|█▊        | 632/3515 [11:58<56:01,  1.17s/it]
overall:  16%|█▌        | 633/4000 [12:01<1:08:12,  1.22s/it]

train:  18%|█▊        | 633/3515 [11:59<58:23,  1.22s/it]
overall:  16%|█▌        | 634/4000 [12:02<1:09:08,  1.23s/it]

train:  18%|█▊        | 634/3515 [12:00<59:11,  1.23s/it]
overall:  16%|█▌        | 635/4000 [12:02<55:26,  1.01it/s]  

train:  18%|█▊        | 635/3515 [12:01<47:26,  1.01it/s]
overall:  16%|█▌        | 636/4000 [12:04<57:15,  1.02s/it]

train:  18%|█▊        | 636/3515 [12:02<48:59,  1.02s/it]
overall:  16%|█▌        | 637/4000 [12:05<1:00:42,  1.08s/it]

train:  18%|█▊        | 637/3515 [12:03<51:57,  1.08s/it]
overall:  16%|█▌        | 638/4000 [12:05<48:47,  1.15it/s]  

train:  18%|█▊        | 638/3515 [12:03<41:44,  1.15it/s]
overall:  16%|█▌        | 639/4000 [12:06<55:38,  1.01it/s]

train:  18%|█▊        | 639/3515 [12:05<47:36,  1.01it/s]
overall:  16%|█▌        | 640/4000 [12:07<55:48,  1.00it/s]

train:  18%|█▊        | 640/3515 [12:06<47:45,  1.00it/s]
overall:  16%|█▌        | 641/4000 [12:09<59:02,  1.05s/it]

train:  18%|█▊        | 641/3515 [12:07<50:31,  1.05s/it]
overall:  16%|█▌        | 642/4000 [12:10<1:02:15,  1.11s/it]

train:  18%|█▊        | 642/3515 [12:08<53:15,  1.11s/it]
overall:  16%|█▌        | 643/4000 [12:11<1:04:49,  1.16s/it]

train:  18%|█▊        | 643/3515 [12:09<55:27,  1.16s/it]
overall:  16%|█▌        | 644/4000 [12:12<1:05:30,  1.17s/it]

train:  18%|█▊        | 644/3515 [12:11<56:02,  1.17s/it]
overall:  16%|█▌        | 645/4000 [12:13<56:31,  1.01s/it]  

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overall:  16%|█▌        | 646/4000 [12:14<1:00:04,  1.07s/it]

train:  18%|█▊        | 646/3515 [12:12<51:23,  1.07s/it]
overall:  16%|█▌        | 647/4000 [12:15<59:59,  1.07s/it]  

train:  18%|█▊        | 647/3515 [12:13<51:18,  1.07s/it]
overall:  16%|█▌        | 648/4000 [12:16<1:01:50,  1.11s/it]

train:  18%|█▊        | 648/3515 [12:15<52:53,  1.11s/it]
overall:  16%|█▌        | 649/4000 [12:18<1:04:29,  1.15s/it]

train:  18%|█▊        | 649/3515 [12:16<55:09,  1.15s/it]
overall:  16%|█▋        | 650/4000 [12:19<1:03:12,  1.13s/it]

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overall:  16%|█▋        | 651/4000 [12:20<1:05:34,  1.17s/it]

train:  19%|█▊        | 651/3515 [12:18<56:04,  1.17s/it]
overall:  16%|█▋        | 652/4000 [12:21<1:07:41,  1.21s/it]

train:  19%|█▊        | 652/3515 [12:20<57:53,  1.21s/it]
overall:  16%|█▋        | 653/4000 [12:23<1:08:39,  1.23s/it]

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overall:  16%|█▋        | 654/4000 [12:24<1:08:40,  1.23s/it]

train:  19%|█▊        | 654/3515 [12:22<58:43,  1.23s/it]
overall:  16%|█▋        | 655/4000 [12:25<1:05:08,  1.17s/it]

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overall:  16%|█▋        | 656/4000 [12:26<1:05:55,  1.18s/it]

train:  19%|█▊        | 656/3515 [12:24<56:21,  1.18s/it]
overall:  16%|█▋        | 657/4000 [12:27<1:06:13,  1.19s/it]

train:  19%|█▊        | 657/3515 [12:26<56:37,  1.19s/it]
overall:  16%|█▋        | 658/4000 [12:28<1:04:13,  1.15s/it]

train:  19%|█▊        | 658/3515 [12:27<54:54,  1.15s/it]
overall:  16%|█▋        | 659/4000 [12:29<54:41,  1.02it/s]  

train:  19%|█▊        | 659/3515 [12:27<46:44,  1.02it/s]
overall:  16%|█▋        | 660/4000 [12:30<59:54,  1.08s/it]

train:  19%|█▉        | 660/3515 [12:28<51:12,  1.08s/it]
overall:  17%|█▋        | 661/4000 [12:32<1:03:02,  1.13s/it]

train:  19%|█▉        | 661/3515 [12:30<53:53,  1.13s/it]
overall:  17%|█▋        | 662/4000 [12:33<1:01:54,  1.11s/it]

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overall:  17%|█▋        | 663/4000 [12:34<1:02:13,  1.12s/it]

train:  19%|█▉        | 663/3515 [12:32<53:10,  1.12s/it]
overall:  17%|█▋        | 664/4000 [12:35<1:02:13,  1.12s/it]

train:  19%|█▉        | 664/3515 [12:33<53:11,  1.12s/it]
overall:  17%|█▋        | 665/4000 [12:36<1:04:13,  1.16s/it]

train:  19%|█▉        | 665/3515 [12:34<54:53,  1.16s/it]
overall:  17%|█▋        | 666/4000 [12:37<1:05:36,  1.18s/it]

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overall:  17%|█▋        | 667/4000 [12:38<1:02:41,  1.13s/it]

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overall:  17%|█▋        | 668/4000 [12:40<1:03:14,  1.14s/it]

train:  19%|█▉        | 668/3515 [12:38<54:01,  1.14s/it]
overall:  17%|█▋        | 669/4000 [12:40<1:00:29,  1.09s/it]

train:  19%|█▉        | 669/3515 [12:39<51:41,  1.09s/it]
overall:  17%|█▋        | 670/4000 [12:41<52:00,  1.07it/s]  

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overall:  17%|█▋        | 671/4000 [12:42<47:19,  1.17it/s]

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overall:  17%|█▋        | 672/4000 [12:43<52:02,  1.07it/s]

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overall:  17%|█▋        | 673/4000 [12:44<58:39,  1.06s/it]

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overall:  17%|█▋        | 674/4000 [12:45<46:43,  1.19it/s]

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overall:  17%|█▋        | 675/4000 [12:46<53:17,  1.04it/s]

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overall:  17%|█▋        | 676/4000 [12:47<57:37,  1.04s/it]

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overall:  17%|█▋        | 677/4000 [12:48<1:01:25,  1.11s/it]

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overall:  17%|█▋        | 679/4000 [12:51<1:06:52,  1.21s/it]

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overall:  17%|█▋        | 680/4000 [12:52<1:08:14,  1.23s/it]

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overall:  17%|█▋        | 681/4000 [12:53<1:09:11,  1.25s/it]

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overall:  17%|█▋        | 686/4000 [12:59<1:04:25,  1.17s/it]

train:  20%|█▉        | 686/3515 [12:58<54:59,  1.17s/it]
overall:  17%|█▋        | 687/4000 [13:00<49:40,  1.11it/s]  

