/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")
2023-10-12 18:38:06 | 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_only_demuc_label2 {'model_config': None, 'refresh': False}
Loading model from Local mert_25hz_test_only_demuc_label2
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:  48%|████▊     | 1674/3515 [00:00<00:00, 3925.53it/s]

word -> phonemes:  61%|██████    | 2140/3515 [00:00<00:00, 4177.33it/s]

word -> phonemes:  74%|███████▎  | 2585/3515 [00:00<00:00, 4266.12it/s]

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word -> phonemes:  99%|█████████▉| 3481/3515 [00:00<00:00, 4335.90it/s]
word -> phonemes: 100%|██████████| 3515/3515 [00:00<00:00, 4144.28it/s]


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train:   4%|▍         | 155/3515 [00:32<10:53,  5.14it/s]
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train:   5%|▍         | 159/3515 [00:32<10:52,  5.14it/s]
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train:   5%|▍         | 160/3515 [00:33<11:11,  5.00it/s]
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train:   5%|▍         | 162/3515 [00:33<11:14,  4.97it/s]
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train:   5%|▍         | 163/3515 [00:33<11:20,  4.92it/s]
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train:   5%|▍         | 164/3515 [00:34<11:34,  4.82it/s]
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train:   5%|▍         | 165/3515 [00:34<11:33,  4.83it/s]
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train:   5%|▍         | 166/3515 [00:34<14:27,  3.86it/s]
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train:   5%|▍         | 167/3515 [00:34<13:31,  4.13it/s]
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train:   5%|▍         | 168/3515 [00:35<12:58,  4.30it/s]
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train:   5%|▍         | 170/3515 [00:35<14:22,  3.88it/s]
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train:   5%|▌         | 177/3515 [00:36<11:01,  5.05it/s]
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train:   5%|▌         | 180/3515 [00:37<11:11,  4.96it/s]
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train:   5%|▌         | 181/3515 [00:37<11:59,  4.63it/s]
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train:   5%|▌         | 182/3515 [00:37<11:40,  4.76it/s]
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train:   5%|▌         | 185/3515 [00:38<10:28,  5.30it/s]
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train:   5%|▌         | 186/3515 [00:38<11:01,  5.03it/s]
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train:   5%|▌         | 187/3515 [00:38<11:09,  4.97it/s]
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train:   5%|▌         | 188/3515 [00:38<10:57,  5.06it/s]
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train:   5%|▌         | 189/3515 [00:39<11:22,  4.87it/s]
overall:   5%|▍         | 190/4000 [00:41<16:34,  3.83it/s]

train:   5%|▌         | 190/3515 [00:39<14:27,  3.83it/s]
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train:   5%|▌         | 191/3515 [00:39<13:36,  4.07it/s]
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train:   5%|▌         | 192/3515 [00:40<12:53,  4.29it/s]
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train:   5%|▌         | 193/3515 [00:40<12:24,  4.46it/s]
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train:   6%|▌         | 194/3515 [00:40<14:17,  3.87it/s]
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train:   6%|▌         | 195/3515 [00:40<13:07,  4.21it/s]
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overall:  11%|█         | 449/4000 [01:36<14:00,  4.22it/s]

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overall:  11%|█▏        | 451/4000 [01:36<12:49,  4.61it/s]

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overall:  11%|█▏        | 453/4000 [01:36<12:34,  4.70it/s]

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overall:  13%|█▎        | 536/4000 [01:54<10:49,  5.33it/s]

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overall:  13%|█▎        | 538/4000 [01:54<12:01,  4.80it/s]

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overall:  14%|█▎        | 542/4000 [01:55<14:24,  4.00it/s]

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overall:  14%|█▎        | 543/4000 [01:56<13:46,  4.18it/s]

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overall:  14%|█▎        | 544/4000 [01:56<13:20,  4.32it/s]

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overall:  14%|█▎        | 545/4000 [01:56<12:53,  4.46it/s]

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overall:  14%|█▎        | 546/4000 [01:56<12:43,  4.52it/s]

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overall:  14%|█▎        | 547/4000 [01:56<12:17,  4.68it/s]

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overall:  14%|█▎        | 548/4000 [01:57<12:08,  4.74it/s]

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overall:  14%|█▎        | 549/4000 [01:57<12:03,  4.77it/s]

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overall:  14%|█▍        | 550/4000 [01:57<11:43,  4.91it/s]

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overall:  14%|█▍        | 552/4000 [01:57<11:59,  4.80it/s]

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overall:  14%|█▍        | 554/4000 [01:58<12:06,  4.74it/s]

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overall:  14%|█▍        | 555/4000 [01:58<12:15,  4.68it/s]

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overall:  14%|█▍        | 569/4000 [02:01<12:13,  4.68it/s]

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overall:  25%|██▍       | 996/4000 [03:30<10:48,  4.63it/s]

train:  28%|██▊       | 996/3515 [03:28<09:03,  4.63it/s]
overall:  25%|██▍       | 997/4000 [03:31<11:07,  4.50it/s]

train:  28%|██▊       | 997/3515 [03:29<09:19,  4.50it/s]
overall:  25%|██▍       | 998/4000 [03:31<11:18,  4.43it/s]

train:  28%|██▊       | 998/3515 [03:29<09:28,  4.43it/s]
overall:  25%|██▍       | 999/4000 [03:31<10:43,  4.67it/s]

