/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")
2023-10-13 22:54:05 | 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')
[Featurizer] - Take a list of 13 features and weighted sum them.
[Featurizer] - The selected feature hidden_states's downsample rate is 960
[Runner] - Start a new experiment
mert_test_8x_400k {'model_config': None, 'refresh': False}
Loading model from Local mert_test_8x_400k
load local model succeed
load local feat extractor
Wav2Vec2FeatureExtractor {
  "do_normalize": false,
  "feature_extractor_type": "Wav2Vec2FeatureExtractor",
  "feature_size": 1,
  "padding_side": "right",
  "padding_value": 0,
  "return_attention_mask": true,
  "sampling_rate": 24000
}


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


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

word -> phonemes:  12%|█▏        | 414/3515 [00:00<00:00, 4137.24it/s]

word -> phonemes:  24%|██▎       | 828/3515 [00:00<00:00, 4022.70it/s]

word -> phonemes:  36%|███▋      | 1276/3515 [00:00<00:00, 4224.47it/s]

word -> phonemes:  48%|████▊     | 1701/3515 [00:00<00:00, 4233.71it/s]

word -> phonemes:  61%|██████    | 2141/3515 [00:00<00:00, 4291.93it/s]

word -> phonemes:  73%|███████▎  | 2571/3515 [00:00<00:00, 4248.78it/s]

word -> phonemes:  85%|████████▌ | 2997/3515 [00:00<00:00, 4247.60it/s]

word -> phonemes:  97%|█████████▋| 3422/3515 [00:00<00:00, 4245.47it/s]
word -> phonemes: 100%|██████████| 3515/3515 [00:00<00:00, 4214.68it/s]


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train:   3%|▎         | 121/3515 [00:24<12:56,  4.37it/s]
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overall:   3%|▎         | 130/4000 [00:29<13:15,  4.87it/s]

train:   4%|▎         | 130/3515 [00:26<11:35,  4.87it/s]
overall:   3%|▎         | 131/4000 [00:29<13:02,  4.94it/s]

train:   4%|▎         | 131/3515 [00:27<11:24,  4.94it/s]
overall:   3%|▎         | 132/4000 [00:29<12:17,  5.24it/s]

train:   4%|▍         | 132/3515 [00:27<10:45,  5.24it/s]
overall:   3%|▎         | 133/4000 [00:29<13:10,  4.89it/s]

train:   4%|▍         | 133/3515 [00:27<11:30,  4.89it/s]
overall:   3%|▎         | 134/4000 [00:29<13:05,  4.92it/s]

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overall:   3%|▎         | 135/4000 [00:30<12:42,  5.07it/s]

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train:   4%|▍         | 136/3515 [00:28<10:52,  5.18it/s]
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train:   4%|▍         | 140/3515 [00:28<10:39,  5.28it/s]
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train:   4%|▍         | 141/3515 [00:28<09:18,  6.04it/s]
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train:   4%|▍         | 147/3515 [00:30<11:52,  4.73it/s]
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train:   4%|▍         | 148/3515 [00:30<11:13,  5.00it/s]
overall:   4%|▎         | 149/4000 [00:32<13:01,  4.93it/s]

train:   4%|▍         | 149/3515 [00:30<11:23,  4.93it/s]
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train:   4%|▍         | 151/3515 [00:30<09:37,  5.83it/s]
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train:   4%|▍         | 152/3515 [00:31<09:49,  5.70it/s]
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train:   4%|▍         | 153/3515 [00:31<10:26,  5.37it/s]
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train:   4%|▍         | 154/3515 [00:31<11:13,  4.99it/s]
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train:   4%|▍         | 155/3515 [00:31<11:12,  5.00it/s]
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train:   4%|▍         | 157/3515 [00:32<10:12,  5.48it/s]
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train:   4%|▍         | 158/3515 [00:32<10:25,  5.37it/s]
overall:   4%|▍         | 159/4000 [00:34<12:17,  5.21it/s]

train:   5%|▍         | 159/3515 [00:32<10:44,  5.21it/s]
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train:   5%|▍         | 160/3515 [00:32<10:54,  5.13it/s]
overall:   4%|▍         | 161/4000 [00:34<12:34,  5.09it/s]

train:   5%|▍         | 161/3515 [00:32<10:59,  5.09it/s]
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train:   5%|▍         | 162/3515 [00:33<10:57,  5.10it/s]
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train:   5%|▍         | 163/3515 [00:33<11:02,  5.06it/s]
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train:   5%|▍         | 164/3515 [00:33<11:05,  5.04it/s]
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train:   5%|▍         | 165/3515 [00:33<11:01,  5.07it/s]
overall:   4%|▍         | 166/4000 [00:35<12:33,  5.09it/s]

train:   5%|▍         | 166/3515 [00:33<10:57,  5.09it/s]
overall:   4%|▍         | 167/4000 [00:36<12:41,  5.03it/s]

train:   5%|▍         | 167/3515 [00:34<11:05,  5.03it/s]
overall:   4%|▍         | 168/4000 [00:36<13:15,  4.82it/s]

train:   5%|▍         | 168/3515 [00:34<11:34,  4.82it/s]
overall:   4%|▍         | 169/4000 [00:36<14:37,  4.37it/s]

train:   5%|▍         | 169/3515 [00:34<12:46,  4.37it/s]
overall:   4%|▍         | 170/4000 [00:37<17:10,  3.72it/s]

train:   5%|▍         | 170/3515 [00:34<15:00,  3.72it/s]
overall:   4%|▍         | 171/4000 [00:37<15:31,  4.11it/s]

train:   5%|▍         | 171/3515 [00:35<13:33,  4.11it/s]
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train:   5%|▍         | 173/3515 [00:35<09:51,  5.65it/s]
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train:   5%|▍         | 174/3515 [00:35<10:07,  5.50it/s]
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train:   5%|▍         | 175/3515 [00:35<10:27,  5.32it/s]
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train:   5%|▌         | 176/3515 [00:35<10:40,  5.21it/s]
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train:   5%|▌         | 177/3515 [00:36<11:07,  5.00it/s]
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train:   5%|▌         | 178/3515 [00:36<11:55,  4.66it/s]
overall:   4%|▍         | 179/4000 [00:38<13:22,  4.76it/s]

train:   5%|▌         | 179/3515 [00:36<11:40,  4.76it/s]
overall:   4%|▍         | 180/4000 [00:38<13:02,  4.88it/s]

train:   5%|▌         | 180/3515 [00:36<11:23,  4.88it/s]
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train:   5%|▌         | 181/3515 [00:37<11:45,  4.72it/s]
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train:   5%|▌         | 182/3515 [00:37<11:27,  4.85it/s]
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train:   5%|▌         | 183/3515 [00:37<11:26,  4.86it/s]
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train:   5%|▌         | 184/3515 [00:37<10:11,  5.45it/s]
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train:   5%|▌         | 185/3515 [00:37<10:15,  5.41it/s]
overall:   5%|▍         | 186/4000 [00:40<12:06,  5.25it/s]

train:   5%|▌         | 186/3515 [00:37<10:33,  5.25it/s]
overall:   5%|▍         | 187/4000 [00:40<12:10,  5.22it/s]

