/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")
2023-10-05 17:13:19 | 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_victor_no_cqt {'model_config': None, 'refresh': False}
Loading model from Local mert_25hz_victor_no_cqt
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]

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word -> phonemes:  28%|██▊       | 967/3515 [00:00<00:01, 2413.75it/s]

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word -> phonemes:  91%|█████████ | 3188/3515 [00:01<00:00, 1957.05it/s]

word -> phonemes:  97%|█████████▋| 3413/3515 [00:01<00:00, 2036.69it/s]
word -> phonemes: 100%|██████████| 3515/3515 [00:01<00:00, 2084.72it/s]


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train:   4%|▍         | 158/3515 [00:36<12:11,  4.59it/s]
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train:   5%|▍         | 159/3515 [00:36<12:37,  4.43it/s]
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train:   5%|▍         | 160/3515 [00:36<12:44,  4.39it/s]
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train:   5%|▌         | 181/3515 [00:41<12:24,  4.48it/s]
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overall:  11%|█         | 433/4000 [01:44<14:36,  4.07it/s]

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overall:  16%|█▌        | 649/4000 [02:38<14:27,  3.86it/s]

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overall:  16%|█▋        | 652/4000 [02:39<14:27,  3.86it/s]

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overall:  16%|█▋        | 653/4000 [02:39<13:31,  4.12it/s]

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overall:  16%|█▋        | 654/4000 [02:39<13:06,  4.26it/s]

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overall:  16%|█▋        | 655/4000 [02:39<13:11,  4.22it/s]

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overall:  16%|█▋        | 656/4000 [02:39<12:54,  4.32it/s]

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overall:  16%|█▋        | 657/4000 [02:40<12:30,  4.45it/s]

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overall:  17%|█▋        | 668/4000 [02:42<12:26,  4.46it/s]

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overall:  17%|█▋        | 673/4000 [02:43<13:02,  4.25it/s]

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overall:  17%|█▋        | 676/4000 [02:44<11:46,  4.70it/s]

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overall:  17%|█▋        | 681/4000 [02:45<12:30,  4.42it/s]

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overall:  17%|█▋        | 682/4000 [02:45<12:21,  4.48it/s]

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overall:  17%|█▋        | 683/4000 [02:45<11:41,  4.73it/s]

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overall:  17%|█▋        | 687/4000 [02:46<13:06,  4.21it/s]

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overall:  17%|█▋        | 688/4000 [02:47<12:39,  4.36it/s]

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overall:  17%|█▋        | 689/4000 [02:47<12:25,  4.44it/s]

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overall:  17%|█▋        | 690/4000 [02:47<10:42,  5.15it/s]

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overall:  17%|█▋        | 691/4000 [02:47<11:19,  4.87it/s]

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overall:  17%|█▋        | 692/4000 [02:48<12:44,  4.33it/s]

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overall:  17%|█▋        | 694/4000 [02:48<13:18,  4.14it/s]

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overall:  18%|█▊        | 700/4000 [02:49<11:42,  4.70it/s]

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overall:  18%|█▊        | 702/4000 [02:50<11:22,  4.84it/s]

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overall:  18%|█▊        | 703/4000 [02:50<12:36,  4.36it/s]

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overall:  18%|█▊        | 704/4000 [02:50<10:33,  5.20it/s]

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overall:  18%|█▊        | 705/4000 [02:50<11:17,  4.87it/s]

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overall:  18%|█▊        | 707/4000 [02:51<11:47,  4.65it/s]

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overall:  24%|██▍       | 978/4000 [03:52<10:57,  4.59it/s]

train:  28%|██▊       | 978/3515 [03:49<09:12,  4.59it/s]
overall:  24%|██▍       | 979/4000 [03:52<11:54,  4.23it/s]

train:  28%|██▊       | 979/3515 [03:49<09:59,  4.23it/s]
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train:  28%|██▊       | 980/3515 [03:49<09:55,  4.25it/s]
overall:  25%|██▍       | 981/4000 [03:52<11:34,  4.35it/s]

train:  28%|██▊       | 981/3515 [03:49<09:42,  4.35it/s]
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train:  28%|██▊       | 982/3515 [03:50<09:27,  4.46it/s]
overall:  25%|██▍       | 983/4000 [03:53<11:15,  4.47it/s]

train:  28%|██▊       | 983/3515 [03:50<09:27,  4.47it/s]
overall:  25%|██▍       | 984/4000 [03:53<11:13,  4.48it/s]

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train:  28%|██▊       | 986/3515 [03:50<09:05,  4.63it/s]
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train:  28%|██▊       | 997/3515 [03:53<11:41,  3.59it/s]
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overall:  25%|██▍       | 999/4000 [03:57<11:59,  4.17it/s]

train:  28%|██▊       | 999/3515 [03:54<10:03,  4.17it/s]train loss: 4.149642467498779
train per: 0.8479279954997188
train loss: 2.6563522815704346
train per: 0.6817984194777628
train loss: 2.5106682777404785
train per: 0.660488539314176
train loss: 2.451070785522461
train per: 0.6376785759759607
train loss: 2.4428324699401855
train per: 0.6364628314064169
train loss: 2.365992307662964
train per: 0.6240387200860447
train loss: 2.3360679149627686
train per: 0.6192311445019026
train loss: 2.392350912094116
train per: 0.6215584139470607
train loss: 2.292881965637207
train per: 0.6060532334192983
train loss: 2.28446364402771
train per: 0.6064127158125514
train loss: 2.2814064025878906
train per: 0.6097522445433243
train loss: 2.2840442657470703
train per: 0.605589138836587
train loss: 2.3396096229553223
train per: 0.617942076760066
train loss: 2.2877352237701416
train per: 0.598530827976977
train loss: 2.2373604774475098
train per: 0.5964775964775965
train loss: 2.2573130130767822
train per: 0.604118194509074
train loss: 2.239079713821411
train per: 0.6006731946144431
train loss: 2.242988109588623
train per: 0.6018065382141559
train loss: 2.259232521057129
train per: 0.59873295689299
train loss: 2.2154695987701416
train per: 0.5908061024117618
train loss: 2.203805923461914
train per: 0.5894350045623813
train loss: 2.243511199951172
train per: 0.5964740450538688
train loss: 2.2609829902648926
train per: 0.5973472704115245
train loss: 2.2589380741119385
train per: 0.5949801849405548
train loss: 2.2140846252441406
train per: 0.5864951625128182
train loss: 2.1761090755462646
train per: 0.5812265978050355
train loss: 2.2205491065979004
train per: 0.5881309148264984
train loss: 2.186340570449829
train per: 0.5846262501993484
train loss: 2.188323736190796
train per: 0.5811199414409705
train loss: 2.2123794555664062
train per: 0.5945502532277623
train loss: 2.2422938346862793
train per: 0.5922616903235104
train loss: 2.1864736080169678
train per: 0.5855092343114682
train loss: 2.2245116233825684
train per: 0.5917956831280371
train loss: 2.2247250080108643
train per: 0.5947455953432774
train loss: 2.186558723449707
train per: 0.586163659161533
train loss: 2.20007061958313
train per: 0.5909914649830469
train loss: 2.251987934112549
train per: 0.5904165493948775
train loss: 2.2344913482666016
train per: 0.589178115208484
train loss: 2.2157559394836426
train per: 0.5914631149555217
train loss: 2.208549976348877
train per: 0.587676064562846
train loss: 2.1780667304992676
train per: 0.580857823669579
train loss: 2.1922855377197266
train per: 0.584138948058332
train loss: 2.1949288845062256
train per: 0.582963438101347
train loss: 2.2318482398986816
train per: 0.5914706551123013
train loss: 2.181788682937622
train per: 0.5812287119969723
train loss: 2.183220863342285
train per: 0.5804526748971194
train loss: 2.2122979164123535
train per: 0.5889607032057911
train loss: 2.1969282627105713
train per: 0.5889149860964876
train loss: 2.1923561096191406
train per: 0.5866592111087813
train loss: 2.152042865753174
train per: 0.5769943424660918
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:   7%|▋         | 201/2703 [00:00<00:01, 2006.99it/s]


