/home/tony/Work/glockenspiel/s3prl/s3prl/upstream/byol_s/byol_a/common.py:20: UserWarning: torchaudio._backend.set_audio_backend has been deprecated. With dispatcher enabled, this function is no-op. You can remove the function call.
  torchaudio.set_audio_backend("sox_io")
/home/tony/Work/glockenspiel/s3prl/s3prl/run_downstream.py:157: UserWarning: torchaudio._backend.set_audio_backend has been deprecated. With dispatcher enabled, this function is no-op. You can remove the function call.
  torchaudio.set_audio_backend('sox_io')
[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_speech_test {'model_config': None, 'refresh': False}
Loading model from Local mert_speech_test
load local model succeed
load local feat extractor
Wav2Vec2FeatureExtractor {
  "do_normalize": false,
  "feature_extractor_type": "Wav2Vec2FeatureExtractor",
  "feature_size": 1,
  "padding_side": "right",
  "padding_value": 0,
  "return_attention_mask": true,
  "sampling_rate": 24000
}


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


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

word -> phonemes:  10%|█         | 352/3515 [00:00<00:00, 3407.59it/s]

word -> phonemes:  22%|██▏       | 783/3515 [00:00<00:00, 3930.52it/s]

word -> phonemes:  35%|███▌      | 1237/3515 [00:00<00:00, 4205.96it/s]

word -> phonemes:  47%|████▋     | 1659/3515 [00:00<00:00, 3909.11it/s]

word -> phonemes:  60%|██████    | 2114/3515 [00:00<00:00, 4127.41it/s]

word -> phonemes:  72%|███████▏  | 2530/3515 [00:00<00:00, 4015.45it/s]

word -> phonemes:  84%|████████▎ | 2941/3515 [00:00<00:00, 4029.99it/s]

word -> phonemes:  95%|█████████▌| 3346/3515 [00:00<00:00, 3884.94it/s]
word -> phonemes: 100%|██████████| 3515/3515 [00:00<00:00, 3962.41it/s]


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train:   5%|▍         | 159/3515 [00:34<11:48,  4.74it/s]
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train:   5%|▌         | 185/3515 [00:39<10:53,  5.09it/s]
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train:   5%|▌         | 186/3515 [00:39<11:09,  4.98it/s]
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train:   5%|▌         | 187/3515 [00:40<11:15,  4.93it/s]
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train:   5%|▌         | 188/3515 [00:40<11:14,  4.93it/s]
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overall:  11%|█         | 422/4000 [01:32<15:12,  3.92it/s]

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overall:  13%|█▎        | 508/4000 [01:51<10:27,  5.57it/s]

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overall:  13%|█▎        | 531/4000 [01:56<12:00,  4.81it/s]

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overall:  13%|█▎        | 533/4000 [01:57<12:03,  4.79it/s]

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overall:  13%|█▎        | 535/4000 [01:57<14:35,  3.96it/s]

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overall:  14%|█▎        | 541/4000 [01:58<12:22,  4.66it/s]

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overall:  14%|█▎        | 543/4000 [01:59<12:25,  4.64it/s]

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overall:  14%|█▎        | 545/4000 [01:59<12:16,  4.69it/s]

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overall:  14%|█▎        | 546/4000 [01:59<12:29,  4.61it/s]

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overall:  14%|█▎        | 547/4000 [02:00<13:48,  4.17it/s]

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overall:  14%|█▎        | 548/4000 [02:00<13:11,  4.36it/s]

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overall:  14%|█▎        | 549/4000 [02:00<12:52,  4.47it/s]

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overall:  14%|█▍        | 550/4000 [02:00<12:20,  4.66it/s]

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overall:  14%|█▍        | 552/4000 [02:01<12:18,  4.67it/s]

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overall:  14%|█▍        | 553/4000 [02:01<12:12,  4.70it/s]

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overall:  14%|█▍        | 554/4000 [02:01<12:23,  4.63it/s]

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overall:  14%|█▍        | 555/4000 [02:01<12:23,  4.63it/s]

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overall:  14%|█▍        | 556/4000 [02:02<12:24,  4.63it/s]

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overall:  14%|█▍        | 561/4000 [02:03<14:19,  4.00it/s]

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overall:  14%|█▍        | 562/4000 [02:03<13:32,  4.23it/s]

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overall:  14%|█▍        | 565/4000 [02:04<13:28,  4.25it/s]

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overall:  14%|█▍        | 566/4000 [02:04<13:14,  4.32it/s]

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overall:  14%|█▍        | 567/4000 [02:04<11:47,  4.85it/s]

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overall:  14%|█▍        | 568/4000 [02:04<11:57,  4.79it/s]

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overall:  14%|█▍        | 569/4000 [02:05<12:08,  4.71it/s]

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overall:  14%|█▍        | 571/4000 [02:05<10:45,  5.31it/s]

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overall:  14%|█▍        | 574/4000 [02:05<11:12,  5.09it/s]

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overall:  14%|█▍        | 575/4000 [02:06<10:18,  5.54it/s]

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train:  28%|██▊       | 988/3515 [03:31<08:56,  4.71it/s]
overall:  25%|██▍       | 989/4000 [03:34<10:35,  4.74it/s]

train:  28%|██▊       | 989/3515 [03:32<08:52,  4.74it/s]
overall:  25%|██▍       | 990/4000 [03:34<10:23,  4.83it/s]

train:  28%|██▊       | 990/3515 [03:32<08:43,  4.83it/s]
overall:  25%|██▍       | 991/4000 [03:34<14:00,  3.58it/s]

train:  28%|██▊       | 991/3515 [03:32<11:44,  3.58it/s]
overall:  25%|██▍       | 992/4000 [03:35<12:58,  3.86it/s]

train:  28%|██▊       | 992/3515 [03:33<10:53,  3.86it/s]
overall:  25%|██▍       | 993/4000 [03:35<12:32,  4.00it/s]

train:  28%|██▊       | 993/3515 [03:33<10:30,  4.00it/s]
overall:  25%|██▍       | 994/4000 [03:35<11:46,  4.26it/s]

train:  28%|██▊       | 994/3515 [03:33<09:52,  4.26it/s]
overall:  25%|██▍       | 995/4000 [03:35<11:32,  4.34it/s]

train:  28%|██▊       | 995/3515 [03:33<09:40,  4.34it/s]
overall:  25%|██▍       | 996/4000 [03:36<11:14,  4.45it/s]

train:  28%|██▊       | 996/3515 [03:33<09:25,  4.45it/s]
overall:  25%|██▍       | 997/4000 [03:36<11:16,  4.44it/s]

train:  28%|██▊       | 997/3515 [03:34<09:27,  4.44it/s]
overall:  25%|██▍       | 998/4000 [03:36<11:10,  4.48it/s]

train:  28%|██▊       | 998/3515 [03:34<09:22,  4.47it/s]
overall:  25%|██▍       | 999/4000 [03:36<10:42,  4.67it/s]