train:   5%|▌         | 187/3515 [00:38<10:37,  5.22it/s]
overall:   5%|▍         | 188/4000 [00:40<12:07,  5.24it/s]

train:   5%|▌         | 188/3515 [00:38<10:35,  5.24it/s]
overall:   5%|▍         | 189/4000 [00:40<12:21,  5.14it/s]

train:   5%|▌         | 189/3515 [00:38<10:46,  5.14it/s]
overall:   5%|▍         | 190/4000 [00:40<12:32,  5.07it/s]

train:   5%|▌         | 190/3515 [00:38<10:56,  5.07it/s]
overall:   5%|▍         | 191/4000 [00:41<12:29,  5.08it/s]

train:   5%|▌         | 191/3515 [00:38<10:54,  5.08it/s]
overall:   5%|▍         | 192/4000 [00:41<12:52,  4.93it/s]

train:   5%|▌         | 192/3515 [00:39<11:13,  4.93it/s]
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train:   5%|▌         | 193/3515 [00:39<12:13,  4.53it/s]
overall:   5%|▍         | 194/4000 [00:41<16:48,  3.77it/s]

train:   6%|▌         | 194/3515 [00:39<14:39,  3.77it/s]
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train:   6%|▌         | 195/3515 [00:39<13:08,  4.21it/s]
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train:   6%|▌         | 197/3515 [00:40<10:22,  5.33it/s]
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train:   6%|▌         | 198/3515 [00:40<10:32,  5.24it/s]
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train:   6%|▌         | 206/3515 [00:41<10:00,  5.51it/s]
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train:   6%|▌         | 208/3515 [00:42<10:17,  5.35it/s]
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train:   6%|▋         | 224/3515 [00:45<11:05,  4.95it/s]
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train:   6%|▋         | 225/3515 [00:45<11:30,  4.77it/s]
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overall:   9%|▉         | 378/4000 [01:19<09:52,  6.11it/s]

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overall:   9%|▉         | 379/4000 [01:19<10:35,  5.70it/s]

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overall:  10%|▉         | 380/4000 [01:19<11:15,  5.36it/s]

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overall:  10%|▉         | 382/4000 [01:20<11:24,  5.28it/s]

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overall:  10%|▉         | 383/4000 [01:20<11:26,  5.27it/s]

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overall:  10%|▉         | 384/4000 [01:20<12:15,  4.92it/s]

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overall:  10%|▉         | 385/4000 [01:20<13:18,  4.53it/s]

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overall:  10%|▉         | 386/4000 [01:21<16:02,  3.75it/s]

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overall:  10%|▉         | 387/4000 [01:21<14:27,  4.17it/s]

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overall:  10%|▉         | 388/4000 [01:21<13:32,  4.44it/s]

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overall:  10%|▉         | 389/4000 [01:21<13:11,  4.56it/s]

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overall:  10%|▉         | 390/4000 [01:22<12:23,  4.85it/s]

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overall:  10%|▉         | 391/4000 [01:22<12:09,  4.95it/s]

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overall:  10%|▉         | 392/4000 [01:22<12:18,  4.89it/s]

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overall:  10%|▉         | 397/4000 [01:23<12:58,  4.63it/s]

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overall:  10%|█         | 406/4000 [01:25<11:57,  5.01it/s]

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overall:  10%|█         | 407/4000 [01:25<11:52,  5.04it/s]

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overall:  10%|█         | 408/4000 [01:25<12:06,  4.94it/s]

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overall:  10%|█         | 409/4000 [01:25<13:05,  4.57it/s]

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overall:  10%|█         | 410/4000 [01:26<16:03,  3.73it/s]

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overall:  10%|█         | 411/4000 [01:26<14:21,  4.16it/s]

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overall:  10%|█         | 412/4000 [01:26<13:52,  4.31it/s]

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overall:  10%|█         | 413/4000 [01:26<12:59,  4.60it/s]

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overall:  10%|█         | 414/4000 [01:27<12:41,  4.71it/s]

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overall:  10%|█         | 415/4000 [01:27<11:52,  5.03it/s]

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overall:  10%|█         | 417/4000 [01:27<10:38,  5.61it/s]

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overall:  10%|█         | 418/4000 [01:27<11:33,  5.17it/s]

train:  12%|█▏        | 418/3515 [01:25<09:59,  5.17it/s]
overall:  10%|█         | 419/4000 [01:27<11:37,  5.13it/s]

train:  12%|█▏        | 419/3515 [01:25<10:03,  5.13it/s]
overall:  10%|█         | 420/4000 [01:28<11:55,  5.00it/s]

train:  12%|█▏        | 420/3515 [01:26<10:18,  5.00it/s]
overall:  11%|█         | 421/4000 [01:28<12:26,  4.80it/s]

train:  12%|█▏        | 421/3515 [01:26<10:45,  4.80it/s]
overall:  11%|█         | 422/4000 [01:28<12:28,  4.78it/s]

train:  12%|█▏        | 422/3515 [01:26<10:46,  4.78it/s]
overall:  11%|█         | 423/4000 [01:28<12:18,  4.84it/s]

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overall:  11%|█         | 424/4000 [01:28<11:07,  5.35it/s]

train:  12%|█▏        | 424/3515 [01:26<09:37,  5.35it/s]
overall:  11%|█         | 425/4000 [01:29<11:28,  5.19it/s]

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overall:  11%|█         | 426/4000 [01:29<11:31,  5.17it/s]

train:  12%|█▏        | 426/3515 [01:27<09:57,  5.17it/s]
overall:  11%|█         | 428/4000 [01:29<10:09,  5.86it/s]

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overall:  11%|█         | 429/4000 [01:29<10:33,  5.64it/s]

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overall:  11%|█         | 430/4000 [01:30<10:56,  5.44it/s]

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overall:  11%|█         | 431/4000 [01:30<11:22,  5.23it/s]

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overall:  11%|█         | 432/4000 [01:30<12:01,  4.94it/s]

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overall:  11%|█         | 433/4000 [01:30<13:16,  4.48it/s]

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overall:  11%|█         | 434/4000 [01:31<16:41,  3.56it/s]

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overall:  11%|█         | 435/4000 [01:31<15:18,  3.88it/s]

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overall:  11%|█         | 436/4000 [01:31<14:06,  4.21it/s]

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overall:  11%|█         | 437/4000 [01:31<13:28,  4.40it/s]

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overall:  11%|█         | 438/4000 [01:31<12:56,  4.59it/s]

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overall:  11%|█         | 439/4000 [01:32<12:40,  4.68it/s]

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overall:  11%|█         | 440/4000 [01:32<11:30,  5.15it/s]

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overall:  11%|█         | 441/4000 [01:32<12:00,  4.94it/s]

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overall:  11%|█         | 442/4000 [01:32<12:24,  4.78it/s]

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overall:  11%|█         | 443/4000 [01:32<11:57,  4.96it/s]

train:  13%|█▎        | 443/3515 [01:30<10:19,  4.96it/s]
overall:  11%|█         | 444/4000 [01:33<12:06,  4.89it/s]

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overall:  11%|█         | 445/4000 [01:33<12:38,  4.69it/s]

train:  13%|█▎        | 445/3515 [01:31<10:55,  4.69it/s]
overall:  11%|█         | 446/4000 [01:33<12:35,  4.71it/s]

