/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")
2023-09-23 02:45:03 | 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] - The selected feature hidden_states's downsample rate is 960
[Runner] - Start a new experiment
mert_test_8x_400k_encode_norm2 {'model_config': None, 'refresh': False}
using suno's k-means clusters: mert_test_8x_400k_encode_norm2
load local model succeed
load local feat extractor
Wav2Vec2FeatureExtractor {
  "do_normalize": false,
  "feature_extractor_type": "Wav2Vec2FeatureExtractor",
  "feature_size": 1,
  "padding_side": "right",
  "padding_value": 0,
  "return_attention_mask": true,
  "sampling_rate": 24000
}


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


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

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word -> phonemes:  25%|██▍       | 868/3515 [00:00<00:00, 2898.84it/s]

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word -> phonemes:  82%|████████▏ | 2884/3515 [00:01<00:00, 2461.60it/s]

word -> phonemes:  89%|████████▉ | 3133/3515 [00:01<00:00, 2179.27it/s]

word -> phonemes:  96%|█████████▌| 3358/3515 [00:01<00:00, 2071.69it/s]
word -> phonemes: 100%|██████████| 3515/3515 [00:01<00:00, 2456.69it/s]


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train:   4%|▍         | 155/3515 [00:32<11:44,  4.77it/s]
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train:   5%|▍         | 159/3515 [00:33<10:57,  5.10it/s]
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train:   5%|▍         | 160/3515 [00:33<11:06,  5.03it/s]
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train:   5%|▍         | 161/3515 [00:33<11:14,  4.98it/s]
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train:   5%|▍         | 163/3515 [00:34<11:18,  4.94it/s]
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train:   5%|▍         | 164/3515 [00:34<11:24,  4.90it/s]
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train:   5%|▌         | 178/3515 [00:37<12:45,  4.36it/s]
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train:   5%|▌         | 182/3515 [00:38<11:47,  4.71it/s]
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train:   5%|▌         | 183/3515 [00:38<11:49,  4.70it/s]
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train:   5%|▌         | 184/3515 [00:38<10:34,  5.25it/s]
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train:   5%|▌         | 185/3515 [00:38<10:38,  5.22it/s]
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train:   5%|▌         | 186/3515 [00:39<10:58,  5.06it/s]
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train:   5%|▌         | 187/3515 [00:39<10:59,  5.05it/s]
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train:   5%|▌         | 188/3515 [00:39<10:53,  5.09it/s]
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train:   5%|▌         | 189/3515 [00:39<11:06,  4.99it/s]
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train:   5%|▌         | 190/3515 [00:39<11:33,  4.79it/s]
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train:   5%|▌         | 191/3515 [00:40<11:30,  4.81it/s]
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overall:  10%|█         | 417/4000 [01:29<10:54,  5.48it/s]

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overall:  11%|█         | 421/4000 [01:30<12:40,  4.70it/s]

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overall:  11%|█         | 422/4000 [01:31<12:43,  4.69it/s]

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overall:  11%|█         | 423/4000 [01:31<12:36,  4.73it/s]

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overall:  13%|█▎        | 531/4000 [01:54<14:18,  4.04it/s]

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overall:  13%|█▎        | 532/4000 [01:54<13:51,  4.17it/s]

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overall:  13%|█▎        | 533/4000 [01:54<13:11,  4.38it/s]

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overall:  13%|█▎        | 534/4000 [01:54<11:24,  5.06it/s]

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overall:  13%|█▎        | 535/4000 [01:55<11:30,  5.02it/s]

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overall:  13%|█▎        | 536/4000 [01:55<11:00,  5.25it/s]

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overall:  13%|█▎        | 537/4000 [01:55<11:35,  4.98it/s]

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overall:  13%|█▎        | 538/4000 [01:55<11:25,  5.05it/s]

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overall:  13%|█▎        | 539/4000 [01:55<11:48,  4.88it/s]

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overall:  14%|█▎        | 541/4000 [01:56<12:03,  4.78it/s]

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overall:  14%|█▎        | 542/4000 [01:56<12:22,  4.66it/s]

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overall:  14%|█▎        | 543/4000 [01:56<12:14,  4.71it/s]

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overall:  14%|█▎        | 544/4000 [01:56<12:12,  4.72it/s]

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overall:  14%|█▎        | 545/4000 [01:57<12:09,  4.73it/s]

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overall:  14%|█▎        | 546/4000 [01:57<12:18,  4.67it/s]

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overall:  14%|█▎        | 547/4000 [01:57<11:55,  4.82it/s]

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overall:  14%|█▎        | 548/4000 [01:57<11:50,  4.86it/s]

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overall:  14%|█▎        | 549/4000 [01:58<11:53,  4.83it/s]

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overall:  14%|█▍        | 550/4000 [01:58<11:55,  4.82it/s]

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overall:  14%|█▍        | 551/4000 [01:58<12:05,  4.75it/s]

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overall:  14%|█▍        | 552/4000 [01:58<12:14,  4.70it/s]

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overall:  14%|█▍        | 553/4000 [01:58<13:25,  4.28it/s]

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overall:  14%|█▍        | 554/4000 [01:59<15:59,  3.59it/s]

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overall:  14%|█▍        | 555/4000 [01:59<14:54,  3.85it/s]

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overall:  14%|█▍        | 556/4000 [01:59<14:07,  4.06it/s]

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overall:  14%|█▍        | 557/4000 [01:59<12:42,  4.52it/s]

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overall:  14%|█▍        | 558/4000 [02:00<12:27,  4.60it/s]

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overall:  14%|█▍        | 560/4000 [02:00<12:01,  4.77it/s]