train:  28%|██▊       | 999/3515 [03:34<08:58,  4.67it/s]train loss: 3.5034782886505127
train per: 0.8149527202593019
train loss: 2.538498878479004
train per: 0.6561980512007366
train loss: 2.404635190963745
train per: 0.6292344832956935
train loss: 2.357738971710205
train per: 0.6140467035065827
train loss: 2.329005002975464
train per: 0.6102289083902122
train loss: 2.283956527709961
train per: 0.6097606883570852
train loss: 2.2437891960144043
train per: 0.5950092691969948
train loss: 2.3099491596221924
train per: 0.5994737961092803
train loss: 2.205730676651001
train per: 0.5846430830616515
train loss: 2.193725109100342
train per: 0.5827898054261441
train loss: 2.20965576171875
train per: 0.5956662541797214
train loss: 2.2105109691619873
train per: 0.5866366068774155
train loss: 2.2531371116638184
train per: 0.5956675300211914
train loss: 2.2053773403167725
train per: 0.5788672146200533
train loss: 2.154019594192505
train per: 0.5731204822113913
train loss: 2.178528308868408
train per: 0.5798976268031643
train loss: 2.146225690841675
train per: 0.5771623827009384
train loss: 2.159674882888794
train per: 0.5793786179703012
train loss: 2.1909422874450684
train per: 0.5813524307946564
train loss: 2.1318817138671875
train per: 0.5750717486531394
train loss: 2.122861862182617
train per: 0.5644282226442082
train loss: 2.1619279384613037
train per: 0.5725909741580653
train loss: 2.1728947162628174
train per: 0.5691290790109359
train loss: 2.1752991676330566
train per: 0.5752611985108682
train loss: 2.1527037620544434
train per: 0.5649605421552455
train loss: 2.1012747287750244
train per: 0.5644157520981278
train loss: 2.154928684234619
train per: 0.5721855283911672
train loss: 2.1161856651306152
train per: 0.567265851046864
train loss: 2.11344313621521
train per: 0.5642842204329186
train loss: 2.1246092319488525
train per: 0.5703925624747367
train loss: 2.155320167541504
train per: 0.5685568124504647
train loss: 2.107278347015381
train per: 0.5641747905746338
train loss: 2.1294150352478027
train per: 0.5673183410554865
train loss: 2.1274585723876953
train per: 0.5646536042825216
train loss: 2.1083693504333496
train per: 0.5669192607534209
train loss: 2.106398105621338
train per: 0.5716707587980825
train loss: 2.1799750328063965
train per: 0.5697063514400976
train loss: 2.1548826694488525
train per: 0.5672210171125572
train loss: 2.1341397762298584
train per: 0.5659310954931931
train loss: 2.134761333465576
train per: 0.566396486884212
train loss: 2.1061606407165527
train per: 0.5687317977230606
train loss: 2.1149332523345947
train per: 0.5625921677863346
train loss: 2.1130239963531494
train per: 0.5616164207825529
train loss: 2.139763593673706
train per: 0.570425204012026
train loss: 2.0967602729797363
train per: 0.5587738110256086
train loss: 2.096205234527588
train per: 0.5584133516232281
train loss: 2.1295809745788574
train per: 0.5674250258531541
train loss: 2.1246867179870605
train per: 0.5687751410599066
train loss: 2.1063807010650635
train per: 0.5623820507443908
train loss: 2.0855422019958496
train per: 0.5574029695876671
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  16%|█▌        | 437/2703 [00:00<00:00, 4298.18it/s]


word -> phonemes:  32%|███▏      | 871/2703 [00:00<00:00, 4320.62it/s]


word -> phonemes:  48%|████▊     | 1304/2703 [00:00<00:00, 3889.11it/s]


word -> phonemes:  68%|██████▊   | 1830/2703 [00:00<00:00, 4391.90it/s]


word -> phonemes:  84%|████████▍ | 2276/2703 [00:00<00:00, 4297.47it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 4162.47it/s]



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overall:  48%|████▊     | 1924/4000 [08:56<07:38,  4.53it/s]

train:  55%|█████▍    | 1924/3515 [08:53<05:51,  4.53it/s]
overall:  48%|████▊     | 1925/4000 [08:56<07:05,  4.87it/s]

train:  55%|█████▍    | 1925/3515 [08:54<05:26,  4.87it/s]
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train:  55%|█████▍    | 1926/3515 [08:54<05:27,  4.86it/s]
overall:  48%|████▊     | 1927/4000 [08:56<07:09,  4.82it/s]

train:  55%|█████▍    | 1927/3515 [08:54<05:29,  4.82it/s]
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train:  55%|█████▍    | 1929/3515 [08:54<04:50,  5.45it/s]
overall:  48%|████▊     | 1930/4000 [08:57<06:48,  5.07it/s]

train:  55%|█████▍    | 1930/3515 [08:55<05:12,  5.07it/s]
overall:  48%|████▊     | 1931/4000 [08:57<07:02,  4.90it/s]

train:  55%|█████▍    | 1931/3515 [08:55<05:23,  4.90it/s]
overall:  48%|████▊     | 1932/4000 [08:57<07:11,  4.80it/s]

train:  55%|█████▍    | 1932/3515 [08:55<05:30,  4.80it/s]
overall:  48%|████▊     | 1933/4000 [08:57<07:24,  4.65it/s]

train:  55%|█████▍    | 1933/3515 [08:55<05:40,  4.65it/s]
overall:  48%|████▊     | 1934/4000 [08:58<07:30,  4.58it/s]

train:  55%|█████▌    | 1934/3515 [08:55<05:44,  4.58it/s]
overall:  48%|████▊     | 1935/4000 [08:58<07:40,  4.49it/s]

train:  55%|█████▌    | 1935/3515 [08:56<05:52,  4.49it/s]
overall:  48%|████▊     | 1936/4000 [08:58<06:37,  5.19it/s]

train:  55%|█████▌    | 1936/3515 [08:56<05:04,  5.19it/s]
overall:  48%|████▊     | 1937/4000 [08:58<06:41,  5.14it/s]

train:  55%|█████▌    | 1937/3515 [08:56<05:06,  5.14it/s]
overall:  48%|████▊     | 1938/4000 [08:58<06:45,  5.08it/s]

train:  55%|█████▌    | 1938/3515 [08:56<05:10,  5.08it/s]
overall:  48%|████▊     | 1939/4000 [08:59<11:06,  3.09it/s]

train:  55%|█████▌    | 1939/3515 [08:57<08:29,  3.09it/s]
overall:  48%|████▊     | 1940/4000 [08:59<10:02,  3.42it/s]

train:  55%|█████▌    | 1940/3515 [08:57<07:40,  3.42it/s]
overall:  49%|████▊     | 1941/4000 [08:59<09:28,  3.62it/s]

train:  55%|█████▌    | 1941/3515 [08:57<07:14,  3.62it/s]
overall:  49%|████▊     | 1942/4000 [09:00<08:49,  3.88it/s]

