/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")
2023-10-02 01:50:50 | 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_25hz_test_demuc_label_update4_4and2codebook_varmask_12sec {'model_config': None, 'refresh': False}
Loading model from Local mert_25hz_test_demuc_label_update4_4and2codebook_varmask_12sec
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.


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word -> phonemes:  89%|████████▊ | 3116/3515 [00:01<00:00, 2020.89it/s]

word -> phonemes:  95%|█████████▌| 3343/3515 [00:01<00:00, 2090.17it/s]
word -> phonemes: 100%|██████████| 3515/3515 [00:01<00:00, 2105.19it/s]


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train:   4%|▍         | 132/3515 [00:28<11:53,  4.74it/s]
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train:   4%|▍         | 134/3515 [00:29<11:51,  4.75it/s]
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train:   4%|▍         | 135/3515 [00:29<11:26,  4.93it/s]
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train:   4%|▍         | 136/3515 [00:29<11:18,  4.98it/s]
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train:   4%|▍         | 138/3515 [00:30<10:52,  5.17it/s]
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train:   4%|▍         | 143/3515 [00:31<10:55,  5.14it/s]
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train:   4%|▍         | 144/3515 [00:31<11:12,  5.02it/s]
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train:   4%|▍         | 147/3515 [00:31<09:28,  5.93it/s]
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train:   4%|▍         | 148/3515 [00:31<09:36,  5.84it/s]
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train:   4%|▍         | 149/3515 [00:32<10:22,  5.41it/s]
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train:   4%|▍         | 151/3515 [00:32<10:43,  5.22it/s]
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train:   4%|▍         | 152/3515 [00:32<13:18,  4.21it/s]
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train:   4%|▍         | 153/3515 [00:33<13:07,  4.27it/s]
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train:   4%|▍         | 154/3515 [00:33<13:16,  4.22it/s]
overall:   4%|▍         | 155/4000 [00:36<14:50,  4.32it/s]

train:   4%|▍         | 155/3515 [00:33<12:58,  4.32it/s]
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train:   4%|▍         | 156/3515 [00:33<11:13,  4.98it/s]
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train:   4%|▍         | 157/3515 [00:33<11:20,  4.93it/s]
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train:   4%|▍         | 158/3515 [00:34<11:23,  4.91it/s]
overall:   4%|▍         | 159/4000 [00:37<13:14,  4.83it/s]

train:   5%|▍         | 159/3515 [00:34<11:34,  4.83it/s]
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train:   5%|▍         | 160/3515 [00:34<11:38,  4.80it/s]
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train:   5%|▍         | 161/3515 [00:34<11:47,  4.74it/s]
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train:   5%|▍         | 162/3515 [00:34<11:37,  4.81it/s]
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train:   5%|▍         | 163/3515 [00:35<11:43,  4.77it/s]
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train:   5%|▍         | 164/3515 [00:35<11:42,  4.77it/s]
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train:   5%|▍         | 165/3515 [00:35<11:33,  4.83it/s]
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train:   5%|▍         | 166/3515 [00:35<11:25,  4.89it/s]
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train:   5%|▍         | 167/3515 [00:35<11:30,  4.85it/s]
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train:   5%|▍         | 168/3515 [00:36<11:34,  4.82it/s]
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train:   5%|▍         | 169/3515 [00:36<11:42,  4.77it/s]
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train:   5%|▍         | 170/3515 [00:36<11:32,  4.83it/s]
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train:   5%|▍         | 171/3515 [00:36<11:14,  4.96it/s]
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train:   5%|▍         | 173/3515 [00:36<08:41,  6.41it/s]
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train:   5%|▍         | 174/3515 [00:37<09:22,  5.94it/s]
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train:   5%|▍         | 175/3515 [00:37<11:55,  4.67it/s]
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train:   5%|▌         | 176/3515 [00:37<14:49,  3.75it/s]
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train:   5%|▌         | 177/3515 [00:38<14:02,  3.96it/s]
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train:   5%|▌         | 178/3515 [00:38<14:11,  3.92it/s]
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train:   5%|▌         | 179/3515 [00:38<13:27,  4.13it/s]
overall:   4%|▍         | 180/4000 [00:41<14:46,  4.31it/s]

train:   5%|▌         | 180/3515 [00:38<12:53,  4.31it/s]
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train:   5%|▌         | 181/3515 [00:39<12:37,  4.40it/s]
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train:   5%|▌         | 182/3515 [00:39<12:15,  4.53it/s]
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train:   5%|▌         | 183/3515 [00:39<12:06,  4.59it/s]
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train:   5%|▌         | 184/3515 [00:39<10:34,  5.25it/s]
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train:   5%|▌         | 185/3515 [00:39<10:42,  5.18it/s]
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train:   5%|▌         | 186/3515 [00:39<11:03,  5.02it/s]
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train:   5%|▌         | 187/3515 [00:40<11:03,  5.02it/s]
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train:   5%|▌         | 188/3515 [00:40<10:57,  5.06it/s]
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train:   5%|▌         | 189/3515 [00:40<11:11,  4.95it/s]
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train:   5%|▌         | 190/3515 [00:40<11:21,  4.88it/s]
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train:   5%|▌         | 191/3515 [00:41<11:17,  4.91it/s]
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train:   5%|▌         | 192/3515 [00:41<11:20,  4.88it/s]
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train:   5%|▌         | 193/3515 [00:41<11:25,  4.85it/s]
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train:   6%|▌         | 195/3515 [00:41<10:56,  5.06it/s]
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train:   6%|▌         | 197/3515 [00:42<09:10,  6.03it/s]
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train:   6%|▋         | 224/3515 [00:47<14:02,  3.91it/s]
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overall:   9%|▉         | 370/4000 [01:22<14:31,  4.16it/s]

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overall:   9%|▉         | 371/4000 [01:22<14:05,  4.29it/s]

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overall:   9%|▉         | 373/4000 [01:22<13:22,  4.52it/s]

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overall:   9%|▉         | 374/4000 [01:22<12:24,  4.87it/s]

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overall:  10%|▉         | 380/4000 [01:23<12:21,  4.88it/s]

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overall:  10%|▉         | 382/4000 [01:24<12:06,  4.98it/s]

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overall:  10%|▉         | 383/4000 [01:24<12:00,  5.02it/s]

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overall:  10%|▉         | 389/4000 [01:25<12:01,  5.01it/s]

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overall:  10%|▉         | 391/4000 [01:26<13:10,  4.57it/s]

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overall:  10%|█         | 407/4000 [01:29<12:36,  4.75it/s]

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overall:  10%|█         | 408/4000 [01:29<12:24,  4.83it/s]

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overall:  10%|█         | 409/4000 [01:30<12:17,  4.87it/s]

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overall:  10%|█         | 410/4000 [01:30<12:19,  4.85it/s]

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overall:  10%|█         | 411/4000 [01:30<11:51,  5.04it/s]

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overall:  10%|█         | 412/4000 [01:30<12:09,  4.92it/s]

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overall:  10%|█         | 415/4000 [01:31<12:59,  4.60it/s]

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overall:  10%|█         | 416/4000 [01:31<13:48,  4.33it/s]

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overall:  10%|█         | 417/4000 [01:31<13:30,  4.42it/s]

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overall:  10%|█         | 418/4000 [01:32<13:57,  4.28it/s]

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overall:  10%|█         | 419/4000 [01:32<13:18,  4.49it/s]

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overall:  10%|█         | 420/4000 [01:32<13:07,  4.55it/s]

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overall:  11%|█         | 421/4000 [01:32<12:53,  4.63it/s]

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overall:  11%|█         | 422/4000 [01:32<12:48,  4.66it/s]

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overall:  11%|█         | 423/4000 [01:33<12:38,  4.72it/s]

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overall:  11%|█         | 427/4000 [01:33<10:06,  5.89it/s]

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overall:  11%|█         | 428/4000 [01:33<11:35,  5.14it/s]

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overall:  11%|█         | 429/4000 [01:34<11:42,  5.08it/s]

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overall:  11%|█         | 433/4000 [01:35<12:26,  4.78it/s]

