/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.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%|█▎        | 467/3515 [00:00<00:00, 4666.86it/s]

word -> phonemes:  27%|██▋       | 959/3515 [00:00<00:00, 4813.36it/s]

word -> phonemes:  42%|████▏     | 1465/3515 [00:00<00:00, 4922.26it/s]

word -> phonemes:  56%|█████▌    | 1958/3515 [00:00<00:00, 4877.09it/s]

word -> phonemes:  70%|██████▉   | 2446/3515 [00:00<00:00, 4585.96it/s]

word -> phonemes:  83%|████████▎ | 2908/3515 [00:00<00:00, 4331.58it/s]

word -> phonemes:  95%|█████████▌| 3345/3515 [00:00<00:00, 4292.72it/s]
word -> phonemes: 100%|██████████| 3515/3515 [00:00<00:00, 4489.66it/s]


train:   0%|          | 0/3515 [00:00<?, ?it/s]
overall:   0%|          | 1/4000 [00:04<4:28:35,  4.03s/it]

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overall:   0%|          | 2/4000 [00:05<2:35:15,  2.33s/it]

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overall:   0%|          | 3/4000 [00:06<2:02:25,  1.84s/it]

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overall:   0%|          | 5/4000 [00:08<1:35:56,  1.44s/it]

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overall:   0%|          | 6/4000 [00:09<1:28:31,  1.33s/it]

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overall:   0%|          | 7/4000 [00:11<1:26:45,  1.30s/it]

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overall:   0%|          | 8/4000 [00:12<1:25:27,  1.28s/it]

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overall:   0%|          | 9/4000 [00:13<1:24:55,  1.28s/it]

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overall:   0%|          | 10/4000 [00:14<1:07:25,  1.01s/it]

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overall:   0%|          | 11/4000 [00:14<52:21,  1.27it/s]  

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overall:   0%|          | 14/4000 [00:17<1:08:15,  1.03s/it]

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overall:   0%|          | 15/4000 [00:18<1:08:45,  1.04s/it]

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overall:   0%|          | 16/4000 [00:20<1:12:10,  1.09s/it]

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overall:   0%|          | 17/4000 [00:21<1:13:06,  1.10s/it]

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overall:   0%|          | 18/4000 [00:22<1:17:19,  1.17s/it]

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overall:   0%|          | 19/4000 [00:22<1:02:31,  1.06it/s]

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overall:   0%|          | 20/4000 [00:24<1:07:35,  1.02s/it]

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overall:   1%|          | 21/4000 [00:25<1:12:24,  1.09s/it]

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overall:   1%|          | 22/4000 [00:26<1:16:05,  1.15s/it]

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overall:   1%|          | 23/4000 [00:27<1:17:57,  1.18s/it]

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overall:   1%|          | 24/4000 [00:29<1:16:22,  1.15s/it]

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overall:   1%|          | 25/4000 [00:30<1:15:46,  1.14s/it]

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overall:   1%|          | 26/4000 [00:31<1:16:57,  1.16s/it]

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overall:   1%|          | 27/4000 [00:32<1:19:51,  1.21s/it]

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overall:   1%|          | 28/4000 [00:33<1:18:12,  1.18s/it]

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overall:   1%|          | 29/4000 [00:34<1:17:46,  1.18s/it]

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overall:   1%|          | 30/4000 [00:36<1:19:35,  1.20s/it]

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overall:   1%|          | 31/4000 [00:37<1:19:40,  1.20s/it]

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overall:   1%|          | 32/4000 [00:38<1:21:26,  1.23s/it]

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overall:   1%|          | 33/4000 [00:40<1:22:36,  1.25s/it]

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overall:   1%|          | 34/4000 [00:40<1:03:12,  1.05it/s]

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overall:   1%|          | 35/4000 [00:41<1:09:02,  1.04s/it]

train:   1%|          | 35/3515 [00:39<1:00:35,  1.04s/it]
overall:   1%|          | 36/4000 [00:42<1:13:08,  1.11s/it]

train:   1%|          | 36/3515 [00:40<1:04:11,  1.11s/it]
overall:   1%|          | 37/4000 [00:43<1:13:20,  1.11s/it]

train:   1%|          | 37/3515 [00:42<1:04:21,  1.11s/it]
overall:   1%|          | 38/4000 [00:45<1:14:19,  1.13s/it]

train:   1%|          | 38/3515 [00:43<1:05:13,  1.13s/it]
overall:   1%|          | 39/4000 [00:46<1:13:19,  1.11s/it]

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overall:   1%|          | 40/4000 [00:46<1:06:04,  1.00s/it]

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overall:   1%|          | 41/4000 [00:48<1:09:10,  1.05s/it]

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overall:   1%|          | 42/4000 [00:49<1:13:11,  1.11s/it]

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overall:   1%|          | 43/4000 [00:50<1:13:52,  1.12s/it]

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overall:   1%|          | 45/4000 [00:52<1:04:06,  1.03it/s]

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overall:   1%|          | 46/4000 [00:52<53:13,  1.24it/s]  

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overall:   1%|          | 47/4000 [00:53<1:00:43,  1.08it/s]

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overall:   1%|          | 48/4000 [00:54<1:01:57,  1.06it/s]

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overall:   1%|          | 49/4000 [00:56<1:07:33,  1.03s/it]

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overall:   1%|▏         | 50/4000 [00:57<1:09:30,  1.06s/it]

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overall:   1%|▏         | 51/4000 [00:58<1:12:12,  1.10s/it]

train:   1%|▏         | 51/3515 [00:56<1:03:20,  1.10s/it]
overall:   1%|▏         | 52/4000 [00:59<1:14:30,  1.13s/it]

train:   1%|▏         | 52/3515 [00:57<1:05:21,  1.13s/it]
overall:   1%|▏         | 53/4000 [01:00<1:15:33,  1.15s/it]

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overall:   1%|▏         | 54/4000 [01:01<1:14:56,  1.14s/it]

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overall:   1%|▏         | 56/4000 [01:04<1:18:14,  1.19s/it]

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overall:   1%|▏         | 57/4000 [01:05<1:21:27,  1.24s/it]

train:   2%|▏         | 57/3515 [01:03<1:11:26,  1.24s/it]
overall:   1%|▏         | 58/4000 [01:06<1:21:50,  1.25s/it]

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overall:   1%|▏         | 59/4000 [01:08<1:20:34,  1.23s/it]

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overall:   2%|▏         | 60/4000 [01:09<1:19:16,  1.21s/it]

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overall:   2%|▏         | 61/4000 [01:10<1:17:15,  1.18s/it]

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overall:   2%|▏         | 64/4000 [01:13<1:09:38,  1.06s/it]

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overall:   2%|▏         | 65/4000 [01:14<1:13:39,  1.12s/it]

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overall:   2%|▏         | 66/4000 [01:15<1:16:16,  1.16s/it]

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overall:   2%|▏         | 67/4000 [01:17<1:16:22,  1.17s/it]

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overall:   6%|▋         | 251/4000 [04:48<1:05:28,  1.05s/it]

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train:   7%|▋         | 259/3515 [04:56<1:06:03,  1.22s/it]
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train:   7%|▋         | 260/3515 [04:57<1:05:42,  1.21s/it]
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train:   8%|▊         | 264/3515 [05:02<1:06:42,  1.23s/it]
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train:   8%|▊         | 265/3515 [05:03<1:08:01,  1.26s/it]
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train:   8%|▊         | 266/3515 [05:04<1:08:30,  1.27s/it]
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train:   8%|▊         | 269/3515 [05:08<1:02:36,  1.16s/it]
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train:   8%|▊         | 279/3515 [05:20<59:40,  1.11s/it]  
overall:   7%|▋         | 280/4000 [05:23<1:10:34,  1.14s/it]

train:   8%|▊         | 280/3515 [05:21<1:01:22,  1.14s/it]
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train:   8%|▊         | 281/3515 [05:22<1:03:35,  1.18s/it]
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train:   8%|▊         | 282/3515 [05:23<1:05:59,  1.22s/it]
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train:   8%|▊         | 283/3515 [05:24<1:04:36,  1.20s/it]
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train:   8%|▊         | 284/3515 [05:25<1:00:36,  1.13s/it]
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train:   8%|▊         | 285/3515 [05:27<1:01:26,  1.14s/it]
overall:   7%|▋         | 286/4000 [05:29<1:01:36,  1.00it/s]

train:   8%|▊         | 286/3515 [05:27<53:33,  1.00it/s]  
overall:   7%|▋         | 287/4000 [05:30<1:01:19,  1.01it/s]

train:   8%|▊         | 287/3515 [05:28<53:18,  1.01it/s]
overall:   7%|▋         | 288/4000 [05:31<1:05:29,  1.06s/it]

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overall:   7%|▋         | 289/4000 [05:32<1:08:48,  1.11s/it]

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overall:   8%|▊         | 339/4000 [06:25<55:02,  1.11it/s]  

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overall:  10%|▉         | 390/4000 [07:22<54:15,  1.11it/s]  

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overall:  10%|█         | 404/4000 [07:38<1:08:30,  1.14s/it]

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overall:  11%|█         | 427/4000 [08:04<1:02:23,  1.05s/it]

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overall:  11%|█         | 431/4000 [08:08<49:23,  1.20it/s]  

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overall:  11%|█         | 446/4000 [08:24<55:25,  1.07it/s]  

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overall:  11%|█▏        | 453/4000 [08:31<53:26,  1.11it/s]  

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overall:  11%|█▏        | 457/4000 [08:36<1:07:46,  1.15s/it]

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overall:  12%|█▏        | 497/4000 [09:20<1:05:34,  1.12s/it]

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overall:  12%|█▏        | 499/4000 [09:22<1:04:20,  1.10s/it]

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overall:  12%|█▎        | 500/4000 [09:23<55:14,  1.06it/s]  

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overall:  13%|█▎        | 518/4000 [09:44<57:27,  1.01it/s]  

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overall:  14%|█▎        | 544/4000 [10:12<1:04:21,  1.12s/it]

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overall:  14%|█▎        | 545/4000 [10:14<1:06:00,  1.15s/it]

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overall:  14%|█▎        | 546/4000 [10:15<1:07:08,  1.17s/it]

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overall:  14%|█▎        | 549/4000 [10:18<1:09:14,  1.20s/it]

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overall:  14%|█▍        | 550/4000 [10:20<1:09:46,  1.21s/it]

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overall:  14%|█▍        | 554/4000 [10:24<1:04:53,  1.13s/it]

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overall:  14%|█▍        | 555/4000 [10:24<52:32,  1.09it/s]  

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train:  16%|█▌        | 557/3515 [10:25<52:54,  1.07s/it]
overall:  14%|█▍        | 558/4000 [10:28<1:03:41,  1.11s/it]

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overall:  14%|█▍        | 560/4000 [10:30<1:04:28,  1.12s/it]

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overall:  14%|█▍        | 561/4000 [10:32<1:06:03,  1.15s/it]

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overall:  14%|█▍        | 562/4000 [10:32<1:01:15,  1.07s/it]

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overall:  14%|█▍        | 563/4000 [10:34<1:03:37,  1.11s/it]

train:  16%|█▌        | 563/3515 [10:32<54:38,  1.11s/it]
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overall:  14%|█▍        | 565/4000 [10:35<53:53,  1.06it/s]  

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overall:  14%|█▍        | 566/4000 [10:37<58:43,  1.03s/it]

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overall:  14%|█▍        | 568/4000 [10:38<48:00,  1.19it/s]  

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overall:  14%|█▍        | 569/4000 [10:39<54:20,  1.05it/s]

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overall:  14%|█▍        | 570/4000 [10:41<1:00:03,  1.05s/it]

train:  16%|█▌        | 570/3515 [10:39<51:33,  1.05s/it]
overall:  14%|█▍        | 571/4000 [10:42<1:04:05,  1.12s/it]

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overall:  14%|█▍        | 572/4000 [10:43<1:05:47,  1.15s/it]

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overall:  14%|█▍        | 573/4000 [10:44<1:07:56,  1.19s/it]

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overall:  14%|█▍        | 574/4000 [10:46<1:08:07,  1.19s/it]