train:  55%|█████▌    | 1942/3515 [08:58<06:44,  3.89it/s]
overall:  49%|████▊     | 1943/4000 [09:00<08:22,  4.09it/s]

train:  55%|█████▌    | 1943/3515 [08:58<06:24,  4.09it/s]
overall:  49%|████▊     | 1944/4000 [09:00<06:57,  4.93it/s]

train:  55%|█████▌    | 1944/3515 [08:58<05:18,  4.93it/s]
overall:  49%|████▊     | 1945/4000 [09:00<07:05,  4.83it/s]

train:  55%|█████▌    | 1945/3515 [08:58<05:25,  4.83it/s]
overall:  49%|████▊     | 1946/4000 [09:00<07:11,  4.77it/s]

train:  55%|█████▌    | 1946/3515 [08:58<05:29,  4.77it/s]
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train:  55%|█████▌    | 1948/3515 [08:59<04:51,  5.37it/s]
overall:  49%|████▊     | 1949/4000 [09:01<06:39,  5.14it/s]

train:  55%|█████▌    | 1949/3515 [08:59<05:04,  5.14it/s]
overall:  49%|████▉     | 1950/4000 [09:01<06:56,  4.92it/s]

train:  55%|█████▌    | 1950/3515 [08:59<05:17,  4.92it/s]
overall:  49%|████▉     | 1951/4000 [09:01<07:06,  4.81it/s]

train:  56%|█████▌    | 1951/3515 [08:59<05:25,  4.81it/s]
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train:  56%|█████▌    | 1952/3515 [08:59<05:25,  4.80it/s]
overall:  49%|████▉     | 1953/4000 [09:02<07:11,  4.74it/s]

train:  56%|█████▌    | 1953/3515 [09:00<05:29,  4.74it/s]
overall:  49%|████▉     | 1954/4000 [09:02<07:21,  4.63it/s]

train:  56%|█████▌    | 1954/3515 [09:00<05:36,  4.63it/s]
overall:  49%|████▉     | 1955/4000 [09:02<07:11,  4.74it/s]

train:  56%|█████▌    | 1955/3515 [09:00<05:29,  4.74it/s]
overall:  49%|████▉     | 1956/4000 [09:02<07:04,  4.81it/s]

train:  56%|█████▌    | 1956/3515 [09:00<05:23,  4.82it/s]
overall:  49%|████▉     | 1957/4000 [09:03<07:22,  4.61it/s]

train:  56%|█████▌    | 1957/3515 [09:01<05:37,  4.61it/s]
overall:  49%|████▉     | 1958/4000 [09:03<07:24,  4.59it/s]

train:  56%|█████▌    | 1958/3515 [09:01<05:38,  4.59it/s]
overall:  49%|████▉     | 1959/4000 [09:03<07:18,  4.66it/s]

train:  56%|█████▌    | 1959/3515 [09:01<05:34,  4.66it/s]
overall:  49%|████▉     | 1960/4000 [09:03<07:18,  4.65it/s]

train:  56%|█████▌    | 1960/3515 [09:01<05:34,  4.65it/s]
overall:  49%|████▉     | 1961/4000 [09:04<07:28,  4.55it/s]

train:  56%|█████▌    | 1961/3515 [09:01<05:41,  4.55it/s]
overall:  49%|████▉     | 1962/4000 [09:04<07:33,  4.49it/s]

train:  56%|█████▌    | 1962/3515 [09:02<05:45,  4.49it/s]
overall:  49%|████▉     | 1963/4000 [09:04<11:56,  2.84it/s]

train:  56%|█████▌    | 1963/3515 [09:02<09:05,  2.84it/s]
overall:  49%|████▉     | 1964/4000 [09:05<10:28,  3.24it/s]

train:  56%|█████▌    | 1964/3515 [09:03<07:58,  3.24it/s]
overall:  49%|████▉     | 1965/4000 [09:05<09:57,  3.41it/s]

train:  56%|█████▌    | 1965/3515 [09:03<07:34,  3.41it/s]
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train:  56%|█████▌    | 1966/3515 [09:03<06:51,  3.77it/s]
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train:  56%|█████▌    | 1967/3515 [09:03<06:16,  4.11it/s]
overall:  49%|████▉     | 1968/4000 [09:05<07:40,  4.42it/s]

train:  56%|█████▌    | 1968/3515 [09:03<05:50,  4.42it/s]
overall:  49%|████▉     | 1969/4000 [09:06<08:19,  4.07it/s]

train:  56%|█████▌    | 1969/3515 [09:04<06:20,  4.07it/s]
overall:  49%|████▉     | 1970/4000 [09:06<08:06,  4.17it/s]

train:  56%|█████▌    | 1970/3515 [09:04<06:10,  4.17it/s]
overall:  49%|████▉     | 1971/4000 [09:06<07:52,  4.29it/s]

train:  56%|█████▌    | 1971/3515 [09:04<05:59,  4.29it/s]
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train:  56%|█████▌    | 1972/3515 [09:04<05:47,  4.44it/s]
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train:  56%|█████▌    | 1973/3515 [09:05<05:41,  4.51it/s]
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train:  56%|█████▌    | 1974/3515 [09:05<05:39,  4.54it/s]
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train:  56%|█████▌    | 1975/3515 [09:05<05:41,  4.50it/s]
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train:  56%|█████▌    | 1976/3515 [09:05<05:38,  4.55it/s]
overall:  49%|████▉     | 1977/4000 [09:08<07:30,  4.49it/s]

train:  56%|█████▌    | 1977/3515 [09:05<05:42,  4.49it/s]
overall:  49%|████▉     | 1978/4000 [09:08<07:22,  4.57it/s]

train:  56%|█████▋    | 1978/3515 [09:06<05:36,  4.57it/s]
overall:  49%|████▉     | 1979/4000 [09:08<06:49,  4.94it/s]

train:  56%|█████▋    | 1979/3515 [09:06<05:10,  4.94it/s]
overall:  50%|████▉     | 1980/4000 [09:08<07:02,  4.78it/s]

train:  56%|█████▋    | 1980/3515 [09:06<05:20,  4.78it/s]
overall:  50%|████▉     | 1981/4000 [09:08<06:34,  5.12it/s]

train:  56%|█████▋    | 1981/3515 [09:06<04:59,  5.12it/s]
overall:  50%|████▉     | 1982/4000 [09:08<06:32,  5.14it/s]

train:  56%|█████▋    | 1982/3515 [09:06<04:58,  5.14it/s]
overall:  50%|████▉     | 1984/4000 [09:09<06:01,  5.58it/s]

train:  56%|█████▋    | 1984/3515 [09:07<04:34,  5.58it/s]
overall:  50%|████▉     | 1985/4000 [09:09<06:23,  5.25it/s]

train:  56%|█████▋    | 1985/3515 [09:07<04:51,  5.25it/s]
overall:  50%|████▉     | 1986/4000 [09:09<05:40,  5.91it/s]