train:  28%|██▊       | 999/3515 [03:29<08:59,  4.67it/s]train loss: 4.244696140289307
train per: 0.9308081755109694
train loss: 3.2131810188293457
train per: 0.7955295260990768
train loss: 2.5144996643066406
train per: 0.6534278223399008
train loss: 2.371049165725708
train per: 0.6196490870661336
train loss: 2.3101003170013428
train per: 0.6037981148720806
train loss: 2.23646879196167
train per: 0.5947028771175047
train loss: 2.187018871307373
train per: 0.5807883695970338
train loss: 2.2507734298706055
train per: 0.5896406931008823
train loss: 2.1382007598876953
train per: 0.5699236046907693
train loss: 2.116969347000122
train per: 0.5631405864620443
train loss: 2.1233131885528564
train per: 0.575050683236355
train loss: 2.1375250816345215
train per: 0.5677088494698246
train loss: 2.1740963459014893
train per: 0.5733929832823169
train loss: 2.1461732387542725
train per: 0.5692817630064276
train loss: 2.0631394386291504
train per: 0.5524710979256434
train loss: 2.0879485607147217
train per: 0.5584225221033039
train loss: 2.064537525177002
train per: 0.5564310485516116
train loss: 2.061737537384033
train per: 0.5573701725439749
train loss: 2.098158836364746
train per: 0.554772069962815
train loss: 2.038008451461792
train per: 0.5458687880771361
train loss: 2.0212018489837646
train per: 0.5428740536141459
train loss: 2.064307451248169
train per: 0.5517215399683568
train loss: 2.0881056785583496
train per: 0.547696429355703
train loss: 2.079212188720703
train per: 0.5487930827428846
train loss: 2.051203489303589
train per: 0.5430915332828035
train loss: 2.0003662109375
train per: 0.5365009683666881
train loss: 2.053828001022339
train per: 0.5423649447949527
train loss: 2.0172882080078125
train per: 0.5424782995010594
train loss: 2.02565336227417
train per: 0.5414095994980654
train loss: 2.0340046882629395
train per: 0.5477566160211143
train loss: 2.0675580501556396
train per: 0.5488868074068737
train loss: 2.019575834274292
train per: 0.5389702640474208
train loss: 2.0413312911987305
train per: 0.5481523335970166
train loss: 2.0391528606414795
train per: 0.5435528298944962
train loss: 2.0138754844665527
train per: 0.5439404677533664
train loss: 2.009617328643799
train per: 0.5438734946802292
train loss: 2.071399688720703
train per: 0.5446336429308566
train loss: 2.0515129566192627
train per: 0.5431670281995662
train loss: 2.033688545227051
train per: 0.5401287659114365
train loss: 2.0483505725860596
train per: 0.5453037770666418
train loss: 2.011655807495117
train per: 0.5401641514429442
train loss: 2.0019659996032715
train per: 0.5382052542465454
train loss: 2.0130293369293213
train per: 0.5347017318794098
train loss: 2.0460331439971924
train per: 0.5481417851999697
train loss: 1.9961122274398804
train per: 0.532155922795509
train loss: 2.0080838203430176
train per: 0.5385002286236854
train loss: 2.0251193046569824
train per: 0.5434332988624612
train loss: 2.0231094360351562
train per: 0.5427769228692529
train loss: 2.0093483924865723
train per: 0.5365438829477412
train loss: 1.9752357006072998
train per: 0.5329693406131877
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  16%|█▋        | 441/2703 [00:00<00:00, 4404.01it/s]


word -> phonemes:  33%|███▎      | 883/2703 [00:00<00:00, 4410.25it/s]


word -> phonemes:  52%|█████▏    | 1410/2703 [00:00<00:00, 4800.93it/s]


word -> phonemes:  70%|███████   | 1899/2703 [00:00<00:00, 4835.19it/s]


word -> phonemes:  89%|████████▉ | 2419/2703 [00:00<00:00, 4964.83it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 4849.88it/s]



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overall:  47%|████▋     | 1872/4000 [08:25<07:09,  4.95it/s]

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overall:  47%|████▋     | 1876/4000 [08:26<08:40,  4.08it/s]

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overall:  47%|████▋     | 1877/4000 [08:26<08:07,  4.36it/s]

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overall:  47%|████▋     | 1878/4000 [08:26<08:04,  4.38it/s]

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overall:  47%|████▋     | 1879/4000 [08:26<07:51,  4.50it/s]

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overall:  47%|████▋     | 1893/4000 [08:29<08:00,  4.39it/s]

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overall:  47%|████▋     | 1899/4000 [08:31<06:58,  5.02it/s]

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overall:  48%|████▊     | 1900/4000 [08:31<08:33,  4.09it/s]

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overall:  48%|████▊     | 1901/4000 [08:31<08:10,  4.28it/s]

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overall:  48%|████▊     | 1902/4000 [08:31<07:05,  4.93it/s]

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overall:  48%|████▊     | 1903/4000 [08:32<07:22,  4.74it/s]

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overall:  48%|████▊     | 1904/4000 [08:32<07:21,  4.75it/s]

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overall:  48%|████▊     | 1905/4000 [08:32<06:18,  5.53it/s]

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overall:  48%|████▊     | 1909/4000 [08:33<06:46,  5.14it/s]

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overall:  48%|████▊     | 1910/4000 [08:33<07:04,  4.92it/s]

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overall:  48%|████▊     | 1914/4000 [08:34<07:31,  4.62it/s]

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overall:  48%|████▊     | 1919/4000 [08:35<07:07,  4.87it/s]

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overall:  48%|████▊     | 1920/4000 [08:35<07:13,  4.80it/s]

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overall:  48%|████▊     | 1924/4000 [08:36<08:40,  3.99it/s]

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overall:  48%|████▊     | 1925/4000 [08:36<07:48,  4.43it/s]

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overall:  48%|████▊     | 1926/4000 [08:36<07:36,  4.54it/s]