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overall:  14%|█▍        | 561/4000 [02:00<12:09,  4.71it/s]

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overall:  14%|█▍        | 562/4000 [02:01<13:04,  4.38it/s]

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overall:  14%|█▍        | 563/4000 [02:01<12:42,  4.51it/s]

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overall:  14%|█▍        | 565/4000 [02:01<12:22,  4.62it/s]

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overall:  14%|█▍        | 566/4000 [02:01<12:26,  4.60it/s]

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overall:  14%|█▍        | 567/4000 [02:01<10:53,  5.25it/s]

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overall:  14%|█▍        | 568/4000 [02:02<11:22,  5.03it/s]

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overall:  14%|█▍        | 569/4000 [02:02<11:39,  4.90it/s]

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overall:  14%|█▍        | 571/4000 [02:02<09:04,  6.29it/s]

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overall:  14%|█▍        | 572/4000 [02:02<09:46,  5.85it/s]

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overall:  14%|█▍        | 574/4000 [02:03<10:47,  5.29it/s]

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overall:  14%|█▍        | 575/4000 [02:03<09:58,  5.72it/s]

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overall:  14%|█▍        | 576/4000 [02:03<10:31,  5.42it/s]

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train:  28%|██▊       | 991/3515 [03:28<12:50,  3.27it/s]
overall:  25%|██▍       | 992/4000 [03:31<13:49,  3.62it/s]

train:  28%|██▊       | 992/3515 [03:28<11:36,  3.62it/s]
overall:  25%|██▍       | 993/4000 [03:31<12:55,  3.88it/s]

train:  28%|██▊       | 993/3515 [03:28<10:50,  3.88it/s]
overall:  25%|██▍       | 994/4000 [03:31<12:10,  4.12it/s]

train:  28%|██▊       | 994/3515 [03:28<10:12,  4.12it/s]
overall:  25%|██▍       | 995/4000 [03:31<12:48,  3.91it/s]

train:  28%|██▊       | 995/3515 [03:29<10:44,  3.91it/s]
overall:  25%|██▍       | 996/4000 [03:32<11:36,  4.31it/s]

train:  28%|██▊       | 996/3515 [03:29<09:43,  4.31it/s]
overall:  25%|██▍       | 997/4000 [03:32<11:27,  4.37it/s]

train:  28%|██▊       | 997/3515 [03:29<09:36,  4.37it/s]
overall:  25%|██▍       | 998/4000 [03:32<11:15,  4.44it/s]

train:  28%|██▊       | 998/3515 [03:29<09:26,  4.44it/s]
overall:  25%|██▍       | 999/4000 [03:32<10:44,  4.66it/s]

train:  28%|██▊       | 999/3515 [03:30<09:00,  4.66it/s]train loss: 4.132419586181641
train per: 0.8739653371192843
train loss: 3.698657274246216
train per: 0.8154011406357894
train loss: 3.511359691619873
train per: 0.804142979518729
train loss: 3.4019951820373535
train per: 0.7996129262267947
train loss: 3.340837001800537
train per: 0.803083066350931
train loss: 3.5317559242248535
train per: 0.8058080129066953
train loss: 3.2755768299102783
train per: 0.8019075031710411
train loss: 3.4163079261779785
train per: 0.8027532688423514
train loss: 3.280190944671631
train per: 0.7999610724538951
train loss: 3.314063310623169
train per: 0.8033433817484242
train loss: 3.4316959381103516
train per: 0.8116163344830309
train loss: 3.3118183612823486
train per: 0.7965761569715588
train loss: 3.2789478302001953
train per: 0.8041911937838474
train loss: 3.266359806060791
train per: 0.7977424917695013
train loss: 3.2049317359924316
train per: 0.7957900685173412
train loss: 3.2308712005615234
train per: 0.7984411354118195
train loss: 3.2277824878692627
train per: 0.8019175846593227
train loss: 3.375605344772339
train per: 0.8077127436449565
train loss: 3.3276398181915283
train per: 0.8053711609971078
train loss: 3.2702300548553467
train per: 0.8037359649564473
train loss: 3.2214202880859375
train per: 0.7993785296801401
train loss: 3.2720437049865723
train per: 0.8049423641979959
train loss: 3.2240843772888184
train per: 0.7932495937458826
train loss: 3.2403931617736816
train per: 0.7952443857331571
train loss: 3.264284133911133
train per: 0.7959338356591912
train loss: 3.2503039836883545
train per: 0.795687540348612
train loss: 3.244513988494873
train per: 0.8037509858044164
train loss: 3.185267210006714
train per: 0.7921536463673023
train loss: 3.2145004272460938
train per: 0.793683990379588
train loss: 3.2092700004577637
train per: 0.7957771595691562
train loss: 3.2096571922302246
train per: 0.7986646492302519
train loss: 3.1837997436523438
train per: 0.7962572870229756
train loss: 3.2037253379821777
train per: 0.7949824838964855
train loss: 3.228752613067627
train per: 0.8016735096928435
train loss: 3.2176437377929688
train per: 0.8054298642533937
train loss: 3.338674545288086
train per: 0.808312872676254
train loss: 3.2992939949035645
train per: 0.800520686743597
train loss: 3.2738795280456543
train per: 0.8058568329718004
train loss: 3.260295867919922
train per: 0.802354155403745
train loss: 3.2442195415496826
train per: 0.8010558034150101
train loss: 3.281517505645752
train per: 0.7995234312946783
train loss: 3.288813352584839
train per: 0.8064886121579551
train loss: 3.2410647869110107
train per: 0.7977421423989737
train loss: 3.3033204078674316
train per: 0.7978070286248452
train loss: 3.2360358238220215
train per: 0.7982338841932636
train loss: 3.1990225315093994
train per: 0.8002286236854138
train loss: 3.3245091438293457
train per: 0.8019648397104446
train loss: 3.2626278400421143
train per: 0.8001673820901164
train loss: 3.2549004554748535
train per: 0.7960904918338343
train loss: 3.282426357269287
train per: 0.8019121970501767
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  12%|█▏        | 335/2703 [00:00<00:00, 3348.77it/s]