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overall:  14%|█▍        | 575/4000 [10:47<1:09:25,  1.22s/it]

train:  16%|█▋        | 575/3515 [10:45<59:35,  1.22s/it]
overall:  14%|█▍        | 576/4000 [10:48<1:09:23,  1.22s/it]

train:  16%|█▋        | 576/3515 [10:46<59:34,  1.22s/it]
overall:  14%|█▍        | 577/4000 [10:49<1:07:31,  1.18s/it]

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overall:  14%|█▍        | 578/4000 [10:50<1:08:14,  1.20s/it]

train:  16%|█▋        | 578/3515 [10:49<58:33,  1.20s/it]
overall:  14%|█▍        | 579/4000 [10:51<59:08,  1.04s/it]  

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overall:  14%|█▍        | 580/4000 [10:52<1:01:51,  1.09s/it]

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overall:  15%|█▍        | 581/4000 [10:53<1:01:37,  1.08s/it]

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overall:  15%|█▍        | 582/4000 [10:54<1:02:18,  1.09s/it]

train:  17%|█▋        | 582/3515 [10:53<53:27,  1.09s/it]
overall:  15%|█▍        | 583/4000 [10:56<1:05:23,  1.15s/it]

train:  17%|█▋        | 583/3515 [10:54<56:06,  1.15s/it]
overall:  15%|█▍        | 584/4000 [10:57<1:04:42,  1.14s/it]

train:  17%|█▋        | 584/3515 [10:55<55:31,  1.14s/it]
overall:  15%|█▍        | 585/4000 [10:58<1:07:10,  1.18s/it]

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overall:  15%|█▍        | 586/4000 [10:59<1:08:34,  1.21s/it]

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overall:  15%|█▍        | 587/4000 [11:01<1:09:51,  1.23s/it]

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overall:  15%|█▍        | 588/4000 [11:02<1:09:26,  1.22s/it]

train:  17%|█▋        | 588/3515 [11:00<59:33,  1.22s/it]
overall:  15%|█▍        | 589/4000 [11:03<1:07:38,  1.19s/it]

train:  17%|█▋        | 589/3515 [11:01<58:01,  1.19s/it]
overall:  15%|█▍        | 590/4000 [11:04<58:14,  1.02s/it]  

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overall:  15%|█▍        | 591/4000 [11:05<1:02:27,  1.10s/it]

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overall:  15%|█▍        | 592/4000 [11:06<1:04:31,  1.14s/it]

train:  17%|█▋        | 592/3515 [11:04<55:20,  1.14s/it]
overall:  15%|█▍        | 593/4000 [11:07<1:04:00,  1.13s/it]

train:  17%|█▋        | 593/3515 [11:05<54:53,  1.13s/it]
overall:  15%|█▍        | 594/4000 [11:08<1:05:34,  1.16s/it]

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overall:  15%|█▍        | 595/4000 [11:10<1:06:37,  1.17s/it]

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overall:  15%|█▍        | 596/4000 [11:11<1:07:01,  1.18s/it]

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overall:  15%|█▍        | 597/4000 [11:11<57:45,  1.02s/it]  

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overall:  15%|█▍        | 598/4000 [11:13<1:01:02,  1.08s/it]

train:  17%|█▋        | 598/3515 [11:11<52:20,  1.08s/it]
overall:  15%|█▍        | 599/4000 [11:14<1:01:43,  1.09s/it]

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overall:  15%|█▌        | 600/4000 [11:15<58:55,  1.04s/it]  

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overall:  15%|█▌        | 601/4000 [11:16<55:44,  1.02it/s]

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overall:  15%|█▌        | 602/4000 [11:17<59:03,  1.04s/it]

train:  17%|█▋        | 602/3515 [11:15<50:37,  1.04s/it]
overall:  15%|█▌        | 603/4000 [11:18<1:02:45,  1.11s/it]

train:  17%|█▋        | 603/3515 [11:16<53:47,  1.11s/it]
overall:  15%|█▌        | 604/4000 [11:19<1:03:57,  1.13s/it]

train:  17%|█▋        | 604/3515 [11:17<54:49,  1.13s/it]
overall:  15%|█▌        | 605/4000 [11:21<1:06:24,  1.17s/it]

train:  17%|█▋        | 605/3515 [11:19<56:55,  1.17s/it]
overall:  15%|█▌        | 606/4000 [11:22<1:04:28,  1.14s/it]

train:  17%|█▋        | 606/3515 [11:20<55:15,  1.14s/it]
overall:  15%|█▌        | 607/4000 [11:22<59:30,  1.05s/it]  

train:  17%|█▋        | 607/3515 [11:21<51:00,  1.05s/it]
overall:  15%|█▌        | 608/4000 [11:24<1:03:38,  1.13s/it]

train:  17%|█▋        | 608/3515 [11:22<54:32,  1.13s/it]
overall:  15%|█▌        | 609/4000 [11:25<1:05:06,  1.15s/it]

train:  17%|█▋        | 609/3515 [11:23<55:48,  1.15s/it]
overall:  15%|█▌        | 610/4000 [11:26<1:06:04,  1.17s/it]

train:  17%|█▋        | 610/3515 [11:24<56:37,  1.17s/it]
overall:  15%|█▌        | 611/4000 [11:27<53:53,  1.05it/s]  

train:  17%|█▋        | 611/3515 [11:25<46:10,  1.05it/s]
overall:  15%|█▌        | 612/4000 [11:27<48:11,  1.17it/s]

train:  17%|█▋        | 612/3515 [11:25<41:17,  1.17it/s]
overall:  15%|█▌        | 613/4000 [11:28<54:08,  1.04it/s]

train:  17%|█▋        | 613/3515 [11:27<46:23,  1.04it/s]
overall:  15%|█▌        | 614/4000 [11:30<59:26,  1.05s/it]

train:  17%|█▋        | 614/3515 [11:28<50:55,  1.05s/it]
overall:  15%|█▌        | 615/4000 [11:31<1:02:10,  1.10s/it]

train:  17%|█▋        | 615/3515 [11:29<53:16,  1.10s/it]
overall:  15%|█▌        | 616/4000 [11:32<1:02:26,  1.11s/it]

train:  18%|█▊        | 616/3515 [11:30<53:29,  1.11s/it]
overall:  15%|█▌        | 617/4000 [11:33<1:05:09,  1.16s/it]

train:  18%|█▊        | 617/3515 [11:31<55:49,  1.16s/it]
overall:  15%|█▌        | 618/4000 [11:35<1:07:15,  1.19s/it]

train:  18%|█▊        | 618/3515 [11:33<57:36,  1.19s/it]
overall:  15%|█▌        | 619/4000 [11:36<1:06:51,  1.19s/it]

train:  18%|█▊        | 619/3515 [11:34<57:16,  1.19s/it]
overall:  16%|█▌        | 620/4000 [11:37<1:07:19,  1.20s/it]

train:  18%|█▊        | 620/3515 [11:35<57:40,  1.20s/it]
overall:  16%|█▌        | 621/4000 [11:38<1:07:47,  1.20s/it]

train:  18%|█▊        | 621/3515 [11:36<58:03,  1.20s/it]
overall:  16%|█▌        | 622/4000 [11:39<1:07:35,  1.20s/it]

train:  18%|█▊        | 622/3515 [11:38<57:53,  1.20s/it]
overall:  16%|█▌        | 623/4000 [11:41<1:07:59,  1.21s/it]

train:  18%|█▊        | 623/3515 [11:39<58:13,  1.21s/it]
overall:  16%|█▌        | 624/4000 [11:42<1:07:59,  1.21s/it]

train:  18%|█▊        | 624/3515 [11:40<58:13,  1.21s/it]
overall:  16%|█▌        | 625/4000 [11:43<1:06:34,  1.18s/it]

train:  18%|█▊        | 625/3515 [11:41<57:00,  1.18s/it]
overall:  16%|█▌        | 626/4000 [11:44<1:06:28,  1.18s/it]

train:  18%|█▊        | 626/3515 [11:42<56:55,  1.18s/it]
overall:  16%|█▌        | 627/4000 [11:45<1:07:37,  1.20s/it]

train:  18%|█▊        | 627/3515 [11:44<57:54,  1.20s/it]
overall:  16%|█▌        | 628/4000 [11:47<1:08:16,  1.21s/it]

train:  18%|█▊        | 628/3515 [11:45<58:26,  1.21s/it]
overall:  16%|█▌        | 629/4000 [11:48<1:08:25,  1.22s/it]

train:  18%|█▊        | 629/3515 [11:46<58:34,  1.22s/it]
overall:  16%|█▌        | 630/4000 [11:49<1:04:05,  1.14s/it]

train:  18%|█▊        | 630/3515 [11:47<54:51,  1.14s/it]
overall:  16%|█▌        | 631/4000 [11:50<1:03:48,  1.14s/it]

train:  18%|█▊        | 631/3515 [11:48<54:37,  1.14s/it]
overall:  16%|█▌        | 632/4000 [11:51<1:05:28,  1.17s/it]

train:  18%|█▊        | 632/3515 [11:49<56:03,  1.17s/it]
overall:  16%|█▌        | 633/4000 [11:52<1:08:20,  1.22s/it]

train:  18%|█▊        | 633/3515 [11:51<58:29,  1.22s/it]
overall:  16%|█▌        | 634/4000 [11:54<1:09:24,  1.24s/it]

train:  18%|█▊        | 634/3515 [11:52<59:24,  1.24s/it]
overall:  16%|█▌        | 635/4000 [11:54<55:29,  1.01it/s]  

train:  18%|█▊        | 635/3515 [11:52<47:29,  1.01it/s]
overall:  16%|█▌        | 636/4000 [11:55<57:05,  1.02s/it]

train:  18%|█▊        | 636/3515 [11:53<48:51,  1.02s/it]
overall:  16%|█▌        | 637/4000 [11:56<1:00:26,  1.08s/it]

train:  18%|█▊        | 637/3515 [11:55<51:43,  1.08s/it]
overall:  16%|█▌        | 638/4000 [11:57<48:33,  1.15it/s]  

train:  18%|█▊        | 638/3515 [11:55<41:33,  1.15it/s]
overall:  16%|█▌        | 639/4000 [11:58<55:13,  1.01it/s]

train:  18%|█▊        | 639/3515 [11:56<47:15,  1.01it/s]
overall:  16%|█▌        | 640/4000 [11:59<55:28,  1.01it/s]

train:  18%|█▊        | 640/3515 [11:57<47:28,  1.01it/s]
overall:  16%|█▌        | 641/4000 [12:00<58:37,  1.05s/it]

train:  18%|█▊        | 641/3515 [11:59<50:09,  1.05s/it]
overall:  16%|█▌        | 642/4000 [12:02<1:01:16,  1.09s/it]

train:  18%|█▊        | 642/3515 [12:00<52:25,  1.09s/it]
overall:  16%|█▌        | 643/4000 [12:03<1:04:18,  1.15s/it]

train:  18%|█▊        | 643/3515 [12:01<55:01,  1.15s/it]
overall:  16%|█▌        | 644/4000 [12:04<1:05:05,  1.16s/it]

train:  18%|█▊        | 644/3515 [12:02<55:40,  1.16s/it]
overall:  16%|█▌        | 645/4000 [12:05<56:05,  1.00s/it]  

train:  18%|█▊        | 645/3515 [12:03<47:59,  1.00s/it]
overall:  16%|█▌        | 646/4000 [12:06<59:33,  1.07s/it]

train:  18%|█▊        | 646/3515 [12:04<50:57,  1.07s/it]
overall:  16%|█▌        | 647/4000 [12:07<59:28,  1.06s/it]

train:  18%|█▊        | 647/3515 [12:05<50:52,  1.06s/it]
overall:  16%|█▌        | 648/4000 [12:08<1:01:24,  1.10s/it]

train:  18%|█▊        | 648/3515 [12:06<52:31,  1.10s/it]
overall:  16%|█▌        | 649/4000 [12:09<1:03:42,  1.14s/it]

train:  18%|█▊        | 649/3515 [12:08<54:29,  1.14s/it]
overall:  16%|█▋        | 650/4000 [12:10<1:01:45,  1.11s/it]

train:  18%|█▊        | 650/3515 [12:09<52:48,  1.11s/it]
overall:  16%|█▋        | 651/4000 [12:12<1:05:13,  1.17s/it]

train:  19%|█▊        | 651/3515 [12:10<55:47,  1.17s/it]
overall:  16%|█▋        | 652/4000 [12:13<1:07:27,  1.21s/it]