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overall:  11%|█         | 434/4000 [01:35<12:31,  4.75it/s]

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overall:  11%|█         | 437/4000 [01:35<12:24,  4.78it/s]

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overall:  12%|█▏        | 494/4000 [01:48<13:05,  4.46it/s]

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overall:  12%|█▏        | 495/4000 [01:48<13:00,  4.49it/s]

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overall:  12%|█▏        | 496/4000 [01:48<12:43,  4.59it/s]

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overall:  12%|█▏        | 497/4000 [01:49<12:28,  4.68it/s]

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overall:  12%|█▏        | 498/4000 [01:49<12:00,  4.86it/s]

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overall:  12%|█▏        | 499/4000 [01:49<12:10,  4.80it/s]

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overall:  13%|█▎        | 501/4000 [01:50<12:58,  4.50it/s]

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overall:  13%|█▎        | 503/4000 [01:50<12:35,  4.63it/s]

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overall:  13%|█▎        | 506/4000 [01:50<11:10,  5.21it/s]

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overall:  13%|█▎        | 507/4000 [01:51<11:31,  5.05it/s]

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overall:  13%|█▎        | 508/4000 [01:51<10:39,  5.46it/s]

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overall:  13%|█▎        | 510/4000 [01:51<11:37,  5.00it/s]

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overall:  13%|█▎        | 513/4000 [01:52<14:53,  3.90it/s]

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overall:  13%|█▎        | 515/4000 [01:53<14:25,  4.02it/s]

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overall:  13%|█▎        | 516/4000 [01:53<13:44,  4.22it/s]

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overall:  13%|█▎        | 517/4000 [01:53<11:58,  4.84it/s]

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overall:  13%|█▎        | 518/4000 [01:53<12:17,  4.72it/s]

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overall:  13%|█▎        | 519/4000 [01:53<12:35,  4.61it/s]

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overall:  13%|█▎        | 520/4000 [01:54<13:08,  4.42it/s]

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overall:  13%|█▎        | 521/4000 [01:54<13:08,  4.41it/s]

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overall:  13%|█▎        | 522/4000 [01:54<13:05,  4.43it/s]

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overall:  13%|█▎        | 523/4000 [01:54<12:00,  4.83it/s]

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overall:  13%|█▎        | 524/4000 [01:55<13:06,  4.42it/s]

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overall:  13%|█▎        | 525/4000 [01:55<12:44,  4.54it/s]

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overall:  13%|█▎        | 526/4000 [01:55<12:34,  4.60it/s]

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overall:  13%|█▎        | 527/4000 [01:55<12:09,  4.76it/s]

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overall:  13%|█▎        | 528/4000 [01:55<11:57,  4.84it/s]

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overall:  13%|█▎        | 529/4000 [01:56<11:57,  4.84it/s]

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overall:  13%|█▎        | 530/4000 [01:56<12:13,  4.73it/s]

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overall:  13%|█▎        | 531/4000 [01:56<12:12,  4.74it/s]

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overall:  13%|█▎        | 532/4000 [01:56<12:13,  4.73it/s]

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overall:  13%|█▎        | 533/4000 [01:56<12:03,  4.79it/s]

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overall:  13%|█▎        | 534/4000 [01:57<10:38,  5.43it/s]

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overall:  13%|█▎        | 535/4000 [01:57<12:23,  4.66it/s]

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overall:  13%|█▎        | 536/4000 [01:57<15:06,  3.82it/s]

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overall:  13%|█▎        | 537/4000 [01:57<14:16,  4.04it/s]

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overall:  13%|█▎        | 538/4000 [01:58<12:59,  4.44it/s]

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overall:  13%|█▎        | 539/4000 [01:58<12:48,  4.50it/s]

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overall:  14%|█▎        | 540/4000 [01:58<12:41,  4.55it/s]

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overall:  14%|█▎        | 541/4000 [01:58<12:31,  4.60it/s]

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overall:  14%|█▎        | 542/4000 [01:58<12:42,  4.53it/s]

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overall:  14%|█▎        | 543/4000 [01:59<12:43,  4.53it/s]

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overall:  14%|█▎        | 544/4000 [01:59<12:46,  4.51it/s]

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overall:  14%|█▎        | 545/4000 [01:59<12:43,  4.52it/s]

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overall:  14%|█▎        | 546/4000 [01:59<12:42,  4.53it/s]

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overall:  14%|█▎        | 547/4000 [02:00<12:18,  4.67it/s]

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overall:  14%|█▎        | 548/4000 [02:00<13:08,  4.38it/s]

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overall:  14%|█▎        | 549/4000 [02:00<12:56,  4.44it/s]

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overall:  14%|█▍        | 550/4000 [02:00<12:26,  4.62it/s]

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overall:  14%|█▍        | 551/4000 [02:00<12:31,  4.59it/s]

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overall:  14%|█▍        | 552/4000 [02:01<12:25,  4.62it/s]

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overall:  14%|█▍        | 553/4000 [02:01<12:29,  4.60it/s]

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overall:  14%|█▍        | 554/4000 [02:01<12:34,  4.57it/s]

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overall:  14%|█▍        | 555/4000 [02:01<12:34,  4.57it/s]

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overall:  14%|█▍        | 556/4000 [02:02<12:24,  4.62it/s]

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overall:  14%|█▍        | 557/4000 [02:02<11:27,  5.00it/s]

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overall:  14%|█▍        | 558/4000 [02:02<11:32,  4.97it/s]

train:  16%|█▌        | 558/3515 [01:59<09:54,  4.97it/s]
overall:  14%|█▍        | 559/4000 [02:02<12:33,  4.57it/s]

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overall:  14%|█▍        | 560/4000 [02:03<16:05,  3.56it/s]

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overall:  14%|█▍        | 561/4000 [02:03<14:44,  3.89it/s]

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overall:  14%|█▍        | 562/4000 [02:03<14:48,  3.87it/s]

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overall:  14%|█▍        | 563/4000 [02:03<14:00,  4.09it/s]

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overall:  14%|█▍        | 564/4000 [02:03<13:23,  4.28it/s]

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overall:  14%|█▍        | 565/4000 [02:04<12:57,  4.42it/s]

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overall:  14%|█▍        | 566/4000 [02:04<12:47,  4.47it/s]

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overall:  14%|█▍        | 567/4000 [02:04<11:25,  5.01it/s]

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overall:  14%|█▍        | 568/4000 [02:04<11:50,  4.83it/s]

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overall:  14%|█▍        | 569/4000 [02:04<12:05,  4.73it/s]

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overall:  14%|█▍        | 571/4000 [02:05<09:21,  6.10it/s]

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overall:  14%|█▍        | 572/4000 [02:05<10:59,  5.20it/s]

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overall:  14%|█▍        | 574/4000 [02:05<11:27,  4.98it/s]

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overall:  14%|█▍        | 575/4000 [02:06<10:39,  5.36it/s]

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overall:  14%|█▍        | 576/4000 [02:06<11:21,  5.03it/s]

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overall:  14%|█▍        | 577/4000 [02:06<10:03,  5.67it/s]

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overall:  15%|█▍        | 588/4000 [02:08<13:15,  4.29it/s]