word -> phonemes:  25%|██▍       | 670/2703 [00:00<00:00, 3303.09it/s]


word -> phonemes:  37%|███▋      | 1001/2703 [00:00<00:00, 2806.31it/s]


word -> phonemes:  48%|████▊     | 1289/2703 [00:00<00:00, 2705.55it/s]


word -> phonemes:  60%|██████    | 1623/2703 [00:00<00:00, 2910.71it/s]


word -> phonemes:  72%|███████▏  | 1955/2703 [00:00<00:00, 1845.88it/s]


word -> phonemes:  81%|████████  | 2188/2703 [00:00<00:00, 1949.82it/s]


word -> phonemes:  90%|████████▉ | 2421/2703 [00:01<00:00, 1908.72it/s]


word -> phonemes:  98%|█████████▊| 2637/2703 [00:01<00:00, 1955.11it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:01<00:00, 2203.53it/s]



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overall:  25%|██▍       | 999/4000 [05:18<10:44,  4.66it/s]

train:  28%|██▊       | 999/3515 [05:15<09:00,  4.66it/s]
                                                           

                                                         

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overall:  48%|████▊     | 1919/4000 [08:29<07:11,  4.83it/s]

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overall:  48%|████▊     | 1929/4000 [08:31<07:27,  4.63it/s]

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train:  55%|█████▍    | 1932/3515 [08:30<06:05,  4.33it/s]
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train:  55%|█████▍    | 1933/3515 [08:30<05:56,  4.43it/s]
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train:  55%|█████▌    | 1934/3515 [08:30<05:51,  4.49it/s]
overall:  48%|████▊     | 1935/4000 [08:33<07:42,  4.46it/s]

train:  55%|█████▌    | 1935/3515 [08:30<05:54,  4.46it/s]
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train:  55%|█████▌    | 1936/3515 [08:30<05:01,  5.23it/s]
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overall:  48%|████▊     | 1938/4000 [08:33<07:27,  4.61it/s]

train:  55%|█████▌    | 1938/3515 [08:31<05:42,  4.61it/s]
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train:  55%|█████▌    | 1940/3515 [08:31<05:34,  4.70it/s]
overall:  49%|████▊     | 1941/4000 [08:34<07:01,  4.89it/s]

train:  55%|█████▌    | 1941/3515 [08:31<05:21,  4.89it/s]
overall:  49%|████▊     | 1942/4000 [08:34<07:07,  4.82it/s]

train:  55%|█████▌    | 1942/3515 [08:32<05:26,  4.82it/s]
overall:  49%|████▊     | 1943/4000 [08:34<07:10,  4.78it/s]

train:  55%|█████▌    | 1943/3515 [08:32<05:29,  4.78it/s]
overall:  49%|████▊     | 1945/4000 [08:35<06:15,  5.47it/s]

train:  55%|█████▌    | 1945/3515 [08:32<04:46,  5.47it/s]
overall:  49%|████▊     | 1946/4000 [08:35<06:30,  5.26it/s]

train:  55%|█████▌    | 1946/3515 [08:32<04:58,  5.26it/s]
overall:  49%|████▊     | 1948/4000 [08:35<05:47,  5.91it/s]

train:  55%|█████▌    | 1948/3515 [08:33<04:25,  5.91it/s]
overall:  49%|████▊     | 1949/4000 [08:35<06:07,  5.57it/s]

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train:  55%|█████▌    | 1950/3515 [08:33<04:55,  5.30it/s]
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overall:  49%|████▉     | 1952/4000 [08:36<08:16,  4.13it/s]

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overall:  49%|████▉     | 1959/4000 [08:38<07:20,  4.63it/s]

train:  56%|█████▌    | 1959/3515 [08:35<05:35,  4.63it/s]
overall:  49%|████▉     | 1960/4000 [08:38<07:21,  4.62it/s]

train:  56%|█████▌    | 1960/3515 [08:35<05:36,  4.62it/s]
overall:  49%|████▉     | 1961/4000 [08:38<07:24,  4.59it/s]

train:  56%|█████▌    | 1961/3515 [08:36<05:38,  4.59it/s]
overall:  49%|████▉     | 1962/4000 [08:39<08:07,  4.18it/s]

train:  56%|█████▌    | 1962/3515 [08:36<06:11,  4.18it/s]
overall:  49%|████▉     | 1963/4000 [08:39<07:54,  4.29it/s]

train:  56%|█████▌    | 1963/3515 [08:36<06:01,  4.29it/s]
overall:  49%|████▉     | 1964/4000 [08:39<07:33,  4.49it/s]

train:  56%|█████▌    | 1964/3515 [08:36<05:45,  4.49it/s]
overall:  49%|████▉     | 1965/4000 [08:39<07:27,  4.55it/s]

train:  56%|█████▌    | 1965/3515 [08:37<05:40,  4.55it/s]
overall:  49%|████▉     | 1966/4000 [08:39<07:09,  4.73it/s]

train:  56%|█████▌    | 1966/3515 [08:37<05:27,  4.73it/s]
overall:  49%|████▉     | 1967/4000 [08:40<06:53,  4.92it/s]