word -> phonemes:  17%|█▋        | 456/2703 [00:00<00:00, 2322.69it/s]


word -> phonemes:  26%|██▌       | 708/2703 [00:00<00:00, 2409.13it/s]


word -> phonemes:  37%|███▋      | 1004/2703 [00:00<00:00, 2527.08it/s]


word -> phonemes:  47%|████▋     | 1257/2703 [00:00<00:00, 2345.00it/s]


word -> phonemes:  56%|█████▋    | 1524/2703 [00:00<00:00, 2440.95it/s]


word -> phonemes:  65%|██████▌   | 1770/2703 [00:00<00:00, 2442.42it/s]


word -> phonemes:  76%|███████▋  | 2065/2703 [00:00<00:00, 2597.24it/s]


word -> phonemes:  86%|████████▌ | 2326/2703 [00:00<00:00, 2491.67it/s]


word -> phonemes:  95%|█████████▌| 2577/2703 [00:01<00:00, 2496.23it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:01<00:00, 2444.82it/s]



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train:  54%|█████▍    | 1906/3515 [09:21<05:45,  4.66it/s]
overall:  48%|████▊     | 1907/4000 [09:24<06:51,  5.09it/s]

train:  54%|█████▍    | 1907/3515 [09:21<05:15,  5.09it/s]
overall:  48%|████▊     | 1908/4000 [09:24<07:43,  4.51it/s]

train:  54%|█████▍    | 1908/3515 [09:21<05:56,  4.51it/s]
overall:  48%|████▊     | 1909/4000 [09:25<07:52,  4.43it/s]

train:  54%|█████▍    | 1909/3515 [09:22<06:02,  4.43it/s]
overall:  48%|████▊     | 1910/4000 [09:25<08:36,  4.05it/s]

train:  54%|█████▍    | 1910/3515 [09:22<06:36,  4.05it/s]
overall:  48%|████▊     | 1911/4000 [09:25<07:19,  4.75it/s]

train:  54%|█████▍    | 1911/3515 [09:22<05:37,  4.75it/s]
overall:  48%|████▊     | 1912/4000 [09:25<06:17,  5.53it/s]

train:  54%|█████▍    | 1912/3515 [09:22<04:50,  5.52it/s]
overall:  48%|████▊     | 1913/4000 [09:25<07:18,  4.76it/s]

train:  54%|█████▍    | 1913/3515 [09:23<05:36,  4.76it/s]
overall:  48%|████▊     | 1914/4000 [09:26<07:11,  4.83it/s]

train:  54%|█████▍    | 1914/3515 [09:23<05:31,  4.83it/s]
overall:  48%|████▊     | 1915/4000 [09:26<07:23,  4.70it/s]

train:  54%|█████▍    | 1915/3515 [09:23<05:40,  4.70it/s]
overall:  48%|████▊     | 1916/4000 [09:26<07:04,  4.91it/s]

train:  55%|█████▍    | 1916/3515 [09:23<05:25,  4.91it/s]
overall:  48%|████▊     | 1917/4000 [09:26<07:30,  4.62it/s]

train:  55%|█████▍    | 1917/3515 [09:23<05:45,  4.62it/s]
overall:  48%|████▊     | 1918/4000 [09:27<07:24,  4.69it/s]

train:  55%|█████▍    | 1918/3515 [09:24<05:40,  4.69it/s]
overall:  48%|████▊     | 1919/4000 [09:27<07:38,  4.54it/s]

train:  55%|█████▍    | 1919/3515 [09:24<05:51,  4.54it/s]
overall:  48%|████▊     | 1920/4000 [09:27<07:43,  4.49it/s]

train:  55%|█████▍    | 1920/3515 [09:24<05:55,  4.49it/s]
overall:  48%|████▊     | 1921/4000 [09:27<07:50,  4.41it/s]

train:  55%|█████▍    | 1921/3515 [09:24<06:01,  4.41it/s]
overall:  48%|████▊     | 1922/4000 [09:27<07:52,  4.40it/s]

train:  55%|█████▍    | 1922/3515 [09:25<06:01,  4.40it/s]
overall:  48%|████▊     | 1923/4000 [09:28<07:59,  4.33it/s]

train:  55%|█████▍    | 1923/3515 [09:25<06:07,  4.33it/s]
overall:  48%|████▊     | 1924/4000 [09:28<08:13,  4.20it/s]

train:  55%|█████▍    | 1924/3515 [09:25<06:18,  4.20it/s]
overall:  48%|████▊     | 1925/4000 [09:28<07:33,  4.58it/s]

train:  55%|█████▍    | 1925/3515 [09:25<05:47,  4.58it/s]
overall:  48%|████▊     | 1926/4000 [09:28<08:41,  3.98it/s]

train:  55%|█████▍    | 1926/3515 [09:26<06:39,  3.98it/s]
overall:  48%|████▊     | 1927/4000 [09:29<08:22,  4.12it/s]

train:  55%|█████▍    | 1927/3515 [09:26<06:25,  4.12it/s]
overall:  48%|████▊     | 1928/4000 [09:29<07:06,  4.85it/s]

train:  55%|█████▍    | 1928/3515 [09:26<05:26,  4.85it/s]
overall:  48%|████▊     | 1929/4000 [09:29<07:31,  4.59it/s]

train:  55%|█████▍    | 1929/3515 [09:26<05:45,  4.59it/s]
overall:  48%|████▊     | 1930/4000 [09:29<07:43,  4.46it/s]

train:  55%|█████▍    | 1930/3515 [09:26<05:55,  4.46it/s]
overall:  48%|████▊     | 1931/4000 [09:30<07:53,  4.37it/s]

train:  55%|█████▍    | 1931/3515 [09:27<06:02,  4.37it/s]
overall:  48%|████▊     | 1932/4000 [09:30<08:30,  4.05it/s]

train:  55%|█████▍    | 1932/3515 [09:27<06:30,  4.05it/s]
overall:  48%|████▊     | 1933/4000 [09:30<08:25,  4.09it/s]

train:  55%|█████▍    | 1933/3515 [09:27<06:26,  4.09it/s]
overall:  48%|████▊     | 1934/4000 [09:30<08:59,  3.83it/s]

train:  55%|█████▌    | 1934/3515 [09:27<06:53,  3.83it/s]
overall:  48%|████▊     | 1935/4000 [09:31<08:44,  3.94it/s]

train:  55%|█████▌    | 1935/3515 [09:28<06:41,  3.94it/s]
overall:  48%|████▊     | 1936/4000 [09:31<07:28,  4.60it/s]