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overall:  11%|█         | 447/4000 [01:33<12:23,  4.78it/s]

train:  13%|█▎        | 447/3515 [01:31<10:41,  4.78it/s]
overall:  11%|█         | 448/4000 [01:34<12:22,  4.79it/s]

train:  13%|█▎        | 448/3515 [01:31<10:40,  4.79it/s]
overall:  11%|█         | 449/4000 [01:34<12:31,  4.73it/s]

train:  13%|█▎        | 449/3515 [01:32<10:48,  4.73it/s]
overall:  11%|█▏        | 450/4000 [01:34<12:01,  4.92it/s]

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overall:  11%|█▏        | 451/4000 [01:34<11:49,  5.01it/s]

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overall:  11%|█▏        | 452/4000 [01:34<11:47,  5.01it/s]

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overall:  11%|█▏        | 453/4000 [01:35<11:43,  5.04it/s]

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overall:  11%|█▏        | 454/4000 [01:35<11:46,  5.02it/s]

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overall:  11%|█▏        | 455/4000 [01:35<11:50,  4.99it/s]

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overall:  11%|█▏        | 456/4000 [01:35<12:17,  4.81it/s]

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overall:  11%|█▏        | 457/4000 [01:35<13:00,  4.54it/s]

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overall:  11%|█▏        | 458/4000 [01:36<16:16,  3.63it/s]

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overall:  11%|█▏        | 459/4000 [01:36<14:40,  4.02it/s]

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overall:  12%|█▏        | 460/4000 [01:36<13:59,  4.22it/s]

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overall:  12%|█▏        | 461/4000 [01:36<13:21,  4.42it/s]

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overall:  12%|█▏        | 462/4000 [01:37<12:41,  4.65it/s]

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overall:  12%|█▏        | 463/4000 [01:37<12:13,  4.82it/s]

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overall:  12%|█▏        | 465/4000 [01:37<10:52,  5.42it/s]

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overall:  12%|█▏        | 467/4000 [01:37<10:11,  5.78it/s]

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overall:  12%|█▏        | 469/4000 [01:38<11:38,  5.06it/s]

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overall:  12%|█▏        | 470/4000 [01:38<11:43,  5.01it/s]

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overall:  12%|█▏        | 471/4000 [01:38<11:27,  5.13it/s]

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overall:  12%|█▏        | 472/4000 [01:38<11:43,  5.01it/s]

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overall:  12%|█▏        | 473/4000 [01:39<11:48,  4.98it/s]

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overall:  12%|█▏        | 474/4000 [01:39<11:56,  4.92it/s]

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overall:  12%|█▏        | 475/4000 [01:39<12:02,  4.88it/s]

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overall:  12%|█▏        | 476/4000 [01:39<11:50,  4.96it/s]

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overall:  12%|█▏        | 477/4000 [01:39<11:59,  4.90it/s]

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overall:  12%|█▏        | 478/4000 [01:40<11:51,  4.95it/s]

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overall:  12%|█▏        | 479/4000 [01:40<11:38,  5.04it/s]

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overall:  13%|█▎        | 533/4000 [01:51<13:02,  4.43it/s]

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overall:  13%|█▎        | 535/4000 [01:52<11:32,  5.01it/s]

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overall:  13%|█▎        | 536/4000 [01:52<10:53,  5.30it/s]

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overall:  13%|█▎        | 537/4000 [01:52<11:25,  5.05it/s]

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overall:  13%|█▎        | 539/4000 [01:52<10:57,  5.26it/s]

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overall:  14%|█▎        | 541/4000 [01:53<11:53,  4.85it/s]

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overall:  14%|█▎        | 542/4000 [01:53<11:56,  4.83it/s]

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overall:  14%|█▎        | 543/4000 [01:53<11:53,  4.85it/s]

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overall:  14%|█▎        | 544/4000 [01:54<11:53,  4.85it/s]

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overall:  14%|█▎        | 545/4000 [01:54<11:49,  4.87it/s]

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overall:  14%|█▎        | 546/4000 [01:54<11:52,  4.85it/s]

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overall:  14%|█▎        | 547/4000 [01:54<11:33,  4.98it/s]

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overall:  14%|█▎        | 548/4000 [01:54<11:21,  5.06it/s]

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overall:  14%|█▎        | 549/4000 [01:55<11:25,  5.04it/s]

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overall:  14%|█▍        | 550/4000 [01:55<11:14,  5.11it/s]

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overall:  14%|█▍        | 551/4000 [01:55<11:34,  4.97it/s]

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overall:  14%|█▍        | 553/4000 [01:55<13:05,  4.39it/s]

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overall:  14%|█▍        | 554/4000 [01:56<15:37,  3.68it/s]

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overall:  14%|█▍        | 566/4000 [01:58<12:13,  4.68it/s]

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overall:  14%|█▍        | 568/4000 [01:59<11:08,  5.14it/s]

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overall:  14%|█▍        | 569/4000 [01:59<11:18,  5.06it/s]

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overall:  14%|█▍        | 571/4000 [01:59<08:48,  6.49it/s]

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overall:  25%|██▍       | 991/4000 [03:26<10:32,  4.76it/s]

train:  28%|██▊       | 991/3515 [03:24<08:50,  4.76it/s]
overall:  25%|██▍       | 992/4000 [03:26<10:23,  4.83it/s]

train:  28%|██▊       | 992/3515 [03:24<08:42,  4.83it/s]
overall:  25%|██▍       | 993/4000 [03:26<10:36,  4.72it/s]

train:  28%|██▊       | 993/3515 [03:24<08:54,  4.72it/s]
overall:  25%|██▍       | 994/4000 [03:26<11:02,  4.53it/s]

train:  28%|██▊       | 994/3515 [03:24<09:15,  4.53it/s]
overall:  25%|██▍       | 995/4000 [03:27<10:54,  4.59it/s]

train:  28%|██▊       | 995/3515 [03:25<09:08,  4.59it/s]
overall:  25%|██▍       | 996/4000 [03:27<10:06,  4.95it/s]

train:  28%|██▊       | 996/3515 [03:25<08:28,  4.95it/s]
overall:  25%|██▍       | 997/4000 [03:27<10:35,  4.72it/s]

train:  28%|██▊       | 997/3515 [03:25<08:52,  4.72it/s]
overall:  25%|██▍       | 998/4000 [03:27<10:31,  4.75it/s]

train:  28%|██▊       | 998/3515 [03:25<08:49,  4.75it/s]
overall:  25%|██▍       | 999/4000 [03:27<10:18,  4.85it/s]