train:  56%|█████▌    | 1967/3515 [08:37<05:14,  4.92it/s]
overall:  49%|████▉     | 1968/4000 [08:40<06:39,  5.08it/s]

train:  56%|█████▌    | 1968/3515 [08:37<05:04,  5.08it/s]
overall:  49%|████▉     | 1969/4000 [08:40<06:54,  4.90it/s]

train:  56%|█████▌    | 1969/3515 [08:37<05:15,  4.90it/s]
overall:  49%|████▉     | 1970/4000 [08:40<07:06,  4.76it/s]

train:  56%|█████▌    | 1970/3515 [08:38<05:24,  4.76it/s]
overall:  49%|████▉     | 1971/4000 [08:40<07:11,  4.70it/s]

train:  56%|█████▌    | 1971/3515 [08:38<05:28,  4.70it/s]
overall:  49%|████▉     | 1972/4000 [08:41<07:06,  4.76it/s]

train:  56%|█████▌    | 1972/3515 [08:38<05:24,  4.76it/s]
overall:  49%|████▉     | 1973/4000 [08:41<07:06,  4.75it/s]

train:  56%|█████▌    | 1973/3515 [08:38<05:24,  4.75it/s]
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train:  56%|█████▌    | 1974/3515 [08:38<05:26,  4.72it/s]
overall:  49%|████▉     | 1975/4000 [08:42<09:37,  3.51it/s]

train:  56%|█████▌    | 1975/3515 [08:39<07:19,  3.51it/s]
overall:  49%|████▉     | 1976/4000 [08:42<08:47,  3.84it/s]

train:  56%|█████▌    | 1976/3515 [08:39<06:40,  3.84it/s]
overall:  49%|████▉     | 1977/4000 [08:42<08:20,  4.04it/s]

train:  56%|█████▌    | 1977/3515 [08:39<06:20,  4.04it/s]
overall:  49%|████▉     | 1978/4000 [08:42<09:36,  3.51it/s]

train:  56%|█████▋    | 1978/3515 [08:40<07:18,  3.51it/s]
overall:  49%|████▉     | 1979/4000 [08:42<08:20,  4.04it/s]

train:  56%|█████▋    | 1979/3515 [08:40<06:20,  4.04it/s]
overall:  50%|████▉     | 1980/4000 [08:43<08:06,  4.15it/s]

train:  56%|█████▋    | 1980/3515 [08:40<06:09,  4.15it/s]
overall:  50%|████▉     | 1981/4000 [08:43<07:09,  4.71it/s]

train:  56%|█████▋    | 1981/3515 [08:40<05:25,  4.71it/s]
overall:  50%|████▉     | 1982/4000 [08:43<06:57,  4.84it/s]

train:  56%|█████▋    | 1982/3515 [08:40<05:16,  4.84it/s]
overall:  50%|████▉     | 1984/4000 [08:43<06:07,  5.49it/s]

train:  56%|█████▋    | 1984/3515 [08:41<04:39,  5.49it/s]
overall:  50%|████▉     | 1985/4000 [08:44<06:26,  5.21it/s]

train:  56%|█████▋    | 1985/3515 [08:41<04:53,  5.21it/s]
overall:  50%|████▉     | 1986/4000 [08:44<05:41,  5.90it/s]

train:  57%|█████▋    | 1986/3515 [08:41<04:18,  5.90it/s]
overall:  50%|████▉     | 1987/4000 [08:44<06:00,  5.59it/s]

train:  57%|█████▋    | 1987/3515 [08:41<04:33,  5.59it/s]
overall:  50%|████▉     | 1988/4000 [08:44<06:32,  5.13it/s]

train:  57%|█████▋    | 1988/3515 [08:41<04:57,  5.13it/s]
overall:  50%|████▉     | 1989/4000 [08:44<06:50,  4.89it/s]

train:  57%|█████▋    | 1989/3515 [08:42<05:11,  4.89it/s]
overall:  50%|████▉     | 1990/4000 [08:45<07:04,  4.73it/s]

train:  57%|█████▋    | 1990/3515 [08:42<05:22,  4.73it/s]
overall:  50%|████▉     | 1991/4000 [08:45<07:11,  4.66it/s]

train:  57%|█████▋    | 1991/3515 [08:42<05:27,  4.66it/s]
overall:  50%|████▉     | 1992/4000 [08:45<06:18,  5.30it/s]

train:  57%|█████▋    | 1992/3515 [08:42<04:47,  5.30it/s]
overall:  50%|████▉     | 1993/4000 [08:45<06:32,  5.11it/s]

train:  57%|█████▋    | 1993/3515 [08:42<04:57,  5.11it/s]
overall:  50%|████▉     | 1994/4000 [08:45<06:43,  4.98it/s]

train:  57%|█████▋    | 1994/3515 [08:43<05:05,  4.98it/s]
overall:  50%|████▉     | 1995/4000 [08:46<06:56,  4.81it/s]

train:  57%|█████▋    | 1995/3515 [08:43<05:15,  4.81it/s]
overall:  50%|████▉     | 1996/4000 [08:46<06:58,  4.79it/s]

train:  57%|█████▋    | 1996/3515 [08:43<05:17,  4.79it/s]
overall:  50%|████▉     | 1997/4000 [08:46<07:12,  4.63it/s]

train:  57%|█████▋    | 1997/3515 [08:43<05:27,  4.63it/s]
overall:  50%|████▉     | 1998/4000 [08:46<07:10,  4.65it/s]

train:  57%|█████▋    | 1998/3515 [08:44<05:25,  4.65it/s]
overall:  50%|████▉     | 1999/4000 [08:47<08:31,  3.91it/s]