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overall:  48%|████▊     | 1930/4000 [08:37<06:41,  5.15it/s]

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train:  55%|█████▍    | 1933/3515 [08:36<05:55,  4.44it/s]
overall:  48%|████▊     | 1934/4000 [08:38<07:41,  4.48it/s]

train:  55%|█████▌    | 1934/3515 [08:36<05:53,  4.48it/s]
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train:  55%|█████▌    | 1935/3515 [08:36<05:51,  4.49it/s]
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overall:  48%|████▊     | 1937/4000 [08:38<06:38,  5.18it/s]

train:  55%|█████▌    | 1937/3515 [08:36<05:04,  5.18it/s]
overall:  48%|████▊     | 1938/4000 [08:39<08:26,  4.07it/s]

train:  55%|█████▌    | 1938/3515 [08:37<06:27,  4.07it/s]
overall:  48%|████▊     | 1939/4000 [08:39<08:15,  4.16it/s]

train:  55%|█████▌    | 1939/3515 [08:37<06:18,  4.16it/s]
overall:  48%|████▊     | 1940/4000 [08:39<08:01,  4.27it/s]

train:  55%|█████▌    | 1940/3515 [08:37<06:08,  4.27it/s]
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train:  55%|█████▌    | 1941/3515 [08:37<05:45,  4.56it/s]
overall:  49%|████▊     | 1942/4000 [08:40<07:31,  4.56it/s]

train:  55%|█████▌    | 1942/3515 [08:38<05:44,  4.56it/s]
overall:  49%|████▊     | 1943/4000 [08:40<07:28,  4.59it/s]

train:  55%|█████▌    | 1943/3515 [08:38<05:42,  4.59it/s]
overall:  49%|████▊     | 1945/4000 [08:40<06:29,  5.28it/s]

train:  55%|█████▌    | 1945/3515 [08:38<04:57,  5.28it/s]
overall:  49%|████▊     | 1946/4000 [08:40<06:43,  5.10it/s]

train:  55%|█████▌    | 1946/3515 [08:38<05:07,  5.09it/s]
overall:  49%|████▊     | 1948/4000 [08:41<06:49,  5.02it/s]

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overall:  49%|████▊     | 1949/4000 [08:41<06:55,  4.94it/s]

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train:  55%|█████▌    | 1950/3515 [08:39<05:24,  4.83it/s]
overall:  49%|████▉     | 1951/4000 [08:42<07:06,  4.81it/s]

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overall:  49%|████▉     | 1952/4000 [08:42<07:08,  4.77it/s]

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overall:  49%|████▉     | 1955/4000 [08:42<07:47,  4.37it/s]

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overall:  49%|████▉     | 1956/4000 [08:43<07:30,  4.54it/s]

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overall:  49%|████▉     | 1957/4000 [08:43<07:25,  4.58it/s]

train:  56%|█████▌    | 1957/3515 [08:41<05:39,  4.58it/s]
overall:  49%|████▉     | 1958/4000 [08:43<07:20,  4.64it/s]

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overall:  49%|████▉     | 1959/4000 [08:43<07:14,  4.70it/s]

train:  56%|█████▌    | 1959/3515 [08:41<05:31,  4.70it/s]
overall:  49%|████▉     | 1960/4000 [08:43<07:14,  4.69it/s]

train:  56%|█████▌    | 1960/3515 [08:41<05:31,  4.69it/s]
overall:  49%|████▉     | 1961/4000 [08:44<07:15,  4.68it/s]

train:  56%|█████▌    | 1961/3515 [08:42<05:31,  4.68it/s]
overall:  49%|████▉     | 1962/4000 [08:44<08:46,  3.87it/s]

train:  56%|█████▌    | 1962/3515 [08:42<06:41,  3.87it/s]
overall:  49%|████▉     | 1963/4000 [08:44<08:25,  4.03it/s]

train:  56%|█████▌    | 1963/3515 [08:42<06:25,  4.03it/s]
overall:  49%|████▉     | 1964/4000 [08:44<07:53,  4.30it/s]

train:  56%|█████▌    | 1964/3515 [08:42<06:00,  4.30it/s]
overall:  49%|████▉     | 1965/4000 [08:45<07:42,  4.40it/s]

train:  56%|█████▌    | 1965/3515 [08:43<05:52,  4.40it/s]
overall:  49%|████▉     | 1966/4000 [08:45<07:22,  4.60it/s]

train:  56%|█████▌    | 1966/3515 [08:43<05:36,  4.60it/s]
overall:  49%|████▉     | 1967/4000 [08:45<07:02,  4.81it/s]

train:  56%|█████▌    | 1967/3515 [08:43<05:21,  4.81it/s]
overall:  49%|████▉     | 1968/4000 [08:45<06:43,  5.04it/s]

train:  56%|█████▌    | 1968/3515 [08:43<05:06,  5.04it/s]
overall:  49%|████▉     | 1969/4000 [08:45<06:55,  4.88it/s]

train:  56%|█████▌    | 1969/3515 [08:43<05:16,  4.88it/s]
overall:  49%|████▉     | 1970/4000 [08:46<07:08,  4.74it/s]

train:  56%|█████▌    | 1970/3515 [08:44<05:25,  4.74it/s]
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train:  56%|█████▌    | 1971/3515 [08:44<05:28,  4.70it/s]
overall:  49%|████▉     | 1972/4000 [08:46<08:25,  4.01it/s]