train:  55%|█████▌    | 1936/3515 [09:28<05:43,  4.60it/s]
overall:  48%|████▊     | 1937/4000 [09:31<07:56,  4.33it/s]

train:  55%|█████▌    | 1937/3515 [09:28<06:04,  4.33it/s]
overall:  48%|████▊     | 1938/4000 [09:31<07:49,  4.39it/s]

train:  55%|█████▌    | 1938/3515 [09:28<05:58,  4.39it/s]
overall:  48%|████▊     | 1939/4000 [09:31<07:54,  4.34it/s]

train:  55%|█████▌    | 1939/3515 [09:28<06:02,  4.34it/s]
overall:  48%|████▊     | 1940/4000 [09:32<08:03,  4.26it/s]

train:  55%|█████▌    | 1940/3515 [09:29<06:09,  4.26it/s]
overall:  49%|████▊     | 1941/4000 [09:32<07:54,  4.34it/s]

train:  55%|█████▌    | 1941/3515 [09:29<06:02,  4.34it/s]
overall:  49%|████▊     | 1942/4000 [09:32<07:51,  4.37it/s]

train:  55%|█████▌    | 1942/3515 [09:29<06:00,  4.37it/s]
overall:  49%|████▊     | 1943/4000 [09:32<07:45,  4.42it/s]

train:  55%|█████▌    | 1943/3515 [09:29<05:55,  4.42it/s]
overall:  49%|████▊     | 1944/4000 [09:32<06:33,  5.22it/s]

train:  55%|█████▌    | 1944/3515 [09:30<05:00,  5.22it/s]
overall:  49%|████▊     | 1945/4000 [09:33<07:45,  4.41it/s]

train:  55%|█████▌    | 1945/3515 [09:30<05:55,  4.41it/s]
overall:  49%|████▊     | 1946/4000 [09:33<07:54,  4.33it/s]

train:  55%|█████▌    | 1946/3515 [09:30<06:02,  4.33it/s]
overall:  49%|████▊     | 1948/4000 [09:33<06:46,  5.04it/s]

train:  55%|█████▌    | 1948/3515 [09:30<05:10,  5.04it/s]
overall:  49%|████▊     | 1949/4000 [09:34<07:05,  4.82it/s]

train:  55%|█████▌    | 1949/3515 [09:31<05:24,  4.82it/s]
overall:  49%|████▉     | 1950/4000 [09:34<08:01,  4.26it/s]

train:  55%|█████▌    | 1950/3515 [09:31<06:07,  4.26it/s]
overall:  49%|████▉     | 1951/4000 [09:34<08:04,  4.23it/s]

train:  56%|█████▌    | 1951/3515 [09:31<06:09,  4.23it/s]
overall:  49%|████▉     | 1952/4000 [09:34<08:18,  4.11it/s]

train:  56%|█████▌    | 1952/3515 [09:31<06:20,  4.11it/s]
overall:  49%|████▉     | 1953/4000 [09:35<08:20,  4.09it/s]

train:  56%|█████▌    | 1953/3515 [09:32<06:22,  4.09it/s]
overall:  49%|████▉     | 1954/4000 [09:35<08:20,  4.09it/s]

train:  56%|█████▌    | 1954/3515 [09:32<06:21,  4.09it/s]
overall:  49%|████▉     | 1955/4000 [09:35<07:57,  4.28it/s]

train:  56%|█████▌    | 1955/3515 [09:32<06:04,  4.28it/s]
overall:  49%|████▉     | 1956/4000 [09:35<08:10,  4.17it/s]

train:  56%|█████▌    | 1956/3515 [09:32<06:14,  4.17it/s]
overall:  49%|████▉     | 1957/4000 [09:36<08:03,  4.22it/s]

train:  56%|█████▌    | 1957/3515 [09:33<06:08,  4.22it/s]
overall:  49%|████▉     | 1958/4000 [09:36<08:19,  4.09it/s]

train:  56%|█████▌    | 1958/3515 [09:33<06:21,  4.09it/s]
overall:  49%|████▉     | 1959/4000 [09:36<08:09,  4.17it/s]

train:  56%|█████▌    | 1959/3515 [09:33<06:13,  4.17it/s]
overall:  49%|████▉     | 1960/4000 [09:36<08:03,  4.22it/s]

train:  56%|█████▌    | 1960/3515 [09:33<06:08,  4.22it/s]
overall:  49%|████▉     | 1961/4000 [09:37<08:18,  4.09it/s]

train:  56%|█████▌    | 1961/3515 [09:34<06:19,  4.09it/s]
overall:  49%|████▉     | 1962/4000 [09:37<08:23,  4.05it/s]

train:  56%|█████▌    | 1962/3515 [09:34<06:23,  4.05it/s]
overall:  49%|████▉     | 1963/4000 [09:37<08:15,  4.11it/s]

train:  56%|█████▌    | 1963/3515 [09:34<06:17,  4.11it/s]
overall:  49%|████▉     | 1964/4000 [09:37<08:09,  4.16it/s]

train:  56%|█████▌    | 1964/3515 [09:34<06:12,  4.16it/s]
overall:  49%|████▉     | 1965/4000 [09:38<08:17,  4.09it/s]

train:  56%|█████▌    | 1965/3515 [09:35<06:19,  4.09it/s]
overall:  49%|████▉     | 1966/4000 [09:38<07:53,  4.30it/s]

train:  56%|█████▌    | 1966/3515 [09:35<06:00,  4.30it/s]
overall:  49%|████▉     | 1967/4000 [09:38<07:32,  4.49it/s]

train:  56%|█████▌    | 1967/3515 [09:35<05:44,  4.49it/s]
overall:  49%|████▉     | 1968/4000 [09:38<07:13,  4.69it/s]

train:  56%|█████▌    | 1968/3515 [09:35<05:29,  4.69it/s]
overall:  49%|████▉     | 1969/4000 [09:38<08:10,  4.14it/s]

train:  56%|█████▌    | 1969/3515 [09:35<06:13,  4.14it/s]
overall:  49%|████▉     | 1970/4000 [09:39<08:13,  4.11it/s]

train:  56%|█████▌    | 1970/3515 [09:36<06:15,  4.11it/s]
overall:  49%|████▉     | 1971/4000 [09:39<08:06,  4.17it/s]

train:  56%|█████▌    | 1971/3515 [09:36<06:10,  4.17it/s]
overall:  49%|████▉     | 1972/4000 [09:39<08:01,  4.21it/s]

train:  56%|█████▌    | 1972/3515 [09:36<06:06,  4.21it/s]
overall:  49%|████▉     | 1973/4000 [09:39<07:55,  4.26it/s]

train:  56%|█████▌    | 1973/3515 [09:36<06:01,  4.26it/s]
overall:  49%|████▉     | 1974/4000 [09:40<08:37,  3.92it/s]

train:  56%|█████▌    | 1974/3515 [09:37<06:33,  3.92it/s]
overall:  49%|████▉     | 1975/4000 [09:40<08:18,  4.06it/s]

train:  56%|█████▌    | 1975/3515 [09:37<06:19,  4.06it/s]
overall:  49%|████▉     | 1976/4000 [09:40<08:28,  3.98it/s]

train:  56%|█████▌    | 1976/3515 [09:37<06:26,  3.98it/s]
overall:  49%|████▉     | 1977/4000 [09:40<08:29,  3.97it/s]