train:  28%|██▊       | 999/3515 [03:25<08:38,  4.85it/s]train loss: 4.425655364990234
train per: 0.9299241916905521
train loss: 2.8756186962127686
train per: 0.7082939055267129
train loss: 2.3585712909698486
train per: 0.6190327856085974
train loss: 2.236919403076172
train per: 0.579337390817184
train loss: 2.1981520652770996
train per: 0.5756837071086967
train loss: 2.135572910308838
train per: 0.5672761495025544
train loss: 2.077003240585327
train per: 0.5515172211923114
train loss: 2.1514060497283936
train per: 0.563489954289359
train loss: 2.0373666286468506
train per: 0.5433312247579193
train loss: 2.0186684131622314
train per: 0.5357632228007674
train loss: 2.0406124591827393
train per: 0.5522498091150838
train loss: 2.0400569438934326
train per: 0.5419680903775642
train loss: 2.1058058738708496
train per: 0.5555686366847187
train loss: 2.0460681915283203
train per: 0.5384425880719357
train loss: 1.9640347957611084
train per: 0.5238397965670692
train loss: 1.982377052307129
train per: 0.5279199627733829
train loss: 1.9557784795761108
train per: 0.5233833129334965
train loss: 1.9874550104141235
train per: 0.5339634777258871
train loss: 2.024564027786255
train per: 0.532736537666988
train loss: 1.9599716663360596
train per: 0.5262071396203615
train loss: 1.9413807392120361
train per: 0.5205553774445733
train loss: 1.9859607219696045
train per: 0.5284411964137723
train loss: 1.9944324493408203
train per: 0.5214985287013044
train loss: 1.9836667776107788
train per: 0.5240782995076257
train loss: 1.959641695022583
train per: 0.5185920014267243
train loss: 1.909440279006958
train per: 0.5122530664945126
train loss: 1.957513451576233
train per: 0.519790023659306
train loss: 1.9154231548309326
train per: 0.5122229057025038
train loss: 1.925869345664978
train per: 0.5110843877444317
train loss: 1.9444820880889893
train per: 0.5216491903844782
train loss: 1.9679447412490845
train per: 0.5209068857026202
train loss: 1.906036376953125
train per: 0.5069563513447313
train loss: 1.9460262060165405
train per: 0.518544468301503
train loss: 1.9464409351348877
train per: 0.5208409126344784
train loss: 1.9253638982772827
train per: 0.5163004961020553
train loss: 1.9351470470428467
train per: 0.5248743131065123
train loss: 1.985337495803833
train per: 0.5174969509334835
train loss: 1.9698365926742554
train per: 0.5202458423716558
train loss: 1.9571908712387085
train per: 0.51978178601268
train loss: 1.9529863595962524
train per: 0.5190254841045525
train loss: 1.919341802597046
train per: 0.5145618215514959
train loss: 1.9133516550064087
train per: 0.5148833906821781
train loss: 1.9310169219970703
train per: 0.5118922386144965
train loss: 1.9682252407073975
train per: 0.5213359945428362
train loss: 1.9119278192520142
train per: 0.5094487195660401
train loss: 1.9143426418304443
train per: 0.5100137174211248
train loss: 1.942051887512207
train per: 0.5212771458117891
train loss: 1.9482171535491943
train per: 0.5218271644933992
train loss: 1.9154869318008423
train per: 0.5097504717970225
train loss: 1.8924624919891357
train per: 0.5046569656842157
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  19%|█▉        | 520/2703 [00:00<00:00, 5195.88it/s]


word -> phonemes:  40%|████      | 1083/2703 [00:00<00:00, 5449.77it/s]


word -> phonemes:  60%|██████    | 1628/2703 [00:00<00:00, 4847.78it/s]


word -> phonemes:  80%|███████▉  | 2153/2703 [00:00<00:00, 4991.18it/s]


word -> phonemes:  99%|█████████▊| 2663/2703 [00:00<00:00, 5026.77it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 5044.60it/s]



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train:  56%|█████▌    | 1952/3515 [08:33<05:24,  4.82it/s]
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train:  56%|█████▌    | 1953/3515 [08:33<05:33,  4.68it/s]
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train:  56%|█████▌    | 1954/3515 [08:34<05:58,  4.36it/s]
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train:  56%|█████▌    | 1955/3515 [08:34<05:42,  4.56it/s]
overall:  49%|████▉     | 1956/4000 [08:36<07:14,  4.70it/s]

train:  56%|█████▌    | 1956/3515 [08:34<05:31,  4.70it/s]
overall:  49%|████▉     | 1957/4000 [08:36<07:37,  4.47it/s]

train:  56%|█████▌    | 1957/3515 [08:34<05:48,  4.47it/s]
overall:  49%|████▉     | 1958/4000 [08:37<07:30,  4.54it/s]

train:  56%|█████▌    | 1958/3515 [08:35<05:43,  4.54it/s]
overall:  49%|████▉     | 1959/4000 [08:37<07:21,  4.63it/s]

train:  56%|█████▌    | 1959/3515 [08:35<05:36,  4.63it/s]
overall:  49%|████▉     | 1960/4000 [08:37<07:18,  4.65it/s]

train:  56%|█████▌    | 1960/3515 [08:35<05:34,  4.65it/s]
overall:  49%|████▉     | 1961/4000 [08:37<07:16,  4.67it/s]

train:  56%|█████▌    | 1961/3515 [08:35<05:32,  4.67it/s]
overall:  49%|████▉     | 1962/4000 [08:38<07:19,  4.64it/s]

train:  56%|█████▌    | 1962/3515 [08:35<05:34,  4.64it/s]
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train:  56%|█████▌    | 1963/3515 [08:36<05:37,  4.60it/s]
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train:  56%|█████▌    | 1964/3515 [08:36<05:28,  4.73it/s]
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train:  56%|█████▌    | 1967/3515 [08:36<05:12,  4.95it/s]
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train:  56%|█████▌    | 1968/3515 [08:37<05:07,  5.04it/s]
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train:  56%|█████▌    | 1969/3515 [08:37<05:50,  4.41it/s]
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train:  56%|█████▌    | 1970/3515 [08:37<07:27,  3.45it/s]
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train:  56%|█████▌    | 1971/3515 [08:38<06:52,  3.75it/s]
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train:  56%|█████▌    | 1975/3515 [08:38<05:50,  4.40it/s]
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train:  56%|█████▌    | 1976/3515 [08:39<05:38,  4.54it/s]
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train:  56%|█████▌    | 1977/3515 [08:39<05:45,  4.45it/s]
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train:  56%|█████▋    | 1978/3515 [08:39<05:43,  4.47it/s]
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train:  56%|█████▋    | 1979/3515 [08:39<05:15,  4.88it/s]
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train:  56%|█████▋    | 1980/3515 [08:39<05:23,  4.74it/s]
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train:  56%|█████▋    | 1982/3515 [08:40<05:05,  5.02it/s]
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train:  56%|█████▋    | 1984/3515 [08:40<04:31,  5.64it/s]
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train:  56%|█████▋    | 1985/3515 [08:40<04:44,  5.37it/s]
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train:  57%|█████▋    | 1986/3515 [08:40<04:11,  6.07it/s]
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train:  57%|█████▋    | 1987/3515 [08:41<04:28,  5.69it/s]
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train:  57%|█████▋    | 1988/3515 [08:41<04:54,  5.19it/s]
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train:  57%|█████▋    | 1989/3515 [08:41<05:04,  5.02it/s]
overall:  50%|████▉     | 1990/4000 [08:43<06:52,  4.87it/s]

train:  57%|█████▋    | 1990/3515 [08:41<05:13,  4.87it/s]
overall:  50%|████▉     | 1991/4000 [08:44<06:59,  4.79it/s]

train:  57%|█████▋    | 1991/3515 [08:42<05:17,  4.79it/s]
overall:  50%|████▉     | 1992/4000 [08:44<06:12,  5.40it/s]