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train:  28%|██▊       | 999/3515 [18:53<50:24,  1.20s/it]train loss: 273.7108154296875
train per: 1.0114409093165235
train loss: 280.20550537109375
train per: 1.2212986237276324
train loss: 83.31893157958984
train per: 0.9243846739406242
train loss: 54.00324249267578
train per: 0.887599221207129
train loss: 38.14423751831055
train per: 0.9083240994097826
train loss: 36.53797149658203
train per: 0.9014448128848886
train loss: 32.671104431152344
train per: 0.8964101716395294
train loss: 28.101781845092773
train per: 0.9190942117814875
train loss: 29.2976016998291
train per: 0.8955842836891438
train loss: 24.46490478515625
train per: 0.8958776250972258
train loss: 25.520526885986328
train per: 0.9375584658559402
train loss: 24.932424545288086
train per: 0.9126264649904838
train loss: 21.953983306884766
train per: 0.9008053275514945
train loss: 21.46290397644043
train per: 0.9708015535070891
train loss: 20.451679229736328
train per: 0.9097742513940407
train loss: 19.583633422851562
train per: 0.9042735946295953
train loss: 23.71026039123535
train per: 0.8970417633410673
train loss: 23.287174224853516
train per: 0.9318336913939087
train loss: 21.048288345336914
train per: 0.9119336311423102
train loss: 20.27315902709961
train per: 0.9253731343283582
train loss: 19.099716186523438
train per: 0.9387714646777511
train loss: 21.305622100830078
train per: 0.8995765112076174
train loss: 19.988849639892578
train per: 0.9405119332349499
train loss: 20.4245548248291
train per: 0.9402373409765173
train loss: 18.079288482666016
train per: 0.908182009026976
train loss: 17.772441864013672
train per: 0.8997355921098814
train loss: 19.4703426361084
train per: 0.9216284626120692
train loss: 19.477346420288086
train per: 0.9070152781500523
train loss: 19.136180877685547
train per: 0.8960087229942185
train loss: 19.080833435058594
train per: 0.9066339066339066
train loss: 21.3829402923584
train per: 0.9059005111077375
train loss: 23.243858337402344
train per: 0.9490488791252684
train loss: 25.537431716918945
train per: 0.9019438124443565
train loss: 25.757226943969727
train per: 0.8969102953953084
train loss: 20.8839054107666
train per: 0.8966775676572349
train loss: 20.79218101501465
train per: 0.9694098817698384
train loss: 18.355091094970703
train per: 0.9067851165186044
train loss: 16.957557678222656
train per: 0.8925045231325924
train loss: 16.863801956176758
train per: 0.9001989554837105
train loss: 17.566356658935547
train per: 0.9139516069721262
train loss: 17.285133361816406
train per: 0.9124610064566053
train loss: 19.085622787475586
train per: 0.9013504120742727
train loss: 18.788347244262695
train per: 0.8997334954179914
train loss: 18.013906478881836
train per: 0.9057579373435343
train loss: 18.10711097717285
train per: 0.9085552904513804
train loss: 16.316091537475586
train per: 0.8975547543717657
train loss: 16.552751541137695
train per: 0.9213851404805498
train loss: 18.367006301879883
train per: 0.912806114490719
train loss: 18.6508731842041
train per: 0.9187326032101142
train loss: 17.6772518157959
train per: 0.8961769382282446
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  22%|██▏       | 601/2703 [00:00<00:00, 6000.99it/s]


word -> phonemes:  45%|████▌     | 1218/2703 [00:00<00:00, 6096.77it/s]


word -> phonemes:  69%|██████▊   | 1857/2703 [00:00<00:00, 6229.28it/s]


word -> phonemes:  92%|█████████▏| 2480/2703 [00:00<00:00, 5984.27it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 5977.67it/s]



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overall:  25%|██▍       | 999/4000 [21:39<1:00:07,  1.20s/it]

train:  28%|██▊       | 999/3515 [21:37<50:24,  1.20s/it]
                                                             

                                                         

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train:  29%|██▊       | 1004/3515 [21:42<9:03:15, 12.98s/it] 
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train:  54%|█████▍    | 1914/3515 [38:48<27:47,  1.04s/it]
overall:  48%|████▊     | 1915/4000 [38:51<35:16,  1.02s/it]

train:  54%|█████▍    | 1915/3515 [38:49<27:04,  1.02s/it]
overall:  48%|████▊     | 1916/4000 [38:51<27:46,  1.25it/s]

train:  55%|█████▍    | 1916/3515 [38:49<21:18,  1.25it/s]
overall:  48%|████▊     | 1917/4000 [38:52<32:09,  1.08it/s]

train:  55%|█████▍    | 1917/3515 [38:51<24:40,  1.08it/s]
overall:  48%|████▊     | 1918/4000 [38:54<35:10,  1.01s/it]

train:  55%|█████▍    | 1918/3515 [38:52<26:58,  1.01s/it]
overall:  48%|████▊     | 1919/4000 [38:55<36:54,  1.06s/it]

train:  55%|█████▍    | 1919/3515 [38:53<28:18,  1.06s/it]
overall:  48%|████▊     | 1920/4000 [38:56<38:15,  1.10s/it]

train:  55%|█████▍    | 1920/3515 [38:54<29:20,  1.10s/it]
overall:  48%|████▊     | 1921/4000 [38:57<39:36,  1.14s/it]

train:  55%|█████▍    | 1921/3515 [38:55<30:22,  1.14s/it]
overall:  48%|████▊     | 1922/4000 [38:59<41:46,  1.21s/it]

train:  55%|█████▍    | 1922/3515 [38:57<32:01,  1.21s/it]
overall:  48%|████▊     | 1923/4000 [39:00<42:30,  1.23s/it]

train:  55%|█████▍    | 1923/3515 [38:58<32:34,  1.23s/it]
overall:  48%|████▊     | 1924/4000 [39:01<42:25,  1.23s/it]

train:  55%|█████▍    | 1924/3515 [38:59<32:30,  1.23s/it]
overall:  48%|████▊     | 1925/4000 [39:02<42:59,  1.24s/it]

train:  55%|█████▍    | 1925/3515 [39:01<32:56,  1.24s/it]
overall:  48%|████▊     | 1926/4000 [39:04<43:09,  1.25s/it]

train:  55%|█████▍    | 1926/3515 [39:02<33:04,  1.25s/it]
overall:  48%|████▊     | 1927/4000 [39:04<33:17,  1.04it/s]

train:  55%|█████▍    | 1927/3515 [39:02<25:30,  1.04it/s]
overall:  48%|████▊     | 1928/4000 [39:05<36:13,  1.05s/it]

train:  55%|█████▍    | 1928/3515 [39:03<27:44,  1.05s/it]
overall:  48%|████▊     | 1929/4000 [39:06<37:30,  1.09s/it]

train:  55%|█████▍    | 1929/3515 [39:05<28:43,  1.09s/it]
overall:  48%|████▊     | 1930/4000 [39:08<38:41,  1.12s/it]

train:  55%|█████▍    | 1930/3515 [39:06<29:37,  1.12s/it]
overall:  48%|████▊     | 1931/4000 [39:09<39:11,  1.14s/it]

train:  55%|█████▍    | 1931/3515 [39:07<30:00,  1.14s/it]
overall:  48%|████▊     | 1932/4000 [39:10<40:02,  1.16s/it]

train:  55%|█████▍    | 1932/3515 [39:08<30:39,  1.16s/it]
overall:  48%|████▊     | 1933/4000 [39:11<39:39,  1.15s/it]

train:  55%|█████▍    | 1933/3515 [39:09<30:21,  1.15s/it]
overall:  48%|████▊     | 1934/4000 [39:12<40:10,  1.17s/it]

train:  55%|█████▌    | 1934/3515 [39:10<30:44,  1.17s/it]
overall:  48%|████▊     | 1935/4000 [39:14<42:50,  1.24s/it]

train:  55%|█████▌    | 1935/3515 [39:12<32:46,  1.24s/it]
overall:  48%|████▊     | 1936/4000 [39:15<42:41,  1.24s/it]

train:  55%|█████▌    | 1936/3515 [39:13<32:39,  1.24s/it]
overall:  48%|████▊     | 1937/4000 [39:16<42:13,  1.23s/it]

train:  55%|█████▌    | 1937/3515 [39:14<32:17,  1.23s/it]
overall:  48%|████▊     | 1938/4000 [39:17<42:01,  1.22s/it]

train:  55%|█████▌    | 1938/3515 [39:16<32:08,  1.22s/it]
overall:  48%|████▊     | 1939/4000 [39:19<41:49,  1.22s/it]

train:  55%|█████▌    | 1939/3515 [39:17<31:59,  1.22s/it]
overall:  48%|████▊     | 1940/4000 [39:20<40:25,  1.18s/it]

train:  55%|█████▌    | 1940/3515 [39:18<30:54,  1.18s/it]
overall:  49%|████▊     | 1941/4000 [39:21<40:23,  1.18s/it]

train:  55%|█████▌    | 1941/3515 [39:19<30:52,  1.18s/it]
overall:  49%|████▊     | 1942/4000 [39:22<40:51,  1.19s/it]

train:  55%|█████▌    | 1942/3515 [39:20<31:13,  1.19s/it]
overall:  49%|████▊     | 1943/4000 [39:23<41:00,  1.20s/it]

train:  55%|█████▌    | 1943/3515 [39:21<31:20,  1.20s/it]
overall:  49%|████▊     | 1944/4000 [39:24<40:26,  1.18s/it]

train:  55%|█████▌    | 1944/3515 [39:23<30:54,  1.18s/it]
overall:  49%|████▊     | 1945/4000 [39:26<40:48,  1.19s/it]

train:  55%|█████▌    | 1945/3515 [39:24<31:10,  1.19s/it]
overall:  49%|████▊     | 1946/4000 [39:27<43:45,  1.28s/it]

train:  55%|█████▌    | 1946/3515 [39:25<33:25,  1.28s/it]
overall:  49%|████▊     | 1947/4000 [39:28<43:19,  1.27s/it]