train:  19%|█▊        | 652/3515 [12:11<57:41,  1.21s/it]
overall:  16%|█▋        | 653/4000 [12:14<1:08:14,  1.22s/it]

train:  19%|█▊        | 653/3515 [12:12<58:21,  1.22s/it]
overall:  16%|█▋        | 654/4000 [12:15<1:08:06,  1.22s/it]

train:  19%|█▊        | 654/3515 [12:14<58:13,  1.22s/it]
overall:  16%|█▋        | 655/4000 [12:16<1:03:11,  1.13s/it]

train:  19%|█▊        | 655/3515 [12:15<54:01,  1.13s/it]
overall:  16%|█▋        | 656/4000 [12:18<1:05:59,  1.18s/it]

train:  19%|█▊        | 656/3515 [12:16<56:25,  1.18s/it]
overall:  16%|█▋        | 657/4000 [12:19<1:06:12,  1.19s/it]

train:  19%|█▊        | 657/3515 [12:17<56:36,  1.19s/it]
overall:  16%|█▋        | 658/4000 [12:20<1:04:02,  1.15s/it]

train:  19%|█▊        | 658/3515 [12:18<54:44,  1.15s/it]
overall:  16%|█▋        | 659/4000 [12:20<54:22,  1.02it/s]  

train:  19%|█▊        | 659/3515 [12:19<46:28,  1.02it/s]
overall:  16%|█▋        | 660/4000 [12:22<59:20,  1.07s/it]

train:  19%|█▉        | 660/3515 [12:20<50:43,  1.07s/it]
overall:  17%|█▋        | 661/4000 [12:23<1:02:33,  1.12s/it]

train:  19%|█▉        | 661/3515 [12:21<53:28,  1.12s/it]
overall:  17%|█▋        | 662/4000 [12:24<1:01:23,  1.10s/it]

train:  19%|█▉        | 662/3515 [12:22<52:28,  1.10s/it]
overall:  17%|█▋        | 663/4000 [12:25<1:01:45,  1.11s/it]

train:  19%|█▉        | 663/3515 [12:23<52:46,  1.11s/it]
overall:  17%|█▋        | 664/4000 [12:26<1:01:53,  1.11s/it]

train:  19%|█▉        | 664/3515 [12:25<52:53,  1.11s/it]
overall:  17%|█▋        | 665/4000 [12:28<1:03:42,  1.15s/it]

train:  19%|█▉        | 665/3515 [12:26<54:26,  1.15s/it]
overall:  17%|█▋        | 666/4000 [12:29<1:05:14,  1.17s/it]

train:  19%|█▉        | 666/3515 [12:27<55:45,  1.17s/it]
overall:  17%|█▋        | 667/4000 [12:30<1:02:23,  1.12s/it]

train:  19%|█▉        | 667/3515 [12:28<53:18,  1.12s/it]
overall:  17%|█▋        | 668/4000 [12:31<1:02:53,  1.13s/it]

train:  19%|█▉        | 668/3515 [12:29<53:43,  1.13s/it]
overall:  17%|█▋        | 669/4000 [12:32<59:57,  1.08s/it]  

train:  19%|█▉        | 669/3515 [12:30<51:13,  1.08s/it]
overall:  17%|█▋        | 670/4000 [12:32<51:34,  1.08it/s]

train:  19%|█▉        | 670/3515 [12:31<44:03,  1.08it/s]
overall:  17%|█▋        | 671/4000 [12:33<46:56,  1.18it/s]

train:  19%|█▉        | 671/3515 [12:31<40:06,  1.18it/s]
overall:  17%|█▋        | 672/4000 [12:34<51:37,  1.07it/s]

train:  19%|█▉        | 672/3515 [12:32<44:06,  1.07it/s]
overall:  17%|█▋        | 673/4000 [12:36<57:17,  1.03s/it]

train:  19%|█▉        | 673/3515 [12:34<48:56,  1.03s/it]
overall:  17%|█▋        | 674/4000 [12:36<45:01,  1.23it/s]

train:  19%|█▉        | 674/3515 [12:34<38:27,  1.23it/s]
overall:  17%|█▋        | 675/4000 [12:37<52:36,  1.05it/s]

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overall:  17%|█▋        | 676/4000 [12:38<57:16,  1.03s/it]

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overall:  17%|█▋        | 677/4000 [12:40<1:00:59,  1.10s/it]

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overall:  17%|█▋        | 678/4000 [12:41<1:02:40,  1.13s/it]

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overall:  17%|█▋        | 679/4000 [12:42<1:04:54,  1.17s/it]

train:  19%|█▉        | 679/3515 [12:40<55:26,  1.17s/it]
overall:  17%|█▋        | 680/4000 [12:43<1:07:55,  1.23s/it]

train:  19%|█▉        | 680/3515 [12:42<58:00,  1.23s/it]
overall:  17%|█▋        | 681/4000 [12:45<1:08:56,  1.25s/it]

train:  19%|█▉        | 681/3515 [12:43<58:52,  1.25s/it]
overall:  17%|█▋        | 682/4000 [12:46<1:08:26,  1.24s/it]

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overall:  17%|█▋        | 683/4000 [12:47<1:08:16,  1.24s/it]

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overall:  17%|█▋        | 684/4000 [12:48<1:08:04,  1.23s/it]

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overall:  17%|█▋        | 685/4000 [12:49<1:06:11,  1.20s/it]

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overall:  17%|█▋        | 686/4000 [12:51<1:03:59,  1.16s/it]

train:  20%|█▉        | 686/3515 [12:49<54:37,  1.16s/it]
overall:  17%|█▋        | 687/4000 [12:51<49:22,  1.12it/s]  

train:  20%|█▉        | 687/3515 [12:49<42:08,  1.12it/s]
overall:  17%|█▋        | 688/4000 [12:52<53:20,  1.03it/s]

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train:  28%|██▊       | 999/3515 [18:41<49:58,  1.19s/it]train loss: 288.005615234375
train per: 1.0153869062391423
train loss: 180.70970153808594
train per: 0.936562056693462
train loss: 64.18331909179688
train per: 0.906876427302715
train loss: 51.75049591064453
train per: 0.9065448554740153
train loss: 38.22338104248047
train per: 0.9111734243911264
train loss: 36.27304458618164
train per: 0.8914969208905732
train loss: 34.87556838989258
train per: 0.8934071686365265
train loss: 26.714252471923828
train per: 0.8934629014643279
train loss: 26.248733520507812
train per: 0.8919873897128833
train loss: 25.299036026000977
train per: 0.8932849364791289
train loss: 24.552396774291992
train per: 0.912979420018709
train loss: 22.47393035888672
train per: 0.8887608935189822
train loss: 22.220233917236328
train per: 0.8927004284755562
train loss: 21.741825103759766
train per: 0.8951382714894015
train loss: 20.769094467163086
train per: 0.8907858213171534
train loss: 24.952993392944336
train per: 0.903956444749848
train loss: 29.885162353515625
train per: 0.9058215566336216
train loss: 22.951425552368164
train per: 0.8848729938076583
train loss: 19.506797790527344
train per: 0.9003956604977664
train loss: 17.242931365966797
train per: 0.8879750356805922
train loss: 19.402721405029297
train per: 0.8983571623262383
train loss: 19.39764976501465
train per: 0.9188358104280744
train loss: 18.271818161010742
train per: 0.9418604651162791
train loss: 18.485965728759766
train per: 0.8892241162568512
train loss: 20.871906280517578
train per: 0.9076571848430776
train loss: 19.037403106689453
train per: 0.8941198493109016
train loss: 19.4217529296875
train per: 0.9125446502495683
train loss: 19.501567840576172
train per: 0.9034576865908038
train loss: 21.113170623779297
train per: 0.8886043209250432
train loss: 15.767999649047852
train per: 0.9033746176603319
train loss: 16.845083236694336
train per: 0.9136936389858813
train loss: 16.225910186767578
train per: 0.9063607768735333
train loss: 14.473930358886719
train per: 0.8996933425660303
train loss: 14.775398254394531
train per: 0.9402150304083405
train loss: 14.448237419128418
train per: 0.9186691312384473
train loss: 16.516271591186523
train per: 0.9133667200165212
train loss: 15.576169967651367
train per: 0.9091541135573581
train loss: 16.93251609802246
train per: 0.9108813646937193
train loss: 16.25201988220215
train per: 0.8942054215369312
train loss: 14.49298095703125
train per: 0.9004927557549459
train loss: 17.01993179321289
train per: 0.9594225328271225
train loss: 17.153064727783203
train per: 0.8882434713533909
train loss: 18.503559112548828
train per: 0.8991490555451656
train loss: 18.053569793701172
train per: 0.9157483446807515
train loss: 17.911121368408203
train per: 0.9293470321858109
train loss: 19.07320785522461
train per: 0.8966227650651166
train loss: 17.070934295654297
train per: 0.8874347324879637
train loss: 17.200027465820312
train per: 0.8941402797275516
train loss: 18.211387634277344
train per: 0.9513540230483079
train loss: 14.984159469604492
train per: 0.8994992762049407
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  22%|██▏       | 582/2703 [00:00<00:00, 5814.71it/s]


word -> phonemes:  44%|████▍     | 1184/2703 [00:00<00:00, 5932.33it/s]


word -> phonemes:  66%|██████▌   | 1781/2703 [00:00<00:00, 5946.40it/s]


word -> phonemes:  88%|████████▊ | 2376/2703 [00:00<00:00, 5876.46it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 5827.57it/s]



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overall:  25%|██▌       | 1005/4000 [21:32<7:47:07,  9.36s/it] 

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train:  55%|█████▍    | 1919/3515 [38:30<29:14,  1.10s/it]
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train:  55%|█████▍    | 1920/3515 [38:31<29:55,  1.13s/it]
overall:  48%|████▊     | 1921/4000 [38:34<39:51,  1.15s/it]

train:  55%|█████▍    | 1921/3515 [38:32<30:33,  1.15s/it]
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train:  55%|█████▍    | 1923/3515 [38:34<31:04,  1.17s/it]
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train:  55%|█████▍    | 1924/3515 [38:36<31:18,  1.18s/it]
overall:  48%|████▊     | 1925/4000 [38:39<43:30,  1.26s/it]

train:  55%|█████▍    | 1925/3515 [38:37<33:20,  1.26s/it]
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train:  55%|█████▍    | 1926/3515 [38:38<33:17,  1.26s/it]
overall:  48%|████▊     | 1927/4000 [38:40<33:24,  1.03it/s]

train:  55%|█████▍    | 1927/3515 [38:39<25:35,  1.03it/s]
overall:  48%|████▊     | 1928/4000 [38:42<36:52,  1.07s/it]

train:  55%|█████▍    | 1928/3515 [38:40<28:14,  1.07s/it]
overall:  48%|████▊     | 1929/4000 [38:43<37:40,  1.09s/it]

train:  55%|█████▍    | 1929/3515 [38:41<28:50,  1.09s/it]
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train:  55%|█████▍    | 1930/3515 [38:42<29:41,  1.12s/it]
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train:  55%|█████▍    | 1931/3515 [38:43<29:55,  1.13s/it]
overall:  48%|████▊     | 1932/4000 [38:46<39:56,  1.16s/it]

train:  55%|█████▍    | 1932/3515 [38:45<30:34,  1.16s/it]
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train:  55%|█████▍    | 1933/3515 [38:46<30:12,  1.15s/it]
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train:  55%|█████▌    | 1934/3515 [38:47<30:36,  1.16s/it]
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train:  55%|█████▌    | 1935/3515 [38:48<31:27,  1.19s/it]
overall:  48%|████▊     | 1936/4000 [38:51<41:27,  1.21s/it]

train:  55%|█████▌    | 1936/3515 [38:49<31:43,  1.21s/it]
overall:  48%|████▊     | 1937/4000 [38:52<41:12,  1.20s/it]

train:  55%|█████▌    | 1937/3515 [38:51<31:31,  1.20s/it]
overall:  48%|████▊     | 1938/4000 [38:54<41:14,  1.20s/it]

train:  55%|█████▌    | 1938/3515 [38:52<31:32,  1.20s/it]
overall:  48%|████▊     | 1939/4000 [38:55<41:12,  1.20s/it]