train:  56%|█████▌    | 1972/3515 [08:44<06:24,  4.01it/s]
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train:  56%|█████▌    | 1973/3515 [08:44<06:13,  4.13it/s]
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train:  56%|█████▌    | 1974/3515 [08:45<06:05,  4.21it/s]
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train:  56%|█████▌    | 1975/3515 [08:45<06:00,  4.27it/s]
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train:  56%|█████▌    | 1976/3515 [08:45<05:51,  4.38it/s]
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train:  56%|█████▌    | 1977/3515 [08:45<05:48,  4.42it/s]
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train:  56%|█████▋    | 1978/3515 [08:45<05:36,  4.57it/s]
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train:  56%|█████▋    | 1979/3515 [08:46<05:40,  4.51it/s]
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train:  56%|█████▋    | 1980/3515 [08:46<05:42,  4.48it/s]
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train:  56%|█████▋    | 1981/3515 [08:46<05:07,  4.99it/s]
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train:  56%|█████▋    | 1982/3515 [08:46<05:20,  4.79it/s]
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train:  56%|█████▋    | 1984/3515 [08:47<04:41,  5.44it/s]
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train:  56%|█████▋    | 1985/3515 [08:47<04:51,  5.25it/s]
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train:  57%|█████▋    | 1986/3515 [08:47<05:13,  4.88it/s]
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train:  57%|█████▋    | 1987/3515 [08:47<05:22,  4.73it/s]
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train:  57%|█████▋    | 1988/3515 [08:48<05:27,  4.66it/s]
overall:  50%|████▉     | 1989/4000 [08:50<07:14,  4.63it/s]

train:  57%|█████▋    | 1989/3515 [08:48<05:29,  4.63it/s]
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train:  57%|█████▋    | 1990/3515 [08:48<05:36,  4.54it/s]
overall:  50%|████▉     | 1991/4000 [08:50<07:32,  4.44it/s]

train:  57%|█████▋    | 1991/3515 [08:48<05:43,  4.44it/s]
overall:  50%|████▉     | 1992/4000 [08:50<06:31,  5.13it/s]

train:  57%|█████▋    | 1992/3515 [08:48<04:57,  5.13it/s]
overall:  50%|████▉     | 1993/4000 [08:51<06:49,  4.91it/s]

train:  57%|█████▋    | 1993/3515 [08:49<05:10,  4.91it/s]
overall:  50%|████▉     | 1994/4000 [08:51<06:49,  4.90it/s]

train:  57%|█████▋    | 1994/3515 [08:49<05:10,  4.90it/s]
overall:  50%|████▉     | 1995/4000 [08:51<06:57,  4.81it/s]

train:  57%|█████▋    | 1995/3515 [08:49<05:16,  4.81it/s]
overall:  50%|████▉     | 1996/4000 [08:51<07:52,  4.24it/s]

train:  57%|█████▋    | 1996/3515 [08:49<05:58,  4.24it/s]
overall:  50%|████▉     | 1997/4000 [08:52<07:56,  4.20it/s]

train:  57%|█████▋    | 1997/3515 [08:50<06:01,  4.20it/s]
overall:  50%|████▉     | 1998/4000 [08:52<07:39,  4.36it/s]

train:  57%|█████▋    | 1998/3515 [08:50<05:47,  4.36it/s]
overall:  50%|████▉     | 1999/4000 [08:52<07:24,  4.50it/s]

train:  57%|█████▋    | 1999/3515 [08:50<05:36,  4.50it/s]dev loss: 2.243777275085449
dev per: 0.5722788761706555
[Runner] - Save the checkpoint to:
1. result/downstream/grid/dev-best.ckpt
train loss: 2.0061755180358887
train per: 0.5403036350317023
train loss: 1.9911819696426392
train per: 0.5438717787554996
train loss: 2.052217960357666
train per: 0.5458918475287251
train loss: 2.0095877647399902
train per: 0.5432298344389319
train loss: 2.044407367706299
train per: 0.5399538638985005
train loss: 2.018346071243286
train per: 0.5392308412966086
train loss: 2.0014634132385254
train per: 0.5407877688520342
train loss: 2.00580096244812
train per: 0.5333048676345005
train loss: 2.0074820518493652
train per: 0.5362232496067871
train loss: 1.9942340850830078
train per: 0.5320275415992906
train loss: 2.0205137729644775
train per: 0.5357612380930415
train loss: 1.973525047302246
train per: 0.5320757451330853
train loss: 2.0054314136505127
train per: 0.5311313591495824
train loss: 1.9714282751083374
train per: 0.5321238348868176
train loss: 1.9778398275375366
train per: 0.5305323340059576
train loss: 2.04553484916687
train per: 0.544051039789607
train loss: 2.0098519325256348
train per: 0.5354112160163804
train loss: 1.957437515258789
train per: 0.5276373488255174
train loss: 1.999406099319458
train per: 0.5316235770038638
train loss: 1.9944995641708374
train per: 0.5309581459702525
train loss: 1.9651527404785156
train per: 0.5281028434042344
train loss: 1.9713687896728516
train per: 0.5288802051532544
train loss: 1.9545589685440063
train per: 0.5345517150046352
train loss: 2.014007091522217
train per: 0.5336072582177466
train loss: 2.036628484725952
train per: 0.5456864507665022
train loss: 2.0078511238098145
train per: 0.5360900528371239
train loss: 1.9697479009628296
train per: 0.5316941367198055
train loss: 2.029865264892578
train per: 0.5403525375606294
train loss: 2.0075840950012207
train per: 0.5339833064459564
train loss: 2.021204710006714
train per: 0.5411567724620195
train loss: 1.9919612407684326
train per: 0.532127741439015
train loss: 2.0190494060516357
train per: 0.5438826876778289
train loss: 2.003619432449341
train per: 0.5326337638376384
train loss: 2.002758026123047
train per: 0.5368022899202617
train loss: 1.9578800201416016
train per: 0.5229900316188362
train loss: 1.963242769241333
train per: 0.5419142710627131
train loss: 2.019299268722534
train per: 0.5460023359524315
train loss: 1.984331488609314
train per: 0.5358463409186788
train loss: 1.9734992980957031
train per: 0.534848897359107
train loss: 2.039590358734131
train per: 0.5368136439267887
train loss: 2.0160491466522217
train per: 0.5280312907431551
train loss: 2.005643367767334
train per: 0.5354112019750038
train loss: 1.967717170715332
train per: 0.5282065325632345
train loss: 1.9400886297225952
train per: 0.5236295848448206
train loss: 1.97663152217865
train per: 0.5276829862803817
train loss: 1.9863555431365967
train per: 0.5327050255696271
train loss: 1.975252389907837
train per: 0.5296433878157504
train loss: 2.0261740684509277
train per: 0.5366662031242757
train loss: 1.9424324035644531
train per: 0.5219007673609456
train loss: 1.9777826070785522
train per: 0.5273387389567954
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  21%|██        | 566/2703 [00:00<00:00, 5649.92it/s]