train:  57%|█████▋    | 1999/3515 [08:44<06:27,  3.91it/s]dev loss: 3.575636386871338
dev per: 0.8202445369406868
[Runner] - Save the checkpoint to:
1. result/downstream/grid/dev-best.ckpt
train loss: 3.2284820079803467
train per: 0.7976103266223761
train loss: 3.3399505615234375
train per: 0.811502199874293
train loss: 3.2293803691864014
train per: 0.8013405070217035
train loss: 3.24883770942688
train per: 0.8033892636155862
train loss: 3.2913222312927246
train per: 0.8011303344867359
train loss: 3.2159743309020996
train per: 0.7998173130972457
train loss: 3.220243453979492
train per: 0.8045348535890127
train loss: 3.1965274810791016
train per: 0.8037624956045613
train loss: 3.2181057929992676
train per: 0.7988179781707259
train loss: 3.2295475006103516
train per: 0.8027750247770069
train loss: 3.2039990425109863
train per: 0.7984869801877437
train loss: 3.193908452987671
train per: 0.7959277329597604
train loss: 3.2404582500457764
train per: 0.8032396861554036
train loss: 3.2372138500213623
train per: 0.8104749223257879
train loss: 3.23626708984375
train per: 0.8006630152781782
train loss: 3.2381625175476074
train per: 0.8023182194516145
train loss: 3.2237942218780518
train per: 0.7986577181208053
train loss: 3.237300395965576
train per: 0.8007988157416976
train loss: 3.245864152908325
train per: 0.8105437854938672
train loss: 3.2302451133728027
train per: 0.8015219647180907
train loss: 3.205441951751709
train per: 0.7982875788130811
train loss: 3.211921215057373
train per: 0.8031505678349005
train loss: 3.2304954528808594
train per: 0.795099986756721
train loss: 3.2606399059295654
train per: 0.7972164164924948
train loss: 3.2988696098327637
train per: 0.806904594154661
train loss: 3.2090277671813965
train per: 0.8018607856650586
train loss: 3.344348430633545
train per: 0.801432045393137
train loss: 3.245110273361206
train per: 0.7964746243937064
train loss: 3.2407259941101074
train per: 0.7966379088634823
train loss: 3.206752300262451
train per: 0.7965429788491369
train loss: 3.230569839477539
train per: 0.7997178401949467
train loss: 3.312645435333252
train per: 0.8073004061185283
train loss: 3.2533230781555176
train per: 0.8002075645756458
train loss: 3.438607692718506
train per: 0.8037466775710489
train loss: 3.2479259967803955
train per: 0.8049286765948203
train loss: 3.569728374481201
train per: 0.806159693523574
train loss: 3.32731556892395
train per: 0.8113452962412402
train loss: 3.315931797027588
train per: 0.7987195076556568
train loss: 3.3034679889678955
train per: 0.805091206098557
train loss: 3.2786450386047363
train per: 0.7985764466629691
train loss: 3.2139804363250732
train per: 0.7962729847592501
train loss: 3.250286102294922
train per: 0.7941161343414083
train loss: 3.3148205280303955
train per: 0.8006124278032265
train loss: 3.2477707862854004
train per: 0.796276702942362
train loss: 3.2224173545837402
train per: 0.8050699909464447
train loss: 3.243389129638672
train per: 0.7987630190902032
train loss: 3.233938217163086
train per: 0.7953937592867756
train loss: 3.225623369216919
train per: 0.7960413479812729
train loss: 3.1741883754730225
train per: 0.7981030456126972
train loss: 3.1897120475769043
train per: 0.796320948807939
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  11%|█         | 303/2703 [00:00<00:00, 3023.82it/s]


word -> phonemes:  23%|██▎       | 625/2703 [00:00<00:00, 3135.80it/s]


word -> phonemes:  35%|███▍      | 939/2703 [00:00<00:01, 1536.40it/s]


word -> phonemes:  45%|████▍     | 1208/2703 [00:00<00:00, 1815.32it/s]


word -> phonemes:  57%|█████▋    | 1531/2703 [00:00<00:00, 2177.60it/s]


word -> phonemes:  67%|██████▋   | 1807/2703 [00:00<00:00, 2333.25it/s]


word -> phonemes:  78%|███████▊  | 2104/2703 [00:00<00:00, 2508.12it/s]


word -> phonemes:  89%|████████▊ | 2395/2703 [00:01<00:00, 2620.33it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:01<00:00, 2393.16it/s]



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


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overall:  75%|███████▍  | 2988/4000 [14:06<03:41,  4.57it/s]

train:  85%|████████▌ | 2988/3515 [14:04<01:55,  4.57it/s]
overall:  75%|███████▍  | 2989/4000 [14:07<04:04,  4.14it/s]

train:  85%|████████▌ | 2989/3515 [14:04<02:06,  4.14it/s]
overall:  75%|███████▍  | 2990/4000 [14:07<03:52,  4.34it/s]

train:  85%|████████▌ | 2990/3515 [14:04<02:01,  4.34it/s]
overall:  75%|███████▍  | 2991/4000 [14:07<03:36,  4.66it/s]

train:  85%|████████▌ | 2991/3515 [14:04<01:52,  4.66it/s]
overall:  75%|███████▍  | 2992/4000 [14:07<03:36,  4.66it/s]

train:  85%|████████▌ | 2992/3515 [14:05<01:52,  4.66it/s]
overall:  75%|███████▍  | 2993/4000 [14:08<03:32,  4.74it/s]

train:  85%|████████▌ | 2993/3515 [14:05<01:50,  4.74it/s]
overall:  75%|███████▍  | 2994/4000 [14:08<03:26,  4.87it/s]