train:  57%|█████▋    | 1986/3515 [09:07<04:18,  5.91it/s]
overall:  50%|████▉     | 1987/4000 [09:10<08:53,  3.77it/s]

train:  57%|█████▋    | 1987/3515 [09:08<06:44,  3.77it/s]
overall:  50%|████▉     | 1988/4000 [09:10<08:30,  3.94it/s]

train:  57%|█████▋    | 1988/3515 [09:08<06:27,  3.94it/s]
overall:  50%|████▉     | 1989/4000 [09:10<08:31,  3.93it/s]

train:  57%|█████▋    | 1989/3515 [09:08<06:28,  3.93it/s]
overall:  50%|████▉     | 1990/4000 [09:10<08:16,  4.05it/s]

train:  57%|█████▋    | 1990/3515 [09:08<06:16,  4.05it/s]
overall:  50%|████▉     | 1991/4000 [09:11<08:04,  4.14it/s]

train:  57%|█████▋    | 1991/3515 [09:08<06:07,  4.14it/s]
overall:  50%|████▉     | 1992/4000 [09:11<07:03,  4.74it/s]

train:  57%|█████▋    | 1992/3515 [09:09<05:21,  4.74it/s]
overall:  50%|████▉     | 1993/4000 [09:11<07:59,  4.18it/s]

train:  57%|█████▋    | 1993/3515 [09:09<06:03,  4.18it/s]
overall:  50%|████▉     | 1994/4000 [09:11<07:44,  4.32it/s]

train:  57%|█████▋    | 1994/3515 [09:09<05:52,  4.32it/s]
overall:  50%|████▉     | 1995/4000 [09:11<07:37,  4.38it/s]

train:  57%|█████▋    | 1995/3515 [09:09<05:46,  4.38it/s]
overall:  50%|████▉     | 1996/4000 [09:12<07:26,  4.49it/s]

train:  57%|█████▋    | 1996/3515 [09:10<05:38,  4.49it/s]
overall:  50%|████▉     | 1997/4000 [09:12<07:24,  4.51it/s]

train:  57%|█████▋    | 1997/3515 [09:10<05:36,  4.51it/s]
overall:  50%|████▉     | 1998/4000 [09:12<07:17,  4.57it/s]

train:  57%|█████▋    | 1998/3515 [09:10<05:31,  4.57it/s]
overall:  50%|████▉     | 1999/4000 [09:12<07:18,  4.56it/s]

train:  57%|█████▋    | 1999/3515 [09:10<05:32,  4.56it/s]dev loss: 2.3559067249298096
dev per: 0.5950312174817898
[Runner] - Save the checkpoint to:
1. result/downstream/grid/dev-best.ckpt
train loss: 2.0999038219451904
train per: 0.5616237653775229
train loss: 2.081334352493286
train per: 0.5652419861722188
train loss: 2.1458587646484375
train per: 0.5667061827466715
train loss: 2.0964722633361816
train per: 0.5671163387033837
train loss: 2.1411168575286865
train per: 0.562722029988466
train loss: 2.111041307449341
train per: 0.5590687652239086
train loss: 2.082040309906006
train per: 0.5569318476289195
train loss: 2.0990498065948486
train per: 0.5591751645149947
train loss: 2.0837175846099854
train per: 0.5568609694485487
train loss: 2.0768837928771973
train per: 0.5548484690417819
train loss: 2.12496018409729
train per: 0.5593560440067348
train loss: 2.069749116897583
train per: 0.5530167624752428
train loss: 2.1153812408447266
train per: 0.5586180713743356
train loss: 2.0746822357177734
train per: 0.5550099866844208
train loss: 2.0854358673095703
train per: 0.5586384164504661
train loss: 2.1362671852111816
train per: 0.5650659913310281
train loss: 2.1013383865356445
train per: 0.5584347628256171
train loss: 2.0582385063171387
train per: 0.5555679691645952
train loss: 2.109632968902588
train per: 0.5618598138111661
train loss: 2.0995967388153076
train per: 0.5578461893231869
train loss: 2.0664045810699463
train per: 0.555408356026594
train loss: 2.0607056617736816
train per: 0.5507143729393088
train loss: 2.0486679077148438
train per: 0.5565355582042114
train loss: 2.0971765518188477
train per: 0.5561941858255748
train loss: 2.1284191608428955
train per: 0.5678433468574622
train loss: 2.1070072650909424
train per: 0.5616586262347806
train loss: 2.0855329036712646
train per: 0.5578762496622535
train loss: 2.133330821990967
train per: 0.5679876966757365
train loss: 2.1026968955993652
train per: 0.5583456080054242
train loss: 2.1077961921691895
train per: 0.5600423509713639
train loss: 2.08243465423584
train per: 0.5562395793253816
train loss: 2.1172239780426025
train per: 0.5673500158070086
train loss: 2.1098084449768066
train per: 0.5603782287822878
train loss: 2.1120495796203613
train per: 0.5685442649764875
train loss: 2.0608954429626465
train per: 0.5516642127875262
train loss: 2.0648505687713623
train per: 0.5647190130011162
train loss: 2.1195552349090576
train per: 0.572095986409004
train loss: 2.08417010307312
train per: 0.5615554507779735
train loss: 2.0690255165100098
train per: 0.5571195208276614
train loss: 2.1443982124328613
train per: 0.5652847106674062
train loss: 2.109830617904663
train per: 0.5554331699860631
train loss: 2.12140154838562
train per: 0.5629532479555625
train loss: 2.0748674869537354
train per: 0.5528530173272257
train loss: 2.0485453605651855
train per: 0.5493752519145506
train loss: 2.073495626449585
train per: 0.5524990133946189
train loss: 2.0852444171905518
train per: 0.5583282015582747
train loss: 2.0644898414611816
train per: 0.5536651807825657
train loss: 2.127941608428955
train per: 0.5623000973439021
train loss: 2.04606032371521
train per: 0.5482579476669368
train loss: 2.0814452171325684
train per: 0.5528016458913227
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  14%|█▍        | 386/2703 [00:00<00:00, 3857.34it/s]


word -> phonemes:  30%|███       | 815/2703 [00:00<00:00, 4103.82it/s]


word -> phonemes:  45%|████▌     | 1226/2703 [00:00<00:00, 3976.60it/s]


word -> phonemes:  63%|██████▎   | 1710/2703 [00:00<00:00, 4310.01it/s]


word -> phonemes:  80%|███████▉  | 2157/2703 [00:00<00:00, 4366.60it/s]


word -> phonemes:  96%|█████████▋| 2605/2703 [00:00<00:00, 4384.00it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 4144.81it/s]



