/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")
2023-10-11 04:00:52 | 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 2 features and weighted sum them.
[Featurizer] - The selected feature hidden_states's downsample rate is 960
[Runner] - Start a new experiment
mert_test_8x_400k_double_encode {'model_config': None, 'refresh': False}
using suno's k-means clusters: mert_test_8x_400k_double_encode
load local model succeed
load local feat extractor
Wav2Vec2FeatureExtractor {
  "do_normalize": false,
  "feature_extractor_type": "Wav2Vec2FeatureExtractor",
  "feature_size": 1,
  "padding_side": "right",
  "padding_value": 0,
  "return_attention_mask": true,
  "sampling_rate": 24000
}


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


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

word -> phonemes:  12%|█▏        | 409/3515 [00:00<00:00, 4079.97it/s]

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word -> phonemes:  49%|████▉     | 1729/3515 [00:00<00:00, 4383.47it/s]

word -> phonemes:  62%|██████▏   | 2168/3515 [00:00<00:00, 4242.61it/s]

word -> phonemes:  74%|███████▍  | 2594/3515 [00:00<00:00, 4082.80it/s]

word -> phonemes:  85%|████████▌ | 3004/3515 [00:00<00:00, 3805.72it/s]

word -> phonemes:  96%|█████████▋| 3389/3515 [00:00<00:00, 3790.30it/s]
word -> phonemes: 100%|██████████| 3515/3515 [00:00<00:00, 4003.62it/s]


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train:   4%|▍         | 153/3515 [00:32<12:08,  4.62it/s]
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train:   4%|▍         | 154/3515 [00:32<11:53,  4.71it/s]
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train:   4%|▍         | 155/3515 [00:32<11:42,  4.78it/s]
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train:   4%|▍         | 157/3515 [00:32<10:41,  5.24it/s]
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train:   4%|▍         | 158/3515 [00:33<10:52,  5.14it/s]
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train:   5%|▍         | 159/3515 [00:33<11:07,  5.03it/s]
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train:   5%|▍         | 160/3515 [00:33<11:13,  4.98it/s]
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train:   5%|▍         | 161/3515 [00:33<11:17,  4.95it/s]
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train:   5%|▍         | 162/3515 [00:33<11:24,  4.90it/s]
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train:   5%|▍         | 163/3515 [00:34<11:29,  4.86it/s]
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train:   5%|▍         | 164/3515 [00:34<11:27,  4.87it/s]
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train:   5%|▍         | 165/3515 [00:34<11:19,  4.93it/s]
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train:   5%|▍         | 166/3515 [00:34<11:31,  4.84it/s]
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train:   5%|▍         | 169/3515 [00:35<12:12,  4.57it/s]
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train:   5%|▍         | 170/3515 [00:35<12:28,  4.47it/s]
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train:   5%|▍         | 171/3515 [00:35<11:50,  4.70it/s]
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train:   5%|▍         | 173/3515 [00:36<09:46,  5.70it/s]
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train:   5%|▌         | 176/3515 [00:36<11:57,  4.65it/s]
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train:   5%|▌         | 177/3515 [00:37<12:43,  4.37it/s]
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train:   5%|▌         | 178/3515 [00:37<12:35,  4.42it/s]
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train:   5%|▌         | 179/3515 [00:37<12:19,  4.51it/s]
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train:   5%|▌         | 180/3515 [00:37<11:54,  4.67it/s]
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train:   5%|▌         | 182/3515 [00:38<11:57,  4.64it/s]
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train:   5%|▌         | 183/3515 [00:38<12:00,  4.63it/s]
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train:   5%|▌         | 184/3515 [00:38<10:28,  5.30it/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<10:47,  5.14it/s]
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train:   5%|▌         | 187/3515 [00:39<10:53,  5.09it/s]
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train:   5%|▌         | 188/3515 [00:39<10:54,  5.08it/s]
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train:   5%|▌         | 189/3515 [00:39<11:05,  5.00it/s]
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train:   5%|▌         | 190/3515 [00:39<11:28,  4.83it/s]
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train:   5%|▌         | 191/3515 [00:39<11:20,  4.88it/s]
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train:   5%|▌         | 193/3515 [00:40<12:00,  4.61it/s]
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train:   6%|▌         | 195/3515 [00:40<11:32,  4.79it/s]
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overall:  11%|█         | 422/4000 [01:30<12:36,  4.73it/s]

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overall:  13%|█▎        | 510/4000 [01:48<12:09,  4.79it/s]

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overall:  13%|█▎        | 526/4000 [01:52<11:51,  4.88it/s]

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overall:  13%|█▎        | 528/4000 [01:52<11:27,  5.05it/s]

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overall:  13%|█▎        | 531/4000 [01:53<11:36,  4.98it/s]

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overall:  13%|█▎        | 533/4000 [01:53<13:44,  4.21it/s]

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overall:  13%|█▎        | 534/4000 [01:53<11:45,  4.91it/s]

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overall:  13%|█▎        | 536/4000 [01:54<11:07,  5.19it/s]

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overall:  13%|█▎        | 537/4000 [01:54<11:20,  5.09it/s]

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overall:  13%|█▎        | 538/4000 [01:54<10:01,  5.76it/s]

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overall:  13%|█▎        | 539/4000 [01:54<10:46,  5.35it/s]

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overall:  14%|█▎        | 540/4000 [01:54<11:10,  5.16it/s]

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overall:  14%|█▎        | 541/4000 [01:55<11:16,  5.12it/s]

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overall:  14%|█▎        | 542/4000 [01:55<11:34,  4.98it/s]

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overall:  14%|█▎        | 543/4000 [01:55<11:37,  4.96it/s]

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overall:  14%|█▎        | 544/4000 [01:55<14:59,  3.84it/s]

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overall:  14%|█▎        | 545/4000 [01:56<14:00,  4.11it/s]

train:  16%|█▌        | 545/3515 [01:54<12:02,  4.11it/s]
overall:  14%|█▎        | 546/4000 [01:56<13:28,  4.27it/s]