word -> phonemes:  42%|████▏     | 1131/2703 [00:00<00:00, 5432.63it/s]


word -> phonemes:  62%|██████▏   | 1675/2703 [00:00<00:00, 5339.17it/s]


word -> phonemes:  82%|████████▏ | 2210/2703 [00:00<00:00, 5171.77it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 5306.60it/s]



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overall:  75%|███████▍  | 2987/4000 [14:18<03:34,  4.72it/s]

train:  85%|████████▍ | 2987/3515 [14:15<01:51,  4.72it/s]
overall:  75%|███████▍  | 2988/4000 [14:18<03:37,  4.65it/s]

train:  85%|████████▌ | 2988/3515 [14:16<01:53,  4.65it/s]
overall:  75%|███████▍  | 2989/4000 [14:18<03:38,  4.62it/s]

train:  85%|████████▌ | 2989/3515 [14:16<01:53,  4.62it/s]
overall:  75%|███████▍  | 2990/4000 [14:18<03:38,  4.62it/s]

train:  85%|████████▌ | 2990/3515 [14:16<01:53,  4.62it/s]
overall:  75%|███████▍  | 2991/4000 [14:18<03:26,  4.89it/s]

train:  85%|████████▌ | 2991/3515 [14:16<01:47,  4.89it/s]
overall:  75%|███████▍  | 2992/4000 [14:19<03:30,  4.78it/s]

train:  85%|████████▌ | 2992/3515 [14:16<01:49,  4.78it/s]
overall:  75%|███████▍  | 2993/4000 [14:19<03:31,  4.77it/s]

train:  85%|████████▌ | 2993/3515 [14:17<01:49,  4.77it/s]
overall:  75%|███████▍  | 2994/4000 [14:19<04:13,  3.96it/s]

train:  85%|████████▌ | 2994/3515 [14:17<02:11,  3.96it/s]
overall:  75%|███████▍  | 2995/4000 [14:19<04:08,  4.05it/s]

train:  85%|████████▌ | 2995/3515 [14:17<02:08,  4.05it/s]
overall:  75%|███████▍  | 2996/4000 [14:20<04:05,  4.09it/s]

train:  85%|████████▌ | 2996/3515 [14:18<02:06,  4.09it/s]
overall:  75%|███████▍  | 2997/4000 [14:20<03:57,  4.23it/s]

train:  85%|████████▌ | 2997/3515 [14:18<02:02,  4.23it/s]
overall:  75%|███████▍  | 2998/4000 [14:20<03:51,  4.33it/s]

train:  85%|████████▌ | 2998/3515 [14:18<01:59,  4.33it/s]
overall:  75%|███████▍  | 2999/4000 [14:20<03:50,  4.35it/s]