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


dev:   0%|          | 1/2703 [00:01<53:59,  1.20s/it]


dev:   0%|          | 2/2703 [00:01<24:53,  1.81it/s]


dev:   0%|          | 4/2703 [00:01<11:02,  4.07it/s]


dev:   0%|          | 6/2703 [00:01<07:15,  6.19it/s]


dev:   0%|          | 8/2703 [00:01<05:33,  8.08it/s]


dev:   0%|          | 10/2703 [00:01<04:47,  9.36it/s]


dev:   0%|          | 12/2703 [00:02<04:26, 10.11it/s]


dev:   1%|          | 14/2703 [00:02<04:17, 10.45it/s]


dev:   1%|          | 16/2703 [00:02<03:53, 11.53it/s]


dev:   1%|          | 18/2703 [00:02<03:37, 12.32it/s]


dev:   1%|          | 20/2703 [00:02<03:17, 13.62it/s]


dev:   1%|          | 22/2703 [00:02<03:13, 13.88it/s]


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dev:   1%|          | 30/2703 [00:03<02:58, 14.99it/s]


dev:   1%|          | 32/2703 [00:03<03:03, 14.56it/s]


dev:   1%|▏         | 34/2703 [00:03<03:00, 14.78it/s]


dev:   1%|▏         | 36/2703 [00:03<02:51, 15.58it/s]


dev:   1%|▏         | 38/2703 [00:03<02:44, 16.24it/s]


dev:   1%|▏         | 40/2703 [00:03<02:40, 16.61it/s]


dev:   2%|▏         | 42/2703 [00:03<02:41, 16.43it/s]


dev:   2%|▏         | 44/2703 [00:04<02:48, 15.82it/s]


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dev:   2%|▏         | 48/2703 [00:04<02:48, 15.75it/s]


dev:   2%|▏         | 50/2703 [00:04<02:45, 16.08it/s]


dev:   2%|▏         | 52/2703 [00:04<02:50, 15.57it/s]


dev:   2%|▏         | 54/2703 [00:04<02:44, 16.13it/s]


dev:   2%|▏         | 56/2703 [00:04<02:37, 16.79it/s]


dev:   2%|▏         | 58/2703 [00:04<02:37, 16.84it/s]


dev:   2%|▏         | 60/2703 [00:05<02:33, 17.21it/s]


dev:   2%|▏         | 62/2703 [00:05<02:32, 17.35it/s]


dev:   2%|▏         | 64/2703 [00:05<02:42, 16.25it/s]


dev:   2%|▏         | 66/2703 [00:05<02:47, 15.71it/s]


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train:  85%|████████▌ | 2995/3515 [14:52<02:17,  3.78it/s]
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train:  85%|████████▌ | 2999/3515 [14:52<01:59,  4.31it/s]dev loss: 2.3651647567749023
dev per: 0.602585848074922
train loss: 2.035947322845459
train per: 0.5524083896502517
train loss: 2.0361762046813965
train per: 0.5568895252781143
train loss: 2.0678019523620605
train per: 0.5518415803045784
train loss: 2.096086025238037
train per: 0.555185919214798
train loss: 2.0554256439208984
train per: 0.5511125523847535
train loss: 2.0549941062927246
train per: 0.5470962116518666
train loss: 2.0887551307678223
train per: 0.5521001899669317
train loss: 2.099998950958252
train per: 0.5583512544802868
train loss: 2.018843173980713
train per: 0.5474857615732853
train loss: 2.0533201694488525
train per: 0.5448182272694807
train loss: 2.0622153282165527
train per: 0.5495564728614087
train loss: 2.0712897777557373
train per: 0.5548133795635325
train loss: 2.1178200244903564
train per: 0.5648791702309667
train loss: 2.0827107429504395
train per: 0.5556229528084435
train loss: 2.035033702850342
train per: 0.5530780141843972
train loss: 2.099261522293091
train per: 0.5560958040698721
train loss: 2.097851037979126
train per: 0.5586453173597512
train loss: 2.065765857696533
train per: 0.5539047716462947
train loss: 2.05920147895813
train per: 0.5476751100011892
train loss: 2.0650227069854736
train per: 0.5501405327351022
train loss: 2.0488369464874268
train per: 0.5490964337118184
train loss: 2.1246678829193115
train per: 0.5653086245107748
train loss: 2.123378038406372
train per: 0.560563571396264
train loss: 2.0604166984558105
train per: 0.5513824777358138
train loss: 2.043401002883911
train per: 0.5543256861063465
train loss: 2.041111946105957
train per: 0.5479651162790697
train loss: 2.0271553993225098
train per: 0.5437867447406323
train loss: 2.041778326034546
train per: 0.5494747949541945
train loss: 2.0480005741119385
train per: 0.5474302423551569
train loss: 2.1152122020721436
train per: 0.5608807406227965
train loss: 2.0360231399536133
train per: 0.5513134461264471
train loss: 2.031432628631592
train per: 0.5478299036947148
train loss: 2.053800344467163
train per: 0.5507573992076439
train loss: 2.0599122047424316
train per: 0.5557532770244868
train loss: 2.0817480087280273
train per: 0.5552851909994767
train loss: 2.054786205291748
train per: 0.5524458170186952
train loss: 2.0953216552734375
train per: 0.5622734558007644
train loss: 2.0393645763397217
train per: 0.5513458439958298
train loss: 2.059234142303467
train per: 0.5534577853203224
train loss: 2.047490358352661
train per: 0.5538353800365156
train loss: 2.027111291885376
train per: 0.5511360811415502
train loss: 2.0575108528137207
train per: 0.5548559735558004
train loss: 2.0287280082702637
train per: 0.5497903703901514
train loss: 2.1109888553619385
train per: 0.5542970441441236
train loss: 2.0377862453460693
train per: 0.5517625135876598
train loss: 2.0729644298553467
train per: 0.5480814898137732
train loss: 2.0543031692504883
train per: 0.5515144528660768
train loss: 2.095851421356201
train per: 0.5555379496117889
train loss: 2.04827618598938
train per: 0.5508823306657241
train loss: 2.097195625305176
train per: 0.5633691685570569
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  18%|█▊        | 475/2703 [00:00<00:00, 4743.06it/s]


word -> phonemes:  35%|███▌      | 950/2703 [00:00<00:00, 4410.30it/s]


word -> phonemes:  54%|█████▍    | 1470/2703 [00:00<00:00, 4755.55it/s]


word -> phonemes:  72%|███████▏  | 1948/2703 [00:00<00:00, 4653.89it/s]


word -> phonemes:  91%|█████████▏| 2471/2703 [00:00<00:00, 4853.32it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 4683.45it/s]



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


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overall:  75%|███████▍  | 2999/4000 [17:03<03:52,  4.31it/s]

train:  85%|████████▌ | 2999/3515 [17:00<01:59,  4.31it/s]
                                                            