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overall:  14%|█▎        | 547/4000 [01:56<12:42,  4.53it/s]

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overall:  14%|█▎        | 548/4000 [01:56<12:27,  4.62it/s]

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overall:  14%|█▎        | 549/4000 [01:56<12:14,  4.70it/s]

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overall:  14%|█▍        | 550/4000 [01:57<11:55,  4.82it/s]

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overall:  14%|█▍        | 551/4000 [01:57<12:12,  4.71it/s]

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overall:  14%|█▍        | 552/4000 [01:57<12:03,  4.77it/s]

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overall:  14%|█▍        | 553/4000 [01:57<11:56,  4.81it/s]

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overall:  14%|█▍        | 554/4000 [01:58<12:01,  4.77it/s]

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overall:  14%|█▍        | 555/4000 [01:58<12:02,  4.77it/s]

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overall:  14%|█▍        | 557/4000 [01:58<12:56,  4.44it/s]

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overall:  14%|█▍        | 558/4000 [01:58<12:34,  4.56it/s]

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overall:  14%|█▍        | 559/4000 [01:59<11:55,  4.81it/s]

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overall:  14%|█▍        | 560/4000 [01:59<11:54,  4.82it/s]

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overall:  14%|█▍        | 561/4000 [01:59<11:46,  4.87it/s]

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overall:  14%|█▍        | 562/4000 [01:59<11:38,  4.92it/s]

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overall:  14%|█▍        | 563/4000 [01:59<11:39,  4.92it/s]

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overall:  14%|█▍        | 565/4000 [02:00<11:52,  4.82it/s]

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overall:  14%|█▍        | 566/4000 [02:00<11:49,  4.84it/s]

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overall:  14%|█▍        | 568/4000 [02:01<14:55,  3.83it/s]

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overall:  14%|█▍        | 569/4000 [02:01<13:58,  4.09it/s]

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overall:  14%|█▍        | 571/4000 [02:01<10:26,  5.47it/s]

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overall:  14%|█▍        | 572/4000 [02:01<10:45,  5.31it/s]

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overall:  14%|█▍        | 573/4000 [02:01<10:48,  5.28it/s]

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overall:  14%|█▍        | 574/4000 [02:02<10:58,  5.20it/s]

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overall:  14%|█▍        | 575/4000 [02:02<10:06,  5.64it/s]

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overall:  14%|█▍        | 577/4000 [02:02<09:21,  6.09it/s]

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train:  28%|██▊       | 992/3515 [03:26<08:26,  4.98it/s]
overall:  25%|██▍       | 993/4000 [03:28<10:11,  4.92it/s]

train:  28%|██▊       | 993/3515 [03:26<08:32,  4.92it/s]
overall:  25%|██▍       | 994/4000 [03:29<10:10,  4.92it/s]

train:  28%|██▊       | 994/3515 [03:26<08:32,  4.92it/s]
overall:  25%|██▍       | 995/4000 [03:29<10:17,  4.86it/s]

train:  28%|██▊       | 995/3515 [03:27<08:38,  4.86it/s]
overall:  25%|██▍       | 996/4000 [03:29<13:11,  3.80it/s]

train:  28%|██▊       | 996/3515 [03:27<11:03,  3.80it/s]
overall:  25%|██▍       | 997/4000 [03:29<12:19,  4.06it/s]

train:  28%|██▊       | 997/3515 [03:27<10:20,  4.06it/s]
overall:  25%|██▍       | 998/4000 [03:30<11:42,  4.27it/s]

train:  28%|██▊       | 998/3515 [03:27<09:48,  4.27it/s]
overall:  25%|██▍       | 999/4000 [03:30<11:00,  4.54it/s]

train:  28%|██▊       | 999/3515 [03:28<09:13,  4.54it/s]train loss: 4.123980522155762
train per: 0.9796147973534061
train loss: 3.5514369010925293
train per: 0.8774200148333802
train loss: 3.364403247833252
train per: 0.8324637229706928
train loss: 3.3306586742401123
train per: 0.8398991570959281
train loss: 3.3294918537139893
train per: 0.8358870780517249
train loss: 3.3594002723693848
train per: 0.8413283140629202
train loss: 3.305187702178955
train per: 0.8428871109376525
train loss: 3.3601810932159424
train per: 0.8411289465291804
train loss: 3.2875752449035645
train per: 0.8352878205440124
train loss: 3.3061306476593018
train per: 0.8526445601534667
train loss: 3.3277485370635986
train per: 0.8463705536979016
train loss: 3.3267219066619873
train per: 0.8386681201070261
train loss: 3.3447775840759277
train per: 0.8412526489286555
train loss: 3.3119266033172607
train per: 0.8366441960986316
train loss: 3.268446445465088
train per: 0.8389960208142027
train loss: 3.301525115966797
train per: 0.8445090739879013
train loss: 3.2859082221984863
train per: 0.843405752753978
train loss: 3.3235785961151123
train per: 0.8435358930618865
train loss: 3.294673442840576
train per: 0.8463297066519763
train loss: 3.27894926071167
train per: 0.8405165903026031
train loss: 3.262974262237549
train per: 0.8435473131273274
train loss: 3.291836977005005
train per: 0.8479118008990683
train loss: 3.272739887237549
train per: 0.837190917475515
train loss: 3.2850489616394043
train per: 0.8385733157199472
train loss: 3.2659993171691895
train per: 0.8343439297338268
train loss: 3.277186155319214
train per: 0.8401549386701097
train loss: 3.280188798904419
train per: 0.8418030362776026
train loss: 3.2473511695861816
train per: 0.8324562003052879
train loss: 3.2565712928771973
train per: 0.8343093171598871
train loss: 3.2572288513183594
train per: 0.8476591292769337
train loss: 3.2801833152770996
train per: 0.8460984220765185
train loss: 3.2670998573303223
train per: 0.8384607847940038
train loss: 3.2851219177246094
train per: 0.836862922364109
train loss: 3.2770931720733643
train per: 0.8452263395873395
train loss: 3.2685227394104004
train per: 0.8451998037398463
train loss: 3.2985999584198
train per: 0.8446159242371097
train loss: 3.3008835315704346
train per: 0.840533821183976
train loss: 3.2928595542907715
train per: 0.8403470715835141
train loss: 3.2654247283935547
train per: 0.8395586572959158
train loss: 3.3170623779296875
train per: 0.8287356053350774
train loss: 3.2859623432159424
train per: 0.8396081546200689
train loss: 3.298149824142456
train per: 0.8475886176197498
train loss: 3.2754721641540527
train per: 0.841565105837075
train loss: 3.2910873889923096
train per: 0.8409337813597433
train loss: 3.2818145751953125
train per: 0.8359026113283714
train loss: 3.2616615295410156
train per: 0.8424096936442615
train loss: 3.3104355335235596
train per: 0.8448035160289555
train loss: 3.276648998260498
train per: 0.8384492859264059
train loss: 3.266932249069214
train per: 0.8465320006523613
train loss: 3.2546935081481934
train per: 0.8516935543642068
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  16%|█▌        | 419/2703 [00:00<00:00, 4184.25it/s]


