/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_valid {'model_config': None, 'refresh': False}
Loading model from Local mert_speech_test_valid
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:  98%|█████████▊| 3436/3515 [00:00<00:00, 3913.83it/s]
word -> phonemes: 100%|██████████| 3515/3515 [00:00<00:00, 4012.98it/s]


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train:   4%|▍         | 155/3515 [00:32<12:24,  4.52it/s]
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train:   4%|▍         | 158/3515 [00:33<11:05,  5.04it/s]
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train:   5%|▍         | 159/3515 [00:33<11:32,  4.84it/s]
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train:   5%|▍         | 160/3515 [00:33<11:36,  4.82it/s]
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train:   5%|▍         | 162/3515 [00:34<11:30,  4.86it/s]
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train:   5%|▍         | 163/3515 [00:34<11:33,  4.83it/s]
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train:   5%|▍         | 164/3515 [00:34<11:47,  4.74it/s]
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train:   5%|▍         | 165/3515 [00:34<11:34,  4.82it/s]
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train:   5%|▍         | 166/3515 [00:35<11:43,  4.76it/s]
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train:   5%|▍         | 167/3515 [00:35<11:40,  4.78it/s]
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train:   5%|▍         | 168/3515 [00:35<11:40,  4.78it/s]
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train:   5%|▍         | 169/3515 [00:35<12:40,  4.40it/s]
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train:   5%|▍         | 170/3515 [00:36<14:50,  3.76it/s]
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train:   5%|▌         | 178/3515 [00:37<12:48,  4.34it/s]
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train:   5%|▌         | 180/3515 [00:38<12:08,  4.58it/s]
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train:   5%|▌         | 181/3515 [00:38<12:11,  4.56it/s]
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train:   5%|▌         | 182/3515 [00:38<11:50,  4.69it/s]
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train:   5%|▌         | 183/3515 [00:38<11:46,  4.72it/s]
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train:   5%|▌         | 184/3515 [00:38<10:17,  5.40it/s]
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train:   5%|▌         | 185/3515 [00:39<10:35,  5.24it/s]
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train:   5%|▌         | 186/3515 [00:39<10:52,  5.10it/s]
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train:   5%|▌         | 187/3515 [00:39<11:02,  5.02it/s]
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train:   5%|▌         | 188/3515 [00:39<10:56,  5.07it/s]
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train:   5%|▌         | 189/3515 [00:39<11:11,  4.96it/s]
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train:   5%|▌         | 190/3515 [00:40<11:44,  4.72it/s]
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train:   5%|▌         | 191/3515 [00:40<11:28,  4.83it/s]
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train:   5%|▌         | 192/3515 [00:40<11:24,  4.86it/s]
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train:   6%|▌         | 194/3515 [00:41<14:07,  3.92it/s]
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train:   6%|▌         | 195/3515 [00:41<12:40,  4.37it/s]
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train:   6%|▌         | 197/3515 [00:41<10:01,  5.52it/s]
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train:   6%|▌         | 198/3515 [00:41<10:14,  5.39it/s]
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overall:  13%|█▎        | 536/4000 [01:55<12:17,  4.70it/s]

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overall:  13%|█▎        | 539/4000 [01:55<11:07,  5.18it/s]

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overall:  14%|█▎        | 546/4000 [01:57<12:09,  4.74it/s]

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overall:  14%|█▎        | 547/4000 [01:57<11:52,  4.85it/s]

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overall:  14%|█▎        | 548/4000 [01:57<11:42,  4.92it/s]

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overall:  14%|█▎        | 549/4000 [01:57<11:43,  4.90it/s]

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overall:  14%|█▍        | 550/4000 [01:58<11:29,  5.00it/s]

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overall:  14%|█▍        | 551/4000 [01:58<11:44,  4.90it/s]

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overall:  14%|█▍        | 552/4000 [01:58<11:51,  4.85it/s]

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overall:  14%|█▍        | 553/4000 [01:58<11:58,  4.80it/s]

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overall:  14%|█▍        | 554/4000 [01:59<15:27,  3.72it/s]

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overall:  14%|█▍        | 555/4000 [01:59<14:26,  3.98it/s]

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overall:  14%|█▍        | 556/4000 [01:59<13:42,  4.18it/s]

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overall:  14%|█▍        | 557/4000 [01:59<12:25,  4.62it/s]

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overall:  14%|█▍        | 558/4000 [02:00<15:27,  3.71it/s]

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overall:  14%|█▍        | 560/4000 [02:00<13:32,  4.23it/s]

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overall:  14%|█▍        | 561/4000 [02:00<13:04,  4.38it/s]

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overall:  14%|█▍        | 562/4000 [02:01<12:35,  4.55it/s]

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overall:  14%|█▍        | 563/4000 [02:01<12:25,  4.61it/s]

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overall:  14%|█▍        | 565/4000 [02:01<12:08,  4.72it/s]

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overall:  14%|█▍        | 566/4000 [02:01<12:02,  4.75it/s]

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overall:  14%|█▍        | 568/4000 [02:02<11:07,  5.15it/s]

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overall:  14%|█▍        | 569/4000 [02:02<11:20,  5.04it/s]

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overall:  14%|█▍        | 571/4000 [02:02<08:47,  6.50it/s]

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overall:  14%|█▍        | 572/4000 [02:02<09:32,  5.99it/s]

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overall:  14%|█▍        | 574/4000 [02:03<10:18,  5.54it/s]

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overall:  14%|█▍        | 577/4000 [02:03<09:13,  6.18it/s]

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train:  28%|██▊       | 993/3515 [03:29<08:42,  4.83it/s]
overall:  25%|██▍       | 994/4000 [03:31<10:13,  4.90it/s]

train:  28%|██▊       | 994/3515 [03:29<08:34,  4.90it/s]
overall:  25%|██▍       | 995/4000 [03:31<10:19,  4.85it/s]

train:  28%|██▊       | 995/3515 [03:29<08:39,  4.85it/s]
overall:  25%|██▍       | 996/4000 [03:32<15:17,  3.27it/s]

train:  28%|██▊       | 996/3515 [03:29<12:49,  3.27it/s]
overall:  25%|██▍       | 997/4000 [03:32<13:54,  3.60it/s]

train:  28%|██▊       | 997/3515 [03:30<11:39,  3.60it/s]
overall:  25%|██▍       | 998/4000 [03:32<13:01,  3.84it/s]

train:  28%|██▊       | 998/3515 [03:30<10:55,  3.84it/s]
overall:  25%|██▍       | 999/4000 [03:32<12:03,  4.15it/s]