train:  85%|████████▌ | 2999/3515 [14:18<01:58,  4.35it/s]dev loss: 2.234469413757324
dev per: 0.5697970863683662
[Runner] - Save the checkpoint to:
1. result/downstream/grid/dev-best.ckpt
train loss: 1.9277986288070679
train per: 0.5266417167012197
train loss: 1.9415581226348877
train per: 0.5372563057605463
train loss: 1.9748541116714478
train per: 0.5294117647058824
train loss: 1.99698805809021
train per: 0.5323707059267648
train loss: 1.9491617679595947
train per: 0.5237976451806027
train loss: 1.9530891180038452
train per: 0.5221541497441545
train loss: 1.9829413890838623
train per: 0.5259504209761017
train loss: 2.0149903297424316
train per: 0.536415770609319
train loss: 1.923403024673462
train per: 0.5225380908338607
train loss: 1.9634323120117188
train per: 0.527176630240697
train loss: 1.9658212661743164
train per: 0.5262822764798876
train loss: 1.9655237197875977
train per: 0.531613297980828
train loss: 2.0161354541778564
train per: 0.5426914029084687
train loss: 1.9971832036972046
train per: 0.532937037486352
train loss: 1.9221906661987305
train per: 0.523886524822695
train loss: 1.9920746088027954
train per: 0.5329680224331764
train loss: 1.9880187511444092
train per: 0.5296624812809584
train loss: 1.9647386074066162
train per: 0.5306091136909937
train loss: 1.95809805393219
train per: 0.5221310500654062
train loss: 1.9707186222076416
train per: 0.5276037234728347
train loss: 1.9504226446151733
train per: 0.5283863745402207
train loss: 2.0244967937469482
train per: 0.5364266515773094
train loss: 2.0322060585021973
train per: 0.5385137274413135
train loss: 1.9576647281646729
train per: 0.52813913367837
train loss: 1.951946496963501
train per: 0.5258629931389366
train loss: 1.9444029331207275
train per: 0.5245663362561952
train loss: 1.9314320087432861
train per: 0.5198687224045522
train loss: 1.9459903240203857
train per: 0.5239819655618975
train loss: 1.9420759677886963
train per: 0.5209892451801557
train loss: 2.017282485961914
train per: 0.530013875304233
train loss: 1.9290637969970703
train per: 0.5268811219946572
train loss: 1.9358056783676147
train per: 0.5257287444166172
train loss: 1.9513099193572998
train per: 0.5288044744814728
train loss: 1.9552990198135376
train per: 0.5307150555151758
train loss: 1.9860919713974
train per: 0.5263736263736264
train loss: 1.9416542053222656
train per: 0.5283185352671924
train loss: 1.9883196353912354
train per: 0.5386018986561459
train loss: 1.9388500452041626
train per: 0.5258269358354658
train loss: 1.9599498510360718
train per: 0.5272592278319899
train loss: 1.935908317565918
train per: 0.522372008103444
train loss: 1.912806749343872
train per: 0.5191169890120817
train loss: 1.9569470882415771
train per: 0.5314549556639908
train loss: 1.9330692291259766
train per: 0.5265308302400726
train loss: 2.006687641143799
train per: 0.5252170742268512
train loss: 1.9387187957763672
train per: 0.5253118691443657
train loss: 1.971105933189392
train per: 0.527159105111861
train loss: 1.978104829788208
train per: 0.5311968644629528
train loss: 2.0003371238708496
train per: 0.5319736514475858
train loss: 1.945408582687378
train per: 0.5284643154679256
train loss: 1.9916512966156006
train per: 0.536788637932735
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  22%|██▏       | 604/2703 [00:00<00:00, 6031.78it/s]


word -> phonemes:  45%|████▍     | 1208/2703 [00:00<00:00, 5602.00it/s]


word -> phonemes:  66%|██████▌   | 1771/2703 [00:00<00:00, 5404.48it/s]


word -> phonemes:  86%|████████▌ | 2313/2703 [00:00<00:00, 5151.60it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 5175.74it/s]



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train: 100%|██████████| 3515/3515 [18:04<00:00,  4.95it/s]403-128339-0009 Failed!!!
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/home/victor/glockenspiel/s3prl/data/LibriSpeech/train-clean-100/403/128339/403-128339-0009.flac WTF Failed!!!
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train: 100%|██████████| 3515/3515 [18:05<00:00,  3.24it/s]
dev loss: 2.2221055030822754
dev per: 0.5686524453694068
[Runner] - Save the checkpoint to:
1. result/downstream/grid/dev-best.ckpt
train loss: 1.9060137271881104
train per: 0.5198147452747528
train loss: 1.9584167003631592
train per: 0.5278914906391573
train loss: 1.9235929250717163
train per: 0.5191783489096573
train loss: 1.9306647777557373
train per: 0.5188265537577499
train loss: 1.9613096714019775
train per: 0.5242502426207778
train loss: 1.9537795782089233
train per: 0.5251091703056768
train loss: 1.919759750366211
train per: 0.5205762353296731
train loss: 1.9805456399917603
train per: 0.5254917028889796
train loss: 1.9838148355484009
train per: 0.5305380574160297
train loss: 1.9348551034927368
train per: 0.5229898720935762
train loss: 1.966418981552124
train per: 0.5273541615145769
train loss: 2.00895357131958
train per: 0.5371133777767308
train loss: 1.9222828149795532
train per: 0.5260032708516794
train loss: 1.935817003250122
train per: 0.5214234011254583
train loss: 1.9536259174346924
train per: 0.5295113335295849
train loss: 1.972792387008667
train per: 0.5273187299126986
train loss: 1.987837553024292
train per: 0.5292421746293245
train loss: 1.9614441394805908
train per: 0.5310503717666771
train loss: 1.971222162246704
train per: 0.5312631800927878
train loss: 1.9692894220352173
train per: 0.5310275498560018
train loss: 1.9737348556518555
train per: 0.5340064931491774
train loss: 1.993302583694458
train per: 0.531263777587593
train loss: 2.0034356117248535
train per: 0.5334638618944151
train loss: 1.9685032367706299
train per: 0.5333283847980997
train loss: 1.995806336402893
train per: 0.532936536054229
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.


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

word -> phonemes:  13%|█▎        | 463/3515 [00:00<00:00, 4629.25it/s]

word -> phonemes:  26%|██▋       | 926/3515 [00:00<00:00, 4536.42it/s]

word -> phonemes:  41%|████      | 1445/3515 [00:00<00:00, 4831.11it/s]

word -> phonemes:  55%|█████▍    | 1929/3515 [00:00<00:00, 4757.34it/s]

word -> phonemes:  68%|██████▊   | 2406/3515 [00:00<00:00, 4329.07it/s]

word -> phonemes:  83%|████████▎ | 2900/3515 [00:00<00:00, 4519.87it/s]

word -> phonemes:  96%|█████████▌| 3364/3515 [00:00<00:00, 4553.90it/s]
word -> phonemes: 100%|██████████| 3515/3515 [00:00<00:00, 4576.01it/s]