word -> phonemes:  35%|███▍      | 933/2703 [00:00<00:00, 4742.60it/s]


word -> phonemes:  54%|█████▍    | 1459/2703 [00:00<00:00, 4976.09it/s]


word -> phonemes:  72%|███████▏  | 1957/2703 [00:00<00:00, 4739.96it/s]


word -> phonemes:  90%|█████████ | 2433/2703 [00:00<00:00, 4614.77it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 4578.38it/s]



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overall:  48%|████▊     | 1901/4000 [08:21<07:22,  4.75it/s]

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overall:  48%|████▊     | 1903/4000 [08:21<06:47,  5.15it/s]

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overall:  48%|████▊     | 1904/4000 [08:22<06:57,  5.02it/s]

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overall:  48%|████▊     | 1919/4000 [08:25<06:55,  5.01it/s]

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train:  55%|█████▍    | 1920/3515 [08:23<05:58,  4.45it/s]
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train:  55%|█████▍    | 1922/3515 [08:23<05:53,  4.50it/s]
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overall:  48%|████▊     | 1926/4000 [08:26<07:06,  4.86it/s]

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train:  55%|█████▍    | 1930/3515 [08:25<04:56,  5.34it/s]
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train:  55%|█████▍    | 1932/3515 [08:25<05:51,  4.51it/s]
overall:  48%|████▊     | 1933/4000 [08:28<08:04,  4.27it/s]

train:  55%|█████▍    | 1933/3515 [08:26<06:10,  4.27it/s]
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train:  55%|█████▌    | 1934/3515 [08:26<06:00,  4.39it/s]
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train:  55%|█████▌    | 1935/3515 [08:26<05:54,  4.46it/s]
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train:  55%|█████▌    | 1936/3515 [08:26<05:00,  5.25it/s]
overall:  48%|████▊     | 1937/4000 [08:28<07:15,  4.74it/s]

train:  55%|█████▌    | 1937/3515 [08:26<05:32,  4.74it/s]
overall:  48%|████▊     | 1938/4000 [08:29<07:05,  4.85it/s]

train:  55%|█████▌    | 1938/3515 [08:27<05:25,  4.85it/s]
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train:  55%|█████▌    | 1939/3515 [08:27<05:32,  4.74it/s]
overall:  48%|████▊     | 1940/4000 [08:29<07:14,  4.74it/s]

train:  55%|█████▌    | 1940/3515 [08:27<05:32,  4.74it/s]
overall:  49%|████▊     | 1941/4000 [08:29<06:57,  4.94it/s]

train:  55%|█████▌    | 1941/3515 [08:27<05:18,  4.94it/s]
overall:  49%|████▊     | 1942/4000 [08:29<07:02,  4.88it/s]

train:  55%|█████▌    | 1942/3515 [08:27<05:22,  4.88it/s]
overall:  49%|████▊     | 1943/4000 [08:30<07:05,  4.84it/s]

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overall:  49%|████▊     | 1944/4000 [08:30<06:39,  5.15it/s]

train:  55%|█████▌    | 1944/3515 [08:28<05:05,  5.15it/s]
overall:  49%|████▊     | 1945/4000 [08:30<06:48,  5.03it/s]

train:  55%|█████▌    | 1945/3515 [08:28<05:11,  5.03it/s]
overall:  49%|████▊     | 1946/4000 [08:30<06:57,  4.92it/s]

train:  55%|█████▌    | 1946/3515 [08:28<05:18,  4.92it/s]
overall:  49%|████▊     | 1947/4000 [08:30<06:08,  5.57it/s]

train:  55%|█████▌    | 1947/3515 [08:28<04:41,  5.57it/s]
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train:  55%|█████▌    | 1948/3515 [08:29<05:01,  5.20it/s]
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train:  55%|█████▌    | 1949/3515 [08:29<05:12,  5.01it/s]
overall:  49%|████▉     | 1950/4000 [08:31<07:00,  4.87it/s]

train:  55%|█████▌    | 1950/3515 [08:29<05:21,  4.87it/s]
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train:  56%|█████▌    | 1955/3515 [08:30<06:15,  4.15it/s]
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overall:  49%|████▉     | 1957/4000 [08:33<08:20,  4.08it/s]

train:  56%|█████▌    | 1957/3515 [08:31<06:21,  4.08it/s]
overall:  49%|████▉     | 1958/4000 [08:33<07:57,  4.27it/s]

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overall:  49%|████▉     | 1959/4000 [08:33<07:36,  4.47it/s]