train:  56%|█████▌    | 1977/3515 [09:37<06:27,  3.97it/s]
overall:  49%|████▉     | 1978/4000 [09:41<08:06,  4.16it/s]

train:  56%|█████▋    | 1978/3515 [09:38<06:09,  4.16it/s]
overall:  49%|████▉     | 1979/4000 [09:41<07:21,  4.58it/s]

train:  56%|█████▋    | 1979/3515 [09:38<05:35,  4.58it/s]
overall:  50%|████▉     | 1980/4000 [09:41<08:03,  4.18it/s]

train:  56%|█████▋    | 1980/3515 [09:38<06:07,  4.18it/s]
overall:  50%|████▉     | 1981/4000 [09:41<07:23,  4.55it/s]

train:  56%|█████▋    | 1981/3515 [09:38<05:37,  4.55it/s]
overall:  50%|████▉     | 1982/4000 [09:42<08:00,  4.20it/s]

train:  56%|█████▋    | 1982/3515 [09:39<06:04,  4.20it/s]
overall:  50%|████▉     | 1983/4000 [09:42<06:38,  5.06it/s]

train:  56%|█████▋    | 1983/3515 [09:39<05:02,  5.06it/s]
overall:  50%|████▉     | 1984/4000 [09:42<07:06,  4.73it/s]

train:  56%|█████▋    | 1984/3515 [09:39<05:23,  4.73it/s]
overall:  50%|████▉     | 1985/4000 [09:42<07:41,  4.37it/s]

train:  56%|█████▋    | 1985/3515 [09:39<05:50,  4.37it/s]
overall:  50%|████▉     | 1986/4000 [09:42<06:29,  5.17it/s]

train:  57%|█████▋    | 1986/3515 [09:39<04:55,  5.17it/s]
overall:  50%|████▉     | 1987/4000 [09:42<06:41,  5.02it/s]

train:  57%|█████▋    | 1987/3515 [09:40<05:04,  5.02it/s]
overall:  50%|████▉     | 1988/4000 [09:43<07:27,  4.50it/s]

train:  57%|█████▋    | 1988/3515 [09:40<05:39,  4.50it/s]
overall:  50%|████▉     | 1989/4000 [09:43<07:35,  4.41it/s]

train:  57%|█████▋    | 1989/3515 [09:40<05:45,  4.41it/s]
overall:  50%|████▉     | 1990/4000 [09:43<07:38,  4.39it/s]

train:  57%|█████▋    | 1990/3515 [09:40<05:47,  4.39it/s]
overall:  50%|████▉     | 1991/4000 [09:43<07:38,  4.38it/s]

train:  57%|█████▋    | 1991/3515 [09:41<05:47,  4.38it/s]
overall:  50%|████▉     | 1992/4000 [09:44<06:37,  5.05it/s]

train:  57%|█████▋    | 1992/3515 [09:41<05:01,  5.05it/s]
overall:  50%|████▉     | 1993/4000 [09:44<07:23,  4.53it/s]

train:  57%|█████▋    | 1993/3515 [09:41<05:36,  4.53it/s]
overall:  50%|████▉     | 1994/4000 [09:44<07:17,  4.58it/s]

train:  57%|█████▋    | 1994/3515 [09:41<05:31,  4.58it/s]
overall:  50%|████▉     | 1995/4000 [09:44<07:20,  4.55it/s]

train:  57%|█████▋    | 1995/3515 [09:41<05:34,  4.55it/s]
overall:  50%|████▉     | 1996/4000 [09:45<07:17,  4.58it/s]

train:  57%|█████▋    | 1996/3515 [09:42<05:31,  4.58it/s]
overall:  50%|████▉     | 1997/4000 [09:45<07:24,  4.50it/s]

train:  57%|█████▋    | 1997/3515 [09:42<05:37,  4.50it/s]
overall:  50%|████▉     | 1998/4000 [09:45<07:56,  4.20it/s]

train:  57%|█████▋    | 1998/3515 [09:42<06:01,  4.20it/s]
overall:  50%|████▉     | 1999/4000 [09:45<07:39,  4.36it/s]

train:  57%|█████▋    | 1999/3515 [09:42<05:47,  4.36it/s]dev loss: 2.4359965324401855
dev per: 0.6165348595213319
[Runner] - Save the checkpoint to:
1. result/downstream/grid/dev-best.ckpt
train loss: 2.193066120147705
train per: 0.5888801879404855
train loss: 2.1633496284484863
train per: 0.5852294154619736
train loss: 2.220186710357666
train per: 0.5873381360569031
train loss: 2.1828837394714355
train per: 0.5862366910084175
train loss: 2.2310805320739746
train per: 0.5852364475201846
train loss: 2.1977968215942383
train per: 0.580639872587596
train loss: 2.1730411052703857
train per: 0.5817569318476289
train loss: 2.1828901767730713
train per: 0.5797458180539509
train loss: 2.1843576431274414
train per: 0.5791668652590439
train loss: 2.1740143299102783
train per: 0.5811903395754003
train loss: 2.2050042152404785
train per: 0.5873561362640404
train loss: 2.1433660984039307
train per: 0.5747065359161393
train loss: 2.193601131439209
train per: 0.5798532017210832
train loss: 2.1631178855895996
train per: 0.5793386595650244
train loss: 2.1671485900878906
train per: 0.5753819544537331
train loss: 2.2167305946350098
train per: 0.5852530073540155
train loss: 2.1867923736572266
train per: 0.5817995677397338
train loss: 2.1583733558654785
train per: 0.5814875848392593
train loss: 2.1953861713409424
train per: 0.5843425044731997
train loss: 2.1849451065063477
train per: 0.57876167416119
train loss: 2.146613359451294
train per: 0.5753538922008783
train loss: 2.155505657196045
train per: 0.5800952497252412
train loss: 2.1459665298461914
train per: 0.5804529201430274
train loss: 2.1867308616638184
train per: 0.5787573627208816
train loss: 2.2311222553253174
train per: 0.595150749495882
train loss: 2.194397449493408
train per: 0.5843096714909258
train loss: 2.1806864738464355
train per: 0.5817076465820049
train loss: 2.2154927253723145
train per: 0.591080089908908
train loss: 2.1904866695404053
train per: 0.578148745645414
train loss: 2.2000088691711426
train per: 0.5885553886686529
train loss: 2.1614394187927246
train per: 0.5771707066820572
train loss: 2.190913677215576
train per: 0.5877775345930303
train loss: 2.1945700645446777
train per: 0.5840867158671587
train loss: 2.195518732070923
train per: 0.5835463095481497
train loss: 2.1451008319854736
train per: 0.5741353093094542
train loss: 2.1465556621551514
train per: 0.5834514795933757
train loss: 2.1954727172851562
train per: 0.5877309407517519
train loss: 2.1655585765838623
train per: 0.5826240166761794
train loss: 2.1497280597686768
train per: 0.5780288592431255
train loss: 2.2249646186828613
train per: 0.5856674061748937
train loss: 2.203094005584717
train per: 0.5802499662815268
train loss: 2.2080721855163574
train per: 0.5847348660186186
train loss: 2.1503193378448486
train per: 0.5725702051384186
train loss: 2.135500431060791
train per: 0.577589681580008
train loss: 2.1817522048950195
train per: 0.582561459711679
train loss: 2.1772704124450684
train per: 0.5793997161905272
train loss: 2.1703104972839355
train per: 0.5805844477464092
train loss: 2.2107272148132324
train per: 0.5838548185231539
train loss: 2.127603054046631
train per: 0.5684667079738811
train loss: 2.1789536476135254
train per: 0.5786760256565412
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:   9%|▉         | 239/2703 [00:00<00:01, 2384.46it/s]