train:  28%|██▊       | 999/3515 [03:30<10:06,  4.15it/s]train loss: 3.7284576892852783
train per: 0.8166403257346442
train loss: 2.6450278759002686
train per: 0.6733075880412266
train loss: 2.483715772628784
train per: 0.648547620901799
train loss: 2.4309213161468506
train per: 0.6298861697522219
train loss: 2.3802735805511475
train per: 0.6222315085666528
train loss: 2.340567111968994
train per: 0.6250067222371605
train loss: 2.2877700328826904
train per: 0.6087179236998732
train loss: 2.3590569496154785
train per: 0.6170405017540129
train loss: 2.263744354248047
train per: 0.5985840105104374
train loss: 2.2358922958374023
train per: 0.5980816662099205
train loss: 2.2383832931518555
train per: 0.6045391116610938
train loss: 2.251986026763916
train per: 0.5991229808740461
train loss: 2.2962212562561035
train per: 0.604214739816341
train loss: 2.2393951416015625
train per: 0.5880271438489619
train loss: 2.1885263919830322
train per: 0.5835511290056744
train loss: 2.209282398223877
train per: 0.5886924150767799
train loss: 2.18808650970459
train per: 0.5878212974296205
train loss: 2.1930251121520996
train per: 0.5885231689924215
train loss: 2.2173306941986084
train per: 0.5896983886517009
train loss: 2.1576573848724365
train per: 0.5808368158702986
train loss: 2.1704330444335938
train per: 0.5827763939924536
train loss: 2.2075695991516113
train per: 0.5864034757276677
train loss: 2.2248477935791016
train per: 0.5816241380824806
train loss: 2.2171101570129395
train per: 0.5835715143509067
train loss: 2.180539131164551
train per: 0.5760176557135851
train loss: 2.1304681301116943
train per: 0.5704325371207231
train loss: 2.193716526031494
train per: 0.581747831230284
train loss: 2.154224157333374
train per: 0.578201535552366
train loss: 2.1441402435302734
train per: 0.5727805082087211
train loss: 2.159921407699585
train per: 0.5787621561214542
train loss: 2.181696653366089
train per: 0.5753536518000817
train loss: 2.1470417976379395
train per: 0.5742908930583451
train loss: 2.1557135581970215
train per: 0.5758164764380156
train loss: 2.1661477088928223
train per: 0.5808949638792162
train loss: 2.149470806121826
train per: 0.5766777517309055
train loss: 2.1522793769836426
train per: 0.5776043493511048
train loss: 2.2002549171447754
train per: 0.578478281264659
train loss: 2.1895744800567627
train per: 0.5785972523499638
train loss: 2.173288583755493
train per: 0.5783162136924362
train loss: 2.1792454719543457
train per: 0.5780757282006961
train loss: 2.1395580768585205
train per: 0.5792163092401377
train loss: 2.1413626670837402
train per: 0.5756185482549566
train loss: 2.144300937652588
train per: 0.5708017960230918
train loss: 2.174093723297119
train per: 0.5776256284580986
train loss: 2.131256580352783
train per: 0.5715655355115429
train loss: 2.132129192352295
train per: 0.5700045724737083
train loss: 2.169001817703247
train per: 0.5805584281282317
train loss: 2.1718790531158447
train per: 0.5805728787019789
train loss: 2.161512851715088
train per: 0.5756855618461825
train loss: 2.118135929107666
train per: 0.5709168169577785
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  17%|█▋        | 460/2703 [00:00<00:00, 4356.60it/s]


word -> phonemes:  34%|███▎      | 911/2703 [00:00<00:00, 4440.82it/s]


word -> phonemes:  50%|█████     | 1356/2703 [00:00<00:00, 4189.35it/s]


word -> phonemes:  66%|██████▌   | 1783/2703 [00:00<00:00, 4215.49it/s]


word -> phonemes:  82%|████████▏ | 2218/2703 [00:00<00:00, 4260.86it/s]


word -> phonemes:  98%|█████████▊| 2645/2703 [00:00<00:00, 2481.37it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 3191.22it/s]



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overall:  48%|████▊     | 1937/4000 [08:45<06:44,  5.11it/s]

train:  55%|█████▌    | 1937/3515 [08:43<05:09,  5.11it/s]
overall:  48%|████▊     | 1938/4000 [08:45<06:42,  5.12it/s]

train:  55%|█████▌    | 1938/3515 [08:43<05:08,  5.12it/s]
overall:  48%|████▊     | 1939/4000 [08:46<07:13,  4.75it/s]

train:  55%|█████▌    | 1939/3515 [08:44<05:31,  4.75it/s]
overall:  48%|████▊     | 1940/4000 [08:46<07:41,  4.46it/s]

train:  55%|█████▌    | 1940/3515 [08:44<05:52,  4.46it/s]
overall:  49%|████▊     | 1941/4000 [08:46<07:14,  4.74it/s]

train:  55%|█████▌    | 1941/3515 [08:44<05:31,  4.74it/s]
overall:  49%|████▊     | 1942/4000 [08:46<07:13,  4.74it/s]

train:  55%|█████▌    | 1942/3515 [08:44<05:31,  4.74it/s]
overall:  49%|████▊     | 1943/4000 [08:47<07:12,  4.75it/s]

train:  55%|█████▌    | 1943/3515 [08:44<05:30,  4.75it/s]
overall:  49%|████▊     | 1945/4000 [08:47<06:16,  5.46it/s]

train:  55%|█████▌    | 1945/3515 [08:45<04:47,  5.46it/s]
overall:  49%|████▊     | 1946/4000 [08:47<06:29,  5.27it/s]

train:  55%|█████▌    | 1946/3515 [08:45<04:57,  5.27it/s]
overall:  49%|████▊     | 1947/4000 [08:47<05:48,  5.89it/s]

train:  55%|█████▌    | 1947/3515 [08:45<04:26,  5.89it/s]
overall:  49%|████▊     | 1948/4000 [08:47<06:44,  5.07it/s]

train:  55%|█████▌    | 1948/3515 [08:45<05:09,  5.07it/s]
overall:  49%|████▊     | 1949/4000 [08:48<06:51,  4.99it/s]

train:  55%|█████▌    | 1949/3515 [08:45<05:14,  4.99it/s]
overall:  49%|████▉     | 1950/4000 [08:48<07:02,  4.86it/s]

train:  55%|█████▌    | 1950/3515 [08:46<05:22,  4.85it/s]
overall:  49%|████▉     | 1951/4000 [08:48<07:11,  4.75it/s]

train:  56%|█████▌    | 1951/3515 [08:46<05:28,  4.75it/s]
overall:  49%|████▉     | 1952/4000 [08:48<07:09,  4.77it/s]

train:  56%|█████▌    | 1952/3515 [08:46<05:27,  4.77it/s]
overall:  49%|████▉     | 1953/4000 [08:49<07:39,  4.45it/s]