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overall:  49%|████▉     | 1960/4000 [08:33<07:26,  4.57it/s]

train:  56%|█████▌    | 1960/3515 [08:31<05:40,  4.57it/s]
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overall:  49%|████▉     | 1962/4000 [08:34<07:42,  4.41it/s]

train:  56%|█████▌    | 1962/3515 [08:32<05:52,  4.41it/s]
overall:  49%|████▉     | 1963/4000 [08:34<07:37,  4.45it/s]

train:  56%|█████▌    | 1963/3515 [08:32<05:48,  4.45it/s]
overall:  49%|████▉     | 1964/4000 [08:34<07:24,  4.58it/s]

train:  56%|█████▌    | 1964/3515 [08:32<05:38,  4.58it/s]
overall:  49%|████▉     | 1965/4000 [08:34<07:19,  4.63it/s]

train:  56%|█████▌    | 1965/3515 [08:32<05:34,  4.63it/s]
overall:  49%|████▉     | 1966/4000 [08:35<07:03,  4.80it/s]

train:  56%|█████▌    | 1966/3515 [08:33<05:22,  4.80it/s]
overall:  49%|████▉     | 1967/4000 [08:35<06:46,  5.00it/s]

train:  56%|█████▌    | 1967/3515 [08:33<05:09,  5.00it/s]
overall:  49%|████▉     | 1968/4000 [08:35<07:16,  4.66it/s]

train:  56%|█████▌    | 1968/3515 [08:33<05:32,  4.66it/s]
overall:  49%|████▉     | 1969/4000 [08:35<07:15,  4.66it/s]

train:  56%|█████▌    | 1969/3515 [08:33<05:31,  4.66it/s]
overall:  49%|████▉     | 1970/4000 [08:35<07:17,  4.64it/s]

train:  56%|█████▌    | 1970/3515 [08:33<05:33,  4.64it/s]
overall:  49%|████▉     | 1971/4000 [08:36<07:39,  4.42it/s]

train:  56%|█████▌    | 1971/3515 [08:34<05:49,  4.42it/s]
overall:  49%|████▉     | 1972/4000 [08:36<07:24,  4.56it/s]

train:  56%|█████▌    | 1972/3515 [08:34<05:38,  4.56it/s]
overall:  49%|████▉     | 1973/4000 [08:36<07:24,  4.56it/s]

train:  56%|█████▌    | 1973/3515 [08:34<05:38,  4.56it/s]
overall:  49%|████▉     | 1974/4000 [08:36<07:22,  4.58it/s]

train:  56%|█████▌    | 1974/3515 [08:34<05:36,  4.58it/s]
overall:  49%|████▉     | 1975/4000 [08:37<07:21,  4.59it/s]

train:  56%|█████▌    | 1975/3515 [08:34<05:35,  4.59it/s]
overall:  49%|████▉     | 1976/4000 [08:37<07:11,  4.69it/s]

train:  56%|█████▌    | 1976/3515 [08:35<05:27,  4.69it/s]
overall:  49%|████▉     | 1977/4000 [08:37<07:17,  4.62it/s]

train:  56%|█████▌    | 1977/3515 [08:35<05:32,  4.62it/s]
overall:  49%|████▉     | 1978/4000 [08:37<07:04,  4.77it/s]

train:  56%|█████▋    | 1978/3515 [08:35<05:22,  4.77it/s]
overall:  49%|████▉     | 1979/4000 [08:37<07:38,  4.41it/s]

train:  56%|█████▋    | 1979/3515 [08:35<05:48,  4.41it/s]
overall:  50%|████▉     | 1980/4000 [08:38<07:34,  4.44it/s]

train:  56%|█████▋    | 1980/3515 [08:36<05:45,  4.44it/s]
overall:  50%|████▉     | 1981/4000 [08:38<07:07,  4.72it/s]

train:  56%|█████▋    | 1981/3515 [08:36<05:25,  4.72it/s]
overall:  50%|████▉     | 1982/4000 [08:38<06:53,  4.88it/s]

train:  56%|█████▋    | 1982/3515 [08:36<05:13,  4.88it/s]
overall:  50%|████▉     | 1984/4000 [08:38<06:07,  5.49it/s]

train:  56%|█████▋    | 1984/3515 [08:36<04:38,  5.49it/s]
overall:  50%|████▉     | 1985/4000 [08:39<06:48,  4.93it/s]

train:  56%|█████▋    | 1985/3515 [08:37<05:10,  4.93it/s]
overall:  50%|████▉     | 1986/4000 [08:39<05:57,  5.64it/s]

train:  57%|█████▋    | 1986/3515 [08:37<04:31,  5.64it/s]
overall:  50%|████▉     | 1987/4000 [08:39<06:10,  5.43it/s]

train:  57%|█████▋    | 1987/3515 [08:37<04:41,  5.43it/s]
overall:  50%|████▉     | 1988/4000 [08:39<06:38,  5.05it/s]

train:  57%|█████▋    | 1988/3515 [08:37<05:02,  5.05it/s]
overall:  50%|████▉     | 1989/4000 [08:39<06:43,  4.98it/s]

train:  57%|█████▋    | 1989/3515 [08:37<05:06,  4.98it/s]
overall:  50%|████▉     | 1990/4000 [08:40<06:58,  4.80it/s]

train:  57%|█████▋    | 1990/3515 [08:38<05:17,  4.80it/s]
overall:  50%|████▉     | 1991/4000 [08:40<07:00,  4.77it/s]

train:  57%|█████▋    | 1991/3515 [08:38<05:19,  4.77it/s]
overall:  50%|████▉     | 1992/4000 [08:40<06:45,  4.95it/s]

train:  57%|█████▋    | 1992/3515 [08:38<05:07,  4.95it/s]
overall:  50%|████▉     | 1993/4000 [08:40<06:51,  4.88it/s]

train:  57%|█████▋    | 1993/3515 [08:38<05:11,  4.88it/s]
overall:  50%|████▉     | 1994/4000 [08:40<06:49,  4.90it/s]