train:  55%|█████▌    | 1939/3515 [38:53<31:31,  1.20s/it]
overall:  48%|████▊     | 1940/4000 [38:56<39:58,  1.16s/it]

train:  55%|█████▌    | 1940/3515 [38:54<30:33,  1.16s/it]
overall:  49%|████▊     | 1941/4000 [38:57<40:01,  1.17s/it]

train:  55%|█████▌    | 1941/3515 [38:55<30:35,  1.17s/it]
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train:  55%|█████▌    | 1942/3515 [38:56<30:59,  1.18s/it]
overall:  49%|████▊     | 1943/4000 [39:00<42:26,  1.24s/it]

train:  55%|█████▌    | 1943/3515 [38:58<32:26,  1.24s/it]
overall:  49%|████▊     | 1944/4000 [39:01<41:21,  1.21s/it]

train:  55%|█████▌    | 1944/3515 [38:59<31:35,  1.21s/it]
overall:  49%|████▊     | 1945/4000 [39:02<41:18,  1.21s/it]

train:  55%|█████▌    | 1945/3515 [39:00<31:33,  1.21s/it]
overall:  49%|████▊     | 1946/4000 [39:03<41:27,  1.21s/it]

train:  55%|█████▌    | 1946/3515 [39:01<31:39,  1.21s/it]
overall:  49%|████▊     | 1947/4000 [39:04<41:35,  1.22s/it]

train:  55%|█████▌    | 1947/3515 [39:03<31:45,  1.22s/it]
overall:  49%|████▊     | 1948/4000 [39:05<38:03,  1.11s/it]

train:  55%|█████▌    | 1948/3515 [39:03<29:03,  1.11s/it]
overall:  49%|████▊     | 1949/4000 [39:06<39:28,  1.15s/it]

train:  55%|█████▌    | 1949/3515 [39:05<30:08,  1.15s/it]
overall:  49%|████▉     | 1950/4000 [39:08<40:33,  1.19s/it]

train:  55%|█████▌    | 1950/3515 [39:06<30:57,  1.19s/it]
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train:  56%|█████▌    | 1951/3515 [39:07<31:02,  1.19s/it]
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train:  56%|█████▌    | 1952/3515 [39:08<29:35,  1.14s/it]
overall:  49%|████▉     | 1953/4000 [39:11<40:09,  1.18s/it]

train:  56%|█████▌    | 1953/3515 [39:09<30:38,  1.18s/it]
overall:  49%|████▉     | 1954/4000 [39:12<40:39,  1.19s/it]

train:  56%|█████▌    | 1954/3515 [39:11<31:01,  1.19s/it]
overall:  49%|████▉     | 1955/4000 [39:14<39:51,  1.17s/it]

train:  56%|█████▌    | 1955/3515 [39:12<30:24,  1.17s/it]
overall:  49%|████▉     | 1956/4000 [39:15<39:24,  1.16s/it]

train:  56%|█████▌    | 1956/3515 [39:13<30:03,  1.16s/it]
overall:  49%|████▉     | 1957/4000 [39:16<39:27,  1.16s/it]

train:  56%|█████▌    | 1957/3515 [39:14<30:05,  1.16s/it]
overall:  49%|████▉     | 1958/4000 [39:17<39:41,  1.17s/it]

train:  56%|█████▌    | 1958/3515 [39:15<30:15,  1.17s/it]
overall:  49%|████▉     | 1959/4000 [39:18<40:07,  1.18s/it]

train:  56%|█████▌    | 1959/3515 [39:16<30:35,  1.18s/it]
overall:  49%|████▉     | 1960/4000 [39:20<40:43,  1.20s/it]

train:  56%|█████▌    | 1960/3515 [39:18<31:02,  1.20s/it]
overall:  49%|████▉     | 1961/4000 [39:21<41:27,  1.22s/it]

train:  56%|█████▌    | 1961/3515 [39:19<31:35,  1.22s/it]
overall:  49%|████▉     | 1962/4000 [39:22<41:27,  1.22s/it]

train:  56%|█████▌    | 1962/3515 [39:20<31:35,  1.22s/it]
overall:  49%|████▉     | 1963/4000 [39:23<40:40,  1.20s/it]

train:  56%|█████▌    | 1963/3515 [39:21<30:59,  1.20s/it]
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train:  56%|█████▌    | 1964/3515 [39:23<31:15,  1.21s/it]
overall:  49%|████▉     | 1965/4000 [39:25<38:12,  1.13s/it]

train:  56%|█████▌    | 1965/3515 [39:24<29:05,  1.13s/it]
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train:  56%|█████▌    | 1966/3515 [39:25<29:53,  1.16s/it]
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train:  56%|█████▌    | 1967/3515 [39:26<30:57,  1.20s/it]
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train:  56%|█████▌    | 1968/3515 [39:27<25:36,  1.01it/s]
overall:  49%|████▉     | 1969/4000 [39:30<35:13,  1.04s/it]

train:  56%|█████▌    | 1969/3515 [39:28<26:48,  1.04s/it]
overall:  49%|████▉     | 1970/4000 [39:31<36:57,  1.09s/it]

train:  56%|█████▌    | 1970/3515 [39:29<28:07,  1.09s/it]
overall:  49%|████▉     | 1971/4000 [39:32<37:46,  1.12s/it]

train:  56%|█████▌    | 1971/3515 [39:30<28:44,  1.12s/it]
overall:  49%|████▉     | 1972/4000 [39:33<38:45,  1.15s/it]

train:  56%|█████▌    | 1972/3515 [39:31<29:29,  1.15s/it]
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train:  56%|█████▌    | 1973/3515 [39:33<31:26,  1.22s/it]
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train:  56%|█████▌    | 1974/3515 [39:34<31:16,  1.22s/it]
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train:  56%|█████▌    | 1975/3515 [39:34<25:11,  1.02it/s]
overall:  49%|████▉     | 1976/4000 [39:37<36:13,  1.07s/it]

train:  56%|█████▌    | 1976/3515 [39:36<27:32,  1.07s/it]
overall:  49%|████▉     | 1977/4000 [39:39<37:47,  1.12s/it]

train:  56%|█████▌    | 1977/3515 [39:37<28:44,  1.12s/it]
overall:  49%|████▉     | 1978/4000 [39:40<38:08,  1.13s/it]

train:  56%|█████▋    | 1978/3515 [39:38<28:59,  1.13s/it]
overall:  49%|████▉     | 1979/4000 [39:41<38:48,  1.15s/it]

train:  56%|█████▋    | 1979/3515 [39:39<29:29,  1.15s/it]
overall:  50%|████▉     | 1980/4000 [39:42<38:48,  1.15s/it]

train:  56%|█████▋    | 1980/3515 [39:40<29:29,  1.15s/it]
overall:  50%|████▉     | 1981/4000 [39:43<37:54,  1.13s/it]

train:  56%|█████▋    | 1981/3515 [39:41<28:48,  1.13s/it]
overall:  50%|████▉     | 1982/4000 [39:44<38:54,  1.16s/it]

train:  56%|█████▋    | 1982/3515 [39:43<29:33,  1.16s/it]
overall:  50%|████▉     | 1983/4000 [39:46<40:10,  1.20s/it]

train:  56%|█████▋    | 1983/3515 [39:44<30:31,  1.20s/it]
overall:  50%|████▉     | 1984/4000 [39:47<40:48,  1.21s/it]

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overall:  50%|████▉     | 1985/4000 [39:48<40:48,  1.22s/it]

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train:  57%|█████▋    | 1987/3515 [39:49<30:56,  1.21s/it]
overall:  50%|████▉     | 1988/4000 [39:52<39:48,  1.19s/it]

train:  57%|█████▋    | 1988/3515 [39:50<30:12,  1.19s/it]
overall:  50%|████▉     | 1989/4000 [39:53<39:42,  1.18s/it]

train:  57%|█████▋    | 1989/3515 [39:51<30:07,  1.18s/it]
overall:  50%|████▉     | 1990/4000 [39:54<39:29,  1.18s/it]

train:  57%|█████▋    | 1990/3515 [39:52<29:57,  1.18s/it]
overall:  50%|████▉     | 1991/4000 [39:55<41:12,  1.23s/it]

train:  57%|█████▋    | 1991/3515 [39:54<31:15,  1.23s/it]
overall:  50%|████▉     | 1992/4000 [39:57<41:09,  1.23s/it]

train:  57%|█████▋    | 1992/3515 [39:55<31:12,  1.23s/it]
overall:  50%|████▉     | 1993/4000 [39:58<41:27,  1.24s/it]

train:  57%|█████▋    | 1993/3515 [39:56<31:26,  1.24s/it]
overall:  50%|████▉     | 1994/4000 [39:59<39:16,  1.17s/it]

train:  57%|█████▋    | 1994/3515 [39:57<29:47,  1.17s/it]
overall:  50%|████▉     | 1995/4000 [40:00<38:53,  1.16s/it]

train:  57%|█████▋    | 1995/3515 [39:58<29:29,  1.16s/it]
overall:  50%|████▉     | 1996/4000 [40:01<38:55,  1.17s/it]

train:  57%|█████▋    | 1996/3515 [39:59<29:29,  1.17s/it]
overall:  50%|████▉     | 1997/4000 [40:03<41:14,  1.24s/it]

train:  57%|█████▋    | 1997/3515 [40:01<31:15,  1.24s/it]
overall:  50%|████▉     | 1998/4000 [40:04<41:09,  1.23s/it]

train:  57%|█████▋    | 1998/3515 [40:02<31:11,  1.23s/it]
overall:  50%|████▉     | 1999/4000 [40:05<40:30,  1.21s/it]

train:  57%|█████▋    | 1999/3515 [40:03<30:41,  1.21s/it]dev loss: 16.715970993041992
dev per: 0.8998491155046826
[Runner] - Save the checkpoint to:
1. result/downstream/grid/dev-best.ckpt
train loss: 18.377344131469727
train per: 0.9256280193236714
train loss: 14.173051834106445
train per: 0.9048912378575449
train loss: 15.155080795288086
train per: 0.901171875
train loss: 18.116514205932617
train per: 0.9182944525058601
train loss: 20.15243148803711
train per: 0.9112525924854097
train loss: 20.21717071533203
train per: 0.9111762485288566
train loss: 17.473079681396484
train per: 0.8939683941892422
train loss: 17.718029022216797
train per: 0.9075686003927604
train loss: 22.009571075439453
train per: 0.9353930257599602
train loss: 20.653385162353516
train per: 0.8973719183097828
train loss: 20.97231674194336
train per: 0.8977929652372755
train loss: 22.288188934326172
train per: 0.8836374943194049
train loss: 18.354015350341797
train per: 0.8865482713017192
train loss: 18.154129028320312
train per: 0.88890223396589
train loss: 19.861156463623047
train per: 0.896435871531612
train loss: 17.449413299560547
train per: 0.9091213432220849
train loss: 19.604900360107422
train per: 0.9158802836562622
train loss: 18.630313873291016
train per: 0.8936466536679243
train loss: 16.69192886352539
train per: 0.9314440727962285
train loss: 17.93667984008789
train per: 0.8924713031735314
train loss: 18.856679916381836
train per: 0.9081701067956516
train loss: 17.7342586517334
train per: 0.9021289667068358
train loss: 15.590591430664062
train per: 0.8940958125507482
train loss: 13.75971794128418
train per: 0.9004629037620521
train loss: 15.752937316894531
train per: 0.9136989938925442
train loss: 16.047372817993164
train per: 0.9244998564181105
train loss: 15.619413375854492
train per: 0.9177670424047235
train loss: 17.08942413330078
train per: 0.8940026141162276
train loss: 16.508195877075195
train per: 0.910198326475891
train loss: 17.444766998291016
train per: 0.888044863624777
train loss: 22.700441360473633
train per: 0.9030359708948245
train loss: 21.332033157348633
train per: 0.9069789426417413
train loss: 17.54147720336914
train per: 0.8999123278373257
train loss: 18.550256729125977
train per: 0.9270940822827404
train loss: 18.411449432373047
train per: 0.891485549583236
train loss: 15.833186149597168
train per: 0.8983242142454057
train loss: 15.973358154296875
train per: 0.8984095614530397
train loss: 16.461395263671875
train per: 0.9630939836419289
train loss: 15.865867614746094
train per: 0.894759751408604
train loss: 14.314640998840332
train per: 0.9108267569518783
train loss: 14.089447021484375
train per: 0.9064513739722984
train loss: 14.808626174926758
train per: 0.9285660272729565
train loss: 15.8347749710083
train per: 0.909618656791112
train loss: 15.50769329071045
train per: 0.919606652907612
train loss: 15.472738265991211
train per: 0.9048569361638437
train loss: 20.087827682495117
train per: 0.8999870550161813
train loss: 16.449718475341797
train per: 0.9089902985777527
train loss: 15.983853340148926
train per: 0.9074275705358834
train loss: 14.932957649230957
train per: 0.8903246769476868
train loss: 17.86638069152832
train per: 0.9129823925309887
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  23%|██▎       | 611/2703 [00:00<00:00, 6103.66it/s]


word -> phonemes:  45%|████▌     | 1222/2703 [00:00<00:00, 5839.91it/s]


word -> phonemes:  68%|██████▊   | 1849/2703 [00:00<00:00, 6028.01it/s]


word -> phonemes:  91%|█████████ | 2453/2703 [00:00<00:00, 5982.51it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 5931.17it/s]