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train:   2%|▏         | 74/3515 [00:16<13:08,  4.36it/s]
overall:  90%|████████▉ | 3590/4000 [18:25<01:32,  4.44it/s]

train:   2%|▏         | 75/3515 [00:16<12:55,  4.44it/s]
overall:  90%|████████▉ | 3591/4000 [18:26<01:28,  4.60it/s]

train:   2%|▏         | 76/3515 [00:17<12:26,  4.60it/s]
overall:  90%|████████▉ | 3592/4000 [18:26<01:25,  4.78it/s]

train:   2%|▏         | 77/3515 [00:17<11:59,  4.78it/s]
overall:  90%|████████▉ | 3593/4000 [18:26<01:26,  4.73it/s]

train:   2%|▏         | 78/3515 [00:17<12:07,  4.73it/s]
overall:  90%|████████▉ | 3594/4000 [18:26<01:25,  4.77it/s]

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overall:  90%|████████▉ | 3595/4000 [18:26<01:23,  4.87it/s]

train:   2%|▏         | 80/3515 [00:17<11:45,  4.87it/s]
overall:  90%|████████▉ | 3596/4000 [18:27<01:21,  4.96it/s]

train:   2%|▏         | 81/3515 [00:18<11:32,  4.96it/s]
overall:  90%|████████▉ | 3597/4000 [18:27<01:23,  4.83it/s]

train:   2%|▏         | 82/3515 [00:18<11:50,  4.83it/s]
overall:  90%|████████▉ | 3598/4000 [18:27<01:22,  4.90it/s]

train:   2%|▏         | 83/3515 [00:18<11:40,  4.90it/s]
overall:  90%|████████▉ | 3599/4000 [18:27<01:21,  4.91it/s]

train:   2%|▏         | 84/3515 [00:18<11:38,  4.92it/s]
overall:  90%|█████████ | 3600/4000 [18:27<01:36,  4.14it/s]

train:   2%|▏         | 85/3515 [00:18<13:48,  4.14it/s]
overall:  90%|█████████ | 3601/4000 [18:28<01:33,  4.29it/s]

train:   2%|▏         | 86/3515 [00:19<13:19,  4.29it/s]
overall:  90%|█████████ | 3602/4000 [18:28<01:28,  4.51it/s]

train:   2%|▏         | 87/3515 [00:19<12:39,  4.51it/s]
overall:  90%|█████████ | 3603/4000 [18:28<01:29,  4.45it/s]

train:   3%|▎         | 88/3515 [00:19<12:49,  4.46it/s]
overall:  90%|█████████ | 3604/4000 [18:28<01:27,  4.52it/s]

train:   3%|▎         | 89/3515 [00:19<12:38,  4.52it/s]
overall:  90%|█████████ | 3606/4000 [18:29<01:09,  5.65it/s]

train:   3%|▎         | 91/3515 [00:20<10:06,  5.65it/s]
overall:  90%|█████████ | 3607/4000 [18:29<01:16,  5.16it/s]

train:   3%|▎         | 92/3515 [00:20<11:03,  5.16it/s]
overall:  90%|█████████ | 3608/4000 [18:29<01:12,  5.37it/s]

train:   3%|▎         | 93/3515 [00:20<10:37,  5.37it/s]
overall:  90%|█████████ | 3609/4000 [18:29<01:14,  5.25it/s]

train:   3%|▎         | 94/3515 [00:20<10:52,  5.24it/s]
overall:  90%|█████████ | 3610/4000 [18:29<01:16,  5.11it/s]

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overall:  90%|█████████ | 3611/4000 [18:30<01:22,  4.74it/s]

train:   3%|▎         | 96/3515 [00:21<12:01,  4.74it/s]
overall:  90%|█████████ | 3612/4000 [18:30<01:37,  3.96it/s]

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overall:  90%|█████████ | 3613/4000 [18:30<01:32,  4.20it/s]

train:   3%|▎         | 98/3515 [00:21<13:33,  4.20it/s]
overall:  90%|█████████ | 3614/4000 [18:30<01:28,  4.37it/s]

train:   3%|▎         | 99/3515 [00:21<13:01,  4.37it/s]
overall:  90%|█████████ | 3615/4000 [18:31<01:46,  3.62it/s]

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overall:  90%|█████████ | 3616/4000 [18:31<01:39,  3.85it/s]

train:   3%|▎         | 101/3515 [00:22<14:45,  3.86it/s]
overall:  90%|█████████ | 3617/4000 [18:31<01:35,  4.03it/s]

train:   3%|▎         | 102/3515 [00:22<14:06,  4.03it/s]
overall:  90%|█████████ | 3618/4000 [18:31<01:31,  4.16it/s]

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train:   3%|▎         | 104/3515 [00:23<13:17,  4.28it/s]
overall:  90%|█████████ | 3620/4000 [18:32<01:29,  4.24it/s]

train:   3%|▎         | 105/3515 [00:23<13:25,  4.23it/s]
overall:  91%|█████████ | 3621/4000 [18:32<01:27,  4.32it/s]

train:   3%|▎         | 106/3515 [00:23<13:09,  4.32it/s]
overall:  91%|█████████ | 3622/4000 [18:32<01:24,  4.48it/s]

train:   3%|▎         | 107/3515 [00:23<12:40,  4.48it/s]
overall:  91%|█████████ | 3623/4000 [18:33<01:22,  4.57it/s]

train:   3%|▎         | 108/3515 [00:24<12:25,  4.57it/s]
overall:  91%|█████████ | 3624/4000 [18:33<01:21,  4.60it/s]

train:   3%|▎         | 109/3515 [00:24<12:20,  4.60it/s]
overall:  91%|█████████ | 3625/4000 [18:33<01:21,  4.61it/s]

train:   3%|▎         | 110/3515 [00:24<12:19,  4.61it/s]
overall:  91%|█████████ | 3626/4000 [18:33<01:18,  4.78it/s]

train:   3%|▎         | 111/3515 [00:24<11:51,  4.78it/s]
overall:  91%|█████████ | 3627/4000 [18:34<01:28,  4.21it/s]

train:   3%|▎         | 112/3515 [00:24<13:27,  4.21it/s]
overall:  91%|█████████ | 3629/4000 [18:34<01:13,  5.05it/s]

train:   3%|▎         | 114/3515 [00:25<11:13,  5.05it/s]
overall:  91%|█████████ | 3630/4000 [18:34<01:14,  4.98it/s]

train:   3%|▎         | 115/3515 [00:25<11:22,  4.98it/s]
overall:  91%|█████████ | 3631/4000 [18:34<01:14,  4.97it/s]

train:   3%|▎         | 116/3515 [00:25<11:23,  4.97it/s]
overall:  91%|█████████ | 3632/4000 [18:34<01:14,  4.92it/s]