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train:  28%|██▊       | 980/3515 [03:32<09:27,  4.46it/s]
overall:  25%|██▍       | 981/4000 [03:35<11:13,  4.48it/s]

train:  28%|██▊       | 981/3515 [03:32<09:25,  4.48it/s]
overall:  25%|██▍       | 982/4000 [03:36<10:58,  4.58it/s]

train:  28%|██▊       | 982/3515 [03:33<09:12,  4.58it/s]
overall:  25%|██▍       | 983/4000 [03:36<11:06,  4.53it/s]

train:  28%|██▊       | 983/3515 [03:33<09:19,  4.53it/s]
overall:  25%|██▍       | 984/4000 [03:36<11:11,  4.49it/s]

train:  28%|██▊       | 984/3515 [03:33<09:23,  4.49it/s]
overall:  25%|██▍       | 985/4000 [03:36<11:03,  4.54it/s]

train:  28%|██▊       | 985/3515 [03:33<09:17,  4.54it/s]
overall:  25%|██▍       | 986/4000 [03:37<11:45,  4.27it/s]

train:  28%|██▊       | 986/3515 [03:34<09:51,  4.27it/s]
overall:  25%|██▍       | 987/4000 [03:37<11:17,  4.45it/s]

train:  28%|██▊       | 987/3515 [03:34<09:28,  4.45it/s]
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overall:  25%|██▍       | 989/4000 [03:37<12:46,  3.93it/s]

train:  28%|██▊       | 989/3515 [03:34<10:42,  3.93it/s]
overall:  25%|██▍       | 990/4000 [03:38<12:04,  4.15it/s]

train:  28%|██▊       | 990/3515 [03:35<10:07,  4.15it/s]
overall:  25%|██▍       | 991/4000 [03:38<11:46,  4.26it/s]

train:  28%|██▊       | 991/3515 [03:35<09:52,  4.26it/s]
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overall:  25%|██▍       | 993/4000 [03:38<11:22,  4.41it/s]

train:  28%|██▊       | 993/3515 [03:35<09:32,  4.41it/s]
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train:  28%|██▊       | 995/3515 [03:36<09:27,  4.44it/s]
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train:  28%|██▊       | 996/3515 [03:36<08:58,  4.68it/s]
overall:  25%|██▍       | 997/4000 [03:39<10:44,  4.66it/s]

train:  28%|██▊       | 997/3515 [03:36<09:00,  4.66it/s]
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overall:  25%|██▍       | 999/4000 [03:40<10:48,  4.63it/s]

train:  28%|██▊       | 999/3515 [03:37<09:03,  4.63it/s]train loss: 3.934178590774536
train per: 0.8303286812568643
train loss: 2.8028950691223145
train per: 0.7167847369632491
train loss: 2.5897700786590576
train per: 0.6770241154634894
train loss: 2.5411489009857178
train per: 0.6581527413481372
train loss: 2.526674747467041
train per: 0.6601894414263825
train loss: 2.5413098335266113
train per: 0.6699381554181232
train loss: 2.446993350982666
train per: 0.6461849936579178
train loss: 2.5001635551452637
train per: 0.6486393111512704
train loss: 2.4039831161499023
train per: 0.634786628387913
train loss: 2.3956458568573
train per: 0.635982460948205
train loss: 2.4037537574768066
train per: 0.6383718174876912
train loss: 2.4039416313171387
train per: 0.633683480329006
train loss: 2.4483642578125
train per: 0.6435366140805274
train loss: 2.4016273021698
train per: 0.6313856352601286
train loss: 2.3487823009490967
train per: 0.6266864448682631
train loss: 2.358884334564209
train per: 0.6229641693811075
train loss: 2.344348430633545
train per: 0.6272694818441452
train loss: 2.337423801422119
train per: 0.6210184848569591
train loss: 2.366758108139038
train per: 0.6239636413717119
train loss: 2.3242862224578857
train per: 0.6195810885655304
train loss: 2.301501989364624
train per: 0.6151569705788059
train loss: 2.3725383281707764
train per: 0.6284688214169115
train loss: 2.3744702339172363
train per: 0.6217883965040186
train loss: 2.3689486980438232
train per: 0.6253632760898282
train loss: 2.3205792903900146
train per: 0.6134022916759553
train loss: 2.2975780963897705
train per: 0.6148741123305358
train loss: 2.3533918857574463
train per: 0.6235459384858044
train loss: 2.3027164936065674
train per: 0.6167726061103137
train loss: 2.298499345779419
train per: 0.6091969047370072
train loss: 2.3139119148254395
train per: 0.6148560287229237
train loss: 2.3378684520721436
train per: 0.6176477652088287
train loss: 2.288757801055908
train per: 0.6116200460490864
train loss: 2.3331665992736816
train per: 0.6211097299129845
train loss: 2.3293309211730957
train per: 0.6210436048022452
train loss: 2.308565855026245
train per: 0.6159025241236439
train loss: 2.305823564529419
train per: 0.6168011224131884
train loss: 2.3617701530456543
train per: 0.6231588329111549
train loss: 2.334365129470825
train per: 0.613063388768378
train loss: 2.324131488800049
train per: 0.6173883127733818
train loss: 2.3242948055267334
train per: 0.6182756768120343
train loss: 2.290757417678833
train per: 0.6146147736298649
train loss: 2.305602550506592
train per: 0.6137691845540445
train loss: 2.3016974925994873
train per: 0.6074150096215523
train loss: 2.3425774574279785
train per: 0.6201965589550542
train loss: 2.2994635105133057
train per: 0.6073924561624826
train loss: 2.2930705547332764
train per: 0.6087334247828075
train loss: 2.3176403045654297
train per: 0.6147621509824198
train loss: 2.3127493858337402
train per: 0.6153991522907049
train loss: 2.305131435394287
train per: 0.6135458167330677
train loss: 2.2793655395507812
train per: 0.6095066333967438
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:   6%|▌         | 166/2703 [00:00<00:01, 1654.90it/s]


word -> phonemes:  16%|█▌        | 424/2703 [00:00<00:01, 2172.41it/s]


word -> phonemes:  26%|██▌       | 703/2703 [00:00<00:00, 2449.46it/s]


word -> phonemes:  37%|███▋      | 1012/2703 [00:00<00:00, 2698.79it/s]


word -> phonemes:  48%|████▊     | 1298/2703 [00:00<00:00, 2753.99it/s]


word -> phonemes:  58%|█████▊    | 1574/2703 [00:00<00:00, 2730.83it/s]


word -> phonemes:  68%|██████▊   | 1848/2703 [00:00<00:00, 2440.71it/s]


word -> phonemes:  79%|███████▉  | 2148/2703 [00:00<00:00, 2555.59it/s]


word -> phonemes:  90%|████████▉ | 2431/2703 [00:00<00:00, 2635.29it/s]


word -> phonemes: 100%|█████████▉| 2698/2703 [00:01<00:00, 2629.61it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:01<00:00, 2566.25it/s]



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train:  55%|█████▌    | 1943/3515 [08:05<05:06,  5.13it/s]
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train:  56%|█████▌    | 1961/3515 [08:09<05:15,  4.92it/s]
overall:  49%|████▉     | 1962/4000 [08:12<06:59,  4.85it/s]

train:  56%|█████▌    | 1962/3515 [08:09<05:19,  4.85it/s]
overall:  49%|████▉     | 1963/4000 [08:12<07:08,  4.75it/s]

train:  56%|█████▌    | 1963/3515 [08:09<05:26,  4.75it/s]
overall:  49%|████▉     | 1964/4000 [08:12<06:50,  4.96it/s]

train:  56%|█████▌    | 1964/3515 [08:09<05:12,  4.96it/s]
overall:  49%|████▉     | 1965/4000 [08:13<06:57,  4.88it/s]

train:  56%|█████▌    | 1965/3515 [08:10<05:17,  4.88it/s]
overall:  49%|████▉     | 1966/4000 [08:13<06:44,  5.03it/s]

train:  56%|█████▌    | 1966/3515 [08:10<05:08,  5.03it/s]
overall:  49%|████▉     | 1967/4000 [08:13<06:26,  5.26it/s]

train:  56%|█████▌    | 1967/3515 [08:10<04:54,  5.26it/s]
overall:  49%|████▉     | 1968/4000 [08:13<06:10,  5.49it/s]

train:  56%|█████▌    | 1968/3515 [08:10<04:42,  5.49it/s]
overall:  49%|████▉     | 1969/4000 [08:13<06:31,  5.18it/s]

train:  56%|█████▌    | 1969/3515 [08:10<04:58,  5.18it/s]
overall:  49%|████▉     | 1970/4000 [08:14<09:16,  3.65it/s]

train:  56%|█████▌    | 1970/3515 [08:11<07:03,  3.65it/s]
overall:  49%|████▉     | 1971/4000 [08:14<08:33,  3.95it/s]

train:  56%|█████▌    | 1971/3515 [08:11<06:30,  3.95it/s]
overall:  49%|████▉     | 1972/4000 [08:14<09:11,  3.68it/s]