train:  56%|█████▌    | 1953/3515 [08:46<05:50,  4.45it/s]
overall:  49%|████▉     | 1954/4000 [08:49<07:59,  4.26it/s]

train:  56%|█████▌    | 1954/3515 [08:47<06:06,  4.26it/s]
overall:  49%|████▉     | 1955/4000 [08:49<07:33,  4.51it/s]

train:  56%|█████▌    | 1955/3515 [08:47<05:45,  4.51it/s]
overall:  49%|████▉     | 1956/4000 [08:49<07:59,  4.26it/s]

train:  56%|█████▌    | 1956/3515 [08:47<06:05,  4.26it/s]
overall:  49%|████▉     | 1957/4000 [08:49<07:43,  4.41it/s]

train:  56%|█████▌    | 1957/3515 [08:47<05:53,  4.41it/s]
overall:  49%|████▉     | 1958/4000 [08:50<07:39,  4.45it/s]

train:  56%|█████▌    | 1958/3515 [08:48<05:50,  4.45it/s]
overall:  49%|████▉     | 1959/4000 [08:50<07:26,  4.57it/s]

train:  56%|█████▌    | 1959/3515 [08:48<05:40,  4.57it/s]
overall:  49%|████▉     | 1960/4000 [08:50<07:35,  4.48it/s]

train:  56%|█████▌    | 1960/3515 [08:48<05:47,  4.48it/s]
overall:  49%|████▉     | 1961/4000 [08:50<07:29,  4.54it/s]

train:  56%|█████▌    | 1961/3515 [08:48<05:42,  4.54it/s]
overall:  49%|████▉     | 1962/4000 [08:51<07:24,  4.58it/s]

train:  56%|█████▌    | 1962/3515 [08:48<05:38,  4.58it/s]
overall:  49%|████▉     | 1963/4000 [08:51<07:45,  4.38it/s]

train:  56%|█████▌    | 1963/3515 [08:49<05:54,  4.38it/s]
overall:  49%|████▉     | 1964/4000 [08:51<08:11,  4.14it/s]

train:  56%|█████▌    | 1964/3515 [08:49<06:14,  4.14it/s]
overall:  49%|████▉     | 1965/4000 [08:51<07:56,  4.27it/s]

train:  56%|█████▌    | 1965/3515 [08:49<06:03,  4.27it/s]
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train:  56%|█████▌    | 1966/3515 [08:49<05:47,  4.45it/s]
overall:  49%|████▉     | 1967/4000 [08:52<07:10,  4.72it/s]

train:  56%|█████▌    | 1967/3515 [08:50<05:28,  4.72it/s]
overall:  49%|████▉     | 1968/4000 [08:52<06:48,  4.97it/s]

train:  56%|█████▌    | 1968/3515 [08:50<05:11,  4.97it/s]
overall:  49%|████▉     | 1969/4000 [08:52<06:59,  4.85it/s]

train:  56%|█████▌    | 1969/3515 [08:50<05:18,  4.85it/s]
overall:  49%|████▉     | 1970/4000 [08:52<07:06,  4.76it/s]

train:  56%|█████▌    | 1970/3515 [08:50<05:24,  4.76it/s]
overall:  49%|████▉     | 1971/4000 [08:53<07:44,  4.37it/s]

train:  56%|█████▌    | 1971/3515 [08:50<05:53,  4.37it/s]
overall:  49%|████▉     | 1972/4000 [08:53<07:55,  4.26it/s]

train:  56%|█████▌    | 1972/3515 [08:51<06:01,  4.26it/s]
overall:  49%|████▉     | 1973/4000 [08:53<07:44,  4.36it/s]

train:  56%|█████▌    | 1973/3515 [08:51<05:53,  4.36it/s]
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train:  56%|█████▌    | 1974/3515 [08:51<05:49,  4.41it/s]
overall:  49%|████▉     | 1975/4000 [08:53<07:35,  4.45it/s]

train:  56%|█████▌    | 1975/3515 [08:51<05:46,  4.45it/s]
overall:  49%|████▉     | 1976/4000 [08:54<07:20,  4.59it/s]

train:  56%|█████▌    | 1976/3515 [08:52<05:35,  4.59it/s]
overall:  49%|████▉     | 1977/4000 [08:54<07:46,  4.34it/s]

train:  56%|█████▌    | 1977/3515 [08:52<05:54,  4.34it/s]
overall:  49%|████▉     | 1978/4000 [08:54<07:46,  4.33it/s]

train:  56%|█████▋    | 1978/3515 [08:52<05:54,  4.33it/s]
overall:  49%|████▉     | 1979/4000 [08:54<07:07,  4.73it/s]

train:  56%|█████▋    | 1979/3515 [08:52<05:24,  4.73it/s]
overall:  50%|████▉     | 1980/4000 [08:55<07:46,  4.33it/s]

train:  56%|█████▋    | 1980/3515 [08:52<05:56,  4.31it/s]
overall:  50%|████▉     | 1981/4000 [08:55<06:56,  4.85it/s]

train:  56%|█████▋    | 1981/3515 [08:53<05:15,  4.86it/s]
overall:  50%|████▉     | 1982/4000 [08:55<06:53,  4.88it/s]

train:  56%|█████▋    | 1982/3515 [08:53<05:13,  4.89it/s]
overall:  50%|████▉     | 1984/4000 [08:55<06:00,  5.59it/s]

train:  56%|█████▋    | 1984/3515 [08:53<04:33,  5.59it/s]
overall:  50%|████▉     | 1985/4000 [08:55<06:18,  5.32it/s]

train:  56%|█████▋    | 1985/3515 [08:53<04:47,  5.32it/s]
overall:  50%|████▉     | 1986/4000 [08:56<05:40,  5.91it/s]

train:  57%|█████▋    | 1986/3515 [08:53<04:18,  5.92it/s]
overall:  50%|████▉     | 1987/4000 [08:56<06:13,  5.39it/s]

train:  57%|█████▋    | 1987/3515 [08:54<04:43,  5.39it/s]
overall:  50%|████▉     | 1988/4000 [08:56<07:02,  4.76it/s]

train:  57%|█████▋    | 1988/3515 [08:54<05:20,  4.76it/s]
overall:  50%|████▉     | 1989/4000 [08:56<07:08,  4.70it/s]

train:  57%|█████▋    | 1989/3515 [08:54<05:24,  4.70it/s]
overall:  50%|████▉     | 1990/4000 [08:57<07:19,  4.57it/s]

train:  57%|█████▋    | 1990/3515 [08:54<05:33,  4.57it/s]
overall:  50%|████▉     | 1991/4000 [08:57<07:23,  4.53it/s]

train:  57%|█████▋    | 1991/3515 [08:55<05:36,  4.53it/s]
overall:  50%|████▉     | 1992/4000 [08:57<06:28,  5.16it/s]