train:  57%|█████▋    | 1994/3515 [08:38<05:10,  4.90it/s]
overall:  50%|████▉     | 1995/4000 [08:41<07:08,  4.67it/s]

train:  57%|█████▋    | 1995/3515 [08:39<05:25,  4.67it/s]
overall:  50%|████▉     | 1996/4000 [08:41<07:02,  4.75it/s]

train:  57%|█████▋    | 1996/3515 [08:39<05:20,  4.75it/s]
overall:  50%|████▉     | 1997/4000 [08:41<07:08,  4.68it/s]

train:  57%|█████▋    | 1997/3515 [08:39<05:24,  4.68it/s]
overall:  50%|████▉     | 1998/4000 [08:41<06:58,  4.78it/s]

train:  57%|█████▋    | 1998/3515 [08:39<05:17,  4.78it/s]
overall:  50%|████▉     | 1999/4000 [08:41<06:50,  4.88it/s]

train:  57%|█████▋    | 1999/3515 [08:39<05:10,  4.88it/s]dev loss: 3.3530290126800537
dev per: 0.8672892819979189
[Runner] - Save the checkpoint to:
1. result/downstream/grid/dev-best.ckpt
train loss: 3.2572948932647705
train per: 0.8430292772879986
train loss: 3.2725658416748047
train per: 0.8487429289754871
train loss: 3.255725860595703
train per: 0.8407122013496261
train loss: 3.2507216930389404
train per: 0.8447237861642232
train loss: 3.283651351928711
train per: 0.846966551326413
train loss: 3.266352415084839
train per: 0.8363078508525389
train loss: 3.262688398361206
train per: 0.8502202643171806
train loss: 3.248922348022461
train per: 0.84623499271613
train loss: 3.271071195602417
train per: 0.8442400266908155
train loss: 3.275362491607666
train per: 0.8416879661989464
train loss: 3.2716917991638184
train per: 0.8323684756786678
train loss: 3.248467206954956
train per: 0.8419641563209507
train loss: 3.2682926654815674
train per: 0.8421665401164262
train loss: 3.255530834197998
train per: 0.85255770084332
train loss: 3.240192413330078
train per: 0.8457288363601422
train loss: 3.259812831878662
train per: 0.8394048604685141
train loss: 3.2566211223602295
train per: 0.8389261744966443
train loss: 3.2673866748809814
train per: 0.8513811691757673
train loss: 3.256290912628174
train per: 0.850115395586443
train loss: 3.2636256217956543
train per: 0.8408163265306122
train loss: 3.2472026348114014
train per: 0.843723166752533
train loss: 3.256671905517578
train per: 0.8471364024911466
train loss: 3.2449326515197754
train per: 0.8405774069659647
train loss: 3.2653229236602783
train per: 0.8412027360820825
train loss: 3.2812037467956543
train per: 0.8450717912587158
train loss: 3.268662691116333
train per: 0.8538479209740409
train loss: 3.300724744796753
train per: 0.8542826263172115
train loss: 3.2712674140930176
train per: 0.838850112386135
train loss: 3.276048183441162
train per: 0.8307965677678801
train loss: 3.2567591667175293
train per: 0.8424149902740502
train loss: 3.2562572956085205
train per: 0.8451199179171476
train loss: 3.300046443939209
train per: 0.843121519418302
train loss: 3.290034532546997
train per: 0.8390452029520296
train loss: 3.2925662994384766
train per: 0.8396800245348599
train loss: 3.265810489654541
train per: 0.8434988293789675
train loss: 3.317234516143799
train per: 0.849325812192694
train loss: 3.296091079711914
train per: 0.8564451051178594
train loss: 3.26507306098938
train per: 0.8447030796337196
train loss: 3.2640299797058105
train per: 0.8469915600326708
train loss: 3.289524793624878
train per: 0.8403124422259197
train loss: 3.2596073150634766
train per: 0.8388032189902441
train loss: 3.2786412239074707
train per: 0.8435683793653243
train loss: 3.2783095836639404
train per: 0.8444532961561442
train loss: 3.2559828758239746
train per: 0.8451481257557436
train loss: 3.244921922683716
train per: 0.8451145622954245
train loss: 3.257441997528076
train per: 0.8430747811186378
train loss: 3.2525794506073
train per: 0.8386577513620604
train loss: 3.2572014331817627
train per: 0.8454781439762666
train loss: 3.2361717224121094
train per: 0.8472665745198036
train loss: 3.2460198402404785
train per: 0.8466658598571947
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  14%|█▎        | 366/2703 [00:00<00:00, 3657.45it/s]


word -> phonemes:  31%|███▏      | 851/2703 [00:00<00:01, 1766.26it/s]


word -> phonemes:  51%|█████     | 1369/2703 [00:00<00:00, 2632.62it/s]


word -> phonemes:  71%|███████   | 1922/2703 [00:00<00:00, 3403.40it/s]


word -> phonemes:  88%|████████▊ | 2379/2703 [00:00<00:00, 3700.52it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 3278.11it/s]



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overall:  75%|███████▍  | 2999/4000 [14:01<03:32,  4.70it/s]