word -> phonemes:  18%|█▊        | 478/2703 [00:00<00:01, 2104.59it/s]


word -> phonemes:  29%|██▊       | 777/2703 [00:00<00:00, 2479.51it/s]


word -> phonemes:  38%|███▊      | 1029/2703 [00:00<00:00, 2346.02it/s]


word -> phonemes:  49%|████▊     | 1316/2703 [00:00<00:00, 2520.72it/s]


word -> phonemes:  58%|█████▊    | 1572/2703 [00:00<00:00, 2369.82it/s]


word -> phonemes:  69%|██████▉   | 1864/2703 [00:00<00:00, 2534.91it/s]


word -> phonemes:  78%|███████▊  | 2121/2703 [00:00<00:00, 2294.96it/s]


word -> phonemes:  89%|████████▉ | 2402/2703 [00:00<00:00, 2433.13it/s]


word -> phonemes:  98%|█████████▊| 2651/2703 [00:01<00:00, 2354.33it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:01<00:00, 2387.96it/s]



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overall:  74%|███████▍  | 2973/4000 [15:37<04:09,  4.11it/s]

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overall:  75%|███████▍  | 2981/4000 [15:39<03:18,  5.12it/s]

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overall:  75%|███████▍  | 2994/4000 [15:42<03:43,  4.49it/s]

train:  85%|████████▌ | 2994/3515 [15:39<01:55,  4.49it/s]
overall:  75%|███████▍  | 2995/4000 [15:42<03:48,  4.41it/s]

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overall:  75%|███████▍  | 2996/4000 [15:43<04:29,  3.73it/s]

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overall:  75%|███████▍  | 2998/4000 [15:43<03:59,  4.19it/s]

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overall:  75%|███████▍  | 2999/4000 [15:43<03:57,  4.21it/s]

train:  85%|████████▌ | 2999/3515 [15:40<02:02,  4.21it/s]dev loss: 2.4708666801452637
dev per: 0.6272528616024974
train loss: 2.1440558433532715
train per: 0.5767211437494951
train loss: 2.138017416000366
train per: 0.5824154642581783
train loss: 2.1552131175994873
train per: 0.5772150051087432
train loss: 2.175175428390503
train per: 0.577765194412986
train loss: 2.1267144680023193
train per: 0.5696467770904011
train loss: 2.1437201499938965
train per: 0.5732314540740231
train loss: 2.177140712738037
train per: 0.5776167358521541
train loss: 2.192873001098633
train per: 0.5817204301075268
train loss: 2.1048922538757324
train per: 0.5696587645426666
train loss: 2.1525509357452393
train per: 0.5733161917005928
train loss: 2.149454116821289
train per: 0.5755752678728263
train loss: 2.1637604236602783
train per: 0.5798235774015909
train loss: 2.2224364280700684
train per: 0.5897401625320787
train loss: 2.1618688106536865
train per: 0.5769501395123134
train loss: 2.111138105392456
train per: 0.576709219858156
train loss: 2.1874966621398926
train per: 0.5831596820251601
train loss: 2.1829636096954346
train per: 0.5821218753599816
train loss: 2.15539813041687
train per: 0.5750524216232803
train loss: 2.1634535789489746
train per: 0.5776430015459627
train loss: 2.154571533203125
train per: 0.5728578427580516
train loss: 2.1479995250701904
train per: 0.5792686177301561
train loss: 2.2149767875671387
train per: 0.5866930730419201
train loss: 2.226712703704834
train per: 0.588583834637478
train loss: 2.146186113357544
train per: 0.5755117265818063
train loss: 2.1415855884552
train per: 0.574104845626072
train loss: 2.139401912689209
train per: 0.5751763248189097
train loss: 2.1197636127471924
train per: 0.5691450428541072
train loss: 2.138427972793579
train per: 0.5753992997266056
train loss: 2.144909620285034
train per: 0.5746642216384993
train loss: 2.2048797607421875
train per: 0.5847644610240429
train loss: 2.128584861755371
train per: 0.5754118432769367
train loss: 2.1310508251190186
train per: 0.5732359092200047
train loss: 2.131436586380005
train per: 0.5733395478909346
train loss: 2.153481960296631
train per: 0.5807413719642096
train loss: 2.167630672454834
train per: 0.5751700680272109
train loss: 2.148099422454834
train per: 0.5817294435559477
train loss: 2.185701370239258
train per: 0.5870053014424855
train loss: 2.13067364692688
train per: 0.5722206425931191
train loss: 2.1592249870300293
train per: 0.5767925328807807
train loss: 2.13433837890625
train per: 0.5739939474276567
train loss: 2.122683048248291
train per: 0.5718192213990951
train loss: 2.141958475112915
train per: 0.5812214701715724
train loss: 2.1252245903015137
train per: 0.5785243143643015
train loss: 2.195669412612915
train per: 0.5776567378472618
train loss: 2.1326608657836914
train per: 0.5767896889072933
train loss: 2.1754605770111084
train per: 0.5771278590176228
train loss: 2.175459861755371
train per: 0.5824375342228882
train loss: 2.1942801475524902
train per: 0.5837653077393213
train loss: 2.1485707759857178
train per: 0.5741082022670471
train loss: 2.1862425804138184
train per: 0.5832429233652234
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:   6%|▌         | 154/2703 [00:00<00:01, 1478.82it/s]


word -> phonemes:  14%|█▍        | 388/2703 [00:00<00:01, 1940.08it/s]


word -> phonemes:  22%|██▏       | 586/2703 [00:00<00:01, 1957.01it/s]


word -> phonemes:  29%|██▉       | 782/2703 [00:00<00:01, 1577.03it/s]


word -> phonemes:  38%|███▊      | 1028/2703 [00:00<00:00, 1844.57it/s]


word -> phonemes:  48%|████▊     | 1287/2703 [00:00<00:00, 2072.07it/s]


word -> phonemes:  56%|█████▌    | 1504/2703 [00:00<00:00, 2052.76it/s]


word -> phonemes:  67%|██████▋   | 1799/2703 [00:00<00:00, 2318.82it/s]


word -> phonemes:  77%|███████▋  | 2079/2703 [00:00<00:00, 2460.23it/s]


word -> phonemes:  86%|████████▌ | 2330/2703 [00:01<00:00, 2189.59it/s]


word -> phonemes:  95%|█████████▍| 2562/2703 [00:01<00:00, 2202.88it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:01<00:00, 2100.73it/s]



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train: 100%|██████████| 3515/3515 [19:42<00:00,  4.47it/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!!!
403-128339-0009 Failed!!!