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


dev:   0%|          | 1/2703 [00:01<1:00:39,  1.35s/it]


dev:   0%|          | 2/2703 [00:01<30:50,  1.46it/s]  


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dev:   0%|          | 9/2703 [00:03<10:28,  4.29it/s]


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dev:   0%|          | 12/2703 [00:03<09:19,  4.81it/s]


dev:   0%|          | 13/2703 [00:03<08:46,  5.11it/s]


dev:   1%|          | 14/2703 [00:03<08:18,  5.40it/s]


dev:   1%|          | 15/2703 [00:04<08:27,  5.30it/s]


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dev:   1%|          | 17/2703 [00:04<07:47,  5.75it/s]


dev:   1%|          | 18/2703 [00:04<07:52,  5.68it/s]


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dev: 100%|██████████| 2703/2703 [02:44<00:00, 16.44it/s]

                                                            

                                                          

overall:  50%|████▉     | 1999/4000 [42:52<40:30,  1.21s/it]

train:  57%|█████▋    | 1999/3515 [42:51<30:41,  1.21s/it]
                                                            

                                                          

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overall:  50%|█████     | 2012/4000 [43:06<1:02:44,  1.89s/it]

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overall:  50%|█████     | 2015/4000 [43:09<45:43,  1.38s/it]

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overall:  50%|█████     | 2016/4000 [43:10<40:40,  1.23s/it]

train:  57%|█████▋    | 2016/3515 [43:08<30:43,  1.23s/it]
overall:  50%|█████     | 2017/4000 [43:11<40:59,  1.24s/it]

train:  57%|█████▋    | 2017/3515 [43:10<30:58,  1.24s/it]
overall:  50%|█████     | 2018/4000 [43:13<40:49,  1.24s/it]

train:  57%|█████▋    | 2018/3515 [43:11<30:50,  1.24s/it]
overall:  50%|█████     | 2019/4000 [43:14<40:35,  1.23s/it]

train:  57%|█████▋    | 2019/3515 [43:12<30:38,  1.23s/it]
overall:  50%|█████     | 2020/4000 [43:15<40:28,  1.23s/it]

train:  57%|█████▋    | 2020/3515 [43:13<30:33,  1.23s/it]
overall:  51%|█████     | 2021/4000 [43:16<41:22,  1.25s/it]

train:  57%|█████▋    | 2021/3515 [43:15<31:13,  1.25s/it]
overall:  51%|█████     | 2022/4000 [43:17<40:10,  1.22s/it]

train:  58%|█████▊    | 2022/3515 [43:16<30:19,  1.22s/it]
overall:  51%|█████     | 2023/4000 [43:19<39:27,  1.20s/it]

train:  58%|█████▊    | 2023/3515 [43:17<29:46,  1.20s/it]
overall:  51%|█████     | 2024/4000 [43:20<40:35,  1.23s/it]

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overall:  51%|█████     | 2025/4000 [43:21<40:20,  1.23s/it]

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overall:  51%|█████     | 2026/4000 [43:22<40:36,  1.23s/it]

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overall:  51%|█████     | 2027/4000 [43:23<35:39,  1.08s/it]

train:  58%|█████▊    | 2027/3515 [43:21<26:53,  1.08s/it]
overall:  51%|█████     | 2028/4000 [43:24<33:36,  1.02s/it]

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overall:  51%|█████     | 2029/4000 [43:25<34:26,  1.05s/it]

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overall:  51%|█████     | 2030/4000 [43:26<35:53,  1.09s/it]

train:  58%|█████▊    | 2030/3515 [43:25<27:03,  1.09s/it]
overall:  51%|█████     | 2031/4000 [43:27<32:41,  1.00it/s]

train:  58%|█████▊    | 2031/3515 [43:25<24:37,  1.00it/s]
overall:  51%|█████     | 2032/4000 [43:28<34:51,  1.06s/it]

train:  58%|█████▊    | 2032/3515 [43:27<26:16,  1.06s/it]
overall:  51%|█████     | 2033/4000 [43:29<34:05,  1.04s/it]

train:  58%|█████▊    | 2033/3515 [43:28<25:41,  1.04s/it]
overall:  51%|█████     | 2034/4000 [43:31<35:42,  1.09s/it]

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overall:  51%|█████     | 2035/4000 [43:32<36:18,  1.11s/it]

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overall:  51%|█████     | 2036/4000 [43:33<37:06,  1.13s/it]

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overall:  51%|█████     | 2037/4000 [43:34<36:42,  1.12s/it]

train:  58%|█████▊    | 2037/3515 [43:32<27:38,  1.12s/it]
overall:  51%|█████     | 2038/4000 [43:35<37:36,  1.15s/it]

train:  58%|█████▊    | 2038/3515 [43:33<28:18,  1.15s/it]
overall:  51%|█████     | 2039/4000 [43:37<39:55,  1.22s/it]

train:  58%|█████▊    | 2039/3515 [43:35<30:02,  1.22s/it]
overall:  51%|█████     | 2040/4000 [43:38<39:40,  1.21s/it]

train:  58%|█████▊    | 2040/3515 [43:36<29:51,  1.21s/it]
overall:  51%|█████     | 2041/4000 [43:39<39:24,  1.21s/it]

train:  58%|█████▊    | 2041/3515 [43:37<29:39,  1.21s/it]
overall:  51%|█████     | 2042/4000 [43:40<38:45,  1.19s/it]

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overall:  51%|█████     | 2043/4000 [43:41<38:54,  1.19s/it]

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overall:  51%|█████     | 2044/4000 [43:43<39:37,  1.22s/it]

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overall:  51%|█████     | 2045/4000 [43:44<39:31,  1.21s/it]

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overall:  51%|█████     | 2046/4000 [43:45<39:29,  1.21s/it]

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overall:  51%|█████     | 2047/4000 [43:46<39:17,  1.21s/it]

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overall:  51%|█████     | 2048/4000 [43:47<37:41,  1.16s/it]

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overall:  51%|█████     | 2049/4000 [43:48<38:23,  1.18s/it]

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overall:  51%|█████▏    | 2050/4000 [43:50<38:47,  1.19s/it]

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overall:  51%|█████▏    | 2051/4000 [43:51<38:57,  1.20s/it]

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overall:  51%|█████▏    | 2052/4000 [43:52<37:37,  1.16s/it]

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overall:  51%|█████▏    | 2053/4000 [43:53<36:59,  1.14s/it]

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overall:  51%|█████▏    | 2054/4000 [43:54<31:16,  1.04it/s]

train:  58%|█████▊    | 2054/3515 [43:52<23:29,  1.04it/s]
overall:  51%|█████▏    | 2055/4000 [43:55<32:20,  1.00it/s]

train:  58%|█████▊    | 2055/3515 [43:53<24:16,  1.00it/s]
overall:  51%|█████▏    | 2056/4000 [43:56<33:57,  1.05s/it]

train:  58%|█████▊    | 2056/3515 [43:54<25:29,  1.05s/it]
overall:  51%|█████▏    | 2057/4000 [43:57<35:29,  1.10s/it]

train:  59%|█████▊    | 2057/3515 [43:55<26:37,  1.10s/it]
overall:  51%|█████▏    | 2058/4000 [43:58<36:38,  1.13s/it]

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overall:  51%|█████▏    | 2059/4000 [44:00<37:53,  1.17s/it]

train:  59%|█████▊    | 2059/3515 [43:58<28:25,  1.17s/it]
overall:  52%|█████▏    | 2060/4000 [44:01<38:15,  1.18s/it]

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overall:  52%|█████▏    | 2061/4000 [44:02<35:14,  1.09s/it]

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overall:  52%|█████▏    | 2062/4000 [44:03<36:53,  1.14s/it]

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overall:  52%|█████▏    | 2063/4000 [44:04<36:50,  1.14s/it]

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overall:  52%|█████▏    | 2064/4000 [44:04<29:56,  1.08it/s]

train:  59%|█████▊    | 2064/3515 [44:03<22:26,  1.08it/s]
overall:  52%|█████▏    | 2065/4000 [44:06<33:08,  1.03s/it]

train:  59%|█████▊    | 2065/3515 [44:04<24:49,  1.03s/it]
overall:  52%|█████▏    | 2066/4000 [44:07<32:11,  1.00it/s]

train:  59%|█████▉    | 2066/3515 [44:05<24:07,  1.00it/s]
overall:  52%|█████▏    | 2067/4000 [44:08<34:14,  1.06s/it]

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overall:  52%|█████▏    | 2069/4000 [44:11<39:53,  1.24s/it]

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overall:  52%|█████▏    | 2070/4000 [44:12<39:35,  1.23s/it]

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overall:  52%|█████▏    | 2071/4000 [44:13<39:20,  1.22s/it]

train:  59%|█████▉    | 2071/3515 [44:11<29:27,  1.22s/it]
overall:  52%|█████▏    | 2072/4000 [44:14<36:51,  1.15s/it]

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overall:  52%|█████▏    | 2073/4000 [44:15<37:49,  1.18s/it]

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overall:  52%|█████▏    | 2074/4000 [44:16<38:10,  1.19s/it]

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overall:  52%|█████▏    | 2075/4000 [44:17<35:43,  1.11s/it]

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overall:  52%|█████▏    | 2076/4000 [44:19<37:08,  1.16s/it]

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overall:  52%|█████▏    | 2077/4000 [44:20<36:58,  1.15s/it]

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overall:  52%|█████▏    | 2080/4000 [44:23<37:12,  1.16s/it]

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train:  59%|█████▉    | 2086/3515 [44:29<27:54,  1.17s/it]
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train:  59%|█████▉    | 2087/3515 [44:30<29:05,  1.22s/it]
overall:  52%|█████▏    | 2088/4000 [44:33<38:12,  1.20s/it]

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overall:  74%|███████▍  | 2977/4000 [1:00:59<17:40,  1.04s/it]

train:  85%|████████▍ | 2977/3515 [1:00:57<09:17,  1.04s/it]
overall:  74%|███████▍  | 2978/4000 [1:01:00<18:13,  1.07s/it]

train:  85%|████████▍ | 2978/3515 [1:00:58<09:34,  1.07s/it]
overall:  74%|███████▍  | 2979/4000 [1:01:00<15:31,  1.10it/s]

train:  85%|████████▍ | 2979/3515 [1:00:59<08:09,  1.10it/s]
overall:  74%|███████▍  | 2980/4000 [1:01:01<14:19,  1.19it/s]

train:  85%|████████▍ | 2980/3515 [1:00:59<07:30,  1.19it/s]
overall:  75%|███████▍  | 2981/4000 [1:01:02<16:47,  1.01it/s]

train:  85%|████████▍ | 2981/3515 [1:01:01<08:48,  1.01it/s]
overall:  75%|███████▍  | 2982/4000 [1:01:04<17:15,  1.02s/it]

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overall:  75%|███████▍  | 2983/4000 [1:01:04<14:50,  1.14it/s]

train:  85%|████████▍ | 2983/3515 [1:01:02<07:45,  1.14it/s]
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overall:  75%|███████▍  | 2985/4000 [1:01:07<17:29,  1.03s/it]