train:  56%|█████▌    | 1972/3515 [08:11<06:59,  3.68it/s]
overall:  49%|████▉     | 1973/4000 [08:15<08:34,  3.94it/s]

train:  56%|█████▌    | 1973/3515 [08:12<06:31,  3.94it/s]
overall:  49%|████▉     | 1974/4000 [08:15<08:10,  4.13it/s]

train:  56%|█████▌    | 1974/3515 [08:12<06:12,  4.13it/s]
overall:  49%|████▉     | 1975/4000 [08:15<07:56,  4.25it/s]

train:  56%|█████▌    | 1975/3515 [08:12<06:02,  4.25it/s]
overall:  49%|████▉     | 1976/4000 [08:15<07:29,  4.51it/s]

train:  56%|█████▌    | 1976/3515 [08:12<05:41,  4.51it/s]
overall:  49%|████▉     | 1977/4000 [08:15<07:23,  4.56it/s]

train:  56%|█████▌    | 1977/3515 [08:12<05:37,  4.56it/s]
overall:  49%|████▉     | 1978/4000 [08:16<07:01,  4.80it/s]

train:  56%|█████▋    | 1978/3515 [08:13<05:20,  4.80it/s]
overall:  49%|████▉     | 1979/4000 [08:16<06:26,  5.23it/s]

train:  56%|█████▋    | 1979/3515 [08:13<04:53,  5.23it/s]
overall:  50%|████▉     | 1980/4000 [08:16<06:42,  5.02it/s]

train:  56%|█████▋    | 1980/3515 [08:13<05:05,  5.02it/s]
overall:  50%|████▉     | 1981/4000 [08:16<06:05,  5.52it/s]

train:  56%|█████▋    | 1981/3515 [08:13<04:37,  5.52it/s]
overall:  50%|████▉     | 1982/4000 [08:16<06:09,  5.47it/s]

train:  56%|█████▋    | 1982/3515 [08:13<04:40,  5.47it/s]
overall:  50%|████▉     | 1984/4000 [08:17<05:32,  6.06it/s]

train:  56%|█████▋    | 1984/3515 [08:14<04:12,  6.06it/s]
overall:  50%|████▉     | 1985/4000 [08:17<05:52,  5.72it/s]

train:  56%|█████▋    | 1985/3515 [08:14<04:27,  5.72it/s]
overall:  50%|████▉     | 1987/4000 [08:17<05:28,  6.13it/s]

train:  57%|█████▋    | 1987/3515 [08:14<04:09,  6.13it/s]
overall:  50%|████▉     | 1988/4000 [08:17<05:49,  5.75it/s]

train:  57%|█████▋    | 1988/3515 [08:14<04:25,  5.75it/s]
overall:  50%|████▉     | 1989/4000 [08:18<06:12,  5.40it/s]

train:  57%|█████▋    | 1989/3515 [08:15<04:42,  5.40it/s]
overall:  50%|████▉     | 1990/4000 [08:18<06:29,  5.16it/s]

train:  57%|█████▋    | 1990/3515 [08:15<04:55,  5.16it/s]
overall:  50%|████▉     | 1991/4000 [08:18<06:38,  5.04it/s]

train:  57%|█████▋    | 1991/3515 [08:15<05:02,  5.04it/s]
overall:  50%|████▉     | 1992/4000 [08:18<05:49,  5.74it/s]

train:  57%|█████▋    | 1992/3515 [08:15<04:25,  5.74it/s]
overall:  50%|████▉     | 1993/4000 [08:18<06:11,  5.41it/s]

train:  57%|█████▋    | 1993/3515 [08:15<04:41,  5.41it/s]
overall:  50%|████▉     | 1994/4000 [08:19<08:32,  3.91it/s]

train:  57%|█████▋    | 1994/3515 [08:16<06:28,  3.91it/s]
overall:  50%|████▉     | 1995/4000 [08:19<08:00,  4.17it/s]

train:  57%|█████▋    | 1995/3515 [08:16<06:04,  4.17it/s]
overall:  50%|████▉     | 1996/4000 [08:19<08:49,  3.78it/s]

train:  57%|█████▋    | 1996/3515 [08:16<06:41,  3.78it/s]
overall:  50%|████▉     | 1997/4000 [08:19<08:21,  4.00it/s]

train:  57%|█████▋    | 1997/3515 [08:16<06:19,  4.00it/s]
overall:  50%|████▉     | 1998/4000 [08:20<07:53,  4.22it/s]

train:  57%|█████▋    | 1998/3515 [08:17<05:59,  4.22it/s]
overall:  50%|████▉     | 1999/4000 [08:20<07:30,  4.44it/s]

train:  57%|█████▋    | 1999/3515 [08:17<05:41,  4.44it/s]dev loss: 2.5190837383270264
dev per: 0.6410197710718002
[Runner] - Save the checkpoint to:
1. result/downstream/grid/dev-best.ckpt
train loss: 2.2946364879608154
train per: 0.6124737919013817
train loss: 2.2815399169921875
train per: 0.6138592080452545
train loss: 2.3371825218200684
train per: 0.6133275579062557
train loss: 2.281982421875
train per: 0.6121299960978873
train loss: 2.3473286628723145
train per: 0.6119953863898501
train loss: 2.2933197021484375
train per: 0.6082302791830616
train loss: 2.2747957706451416
train per: 0.6065042757190983
train loss: 2.282858371734619
train per: 0.6067463706233988
train loss: 2.284027576446533
train per: 0.6048806062628093
train loss: 2.287623882293701
train per: 0.6096447759636952
train loss: 2.310297727584839
train per: 0.6081370943561594
train loss: 2.2665421962738037
train per: 0.6034491087387083
train loss: 2.311532974243164
train per: 0.6140470766894457
train loss: 2.259270191192627
train per: 0.6056646693297825
train loss: 2.2788708209991455
train per: 0.6043047948496204
train loss: 2.3271403312683105
train per: 0.6116495397652559
train loss: 2.306241512298584
train per: 0.6156296212035036
train loss: 2.2655229568481445
train per: 0.6092785520766416
train loss: 2.306877613067627
train per: 0.6147861940201748
train loss: 2.3032491207122803
train per: 0.6129828202467428
train loss: 2.245579719543457
train per: 0.6036407350163147
train loss: 2.2684848308563232
train per: 0.6044205641714495
train loss: 2.2504284381866455
train per: 0.6057740696596478
train loss: 2.3101487159729004
train per: 0.6086595097852936
train loss: 2.3310532569885254
train per: 0.6185709773815019
train loss: 2.2994120121002197
train per: 0.6069836894096026
train loss: 2.288857936859131
train per: 0.6059983788165361
train loss: 2.324650287628174
train per: 0.6141724831420797
train loss: 2.3049168586730957
train per: 0.6068130275186459
train loss: 2.3041675090789795
train per: 0.6113559697633763
train loss: 2.274806499481201
train per: 0.6043350006412723
train loss: 2.3165054321289062
train per: 0.6206317939738819
train loss: 2.2969987392425537
train per: 0.6087177121771218
train loss: 2.292346954345703
train per: 0.612374769985688
train loss: 2.2493536472320557
train per: 0.5963167676377592
train loss: 2.260808229446411
train per: 0.6162710023830352
train loss: 2.3159937858581543
train per: 0.6168507114036951
train loss: 2.266824245452881
train per: 0.6111869369928282
train loss: 2.258042335510254
train per: 0.6057990743261639
train loss: 2.334789276123047
train per: 0.6124976890367906
train loss: 2.3119659423828125
train per: 0.6077867194173447
train loss: 2.3102753162384033
train per: 0.6142827752918788
train loss: 2.264061450958252
train per: 0.6043616809400518
train loss: 2.237853765487671
train per: 0.5992543329302701
train loss: 2.2756307125091553
train per: 0.6068899876964505
train loss: 2.273515224456787
train per: 0.6064151650646603
train loss: 2.279998779296875
train per: 0.6054234769687964
train loss: 2.3218536376953125
train per: 0.6143095536086776
train loss: 2.244652271270752
train per: 0.5978266050235927
train loss: 2.2773876190185547
train per: 0.6024688369841462
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:   8%|▊         | 217/2703 [00:00<00:01, 2163.46it/s]