train:  57%|█████▋    | 1992/3515 [08:42<04:42,  5.40it/s]
overall:  50%|████▉     | 1993/4000 [08:44<07:11,  4.65it/s]

train:  57%|█████▋    | 1993/3515 [08:42<05:27,  4.65it/s]
overall:  50%|████▉     | 1994/4000 [08:44<08:58,  3.72it/s]

train:  57%|█████▋    | 1994/3515 [08:42<06:48,  3.72it/s]
overall:  50%|████▉     | 1995/4000 [08:45<08:24,  3.97it/s]

train:  57%|█████▋    | 1995/3515 [08:43<06:22,  3.97it/s]
overall:  50%|████▉     | 1996/4000 [08:45<07:55,  4.22it/s]

train:  57%|█████▋    | 1996/3515 [08:43<06:00,  4.22it/s]
overall:  50%|████▉     | 1997/4000 [08:45<07:45,  4.30it/s]

train:  57%|█████▋    | 1997/3515 [08:43<05:53,  4.30it/s]
overall:  50%|████▉     | 1998/4000 [08:45<07:28,  4.46it/s]

train:  57%|█████▋    | 1998/3515 [08:43<05:40,  4.46it/s]
overall:  50%|████▉     | 1999/4000 [08:45<07:12,  4.62it/s]

train:  57%|█████▋    | 1999/3515 [08:43<05:27,  4.62it/s]dev loss: 2.2096991539001465
dev per: 0.5533922996878252
[Runner] - Save the checkpoint to:
1. result/downstream/grid/dev-best.ckpt
train loss: 1.9176609516143799
train per: 0.5137545153712078
train loss: 1.9054698944091797
train per: 0.516970458830924
train loss: 1.9702638387680054
train per: 0.5201532008024804
train loss: 1.9127652645111084
train per: 0.5123473995205976
train loss: 1.9583460092544556
train per: 0.5119953863898501
train loss: 1.9393160343170166
train per: 0.5120385984635563
train loss: 1.9111133813858032
train per: 0.5136045607670381
train loss: 1.9165496826171875
train per: 0.5067564173406339
train loss: 1.918036699295044
train per: 0.5095324341070492
train loss: 1.9145212173461914
train per: 0.5092066141567994
train loss: 1.9550209045410156
train per: 0.5156952741195193
train loss: 1.8902660608291626
train per: 0.5050722187333945
train loss: 1.9207061529159546
train per: 0.5091875474563402
train loss: 1.87123703956604
train per: 0.5067410119840213
train loss: 1.904261589050293
train per: 0.508407802440665
train loss: 1.9526174068450928
train per: 0.5158768811182
train loss: 1.927086591720581
train per: 0.513980207029917
train loss: 1.8675968647003174
train per: 0.5043711420830657
train loss: 1.920710802078247
train per: 0.5131084199880714
train loss: 1.9138545989990234
train per: 0.5084515161997002
train loss: 1.8757445812225342
train per: 0.5064645126468929
train loss: 1.894788146018982
train per: 0.5085358407619978
train loss: 1.8694102764129639
train per: 0.5058402860548272
train loss: 1.9345474243164062
train per: 0.5085740072202166
train loss: 1.9553676843643188
train per: 0.5223634022497023
train loss: 1.9159942865371704
train per: 0.510360670801746
train loss: 1.892896294593811
train per: 0.5053499054309646
train loss: 1.96195387840271
train per: 0.520194013959541
train loss: 1.9299771785736084
train per: 0.5095041032475275
train loss: 1.9331690073013306
train per: 0.5143426981508384
train loss: 1.8992191553115845
train per: 0.5085802231627549
train loss: 1.931695580482483
train per: 0.5148464288319836
train loss: 1.9218342304229736
train per: 0.5094787822878228
train loss: 1.9281200170516968
train per: 0.5158965446738908
train loss: 1.872675895690918
train per: 0.5033429074847336
train loss: 1.867885947227478
train per: 0.513227353624325
train loss: 1.9436829090118408
train per: 0.5232002548311744
train loss: 1.894913673400879
train per: 0.5095912847110207
train loss: 1.8783166408538818
train per: 0.503158181323169
train loss: 1.972022294998169
train per: 0.5162460713625439
train loss: 1.937055230140686
train per: 0.5097783572359843
train loss: 1.9152348041534424
train per: 0.5091549657974592
train loss: 1.8973884582519531
train per: 0.5073690499900418
train loss: 1.856269121170044
train per: 0.5036023780733575
train loss: 1.9047447443008423
train per: 0.5063490958051861
train loss: 1.9146772623062134
train per: 0.5131061072585611
train loss: 1.8947715759277344
train per: 0.5079247152055473
train loss: 1.9503076076507568
train per: 0.5144161683585964
train loss: 1.8570270538330078
train per: 0.4979266955817168
train loss: 1.901431679725647
train per: 0.5037879704707733
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  21%|██        | 561/2703 [00:00<00:00, 5603.42it/s]


word -> phonemes:  42%|████▏     | 1122/2703 [00:00<00:00, 5132.36it/s]


word -> phonemes:  63%|██████▎   | 1704/2703 [00:00<00:00, 5430.32it/s]


word -> phonemes:  83%|████████▎ | 2250/2703 [00:00<00:00, 5309.29it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 5247.64it/s]



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dev:   3%|▎         | 68/2703 [00:05<02:31, 17.42it/s]


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train:  85%|████████▍ | 2978/3515 [14:04<02:15,  3.97it/s]
overall:  74%|███████▍  | 2979/4000 [14:06<04:03,  4.20it/s]

train:  85%|████████▍ | 2979/3515 [14:04<02:07,  4.20it/s]
overall:  74%|███████▍  | 2980/4000 [14:07<03:51,  4.41it/s]

train:  85%|████████▍ | 2980/3515 [14:04<02:01,  4.41it/s]
overall:  75%|███████▍  | 2982/4000 [14:07<02:44,  6.18it/s]

train:  85%|████████▍ | 2982/3515 [14:05<01:26,  6.18it/s]
overall:  75%|███████▍  | 2983/4000 [14:07<03:15,  5.20it/s]

train:  85%|████████▍ | 2983/3515 [14:05<01:42,  5.20it/s]
overall:  75%|███████▍  | 2984/4000 [14:07<03:15,  5.19it/s]

train:  85%|████████▍ | 2984/3515 [14:05<01:42,  5.19it/s]
overall:  75%|███████▍  | 2985/4000 [14:07<03:19,  5.10it/s]

train:  85%|████████▍ | 2985/3515 [14:05<01:43,  5.10it/s]
overall:  75%|███████▍  | 2986/4000 [14:08<03:19,  5.07it/s]

train:  85%|████████▍ | 2986/3515 [14:06<01:44,  5.07it/s]
overall:  75%|███████▍  | 2987/4000 [14:08<03:19,  5.07it/s]

train:  85%|████████▍ | 2987/3515 [14:06<01:44,  5.07it/s]
overall:  75%|███████▍  | 2988/4000 [14:08<03:25,  4.91it/s]

train:  85%|████████▌ | 2988/3515 [14:06<01:47,  4.91it/s]
overall:  75%|███████▍  | 2989/4000 [14:08<03:29,  4.81it/s]