                                                          

overall:  75%|███████▍  | 2999/4000 [17:03<03:52,  4.31it/s]

train:  85%|████████▌ | 2999/3515 [17:00<01:59,  4.31it/s]
overall:  75%|███████▌  | 3000/4000 [17:03<10:42:59, 38.58s/it]

train:  85%|████████▌ | 3000/3515 [17:01<5:31:08, 38.58s/it]
overall:  75%|███████▌  | 3001/4000 [17:03<7:32:16, 27.16s/it] 

train:  85%|████████▌ | 3001/3515 [17:01<3:52:42, 27.16s/it]
overall:  75%|███████▌  | 3002/4000 [17:03<5:17:23, 19.08s/it]

train:  85%|████████▌ | 3002/3515 [17:01<2:43:09, 19.08s/it]
overall:  75%|███████▌  | 3003/4000 [17:04<3:42:59, 13.42s/it]

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train: 100%|██████████| 3515/3515 [18:51<00:00,  4.87it/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 [18:51<00:00,  3.11it/s]
dev loss: 2.3360795974731445
dev per: 0.5937617065556712
[Runner] - Save the checkpoint to:
1. result/downstream/grid/dev-best.ckpt
train loss: 2.0079827308654785
train per: 0.5434722743772687
train loss: 2.0581915378570557
train per: 0.5551007041100376
train loss: 2.01843523979187
train per: 0.5453903816199377
train loss: 2.0378096103668213
train per: 0.5457180301426483
train loss: 2.06619930267334
train per: 0.5487490235993088
train loss: 2.053797483444214
train per: 0.5503198943840764
train loss: 2.028557062149048
train per: 0.5463154183246864
train loss: 2.0775306224823
train per: 0.5531327297615332
train loss: 2.083418607711792
train per: 0.5574782760251973
train loss: 2.0407474040985107
train per: 0.5498074271313775
train loss: 2.0583786964416504
train per: 0.5497485780232463
train loss: 2.0961804389953613
train per: 0.5543567878259641
train loss: 2.0242035388946533
train per: 0.5513146307711662
train loss: 2.0329995155334473
train per: 0.5467111868680973
train loss: 2.0578856468200684
train per: 0.551491512118536
train loss: 2.0802536010742188
train per: 0.5513437122472704
train loss: 2.0884604454040527
train per: 0.5535877722862896
train loss: 2.0569443702697754
train per: 0.5539585296889726
train loss: 2.09090256690979
train per: 0.5618673555461831
train loss: 2.063103437423706
train per: 0.5532250176601641
train loss: 2.0674312114715576
train per: 0.5592362295713421
train loss: 2.0899901390075684
train per: 0.5580538914390933
train loss: 2.1037750244140625
train per: 0.5607077194909386
train loss: 2.074488639831543
train per: 0.5593081947743468
train loss: 2.0803093910217285
train per: 0.5530598266373793
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.


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

word -> phonemes:  12%|█▏        | 438/3515 [00:00<00:00, 4376.79it/s]

word -> phonemes:  25%|██▌       | 893/3515 [00:00<00:00, 4476.55it/s]

word -> phonemes:  38%|███▊      | 1341/3515 [00:00<00:00, 4446.03it/s]

word -> phonemes:  51%|█████     | 1786/3515 [00:00<00:00, 4292.10it/s]

word -> phonemes:  63%|██████▎   | 2216/3515 [00:00<00:00, 4194.43it/s]

word -> phonemes:  75%|███████▌  | 2639/3515 [00:00<00:00, 4204.81it/s]

word -> phonemes:  87%|████████▋ | 3060/3515 [00:00<00:00, 4161.07it/s]

word -> phonemes:  99%|█████████▉| 3492/3515 [00:00<00:00, 4209.77it/s]
word -> phonemes: 100%|██████████| 3515/3515 [00:00<00:00, 4252.53it/s]


train:   0%|          | 0/3515 [00:00<?, ?it/s]
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overall:  88%|████████▊ | 3531/4000 [19:00<01:44,  4.50it/s]

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overall:  88%|████████▊ | 3532/4000 [19:00<01:43,  4.53it/s]

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overall:  88%|████████▊ | 3533/4000 [19:00<01:37,  4.81it/s]

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overall:  88%|████████▊ | 3534/4000 [19:00<01:38,  4.72it/s]

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overall:  88%|████████▊ | 3535/4000 [19:00<01:39,  4.67it/s]

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overall:  88%|████████▊ | 3536/4000 [19:01<01:40,  4.62it/s]

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overall:  88%|████████▊ | 3538/4000 [19:01<01:25,  5.38it/s]

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overall:  88%|████████▊ | 3539/4000 [19:01<01:31,  5.05it/s]

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overall:  88%|████████▊ | 3540/4000 [19:02<01:49,  4.22it/s]

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overall:  89%|████████▊ | 3542/4000 [19:02<01:43,  4.42it/s]

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overall:  89%|████████▊ | 3543/4000 [19:02<01:28,  5.19it/s]

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overall:  89%|████████▊ | 3544/4000 [19:02<01:31,  4.98it/s]

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overall:  89%|████████▊ | 3546/4000 [19:03<01:21,  5.60it/s]

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overall:  89%|████████▊ | 3547/4000 [19:03<01:26,  5.23it/s]

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overall:  89%|████████▊ | 3548/4000 [19:03<01:32,  4.90it/s]

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overall:  89%|████████▊ | 3549/4000 [19:03<01:32,  4.85it/s]

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overall:  89%|████████▉ | 3550/4000 [19:04<01:30,  4.98it/s]

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overall:  89%|████████▉ | 3551/4000 [19:04<01:34,  4.73it/s]

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overall:  89%|████████▉ | 3552/4000 [19:04<01:50,  4.05it/s]

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overall:  89%|████████▉ | 3553/4000 [19:04<01:46,  4.21it/s]

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overall:  89%|████████▉ | 3554/4000 [19:05<01:42,  4.34it/s]

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overall:  89%|████████▉ | 3568/4000 [19:07<01:17,  5.58it/s]

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overall:  89%|████████▉ | 3579/4000 [19:10<01:39,  4.25it/s]

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overall:  90%|████████▉ | 3584/4000 [19:11<01:20,  5.15it/s]

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overall:  90%|████████▉ | 3586/4000 [19:11<01:09,  5.96it/s]

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overall:  90%|████████▉ | 3587/4000 [19:11<01:15,  5.50it/s]

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overall:  90%|████████▉ | 3590/4000 [19:12<01:32,  4.46it/s]

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overall:  90%|████████▉ | 3591/4000 [19:12<01:28,  4.61it/s]

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overall:  90%|████████▉ | 3592/4000 [19:13<01:24,  4.84it/s]

train:   2%|▏         | 77/3515 [00:17<11:50,  4.84it/s]
overall:  90%|████████▉ | 3593/4000 [19:13<01:25,  4.76it/s]

train:   2%|▏         | 78/3515 [00:17<12:01,  4.76it/s]
overall:  90%|████████▉ | 3594/4000 [19:13<01:23,  4.85it/s]

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overall:  90%|████████▉ | 3595/4000 [19:13<01:18,  5.14it/s]

train:   2%|▏         | 80/3515 [00:17<11:08,  5.14it/s]
overall:  90%|████████▉ | 3596/4000 [19:13<01:20,  5.05it/s]