word -> phonemes:  16%|█▌        | 434/2703 [00:00<00:01, 2134.48it/s]


word -> phonemes:  24%|██▍       | 648/2703 [00:00<00:00, 2136.21it/s]


word -> phonemes:  32%|███▏      | 863/2703 [00:00<00:00, 2139.17it/s]


word -> phonemes:  40%|███▉      | 1077/2703 [00:00<00:00, 2139.21it/s]


word -> phonemes:  48%|████▊     | 1291/2703 [00:00<00:00, 2123.49it/s]


word -> phonemes:  56%|█████▌    | 1506/2703 [00:00<00:00, 2127.35it/s]


word -> phonemes:  64%|██████▍   | 1725/2703 [00:00<00:00, 2144.63it/s]


word -> phonemes:  72%|███████▏  | 1945/2703 [00:00<00:00, 2160.59it/s]


word -> phonemes:  80%|████████  | 2163/2703 [00:01<00:00, 2165.50it/s]


word -> phonemes:  88%|████████▊ | 2380/2703 [00:01<00:00, 2121.70it/s]


word -> phonemes:  96%|█████████▌| 2594/2703 [00:01<00:00, 2123.00it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:01<00:00, 2130.89it/s]



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


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dev:   2%|▏         | 66/2703 [00:04<02:07, 20.67it/s]


dev:   3%|▎         | 69/2703 [00:04<02:06, 20.89it/s]


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dev:   3%|▎         | 75/2703 [00:04<02:04, 21.11it/s]


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overall:  75%|███████▍  | 2995/4000 [13:03<03:22,  4.96it/s]

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train:  85%|████████▌ | 2999/3515 [13:00<01:47,  4.82it/s]dev loss: 2.5429012775421143
dev per: 0.6479448491155047
train loss: 2.2438292503356934
train per: 0.6015993107347675
train loss: 2.24178409576416
train per: 0.6092355986342108
train loss: 2.2589783668518066
train per: 0.60382912470199
train loss: 2.2890515327453613
train per: 0.6041666666666666
train loss: 2.262890338897705
train per: 0.6019257633206945
train loss: 2.2662124633789062
train per: 0.6021201899910511
train loss: 2.2830982208251953
train per: 0.6041652008724407
train loss: 2.2906875610351562
train per: 0.6086977299880526
train loss: 2.2238881587982178
train per: 0.597746190916614
train loss: 2.255229949951172
train per: 0.6022665047734685
train loss: 2.2551522254943848
train per: 0.5996838222378359
train loss: 2.2603824138641357
train per: 0.6047827860493575
train loss: 2.324492931365967
train per: 0.6173011120615911
train loss: 2.279575824737549
train per: 0.6050467062962513
train loss: 2.2366185188293457
train per: 0.6060709219858156
train loss: 2.3072447776794434
train per: 0.6106351778961179
train loss: 2.28816294670105
train per: 0.6074415389932035
train loss: 2.267028570175171
train per: 0.606479824067918
train loss: 2.2577528953552246
train per: 0.602854084909026
train loss: 2.2656219005584717
train per: 0.6010675330703179
train loss: 2.270580768585205
train per: 0.6045631430246815
train loss: 2.32319712638855
train per: 0.6143961899372848
train loss: 2.3197524547576904
train per: 0.6132118141933149
train loss: 2.267362356185913
train per: 0.6048165244556348
train loss: 2.255397081375122
train per: 0.6036395797598628
train loss: 2.2461938858032227
train per: 0.6022207396111323
train loss: 2.2264132499694824
train per: 0.5972186149741459
train loss: 2.247079849243164
train per: 0.6018753897069404
train loss: 2.245253801345825
train per: 0.6002131139416167
train loss: 2.3183047771453857
train per: 0.6108773286627391
train loss: 2.2370259761810303
train per: 0.6039347729296527
train loss: 2.243635892868042
train per: 0.6001910614236659
train loss: 2.234790563583374
train per: 0.5994406898158937
train loss: 2.246281147003174
train per: 0.6060803528910499
train loss: 2.2791473865509033
train per: 0.6028257456828885
train loss: 2.2727739810943604
train per: 0.6099652567142778
train loss: 2.2812678813934326
train per: 0.6083343607446677
train loss: 2.2419626712799072
train per: 0.6021230215145483
train loss: 2.2712769508361816
train per: 0.6034949087823505
train loss: 2.24566912651062
train per: 0.6035064902583598
train loss: 2.2243800163269043
train per: 0.5990155620742803
train loss: 2.261009454727173
train per: 0.6088724487118946
train loss: 2.243807077407837
train per: 0.6046412262664566
train loss: 2.3094937801361084
train per: 0.6059390596868661
train loss: 2.252084493637085
train per: 0.6080024846006522
train loss: 2.2833662033081055
train per: 0.6039995000624921
train loss: 2.274379253387451
train per: 0.6071068330499438
train loss: 2.3057923316955566
train per: 0.6089594132693483
train loss: 2.2752866744995117
train per: 0.6068768776350004
train loss: 2.3054606914520264
train per: 0.6150014794358418
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:   8%|▊         | 204/2703 [00:00<00:01, 2032.16it/s]


word -> phonemes:  15%|█▌        | 411/2703 [00:00<00:01, 2050.73it/s]


word -> phonemes:  23%|██▎       | 617/2703 [00:00<00:01, 2039.99it/s]


word -> phonemes:  30%|███       | 822/2703 [00:00<00:00, 2038.63it/s]


word -> phonemes:  38%|███▊      | 1033/2703 [00:00<00:00, 2061.31it/s]


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word -> phonemes:  61%|██████▏   | 1659/2703 [00:00<00:00, 2065.54it/s]


word -> phonemes:  69%|██████▉   | 1870/2703 [00:00<00:00, 2078.21it/s]


word -> phonemes:  77%|███████▋  | 2078/2703 [00:01<00:00, 2060.12it/s]


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word -> phonemes:  92%|█████████▏| 2494/2703 [00:01<00:00, 2040.49it/s]


word -> phonemes: 100%|█████████▉| 2699/2703 [00:01<00:00, 2000.33it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:01<00:00, 2042.50it/s]



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train:  99%|█████████▉| 3488/3515 [16:01<00:05,  4.81it/s]
overall:  87%|████████▋ | 3489/4000 [16:04<01:45,  4.86it/s]

train:  99%|█████████▉| 3489/3515 [16:01<00:05,  4.86it/s]
overall:  87%|████████▋ | 3490/4000 [16:05<01:44,  4.89it/s]

train:  99%|█████████▉| 3490/3515 [16:02<00:05,  4.89it/s]
overall:  87%|████████▋ | 3491/4000 [16:05<01:43,  4.92it/s]

train:  99%|█████████▉| 3491/3515 [16:02<00:04,  4.92it/s]
overall:  87%|████████▋ | 3492/4000 [16:05<01:43,  4.91it/s]

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train:  99%|█████████▉| 3495/3515 [16:03<00:04,  4.93it/s]
overall:  87%|████████▋ | 3496/4000 [16:06<01:40,  4.99it/s]

train:  99%|█████████▉| 3496/3515 [16:03<00:03,  4.99it/s]
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train:  99%|█████████▉| 3497/3515 [16:03<00:03,  5.71it/s]
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overall:  88%|████████▊ | 3515/4000 [16:09<01:31,  5.31it/s]

train: 100%|██████████| 3515/3515 [16:06<00:00,  5.31it/s]403-128339-0009 Failed!!!
403-128339-0009 Failed!!!
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403-128339-0009 Failed!!!
403-128339-0009 Failed!!!
/home/victor/glockenspiel/s3prl/data/LibriSpeech/train-clean-100/403/128339/403-128339-0009.flac WTF Failed!!!
403-128339-0009 Failed!!!