train:  85%|████████▌ | 2989/3515 [14:06<01:49,  4.81it/s]
overall:  75%|███████▍  | 2990/4000 [14:08<03:29,  4.81it/s]

train:  85%|████████▌ | 2990/3515 [14:06<01:49,  4.81it/s]
overall:  75%|███████▍  | 2991/4000 [14:09<03:19,  5.07it/s]

train:  85%|████████▌ | 2991/3515 [14:07<01:43,  5.07it/s]
overall:  75%|███████▍  | 2992/4000 [14:09<03:24,  4.92it/s]

train:  85%|████████▌ | 2992/3515 [14:07<01:46,  4.92it/s]
overall:  75%|███████▍  | 2993/4000 [14:09<03:26,  4.88it/s]

train:  85%|████████▌ | 2993/3515 [14:07<01:46,  4.88it/s]
overall:  75%|███████▍  | 2994/4000 [14:09<03:23,  4.94it/s]

train:  85%|████████▌ | 2994/3515 [14:07<01:45,  4.94it/s]
overall:  75%|███████▍  | 2995/4000 [14:09<03:27,  4.83it/s]

train:  85%|████████▌ | 2995/3515 [14:07<01:47,  4.83it/s]
overall:  75%|███████▍  | 2996/4000 [14:10<03:31,  4.74it/s]

train:  85%|████████▌ | 2996/3515 [14:08<01:49,  4.74it/s]
overall:  75%|███████▍  | 2997/4000 [14:10<03:33,  4.69it/s]

train:  85%|████████▌ | 2997/3515 [14:08<01:50,  4.69it/s]
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train:  85%|████████▌ | 2998/3515 [14:08<01:48,  4.77it/s]
overall:  75%|███████▍  | 2999/4000 [14:10<03:33,  4.70it/s]

train:  85%|████████▌ | 2999/3515 [14:08<01:49,  4.70it/s]dev loss: 2.2157857418060303
dev per: 0.5546462018730489
train loss: 1.8584911823272705
train per: 0.5006865727901779
train loss: 1.8613195419311523
train per: 0.5146216543672211
train loss: 1.8969618082046509
train per: 0.504524886877828
train loss: 1.9166371822357178
train per: 0.5072432993582484
train loss: 1.8811613321304321
train per: 0.5021452803831571
train loss: 1.8651115894317627
train per: 0.498038135884904
train loss: 1.9075853824615479
train per: 0.5063674101174981
train loss: 1.9327144622802734
train per: 0.5116129032258064
train loss: 1.845632553100586
train per: 0.49693326193837317
train loss: 1.8689273595809937
train per: 0.5001071352046282
train loss: 1.8831621408462524
train per: 0.5039083084489724
train loss: 1.881890058517456
train per: 0.5037986946767286
train loss: 1.9636118412017822
train per: 0.5169749786142002
train loss: 1.9208314418792725
train per: 0.5094019167778722
train loss: 1.8589084148406982
train per: 0.5072056737588653
train loss: 1.9223295450210571
train per: 0.5051066347662782
train loss: 1.9153764247894287
train per: 0.5061168068194909
train loss: 1.9025018215179443
train per: 0.5077737431596174
train loss: 1.882131814956665
train per: 0.5051968129385183
train loss: 1.8973900079727173
train per: 0.5061241329517031
train loss: 1.8830182552337646
train per: 0.5058105442720827
train loss: 1.9437856674194336
train per: 0.5156316310652144
train loss: 1.9514516592025757
train per: 0.5115111493057126
train loss: 1.8871421813964844
train per: 0.5084860353429385
train loss: 1.8790302276611328
train per: 0.5058158233276158
train loss: 1.866161584854126
train per: 0.49983320625238276
train loss: 1.8437011241912842
train per: 0.4967298656529644
train loss: 1.8645732402801514
train per: 0.5013190081059044
train loss: 1.8542121648788452
train per: 0.49781929920206175
train loss: 1.9258668422698975
train per: 0.508473034142347
train loss: 1.8412153720855713
train per: 0.49813557435440786
train loss: 1.8624706268310547
train per: 0.5037566806950505
train loss: 1.8787158727645874
train per: 0.5076672104404568
train loss: 1.882879614830017
train per: 0.5079575929221284
train loss: 1.9108963012695312
train per: 0.5059916274201989
train loss: 1.8760643005371094
train per: 0.5053769370760491
train loss: 1.9257819652557373
train per: 0.5169522870176304
train loss: 1.8573671579360962
train per: 0.5017770827409724
train loss: 1.8855575323104858
train per: 0.5098907509546033
train loss: 1.8606412410736084
train per: 0.5045394292574344
train loss: 1.8389546871185303
train per: 0.49850842738527323
train loss: 1.8866386413574219
train per: 0.5132483341203631
train loss: 1.8784112930297852
train per: 0.5117899965284268
train loss: 1.944417953491211
train per: 0.5113607876205019
train loss: 1.8688619136810303
train per: 0.5047621512500647
train loss: 1.902562141418457
train per: 0.5064116985376828
train loss: 1.897157073020935
train per: 0.5122914205020318
train loss: 1.9214966297149658
train per: 0.5114426058808882
train loss: 1.8751436471939087
train per: 0.5056423720683648
train loss: 1.9323841333389282
train per: 0.5217477068744452
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  19%|█▊        | 501/2703 [00:00<00:00, 5008.06it/s]


word -> phonemes:  37%|███▋      | 1013/2703 [00:00<00:00, 5072.38it/s]


word -> phonemes:  56%|█████▋    | 1521/2703 [00:00<00:00, 5005.42it/s]


word -> phonemes:  75%|███████▍  | 2022/2703 [00:00<00:00, 4898.47it/s]


word -> phonemes:  93%|█████████▎| 2513/2703 [00:00<00:00, 4693.25it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 4788.39it/s]



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train: 100%|██████████| 3515/3515 [17:51<00:00,  5.07it/s]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 [17:51<00:00,  3.28it/s]
dev loss: 2.221815586090088
dev per: 0.5573517169614984
train loss: 1.8315242528915405
train per: 0.4944548754537489
train loss: 1.8686081171035767
train per: 0.5064134053818024
train loss: 1.8483247756958008
train per: 0.4968603971962617
train loss: 1.8508867025375366
train per: 0.49707646554765866
train loss: 1.8775135278701782
train per: 0.4999171538807489
train loss: 1.872511863708496
train per: 0.5041383162384483
train loss: 1.8396227359771729
train per: 0.5008562937591297
train loss: 1.8992109298706055
train per: 0.5021253091904613
train loss: 1.9124767780303955
train per: 0.5094240968055175
train loss: 1.8562999963760376
train per: 0.49843088773714994
train loss: 1.90390145778656
train per: 0.5090264611326354
train loss: 1.928598403930664
train per: 0.5140986078066476
train loss: 1.835985541343689
train per: 0.49983645741602717
train loss: 1.8680212497711182
train per: 0.5008289163378242
train loss: 1.8915798664093018
train per: 0.5128544794426455
train loss: 1.9050376415252686
train per: 0.5076018326457112
train loss: 1.8973944187164307
train per: 0.5030431997071206
train loss: 1.8840917348861694
train per: 0.510210493245366
train loss: 1.9088484048843384
train per: 0.5130482918599747
train loss: 1.8989570140838623
train per: 0.5075802858229637
train loss: 1.9183028936386108
train per: 0.5154624993121664
train loss: 1.9286909103393555
train per: 0.5098939287844602
train loss: 1.9448124170303345
train per: 0.5126429645901482
train loss: 1.892456293106079
train per: 0.5117032858273951
train loss: 1.919753074645996
train per: 0.505184345402584
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.