train:  57%|█████▋    | 1992/3515 [08:55<04:54,  5.16it/s]
overall:  50%|████▉     | 1993/4000 [08:57<06:49,  4.90it/s]

train:  57%|█████▋    | 1993/3515 [08:55<05:10,  4.90it/s]
overall:  50%|████▉     | 1994/4000 [08:57<06:48,  4.92it/s]

train:  57%|█████▋    | 1994/3515 [08:55<05:09,  4.92it/s]
overall:  50%|████▉     | 1995/4000 [08:58<07:32,  4.43it/s]

train:  57%|█████▋    | 1995/3515 [08:55<05:42,  4.43it/s]
overall:  50%|████▉     | 1996/4000 [08:58<07:38,  4.37it/s]

train:  57%|█████▋    | 1996/3515 [08:56<05:47,  4.37it/s]
overall:  50%|████▉     | 1997/4000 [08:58<07:29,  4.46it/s]

train:  57%|█████▋    | 1997/3515 [08:56<05:40,  4.46it/s]
overall:  50%|████▉     | 1998/4000 [08:58<07:16,  4.59it/s]

train:  57%|█████▋    | 1998/3515 [08:56<05:30,  4.59it/s]
overall:  50%|████▉     | 1999/4000 [08:58<07:11,  4.64it/s]

train:  57%|█████▋    | 1999/3515 [08:56<05:26,  4.64it/s]dev loss: 2.415306329727173
dev per: 0.6094849115504682
[Runner] - Save the checkpoint to:
1. result/downstream/grid/dev-best.ckpt
train loss: 2.1477255821228027
train per: 0.5770328643241468
train loss: 2.1205010414123535
train per: 0.5784098051539912
train loss: 2.1962127685546875
train per: 0.5793589275943827
train loss: 2.1283071041107178
train per: 0.5748926919003289
train loss: 2.1840450763702393
train per: 0.5783852364475202
train loss: 2.150513172149658
train per: 0.5705686715383174
train loss: 2.115816593170166
train per: 0.5686188131640322
train loss: 2.130099296569824
train per: 0.5687195458883809
train loss: 2.1226704120635986
train per: 0.5664887278966684
train loss: 2.122260570526123
train per: 0.5696364300245162
train loss: 2.160618305206299
train per: 0.5708190142306894
train loss: 2.1102352142333984
train per: 0.5652142408579296
train loss: 2.1579182147979736
train per: 0.5711465451784359
train loss: 2.1065073013305664
train per: 0.5651353750554816
train loss: 2.130510091781616
train per: 0.5718266551359662
train loss: 2.1690802574157715
train per: 0.5722982515949935
train loss: 2.1535210609436035
train per: 0.5742463883517234
train loss: 2.1066901683807373
train per: 0.5707342960087144
train loss: 2.1574597358703613
train per: 0.5725695614967715
train loss: 2.1482291221618652
train per: 0.5715669318574887
train loss: 2.1096272468566895
train per: 0.5654424572508034
train loss: 2.111311674118042
train per: 0.5620954939553059
train loss: 2.0850069522857666
train per: 0.5676334260362866
train loss: 2.1455795764923096
train per: 0.5702308569257077
train loss: 2.173227071762085
train per: 0.5808653822793421
train loss: 2.144441843032837
train per: 0.5695841948081782
train loss: 2.128669023513794
train per: 0.5687922183193731
train loss: 2.170419216156006
train per: 0.5748728262155448
train loss: 2.1406893730163574
train per: 0.5662715391269786
train loss: 2.147134304046631
train per: 0.5714426415187255
train loss: 2.120360851287842
train per: 0.5658073618058228
train loss: 2.163041353225708
train per: 0.5809926801391017
train loss: 2.1560580730438232
train per: 0.5736854243542435
train loss: 2.1508917808532715
train per: 0.5762114087098753
train loss: 2.1006717681884766
train per: 0.5611981366609543
train loss: 2.1137213706970215
train per: 0.5785345841754397
train loss: 2.16504168510437
train per: 0.5792365682735188
train loss: 2.125297784805298
train per: 0.571853984167556
train loss: 2.109556198120117
train per: 0.5697522461203376
train loss: 2.1977670192718506
train per: 0.5760537992235164
train loss: 2.1510491371154785
train per: 0.566245560401025
train loss: 2.150707244873047
train per: 0.5732140101836136
train loss: 2.1101250648498535
train per: 0.5608444532961562
train loss: 2.091540575027466
train per: 0.5657748891575978
train loss: 2.129403591156006
train per: 0.5661257747754022
train loss: 2.1288256645202637
train per: 0.5697876783849635
train loss: 2.11083984375
train per: 0.5644873699851412
train loss: 2.16599702835083
train per: 0.5719186019561489
train loss: 2.07550048828125
train per: 0.5550498069682094
train loss: 2.114668846130371
train per: 0.5596756625922789
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  18%|█▊        | 493/2703 [00:00<00:00, 4924.37it/s]


word -> phonemes:  36%|███▋      | 986/2703 [00:00<00:00, 4762.34it/s]


word -> phonemes:  56%|█████▌    | 1507/2703 [00:00<00:00, 4960.32it/s]


word -> phonemes:  75%|███████▍  | 2022/2703 [00:00<00:00, 5031.07it/s]


word -> phonemes:  93%|█████████▎| 2526/2703 [00:00<00:00, 4848.92it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 4895.61it/s]



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


dev:   0%|          | 1/2703 [00:01<55:22,  1.23s/it]


dev:   0%|          | 3/2703 [00:01<16:29,  2.73it/s]


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dev:   1%|          | 19/2703 [00:02<03:07, 14.33it/s]


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dev:   1%|          | 33/2703 [00:03<02:53, 15.41it/s]


dev:   1%|▏         | 36/2703 [00:03<02:40, 16.65it/s]


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dev:   2%|▏         | 58/2703 [00:04<02:24, 18.31it/s]


dev:   2%|▏         | 61/2703 [00:04<02:25, 18.22it/s]


dev:   2%|▏         | 64/2703 [00:04<02:19, 18.91it/s]


dev:   2%|▏         | 66/2703 [00:05<02:32, 17.33it/s]


dev:   3%|▎         | 68/2703 [00:05<02:27, 17.81it/s]


dev:   3%|▎         | 70/2703 [00:05<02:35, 16.98it/s]


dev:   3%|▎         | 72/2703 [00:05<02:32, 17.26it/s]


dev:   3%|▎         | 74/2703 [00:05<02:30, 17.51it/s]


dev:   3%|▎         | 76/2703 [00:05<02:25, 18.05it/s]


dev:   3%|▎         | 78/2703 [00:05<02:26, 17.92it/s]


dev:   3%|▎         | 80/2703 [00:05<02:30, 17.47it/s]


dev:   3%|▎         | 82/2703 [00:06<02:32, 17.24it/s]


dev:   3%|▎         | 84/2703 [00:06<02:31, 17.31it/s]