train:  85%|████████▌ | 2999/3515 [13:59<01:49,  4.70it/s]dev loss: 3.3617169857025146
dev per: 0.85974505723205
[Runner] - Save the checkpoint to:
1. result/downstream/grid/dev-best.ckpt
train loss: 3.256159543991089
train per: 0.8548235104062896
train loss: 3.2498326301574707
train per: 0.8513052098248706
train loss: 3.2618250846862793
train per: 0.8472485768500949
train loss: 3.233574390411377
train per: 0.8453897697244243
train loss: 3.241652011871338
train per: 0.8478597086409898
train loss: 3.2500908374786377
train per: 0.8423854431977238
train loss: 3.255364179611206
train per: 0.8449072445413823
train loss: 3.264483690261841
train per: 0.8445639187574672
train loss: 3.2194085121154785
train per: 0.8422333641629752
train loss: 3.2441439628601074
train per: 0.8480584720139037
train loss: 3.2451252937316895
train per: 0.8415378535043035
train loss: 3.2707927227020264
train per: 0.8435906587803386
train loss: 3.3059897422790527
train per: 0.8405421300256629
train loss: 3.264481782913208
train per: 0.838675239597234
train loss: 3.2437171936035156
train per: 0.8519716312056738
train loss: 3.280306339263916
train per: 0.8417329114249698
train loss: 3.271672487258911
train per: 0.8405713627462273
train loss: 3.2789721488952637
train per: 0.8443972791898942
train loss: 3.2494075298309326
train per: 0.8399809727672731
train loss: 3.2642388343811035
train per: 0.8411593306000361
train loss: 3.256801128387451
train per: 0.8474332320486166
train loss: 3.270420551300049
train per: 0.8448625453859575
train loss: 3.2771389484405518
train per: 0.8398615948256366
train loss: 3.2809348106384277
train per: 0.8334032731850608
train loss: 3.2967677116394043
train per: 0.8369961406518011
train loss: 3.2500717639923096
train per: 0.8422131147540983
train loss: 3.2393879890441895
train per: 0.8441432720232332
train loss: 3.2469024658203125
train per: 0.8451484483668281
train loss: 3.2569050788879395
train per: 0.8479456807255786
train loss: 3.2861125469207764
train per: 0.8396151309055342
train loss: 3.2673633098602295
train per: 0.846226625111309
train loss: 3.275184154510498
train per: 0.8418321241382871
train loss: 3.263519287109375
train per: 0.8480540666511303
train loss: 3.2572293281555176
train per: 0.8514749743101331
train loss: 3.263507843017578
train per: 0.8399005756148613
train loss: 3.266806125640869
train per: 0.8493078916891854
train loss: 3.266535520553589
train per: 0.8352114412526199
train loss: 3.2415289878845215
train per: 0.8389726092313525
train loss: 3.261404037475586
train per: 0.84402842596521
train loss: 3.2518067359924316
train per: 0.843133331665958
train loss: 3.255955934524536
train per: 0.850917317158057
train loss: 3.2588419914245605
train per: 0.8482606642531088
train loss: 3.231508731842041
train per: 0.839666728976954
train loss: 3.2747397422790527
train per: 0.8309897673146608
train loss: 3.2522950172424316
train per: 0.8435736839380921
train loss: 3.2580745220184326
train per: 0.8430946131733533
train loss: 3.2770328521728516
train per: 0.8438283524020865
train loss: 3.270402431488037
train per: 0.8354573646920344
train loss: 3.2879791259765625
train per: 0.8453459897503219
train loss: 3.2780349254608154
train per: 0.8482345398954532
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  17%|█▋        | 468/2703 [00:00<00:00, 4679.61it/s]


word -> phonemes:  38%|███▊      | 1015/2703 [00:00<00:00, 5144.14it/s]


word -> phonemes:  57%|█████▋    | 1541/2703 [00:00<00:00, 5193.74it/s]


word -> phonemes:  76%|███████▌  | 2061/2703 [00:00<00:00, 4884.67it/s]


word -> phonemes:  96%|█████████▌| 2585/2703 [00:00<00:00, 5006.93it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 5006.95it/s]



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


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dev:   7%|▋         | 189/2703 [00:11<02:10, 19.21it/s]


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overall:  88%|████████▊ | 3515/4000 [17:54<01:33,  5.21it/s]

train: 100%|██████████| 3515/3515 [17:52<00:00,  5.21it/s]403-128339-0009 Failed!!!
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/home/victor/glockenspiel/s3prl/data/LibriSpeech/train-clean-100/403/128339/403-128339-0009.flac WTF Failed!!!
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train: 100%|██████████| 3515/3515 [17:52<00:00,  3.28it/s]
dev loss: 3.4088151454925537
dev per: 0.8132206035379813
[Runner] - Save the checkpoint to:
1. result/downstream/grid/dev-best.ckpt
train loss: 3.2401275634765625
train per: 0.8393040430592064
train loss: 3.260249614715576
train per: 0.8526008405654714
train loss: 3.2259116172790527
train per: 0.8430441978193146
train loss: 3.2359871864318848
train per: 0.8466152527849186
train loss: 3.253530979156494
train per: 0.8401780008047909
train loss: 3.2465617656707764
train per: 0.8391642124504926
train loss: 3.2512969970703125
train per: 0.8452374955926056
train loss: 3.2553067207336426
train per: 0.8476981820801613
train loss: 3.264601945877075
train per: 0.841022831959764
train loss: 3.241346836090088
train per: 0.8386429556369169
train loss: 3.254342555999756
train per: 0.8493391586294068
train loss: 3.279900074005127
train per: 0.8353160114013805
train loss: 3.255711793899536
train per: 0.8499937099006164
train loss: 3.2342541217803955
train per: 0.8404978167978144
train loss: 3.2613766193389893
train per: 0.8430477872632716
train loss: 3.256481647491455
train per: 0.8422648218641016
train loss: 3.2569804191589355
train per: 0.8384587223137471
train loss: 3.263411045074463
train per: 0.8488846999685831
train loss: 3.2591757774353027
train per: 0.8428405735976381
train loss: 3.265031099319458
train per: 0.8445633864043905
train loss: 3.2758965492248535
train per: 0.8364331700874924
train loss: 3.2606616020202637
train per: 0.8478435644077906
train loss: 3.3086185455322266
train per: 0.8382560110790096
train loss: 3.2779312133789062
train per: 0.8458778701504355
train loss: 3.2809016704559326
train per: 0.8296842154987127
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.