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overall:  75%|███████▍  | 2994/4000 [1:01:17<17:45,  1.06s/it]

train:  85%|████████▌ | 2994/3515 [1:01:15<09:11,  1.06s/it]
overall:  75%|███████▍  | 2995/4000 [1:01:18<18:25,  1.10s/it]

train:  85%|████████▌ | 2995/3515 [1:01:16<09:32,  1.10s/it]
overall:  75%|███████▍  | 2996/4000 [1:01:19<19:14,  1.15s/it]

train:  85%|████████▌ | 2996/3515 [1:01:17<09:56,  1.15s/it]
overall:  75%|███████▍  | 2997/4000 [1:01:20<19:24,  1.16s/it]

train:  85%|████████▌ | 2997/3515 [1:01:19<10:01,  1.16s/it]
overall:  75%|███████▍  | 2998/4000 [1:01:22<19:43,  1.18s/it]

train:  85%|████████▌ | 2998/3515 [1:01:20<10:10,  1.18s/it]
overall:  75%|███████▍  | 2999/4000 [1:01:23<18:32,  1.11s/it]

train:  85%|████████▌ | 2999/3515 [1:01:21<09:33,  1.11s/it]dev loss: 15.919678688049316
dev per: 0.8930489073881374
[Runner] - Save the checkpoint to:
1. result/downstream/grid/dev-best.ckpt
train loss: 19.80950164794922
train per: 0.8954988284622025
train loss: 19.420446395874023
train per: 0.8869226815478376
train loss: 18.95064926147461
train per: 0.8908696176577011
train loss: 17.338529586791992
train per: 0.919832500882902
train loss: 19.978939056396484
train per: 0.9006237314984407
train loss: 15.867793083190918
train per: 0.9196519256636196
train loss: 17.052486419677734
train per: 0.9264710219731603
train loss: 16.580171585083008
train per: 0.8913168752737247
train loss: 16.125778198242188
train per: 0.9467697798929209
train loss: 17.94526481628418
train per: 0.900479694384754
train loss: 18.577083587646484
train per: 0.9103764661369655
train loss: 18.957561492919922
train per: 0.8986492584458952
train loss: 18.980112075805664
train per: 0.910038233750656
train loss: 19.50119972229004
train per: 0.8987067917740289
train loss: 21.214059829711914
train per: 0.9201401562157822
train loss: 17.659717559814453
train per: 0.9027226874296068
train loss: 16.903833389282227
train per: 0.899576165544752
train loss: 18.851102828979492
train per: 0.9144283404713958
train loss: 17.820947647094727
train per: 0.9104187175202033
train loss: 21.843494415283203
train per: 0.9021625574592561
train loss: 20.05101203918457
train per: 0.9232602596886715
train loss: 20.07644271850586
train per: 0.894413107708837
train loss: 21.55221176147461
train per: 0.9123403648124807
train loss: 18.13694953918457
train per: 0.8928634628510757
train loss: 18.795269012451172
train per: 0.8909122542481007
train loss: 17.0642147064209
train per: 0.8964158331878382
train loss: 19.586406707763672
train per: 0.9245569236214699
train loss: 19.3275203704834
train per: 0.8947849954254345
train loss: 19.79979133605957
train per: 0.8900480791672502
train loss: 19.221019744873047
train per: 0.9008920453149191
train loss: 23.087112426757812
train per: 0.9312662721893491
train loss: 19.196636199951172
train per: 0.9033098775084701
train loss: 19.023780822753906
train per: 0.9140127388535032
train loss: 16.806861877441406
train per: 0.8970293461858967
train loss: 17.005905151367188
train per: 0.904022450888681
train loss: 17.291336059570312
train per: 0.8983600407310145
train loss: 18.293210983276367
train per: 0.9148687750647241
train loss: 17.185672760009766
train per: 0.8937214462863856
train loss: 18.732458114624023
train per: 0.9081522576668207
train loss: 18.208524703979492
train per: 0.910843140103637
train loss: 17.555072784423828
train per: 0.8935096613736369
train loss: 17.271121978759766
train per: 0.935194572252983
train loss: 17.08310317993164
train per: 0.9020428191420676
train loss: 18.08146858215332
train per: 0.8967035640433038
train loss: 21.657249450683594
train per: 0.9188602873091881
train loss: 20.452159881591797
train per: 0.8927242969796161
train loss: 20.699108123779297
train per: 0.8993030034216196
train loss: 23.174854278564453
train per: 0.8996435491973876
train loss: 21.613452911376953
train per: 0.9056578596210302
train loss: 20.167261123657227
train per: 0.9095186306033668
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  21%|██        | 562/2703 [00:00<00:00, 5619.21it/s]


word -> phonemes:  42%|████▏     | 1131/2703 [00:00<00:00, 5657.26it/s]


word -> phonemes:  63%|██████▎   | 1700/2703 [00:00<00:00, 5668.23it/s]


word -> phonemes:  84%|████████▍ | 2267/2703 [00:00<00:00, 5665.71it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 5617.39it/s]



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overall:  76%|███████▌  | 3036/4000 [1:04:53<19:17,  1.20s/it]

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overall:  77%|███████▋  | 3095/4000 [1:05:59<16:38,  1.10s/it]

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overall:  77%|███████▋  | 3097/4000 [1:06:01<15:09,  1.01s/it]

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overall:  77%|███████▋  | 3098/4000 [1:06:02<16:16,  1.08s/it]

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overall:  77%|███████▋  | 3099/4000 [1:06:02<12:32,  1.20it/s]

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overall:  78%|███████▊  | 3101/4000 [1:06:04<12:12,  1.23it/s]

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overall:  78%|███████▊  | 3102/4000 [1:06:05<13:55,  1.08it/s]

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overall:  78%|███████▊  | 3103/4000 [1:06:07<15:24,  1.03s/it]

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overall:  78%|███████▊  | 3108/4000 [1:06:12<15:50,  1.07s/it]

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overall:  78%|███████▊  | 3109/4000 [1:06:13<16:12,  1.09s/it]

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overall:  78%|███████▊  | 3110/4000 [1:06:14<16:15,  1.10s/it]

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overall:  78%|███████▊  | 3111/4000 [1:06:16<16:44,  1.13s/it]

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overall:  78%|███████▊  | 3121/4000 [1:06:27<16:50,  1.15s/it]

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overall:  78%|███████▊  | 3129/4000 [1:06:35<15:15,  1.05s/it]

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overall:  78%|███████▊  | 3133/4000 [1:06:40<16:39,  1.15s/it]

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overall:  78%|███████▊  | 3134/4000 [1:06:41<15:57,  1.11s/it]

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overall:  78%|███████▊  | 3135/4000 [1:06:42<16:41,  1.16s/it]

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overall:  78%|███████▊  | 3136/4000 [1:06:43<17:08,  1.19s/it]

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overall:  78%|███████▊  | 3137/4000 [1:06:44<17:12,  1.20s/it]

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overall:  78%|███████▊  | 3138/4000 [1:06:46<18:07,  1.26s/it]

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overall:  78%|███████▊  | 3139/4000 [1:06:47<16:46,  1.17s/it]

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overall:  78%|███████▊  | 3140/4000 [1:06:47<13:22,  1.07it/s]

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overall:  79%|███████▊  | 3141/4000 [1:06:48<12:41,  1.13it/s]

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overall:  79%|███████▊  | 3145/4000 [1:06:52<15:11,  1.07s/it]

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overall:  79%|███████▊  | 3146/4000 [1:06:53<15:29,  1.09s/it]

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overall:  87%|████████▋ | 3498/4000 [1:13:30<11:07,  1.33s/it]

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overall:  88%|████████▊ | 3515/4000 [1:13:48<09:14,  1.14s/it]

train: 100%|██████████| 3515/3515 [1:13:47<00:00,  1.14s/it]403-128339-0009 Failed!!!
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 [1:13:47<00:00,  1.26s/it]
dev loss: 16.180749893188477
dev per: 0.8812122788761707
[Runner] - Save the checkpoint to:
1. result/downstream/grid/dev-best.ckpt
train loss: 20.01369857788086
train per: 0.8990413984305249
train loss: 21.952655792236328
train per: 0.8991604521363914
train loss: 19.384437561035156
train per: 0.8982506669184825
train loss: 18.55854606628418
train per: 0.8989386821763229
train loss: 21.26076889038086
train per: 0.9284960196307815
train loss: 15.9694242477417
train per: 0.9006866433400857
train loss: 18.119428634643555
train per: 0.9163140446864135
train loss: 18.6451473236084
train per: 0.89072751833269
train loss: 20.714214324951172
train per: 0.8996315588870537
train loss: 19.288639068603516
train per: 0.9084211284168087
train loss: 18.568544387817383
train per: 0.9281676438882024
train loss: 16.70773696899414
train per: 0.8807890628695776
train loss: 16.49863624572754
train per: 0.8990352587036443
train loss: 16.073749542236328
train per: 0.9141336287875138
train loss: 14.733377456665039
train per: 0.8989574595566208
train loss: 17.273082733154297
train per: 0.9007481673678112
train loss: 15.085110664367676
train per: 0.9101735051687235
train loss: 17.25712013244629
train per: 0.9027217245791909
train loss: 15.464208602905273
train per: 0.8938247011952192
train loss: 16.8783016204834
train per: 0.937870855148342
train loss: 16.04886245727539
train per: 0.8862984599044078
train loss: 18.098669052124023
train per: 0.9345677367790063
train loss: 18.940595626831055
train per: 0.9036488735438039
train loss: 20.259510040283203
train per: 0.9392702958829104
train loss: 20.25912857055664
train per: 0.9069009363079413
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.


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

word -> phonemes:  12%|█▏        | 412/3515 [00:00<00:00, 4118.39it/s]

word -> phonemes:  25%|██▌       | 893/3515 [00:00<00:00, 4522.49it/s]

word -> phonemes:  39%|███▉      | 1386/3515 [00:00<00:00, 4704.03it/s]

word -> phonemes:  53%|█████▎    | 1857/3515 [00:00<00:00, 4648.86it/s]

word -> phonemes:  67%|██████▋   | 2351/3515 [00:00<00:00, 4750.31it/s]

word -> phonemes:  81%|████████  | 2830/3515 [00:00<00:00, 4762.55it/s]

word -> phonemes:  94%|█████████▍| 3307/3515 [00:00<00:00, 4724.18it/s]
word -> phonemes: 100%|██████████| 3515/3515 [00:00<00:00, 4669.77it/s]


train:   0%|          | 0/3515 [00:00<?, ?it/s]
overall:  88%|████████▊ | 3516/4000 [1:13:53<17:40,  2.19s/it]

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overall:  88%|████████▊ | 3520/4000 [1:13:58<11:41,  1.46s/it]

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overall:  88%|████████▊ | 3521/4000 [1:13:59<11:16,  1.41s/it]

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overall:  88%|████████▊ | 3522/4000 [1:14:01<10:45,  1.35s/it]

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overall:  88%|████████▊ | 3523/4000 [1:14:01<08:32,  1.07s/it]

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overall:  88%|████████▊ | 3524/4000 [1:14:02<08:53,  1.12s/it]

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overall:  88%|████████▊ | 3525/4000 [1:14:03<08:53,  1.12s/it]

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overall:  88%|████████▊ | 3526/4000 [1:14:05<09:15,  1.17s/it]

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overall:  88%|████████▊ | 3527/4000 [1:14:06<09:06,  1.15s/it]

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overall:  88%|████████▊ | 3528/4000 [1:14:07<09:21,  1.19s/it]

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overall:  88%|████████▊ | 3529/4000 [1:14:08<09:14,  1.18s/it]

train:   0%|          | 14/3515 [00:17<1:08:19,  1.17s/it]
overall:  88%|████████▊ | 3530/4000 [1:14:09<09:12,  1.18s/it]

train:   0%|          | 15/3515 [00:18<1:08:23,  1.17s/it]
overall:  88%|████████▊ | 3531/4000 [1:14:11<09:15,  1.18s/it]

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overall:  88%|████████▊ | 3532/4000 [1:14:12<09:19,  1.20s/it]

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overall:  88%|████████▊ | 3533/4000 [1:14:13<09:18,  1.20s/it]

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overall:  88%|████████▊ | 3534/4000 [1:14:14<09:30,  1.22s/it]

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overall:  88%|████████▊ | 3535/4000 [1:14:16<09:37,  1.24s/it]