train:  55%|█████▌    | 1947/3515 [39:27<33:05,  1.27s/it]
overall:  49%|████▊     | 1948/4000 [39:29<39:21,  1.15s/it]

train:  55%|█████▌    | 1948/3515 [39:27<30:03,  1.15s/it]
overall:  49%|████▊     | 1949/4000 [39:30<39:14,  1.15s/it]

train:  55%|█████▌    | 1949/3515 [39:29<29:57,  1.15s/it]
overall:  49%|████▉     | 1950/4000 [39:32<40:31,  1.19s/it]

train:  55%|█████▌    | 1950/3515 [39:30<30:56,  1.19s/it]
overall:  49%|████▉     | 1951/4000 [39:33<40:48,  1.20s/it]

train:  56%|█████▌    | 1951/3515 [39:31<31:09,  1.20s/it]
overall:  49%|████▉     | 1952/4000 [39:34<38:20,  1.12s/it]

train:  56%|█████▌    | 1952/3515 [39:32<29:15,  1.12s/it]
overall:  49%|████▉     | 1953/4000 [39:35<39:58,  1.17s/it]

train:  56%|█████▌    | 1953/3515 [39:33<30:30,  1.17s/it]
overall:  49%|████▉     | 1954/4000 [39:36<40:30,  1.19s/it]

train:  56%|█████▌    | 1954/3515 [39:35<30:54,  1.19s/it]
overall:  49%|████▉     | 1955/4000 [39:37<39:47,  1.17s/it]

train:  56%|█████▌    | 1955/3515 [39:36<30:21,  1.17s/it]
overall:  49%|████▉     | 1956/4000 [39:39<39:22,  1.16s/it]

train:  56%|█████▌    | 1956/3515 [39:37<30:01,  1.16s/it]
overall:  49%|████▉     | 1957/4000 [39:40<39:32,  1.16s/it]

train:  56%|█████▌    | 1957/3515 [39:38<30:09,  1.16s/it]
overall:  49%|████▉     | 1958/4000 [39:41<39:48,  1.17s/it]

train:  56%|█████▌    | 1958/3515 [39:39<30:21,  1.17s/it]
overall:  49%|████▉     | 1959/4000 [39:42<41:34,  1.22s/it]

train:  56%|█████▌    | 1959/3515 [39:40<31:41,  1.22s/it]
overall:  49%|████▉     | 1960/4000 [39:44<41:51,  1.23s/it]

train:  56%|█████▌    | 1960/3515 [39:42<31:54,  1.23s/it]
overall:  49%|████▉     | 1961/4000 [39:45<42:20,  1.25s/it]

train:  56%|█████▌    | 1961/3515 [39:43<32:16,  1.25s/it]
overall:  49%|████▉     | 1962/4000 [39:46<42:17,  1.25s/it]

train:  56%|█████▌    | 1962/3515 [39:44<32:13,  1.25s/it]
overall:  49%|████▉     | 1963/4000 [39:47<41:20,  1.22s/it]

train:  56%|█████▌    | 1963/3515 [39:45<31:30,  1.22s/it]
overall:  49%|████▉     | 1964/4000 [39:48<41:30,  1.22s/it]

train:  56%|█████▌    | 1964/3515 [39:47<31:37,  1.22s/it]
overall:  49%|████▉     | 1965/4000 [39:49<38:39,  1.14s/it]

train:  56%|█████▌    | 1965/3515 [39:48<29:26,  1.14s/it]
overall:  49%|████▉     | 1966/4000 [39:51<39:42,  1.17s/it]

train:  56%|█████▌    | 1966/3515 [39:49<30:14,  1.17s/it]
overall:  49%|████▉     | 1967/4000 [39:52<39:14,  1.16s/it]

train:  56%|█████▌    | 1967/3515 [39:50<29:52,  1.16s/it]
overall:  49%|████▉     | 1968/4000 [39:52<32:38,  1.04it/s]

train:  56%|█████▌    | 1968/3515 [39:50<24:50,  1.04it/s]
overall:  49%|████▉     | 1969/4000 [39:53<34:34,  1.02s/it]

train:  56%|█████▌    | 1969/3515 [39:52<26:19,  1.02s/it]
overall:  49%|████▉     | 1970/4000 [39:55<39:24,  1.16s/it]

train:  56%|█████▌    | 1970/3515 [39:53<29:59,  1.16s/it]
overall:  49%|████▉     | 1971/4000 [39:56<39:34,  1.17s/it]

train:  56%|█████▌    | 1971/3515 [39:54<30:06,  1.17s/it]
overall:  49%|████▉     | 1972/4000 [39:57<40:11,  1.19s/it]

train:  56%|█████▌    | 1972/3515 [39:56<30:34,  1.19s/it]
overall:  49%|████▉     | 1973/4000 [39:59<41:06,  1.22s/it]

train:  56%|█████▌    | 1973/3515 [39:57<31:16,  1.22s/it]
overall:  49%|████▉     | 1974/4000 [40:00<41:08,  1.22s/it]

train:  56%|█████▌    | 1974/3515 [39:58<31:17,  1.22s/it]
overall:  49%|████▉     | 1975/4000 [40:00<33:10,  1.02it/s]

train:  56%|█████▌    | 1975/3515 [39:58<25:13,  1.02it/s]
overall:  49%|████▉     | 1976/4000 [40:02<35:37,  1.06s/it]

train:  56%|█████▌    | 1976/3515 [40:00<27:05,  1.06s/it]
overall:  49%|████▉     | 1977/4000 [40:03<37:25,  1.11s/it]

train:  56%|█████▌    | 1977/3515 [40:01<28:27,  1.11s/it]
overall:  49%|████▉     | 1978/4000 [40:04<38:01,  1.13s/it]

train:  56%|█████▋    | 1978/3515 [40:02<28:53,  1.13s/it]
overall:  49%|████▉     | 1979/4000 [40:05<38:54,  1.16s/it]

train:  56%|█████▋    | 1979/3515 [40:03<29:34,  1.16s/it]
overall:  50%|████▉     | 1980/4000 [40:06<39:01,  1.16s/it]

train:  56%|█████▋    | 1980/3515 [40:04<29:39,  1.16s/it]
overall:  50%|████▉     | 1981/4000 [40:07<38:18,  1.14s/it]

train:  56%|█████▋    | 1981/3515 [40:06<29:06,  1.14s/it]
overall:  50%|████▉     | 1982/4000 [40:09<39:12,  1.17s/it]

train:  56%|█████▋    | 1982/3515 [40:07<29:46,  1.17s/it]
overall:  50%|████▉     | 1983/4000 [40:10<41:46,  1.24s/it]

train:  56%|█████▋    | 1983/3515 [40:08<31:43,  1.24s/it]
overall:  50%|████▉     | 1984/4000 [40:11<42:07,  1.25s/it]

train:  56%|█████▋    | 1984/3515 [40:10<31:59,  1.25s/it]
overall:  50%|████▉     | 1985/4000 [40:13<41:48,  1.24s/it]

train:  56%|█████▋    | 1985/3515 [40:11<31:44,  1.24s/it]
overall:  50%|████▉     | 1986/4000 [40:14<41:37,  1.24s/it]

train:  57%|█████▋    | 1986/3515 [40:12<31:36,  1.24s/it]
overall:  50%|████▉     | 1987/4000 [40:15<41:19,  1.23s/it]

train:  57%|█████▋    | 1987/3515 [40:13<31:22,  1.23s/it]
overall:  50%|████▉     | 1988/4000 [40:16<40:17,  1.20s/it]

train:  57%|█████▋    | 1988/3515 [40:14<30:35,  1.20s/it]
overall:  50%|████▉     | 1989/4000 [40:17<40:11,  1.20s/it]

train:  57%|█████▋    | 1989/3515 [40:16<30:29,  1.20s/it]
overall:  50%|████▉     | 1990/4000 [40:19<39:52,  1.19s/it]

train:  57%|█████▋    | 1990/3515 [40:17<30:15,  1.19s/it]
overall:  50%|████▉     | 1991/4000 [40:20<39:57,  1.19s/it]

train:  57%|█████▋    | 1991/3515 [40:18<30:18,  1.19s/it]
overall:  50%|████▉     | 1992/4000 [40:21<40:26,  1.21s/it]

train:  57%|█████▋    | 1992/3515 [40:19<30:40,  1.21s/it]
overall:  50%|████▉     | 1993/4000 [40:22<41:03,  1.23s/it]

train:  57%|█████▋    | 1993/3515 [40:20<31:07,  1.23s/it]
overall:  50%|████▉     | 1994/4000 [40:23<41:20,  1.24s/it]