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overall:  90%|████████▉ | 3597/4000 [19:14<01:22,  4.91it/s]

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overall:  90%|████████▉ | 3598/4000 [19:14<01:20,  4.97it/s]

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overall:  90%|████████▉ | 3599/4000 [19:14<01:19,  5.06it/s]

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overall:  90%|█████████ | 3600/4000 [19:14<01:39,  4.02it/s]

train:   2%|▏         | 85/3515 [00:19<14:12,  4.02it/s]
overall:  90%|█████████ | 3601/4000 [19:14<01:36,  4.16it/s]

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overall:  90%|█████████ | 3602/4000 [19:15<01:30,  4.41it/s]

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overall:  90%|█████████ | 3603/4000 [19:15<01:30,  4.41it/s]

train:   3%|▎         | 88/3515 [00:19<12:57,  4.41it/s]
overall:  90%|█████████ | 3604/4000 [19:15<01:28,  4.48it/s]

train:   3%|▎         | 89/3515 [00:20<12:44,  4.48it/s]
overall:  90%|█████████ | 3606/4000 [19:15<01:09,  5.70it/s]

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overall:  90%|█████████ | 3607/4000 [19:16<01:11,  5.48it/s]

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overall:  90%|█████████ | 3608/4000 [19:16<01:10,  5.55it/s]

train:   3%|▎         | 93/3515 [00:20<10:16,  5.55it/s]
overall:  90%|█████████ | 3609/4000 [19:16<01:12,  5.40it/s]

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overall:  90%|█████████ | 3610/4000 [19:16<01:14,  5.25it/s]

train:   3%|▎         | 95/3515 [00:21<10:51,  5.25it/s]
overall:  90%|█████████ | 3611/4000 [19:16<01:17,  4.99it/s]

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overall:  90%|█████████ | 3612/4000 [19:17<01:34,  4.13it/s]

train:   3%|▎         | 97/3515 [00:21<13:48,  4.13it/s]
overall:  90%|█████████ | 3613/4000 [19:17<01:28,  4.37it/s]

train:   3%|▎         | 98/3515 [00:21<13:02,  4.37it/s]
overall:  90%|█████████ | 3614/4000 [19:17<01:41,  3.80it/s]

train:   3%|▎         | 99/3515 [00:22<14:58,  3.80it/s]
overall:  90%|█████████ | 3615/4000 [19:17<01:36,  3.98it/s]

train:   3%|▎         | 100/3515 [00:22<14:18,  3.98it/s]
overall:  90%|█████████ | 3616/4000 [19:18<01:33,  4.12it/s]

train:   3%|▎         | 101/3515 [00:22<13:49,  4.12it/s]
overall:  90%|█████████ | 3617/4000 [19:18<01:29,  4.28it/s]

train:   3%|▎         | 102/3515 [00:22<13:16,  4.28it/s]
overall:  90%|█████████ | 3618/4000 [19:18<01:31,  4.20it/s]

train:   3%|▎         | 103/3515 [00:23<13:33,  4.20it/s]
overall:  90%|█████████ | 3619/4000 [19:18<01:28,  4.30it/s]

train:   3%|▎         | 104/3515 [00:23<13:13,  4.30it/s]
overall:  90%|█████████ | 3620/4000 [19:19<01:27,  4.34it/s]

train:   3%|▎         | 105/3515 [00:23<13:06,  4.33it/s]
overall:  91%|█████████ | 3621/4000 [19:19<01:26,  4.37it/s]

train:   3%|▎         | 106/3515 [00:23<12:59,  4.37it/s]
overall:  91%|█████████ | 3622/4000 [19:19<01:23,  4.51it/s]

train:   3%|▎         | 107/3515 [00:23<12:35,  4.51it/s]
overall:  91%|█████████ | 3623/4000 [19:19<01:21,  4.61it/s]

train:   3%|▎         | 108/3515 [00:24<12:19,  4.61it/s]
overall:  91%|█████████ | 3624/4000 [19:20<01:27,  4.32it/s]

train:   3%|▎         | 109/3515 [00:24<13:08,  4.32it/s]
overall:  91%|█████████ | 3625/4000 [19:20<01:25,  4.40it/s]

train:   3%|▎         | 110/3515 [00:24<12:53,  4.40it/s]
overall:  91%|█████████ | 3626/4000 [19:20<01:29,  4.17it/s]

train:   3%|▎         | 111/3515 [00:24<13:35,  4.17it/s]
overall:  91%|█████████ | 3627/4000 [19:20<01:27,  4.25it/s]

train:   3%|▎         | 112/3515 [00:25<13:20,  4.25it/s]
overall:  91%|█████████ | 3628/4000 [19:20<01:13,  5.09it/s]

train:   3%|▎         | 113/3515 [00:25<11:07,  5.09it/s]
overall:  91%|█████████ | 3629/4000 [19:21<01:14,  4.97it/s]

train:   3%|▎         | 114/3515 [00:25<11:23,  4.97it/s]
overall:  91%|█████████ | 3630/4000 [19:21<01:16,  4.86it/s]

train:   3%|▎         | 115/3515 [00:25<11:39,  4.86it/s]
overall:  91%|█████████ | 3631/4000 [19:21<01:14,  4.95it/s]

train:   3%|▎         | 116/3515 [00:25<11:27,  4.95it/s]
overall:  91%|█████████ | 3632/4000 [19:21<01:15,  4.88it/s]

train:   3%|▎         | 117/3515 [00:26<11:36,  4.88it/s]
overall:  91%|█████████ | 3633/4000 [19:21<01:17,  4.77it/s]

train:   3%|▎         | 118/3515 [00:26<11:52,  4.77it/s]
overall:  91%|█████████ | 3634/4000 [19:22<01:17,  4.73it/s]

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overall:  91%|█████████ | 3635/4000 [19:22<01:16,  4.74it/s]

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overall:  91%|█████████ | 3636/4000 [19:22<01:29,  4.08it/s]

train:   3%|▎         | 121/3515 [00:27<13:52,  4.08it/s]
overall:  91%|█████████ | 3637/4000 [19:22<01:26,  4.21it/s]

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overall:  91%|█████████ | 3638/4000 [19:23<01:31,  3.96it/s]

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overall:  91%|█████████ | 3639/4000 [19:23<01:27,  4.12it/s]

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overall:  91%|█████████ | 3640/4000 [19:23<01:24,  4.25it/s]

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overall:  91%|█████████ | 3641/4000 [19:23<01:22,  4.38it/s]

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overall:  91%|█████████ | 3642/4000 [19:24<01:20,  4.44it/s]

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overall:  91%|█████████ | 3643/4000 [19:24<01:19,  4.50it/s]

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overall:  91%|█████████ | 3644/4000 [19:24<01:17,  4.62it/s]

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overall:  91%|█████████ | 3645/4000 [19:24<01:16,  4.64it/s]