train: 100%|██████████| 3515/3515 [16:07<00:00,  3.63it/s]
dev loss: 2.5242919921875
dev per: 0.6472372528616025
train loss: 2.21563720703125
train per: 0.5959444235824258
train loss: 2.254779815673828
train per: 0.6026144861088368
train loss: 2.2390356063842773
train per: 0.604458722741433
train loss: 2.235053300857544
train per: 0.5957961590805988
train loss: 2.2686028480529785
train per: 0.6015575070419201
train loss: 2.2576816082000732
train per: 0.6073423377678481
train loss: 2.2317276000976562
train per: 0.6005137762554777
train loss: 2.2925209999084473
train per: 0.6060373189884969
train loss: 2.298259735107422
train per: 0.6110350322436073
train loss: 2.2349283695220947
train per: 0.599139365698255
train loss: 2.2587475776672363
train per: 0.6032203995273816
train loss: 2.303264617919922
train per: 0.606605262537985
train loss: 2.2167155742645264
train per: 0.5956472512265694
train loss: 2.229219675064087
train per: 0.5977771032292712
train loss: 2.2564327716827393
train per: 0.604896477283878
train loss: 2.264960289001465
train per: 0.5996216179252809
train loss: 2.2854628562927246
train per: 0.6038120080541827
train loss: 2.2450127601623535
train per: 0.6022096554613049
train loss: 2.2867207527160645
train per: 0.6132697174188106
train loss: 2.273972749710083
train per: 0.6097375427919361
train loss: 2.269695997238159
train per: 0.6085401419688549
train loss: 2.296090602874756
train per: 0.610259602168106
train loss: 2.327298402786255
train per: 0.6147895226952556
train loss: 2.2791290283203125
train per: 0.6112678147268409
train loss: 2.285520076751709
train per: 0.6049032806632183
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.


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

word -> phonemes:   5%|▍         | 166/3515 [00:00<00:02, 1654.15it/s]

word -> phonemes:   9%|▉         | 332/3515 [00:00<00:02, 1569.25it/s]

word -> phonemes:  14%|█▍        | 500/3515 [00:00<00:01, 1617.46it/s]

word -> phonemes:  19%|█▉        | 678/3515 [00:00<00:01, 1677.17it/s]

word -> phonemes:  24%|██▍       | 848/3515 [00:00<00:01, 1683.14it/s]

word -> phonemes:  29%|██▉       | 1026/3515 [00:00<00:01, 1714.29it/s]

word -> phonemes:  34%|███▍      | 1210/3515 [00:00<00:01, 1754.40it/s]

word -> phonemes:  40%|███▉      | 1392/3515 [00:00<00:01, 1774.00it/s]

word -> phonemes:  45%|████▍     | 1577/3515 [00:00<00:01, 1795.63it/s]

word -> phonemes:  50%|████▉     | 1757/3515 [00:01<00:01, 1756.96it/s]

word -> phonemes:  55%|█████▍    | 1933/3515 [00:01<00:00, 1733.80it/s]

word -> phonemes:  60%|██████    | 2123/3515 [00:01<00:00, 1779.71it/s]

word -> phonemes:  65%|██████▌   | 2302/3515 [00:01<00:00, 1759.51it/s]

word -> phonemes:  71%|███████   | 2479/3515 [00:01<00:00, 1687.33it/s]

word -> phonemes:  76%|███████▌  | 2658/3515 [00:01<00:00, 1715.48it/s]

word -> phonemes:  81%|████████  | 2837/3515 [00:01<00:00, 1734.74it/s]

word -> phonemes:  86%|████████▌ | 3011/3515 [00:01<00:00, 1701.06it/s]

word -> phonemes:  91%|█████████ | 3182/3515 [00:01<00:00, 1692.34it/s]

word -> phonemes:  95%|█████████▌| 3352/3515 [00:01<00:00, 1650.78it/s]
word -> phonemes: 100%|██████████| 3515/3515 [00:02<00:00, 1707.61it/s]


train:   0%|          | 0/3515 [00:00<?, ?it/s]
overall:  88%|████████▊ | 3516/4000 [16:15<13:19,  1.65s/it]

train:   0%|          | 1/3515 [00:01<1:41:01,  1.72s/it]
overall:  88%|████████▊ | 3517/4000 [16:15<09:34,  1.19s/it]

train:   0%|          | 2/3515 [00:01<45:25,  1.29it/s]  
overall:  88%|████████▊ | 3518/4000 [16:15<07:11,  1.12it/s]

train:   0%|          | 3/3515 [00:02<30:17,  1.93it/s]
overall:  88%|████████▊ | 3519/4000 [16:15<05:32,  1.45it/s]

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overall:  88%|████████▊ | 3520/4000 [16:15<04:20,  1.85it/s]

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overall:  88%|████████▊ | 3521/4000 [16:15<03:23,  2.35it/s]

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overall:  88%|████████▊ | 3523/4000 [16:16<02:26,  3.27it/s]

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overall:  88%|████████▊ | 3524/4000 [16:16<02:15,  3.50it/s]

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overall:  88%|████████▊ | 3525/4000 [16:16<02:00,  3.96it/s]

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overall:  88%|████████▊ | 3527/4000 [16:16<01:37,  4.85it/s]

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overall:  88%|████████▊ | 3528/4000 [16:17<01:51,  4.23it/s]

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overall:  88%|████████▊ | 3529/4000 [16:17<01:48,  4.35it/s]

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overall:  88%|████████▊ | 3530/4000 [16:17<01:40,  4.67it/s]

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overall:  88%|████████▊ | 3531/4000 [16:17<01:38,  4.78it/s]

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overall:  88%|████████▊ | 3532/4000 [16:18<01:38,  4.76it/s]

train:   0%|          | 17/3515 [00:04<11:52,  4.91it/s]
overall:  88%|████████▊ | 3533/4000 [16:18<01:32,  5.03it/s]

train:   1%|          | 18/3515 [00:04<11:19,  5.14it/s]
overall:  88%|████████▊ | 3534/4000 [16:18<01:33,  4.99it/s]

train:   1%|          | 19/3515 [00:05<11:29,  5.07it/s]
overall:  88%|████████▊ | 3535/4000 [16:18<01:34,  4.95it/s]

train:   1%|          | 20/3515 [00:05<11:38,  5.00it/s]
overall:  88%|████████▊ | 3536/4000 [16:18<01:32,  5.00it/s]

train:   1%|          | 21/3515 [00:05<11:32,  5.04it/s]
overall:  88%|████████▊ | 3538/4000 [16:19<01:19,  5.84it/s]

train:   1%|          | 23/3515 [00:05<09:55,  5.87it/s]
overall:  88%|████████▊ | 3539/4000 [16:19<01:23,  5.51it/s]

train:   1%|          | 24/3515 [00:06<10:31,  5.53it/s]
overall:  88%|████████▊ | 3540/4000 [16:19<01:48,  4.23it/s]

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overall:  89%|████████▊ | 3541/4000 [16:19<01:44,  4.39it/s]

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overall:  89%|████████▊ | 3542/4000 [16:20<01:39,  4.58it/s]

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overall:  89%|████████▊ | 3544/4000 [16:20<01:24,  5.39it/s]

train:   1%|          | 29/3515 [00:07<10:45,  5.40it/s]
overall:  89%|████████▊ | 3546/4000 [16:20<01:17,  5.83it/s]

train:   1%|          | 31/3515 [00:07<09:57,  5.83it/s]
overall:  89%|████████▊ | 3547/4000 [16:20<01:21,  5.57it/s]

train:   1%|          | 32/3515 [00:07<10:24,  5.58it/s]
overall:  89%|████████▊ | 3548/4000 [16:21<01:23,  5.41it/s]

train:   1%|          | 33/3515 [00:07<10:43,  5.41it/s]
overall:  89%|████████▊ | 3549/4000 [16:21<01:25,  5.30it/s]

train:   1%|          | 34/3515 [00:07<10:57,  5.30it/s]
overall:  89%|████████▉ | 3550/4000 [16:21<01:23,  5.41it/s]

train:   1%|          | 35/3515 [00:08<10:43,  5.41it/s]
overall:  89%|████████▉ | 3551/4000 [16:21<01:26,  5.17it/s]

train:   1%|          | 36/3515 [00:08<11:13,  5.17it/s]
overall:  89%|████████▉ | 3552/4000 [16:22<01:48,  4.14it/s]

train:   1%|          | 37/3515 [00:08<13:59,  4.14it/s]
overall:  89%|████████▉ | 3553/4000 [16:22<01:43,  4.33it/s]

train:   1%|          | 38/3515 [00:08<13:23,  4.33it/s]
overall:  89%|████████▉ | 3554/4000 [16:22<01:39,  4.47it/s]

train:   1%|          | 39/3515 [00:09<12:56,  4.48it/s]
overall:  89%|████████▉ | 3556/4000 [16:22<01:22,  5.39it/s]