train:  57%|█████▋    | 1994/3515 [40:22<31:20,  1.24s/it]
overall:  50%|████▉     | 1995/4000 [40:25<40:22,  1.21s/it]

train:  57%|█████▋    | 1995/3515 [40:23<30:36,  1.21s/it]
overall:  50%|████▉     | 1996/4000 [40:26<40:04,  1.20s/it]

train:  57%|█████▋    | 1996/3515 [40:24<30:22,  1.20s/it]
overall:  50%|████▉     | 1997/4000 [40:27<40:48,  1.22s/it]

train:  57%|█████▋    | 1997/3515 [40:25<30:55,  1.22s/it]
overall:  50%|████▉     | 1998/4000 [40:28<41:00,  1.23s/it]

train:  57%|█████▋    | 1998/3515 [40:26<31:04,  1.23s/it]
overall:  50%|████▉     | 1999/4000 [40:29<40:29,  1.21s/it]

train:  57%|█████▋    | 1999/3515 [40:28<30:40,  1.21s/it]dev loss: 13.800531387329102
dev per: 0.9112955254942768
[Runner] - Save the checkpoint to:
1. result/downstream/grid/dev-best.ckpt
train loss: 17.59709358215332
train per: 0.9383574879227053
train loss: 19.116634368896484
train per: 0.9103966331449265
train loss: 16.41364288330078
train per: 0.89015625
train loss: 17.491397857666016
train per: 0.9360419689697511
train loss: 17.417734146118164
train per: 0.9538899339217672
train loss: 16.334007263183594
train per: 0.8938112051162481
train loss: 16.4709415435791
train per: 0.9137956419316844
train loss: 13.406211853027344
train per: 0.896979990446367
train loss: 17.4075927734375
train per: 0.9022060244622988
train loss: 22.685617446899414
train per: 0.9241138021751512
train loss: 16.364582061767578
train per: 0.8960715295084916
train loss: 18.890323638916016
train per: 0.9232701093066086
train loss: 17.702983856201172
train per: 0.9099282070659361
train loss: 16.539409637451172
train per: 0.9006005284650492
train loss: 18.931884765625
train per: 0.9291873223222047
train loss: 18.92511558532715
train per: 0.8956530696332922
train loss: 18.876081466674805
train per: 0.9025908760958178
train loss: 20.36988639831543
train per: 0.9254007242156441
train loss: 20.303010940551758
train per: 0.9691590508046037
train loss: 18.487234115600586
train per: 0.9104851934021414
train loss: 20.272489547729492
train per: 0.9114984914515588
train loss: 20.24272346496582
train per: 0.912525696462749
train loss: 18.74656867980957
train per: 0.9265282449831806
train loss: 19.794719696044922
train per: 0.8998746835119307
train loss: 21.332439422607422
train per: 0.8936653586286254
train loss: 19.892696380615234
train per: 0.9125107686417153
train loss: 21.356067657470703
train per: 0.9150831991411702
train loss: 20.506418228149414
train per: 0.9010908908103761
train loss: 18.017667770385742
train per: 0.8932088206740326
train loss: 16.997295379638672
train per: 0.9262554167728779
train loss: 16.163951873779297
train per: 0.8984512214593645
train loss: 17.291889190673828
train per: 0.9046156027698343
train loss: 18.06005096435547
train per: 0.9244039707005288
train loss: 18.500144958496094
train per: 0.9220243169276324
train loss: 18.70293617248535
train per: 0.9603230245903768
train loss: 18.750337600708008
train per: 0.9372868464312879
train loss: 18.181686401367188
train per: 0.8922454357236966
train loss: 16.23488998413086
train per: 0.9280194691153595
train loss: 17.25792694091797
train per: 0.9455178584383237
train loss: 16.83615493774414
train per: 0.8905374791505888
train loss: 18.91240119934082
train per: 0.9025751178925018
train loss: 22.18909454345703
train per: 0.9406649358505785
train loss: 17.79409408569336
train per: 0.8962065859273346
train loss: 17.636655807495117
train per: 0.910331431346364
train loss: 22.722360610961914
train per: 0.9475889939381844
train loss: 16.694862365722656
train per: 0.9372944983818771
train loss: 14.307809829711914
train per: 0.908566450032966
train loss: 17.42570686340332
train per: 0.9445654232153001
train loss: 19.651195526123047
train per: 0.9048714039341148
train loss: 18.085567474365234
train per: 0.939903464841714
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  22%|██▏       | 601/2703 [00:00<00:00, 6004.17it/s]


word -> phonemes:  45%|████▌     | 1222/2703 [00:00<00:00, 6119.95it/s]


word -> phonemes:  68%|██████▊   | 1834/2703 [00:00<00:00, 5882.26it/s]


word -> phonemes:  90%|█████████ | 2442/2703 [00:00<00:00, 5958.09it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 5930.21it/s]



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


dev:   0%|          | 1/2703 [00:01<1:01:55,  1.37s/it]


dev:   0%|          | 2/2703 [00:01<31:15,  1.44it/s]  


dev:   0%|          | 3/2703 [00:01<21:36,  2.08it/s]


dev:   0%|          | 4/2703 [00:02<16:45,  2.68it/s]


dev:   0%|          | 5/2703 [00:02<14:12,  3.17it/s]


dev:   0%|          | 6/2703 [00:02<12:40,  3.55it/s]


dev:   0%|          | 7/2703 [00:02<11:38,  3.86it/s]


dev:   0%|          | 8/2703 [00:02<10:41,  4.20it/s]


dev:   0%|          | 9/2703 [00:03<10:20,  4.34it/s]


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train:  85%|████████▍ | 2978/3515 [1:01:30<09:53,  1.11s/it]
overall:  74%|███████▍  | 2979/4000 [1:01:33<15:57,  1.07it/s]

train:  85%|████████▍ | 2979/3515 [1:01:31<08:22,  1.07it/s]
overall:  74%|███████▍  | 2980/4000 [1:01:34<14:37,  1.16it/s]

train:  85%|████████▍ | 2980/3515 [1:01:32<07:40,  1.16it/s]
overall:  75%|███████▍  | 2981/4000 [1:01:35<16:22,  1.04it/s]

train:  85%|████████▍ | 2981/3515 [1:01:33<08:35,  1.04it/s]
overall:  75%|███████▍  | 2982/4000 [1:01:36<17:02,  1.00s/it]

train:  85%|████████▍ | 2982/3515 [1:01:34<08:55,  1.00s/it]
overall:  75%|███████▍  | 2983/4000 [1:01:36<14:42,  1.15it/s]

train:  85%|████████▍ | 2983/3515 [1:01:35<07:41,  1.15it/s]
overall:  75%|███████▍  | 2984/4000 [1:01:38<16:35,  1.02it/s]

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overall:  75%|███████▍  | 2985/4000 [1:01:39<17:13,  1.02s/it]

train:  85%|████████▍ | 2985/3515 [1:01:37<08:59,  1.02s/it]
overall:  75%|███████▍  | 2986/4000 [1:01:40<18:29,  1.09s/it]

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train:  85%|████████▌ | 2995/3515 [1:01:48<09:19,  1.08s/it]
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train:  85%|████████▌ | 2997/3515 [1:01:51<10:12,  1.18s/it]
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overall:  75%|███████▍  | 2999/4000 [1:01:55<18:47,  1.13s/it]