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dev:   3%|▎         | 90/2703 [00:06<02:29, 17.43it/s]


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dev:   3%|▎         | 94/2703 [00:06<02:33, 16.94it/s]


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dev:   4%|▍         | 102/2703 [00:07<02:21, 18.44it/s]


dev:   4%|▍         | 104/2703 [00:07<02:19, 18.65it/s]


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dev:   4%|▍         | 108/2703 [00:07<02:21, 18.38it/s]


dev:   4%|▍         | 111/2703 [00:07<02:13, 19.41it/s]


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dev:   4%|▍         | 115/2703 [00:07<02:23, 17.97it/s]


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dev:   4%|▍         | 119/2703 [00:08<02:29, 17.26it/s]


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dev:   5%|▍         | 124/2703 [00:08<02:15, 19.01it/s]


dev:   5%|▍         | 126/2703 [00:08<02:21, 18.18it/s]


dev:   5%|▍         | 129/2703 [00:08<02:13, 19.27it/s]


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overall:  74%|███████▍  | 2958/4000 [14:24<03:58,  4.37it/s]

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overall:  74%|███████▍  | 2959/4000 [14:24<03:57,  4.39it/s]

train:  84%|████████▍ | 2959/3515 [14:22<02:06,  4.39it/s]
overall:  74%|███████▍  | 2960/4000 [14:24<03:56,  4.39it/s]

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overall:  74%|███████▍  | 2961/4000 [14:24<03:24,  5.08it/s]

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train:  85%|████████▍ | 2979/3515 [14:26<02:24,  3.71it/s]
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train:  85%|████████▍ | 2980/3515 [14:26<02:15,  3.95it/s]
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train:  85%|████████▍ | 2982/3515 [14:27<01:35,  5.60it/s]
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train:  85%|████████▍ | 2983/3515 [14:27<01:43,  5.15it/s]
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train:  85%|████████▍ | 2984/3515 [14:27<01:42,  5.18it/s]
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train:  85%|████████▌ | 2990/3515 [14:28<01:50,  4.76it/s]
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train:  85%|████████▌ | 2991/3515 [14:29<01:44,  5.04it/s]
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train:  85%|████████▌ | 2992/3515 [14:29<01:48,  4.84it/s]
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train:  85%|████████▌ | 2993/3515 [14:29<01:47,  4.84it/s]
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train:  85%|████████▌ | 2994/3515 [14:29<01:56,  4.47it/s]
overall:  75%|███████▍  | 2995/4000 [14:32<03:46,  4.44it/s]

train:  85%|████████▌ | 2995/3515 [14:29<01:57,  4.44it/s]
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train:  85%|████████▌ | 2996/3515 [14:30<01:55,  4.49it/s]
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train:  85%|████████▌ | 2997/3515 [14:30<01:56,  4.46it/s]
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train:  85%|████████▌ | 2998/3515 [14:30<01:54,  4.53it/s]
overall:  75%|███████▍  | 2999/4000 [14:32<03:43,  4.48it/s]

train:  85%|████████▌ | 2999/3515 [14:30<01:55,  4.48it/s]dev loss: 2.4206907749176025
dev per: 0.6135431841831426
train loss: 2.080261707305908
train per: 0.5614819202498587
train loss: 2.0914978981018066
train per: 0.568041634541249
train loss: 2.1148123741149902
train per: 0.5655865323797012
train loss: 2.1334404945373535
train per: 0.5674311060777651
train loss: 2.1092529296875
train per: 0.5683496308122131
train loss: 2.11047625541687
train per: 0.5651774856015236
train loss: 2.1293511390686035
train per: 0.5645535777105467
train loss: 2.142319917678833
train per: 0.5721385902031063
train loss: 2.062523603439331
train per: 0.5584627366986321
train loss: 2.0953636169433594
train per: 0.5598647715639359
train loss: 2.0982887744903564
train per: 0.5595687686632707
train loss: 2.100226879119873
train per: 0.5649857230267183
train loss: 2.1790385246276855
train per: 0.5746364414029085
train loss: 2.130749225616455
train per: 0.5648671600145578
train loss: 2.0734329223632812
train per: 0.5685957446808511
train loss: 2.1640708446502686
train per: 0.5718659154639706
train loss: 2.1473467350006104
train per: 0.5727681142725493
train loss: 2.1245481967926025
train per: 0.5659745307625428
train loss: 2.1061666011810303
train per: 0.5633012248781067
train loss: 2.122347354888916
train per: 0.5625435135762358
train loss: 2.101130723953247
train per: 0.5669278746201823
train loss: 2.1687607765197754
train per: 0.575234592351582
train loss: 2.1752102375030518
train per: 0.5772536071283187
train loss: 2.1028051376342773
train per: 0.5650673753904975
train loss: 2.09907865524292
train per: 0.5633040308747856
train loss: 2.103196144104004
train per: 0.5657643919176516
train loss: 2.0766444206237793
train per: 0.5588978348641183
train loss: 2.0727152824401855
train per: 0.5542951700321358
train loss: 2.085575580596924
train per: 0.5640333052485503
train loss: 2.156515121459961
train per: 0.57027500398062
train loss: 2.0740532875061035
train per: 0.5560440783615316
train loss: 2.0854907035827637
train per: 0.5612300224626269
train loss: 2.0850327014923096
train per: 0.5601258447914239
train loss: 2.097451686859131
train per: 0.5676583373016868
train loss: 2.121948003768921
train per: 0.5619832548403977
train loss: 2.112704277038574
train per: 0.572299123145646
train loss: 2.1550397872924805
train per: 0.577684625816792
train loss: 2.092372417449951
train per: 0.5647095062079424
train loss: 2.1130266189575195
train per: 0.5665305473058974
train loss: 2.087562084197998
train per: 0.5637145786959458
train loss: 2.069800853729248
train per: 0.5563068662059365
train loss: 2.105576515197754
train per: 0.5684715882260349
train loss: 2.0908446311950684
train per: 0.5665874435869362
train loss: 2.153364658355713
train per: 0.5655552770117824
train loss: 2.089634895324707
train per: 0.5634867229152648
train loss: 2.1214771270751953
train per: 0.5651043619547557
train loss: 2.1124844551086426
train per: 0.5683737283495202
train loss: 2.155975341796875
train per: 0.5707042125993164
train loss: 2.1055309772491455
train per: 0.5675191234758021
train loss: 2.148177146911621
train per: 0.576437518492948
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  17%|█▋        | 470/2703 [00:00<00:00, 4698.81it/s]


word -> phonemes:  35%|███▍      | 940/2703 [00:00<00:00, 4586.67it/s]


word -> phonemes:  54%|█████▍    | 1461/2703 [00:00<00:00, 4864.71it/s]


word -> phonemes:  72%|███████▏  | 1950/2703 [00:00<00:00, 4870.73it/s]


word -> phonemes:  90%|█████████ | 2438/2703 [00:00<00:00, 4795.01it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 4743.66it/s]