train: 100%|██████████| 3515/3515 [19:42<00:00,  2.97it/s]
dev loss: 2.445614814758301
dev per: 0.623194588969823
train loss: 2.101276397705078
train per: 0.5695581424458631
train loss: 2.1558310985565186
train per: 0.5784345832651057
train loss: 2.1225979328155518
train per: 0.5722108644859814
train loss: 2.124239444732666
train per: 0.5668884520389132
train loss: 2.1580898761749268
train per: 0.5743366392879968
train loss: 2.138068199157715
train per: 0.5755306184624759
train loss: 2.112595558166504
train per: 0.5698886818113131
train loss: 2.1745450496673584
train per: 0.576138901563363
train loss: 2.196697235107422
train per: 0.5842442048651744
train loss: 2.125784397125244
train per: 0.5739860206362037
train loss: 2.1602210998535156
train per: 0.5784903690270107
train loss: 2.1904971599578857
train per: 0.5780782549292125
train loss: 2.109199047088623
train per: 0.5696817209711913
train loss: 2.124436140060425
train per: 0.5671188736077708
train loss: 2.1597228050231934
train per: 0.5791629869492689
train loss: 2.1647510528564453
train per: 0.5747076656561282
train loss: 2.177830219268799
train per: 0.575164744645799
train loss: 2.155715227127075
train per: 0.5797465703214997
train loss: 2.1780846118927
train per: 0.5843262336566849
train loss: 2.1550345420837402
train per: 0.5807477041786665
train loss: 2.1578078269958496
train per: 0.5805590711495076
train loss: 2.1894001960754395
train per: 0.5829767369485723
train loss: 2.209618091583252
train per: 0.5858981399680045
train loss: 2.169950008392334
train per: 0.5848921219319082
train loss: 2.1862545013427734
train per: 0.5770566144689293
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.


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

word -> phonemes:   6%|▌         | 209/3515 [00:00<00:01, 2084.53it/s]

word -> phonemes:  12%|█▏        | 418/3515 [00:00<00:01, 2075.54it/s]

word -> phonemes:  18%|█▊        | 626/3515 [00:00<00:01, 2020.20it/s]

word -> phonemes:  24%|██▎       | 829/3515 [00:00<00:01, 1911.59it/s]

word -> phonemes:  30%|██▉       | 1045/3515 [00:00<00:01, 1985.53it/s]

word -> phonemes:  37%|███▋      | 1285/3515 [00:00<00:01, 2119.79it/s]

word -> phonemes:  43%|████▎     | 1498/3515 [00:00<00:00, 2083.62it/s]

word -> phonemes:  49%|████▊     | 1708/3515 [00:00<00:00, 2067.19it/s]

word -> phonemes:  55%|█████▍    | 1930/3515 [00:00<00:00, 2113.41it/s]

word -> phonemes:  61%|██████▏   | 2157/3515 [00:01<00:00, 2160.03it/s]

word -> phonemes:  68%|██████▊   | 2388/3515 [00:01<00:00, 2179.73it/s]

word -> phonemes:  74%|███████▍  | 2607/3515 [00:01<00:00, 1868.79it/s]

word -> phonemes:  80%|███████▉  | 2802/3515 [00:01<00:00, 1879.46it/s]

word -> phonemes:  85%|████████▌ | 2996/3515 [00:01<00:00, 1737.74it/s]

word -> phonemes:  90%|█████████ | 3175/3515 [00:01<00:00, 1276.52it/s]

word -> phonemes:  95%|█████████▍| 3323/3515 [00:01<00:00, 1241.25it/s]
word -> phonemes: 100%|██████████| 3515/3515 [00:01<00:00, 1764.37it/s]


train:   0%|          | 0/3515 [00:00<?, ?it/s]
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train:   0%|          | 1/3515 [00:01<1:42:01,  1.74s/it]
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overall:  88%|████████▊ | 3518/4000 [19:51<07:39,  1.05it/s]

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overall:  88%|████████▊ | 3519/4000 [19:51<06:02,  1.33it/s]

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overall:  89%|████████▉ | 3557/4000 [20:00<02:03,  3.60it/s]

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overall:  89%|████████▉ | 3560/4000 [20:01<01:46,  4.12it/s]

train:   1%|▏         | 45/3515 [00:12<14:01,  4.12it/s]
overall:  89%|████████▉ | 3561/4000 [20:01<01:43,  4.24it/s]

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overall:  89%|████████▉ | 3562/4000 [20:01<01:44,  4.18it/s]

train:   1%|▏         | 47/3515 [00:12<13:48,  4.18it/s]
overall:  89%|████████▉ | 3563/4000 [20:02<01:32,  4.73it/s]

train:   1%|▏         | 48/3515 [00:12<12:12,  4.73it/s]
overall:  89%|████████▉ | 3564/4000 [20:02<01:36,  4.50it/s]

train:   1%|▏         | 49/3515 [00:13<12:51,  4.50it/s]
overall:  89%|████████▉ | 3565/4000 [20:02<01:24,  5.14it/s]

train:   1%|▏         | 50/3515 [00:13<11:14,  5.14it/s]
overall:  89%|████████▉ | 3566/4000 [20:02<01:32,  4.67it/s]

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overall:  89%|████████▉ | 3567/4000 [20:02<01:33,  4.64it/s]

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overall:  89%|████████▉ | 3568/4000 [20:02<01:20,  5.34it/s]

train:   2%|▏         | 53/3515 [00:13<10:48,  5.34it/s]
overall:  89%|████████▉ | 3569/4000 [20:03<01:53,  3.81it/s]

train:   2%|▏         | 54/3515 [00:14<15:09,  3.81it/s]
overall:  89%|████████▉ | 3570/4000 [20:03<01:52,  3.81it/s]

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overall:  89%|████████▉ | 3571/4000 [20:03<01:50,  3.89it/s]

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overall:  89%|████████▉ | 3572/4000 [20:04<02:16,  3.14it/s]

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overall:  89%|████████▉ | 3573/4000 [20:04<02:02,  3.47it/s]

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overall:  89%|████████▉ | 3574/4000 [20:04<01:57,  3.64it/s]

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overall:  89%|████████▉ | 3575/4000 [20:05<01:53,  3.76it/s]

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overall:  89%|████████▉ | 3576/4000 [20:05<01:49,  3.88it/s]

train:   2%|▏         | 61/3515 [00:16<14:49,  3.88it/s]
overall:  89%|████████▉ | 3577/4000 [20:05<01:46,  3.99it/s]

train:   2%|▏         | 62/3515 [00:16<14:25,  3.99it/s]
overall:  89%|████████▉ | 3578/4000 [20:05<01:44,  4.03it/s]

train:   2%|▏         | 63/3515 [00:16<14:17,  4.03it/s]
overall:  89%|████████▉ | 3579/4000 [20:06<01:44,  4.04it/s]

train:   2%|▏         | 64/3515 [00:16<14:13,  4.04it/s]
overall:  90%|████████▉ | 3580/4000 [20:06<01:43,  4.04it/s]

train:   2%|▏         | 65/3515 [00:17<14:13,  4.04it/s]
overall:  90%|████████▉ | 3581/4000 [20:06<01:42,  4.09it/s]

train:   2%|▏         | 66/3515 [00:17<14:03,  4.09it/s]
overall:  90%|████████▉ | 3582/4000 [20:06<01:41,  4.13it/s]

train:   2%|▏         | 67/3515 [00:17<13:54,  4.13it/s]
overall:  90%|████████▉ | 3583/4000 [20:07<01:39,  4.21it/s]

train:   2%|▏         | 68/3515 [00:17<13:39,  4.21it/s]
overall:  90%|████████▉ | 3584/4000 [20:07<01:55,  3.61it/s]

train:   2%|▏         | 69/3515 [00:18<15:53,  3.61it/s]
overall:  90%|████████▉ | 3586/4000 [20:07<01:32,  4.46it/s]