train:  85%|████████▌ | 2999/3515 [1:01:53<09:40,  1.13s/it]dev loss: 15.340489387512207
dev per: 0.935894901144641
train loss: 17.11945152282715
train per: 0.9287951658650881
train loss: 17.100727081298828
train per: 0.9143598404190224
train loss: 17.23324203491211
train per: 0.9121939452418285
train loss: 19.786773681640625
train per: 0.8936986024923061
train loss: 18.597309112548828
train per: 0.9446809563882976
train loss: 16.57904052734375
train per: 0.897911004968569
train loss: 20.00654411315918
train per: 0.9411296268986875
train loss: 18.08603286743164
train per: 0.8887121683608787
train loss: 23.49880599975586
train per: 0.9085306365258774
train loss: 18.771865844726562
train per: 0.8951401098304791
train loss: 19.142505645751953
train per: 0.9351825576995838
train loss: 23.30561065673828
train per: 0.91185584067868
train loss: 21.591632843017578
train per: 0.9095634355398955
train loss: 21.16342544555664
train per: 0.9040546453400748
train loss: 20.857746124267578
train per: 0.9575394797673796
train loss: 20.319599151611328
train per: 0.8939572009206209
train loss: 19.41584014892578
train per: 0.8949887808526552
train loss: 18.753549575805664
train per: 0.9039339705590379
train loss: 20.19418716430664
train per: 0.9394015704768663
train loss: 17.062259674072266
train per: 0.9229262432093607
train loss: 17.06948471069336
train per: 0.9299635045557239
train loss: 19.051448822021484
train per: 0.9161697555734623
train loss: 20.142953872680664
train per: 0.9278223025517848
train loss: 18.776548385620117
train per: 0.9259296711075158
train loss: 20.999759674072266
train per: 1.0233138085020008
train loss: 19.44627571105957
train per: 0.8997830045145038
train loss: 17.53647232055664
train per: 0.9386392941116982
train loss: 17.917125701904297
train per: 0.8986919215647486
train loss: 19.795976638793945
train per: 0.9128039957055502
train loss: 21.086742401123047
train per: 0.9249748113926228
train loss: 22.470272064208984
train per: 0.9063195266272189
train loss: 21.19655990600586
train per: 0.9357310398749022
train loss: 21.126171112060547
train per: 0.9132721078358762
train loss: 19.59393882751465
train per: 0.8960383775140199
train loss: 20.44809913635254
train per: 0.9062140852599225
train loss: 18.451831817626953
train per: 0.9024331421833968
train loss: 19.892847061157227
train per: 0.9285750545712981
train loss: 20.583581924438477
train per: 0.9066179349954314
train loss: 20.345272064208984
train per: 0.9090255303847536
train loss: 20.171545028686523
train per: 0.9063150757905952
train loss: 19.85598373413086
train per: 0.9262004974172565
train loss: 18.786396026611328
train per: 0.8950843536353947
train loss: 20.4653263092041
train per: 0.9434157175692777
train loss: 22.51316261291504
train per: 0.9010582654178324
train loss: 22.604665756225586
train per: 0.9235694065980582
train loss: 18.879196166992188
train per: 0.8892773892773893
train loss: 24.549802780151367
train per: 0.8993030034216196
train loss: 21.584508895874023
train per: 0.9220353580057893
train loss: 24.22654151916504
train per: 0.9228182546036829
train loss: 18.442279815673828
train per: 0.904175335729147
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:   6%|▌         | 163/2703 [00:00<00:03, 702.49it/s]


word -> phonemes:  27%|██▋       | 743/2703 [00:00<00:00, 2644.77it/s]


word -> phonemes:  50%|████▉     | 1346/2703 [00:00<00:00, 3836.55it/s]


word -> phonemes:  72%|███████▏  | 1952/2703 [00:00<00:00, 4579.04it/s]


word -> phonemes:  94%|█████████▎| 2530/2703 [00:00<00:00, 4966.72it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 4071.35it/s]



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overall:  77%|███████▋  | 3095/4000 [1:06:31<16:52,  1.12s/it]

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overall:  77%|███████▋  | 3096/4000 [1:06:32<16:00,  1.06s/it]

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overall:  77%|███████▋  | 3097/4000 [1:06:33<15:20,  1.02s/it]

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overall:  77%|███████▋  | 3098/4000 [1:06:34<16:57,  1.13s/it]

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overall:  77%|███████▋  | 3099/4000 [1:06:34<12:59,  1.16it/s]

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overall:  78%|███████▊  | 3100/4000 [1:06:35<14:35,  1.03it/s]

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overall:  78%|███████▊  | 3101/4000 [1:06:36<12:05,  1.24it/s]

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overall:  78%|███████▊  | 3102/4000 [1:06:37<13:55,  1.07it/s]

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overall:  78%|███████▊  | 3103/4000 [1:06:38<15:26,  1.03s/it]

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overall:  78%|███████▊  | 3104/4000 [1:06:40<16:28,  1.10s/it]

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overall:  78%|███████▊  | 3105/4000 [1:06:41<17:10,  1.15s/it]

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overall:  78%|███████▊  | 3106/4000 [1:06:42<16:54,  1.13s/it]

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overall:  78%|███████▊  | 3107/4000 [1:06:43<15:10,  1.02s/it]

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overall:  78%|███████▊  | 3108/4000 [1:06:44<15:49,  1.06s/it]

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overall:  78%|███████▊  | 3109/4000 [1:06:45<16:16,  1.10s/it]

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overall:  78%|███████▊  | 3110/4000 [1:06:46<16:21,  1.10s/it]

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overall:  78%|███████▊  | 3111/4000 [1:06:48<17:24,  1.17s/it]

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overall:  78%|███████▊  | 3112/4000 [1:06:49<17:27,  1.18s/it]

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overall:  78%|███████▊  | 3113/4000 [1:06:50<17:28,  1.18s/it]

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overall:  78%|███████▊  | 3114/4000 [1:06:51<17:33,  1.19s/it]

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overall:  78%|███████▊  | 3116/4000 [1:06:53<14:49,  1.01s/it]

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overall:  78%|███████▊  | 3117/4000 [1:06:54<14:48,  1.01s/it]

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overall:  78%|███████▊  | 3118/4000 [1:06:55<15:49,  1.08s/it]

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overall:  78%|███████▊  | 3123/4000 [1:07:00<13:56,  1.05it/s]

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overall:  78%|███████▊  | 3124/4000 [1:07:01<15:10,  1.04s/it]

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overall:  78%|███████▊  | 3134/4000 [1:07:12<16:01,  1.11s/it]

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overall:  78%|███████▊  | 3135/4000 [1:07:14<17:18,  1.20s/it]

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overall:  78%|███████▊  | 3138/4000 [1:07:18<17:35,  1.22s/it]

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overall:  78%|███████▊  | 3140/4000 [1:07:19<13:40,  1.05it/s]

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overall:  79%|███████▊  | 3141/4000 [1:07:20<12:56,  1.11it/s]

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overall:  79%|███████▊  | 3143/4000 [1:07:21<12:36,  1.13it/s]

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overall:  79%|███████▊  | 3145/4000 [1:07:24<15:18,  1.07s/it]

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overall:  79%|███████▊  | 3146/4000 [1:07:25<15:59,  1.12s/it]

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overall:  79%|███████▊  | 3147/4000 [1:07:27<16:38,  1.17s/it]

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overall:  79%|███████▊  | 3148/4000 [1:07:28<16:11,  1.14s/it]

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overall:  79%|███████▊  | 3149/4000 [1:07:29<16:23,  1.16s/it]

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train: 100%|██████████| 3515/3515 [1:14:23<00:00,  1.15s/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 [1:14:23<00:00,  1.27s/it]
dev loss: 18.565732955932617
dev per: 0.9317273673257024
train loss: 18.046886444091797
train per: 0.9005450871669565
train loss: 22.94076919555664
train per: 0.9492284602035552
train loss: 21.59164810180664
train per: 0.9187421799381478
train loss: 19.894973754882812
train per: 0.9142992071185345
train loss: 19.384593963623047
train per: 0.9430479070961851
train loss: 28.74576759338379
train per: 0.9881350135487096
train loss: 19.998516082763672
train per: 0.9161253806969787
train loss: 22.243804931640625
train per: 0.8991219606329602
train loss: 24.320392608642578
train per: 0.9184855799771312
train loss: 22.71576499938965
train per: 0.9245002279872327
train loss: 24.10051155090332
train per: 0.9359240659427339
train loss: 21.331989288330078
train per: 0.8969440370878471
train loss: 23.17580795288086
train per: 0.9310617088998001
train loss: 20.013381958007812
train per: 0.9183968399248519
train loss: 18.692073822021484
train per: 0.9015218693828639
train loss: 17.634735107421875
train per: 0.931858830642114
train loss: 18.240734100341797
train per: 0.9164579443508356
train loss: 16.924678802490234
train per: 0.9137218230140762
train loss: 15.337626457214355
train per: 0.8962649402390438
train loss: 15.408531188964844
train per: 0.8946364165212333
train loss: 18.846784591674805
train per: 0.9067445565586829
train loss: 16.935293197631836
train per: 0.9079259357932596
train loss: 25.138792037963867
train per: 0.9368588390173626
train loss: 20.96569061279297
train per: 0.8965989259766242
train loss: 19.87340545654297
train per: 0.8991561669171194
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.