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


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dev:   6%|▌         | 160/2703 [00:10<02:15, 18.72it/s]


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train:  99%|█████████▉| 3495/3515 [18:20<00:04,  4.55it/s]
overall:  87%|████████▋ | 3496/4000 [18:22<01:49,  4.61it/s]

train:  99%|█████████▉| 3496/3515 [18:20<00:04,  4.61it/s]
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train: 100%|██████████| 3515/3515 [18:24<00:00,  5.02it/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 [18:24<00:00,  3.18it/s]
dev loss: 2.4222402572631836
dev per: 0.6164568158168574
train loss: 2.0649681091308594
train per: 0.5603454750281637
train loss: 2.0984606742858887
train per: 0.5653621527209214
train loss: 2.070356845855713
train per: 0.5586302570093458
train loss: 2.0900869369506836
train per: 0.5610665860174404
train loss: 2.108877420425415
train per: 0.5637086657040736
train loss: 2.0993435382843018
train per: 0.567736366406012
train loss: 2.0670299530029297
train per: 0.5576990882989976
train loss: 2.1239867210388184
train per: 0.5634350760068202
train loss: 2.140221357345581
train per: 0.5706247043298558
train loss: 2.089401960372925
train per: 0.561456896961628
train loss: 2.122101068496704
train per: 0.5684334899568598
train loss: 2.1509528160095215
train per: 0.5715059715907752
train loss: 2.065715789794922
train per: 0.5612529877972072
train loss: 2.0746445655822754
train per: 0.5596469516893549
train loss: 2.0981032848358154
train per: 0.5649838092434502
train loss: 2.1199707984924316
train per: 0.5641312028447037
train loss: 2.1201319694519043
train per: 0.5618021233754348
train loss: 2.101195812225342
train per: 0.5680961357210179
train loss: 2.1255552768707275
train per: 0.5734131168283425
train loss: 2.1150288581848145
train per: 0.5690919958702385
train loss: 2.1227927207946777
train per: 0.570819347383481
train loss: 2.1556875705718994
train per: 0.5727067610674551
train loss: 2.166138172149658
train per: 0.5696139060671904
train loss: 2.1194355487823486
train per: 0.5727682106096595
train loss: 2.1372711658477783
train per: 0.5643024162120032
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.


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

word -> phonemes:  10%|▉         | 350/3515 [00:00<00:00, 3493.48it/s]

word -> phonemes:  22%|██▏       | 773/3515 [00:00<00:00, 3923.79it/s]

word -> phonemes:  33%|███▎      | 1166/3515 [00:00<00:00, 3786.07it/s]

word -> phonemes:  46%|████▌     | 1604/3515 [00:00<00:00, 4014.01it/s]

word -> phonemes:  58%|█████▊    | 2054/3515 [00:00<00:00, 4185.34it/s]

word -> phonemes:  71%|███████▏  | 2506/3515 [00:00<00:00, 4297.23it/s]

word -> phonemes:  84%|████████▎ | 2937/3515 [00:00<00:00, 4218.95it/s]

word -> phonemes:  96%|█████████▌| 3360/3515 [00:00<00:00, 4064.65it/s]
word -> phonemes: 100%|██████████| 3515/3515 [00:00<00:00, 4016.68it/s]


train:   0%|          | 0/3515 [00:00<?, ?it/s]
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overall:  88%|████████▊ | 3529/4000 [18:32<01:44,  4.49it/s]

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overall:  88%|████████▊ | 3530/4000 [18:32<01:38,  4.77it/s]

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overall:  88%|████████▊ | 3531/4000 [18:33<01:45,  4.45it/s]

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overall:  88%|████████▊ | 3532/4000 [18:33<01:43,  4.51it/s]

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overall:  88%|████████▊ | 3533/4000 [18:33<01:37,  4.79it/s]

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overall:  88%|████████▊ | 3534/4000 [18:33<01:37,  4.78it/s]

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overall:  88%|████████▊ | 3535/4000 [18:34<01:40,  4.63it/s]

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overall:  88%|████████▊ | 3536/4000 [18:34<01:38,  4.69it/s]

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overall:  88%|████████▊ | 3538/4000 [18:34<01:25,  5.38it/s]

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overall:  88%|████████▊ | 3540/4000 [18:35<01:44,  4.40it/s]

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overall:  89%|████████▊ | 3541/4000 [18:35<01:42,  4.48it/s]

train:   1%|          | 26/3515 [00:06<12:59,  4.48it/s]
overall:  89%|████████▊ | 3542/4000 [18:35<01:39,  4.59it/s]

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overall:  89%|████████▊ | 3544/4000 [18:35<01:31,  5.00it/s]

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overall:  89%|████████▊ | 3546/4000 [18:36<01:20,  5.62it/s]

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overall:  89%|████████▊ | 3547/4000 [18:36<01:31,  4.93it/s]

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overall:  89%|████████▊ | 3548/4000 [18:36<01:33,  4.83it/s]

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overall:  89%|████████▉ | 3550/4000 [18:37<01:30,  4.98it/s]

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overall:  89%|████████▉ | 3551/4000 [18:37<01:32,  4.87it/s]

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overall:  89%|████████▉ | 3552/4000 [18:37<01:45,  4.25it/s]

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overall:  89%|████████▉ | 3553/4000 [18:37<01:44,  4.28it/s]

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overall:  89%|████████▉ | 3554/4000 [18:37<01:41,  4.39it/s]

train:   1%|          | 39/3515 [00:09<13:12,  4.39it/s]
overall:  89%|████████▉ | 3555/4000 [18:38<01:28,  5.05it/s]

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overall:  89%|████████▉ | 3556/4000 [18:38<01:33,  4.73it/s]