train:   2%|▏         | 71/3515 [00:18<12:52,  4.46it/s]
overall:  90%|████████▉ | 3587/4000 [20:07<01:32,  4.45it/s]

train:   2%|▏         | 72/3515 [00:18<12:53,  4.45it/s]
overall:  90%|████████▉ | 3588/4000 [20:08<01:32,  4.47it/s]

train:   2%|▏         | 73/3515 [00:18<12:50,  4.47it/s]
overall:  90%|████████▉ | 3589/4000 [20:08<01:33,  4.38it/s]

train:   2%|▏         | 74/3515 [00:19<13:05,  4.38it/s]
overall:  90%|████████▉ | 3590/4000 [20:08<01:34,  4.35it/s]

train:   2%|▏         | 75/3515 [00:19<13:11,  4.35it/s]
overall:  90%|████████▉ | 3591/4000 [20:08<01:30,  4.50it/s]

train:   2%|▏         | 76/3515 [00:19<12:44,  4.50it/s]
overall:  90%|████████▉ | 3592/4000 [20:09<01:29,  4.57it/s]

train:   2%|▏         | 77/3515 [00:19<12:32,  4.57it/s]
overall:  90%|████████▉ | 3593/4000 [20:09<01:34,  4.33it/s]

train:   2%|▏         | 78/3515 [00:20<13:14,  4.33it/s]
overall:  90%|████████▉ | 3594/4000 [20:09<01:33,  4.32it/s]

train:   2%|▏         | 79/3515 [00:20<13:14,  4.32it/s]
overall:  90%|████████▉ | 3595/4000 [20:09<01:28,  4.58it/s]

train:   2%|▏         | 80/3515 [00:20<12:29,  4.58it/s]
overall:  90%|████████▉ | 3596/4000 [20:09<01:30,  4.48it/s]

train:   2%|▏         | 81/3515 [00:20<12:46,  4.48it/s]
overall:  90%|████████▉ | 3597/4000 [20:10<01:31,  4.38it/s]

train:   2%|▏         | 82/3515 [00:20<13:03,  4.38it/s]
overall:  90%|████████▉ | 3598/4000 [20:10<01:29,  4.51it/s]

train:   2%|▏         | 83/3515 [00:21<12:41,  4.51it/s]
overall:  90%|████████▉ | 3599/4000 [20:10<01:25,  4.68it/s]

train:   2%|▏         | 84/3515 [00:21<12:13,  4.68it/s]
overall:  90%|█████████ | 3600/4000 [20:10<01:30,  4.42it/s]

train:   2%|▏         | 85/3515 [00:21<12:56,  4.42it/s]
overall:  90%|█████████ | 3601/4000 [20:11<01:31,  4.36it/s]

train:   2%|▏         | 86/3515 [00:21<13:06,  4.36it/s]
overall:  90%|█████████ | 3602/4000 [20:11<01:31,  4.34it/s]

train:   2%|▏         | 87/3515 [00:22<13:09,  4.34it/s]
overall:  90%|█████████ | 3603/4000 [20:11<01:32,  4.27it/s]

train:   3%|▎         | 88/3515 [00:22<13:21,  4.27it/s]
overall:  90%|█████████ | 3604/4000 [20:11<01:33,  4.23it/s]

train:   3%|▎         | 89/3515 [00:22<13:29,  4.23it/s]
overall:  90%|█████████ | 3606/4000 [20:12<01:15,  5.20it/s]

train:   3%|▎         | 91/3515 [00:22<10:58,  5.20it/s]
overall:  90%|█████████ | 3607/4000 [20:12<01:20,  4.88it/s]

train:   3%|▎         | 92/3515 [00:23<11:40,  4.88it/s]
overall:  90%|█████████ | 3608/4000 [20:12<01:49,  3.58it/s]

train:   3%|▎         | 93/3515 [00:23<15:57,  3.58it/s]
overall:  90%|█████████ | 3609/4000 [20:13<01:43,  3.77it/s]

train:   3%|▎         | 94/3515 [00:23<15:08,  3.77it/s]
overall:  90%|█████████ | 3610/4000 [20:13<01:38,  3.95it/s]

train:   3%|▎         | 95/3515 [00:24<14:24,  3.95it/s]
overall:  90%|█████████ | 3611/4000 [20:13<01:36,  4.04it/s]

train:   3%|▎         | 96/3515 [00:24<14:06,  4.04it/s]
overall:  90%|█████████ | 3612/4000 [20:13<01:34,  4.09it/s]

train:   3%|▎         | 97/3515 [00:24<13:55,  4.09it/s]
overall:  90%|█████████ | 3613/4000 [20:13<01:34,  4.10it/s]

train:   3%|▎         | 98/3515 [00:24<13:53,  4.10it/s]
overall:  90%|█████████ | 3614/4000 [20:14<01:34,  4.09it/s]

train:   3%|▎         | 99/3515 [00:24<13:56,  4.09it/s]
overall:  90%|█████████ | 3615/4000 [20:14<01:33,  4.14it/s]

train:   3%|▎         | 100/3515 [00:25<13:44,  4.14it/s]
overall:  90%|█████████ | 3616/4000 [20:14<01:33,  4.10it/s]

train:   3%|▎         | 101/3515 [00:25<13:51,  4.10it/s]
overall:  90%|█████████ | 3617/4000 [20:14<01:30,  4.24it/s]

train:   3%|▎         | 102/3515 [00:25<13:25,  4.24it/s]
overall:  90%|█████████ | 3618/4000 [20:15<01:30,  4.23it/s]

train:   3%|▎         | 103/3515 [00:25<13:27,  4.23it/s]
overall:  90%|█████████ | 3619/4000 [20:15<01:32,  4.11it/s]

train:   3%|▎         | 104/3515 [00:26<13:50,  4.11it/s]
overall:  90%|█████████ | 3620/4000 [20:15<01:59,  3.19it/s]

train:   3%|▎         | 105/3515 [00:26<17:49,  3.19it/s]
overall:  91%|█████████ | 3621/4000 [20:16<01:51,  3.39it/s]

train:   3%|▎         | 106/3515 [00:26<16:44,  3.39it/s]
overall:  91%|█████████ | 3622/4000 [20:16<01:45,  3.58it/s]

train:   3%|▎         | 107/3515 [00:27<15:52,  3.58it/s]
overall:  91%|█████████ | 3623/4000 [20:16<01:42,  3.69it/s]

train:   3%|▎         | 108/3515 [00:27<15:22,  3.69it/s]
overall:  91%|█████████ | 3624/4000 [20:16<01:39,  3.79it/s]

train:   3%|▎         | 109/3515 [00:27<14:59,  3.79it/s]
overall:  91%|█████████ | 3625/4000 [20:17<02:07,  2.95it/s]

train:   3%|▎         | 110/3515 [00:28<19:15,  2.95it/s]
overall:  91%|█████████ | 3626/4000 [20:17<01:53,  3.29it/s]

train:   3%|▎         | 111/3515 [00:28<17:15,  3.29it/s]
overall:  91%|█████████ | 3627/4000 [20:17<01:46,  3.51it/s]

train:   3%|▎         | 112/3515 [00:28<16:10,  3.51it/s]
overall:  91%|█████████ | 3628/4000 [20:17<01:27,  4.25it/s]

train:   3%|▎         | 113/3515 [00:28<13:20,  4.25it/s]
overall:  91%|█████████ | 3629/4000 [20:18<01:27,  4.25it/s]