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

word -> phonemes:  12%|█▏        | 417/3515 [00:00<00:00, 4165.02it/s]

word -> phonemes:  24%|██▍       | 843/3515 [00:00<00:00, 4216.13it/s]

word -> phonemes:  37%|███▋      | 1289/3515 [00:00<00:00, 4327.22it/s]

word -> phonemes:  49%|████▉     | 1722/3515 [00:00<00:00, 4322.86it/s]

word -> phonemes:  62%|██████▏   | 2179/3515 [00:00<00:00, 4408.64it/s]

word -> phonemes:  75%|███████▍  | 2620/3515 [00:00<00:00, 4166.25it/s]

word -> phonemes:  87%|████████▋ | 3068/3515 [00:00<00:00, 4263.88it/s]

word -> phonemes: 100%|█████████▉| 3503/3515 [00:00<00:00, 4290.14it/s]
word -> phonemes: 100%|██████████| 3515/3515 [00:00<00:00, 4282.15it/s]


train:   0%|          | 0/3515 [00:00<?, ?it/s]
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overall:  88%|████████▊ | 3524/4000 [1:14:39<08:54,  1.12s/it]

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overall:  88%|████████▊ | 3528/4000 [1:14:44<09:14,  1.17s/it]

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overall:  88%|████████▊ | 3529/4000 [1:14:45<09:12,  1.17s/it]

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overall:  88%|████████▊ | 3530/4000 [1:14:46<09:24,  1.20s/it]

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overall:  88%|████████▊ | 3531/4000 [1:14:48<09:25,  1.21s/it]

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overall:  88%|████████▊ | 3534/4000 [1:14:51<09:31,  1.23s/it]

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overall:  88%|████████▊ | 3535/4000 [1:14:53<09:38,  1.24s/it]

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overall:  88%|████████▊ | 3536/4000 [1:14:54<09:41,  1.25s/it]

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overall:  88%|████████▊ | 3537/4000 [1:14:55<09:42,  1.26s/it]

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overall:  88%|████████▊ | 3538/4000 [1:14:56<09:36,  1.25s/it]

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overall:  88%|████████▊ | 3539/4000 [1:14:58<09:40,  1.26s/it]

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overall:  88%|████████▊ | 3540/4000 [1:14:59<09:40,  1.26s/it]

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overall:  89%|████████▊ | 3541/4000 [1:15:00<09:32,  1.25s/it]

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overall:  89%|████████▊ | 3542/4000 [1:15:01<09:19,  1.22s/it]

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overall:  89%|████████▊ | 3543/4000 [1:15:03<09:17,  1.22s/it]

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overall:  89%|████████▊ | 3544/4000 [1:15:04<09:09,  1.21s/it]

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overall:  89%|████████▊ | 3545/4000 [1:15:05<09:17,  1.22s/it]

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overall:  89%|████████▊ | 3546/4000 [1:15:06<09:01,  1.19s/it]

train:   1%|          | 31/3515 [00:38<1:09:17,  1.19s/it]
overall:  89%|████████▊ | 3547/4000 [1:15:06<07:14,  1.04it/s]

train:   1%|          | 32/3515 [00:39<55:44,  1.04it/s]  
overall:  89%|████████▊ | 3548/4000 [1:15:08<07:57,  1.06s/it]

train:   1%|          | 33/3515 [00:40<1:01:17,  1.06s/it]
overall:  89%|████████▊ | 3549/4000 [1:15:09<08:24,  1.12s/it]

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overall:  89%|████████▉ | 3550/4000 [1:15:10<08:34,  1.14s/it]

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overall:  89%|████████▉ | 3551/4000 [1:15:11<08:33,  1.14s/it]

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overall:  89%|████████▉ | 3552/4000 [1:15:13<08:41,  1.16s/it]

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overall:  89%|████████▉ | 3553/4000 [1:15:14<08:42,  1.17s/it]

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overall:  89%|████████▉ | 3554/4000 [1:15:15<09:08,  1.23s/it]

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overall:  89%|████████▉ | 3555/4000 [1:15:16<09:06,  1.23s/it]

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overall:  89%|████████▉ | 3556/4000 [1:15:18<09:35,  1.30s/it]

train:   1%|          | 41/3515 [00:50<1:14:59,  1.30s/it]
overall:  89%|████████▉ | 3557/4000 [1:15:19<09:20,  1.26s/it]

train:   1%|          | 42/3515 [00:51<1:13:11,  1.26s/it]
overall:  89%|████████▉ | 3558/4000 [1:15:20<08:44,  1.19s/it]

train:   1%|          | 43/3515 [00:52<1:08:39,  1.19s/it]
overall:  89%|████████▉ | 3559/4000 [1:15:21<08:39,  1.18s/it]

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overall:  89%|████████▉ | 3560/4000 [1:15:22<08:54,  1.21s/it]

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overall:  89%|████████▉ | 3561/4000 [1:15:24<08:52,  1.21s/it]

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overall:  89%|████████▉ | 3562/4000 [1:15:24<07:32,  1.03s/it]

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overall:  89%|████████▉ | 3563/4000 [1:15:25<07:09,  1.02it/s]

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overall:  89%|████████▉ | 3564/4000 [1:15:26<07:40,  1.06s/it]

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overall:  89%|████████▉ | 3565/4000 [1:15:28<08:03,  1.11s/it]

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overall:  89%|████████▉ | 3566/4000 [1:15:29<08:03,  1.11s/it]

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overall:  89%|████████▉ | 3567/4000 [1:15:30<08:23,  1.16s/it]

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overall:  89%|████████▉ | 3568/4000 [1:15:31<08:29,  1.18s/it]

train:   2%|▏         | 53/3515 [01:03<1:08:02,  1.18s/it]
overall:  89%|████████▉ | 3569/4000 [1:15:32<08:34,  1.19s/it]

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overall:  89%|████████▉ | 3570/4000 [1:15:34<08:22,  1.17s/it]

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overall:  89%|████████▉ | 3571/4000 [1:15:35<08:35,  1.20s/it]

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overall:  89%|████████▉ | 3572/4000 [1:15:36<08:44,  1.23s/it]

train:   2%|▏         | 57/3515 [01:08<1:10:38,  1.23s/it]
overall:  89%|████████▉ | 3573/4000 [1:15:37<08:50,  1.24s/it]

train:   2%|▏         | 58/3515 [01:10<1:11:34,  1.24s/it]
overall:  89%|████████▉ | 3574/4000 [1:15:39<08:56,  1.26s/it]

train:   2%|▏         | 59/3515 [01:11<1:12:30,  1.26s/it]
overall:  89%|████████▉ | 3575/4000 [1:15:40<08:57,  1.26s/it]

train:   2%|▏         | 60/3515 [01:12<1:12:50,  1.26s/it]
overall:  89%|████████▉ | 3576/4000 [1:15:41<08:48,  1.25s/it]

train:   2%|▏         | 61/3515 [01:13<1:11:48,  1.25s/it]
overall:  89%|████████▉ | 3577/4000 [1:15:42<08:44,  1.24s/it]

train:   2%|▏         | 62/3515 [01:15<1:11:19,  1.24s/it]
overall:  89%|████████▉ | 3578/4000 [1:15:44<08:38,  1.23s/it]

train:   2%|▏         | 63/3515 [01:16<1:10:39,  1.23s/it]
overall:  89%|████████▉ | 3579/4000 [1:15:45<08:36,  1.23s/it]

train:   2%|▏         | 64/3515 [01:17<1:10:30,  1.23s/it]
overall:  90%|████████▉ | 3580/4000 [1:15:46<08:54,  1.27s/it]

train:   2%|▏         | 65/3515 [01:18<1:13:14,  1.27s/it]
overall:  90%|████████▉ | 3581/4000 [1:15:47<08:32,  1.22s/it]

train:   2%|▏         | 66/3515 [01:19<1:10:15,  1.22s/it]
overall:  90%|████████▉ | 3582/4000 [1:15:49<08:29,  1.22s/it]

train:   2%|▏         | 67/3515 [01:21<1:10:01,  1.22s/it]
overall:  90%|████████▉ | 3583/4000 [1:15:50<08:36,  1.24s/it]

train:   2%|▏         | 68/3515 [01:22<1:11:12,  1.24s/it]
overall:  90%|████████▉ | 3584/4000 [1:15:51<08:27,  1.22s/it]

train:   2%|▏         | 69/3515 [01:23<1:10:01,  1.22s/it]
overall:  90%|████████▉ | 3585/4000 [1:15:52<07:40,  1.11s/it]

train:   2%|▏         | 70/3515 [01:24<1:03:45,  1.11s/it]
overall:  90%|████████▉ | 3586/4000 [1:15:53<07:37,  1.11s/it]

train:   2%|▏         | 71/3515 [01:25<1:03:25,  1.11s/it]
overall:  90%|████████▉ | 3587/4000 [1:15:54<07:59,  1.16s/it]

train:   2%|▏         | 72/3515 [01:26<1:06:38,  1.16s/it]
overall:  90%|████████▉ | 3588/4000 [1:15:55<08:07,  1.18s/it]

train:   2%|▏         | 73/3515 [01:28<1:07:48,  1.18s/it]
overall:  90%|████████▉ | 3589/4000 [1:15:57<08:11,  1.20s/it]

train:   2%|▏         | 74/3515 [01:29<1:08:38,  1.20s/it]
overall:  90%|████████▉ | 3590/4000 [1:15:58<08:23,  1.23s/it]

train:   2%|▏         | 75/3515 [01:30<1:10:21,  1.23s/it]
overall:  90%|████████▉ | 3591/4000 [1:15:59<08:27,  1.24s/it]