train:  85%|████████▌ | 2994/3515 [14:05<01:47,  4.87it/s]
overall:  75%|███████▍  | 2995/4000 [14:08<03:30,  4.79it/s]

train:  85%|████████▌ | 2995/3515 [14:05<01:48,  4.79it/s]
overall:  75%|███████▍  | 2996/4000 [14:08<03:32,  4.72it/s]

train:  85%|████████▌ | 2996/3515 [14:06<01:49,  4.72it/s]
overall:  75%|███████▍  | 2997/4000 [14:08<03:33,  4.70it/s]

train:  85%|████████▌ | 2997/3515 [14:06<01:50,  4.70it/s]
overall:  75%|███████▍  | 2998/4000 [14:09<03:25,  4.87it/s]

train:  85%|████████▌ | 2998/3515 [14:06<01:46,  4.87it/s]
overall:  75%|███████▍  | 2999/4000 [14:09<03:29,  4.78it/s]

train:  85%|████████▌ | 2999/3515 [14:06<01:47,  4.78it/s]dev loss: 3.492049217224121
dev per: 0.8275130072840791
train loss: 3.2813949584960938
train per: 0.8005438733475135
train loss: 3.2449851036071777
train per: 0.8030895473069721
train loss: 3.2032179832458496
train per: 0.804432442952367
train loss: 3.1740024089813232
train per: 0.7967157417893544
train loss: 3.205702543258667
train per: 0.8017611255238475
train loss: 3.19136381149292
train per: 0.7969298547532181
train loss: 3.1865932941436768
train per: 0.7981659982644996
train loss: 3.2201874256134033
train per: 0.7961768219832736
train loss: 3.1705355644226074
train per: 0.8014652192961106
train loss: 3.189091682434082
train per: 0.8004190176892126
train loss: 3.174638271331787
train per: 0.7976901457930792
train loss: 3.1983633041381836
train per: 0.8027738119518663
train loss: 3.358872652053833
train per: 0.8023952095808383
train loss: 3.255887985229492
train per: 0.7984229042824215
train loss: 3.277937650680542
train per: 0.8079148936170213
train loss: 3.314265727996826
train per: 0.8084947647346351
train loss: 3.2010154724121094
train per: 0.7998387282571132
train loss: 3.380523681640625
train per: 0.8016416918119982
train loss: 3.203706741333008
train per: 0.8005708169818052
train loss: 3.306025743484497
train per: 0.8058327531523168
train loss: 3.693857192993164
train per: 0.8097446558985021
train loss: 3.471263885498047
train per: 0.8059602961286367
train loss: 3.3455536365509033
train per: 0.7966212854493645
train loss: 3.2443909645080566
train per: 0.7985732270247587
train loss: 3.313349485397339
train per: 0.7978934391080618
train loss: 3.195828914642334
train per: 0.7997998475028594
train loss: 3.169609785079956
train per: 0.8014544424243856
train loss: 3.2186343669891357
train per: 0.8025564775288982
train loss: 3.2282938957214355
train per: 0.7980621499727413
train loss: 3.209084987640381
train per: 0.8014011782635398
train loss: 3.2507262229919434
train per: 0.8061553873552983
train loss: 3.287250518798828
train per: 0.8076218016575869
train loss: 3.1978116035461426
train per: 0.8089256583546959
train loss: 3.19732928276062
train per: 0.8004461264693351
train loss: 3.2070300579071045
train per: 0.8004971219256933
train loss: 3.312143325805664
train per: 0.8063475431533668
train loss: 3.5803604125976562
train per: 0.8021698927382567
train loss: 3.490016222000122
train per: 0.8086911193251825
train loss: 3.290414810180664
train per: 0.804412388629614
train loss: 3.2468559741973877
train per: 0.8018657929620089
train loss: 3.2727293968200684
train per: 0.8031124148560632
train loss: 3.2963624000549316
train per: 0.8027703447190304
train loss: 3.2422797679901123
train per: 0.7950970705263439
train loss: 3.2389888763427734
train per: 0.7998814922856036
train loss: 3.2271175384521484
train per: 0.8028883482581914
train loss: 3.922830581665039
train per: 0.8260967379077615
train loss: 3.394076108932495
train per: 0.8082941871523674
train loss: 3.251368761062622
train per: 0.799533694003667
train loss: 3.2806339263916016
train per: 0.7996768574385903
train loss: 3.275973081588745
train per: 0.8060459611401519
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  10%|█         | 277/2703 [00:00<00:00, 2766.42it/s]


word -> phonemes:  22%|██▏       | 587/2703 [00:00<00:00, 2960.44it/s]


word -> phonemes:  34%|███▎      | 908/2703 [00:00<00:00, 3069.78it/s]


word -> phonemes:  45%|████▍     | 1215/2703 [00:00<00:00, 3068.33it/s]


word -> phonemes:  57%|█████▋    | 1528/2703 [00:00<00:00, 3088.36it/s]


word -> phonemes:  68%|██████▊   | 1843/2703 [00:00<00:00, 3108.23it/s]


word -> phonemes:  80%|███████▉  | 2154/2703 [00:00<00:00, 2943.12it/s]


word -> phonemes:  91%|█████████ | 2462/2703 [00:00<00:00, 2984.72it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 3006.17it/s]