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overall:  89%|████████▉ | 3557/4000 [16:22<01:23,  5.31it/s]

train:   1%|          | 42/3515 [00:09<10:53,  5.31it/s]
overall:  89%|████████▉ | 3558/4000 [16:23<01:24,  5.23it/s]

train:   1%|          | 43/3515 [00:09<11:03,  5.23it/s]
overall:  89%|████████▉ | 3559/4000 [16:23<01:15,  5.82it/s]

train:   1%|▏         | 44/3515 [00:09<09:55,  5.82it/s]
overall:  89%|████████▉ | 3560/4000 [16:23<01:20,  5.49it/s]

train:   1%|▏         | 45/3515 [00:10<10:32,  5.49it/s]
overall:  89%|████████▉ | 3561/4000 [16:23<01:22,  5.33it/s]

train:   1%|▏         | 46/3515 [00:10<10:51,  5.33it/s]
overall:  89%|████████▉ | 3562/4000 [16:23<01:24,  5.20it/s]

train:   1%|▏         | 47/3515 [00:10<11:06,  5.20it/s]
overall:  89%|████████▉ | 3563/4000 [16:23<01:15,  5.78it/s]

train:   1%|▏         | 48/3515 [00:10<09:59,  5.78it/s]
overall:  89%|████████▉ | 3564/4000 [16:24<01:44,  4.15it/s]

train:   1%|▏         | 49/3515 [00:11<13:54,  4.15it/s]
overall:  89%|████████▉ | 3565/4000 [16:24<01:27,  4.99it/s]

train:   1%|▏         | 50/3515 [00:11<11:34,  4.99it/s]
overall:  89%|████████▉ | 3566/4000 [16:24<01:26,  4.99it/s]

train:   1%|▏         | 51/3515 [00:11<11:34,  4.99it/s]
overall:  89%|████████▉ | 3567/4000 [16:24<01:24,  5.12it/s]

train:   1%|▏         | 52/3515 [00:11<11:15,  5.12it/s]
overall:  89%|████████▉ | 3569/4000 [16:25<01:12,  5.94it/s]

train:   2%|▏         | 54/3515 [00:11<09:42,  5.94it/s]
overall:  89%|████████▉ | 3570/4000 [16:25<01:15,  5.69it/s]

train:   2%|▏         | 55/3515 [00:12<10:08,  5.69it/s]
overall:  89%|████████▉ | 3571/4000 [16:25<01:18,  5.44it/s]

train:   2%|▏         | 56/3515 [00:12<10:36,  5.43it/s]
overall:  89%|████████▉ | 3572/4000 [16:25<01:22,  5.21it/s]

train:   2%|▏         | 57/3515 [00:12<11:04,  5.21it/s]
overall:  89%|████████▉ | 3573/4000 [16:25<01:23,  5.14it/s]

train:   2%|▏         | 58/3515 [00:12<11:12,  5.14it/s]
overall:  89%|████████▉ | 3574/4000 [16:26<01:24,  5.07it/s]

train:   2%|▏         | 59/3515 [00:12<11:21,  5.07it/s]
overall:  89%|████████▉ | 3575/4000 [16:26<01:23,  5.10it/s]

train:   2%|▏         | 60/3515 [00:13<11:17,  5.10it/s]
overall:  89%|████████▉ | 3576/4000 [16:26<01:47,  3.96it/s]

train:   2%|▏         | 61/3515 [00:13<14:32,  3.96it/s]
overall:  89%|████████▉ | 3577/4000 [16:26<01:38,  4.29it/s]

train:   2%|▏         | 62/3515 [00:13<13:25,  4.29it/s]
overall:  89%|████████▉ | 3578/4000 [16:27<01:34,  4.45it/s]

train:   2%|▏         | 63/3515 [00:13<12:54,  4.45it/s]
overall:  89%|████████▉ | 3579/4000 [16:27<01:32,  4.56it/s]

train:   2%|▏         | 64/3515 [00:14<12:36,  4.56it/s]
overall:  90%|████████▉ | 3580/4000 [16:27<01:31,  4.57it/s]

train:   2%|▏         | 65/3515 [00:14<12:34,  4.57it/s]
overall:  90%|████████▉ | 3581/4000 [16:27<01:29,  4.68it/s]

train:   2%|▏         | 66/3515 [00:14<12:16,  4.68it/s]
overall:  90%|████████▉ | 3582/4000 [16:27<01:29,  4.69it/s]

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overall:  90%|████████▉ | 3583/4000 [16:28<01:27,  4.79it/s]

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overall:  90%|█████████ | 3613/4000 [16:34<01:27,  4.45it/s]

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overall:  90%|█████████ | 3615/4000 [16:34<01:21,  4.70it/s]

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overall:  90%|█████████ | 3620/4000 [16:35<01:19,  4.79it/s]

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overall:  91%|█████████ | 3621/4000 [16:35<01:19,  4.78it/s]

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overall:  91%|█████████ | 3622/4000 [16:35<01:16,  4.92it/s]

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overall:  91%|█████████ | 3623/4000 [16:36<01:17,  4.89it/s]

train:   3%|▎         | 108/3515 [00:22<11:36,  4.89it/s]
overall:  91%|█████████ | 3624/4000 [16:36<01:37,  3.86it/s]

train:   3%|▎         | 109/3515 [00:23<14:42,  3.86it/s]
overall:  91%|█████████ | 3625/4000 [16:36<01:31,  4.12it/s]

train:   3%|▎         | 110/3515 [00:23<13:46,  4.12it/s]
overall:  91%|█████████ | 3626/4000 [16:36<01:23,  4.48it/s]

train:   3%|▎         | 111/3515 [00:23<12:40,  4.48it/s]
overall:  91%|█████████ | 3627/4000 [16:37<01:21,  4.60it/s]

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overall:  91%|█████████ | 3629/4000 [16:37<01:08,  5.45it/s]

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overall:  91%|█████████ | 3630/4000 [16:37<01:09,  5.35it/s]

train:   3%|▎         | 115/3515 [00:24<10:35,  5.35it/s]
overall:  91%|█████████ | 3631/4000 [16:37<01:08,  5.37it/s]

train:   3%|▎         | 116/3515 [00:24<10:32,  5.37it/s]
overall:  91%|█████████ | 3632/4000 [16:37<01:09,  5.28it/s]

train:   3%|▎         | 117/3515 [00:24<10:43,  5.28it/s]
overall:  91%|█████████ | 3633/4000 [16:38<01:10,  5.17it/s]

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overall:  91%|█████████ | 3634/4000 [16:38<01:11,  5.11it/s]

train:   3%|▎         | 119/3515 [00:25<11:04,  5.11it/s]
overall:  91%|█████████ | 3635/4000 [16:38<01:12,  5.00it/s]

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overall:  91%|█████████ | 3636/4000 [16:38<01:33,  3.89it/s]

train:   3%|▎         | 121/3515 [00:25<14:32,  3.89it/s]
overall:  91%|█████████ | 3637/4000 [16:39<01:28,  4.11it/s]

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overall:  91%|█████████ | 3638/4000 [16:39<01:22,  4.38it/s]

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overall:  91%|█████████ | 3639/4000 [16:39<01:20,  4.48it/s]

train:   4%|▎         | 124/3515 [00:26<12:36,  4.48it/s]
overall:  91%|█████████ | 3640/4000 [16:39<01:19,  4.52it/s]

train:   4%|▎         | 125/3515 [00:26<12:29,  4.52it/s]
overall:  91%|█████████ | 3641/4000 [16:40<01:17,  4.63it/s]

train:   4%|▎         | 126/3515 [00:26<12:11,  4.63it/s]
overall:  91%|█████████ | 3642/4000 [16:40<01:16,  4.66it/s]

train:   4%|▎         | 127/3515 [00:26<12:07,  4.66it/s]
overall:  91%|█████████ | 3643/4000 [16:40<01:15,  4.71it/s]

train:   4%|▎         | 128/3515 [00:27<11:59,  4.71it/s]
overall:  91%|█████████ | 3644/4000 [16:40<01:13,  4.84it/s]