train:   2%|▏         | 76/3515 [01:31<1:11:07,  1.24s/it]
overall:  90%|████████▉ | 3592/4000 [1:16:01<08:44,  1.28s/it]

train:   2%|▏         | 77/3515 [01:33<1:13:35,  1.28s/it]
overall:  90%|████████▉ | 3593/4000 [1:16:02<08:42,  1.28s/it]

train:   2%|▏         | 78/3515 [01:34<1:13:36,  1.28s/it]
overall:  90%|████████▉ | 3594/4000 [1:16:03<08:21,  1.23s/it]

train:   2%|▏         | 79/3515 [01:35<1:10:43,  1.23s/it]
overall:  90%|████████▉ | 3595/4000 [1:16:04<08:07,  1.20s/it]

train:   2%|▏         | 80/3515 [01:36<1:08:55,  1.20s/it]
overall:  90%|████████▉ | 3596/4000 [1:16:05<08:01,  1.19s/it]

train:   2%|▏         | 81/3515 [01:38<1:08:11,  1.19s/it]
overall:  90%|████████▉ | 3597/4000 [1:16:07<08:10,  1.22s/it]

train:   2%|▏         | 82/3515 [01:39<1:09:42,  1.22s/it]
overall:  90%|████████▉ | 3598/4000 [1:16:08<08:18,  1.24s/it]

train:   2%|▏         | 83/3515 [01:40<1:10:57,  1.24s/it]
overall:  90%|████████▉ | 3599/4000 [1:16:09<08:23,  1.26s/it]

train:   2%|▏         | 84/3515 [01:41<1:11:49,  1.26s/it]
overall:  90%|█████████ | 3600/4000 [1:16:11<08:26,  1.27s/it]

train:   2%|▏         | 85/3515 [01:43<1:12:20,  1.27s/it]
overall:  90%|█████████ | 3601/4000 [1:16:12<08:21,  1.26s/it]

train:   2%|▏         | 86/3515 [01:44<1:11:52,  1.26s/it]
overall:  90%|█████████ | 3602/4000 [1:16:13<08:07,  1.23s/it]

train:   2%|▏         | 87/3515 [01:45<1:10:01,  1.23s/it]
overall:  90%|█████████ | 3603/4000 [1:16:14<08:07,  1.23s/it]

train:   3%|▎         | 88/3515 [01:46<1:10:08,  1.23s/it]
overall:  90%|█████████ | 3604/4000 [1:16:15<08:14,  1.25s/it]

train:   3%|▎         | 89/3515 [01:48<1:11:15,  1.25s/it]
overall:  90%|█████████ | 3605/4000 [1:16:17<08:02,  1.22s/it]

train:   3%|▎         | 90/3515 [01:49<1:09:45,  1.22s/it]
overall:  90%|█████████ | 3606/4000 [1:16:18<07:53,  1.20s/it]

train:   3%|▎         | 91/3515 [01:50<1:08:37,  1.20s/it]
overall:  90%|█████████ | 3607/4000 [1:16:19<07:53,  1.21s/it]

train:   3%|▎         | 92/3515 [01:51<1:08:45,  1.21s/it]
overall:  90%|█████████ | 3608/4000 [1:16:20<08:01,  1.23s/it]

train:   3%|▎         | 93/3515 [01:52<1:10:02,  1.23s/it]
overall:  90%|█████████ | 3609/4000 [1:16:21<06:20,  1.03it/s]

train:   3%|▎         | 94/3515 [01:53<55:31,  1.03it/s]  
overall:  90%|█████████ | 3610/4000 [1:16:22<06:17,  1.03it/s]

train:   3%|▎         | 95/3515 [01:54<55:13,  1.03it/s]
overall:  90%|█████████ | 3611/4000 [1:16:23<06:38,  1.02s/it]

train:   3%|▎         | 96/3515 [01:55<58:20,  1.02s/it]
overall:  90%|█████████ | 3612/4000 [1:16:24<06:45,  1.04s/it]

train:   3%|▎         | 97/3515 [01:56<59:28,  1.04s/it]
overall:  90%|█████████ | 3613/4000 [1:16:25<06:49,  1.06s/it]

train:   3%|▎         | 98/3515 [01:57<1:00:19,  1.06s/it]
overall:  90%|█████████ | 3614/4000 [1:16:26<07:00,  1.09s/it]

train:   3%|▎         | 99/3515 [01:58<1:01:56,  1.09s/it]
overall:  90%|█████████ | 3615/4000 [1:16:27<07:09,  1.12s/it]

train:   3%|▎         | 100/3515 [01:59<1:03:28,  1.12s/it]
overall:  90%|█████████ | 3616/4000 [1:16:29<07:38,  1.19s/it]

train:   3%|▎         | 101/3515 [02:01<1:07:53,  1.19s/it]
overall:  90%|█████████ | 3617/4000 [1:16:30<07:39,  1.20s/it]

train:   3%|▎         | 102/3515 [02:02<1:08:17,  1.20s/it]
overall:  90%|█████████ | 3618/4000 [1:16:31<07:47,  1.22s/it]

train:   3%|▎         | 103/3515 [02:03<1:09:38,  1.22s/it]
overall:  90%|█████████ | 3619/4000 [1:16:32<06:36,  1.04s/it]

train:   3%|▎         | 104/3515 [02:04<59:10,  1.04s/it]  
overall:  90%|█████████ | 3620/4000 [1:16:32<05:40,  1.11it/s]

train:   3%|▎         | 105/3515 [02:04<50:59,  1.11it/s]
overall:  91%|█████████ | 3621/4000 [1:16:33<04:27,  1.42it/s]

train:   3%|▎         | 106/3515 [02:05<40:05,  1.42it/s]
overall:  91%|█████████ | 3622/4000 [1:16:34<05:22,  1.17it/s]

train:   3%|▎         | 107/3515 [02:06<48:28,  1.17it/s]
overall:  91%|█████████ | 3623/4000 [1:16:35<06:11,  1.01it/s]

train:   3%|▎         | 108/3515 [02:07<56:00,  1.01it/s]
overall:  91%|█████████ | 3624/4000 [1:16:36<06:23,  1.02s/it]

train:   3%|▎         | 109/3515 [02:08<57:56,  1.02s/it]
overall:  91%|█████████ | 3625/4000 [1:16:37<05:16,  1.18it/s]

train:   3%|▎         | 110/3515 [02:09<47:55,  1.18it/s]
overall:  91%|█████████ | 3626/4000 [1:16:38<06:04,  1.03it/s]

train:   3%|▎         | 111/3515 [02:10<55:16,  1.03it/s]
overall:  91%|█████████ | 3627/4000 [1:16:39<06:23,  1.03s/it]

train:   3%|▎         | 112/3515 [02:11<58:19,  1.03s/it]
overall:  91%|█████████ | 3628/4000 [1:16:40<07:09,  1.15s/it]

train:   3%|▎         | 113/3515 [02:13<1:05:28,  1.15s/it]
overall:  91%|█████████ | 3629/4000 [1:16:42<07:14,  1.17s/it]

train:   3%|▎         | 114/3515 [02:14<1:06:27,  1.17s/it]
overall:  91%|█████████ | 3630/4000 [1:16:42<05:35,  1.10it/s]

train:   3%|▎         | 115/3515 [02:14<51:23,  1.10it/s]  
overall:  91%|█████████ | 3631/4000 [1:16:43<06:09,  1.00s/it]

train:   3%|▎         | 116/3515 [02:15<56:41,  1.00s/it]
overall:  91%|█████████ | 3632/4000 [1:16:44<06:31,  1.06s/it]

train:   3%|▎         | 117/3515 [02:17<1:00:12,  1.06s/it]
overall:  91%|█████████ | 3633/4000 [1:16:45<06:15,  1.02s/it]

train:   3%|▎         | 118/3515 [02:17<57:54,  1.02s/it]  
overall:  91%|█████████ | 3634/4000 [1:16:47<06:32,  1.07s/it]

train:   3%|▎         | 119/3515 [02:19<1:00:43,  1.07s/it]
overall:  91%|█████████ | 3635/4000 [1:16:47<06:20,  1.04s/it]