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train: 100%|██████████| 3515/3515 [17:48<00:00,  5.01it/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 [17:48<00:00,  3.29it/s]
dev loss: 3.5710649490356445
dev per: 0.8113319458896983
[Runner] - Save the checkpoint to:
1. result/downstream/grid/dev-best.ckpt
train loss: 3.1746649742126465
train per: 0.8007760670922518
train loss: 3.1974873542785645
train per: 0.8077615850663173
train loss: 3.1691136360168457
train per: 0.8014505451713395
train loss: 3.1746115684509277
train per: 0.8039971772770805
train loss: 3.2221531867980957
train per: 0.7979738206263166
train loss: 3.19942045211792
train per: 0.7987458109068752
train loss: 3.177877902984619
train per: 0.800659849896741
train loss: 3.2012858390808105
train per: 0.8049038207535842
train loss: 3.2149176597595215
train per: 0.8028782710454896
train loss: 3.1822307109832764
train per: 0.7962531501117398
train loss: 3.2990527153015137
train per: 0.8068584617921029
train loss: 3.346797227859497
train per: 0.7990388918988952
train loss: 3.250328779220581
train per: 0.8072713548874072
train loss: 3.2572104930877686
train per: 0.7985149555187149
train loss: 3.2322330474853516
train per: 0.8000932195074085
train loss: 3.2086825370788574
train per: 0.7972692667137745
train loss: 3.2176353931427
train per: 0.7954649460003661
train loss: 3.2486069202423096
train per: 0.8044821447271966
train loss: 3.258721113204956
train per: 0.8008487979755378
train loss: 3.4394333362579346
train per: 0.799353366298973
train loss: 3.4925169944763184
train per: 0.8056732515269905
train loss: 3.3047637939453125
train per: 0.807930703597085
train loss: 3.360288619995117
train per: 0.8011031255223132
train loss: 3.230318069458008
train per: 0.8020338479809976
train loss: 3.259049654006958
train per: 0.7948935969200973
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.


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

word -> phonemes:   6%|▌         | 216/3515 [00:00<00:01, 2159.65it/s]

word -> phonemes:  13%|█▎        | 452/3515 [00:00<00:01, 2275.74it/s]

word -> phonemes:  21%|██        | 737/3515 [00:00<00:01, 2534.78it/s]

word -> phonemes:  29%|██▉       | 1014/3515 [00:00<00:00, 2627.08it/s]

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word -> phonemes:  45%|████▍     | 1574/3515 [00:00<00:00, 2591.49it/s]

word -> phonemes:  52%|█████▏    | 1835/3515 [00:00<00:00, 2568.61it/s]

word -> phonemes:  60%|██████    | 2119/3515 [00:00<00:00, 2652.16it/s]

word -> phonemes:  68%|██████▊   | 2386/3515 [00:00<00:00, 2654.92it/s]

word -> phonemes:  76%|███████▌  | 2666/3515 [00:01<00:00, 2697.76it/s]

word -> phonemes:  84%|████████▎ | 2942/3515 [00:01<00:00, 2716.52it/s]

word -> phonemes:  91%|█████████▏| 3214/3515 [00:01<00:00, 2519.01it/s]

word -> phonemes:  99%|█████████▉| 3480/3515 [00:01<00:00, 2558.84it/s]
word -> phonemes: 100%|██████████| 3515/3515 [00:01<00:00, 2587.72it/s]


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overall:  90%|████████▉ | 3593/4000 [18:11<01:22,  4.95it/s]

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overall:  90%|████████▉ | 3594/4000 [18:11<01:21,  4.98it/s]

train:   2%|▏         | 79/3515 [00:17<11:29,  4.98it/s]
overall:  90%|████████▉ | 3595/4000 [18:11<01:17,  5.23it/s]

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overall:  90%|████████▉ | 3596/4000 [18:11<01:17,  5.24it/s]

train:   2%|▏         | 81/3515 [00:18<10:55,  5.24it/s]
overall:  90%|████████▉ | 3597/4000 [18:12<01:27,  4.60it/s]

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overall:  90%|████████▉ | 3598/4000 [18:12<01:24,  4.76it/s]

train:   2%|▏         | 83/3515 [00:18<12:01,  4.76it/s]
overall:  90%|████████▉ | 3599/4000 [18:12<01:20,  4.98it/s]

train:   2%|▏         | 84/3515 [00:18<11:28,  4.98it/s]
overall:  90%|█████████ | 3600/4000 [18:12<01:36,  4.13it/s]

train:   2%|▏         | 85/3515 [00:19<13:50,  4.13it/s]
overall:  90%|█████████ | 3601/4000 [18:13<01:33,  4.27it/s]

train:   2%|▏         | 86/3515 [00:19<13:22,  4.27it/s]
overall:  90%|█████████ | 3602/4000 [18:13<01:28,  4.52it/s]

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overall:  90%|█████████ | 3603/4000 [18:13<01:26,  4.59it/s]

train:   3%|▎         | 88/3515 [00:19<12:26,  4.59it/s]
overall:  90%|█████████ | 3604/4000 [18:13<01:24,  4.67it/s]

train:   3%|▎         | 89/3515 [00:19<12:13,  4.67it/s]
overall:  90%|█████████ | 3606/4000 [18:13<01:07,  5.80it/s]

train:   3%|▎         | 91/3515 [00:20<09:50,  5.80it/s]
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overall:  91%|█████████ | 3621/4000 [18:17<01:36,  3.94it/s]

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overall:  91%|█████████ | 3622/4000 [18:17<01:30,  4.19it/s]

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overall:  91%|█████████ | 3623/4000 [18:17<01:26,  4.37it/s]

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overall:  91%|█████████ | 3624/4000 [18:18<01:38,  3.81it/s]

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overall:  91%|█████████ | 3625/4000 [18:18<01:33,  4.02it/s]

train:   3%|▎         | 110/3515 [00:24<14:07,  4.02it/s]
overall:  91%|█████████ | 3626/4000 [18:18<01:26,  4.33it/s]