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overall:  89%|████████▉ | 3557/4000 [18:38<01:35,  4.64it/s]

train:   1%|          | 42/3515 [00:10<12:28,  4.64it/s]
overall:  89%|████████▉ | 3558/4000 [18:38<01:34,  4.68it/s]

train:   1%|          | 43/3515 [00:10<12:22,  4.68it/s]
overall:  89%|████████▉ | 3559/4000 [18:38<01:26,  5.11it/s]

train:   1%|▏         | 44/3515 [00:10<11:19,  5.11it/s]
overall:  89%|████████▉ | 3560/4000 [18:39<01:28,  4.94it/s]

train:   1%|▏         | 45/3515 [00:10<11:42,  4.94it/s]
overall:  89%|████████▉ | 3561/4000 [18:39<01:29,  4.88it/s]

train:   1%|▏         | 46/3515 [00:10<11:50,  4.89it/s]
overall:  89%|████████▉ | 3562/4000 [18:39<01:30,  4.81it/s]

train:   1%|▏         | 47/3515 [00:11<12:00,  4.81it/s]
overall:  89%|████████▉ | 3563/4000 [18:39<01:21,  5.39it/s]

train:   1%|▏         | 48/3515 [00:11<10:42,  5.39it/s]
overall:  89%|████████▉ | 3564/4000 [18:40<01:39,  4.40it/s]

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overall:  89%|████████▉ | 3565/4000 [18:40<01:24,  5.15it/s]

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overall:  89%|████████▉ | 3566/4000 [18:40<01:26,  5.01it/s]

train:   1%|▏         | 51/3515 [00:11<11:31,  5.01it/s]
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train:   1%|▏         | 52/3515 [00:12<12:15,  4.71it/s]
overall:  89%|████████▉ | 3569/4000 [18:40<01:17,  5.53it/s]

train:   2%|▏         | 54/3515 [00:12<10:25,  5.53it/s]
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overall:  89%|████████▉ | 3571/4000 [18:41<01:28,  4.84it/s]

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overall:  89%|████████▉ | 3572/4000 [18:41<01:30,  4.73it/s]

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overall:  89%|████████▉ | 3573/4000 [18:41<01:33,  4.59it/s]

train:   2%|▏         | 58/3515 [00:13<12:33,  4.59it/s]
overall:  89%|████████▉ | 3574/4000 [18:42<01:34,  4.52it/s]

train:   2%|▏         | 59/3515 [00:13<12:43,  4.52it/s]
overall:  89%|████████▉ | 3575/4000 [18:42<01:31,  4.65it/s]

train:   2%|▏         | 60/3515 [00:13<12:23,  4.65it/s]
overall:  89%|████████▉ | 3576/4000 [18:42<01:44,  4.04it/s]

train:   2%|▏         | 61/3515 [00:14<14:14,  4.04it/s]
overall:  89%|████████▉ | 3577/4000 [18:42<01:38,  4.31it/s]

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overall:  89%|████████▉ | 3578/4000 [18:43<01:35,  4.41it/s]

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overall:  90%|████████▉ | 3581/4000 [18:43<01:34,  4.42it/s]

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overall:  90%|████████▉ | 3583/4000 [18:44<01:34,  4.40it/s]

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overall:  90%|████████▉ | 3584/4000 [18:44<01:19,  5.21it/s]

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overall:  90%|████████▉ | 3586/4000 [18:44<01:08,  6.07it/s]

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overall:  90%|████████▉ | 3589/4000 [18:45<01:30,  4.55it/s]

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overall:  90%|████████▉ | 3590/4000 [18:45<01:28,  4.61it/s]

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overall:  90%|█████████ | 3620/4000 [18:51<01:27,  4.33it/s]

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overall:  91%|█████████ | 3622/4000 [18:52<01:22,  4.60it/s]

train:   3%|▎         | 107/3515 [00:23<12:21,  4.60it/s]
overall:  91%|█████████ | 3623/4000 [18:52<01:20,  4.70it/s]

train:   3%|▎         | 108/3515 [00:24<12:05,  4.70it/s]
overall:  91%|█████████ | 3624/4000 [18:52<01:32,  4.07it/s]

train:   3%|▎         | 109/3515 [00:24<13:57,  4.07it/s]
overall:  91%|█████████ | 3625/4000 [18:53<01:28,  4.25it/s]

train:   3%|▎         | 110/3515 [00:24<13:21,  4.25it/s]
overall:  91%|█████████ | 3626/4000 [18:53<01:22,  4.52it/s]

train:   3%|▎         | 111/3515 [00:24<12:33,  4.52it/s]
overall:  91%|█████████ | 3627/4000 [18:53<01:27,  4.25it/s]

train:   3%|▎         | 112/3515 [00:25<13:20,  4.25it/s]
overall:  91%|█████████ | 3628/4000 [18:53<01:12,  5.10it/s]

train:   3%|▎         | 113/3515 [00:25<11:07,  5.10it/s]
overall:  91%|█████████ | 3629/4000 [18:53<01:13,  5.03it/s]

train:   3%|▎         | 114/3515 [00:25<11:16,  5.03it/s]
overall:  91%|█████████ | 3630/4000 [18:54<01:15,  4.92it/s]

train:   3%|▎         | 115/3515 [00:25<11:31,  4.92it/s]
overall:  91%|█████████ | 3631/4000 [18:54<01:17,  4.79it/s]

train:   3%|▎         | 116/3515 [00:25<11:49,  4.79it/s]
overall:  91%|█████████ | 3632/4000 [18:54<01:16,  4.79it/s]

train:   3%|▎         | 117/3515 [00:26<11:49,  4.79it/s]
overall:  91%|█████████ | 3633/4000 [18:54<01:17,  4.75it/s]

train:   3%|▎         | 118/3515 [00:26<11:54,  4.75it/s]
overall:  91%|█████████ | 3634/4000 [18:54<01:16,  4.76it/s]

train:   3%|▎         | 119/3515 [00:26<11:53,  4.76it/s]
overall:  91%|█████████ | 3635/4000 [18:55<01:16,  4.76it/s]

train:   3%|▎         | 120/3515 [00:26<11:52,  4.76it/s]
overall:  91%|█████████ | 3636/4000 [18:55<01:29,  4.05it/s]

train:   3%|▎         | 121/3515 [00:26<13:57,  4.05it/s]
overall:  91%|█████████ | 3637/4000 [18:55<01:25,  4.22it/s]

train:   3%|▎         | 122/3515 [00:27<13:23,  4.22it/s]
overall:  91%|█████████ | 3638/4000 [18:55<01:21,  4.42it/s]

train:   3%|▎         | 123/3515 [00:27<12:47,  4.42it/s]
overall:  91%|█████████ | 3639/4000 [18:56<01:27,  4.12it/s]

train:   4%|▎         | 124/3515 [00:27<13:42,  4.12it/s]
overall:  91%|█████████ | 3640/4000 [18:56<01:25,  4.22it/s]

train:   4%|▎         | 125/3515 [00:27<13:23,  4.22it/s]
overall:  91%|█████████ | 3641/4000 [18:56<01:24,  4.27it/s]

train:   4%|▎         | 126/3515 [00:28<13:13,  4.27it/s]
overall:  91%|█████████ | 3642/4000 [18:56<01:22,  4.35it/s]