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

word -> phonemes:   6%|▌         | 202/3515 [00:00<00:01, 2013.19it/s]

word -> phonemes:  11%|█▏        | 404/3515 [00:00<00:01, 1897.69it/s]

word -> phonemes:  17%|█▋        | 604/3515 [00:00<00:01, 1939.77it/s]

word -> phonemes:  23%|██▎       | 816/3515 [00:00<00:01, 2006.46it/s]

word -> phonemes:  29%|██▉       | 1018/3515 [00:00<00:01, 1984.54it/s]

word -> phonemes:  35%|███▍      | 1217/3515 [00:00<00:01, 1944.00it/s]

word -> phonemes:  40%|████      | 1412/3515 [00:00<00:01, 1907.28it/s]

word -> phonemes:  46%|████▌     | 1603/3515 [00:00<00:01, 1868.50it/s]

word -> phonemes:  52%|█████▏    | 1818/3515 [00:00<00:00, 1951.58it/s]

word -> phonemes:  58%|█████▊    | 2035/3515 [00:01<00:00, 2016.31it/s]

word -> phonemes:  64%|██████▍   | 2264/3515 [00:01<00:00, 2097.39it/s]

word -> phonemes:  70%|███████   | 2475/3515 [00:01<00:00, 2051.44it/s]

word -> phonemes:  76%|███████▋  | 2681/3515 [00:01<00:00, 2007.91it/s]

word -> phonemes:  82%|████████▏ | 2883/3515 [00:01<00:00, 1855.81it/s]

word -> phonemes:  88%|████████▊ | 3077/3515 [00:01<00:00, 1878.39it/s]

word -> phonemes:  93%|█████████▎| 3268/3515 [00:01<00:00, 1886.36it/s]

word -> phonemes:  99%|█████████▊| 3468/3515 [00:01<00:00, 1918.19it/s]
word -> phonemes: 100%|██████████| 3515/3515 [00:01<00:00, 1950.37it/s]


train:   0%|          | 0/3515 [00:00<?, ?it/s]
overall:  88%|████████▊ | 3516/4000 [17:59<13:04,  1.62s/it]

train:   0%|          | 1/3515 [00:01<1:35:06,  1.62s/it]
overall:  88%|████████▊ | 3517/4000 [17:59<09:24,  1.17s/it]

train:   0%|          | 2/3515 [00:01<43:03,  1.36it/s]  
overall:  88%|████████▊ | 3518/4000 [17:59<07:04,  1.14it/s]

train:   0%|          | 3/3515 [00:01<28:58,  2.02it/s]
overall:  88%|████████▊ | 3519/4000 [18:00<05:28,  1.46it/s]

train:   0%|          | 4/3515 [00:02<22:39,  2.58it/s]
overall:  88%|████████▊ | 3520/4000 [18:00<04:17,  1.87it/s]

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overall:  88%|████████▊ | 3521/4000 [18:00<03:24,  2.35it/s]

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overall:  88%|████████▊ | 3523/4000 [18:00<02:26,  3.26it/s]

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overall:  88%|████████▊ | 3524/4000 [18:00<02:15,  3.51it/s]

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overall:  88%|████████▊ | 3525/4000 [18:01<02:00,  3.95it/s]

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overall:  88%|████████▊ | 3527/4000 [18:01<01:38,  4.78it/s]

train:   0%|          | 12/3515 [00:03<10:30,  5.55it/s]
overall:  88%|████████▊ | 3528/4000 [18:01<01:50,  4.27it/s]

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overall:  88%|████████▊ | 3529/4000 [18:01<01:48,  4.34it/s]

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overall:  88%|████████▊ | 3530/4000 [18:02<01:42,  4.59it/s]

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overall:  88%|████████▊ | 3531/4000 [18:02<01:40,  4.66it/s]

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overall:  88%|████████▊ | 3532/4000 [18:02<01:40,  4.66it/s]

train:   0%|          | 17/3515 [00:04<12:07,  4.81it/s]
overall:  88%|████████▊ | 3533/4000 [18:02<01:34,  4.92it/s]

train:   1%|          | 18/3515 [00:04<11:35,  5.03it/s]
overall:  88%|████████▊ | 3534/4000 [18:02<01:37,  4.79it/s]

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overall:  88%|████████▊ | 3535/4000 [18:03<01:39,  4.66it/s]

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overall:  88%|████████▊ | 3536/4000 [18:03<01:39,  4.68it/s]

train:   1%|          | 21/3515 [00:05<12:21,  4.71it/s]
overall:  88%|████████▊ | 3538/4000 [18:03<01:25,  5.42it/s]

train:   1%|          | 23/3515 [00:05<10:41,  5.44it/s]
overall:  88%|████████▊ | 3539/4000 [18:03<01:28,  5.23it/s]

train:   1%|          | 24/3515 [00:06<11:04,  5.25it/s]
overall:  88%|████████▊ | 3540/4000 [18:04<01:52,  4.10it/s]

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overall:  99%|█████████▊| 3941/4000 [20:05<00:13,  4.21it/s]

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overall:  99%|█████████▉| 3965/4000 [20:09<00:07,  4.89it/s]

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overall:  99%|█████████▉| 3966/4000 [20:10<00:06,  5.03it/s]

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overall:  99%|█████████▉| 3972/4000 [20:11<00:05,  4.78it/s]

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overall:  99%|█████████▉| 3973/4000 [20:11<00:04,  5.53it/s]

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overall:  99%|█████████▉| 3974/4000 [20:11<00:05,  5.14it/s]

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overall:  99%|█████████▉| 3977/4000 [20:12<00:04,  5.19it/s]

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train:  13%|█▎        | 463/3515 [02:14<10:02,  5.07it/s]
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train:  13%|█▎        | 464/3515 [02:15<10:35,  4.80it/s]
overall: 100%|█████████▉| 3980/4000 [20:13<00:04,  4.71it/s]

train:  13%|█▎        | 465/3515 [02:15<10:47,  4.71it/s]
overall: 100%|█████████▉| 3981/4000 [20:13<00:04,  4.73it/s]

train:  13%|█▎        | 466/3515 [02:15<10:43,  4.73it/s]
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train:  13%|█▎        | 467/3515 [02:15<10:19,  4.92it/s]
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train:  13%|█▎        | 474/3515 [02:17<12:29,  4.06it/s]
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overall: 100%|█████████▉| 3991/4000 [20:15<00:02,  4.44it/s]