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overall:  88%|████████▊ | 3536/4000 [1:14:17<09:42,  1.25s/it]

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overall:  88%|████████▊ | 3537/4000 [1:14:18<09:42,  1.26s/it]

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overall:  88%|████████▊ | 3538/4000 [1:14:19<09:38,  1.25s/it]

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overall:  88%|████████▊ | 3539/4000 [1:14:21<09:38,  1.26s/it]

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overall:  88%|████████▊ | 3540/4000 [1:14:22<09:45,  1.27s/it]

train:   1%|          | 25/3515 [00:31<1:13:58,  1.27s/it]
overall:  89%|████████▊ | 3541/4000 [1:14:23<09:29,  1.24s/it]

train:   1%|          | 26/3515 [00:32<1:12:05,  1.24s/it]
overall:  89%|████████▊ | 3542/4000 [1:14:24<09:07,  1.20s/it]

train:   1%|          | 27/3515 [00:33<1:09:28,  1.20s/it]
overall:  89%|████████▊ | 3543/4000 [1:14:25<09:07,  1.20s/it]

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overall:  89%|████████▊ | 3544/4000 [1:14:26<08:52,  1.17s/it]

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overall:  89%|████████▊ | 3545/4000 [1:14:28<09:07,  1.20s/it]

train:   1%|          | 30/3515 [00:37<1:09:51,  1.20s/it]
overall:  89%|████████▊ | 3546/4000 [1:14:29<09:01,  1.19s/it]

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overall:  89%|████████▊ | 3548/4000 [1:14:31<07:59,  1.06s/it]

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overall:  89%|████████▊ | 3549/4000 [1:14:32<08:24,  1.12s/it]

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overall:  89%|████████▉ | 3550/4000 [1:14:33<08:36,  1.15s/it]

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overall:  89%|████████▉ | 3551/4000 [1:14:34<08:34,  1.15s/it]

train:   1%|          | 36/3515 [00:43<1:06:30,  1.15s/it]
overall:  89%|████████▉ | 3552/4000 [1:14:36<08:49,  1.18s/it]

train:   1%|          | 37/3515 [00:45<1:08:32,  1.18s/it]
overall:  89%|████████▉ | 3553/4000 [1:14:37<08:44,  1.17s/it]

train:   1%|          | 38/3515 [00:46<1:08:02,  1.17s/it]
overall:  89%|████████▉ | 3554/4000 [1:14:38<09:00,  1.21s/it]

train:   1%|          | 39/3515 [00:47<1:10:10,  1.21s/it]
overall:  89%|████████▉ | 3555/4000 [1:14:39<09:00,  1.22s/it]

train:   1%|          | 40/3515 [00:48<1:10:22,  1.22s/it]
overall:  89%|████████▉ | 3556/4000 [1:14:40<09:00,  1.22s/it]

train:   1%|          | 41/3515 [00:49<1:10:30,  1.22s/it]
overall:  89%|████████▉ | 3557/4000 [1:14:42<08:58,  1.22s/it]

train:   1%|          | 42/3515 [00:51<1:10:20,  1.22s/it]
overall:  89%|████████▉ | 3558/4000 [1:14:43<08:35,  1.17s/it]

train:   1%|          | 43/3515 [00:52<1:07:27,  1.17s/it]
overall:  89%|████████▉ | 3559/4000 [1:14:44<08:32,  1.16s/it]

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overall:  89%|████████▉ | 3560/4000 [1:14:45<08:49,  1.20s/it]

train:   1%|▏         | 45/3515 [00:54<1:09:36,  1.20s/it]
overall:  89%|████████▉ | 3561/4000 [1:14:46<08:48,  1.20s/it]

train:   1%|▏         | 46/3515 [00:55<1:09:39,  1.20s/it]
overall:  89%|████████▉ | 3562/4000 [1:14:47<07:31,  1.03s/it]

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overall:  89%|████████▉ | 3563/4000 [1:14:48<07:08,  1.02it/s]

train:   1%|▏         | 48/3515 [00:57<56:42,  1.02it/s]
overall:  89%|████████▉ | 3564/4000 [1:14:49<07:50,  1.08s/it]

train:   1%|▏         | 49/3515 [00:58<1:02:18,  1.08s/it]
overall:  89%|████████▉ | 3565/4000 [1:14:50<08:07,  1.12s/it]

train:   1%|▏         | 50/3515 [00:59<1:04:43,  1.12s/it]
overall:  89%|████████▉ | 3566/4000 [1:14:52<08:08,  1.13s/it]

train:   1%|▏         | 51/3515 [01:01<1:04:58,  1.13s/it]
overall:  89%|████████▉ | 3567/4000 [1:14:53<08:25,  1.17s/it]

train:   1%|▏         | 52/3515 [01:02<1:07:26,  1.17s/it]
overall:  89%|████████▉ | 3568/4000 [1:14:54<08:18,  1.15s/it]

train:   2%|▏         | 53/3515 [01:03<1:06:31,  1.15s/it]
overall:  89%|████████▉ | 3569/4000 [1:14:55<08:26,  1.17s/it]

train:   2%|▏         | 54/3515 [01:04<1:07:44,  1.17s/it]
overall:  89%|████████▉ | 3570/4000 [1:14:56<08:22,  1.17s/it]

train:   2%|▏         | 55/3515 [01:05<1:07:24,  1.17s/it]
overall:  89%|████████▉ | 3571/4000 [1:14:58<08:33,  1.20s/it]

train:   2%|▏         | 56/3515 [01:07<1:08:57,  1.20s/it]
overall:  89%|████████▉ | 3572/4000 [1:14:59<08:43,  1.22s/it]

train:   2%|▏         | 57/3515 [01:08<1:10:32,  1.22s/it]
overall:  89%|████████▉ | 3573/4000 [1:15:00<08:48,  1.24s/it]

train:   2%|▏         | 58/3515 [01:09<1:11:15,  1.24s/it]
overall:  89%|████████▉ | 3574/4000 [1:15:01<08:54,  1.25s/it]

train:   2%|▏         | 59/3515 [01:10<1:12:14,  1.25s/it]
overall:  89%|████████▉ | 3575/4000 [1:15:03<08:56,  1.26s/it]

train:   2%|▏         | 60/3515 [01:12<1:12:39,  1.26s/it]
overall:  89%|████████▉ | 3576/4000 [1:15:04<08:57,  1.27s/it]

train:   2%|▏         | 61/3515 [01:13<1:13:00,  1.27s/it]
overall:  89%|████████▉ | 3577/4000 [1:15:05<08:49,  1.25s/it]

train:   2%|▏         | 62/3515 [01:14<1:12:00,  1.25s/it]
overall:  89%|████████▉ | 3578/4000 [1:15:06<08:42,  1.24s/it]

train:   2%|▏         | 63/3515 [01:15<1:11:17,  1.24s/it]
overall:  89%|████████▉ | 3579/4000 [1:15:08<08:37,  1.23s/it]

train:   2%|▏         | 64/3515 [01:17<1:10:42,  1.23s/it]
overall:  90%|████████▉ | 3580/4000 [1:15:09<08:30,  1.22s/it]

train:   2%|▏         | 65/3515 [01:18<1:09:54,  1.22s/it]
overall:  90%|████████▉ | 3581/4000 [1:15:10<08:17,  1.19s/it]

train:   2%|▏         | 66/3515 [01:19<1:08:17,  1.19s/it]
overall:  90%|████████▉ | 3582/4000 [1:15:11<08:25,  1.21s/it]

train:   2%|▏         | 67/3515 [01:20<1:09:28,  1.21s/it]
overall:  90%|████████▉ | 3583/4000 [1:15:12<08:31,  1.23s/it]

train:   2%|▏         | 68/3515 [01:21<1:10:30,  1.23s/it]
overall:  90%|████████▉ | 3584/4000 [1:15:14<08:24,  1.21s/it]

train:   2%|▏         | 69/3515 [01:23<1:09:38,  1.21s/it]
overall:  90%|████████▉ | 3585/4000 [1:15:14<07:38,  1.11s/it]

train:   2%|▏         | 70/3515 [01:23<1:03:29,  1.11s/it]
overall:  90%|████████▉ | 3586/4000 [1:15:16<07:37,  1.11s/it]

train:   2%|▏         | 71/3515 [01:25<1:03:27,  1.11s/it]
overall:  90%|████████▉ | 3587/4000 [1:15:17<07:58,  1.16s/it]

train:   2%|▏         | 72/3515 [01:26<1:06:27,  1.16s/it]
overall:  90%|████████▉ | 3588/4000 [1:15:18<08:15,  1.20s/it]

train:   2%|▏         | 73/3515 [01:27<1:08:58,  1.20s/it]
overall:  90%|████████▉ | 3589/4000 [1:15:19<08:16,  1.21s/it]

train:   2%|▏         | 74/3515 [01:28<1:09:16,  1.21s/it]
overall:  90%|████████▉ | 3590/4000 [1:15:21<08:25,  1.23s/it]

train:   2%|▏         | 75/3515 [01:30<1:10:41,  1.23s/it]
overall:  90%|████████▉ | 3591/4000 [1:15:22<08:27,  1.24s/it]

train:   2%|▏         | 76/3515 [01:31<1:11:06,  1.24s/it]
overall:  90%|████████▉ | 3592/4000 [1:15:23<08:16,  1.22s/it]

train:   2%|▏         | 77/3515 [01:32<1:09:45,  1.22s/it]
overall:  90%|████████▉ | 3593/4000 [1:15:24<08:26,  1.25s/it]

train:   2%|▏         | 78/3515 [01:33<1:11:20,  1.25s/it]
overall:  90%|████████▉ | 3594/4000 [1:15:26<08:15,  1.22s/it]

train:   2%|▏         | 79/3515 [01:35<1:09:51,  1.22s/it]
overall:  90%|████████▉ | 3595/4000 [1:15:27<08:01,  1.19s/it]

train:   2%|▏         | 80/3515 [01:36<1:08:07,  1.19s/it]
overall:  90%|████████▉ | 3596/4000 [1:15:28<07:57,  1.18s/it]

train:   2%|▏         | 81/3515 [01:37<1:07:40,  1.18s/it]
overall:  90%|████████▉ | 3597/4000 [1:15:29<08:06,  1.21s/it]

train:   2%|▏         | 82/3515 [01:38<1:09:03,  1.21s/it]
overall:  90%|████████▉ | 3598/4000 [1:15:30<08:15,  1.23s/it]

train:   2%|▏         | 83/3515 [01:39<1:10:26,  1.23s/it]
overall:  90%|████████▉ | 3599/4000 [1:15:32<08:18,  1.24s/it]

train:   2%|▏         | 84/3515 [01:41<1:11:01,  1.24s/it]
overall:  90%|█████████ | 3600/4000 [1:15:33<08:29,  1.27s/it]

train:   2%|▏         | 85/3515 [01:42<1:12:53,  1.27s/it]
overall:  90%|█████████ | 3601/4000 [1:15:34<08:22,  1.26s/it]

train:   2%|▏         | 86/3515 [01:43<1:11:54,  1.26s/it]
overall:  90%|█████████ | 3602/4000 [1:15:35<08:07,  1.23s/it]

train:   2%|▏         | 87/3515 [01:44<1:10:02,  1.23s/it]
overall:  90%|█████████ | 3603/4000 [1:15:37<08:06,  1.22s/it]

train:   3%|▎         | 88/3515 [01:46<1:09:56,  1.22s/it]
overall:  90%|█████████ | 3604/4000 [1:15:38<07:51,  1.19s/it]

train:   3%|▎         | 89/3515 [01:47<1:07:54,  1.19s/it]
overall:  90%|█████████ | 3605/4000 [1:15:39<07:48,  1.19s/it]

train:   3%|▎         | 90/3515 [01:48<1:07:45,  1.19s/it]
overall:  90%|█████████ | 3606/4000 [1:15:40<07:49,  1.19s/it]

train:   3%|▎         | 91/3515 [01:49<1:07:59,  1.19s/it]
overall:  90%|█████████ | 3607/4000 [1:15:41<07:49,  1.20s/it]

train:   3%|▎         | 92/3515 [01:50<1:08:10,  1.20s/it]
overall:  90%|█████████ | 3608/4000 [1:15:43<08:00,  1.23s/it]