train:   3%|▎         | 114/3515 [00:28<13:20,  4.25it/s]
overall:  91%|█████████ | 3630/4000 [20:18<01:25,  4.31it/s]

train:   3%|▎         | 115/3515 [00:29<13:09,  4.30it/s]
overall:  91%|█████████ | 3631/4000 [20:18<01:25,  4.30it/s]

train:   3%|▎         | 116/3515 [00:29<13:11,  4.30it/s]
overall:  91%|█████████ | 3632/4000 [20:18<01:27,  4.18it/s]

train:   3%|▎         | 117/3515 [00:29<13:32,  4.18it/s]
overall:  91%|█████████ | 3633/4000 [20:19<01:28,  4.13it/s]

train:   3%|▎         | 118/3515 [00:29<13:41,  4.13it/s]
overall:  91%|█████████ | 3634/4000 [20:19<01:29,  4.07it/s]

train:   3%|▎         | 119/3515 [00:30<13:53,  4.07it/s]
overall:  91%|█████████ | 3635/4000 [20:19<01:27,  4.17it/s]

train:   3%|▎         | 120/3515 [00:30<13:33,  4.17it/s]
overall:  91%|█████████ | 3636/4000 [20:19<01:27,  4.15it/s]

train:   3%|▎         | 121/3515 [00:30<13:38,  4.15it/s]
overall:  91%|█████████ | 3637/4000 [20:20<01:38,  3.69it/s]

train:   3%|▎         | 122/3515 [00:31<15:19,  3.69it/s]
overall:  91%|█████████ | 3638/4000 [20:20<01:34,  3.82it/s]

train:   3%|▎         | 123/3515 [00:31<14:47,  3.82it/s]
overall:  91%|█████████ | 3639/4000 [20:20<01:32,  3.90it/s]

train:   4%|▎         | 124/3515 [00:31<14:30,  3.89it/s]
overall:  91%|█████████ | 3640/4000 [20:20<01:32,  3.90it/s]

train:   4%|▎         | 125/3515 [00:31<14:28,  3.90it/s]
overall:  91%|█████████ | 3641/4000 [20:21<01:31,  3.90it/s]

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overall:  93%|█████████▎| 3705/4000 [20:36<01:11,  4.11it/s]

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overall:  93%|█████████▎| 3706/4000 [20:36<01:17,  3.79it/s]

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overall:  93%|█████████▎| 3707/4000 [20:37<01:07,  4.36it/s]

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overall:  93%|█████████▎| 3708/4000 [20:37<01:07,  4.35it/s]

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overall:  93%|█████████▎| 3709/4000 [20:37<01:05,  4.46it/s]

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overall: 100%|█████████▉| 3995/4000 [21:43<00:00,  5.38it/s]

train:  14%|█▎        | 480/3515 [01:54<09:23,  5.38it/s]
overall: 100%|█████████▉| 3996/4000 [21:43<00:00,  5.09it/s]

train:  14%|█▎        | 481/3515 [01:54<09:55,  5.09it/s]
overall: 100%|█████████▉| 3997/4000 [21:44<00:00,  4.90it/s]

train:  14%|█▎        | 482/3515 [01:54<10:19,  4.90it/s]
overall: 100%|█████████▉| 3998/4000 [21:44<00:00,  4.72it/s]

train:  14%|█▎        | 483/3515 [01:55<10:42,  4.72it/s]
overall: 100%|█████████▉| 3999/4000 [21:44<00:00,  4.81it/s]

train:  14%|█▍        | 484/3515 [01:55<10:30,  4.81it/s]train loss: 2.1501731872558594
train per: 0.5758811018837351
train loss: 2.140505313873291
train per: 0.5767741184007454
train loss: 2.1351318359375
train per: 0.5743451365730723
train loss: 2.187520980834961
train per: 0.580307328605201
train loss: 2.1825850009918213
train per: 0.5856936379542055
train loss: 2.15515398979187
train per: 0.5756177433760048
train loss: 2.156256675720215
train per: 0.5717039586919105
train loss: 2.1506733894348145
train per: 0.5758333758742151
train loss: 2.163255214691162
train per: 0.5848277970246587
train loss: 2.1625149250030518
train per: 0.5788631318085601
train loss: 2.179868698120117
train per: 0.5789281903125895
train loss: 2.193671226501465
train per: 0.5805443998215083
train loss: 2.127364158630371
train per: 0.5717958412098298
train loss: 2.158629894256592
train per: 0.5766791093476729
train loss: 2.195192337036133
train per: 0.5868408196847762
train loss: 2.139768123626709
train per: 0.5737933836037271
train loss: 2.1306118965148926
train per: 0.5775084971183686
train loss: 2.1593194007873535
train per: 0.5744640395493654
train loss: 2.16229248046875
train per: 0.5776385256821434
train loss: 2.13682222366333
train per: 0.572099544339292
train loss: 2.151601791381836
train per: 0.5755494505494505
train loss: 2.149355173110962
train per: 0.5747628502095742
train loss: 2.174060344696045
train per: 0.5804199137294154
train loss: 2.1513729095458984
train per: 0.5734049795759579
train loss: 2.148987293243408
train per: 0.5708872046366473
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:   8%|▊         | 205/2703 [00:00<00:01, 2049.56it/s]


word -> phonemes:  16%|█▋        | 441/2703 [00:00<00:01, 2230.04it/s]


word -> phonemes:  26%|██▌       | 700/2703 [00:00<00:00, 2392.28it/s]


word -> phonemes:  35%|███▍      | 940/2703 [00:00<00:00, 2395.20it/s]


word -> phonemes:  44%|████▍     | 1195/2703 [00:00<00:00, 2448.99it/s]


word -> phonemes:  54%|█████▍    | 1457/2703 [00:00<00:00, 2506.18it/s]


word -> phonemes:  63%|██████▎   | 1708/2703 [00:00<00:00, 2432.28it/s]


word -> phonemes:  72%|███████▏  | 1952/2703 [00:00<00:00, 2411.91it/s]


word -> phonemes:  81%|████████  | 2194/2703 [00:00<00:00, 2361.65it/s]


word -> phonemes:  90%|████████▉ | 2431/2703 [00:01<00:00, 2314.45it/s]


word -> phonemes:  99%|█████████▉| 2673/2703 [00:01<00:00, 2343.28it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:01<00:00, 2372.13it/s]



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overall: 100%|█████████▉| 3999/4000 [23:05<00:00,  4.81it/s]

train:  14%|█▍        | 484/3515 [03:16<10:30,  4.81it/s]
                                                            

                                                         

overall: 100%|█████████▉| 3999/4000 [23:05<00:00,  4.81it/s]

train:  14%|█▍        | 484/3515 [03:16<10:30,  4.81it/s]
overall: 100%|██████████| 4000/4000 [23:05<00:00, 23.78s/it]

train:  14%|█▍        | 485/3515 [03:16<20:00:50, 23.78s/it]403-128339-0009 Failed!!!

train:  14%|█▍        | 485/3515 [03:16<20:27,  2.47it/s]   

overall: 100%|██████████| 4000/4000 [23:05<00:00,  2.89it/s]
dev loss: 2.483384847640991
dev per: 0.6262851196670135
[Runner] - Save the checkpoint to:
1. result/downstream/grid/states-4000.ckpt