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overall: 100%|█████████▉| 3993/4000 [20:15<00:01,  5.18it/s]

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overall: 100%|█████████▉| 3994/4000 [20:16<00:01,  5.41it/s]

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overall: 100%|█████████▉| 3996/4000 [20:16<00:00,  6.06it/s]

train:  14%|█▎        | 481/3515 [02:18<08:20,  6.06it/s]
overall: 100%|█████████▉| 3997/4000 [20:16<00:00,  5.77it/s]

train:  14%|█▎        | 482/3515 [02:18<08:45,  5.77it/s]
overall: 100%|█████████▉| 3998/4000 [20:16<00:00,  5.45it/s]

train:  14%|█▎        | 483/3515 [02:18<09:16,  5.45it/s]
overall: 100%|█████████▉| 3999/4000 [20:17<00:00,  4.87it/s]

train:  14%|█▍        | 484/3515 [02:19<10:22,  4.87it/s]train loss: 3.2673237323760986
train per: 0.8430220781851326
train loss: 3.2616324424743652
train per: 0.8495093328674179
train loss: 3.241835355758667
train per: 0.8358832064760838
train loss: 3.2587592601776123
train per: 0.8413002364066194
train loss: 3.306926727294922
train per: 0.8470471891878185
train loss: 3.263516664505005
train per: 0.8436538652376699
train loss: 3.2522499561309814
train per: 0.8455077452667814
train loss: 3.2643611431121826
train per: 0.8437133084894584
train loss: 3.328956127166748
train per: 0.8445333197472997
train loss: 3.271155834197998
train per: 0.8447261087304455
train loss: 3.28296160697937
train per: 0.8453970484891076
train loss: 3.260960817337036
train per: 0.8460508701472557
train loss: 3.254915237426758
train per: 0.8436798991808444
train loss: 3.274096727371216
train per: 0.8403769349239082
train loss: 3.3034451007843018
train per: 0.8408968194790837
train loss: 3.2498412132263184
train per: 0.8405565288039201
train loss: 3.258915424346924
train per: 0.8392443721984139
train loss: 3.246217727661133
train per: 0.838166088320578
train loss: 3.2601497173309326
train per: 0.8426752849459713
train loss: 3.235276460647583
train per: 0.8436032246757799
train loss: 3.2723007202148438
train per: 0.8406084656084656
train loss: 3.2330081462860107
train per: 0.8358041032428855
train loss: 3.248190402984619
train per: 0.8513143156740783
train loss: 3.249645948410034
train per: 0.8373370939505933
train loss: 3.2426986694335938
train per: 0.8426462574924456
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:   7%|▋         | 180/2703 [00:00<00:01, 1788.26it/s]


word -> phonemes:  13%|█▎        | 359/2703 [00:00<00:01, 1747.92it/s]


word -> phonemes:  20%|█▉        | 534/2703 [00:00<00:01, 1696.46it/s]


word -> phonemes:  26%|██▌       | 704/2703 [00:00<00:01, 1695.02it/s]


word -> phonemes:  34%|███▎      | 911/2703 [00:00<00:00, 1825.35it/s]


word -> phonemes:  42%|████▏     | 1140/2703 [00:00<00:00, 1980.99it/s]


word -> phonemes:  51%|█████     | 1378/2703 [00:00<00:00, 2107.95it/s]


word -> phonemes:  60%|█████▉    | 1618/2703 [00:00<00:00, 2197.96it/s]


word -> phonemes:  68%|██████▊   | 1839/2703 [00:00<00:00, 2200.80it/s]


word -> phonemes:  77%|███████▋  | 2072/2703 [00:01<00:00, 2239.91it/s]


word -> phonemes:  85%|████████▌ | 2302/2703 [00:01<00:00, 2257.87it/s]


word -> phonemes:  94%|█████████▎| 2528/2703 [00:01<00:00, 2158.27it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:01<00:00, 2056.48it/s]



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


dev:   0%|          | 1/2703 [00:01<56:52,  1.26s/it]


dev:   0%|          | 3/2703 [00:01<17:25,  2.58it/s]


dev:   0%|          | 5/2703 [00:01<10:09,  4.43it/s]


dev:   0%|          | 7/2703 [00:01<07:14,  6.20it/s]


dev:   0%|          | 9/2703 [00:01<05:35,  8.04it/s]


dev:   0%|          | 11/2703 [00:01<04:32,  9.89it/s]


dev:   0%|          | 13/2703 [00:02<03:57, 11.35it/s]


dev:   1%|          | 15/2703 [00:02<03:40, 12.21it/s]


dev:   1%|          | 17/2703 [00:02<03:23, 13.21it/s]


dev:   1%|          | 19/2703 [00:02<03:08, 14.26it/s]


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overall: 100%|█████████▉| 3999/4000 [22:14<00:00,  4.87it/s]

train:  14%|█▍        | 484/3515 [04:16<10:22,  4.87it/s]
                                                            

                                                         

overall: 100%|█████████▉| 3999/4000 [22:14<00:00,  4.87it/s]

train:  14%|█▍        | 484/3515 [04:16<10:22,  4.87it/s]
overall: 100%|██████████| 4000/4000 [22:14<00:00, 31.96s/it]

train:  14%|█▍        | 485/3515 [04:16<26:53:56, 31.96s/it]403-128339-0009 Failed!!!

train:  14%|█▍        | 485/3515 [04:16<26:45,  1.89it/s]   

overall: 100%|██████████| 4000/4000 [22:14<00:00,  3.00it/s]
dev loss: 3.3547489643096924
dev per: 0.8552497398543184
[Runner] - Save the checkpoint to:
1. result/downstream/grid/states-4000.ckpt