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overall:  91%|█████████ | 3633/4000 [18:35<01:16,  4.83it/s]

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overall:  91%|█████████ | 3634/4000 [18:35<01:18,  4.67it/s]

train:   3%|▎         | 119/3515 [00:26<12:07,  4.67it/s]
overall:  91%|█████████ | 3635/4000 [18:35<01:18,  4.67it/s]

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overall:  91%|█████████ | 3636/4000 [18:35<01:17,  4.71it/s]

train:   3%|▎         | 121/3515 [00:26<12:00,  4.71it/s]
overall:  91%|█████████ | 3637/4000 [18:36<01:18,  4.65it/s]

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overall:  91%|█████████ | 3638/4000 [18:36<01:17,  4.69it/s]

train:   3%|▎         | 123/3515 [00:27<12:03,  4.69it/s]
overall:  91%|█████████ | 3639/4000 [18:36<01:37,  3.71it/s]

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overall:  91%|█████████ | 3640/4000 [18:36<01:32,  3.90it/s]

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overall:  91%|█████████ | 3641/4000 [18:37<01:27,  4.09it/s]

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overall:  91%|█████████ | 3642/4000 [18:37<01:24,  4.25it/s]

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overall:  91%|█████████ | 3644/4000 [18:37<01:18,  4.51it/s]

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overall:  91%|█████████ | 3645/4000 [18:37<01:17,  4.55it/s]

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overall:  91%|█████████ | 3647/4000 [18:38<01:09,  5.05it/s]

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overall: 100%|█████████▉| 3994/4000 [19:52<00:01,  5.24it/s]

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overall: 100%|█████████▉| 3999/4000 [19:53<00:00,  5.09it/s]

train:  14%|█▍        | 484/3515 [01:44<09:55,  5.09it/s]train loss: 1.973049521446228
train per: 0.529066234555398
train loss: 1.9409780502319336
train per: 0.5296584257884162
train loss: 1.9433656930923462
train per: 0.5252653819718454
train loss: 2.0101613998413086
train per: 0.5313475177304965
train loss: 1.972036361694336
train per: 0.534016279128737
train loss: 1.964167594909668
train per: 0.5277116205219807
train loss: 1.9801626205444336
train per: 0.5256224899598394
train loss: 1.9468224048614502
train per: 0.5277962121598857
train loss: 1.9567620754241943
train per: 0.5377267169349909
train loss: 1.964858055114746
train per: 0.53567556404564
train loss: 1.9730355739593506
train per: 0.5312199057806929
train loss: 2.0096142292022705
train per: 0.532284694332887
train loss: 1.9279568195343018
train per: 0.5212098298676748
train loss: 1.9640239477157593
train per: 0.5254117831319011
train loss: 2.0022168159484863
train per: 0.5341578176021392
train loss: 1.9370739459991455
train per: 0.5249701678218701
train loss: 1.9426791667938232
train per: 0.528249839909364
train loss: 1.9577211141586304
train per: 0.5290202975709464
train loss: 1.9655624628067017
train per: 0.5288646568313021
train loss: 1.9436832666397095
train per: 0.5212291155508821
train loss: 1.9497621059417725
train per: 0.5292022792022792
train loss: 1.9637359380722046
train per: 0.5238914626075447
train loss: 1.963619589805603
train per: 0.5298968089416363
train loss: 1.945389986038208
train per: 0.5228068469169422
train loss: 1.9422416687011719
train per: 0.518923069302026
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  21%|██        | 565/2703 [00:00<00:00, 5645.58it/s]


word -> phonemes:  42%|████▏     | 1130/2703 [00:00<00:00, 5206.84it/s]


word -> phonemes:  63%|██████▎   | 1708/2703 [00:00<00:00, 5454.89it/s]


word -> phonemes:  83%|████████▎ | 2256/2703 [00:00<00:00, 5282.05it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 5346.57it/s]



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overall: 100%|█████████▉| 3999/4000 [21:52<00:00,  5.09it/s]

train:  14%|█▍        | 484/3515 [03:43<09:55,  5.09it/s]
                                                            

                                                         

overall: 100%|█████████▉| 3999/4000 [21:52<00:00,  5.09it/s]

train:  14%|█▍        | 484/3515 [03:43<09:55,  5.09it/s]
overall: 100%|██████████| 4000/4000 [21:52<00:00, 32.39s/it]

train:  14%|█▍        | 485/3515 [03:43<27:15:54, 32.39s/it]403-128339-0009 Failed!!!

train:  14%|█▍        | 485/3515 [03:44<23:20,  2.16it/s]   

overall: 100%|██████████| 4000/4000 [21:53<00:00,  3.05it/s]
dev loss: 2.242807388305664
dev per: 0.5706191467221644
[Runner] - Save the checkpoint to:
1. result/downstream/grid/states-4000.ckpt