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

word -> phonemes:  13%|█▎        | 442/3515 [00:00<00:00, 4411.36it/s]

word -> phonemes:  26%|██▌       | 906/3515 [00:00<00:00, 4543.16it/s]

word -> phonemes:  39%|███▊      | 1361/3515 [00:00<00:00, 4508.33it/s]

word -> phonemes:  52%|█████▏    | 1821/3515 [00:00<00:00, 4543.92it/s]

word -> phonemes:  65%|██████▍   | 2276/3515 [00:00<00:00, 4386.86it/s]

word -> phonemes:  77%|███████▋  | 2716/3515 [00:00<00:00, 4374.43it/s]

word -> phonemes:  90%|████████▉ | 3157/3515 [00:00<00:00, 4384.01it/s]
word -> phonemes: 100%|██████████| 3515/3515 [00:00<00:00, 4383.06it/s]


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train:   0%|          | 1/3515 [00:01<1:26:20,  1.47s/it]
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overall:  89%|████████▉ | 3560/4000 [18:05<01:25,  5.12it/s]

train:   1%|▏         | 45/3515 [00:10<11:17,  5.12it/s]
overall:  89%|████████▉ | 3561/4000 [18:06<01:28,  4.96it/s]

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overall:  89%|████████▉ | 3563/4000 [18:06<01:21,  5.36it/s]

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overall:  89%|████████▉ | 3569/4000 [18:07<01:19,  5.45it/s]

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overall:  89%|████████▉ | 3570/4000 [18:07<01:21,  5.30it/s]

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overall:  89%|████████▉ | 3571/4000 [18:08<01:25,  5.00it/s]

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overall:  89%|████████▉ | 3573/4000 [18:08<01:27,  4.86it/s]

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overall:  89%|████████▉ | 3574/4000 [18:08<01:29,  4.77it/s]

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overall:  89%|████████▉ | 3575/4000 [18:09<01:30,  4.68it/s]

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overall:  89%|████████▉ | 3576/4000 [18:09<01:48,  3.91it/s]

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overall:  89%|████████▉ | 3577/4000 [18:09<01:40,  4.20it/s]

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overall:  89%|████████▉ | 3578/4000 [18:09<01:37,  4.32it/s]

train:   2%|▏         | 63/3515 [00:14<13:19,  4.32it/s]
overall:  89%|████████▉ | 3579/4000 [18:10<01:39,  4.22it/s]

train:   2%|▏         | 64/3515 [00:14<13:38,  4.22it/s]
overall:  90%|████████▉ | 3580/4000 [18:10<01:38,  4.26it/s]

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overall:  90%|████████▉ | 3581/4000 [18:10<01:35,  4.39it/s]

train:   2%|▏         | 66/3515 [00:14<13:05,  4.39it/s]
overall:  90%|████████▉ | 3582/4000 [18:10<01:33,  4.45it/s]

train:   2%|▏         | 67/3515 [00:15<12:54,  4.45it/s]
overall:  90%|████████▉ | 3583/4000 [18:10<01:33,  4.47it/s]

train:   2%|▏         | 68/3515 [00:15<12:51,  4.47it/s]
overall:  90%|████████▉ | 3584/4000 [18:11<01:19,  5.25it/s]

train:   2%|▏         | 69/3515 [00:15<10:56,  5.25it/s]
overall:  90%|████████▉ | 3586/4000 [18:11<01:09,  5.92it/s]

train:   2%|▏         | 71/3515 [00:15<09:41,  5.92it/s]
overall:  90%|████████▉ | 3587/4000 [18:11<01:15,  5.50it/s]

train:   2%|▏         | 72/3515 [00:15<10:26,  5.50it/s]
overall:  90%|████████▉ | 3588/4000 [18:11<01:34,  4.37it/s]

train:   2%|▏         | 73/3515 [00:16<13:07,  4.37it/s]
overall:  90%|████████▉ | 3589/4000 [18:12<01:33,  4.39it/s]

train:   2%|▏         | 74/3515 [00:16<13:02,  4.40it/s]
overall:  90%|████████▉ | 3590/4000 [18:12<01:31,  4.47it/s]

train:   2%|▏         | 75/3515 [00:16<12:49,  4.47it/s]
overall:  90%|████████▉ | 3591/4000 [18:12<01:29,  4.55it/s]

train:   2%|▏         | 76/3515 [00:16<12:35,  4.55it/s]
overall:  90%|████████▉ | 3592/4000 [18:12<01:24,  4.83it/s]

train:   2%|▏         | 77/3515 [00:17<11:51,  4.83it/s]
overall:  90%|████████▉ | 3593/4000 [18:12<01:25,  4.75it/s]

train:   2%|▏         | 78/3515 [00:17<12:03,  4.75it/s]
overall:  90%|████████▉ | 3594/4000 [18:13<01:24,  4.79it/s]

train:   2%|▏         | 79/3515 [00:17<11:57,  4.79it/s]
overall:  90%|████████▉ | 3595/4000 [18:13<01:21,  4.98it/s]

train:   2%|▏         | 80/3515 [00:17<11:29,  4.98it/s]
overall:  90%|████████▉ | 3596/4000 [18:13<01:20,  5.02it/s]

train:   2%|▏         | 81/3515 [00:17<11:23,  5.02it/s]
overall:  90%|████████▉ | 3597/4000 [18:13<01:22,  4.90it/s]

train:   2%|▏         | 82/3515 [00:18<11:40,  4.90it/s]
overall:  90%|████████▉ | 3598/4000 [18:13<01:20,  5.01it/s]

train:   2%|▏         | 83/3515 [00:18<11:25,  5.01it/s]
overall:  90%|████████▉ | 3599/4000 [18:14<01:17,  5.15it/s]

train:   2%|▏         | 84/3515 [00:18<11:05,  5.15it/s]
overall:  90%|█████████ | 3600/4000 [18:14<01:34,  4.23it/s]

train:   2%|▏         | 85/3515 [00:18<13:31,  4.23it/s]
overall:  90%|█████████ | 3601/4000 [18:14<01:31,  4.36it/s]

train:   2%|▏         | 86/3515 [00:19<13:06,  4.36it/s]
overall:  90%|█████████ | 3602/4000 [18:14<01:26,  4.58it/s]

train:   2%|▏         | 87/3515 [00:19<12:28,  4.58it/s]
overall:  90%|█████████ | 3603/4000 [18:15<01:28,  4.48it/s]

train:   3%|▎         | 88/3515 [00:19<12:44,  4.48it/s]
overall:  90%|█████████ | 3604/4000 [18:15<01:26,  4.57it/s]

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overall:  90%|█████████ | 3606/4000 [18:15<01:07,  5.83it/s]