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overall:  91%|█████████ | 3646/4000 [19:24<01:16,  4.60it/s]

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overall:  91%|█████████ | 3647/4000 [19:25<01:09,  5.11it/s]

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overall:  91%|█████████ | 3648/4000 [19:25<01:13,  4.76it/s]

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overall:  91%|█████████ | 3649/4000 [19:25<01:13,  4.74it/s]

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overall:  91%|█████████▏| 3650/4000 [19:25<01:16,  4.56it/s]

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overall:  91%|█████████▏| 3651/4000 [19:25<01:07,  5.15it/s]

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overall:  91%|█████████▏| 3652/4000 [19:26<01:08,  5.05it/s]

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overall:  91%|█████████▏| 3653/4000 [19:26<01:11,  4.89it/s]

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overall:  91%|█████████▏| 3655/4000 [19:26<00:59,  5.82it/s]

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overall:  91%|█████████▏| 3656/4000 [19:26<01:03,  5.43it/s]

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overall:  91%|█████████▏| 3657/4000 [19:26<01:06,  5.17it/s]

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overall:  91%|█████████▏| 3658/4000 [19:27<01:07,  5.09it/s]

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overall:  91%|█████████▏| 3659/4000 [19:27<01:07,  5.05it/s]

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overall:  92%|█████████▏| 3660/4000 [19:27<01:17,  4.39it/s]

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overall:  92%|█████████▏| 3661/4000 [19:27<01:15,  4.51it/s]

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overall:  92%|█████████▏| 3662/4000 [19:28<01:18,  4.32it/s]

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overall:  92%|█████████▏| 3664/4000 [19:28<01:05,  5.12it/s]

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overall:  92%|█████████▏| 3665/4000 [19:28<01:07,  4.98it/s]

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overall:  92%|█████████▏| 3666/4000 [19:28<01:08,  4.90it/s]

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overall:  92%|█████████▏| 3667/4000 [19:28<00:58,  5.69it/s]

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overall:  92%|█████████▏| 3669/4000 [19:29<00:51,  6.38it/s]

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overall:  92%|█████████▏| 3670/4000 [19:29<00:57,  5.77it/s]

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overall:  92%|█████████▏| 3671/4000 [19:29<01:01,  5.37it/s]

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overall:  92%|█████████▏| 3675/4000 [19:30<01:07,  4.80it/s]

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overall:  92%|█████████▏| 3676/4000 [19:30<01:08,  4.71it/s]

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overall: 100%|█████████▉| 3997/4000 [20:40<00:00,  4.79it/s]

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overall: 100%|█████████▉| 3998/4000 [20:40<00:00,  4.29it/s]

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overall: 100%|█████████▉| 3999/4000 [20:40<00:00,  4.46it/s]

train:  14%|█▍        | 484/3515 [01:45<11:19,  4.46it/s]train loss: 2.067518711090088
train per: 0.5487644318411992
train loss: 2.0360870361328125
train per: 0.5519641245158848
train loss: 2.0519299507141113
train per: 0.5553292772955223
train loss: 2.09262752532959
train per: 0.5570212765957446
train loss: 2.0802183151245117
train per: 0.5602860258133225
train loss: 2.0615248680114746
train per: 0.5528679170388012
train loss: 2.0746946334838867
train per: 0.5491681009753299
train loss: 2.0526978969573975
train per: 0.5496452090458931
train loss: 2.0557475090026855
train per: 0.5571887100061137
train loss: 2.0642447471618652
train per: 0.5600702152924777
train loss: 2.078217029571533
train per: 0.5554254183909841
train loss: 2.108553171157837
train per: 0.5553993752788934
train loss: 2.032320499420166
train per: 0.5474732199117832
train loss: 2.0741991996765137
train per: 0.5537341094781905
train loss: 2.115246295928955
train per: 0.5655002185483249
train loss: 2.052962064743042
train per: 0.5534313352121258
train loss: 2.035374641418457
train per: 0.5520417713413133
train loss: 2.0526819229125977
train per: 0.5509578361933736
train loss: 2.0693697929382324
train per: 0.5533626091676124
train loss: 2.038501262664795
train per: 0.5439887837364178
train loss: 2.040215253829956
train per: 0.5480006105006106
train loss: 2.0642616748809814
train per: 0.5483564968012354
train loss: 2.0604946613311768
train per: 0.5524177212173208
train loss: 2.0549845695495605
train per: 0.5503306749659599
train loss: 2.0475120544433594
train per: 0.5454748105216228
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  17%|█▋        | 451/2703 [00:00<00:00, 4389.98it/s]


word -> phonemes:  33%|███▎      | 890/2703 [00:00<00:00, 4154.10it/s]


word -> phonemes:  48%|████▊     | 1307/2703 [00:00<00:00, 4124.67it/s]


word -> phonemes:  65%|██████▌   | 1767/2703 [00:00<00:00, 4266.44it/s]


word -> phonemes:  81%|████████  | 2195/2703 [00:00<00:00, 4193.26it/s]


word -> phonemes:  97%|█████████▋| 2615/2703 [00:00<00:00, 3812.43it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 4017.04it/s]



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


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dev:   2%|▏         | 62/2703 [00:05<02:42, 16.24it/s]


dev:   2%|▏         | 64/2703 [00:05<02:43, 16.13it/s]


dev:   2%|▏         | 66/2703 [00:05<02:45, 15.94it/s]


dev:   3%|▎         | 68/2703 [00:05<02:45, 15.89it/s]


dev:   3%|▎         | 70/2703 [00:05<02:45, 15.92it/s]


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dev:   3%|▎         | 76/2703 [00:06<02:37, 16.70it/s]


dev:   3%|▎         | 78/2703 [00:06<02:34, 17.03it/s]


dev:   3%|▎         | 80/2703 [00:06<02:39, 16.49it/s]


dev:   3%|▎         | 82/2703 [00:06<02:49, 15.47it/s]


dev:   3%|▎         | 84/2703 [00:06<02:42, 16.10it/s]


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overall: 100%|█████████▉| 3999/4000 [22:50<00:00,  4.46it/s]

train:  14%|█▍        | 484/3515 [03:54<11:19,  4.46it/s]
                                                            

                                                         

overall: 100%|█████████▉| 3999/4000 [22:50<00:00,  4.46it/s]

train:  14%|█▍        | 484/3515 [03:54<11:19,  4.46it/s]
overall: 100%|██████████| 4000/4000 [22:50<00:00, 36.45s/it]

train:  14%|█▍        | 485/3515 [03:54<30:40:51, 36.45s/it]403-128339-0009 Failed!!!

train:  14%|█▍        | 485/3515 [03:55<24:29,  2.06it/s]   

overall: 100%|██████████| 4000/4000 [22:50<00:00,  2.92it/s]
dev loss: 2.3651845455169678
dev per: 0.5993808532778356
[Runner] - Save the checkpoint to:
1. result/downstream/grid/states-4000.ckpt