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overall:  91%|█████████ | 3645/4000 [16:40<01:12,  4.89it/s]

train:   4%|▎         | 130/3515 [00:27<11:31,  4.89it/s]
overall:  91%|█████████ | 3646/4000 [16:41<01:12,  4.89it/s]

train:   4%|▎         | 131/3515 [00:27<11:31,  4.89it/s]
overall:  91%|█████████ | 3647/4000 [16:41<01:05,  5.42it/s]

train:   4%|▍         | 132/3515 [00:27<10:24,  5.42it/s]
overall:  91%|█████████ | 3648/4000 [16:41<01:16,  4.61it/s]

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overall:  91%|█████████ | 3649/4000 [16:41<01:14,  4.71it/s]

train:   4%|▍         | 134/3515 [00:28<11:57,  4.71it/s]
overall:  91%|█████████▏| 3650/4000 [16:41<01:08,  5.09it/s]

train:   4%|▍         | 135/3515 [00:28<11:03,  5.09it/s]
overall:  91%|█████████▏| 3651/4000 [16:41<01:00,  5.73it/s]

train:   4%|▍         | 136/3515 [00:28<09:49,  5.73it/s]
overall:  91%|█████████▏| 3652/4000 [16:42<01:03,  5.51it/s]

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overall:  91%|█████████▏| 3653/4000 [16:42<01:06,  5.24it/s]

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overall:  91%|█████████▏| 3655/4000 [16:42<00:57,  6.05it/s]

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overall:  91%|█████████▏| 3656/4000 [16:42<01:01,  5.63it/s]

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overall:  91%|█████████▏| 3657/4000 [16:43<01:03,  5.39it/s]

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overall:  91%|█████████▏| 3658/4000 [16:43<01:04,  5.32it/s]

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overall:  91%|█████████▏| 3659/4000 [16:43<01:04,  5.30it/s]

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overall:  92%|█████████▏| 3660/4000 [16:43<01:21,  4.18it/s]

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overall:  92%|█████████▏| 3661/4000 [16:44<01:16,  4.43it/s]

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overall:  92%|█████████▏| 3662/4000 [16:44<01:13,  4.60it/s]

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overall:  92%|█████████▏| 3664/4000 [16:44<01:01,  5.48it/s]

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overall:  92%|█████████▏| 3665/4000 [16:44<01:03,  5.29it/s]

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overall:  92%|█████████▏| 3666/4000 [16:44<01:04,  5.16it/s]

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overall:  92%|█████████▏| 3668/4000 [16:45<00:46,  7.17it/s]

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overall:  92%|█████████▏| 3670/4000 [16:45<00:55,  6.00it/s]

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overall:  92%|█████████▏| 3674/4000 [16:46<01:01,  5.26it/s]

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overall:  92%|█████████▏| 3675/4000 [16:46<01:02,  5.18it/s]

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overall:  92%|█████████▏| 3685/4000 [16:48<01:07,  4.66it/s]

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overall:  92%|█████████▏| 3686/4000 [16:48<01:05,  4.81it/s]

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overall:  92%|█████████▏| 3687/4000 [16:48<01:00,  5.18it/s]

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overall:  92%|█████████▏| 3699/4000 [16:51<00:55,  5.40it/s]

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overall:  93%|█████████▎| 3701/4000 [16:51<00:57,  5.20it/s]

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overall:  93%|█████████▎| 3703/4000 [16:52<00:57,  5.15it/s]

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overall:  93%|█████████▎| 3704/4000 [16:52<00:57,  5.16it/s]

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overall:  93%|█████████▎| 3705/4000 [16:52<00:55,  5.35it/s]

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overall: 100%|█████████▉| 3999/4000 [17:52<00:00,  4.87it/s]

train:  14%|█▍        | 484/3515 [01:39<10:22,  4.87it/s]train loss: 2.2677645683288574
train per: 0.6027445817297954
train loss: 2.2536511421203613
train per: 0.6078157304679538
train loss: 2.247332811355591
train per: 0.599979634956597
train loss: 2.3053221702575684
train per: 0.6076595744680852
train loss: 2.275050640106201
train per: 0.6107208966199255
train loss: 2.2648987770080566
train per: 0.604321722734941
train loss: 2.2740638256073
train per: 0.602065404475043
train loss: 2.250304698944092
train per: 0.6020470672316096
train loss: 2.26884126663208
train per: 0.616746484613817
train loss: 2.275223970413208
train per: 0.6100211678455264
train loss: 2.2803876399993896
train per: 0.6063090497384243
train loss: 2.297562837600708
train per: 0.6080767514502454
train loss: 2.2479400634765625
train per: 0.5999495904221802
train loss: 2.281398296356201
train per: 0.6062805084966979
train loss: 2.311377763748169
train per: 0.6126809451572263
train loss: 2.2574970722198486
train per: 0.6024830527839135
train loss: 2.2387778759002686
train per: 0.6030983695384464
train loss: 2.254873275756836
train per: 0.6009411988401389
train loss: 2.276036024093628
train per: 0.6082301277939508
train loss: 2.247464418411255
train per: 0.5981072555205047
train loss: 2.259629011154175
train per: 0.6078805453805454
train loss: 2.2591562271118164
train per: 0.600529450694904
train loss: 2.280061721801758
train per: 0.6039894187459784
train loss: 2.2638981342315674
train per: 0.6053053880567983
train loss: 2.2479350566864014
train per: 0.5981324614851142
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:   8%|▊         | 209/2703 [00:00<00:01, 2083.23it/s]


word -> phonemes:  16%|█▌        | 420/2703 [00:00<00:01, 2094.27it/s]


word -> phonemes:  23%|██▎       | 630/2703 [00:00<00:00, 2083.33it/s]


word -> phonemes:  31%|███       | 839/2703 [00:00<00:00, 2076.11it/s]


word -> phonemes:  39%|███▉      | 1051/2703 [00:00<00:00, 2090.96it/s]


word -> phonemes:  47%|████▋     | 1261/2703 [00:00<00:00, 2085.01it/s]


word -> phonemes:  54%|█████▍    | 1472/2703 [00:00<00:00, 2092.32it/s]


word -> phonemes:  62%|██████▏   | 1682/2703 [00:00<00:00, 2092.68it/s]


word -> phonemes:  70%|███████   | 1897/2703 [00:00<00:00, 2109.50it/s]


word -> phonemes:  78%|███████▊  | 2108/2703 [00:01<00:00, 2081.06it/s]


word -> phonemes:  86%|████████▌ | 2317/2703 [00:01<00:00, 2068.80it/s]


word -> phonemes:  93%|█████████▎| 2524/2703 [00:01<00:00, 2050.61it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:01<00:00, 2068.92it/s]



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overall: 100%|█████████▉| 3999/4000 [19:11<00:00,  4.87it/s]

train:  14%|█▍        | 484/3515 [02:57<10:22,  4.87it/s]
                                                            

                                                         

overall: 100%|█████████▉| 3999/4000 [19:11<00:00,  4.87it/s]

train:  14%|█▍        | 484/3515 [02:57<10:22,  4.87it/s]
overall: 100%|██████████| 4000/4000 [19:11<00:00, 21.45s/it]

train:  14%|█▍        | 485/3515 [02:57<18:03:04, 21.45s/it]403-128339-0009 Failed!!!

train:  14%|█▍        | 485/3515 [02:58<18:33,  2.72it/s]   

overall: 100%|██████████| 4000/4000 [19:11<00:00,  3.47it/s]
dev loss: 2.5509068965911865
dev per: 0.6454786680541102
[Runner] - Save the checkpoint to:
1. result/downstream/grid/states-4000.ckpt