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overall:  91%|█████████ | 3627/4000 [18:18<01:25,  4.36it/s]

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overall:  91%|█████████ | 3629/4000 [18:19<01:12,  5.14it/s]

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overall:  91%|█████████ | 3630/4000 [18:19<01:13,  5.05it/s]

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overall:  91%|█████████ | 3631/4000 [18:19<01:12,  5.10it/s]

train:   3%|▎         | 116/3515 [00:25<11:06,  5.10it/s]
overall:  91%|█████████ | 3632/4000 [18:19<01:14,  4.96it/s]

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overall:  91%|█████████ | 3633/4000 [18:20<01:26,  4.23it/s]

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overall:  91%|█████████ | 3634/4000 [18:20<01:24,  4.34it/s]

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overall:  91%|█████████ | 3635/4000 [18:20<01:22,  4.42it/s]

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overall:  91%|█████████ | 3636/4000 [18:20<01:36,  3.78it/s]

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overall:  91%|█████████ | 3637/4000 [18:21<01:30,  3.99it/s]

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overall:  91%|█████████ | 3638/4000 [18:21<01:25,  4.22it/s]

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overall:  91%|█████████ | 3639/4000 [18:21<01:23,  4.35it/s]

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overall:  91%|█████████ | 3640/4000 [18:21<01:21,  4.42it/s]

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overall:  91%|█████████▏| 3650/4000 [18:23<01:09,  5.01it/s]

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train:  14%|█▍        | 484/3515 [01:44<09:51,  5.12it/s]train loss: 3.2052416801452637
train per: 0.7983593275268381
train loss: 3.347769260406494
train per: 0.8064995195247663
train loss: 3.256747007369995
train per: 0.8032227681185246
train loss: 3.2449753284454346
train per: 0.8033096926713948
train loss: 3.287431240081787
train per: 0.8079214950427264
train loss: 3.224613666534424
train per: 0.7986752009526645
train loss: 3.187839984893799
train per: 0.8001606425702811
train loss: 3.2404723167419434
train per: 0.7985859410893869
train loss: 3.404423952102661
train per: 0.805609333605054
train loss: 3.3106064796447754
train per: 0.80109969538954
train loss: 3.283848285675049
train per: 0.8091148070065849
train loss: 3.263903856277466
train per: 0.7987282463186077
train loss: 3.227602481842041
train per: 0.8019407687460618
train loss: 3.287339687347412
train per: 0.80456289644731
train loss: 3.328498125076294
train per: 0.8017895251073458
train loss: 3.263758897781372
train per: 0.8008987737070608
train loss: 3.5119235515594482
train per: 0.8072016156839564
train loss: 3.6092898845672607
train per: 0.8136854114179779
train loss: 3.2433433532714844
train per: 0.8009325504514728
train loss: 3.186248302459717
train per: 0.7981539899520972
train loss: 3.4041085243225098
train per: 0.8027574277574278
train loss: 3.1729350090026855
train per: 0.7974630487535849
train loss: 3.2109808921813965
train per: 0.8044612854793737
train loss: 3.1978671550750732
train per: 0.7980694417428515
train loss: 3.211164951324463
train per: 0.7980135730915936
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  12%|█▏        | 320/2703 [00:00<00:00, 3198.62it/s]


word -> phonemes:  24%|██▎       | 640/2703 [00:00<00:00, 3012.09it/s]


word -> phonemes:  36%|███▌      | 962/2703 [00:00<00:00, 3103.58it/s]


word -> phonemes:  47%|████▋     | 1282/2703 [00:00<00:00, 3139.14it/s]


word -> phonemes:  59%|█████▉    | 1597/2703 [00:00<00:00, 2938.01it/s]


word -> phonemes:  70%|███████   | 1894/2703 [00:00<00:00, 2638.44it/s]


word -> phonemes:  80%|████████  | 2164/2703 [00:00<00:00, 2442.50it/s]


word -> phonemes:  89%|████████▉ | 2414/2703 [00:00<00:00, 2290.61it/s]


word -> phonemes:  98%|█████████▊| 2647/2703 [00:01<00:00, 2208.67it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:01<00:00, 2527.69it/s]



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dev:   6%|▌         | 160/2703 [00:10<02:12, 19.15it/s]


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dev:   6%|▋         | 172/2703 [00:11<02:05, 20.10it/s]


dev:   6%|▋         | 174/2703 [00:11<02:10, 19.37it/s]


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dev:   7%|▋         | 180/2703 [00:11<02:09, 19.42it/s]


dev:   7%|▋         | 182/2703 [00:11<02:17, 18.31it/s]


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overall: 100%|█████████▉| 3999/4000 [21:33<00:00,  5.12it/s]

train:  14%|█▍        | 484/3515 [03:39<09:51,  5.12it/s]
                                                            

                                                         

overall: 100%|█████████▉| 3999/4000 [21:33<00:00,  5.12it/s]

train:  14%|█▍        | 484/3515 [03:39<09:51,  5.12it/s]
overall: 100%|██████████| 4000/4000 [21:33<00:00, 31.39s/it]

train:  14%|█▍        | 485/3515 [03:39<26:25:04, 31.39s/it]403-128339-0009 Failed!!!

train:  14%|█▍        | 485/3515 [03:39<22:53,  2.21it/s]   

overall: 100%|██████████| 4000/4000 [21:33<00:00,  3.09it/s]
dev loss: 3.5483815670013428
dev per: 0.8232049947970864
[Runner] - Save the checkpoint to:
1. result/downstream/grid/states-4000.ckpt