train:   3%|▎         | 93/3515 [01:52<1:09:54,  1.23s/it]
overall:  90%|█████████ | 3609/4000 [1:15:43<06:20,  1.03it/s]

train:   3%|▎         | 94/3515 [01:52<55:25,  1.03it/s]  
overall:  90%|█████████ | 3610/4000 [1:15:44<06:18,  1.03it/s]

train:   3%|▎         | 95/3515 [01:53<55:22,  1.03it/s]
overall:  90%|█████████ | 3611/4000 [1:15:45<06:38,  1.02s/it]

train:   3%|▎         | 96/3515 [01:54<58:19,  1.02s/it]
overall:  90%|█████████ | 3612/4000 [1:15:46<06:52,  1.06s/it]

train:   3%|▎         | 97/3515 [01:55<1:00:37,  1.06s/it]
overall:  90%|█████████ | 3613/4000 [1:15:47<06:55,  1.07s/it]

train:   3%|▎         | 98/3515 [01:56<1:01:04,  1.07s/it]
overall:  90%|█████████ | 3614/4000 [1:15:49<07:05,  1.10s/it]

train:   3%|▎         | 99/3515 [01:58<1:02:45,  1.10s/it]
overall:  90%|█████████ | 3615/4000 [1:15:50<07:12,  1.12s/it]

train:   3%|▎         | 100/3515 [01:59<1:03:52,  1.12s/it]
overall:  90%|█████████ | 3616/4000 [1:15:51<07:22,  1.15s/it]

train:   3%|▎         | 101/3515 [02:00<1:05:29,  1.15s/it]
overall:  90%|█████████ | 3617/4000 [1:15:52<07:29,  1.17s/it]

train:   3%|▎         | 102/3515 [02:01<1:06:47,  1.17s/it]
overall:  90%|█████████ | 3618/4000 [1:15:53<07:44,  1.22s/it]

train:   3%|▎         | 103/3515 [02:02<1:09:05,  1.22s/it]
overall:  90%|█████████ | 3619/4000 [1:15:54<06:33,  1.03s/it]

train:   3%|▎         | 104/3515 [02:03<58:40,  1.03s/it]  
overall:  90%|█████████ | 3620/4000 [1:15:55<05:39,  1.12it/s]

train:   3%|▎         | 105/3515 [02:04<50:49,  1.12it/s]
overall:  91%|█████████ | 3621/4000 [1:15:55<04:26,  1.42it/s]

train:   3%|▎         | 106/3515 [02:04<39:58,  1.42it/s]
overall:  91%|█████████ | 3622/4000 [1:15:56<05:23,  1.17it/s]

train:   3%|▎         | 107/3515 [02:05<48:38,  1.17it/s]
overall:  91%|█████████ | 3623/4000 [1:15:57<06:11,  1.02it/s]

train:   3%|▎         | 108/3515 [02:06<55:55,  1.02it/s]
overall:  91%|█████████ | 3624/4000 [1:15:59<06:32,  1.04s/it]

train:   3%|▎         | 109/3515 [02:08<59:17,  1.04s/it]
overall:  91%|█████████ | 3625/4000 [1:15:59<05:23,  1.16it/s]

train:   3%|▎         | 110/3515 [02:08<48:54,  1.16it/s]
overall:  91%|█████████ | 3626/4000 [1:16:00<06:10,  1.01it/s]

train:   3%|▎         | 111/3515 [02:09<56:09,  1.01it/s]
overall:  91%|█████████ | 3627/4000 [1:16:01<06:27,  1.04s/it]

train:   3%|▎         | 112/3515 [02:10<58:52,  1.04s/it]
overall:  91%|█████████ | 3628/4000 [1:16:03<06:53,  1.11s/it]

train:   3%|▎         | 113/3515 [02:12<1:02:57,  1.11s/it]
overall:  91%|█████████ | 3629/4000 [1:16:04<07:04,  1.15s/it]

train:   3%|▎         | 114/3515 [02:13<1:04:54,  1.15s/it]
overall:  91%|█████████ | 3630/4000 [1:16:04<05:31,  1.12it/s]

train:   3%|▎         | 115/3515 [02:13<50:47,  1.12it/s]  
overall:  91%|█████████ | 3631/4000 [1:16:05<06:05,  1.01it/s]

train:   3%|▎         | 116/3515 [02:14<56:03,  1.01it/s]
overall:  91%|█████████ | 3632/4000 [1:16:07<06:30,  1.06s/it]

train:   3%|▎         | 117/3515 [02:16<1:00:09,  1.06s/it]
overall:  91%|█████████ | 3633/4000 [1:16:08<06:13,  1.02s/it]

train:   3%|▎         | 118/3515 [02:17<57:39,  1.02s/it]  
overall:  91%|█████████ | 3634/4000 [1:16:09<06:31,  1.07s/it]

train:   3%|▎         | 119/3515 [02:18<1:00:32,  1.07s/it]
overall:  91%|█████████ | 3635/4000 [1:16:10<06:17,  1.03s/it]

train:   3%|▎         | 120/3515 [02:19<58:30,  1.03s/it]  
overall:  91%|█████████ | 3636/4000 [1:16:11<06:40,  1.10s/it]

train:   3%|▎         | 121/3515 [02:20<1:02:14,  1.10s/it]
overall:  91%|█████████ | 3637/4000 [1:16:12<06:28,  1.07s/it]

train:   3%|▎         | 122/3515 [02:21<1:00:33,  1.07s/it]
overall:  91%|█████████ | 3638/4000 [1:16:13<06:40,  1.11s/it]

train:   3%|▎         | 123/3515 [02:22<1:02:31,  1.11s/it]
overall:  91%|█████████ | 3639/4000 [1:16:14<06:56,  1.15s/it]

train:   4%|▎         | 124/3515 [02:23<1:05:13,  1.15s/it]
overall:  91%|█████████ | 3640/4000 [1:16:16<06:46,  1.13s/it]

train:   4%|▎         | 125/3515 [02:25<1:03:46,  1.13s/it]
overall:  91%|█████████ | 3641/4000 [1:16:16<05:29,  1.09it/s]

train:   4%|▎         | 126/3515 [02:25<51:46,  1.09it/s]  
overall:  91%|█████████ | 3642/4000 [1:16:17<06:05,  1.02s/it]

train:   4%|▎         | 127/3515 [02:26<57:42,  1.02s/it]
overall:  91%|█████████ | 3643/4000 [1:16:18<06:05,  1.02s/it]

train:   4%|▎         | 128/3515 [02:27<57:44,  1.02s/it]
overall:  91%|█████████ | 3644/4000 [1:16:19<06:27,  1.09s/it]

train:   4%|▎         | 129/3515 [02:29<1:01:28,  1.09s/it]
overall:  91%|█████████ | 3645/4000 [1:16:20<06:14,  1.06s/it]

train:   4%|▎         | 130/3515 [02:30<59:35,  1.06s/it]  
overall:  91%|█████████ | 3646/4000 [1:16:22<06:38,  1.13s/it]

train:   4%|▎         | 131/3515 [02:31<1:03:29,  1.13s/it]
overall:  91%|█████████ | 3647/4000 [1:16:23<06:35,  1.12s/it]

train:   4%|▍         | 132/3515 [02:32<1:03:07,  1.12s/it]
overall:  91%|█████████ | 3648/4000 [1:16:24<06:59,  1.19s/it]

train:   4%|▍         | 133/3515 [02:33<1:07:10,  1.19s/it]
overall:  91%|█████████ | 3649/4000 [1:16:25<06:51,  1.17s/it]

train:   4%|▍         | 134/3515 [02:34<1:06:01,  1.17s/it]
overall:  91%|█████████▏| 3650/4000 [1:16:27<06:55,  1.19s/it]

train:   4%|▍         | 135/3515 [02:36<1:06:48,  1.19s/it]
overall:  91%|█████████▏| 3651/4000 [1:16:28<07:00,  1.21s/it]

train:   4%|▍         | 136/3515 [02:37<1:07:54,  1.21s/it]
overall:  91%|█████████▏| 3652/4000 [1:16:29<06:44,  1.16s/it]

train:   4%|▍         | 137/3515 [02:38<1:05:26,  1.16s/it]
overall:  91%|█████████▏| 3653/4000 [1:16:30<06:49,  1.18s/it]

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overall: 100%|█████████▉| 3981/4000 [1:22:43<00:22,  1.18s/it]

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overall: 100%|█████████▉| 3982/4000 [1:22:44<00:21,  1.18s/it]

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overall: 100%|█████████▉| 3983/4000 [1:22:45<00:18,  1.11s/it]

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overall: 100%|█████████▉| 3984/4000 [1:22:46<00:15,  1.05it/s]

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overall: 100%|█████████▉| 3985/4000 [1:22:47<00:16,  1.08s/it]

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overall: 100%|█████████▉| 3986/4000 [1:22:48<00:15,  1.13s/it]

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overall: 100%|█████████▉| 3997/4000 [1:23:01<00:03,  1.23s/it]

train:  14%|█▎        | 482/3515 [09:10<1:02:06,  1.23s/it]
overall: 100%|█████████▉| 3998/4000 [1:23:01<00:02,  1.05s/it]

train:  14%|█▎        | 483/3515 [09:10<53:10,  1.05s/it]  
overall: 100%|█████████▉| 3999/4000 [1:23:03<00:01,  1.10s/it]

train:  14%|█▍        | 484/3515 [09:12<55:44,  1.10s/it]train loss: 22.91815948486328
train per: 0.9523603499663494
train loss: 18.737751007080078
train per: 0.902038179991388
train loss: 18.526296615600586
train per: 0.9056373820143139
train loss: 19.916439056396484
train per: 0.8978677784395473
train loss: 19.86368179321289
train per: 0.9021539671443551
train loss: 20.717021942138672
train per: 0.9088245478517966
train loss: 22.152883529663086
train per: 0.9048794077847648
train loss: 20.393661499023438
train per: 0.951598589691315
train loss: 17.354904174804688
train per: 0.9352826510721247
train loss: 16.041046142578125
train per: 0.8952097235462345
train loss: 18.9625186920166
train per: 0.9056664668726082
train loss: 18.662235260009766
train per: 0.9116235603152152
train loss: 17.871021270751953
train per: 0.9104106390538551
train loss: 15.939764022827148
train per: 0.9107353330286484
train loss: 20.343509674072266
train per: 0.9462850663116896
train loss: 17.763212203979492
train per: 0.8949377355789876
train loss: 20.077892303466797
train per: 0.9137363966142684
train loss: 19.05588150024414
train per: 0.9071298074670914
train loss: 17.430734634399414
train per: 0.8968139325720204
train loss: 18.7515926361084
train per: 0.929100206059681
train loss: 17.392215728759766
train per: 0.8967302929477398
train loss: 18.044469833374023
train per: 0.9144038383013475
train loss: 15.235151290893555
train per: 0.9042287911060315
train loss: 13.502540588378906
train per: 0.9328393465449935
train loss: 12.153960227966309
train per: 0.9017372704507512
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  20%|██        | 547/2703 [00:00<00:00, 5467.18it/s]


word -> phonemes:  42%|████▏     | 1124/2703 [00:00<00:00, 5639.45it/s]


word -> phonemes:  63%|██████▎   | 1697/2703 [00:00<00:00, 5680.18it/s]


word -> phonemes:  84%|████████▍ | 2276/2703 [00:00<00:00, 5720.70it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 5623.17it/s]



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overall: 100%|█████████▉| 3999/4000 [1:25:53<00:01,  1.10s/it]

train:  14%|█▍        | 484/3515 [12:02<55:44,  1.10s/it]
                                                              

                                                         

overall: 100%|█████████▉| 3999/4000 [1:25:53<00:01,  1.10s/it]

train:  14%|█▍        | 484/3515 [12:02<55:44,  1.10s/it]
overall: 100%|██████████| 4000/4000 [1:25:53<00:00, 51.89s/it]

train:  14%|█▍        | 485/3515 [12:02<43:40:13, 51.89s/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 [12:02<1:15:16,  1.49s/it] 

overall: 100%|██████████| 4000/4000 [1:25:53<00:00,  1.29s/it]
dev loss: 12.773168563842773
dev per: 0.9191831425598335
[Runner] - Save the checkpoint to:
1. result/downstream/grid/states-4000.ckpt