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overall:  91%|█████████ | 3636/4000 [1:16:49<06:35,  1.09s/it]

train:   3%|▎         | 121/3515 [02:21<1:01:26,  1.09s/it]
overall:  91%|█████████ | 3637/4000 [1:16:50<06:25,  1.06s/it]

train:   3%|▎         | 122/3515 [02:22<1:00:04,  1.06s/it]
overall:  91%|█████████ | 3638/4000 [1:16:51<06:37,  1.10s/it]

train:   3%|▎         | 123/3515 [02:23<1:02:04,  1.10s/it]
overall:  91%|█████████ | 3639/4000 [1:16:52<06:56,  1.15s/it]

train:   4%|▎         | 124/3515 [02:24<1:05:16,  1.15s/it]
overall:  91%|█████████ | 3640/4000 [1:16:53<07:08,  1.19s/it]

train:   4%|▎         | 125/3515 [02:26<1:07:14,  1.19s/it]
overall:  91%|█████████ | 3641/4000 [1:16:54<05:44,  1.04it/s]

train:   4%|▎         | 126/3515 [02:26<54:07,  1.04it/s]  
overall:  91%|█████████ | 3642/4000 [1:16:55<06:13,  1.04s/it]

train:   4%|▎         | 127/3515 [02:27<58:55,  1.04s/it]
overall:  91%|█████████ | 3643/4000 [1:16:56<06:12,  1.04s/it]

train:   4%|▎         | 128/3515 [02:28<58:53,  1.04s/it]
overall:  91%|█████████ | 3644/4000 [1:16:57<06:31,  1.10s/it]

train:   4%|▎         | 129/3515 [02:30<1:01:58,  1.10s/it]
overall:  91%|█████████ | 3645/4000 [1:16:58<06:18,  1.07s/it]

train:   4%|▎         | 130/3515 [02:31<1:00:06,  1.07s/it]
overall:  91%|█████████ | 3646/4000 [1:17:00<06:40,  1.13s/it]

train:   4%|▎         | 131/3515 [02:32<1:03:43,  1.13s/it]
overall:  91%|█████████ | 3647/4000 [1:17:01<06:37,  1.12s/it]

train:   4%|▍         | 132/3515 [02:33<1:03:25,  1.12s/it]
overall:  91%|█████████ | 3648/4000 [1:17:02<06:53,  1.17s/it]

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overall:  91%|█████████ | 3649/4000 [1:17:03<06:47,  1.16s/it]

train:   4%|▍         | 134/3515 [02:35<1:05:27,  1.16s/it]
overall:  91%|█████████▏| 3650/4000 [1:17:04<06:51,  1.18s/it]

train:   4%|▍         | 135/3515 [02:37<1:06:16,  1.18s/it]
overall:  91%|█████████▏| 3651/4000 [1:17:06<06:59,  1.20s/it]

train:   4%|▍         | 136/3515 [02:38<1:07:45,  1.20s/it]
overall:  91%|█████████▏| 3652/4000 [1:17:07<07:03,  1.22s/it]

train:   4%|▍         | 137/3515 [02:39<1:08:27,  1.22s/it]
overall:  91%|█████████▏| 3653/4000 [1:17:08<07:02,  1.22s/it]

train:   4%|▍         | 138/3515 [02:40<1:08:34,  1.22s/it]
overall:  91%|█████████▏| 3654/4000 [1:17:09<07:04,  1.23s/it]

train:   4%|▍         | 139/3515 [02:42<1:08:59,  1.23s/it]
overall:  91%|█████████▏| 3655/4000 [1:17:11<07:02,  1.23s/it]

train:   4%|▍         | 140/3515 [02:43<1:08:56,  1.23s/it]
overall:  91%|█████████▏| 3656/4000 [1:17:12<06:53,  1.20s/it]

train:   4%|▍         | 141/3515 [02:44<1:07:32,  1.20s/it]
overall:  91%|█████████▏| 3657/4000 [1:17:13<06:38,  1.16s/it]

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overall: 100%|█████████▉| 3984/4000 [1:23:26<00:15,  1.04it/s]

train:  13%|█▎        | 469/3515 [08:58<48:48,  1.04it/s]
overall: 100%|█████████▉| 3985/4000 [1:23:27<00:15,  1.05s/it]

train:  13%|█▎        | 470/3515 [08:59<53:08,  1.05s/it]
overall: 100%|█████████▉| 3986/4000 [1:23:28<00:15,  1.12s/it]

train:  13%|█▎        | 471/3515 [09:00<56:48,  1.12s/it]
overall: 100%|█████████▉| 3987/4000 [1:23:30<00:15,  1.17s/it]

train:  13%|█▎        | 472/3515 [09:02<59:19,  1.17s/it]
overall: 100%|█████████▉| 3988/4000 [1:23:31<00:13,  1.14s/it]

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overall: 100%|█████████▉| 3989/4000 [1:23:31<00:10,  1.01it/s]

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overall: 100%|█████████▉| 3991/4000 [1:23:34<00:09,  1.10s/it]

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overall: 100%|█████████▉| 3992/4000 [1:23:35<00:09,  1.16s/it]

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overall: 100%|█████████▉| 3993/4000 [1:23:36<00:07,  1.14s/it]

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overall: 100%|█████████▉| 3994/4000 [1:23:37<00:07,  1.18s/it]

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overall: 100%|█████████▉| 3995/4000 [1:23:39<00:05,  1.18s/it]

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overall: 100%|█████████▉| 3996/4000 [1:23:40<00:04,  1.18s/it]

train:  14%|█▎        | 481/3515 [09:12<59:29,  1.18s/it]
overall: 100%|█████████▉| 3997/4000 [1:23:41<00:03,  1.20s/it]

train:  14%|█▎        | 482/3515 [09:13<1:00:29,  1.20s/it]
overall: 100%|█████████▉| 3998/4000 [1:23:42<00:02,  1.03s/it]

train:  14%|█▎        | 483/3515 [09:14<52:01,  1.03s/it]  
overall: 100%|█████████▉| 3999/4000 [1:23:43<00:01,  1.09s/it]

train:  14%|█▍        | 484/3515 [09:15<55:14,  1.09s/it]train loss: 18.403221130371094
train per: 0.9028218440534564
train loss: 17.47256088256836
train per: 0.9084972010908569
train loss: 20.064640045166016
train per: 0.9023700860906545
train loss: 19.871803283691406
train per: 0.9634782608695652
train loss: 19.01314353942871
train per: 0.9029185599440755
train loss: 21.686290740966797
train per: 0.9260048477745518
train loss: 22.14466094970703
train per: 0.9002096102311019
train loss: 20.128469467163086
train per: 0.9036768762142326
train loss: 21.58233642578125
train per: 0.923638726445744
train loss: 22.157724380493164
train per: 0.9299094375595806
train loss: 23.192556381225586
train per: 0.8922495274102079
train loss: 23.7672176361084
train per: 0.9256415437462113
train loss: 22.886211395263672
train per: 0.9297497588954875
train loss: 22.385679244995117
train per: 0.9210545305847545
train loss: 22.16008186340332
train per: 0.9137948035300498
train loss: 20.817523956298828
train per: 0.9214657187842932
train loss: 18.98563003540039
train per: 0.8900846432889964
train loss: 20.189786911010742
train per: 0.9051388953951375
train loss: 20.442859649658203
train per: 0.920307432340356
train loss: 22.3075008392334
train per: 0.9222061105599226
train loss: 22.759769439697266
train per: 0.9119655767643159
train loss: 22.668230056762695
train per: 0.9052674561045324
train loss: 21.023252487182617
train per: 0.9033716037196737
train loss: 20.412052154541016
train per: 0.9048661013999055
train loss: 21.449928283691406
train per: 0.9600636477462438
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  22%|██▏       | 583/2703 [00:00<00:00, 5828.49it/s]


word -> phonemes:  44%|████▎     | 1181/2703 [00:00<00:00, 5914.68it/s]


word -> phonemes:  66%|██████▌   | 1773/2703 [00:00<00:00, 5843.69it/s]


word -> phonemes:  88%|████████▊ | 2368/2703 [00:00<00:00, 5882.24it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 5834.90it/s]



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overall: 100%|█████████▉| 3999/4000 [1:26:32<00:01,  1.09s/it]

train:  14%|█▍        | 484/3515 [12:04<55:14,  1.09s/it]
                                                              

                                                         

overall: 100%|█████████▉| 3999/4000 [1:26:32<00:01,  1.09s/it]

train:  14%|█▍        | 484/3515 [12:04<55:14,  1.09s/it]
                                                              

                                                         

overall: 100%|█████████▉| 3999/4000 [1:26:32<00:01,  1.09s/it]

train:  14%|█▍        | 484/3515 [12:04<55:14,  1.09s/it]
overall: 100%|██████████| 4000/4000 [1:26:32<00:00, 51.62s/it]

train:  14%|█▍        | 485/3515 [12:05<43:26:53, 51.62s/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 [12:05<1:15:31,  1.50s/it] 

overall: 100%|██████████| 4000/4000 [1:26:33<00:00,  1.30s/it]
dev loss: 23.28159523010254
dev per: 0.8554422476586888
[Runner] - Save the checkpoint to:
1. result/downstream/grid/dev-best.ckpt
2. result/downstream/grid/states-4000.ckpt