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train:   3%|▎         | 95/3515 [00:20<10:47,  5.28it/s]
overall:  90%|█████████ | 3611/4000 [18:16<01:17,  4.99it/s]

train:   3%|▎         | 96/3515 [00:20<11:25,  4.99it/s]
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train:   3%|▎         | 98/3515 [00:21<12:43,  4.48it/s]
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train:   3%|▎         | 99/3515 [00:21<12:22,  4.60it/s]
overall:  90%|█████████ | 3615/4000 [18:17<01:26,  4.44it/s]

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train:   3%|▎         | 101/3515 [00:22<12:39,  4.49it/s]
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train:   3%|▎         | 104/3515 [00:22<12:43,  4.47it/s]
overall:  90%|█████████ | 3620/4000 [18:18<01:25,  4.46it/s]

train:   3%|▎         | 105/3515 [00:22<12:44,  4.46it/s]
overall:  91%|█████████ | 3621/4000 [18:18<01:24,  4.48it/s]

train:   3%|▎         | 106/3515 [00:23<12:40,  4.48it/s]
overall:  91%|█████████ | 3622/4000 [18:19<01:22,  4.60it/s]

train:   3%|▎         | 107/3515 [00:23<12:21,  4.60it/s]
overall:  91%|█████████ | 3623/4000 [18:19<01:23,  4.52it/s]

train:   3%|▎         | 108/3515 [00:23<12:32,  4.53it/s]
overall:  91%|█████████ | 3624/4000 [18:19<01:34,  3.96it/s]

train:   3%|▎         | 109/3515 [00:23<14:19,  3.96it/s]
overall:  91%|█████████ | 3625/4000 [18:19<01:30,  4.16it/s]

train:   3%|▎         | 110/3515 [00:24<13:38,  4.16it/s]
overall:  91%|█████████ | 3626/4000 [18:20<01:23,  4.45it/s]

train:   3%|▎         | 111/3515 [00:24<12:44,  4.45it/s]
overall:  91%|█████████ | 3627/4000 [18:20<01:26,  4.31it/s]

train:   3%|▎         | 112/3515 [00:24<13:09,  4.31it/s]
overall:  91%|█████████ | 3629/4000 [18:20<01:11,  5.15it/s]

train:   3%|▎         | 114/3515 [00:24<10:59,  5.15it/s]
overall:  91%|█████████ | 3630/4000 [18:20<01:12,  5.09it/s]

train:   3%|▎         | 115/3515 [00:25<11:08,  5.09it/s]
overall:  91%|█████████ | 3631/4000 [18:20<01:13,  5.05it/s]

train:   3%|▎         | 116/3515 [00:25<11:12,  5.05it/s]
overall:  91%|█████████ | 3632/4000 [18:21<01:14,  4.97it/s]

train:   3%|▎         | 117/3515 [00:25<11:24,  4.97it/s]
overall:  91%|█████████ | 3633/4000 [18:21<01:15,  4.89it/s]

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overall:  91%|█████████ | 3634/4000 [18:21<01:16,  4.77it/s]

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overall:  91%|█████████ | 3635/4000 [18:21<01:18,  4.66it/s]

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overall:  91%|█████████ | 3636/4000 [18:22<01:31,  3.99it/s]

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overall:  91%|█████████ | 3637/4000 [18:22<01:27,  4.17it/s]

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overall:  91%|█████████ | 3638/4000 [18:22<01:23,  4.35it/s]

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overall:  91%|█████████ | 3639/4000 [18:22<01:25,  4.23it/s]

train:   4%|▎         | 124/3515 [00:27<13:22,  4.23it/s]
overall:  91%|█████████ | 3640/4000 [18:23<01:23,  4.30it/s]

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overall:  91%|█████████ | 3641/4000 [18:23<01:21,  4.39it/s]

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overall: 100%|█████████▉| 3993/4000 [19:38<00:01,  5.13it/s]

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overall: 100%|█████████▉| 3994/4000 [19:38<00:01,  5.32it/s]

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overall: 100%|█████████▉| 3999/4000 [19:39<00:00,  4.77it/s]

train:  14%|█▍        | 484/3515 [01:43<10:36,  4.77it/s]train loss: 1.8871225118637085
train per: 0.50321551549524
train loss: 1.8395845890045166
train per: 0.5000436795666987
train loss: 1.8739843368530273
train per: 0.5069113866048927
train loss: 1.9307911396026611
train per: 0.5102836879432624
train loss: 1.906418800354004
train per: 0.51329969318153
train loss: 1.8799079656600952
train per: 0.5052346928649399
train loss: 1.8957910537719727
train per: 0.506092943201377
train loss: 1.8705753087997437
train per: 0.503726581244576
train loss: 1.9003709554672241
train per: 0.519716731200326
train loss: 1.8892910480499268
train per: 0.5081315504156125
train loss: 1.891242265701294
train per: 0.5090185055048021
train loss: 1.9314000606536865
train per: 0.5100178491744757
train loss: 1.8606493473052979
train per: 0.5003150598613737
train loss: 1.8951365947723389
train per: 0.5049205147615443
train loss: 1.9250881671905518
train per: 0.5154655079320186
train loss: 1.8678982257843018
train per: 0.5053697920633712
train loss: 1.8512436151504517
train per: 0.5032018127185853
train loss: 1.8911540508270264
train per: 0.507154061890954
train loss: 1.8911577463150024
train per: 0.5078452657028667
train loss: 1.8607635498046875
train per: 0.49515130272228064
train loss: 1.8772722482681274
train per: 0.5055199430199431
train loss: 1.8789503574371338
train per: 0.500904478270461
train loss: 1.8995062112808228
train per: 0.5078286980767855
train loss: 1.8778400421142578
train per: 0.4998541139856059
train loss: 1.8694183826446533
train per: 0.49653242185564966
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  16%|█▌        | 425/2703 [00:00<00:00, 4248.36it/s]


word -> phonemes:  33%|███▎      | 880/2703 [00:00<00:00, 4424.60it/s]


word -> phonemes:  49%|████▉     | 1323/2703 [00:00<00:00, 4301.90it/s]


word -> phonemes:  66%|██████▋   | 1795/2703 [00:00<00:00, 4463.30it/s]


word -> phonemes:  84%|████████▎ | 2258/2703 [00:00<00:00, 4393.50it/s]


word -> phonemes: 100%|█████████▉| 2698/2703 [00:00<00:00, 4325.13it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 4353.39it/s]



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overall: 100%|█████████▉| 3999/4000 [21:36<00:00,  4.77it/s]

train:  14%|█▍        | 484/3515 [03:41<10:36,  4.77it/s]
                                                            

                                                         

overall: 100%|█████████▉| 3999/4000 [21:36<00:00,  4.77it/s]

train:  14%|█▍        | 484/3515 [03:41<10:36,  4.77it/s]
overall: 100%|██████████| 4000/4000 [21:36<00:00, 31.92s/it]

train:  14%|█▍        | 485/3515 [03:41<26:51:46, 31.92s/it]403-128339-0009 Failed!!!

train:  14%|█▍        | 485/3515 [03:41<23:03,  2.19it/s]   

overall: 100%|██████████| 4000/4000 [21:37<00:00,  3.08it/s]
dev loss: 2.227613925933838
dev per: 0.5555046826222685
[Runner] - Save the checkpoint to:
1. result/downstream/grid/states-4000.ckpt