train:   4%|▎         | 127/3515 [00:28<12:58,  4.35it/s]
overall:  91%|█████████ | 3643/4000 [18:57<01:24,  4.22it/s]

train:   4%|▎         | 128/3515 [00:28<13:23,  4.22it/s]
overall:  91%|█████████ | 3644/4000 [18:57<01:20,  4.41it/s]

train:   4%|▎         | 129/3515 [00:28<12:47,  4.41it/s]
overall:  91%|█████████ | 3645/4000 [18:57<01:18,  4.53it/s]

train:   4%|▎         | 130/3515 [00:29<12:26,  4.53it/s]
overall:  91%|█████████ | 3646/4000 [18:57<01:17,  4.56it/s]

train:   4%|▎         | 131/3515 [00:29<12:22,  4.56it/s]
overall:  91%|█████████ | 3647/4000 [18:57<01:09,  5.10it/s]

train:   4%|▍         | 132/3515 [00:29<11:02,  5.10it/s]
overall:  91%|█████████ | 3648/4000 [18:58<01:12,  4.87it/s]

train:   4%|▍         | 133/3515 [00:29<11:34,  4.87it/s]
overall:  91%|█████████ | 3649/4000 [18:58<01:13,  4.80it/s]

train:   4%|▍         | 134/3515 [00:29<11:43,  4.80it/s]
overall:  91%|█████████▏| 3650/4000 [18:58<01:09,  5.04it/s]

train:   4%|▍         | 135/3515 [00:29<11:10,  5.04it/s]
overall:  91%|█████████▏| 3651/4000 [18:58<01:07,  5.18it/s]

train:   4%|▍         | 136/3515 [00:30<10:52,  5.18it/s]
overall:  91%|█████████▏| 3652/4000 [18:58<01:08,  5.11it/s]

train:   4%|▍         | 137/3515 [00:30<11:01,  5.11it/s]
overall:  91%|█████████▏| 3653/4000 [18:59<01:11,  4.85it/s]

train:   4%|▍         | 138/3515 [00:30<11:36,  4.85it/s]
overall:  91%|█████████▏| 3655/4000 [18:59<01:02,  5.48it/s]

train:   4%|▍         | 140/3515 [00:30<10:16,  5.48it/s]
overall:  91%|█████████▏| 3656/4000 [18:59<01:05,  5.22it/s]

train:   4%|▍         | 141/3515 [00:31<10:46,  5.22it/s]
overall:  91%|█████████▏| 3657/4000 [18:59<01:08,  5.04it/s]

train:   4%|▍         | 142/3515 [00:31<11:09,  5.04it/s]
overall:  91%|█████████▏| 3658/4000 [19:00<01:08,  5.02it/s]

train:   4%|▍         | 143/3515 [00:31<11:11,  5.02it/s]
overall:  91%|█████████▏| 3659/4000 [19:00<01:08,  5.01it/s]

train:   4%|▍         | 144/3515 [00:31<11:12,  5.01it/s]
overall:  92%|█████████▏| 3660/4000 [19:00<01:21,  4.15it/s]

train:   4%|▍         | 145/3515 [00:32<13:31,  4.15it/s]
overall:  92%|█████████▏| 3661/4000 [19:00<01:17,  4.35it/s]

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overall:  92%|█████████▏| 3662/4000 [19:00<01:15,  4.48it/s]

train:   4%|▍         | 147/3515 [00:32<12:32,  4.48it/s]
overall:  92%|█████████▏| 3663/4000 [19:01<01:05,  5.16it/s]

train:   4%|▍         | 148/3515 [00:32<10:52,  5.16it/s]
overall:  92%|█████████▏| 3664/4000 [19:01<01:06,  5.02it/s]

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overall:  92%|█████████▏| 3665/4000 [19:01<01:07,  4.93it/s]

train:   4%|▍         | 150/3515 [00:33<11:23,  4.93it/s]
overall:  92%|█████████▏| 3666/4000 [19:01<01:08,  4.87it/s]

train:   4%|▍         | 151/3515 [00:33<11:30,  4.87it/s]
overall:  92%|█████████▏| 3667/4000 [19:01<00:58,  5.68it/s]

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overall:  92%|█████████▏| 3669/4000 [19:02<00:51,  6.39it/s]

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overall:  92%|█████████▏| 3670/4000 [19:02<00:56,  5.82it/s]

train:   4%|▍         | 155/3515 [00:33<09:37,  5.82it/s]
overall:  92%|█████████▏| 3671/4000 [19:02<01:00,  5.45it/s]

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overall:  92%|█████████▏| 3672/4000 [19:02<01:12,  4.54it/s]

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overall:  92%|█████████▏| 3674/4000 [19:03<01:02,  5.21it/s]

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overall:  92%|█████████▏| 3675/4000 [19:03<01:08,  4.76it/s]

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overall:  92%|█████████▏| 3680/4000 [19:04<01:09,  4.61it/s]

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overall:  92%|█████████▏| 3682/4000 [19:04<00:59,  5.38it/s]

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overall:  92%|█████████▏| 3683/4000 [19:05<01:00,  5.22it/s]

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overall:  92%|█████████▏| 3684/4000 [19:05<01:13,  4.32it/s]

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overall:  92%|█████████▏| 3695/4000 [19:07<00:59,  5.13it/s]

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overall:  93%|█████████▎| 3703/4000 [19:09<01:02,  4.73it/s]

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train:  14%|█▍        | 484/3515 [01:44<10:51,  4.65it/s]train loss: 2.114514112472534
train per: 0.5620569171561677
train loss: 2.0886282920837402
train per: 0.5686205992836552
train loss: 2.106877088546753
train per: 0.5706030598477713
train loss: 2.1479640007019043
train per: 0.5702364066193853
train loss: 2.136517286300659
train per: 0.5735223267489921
train loss: 2.111274480819702
train per: 0.5651483576461248
train loss: 2.1122641563415527
train per: 0.5618818129661504
train loss: 2.09981632232666
train per: 0.5585532696921742
train loss: 2.118091344833374
train per: 0.5734664764621968
train loss: 2.1009581089019775
train per: 0.5666787134080231
train loss: 2.1212055683135986
train per: 0.569428177298873
train loss: 2.158571720123291
train per: 0.5717759928603302
train loss: 2.0864148139953613
train per: 0.5651921865154379
train loss: 2.1235480308532715
train per: 0.5675428750424182
train loss: 2.1434528827667236
train per: 0.5753991720875222
train loss: 2.1029350757598877
train per: 0.563460024881306
train loss: 2.085479259490967
train per: 0.565169203487513
train loss: 2.1061418056488037
train per: 0.566145362931977
train loss: 2.1150288581848145
train per: 0.5667587704149603
train loss: 2.084979295730591
train per: 0.5589905362776025
train loss: 2.0885519981384277
train per: 0.5605667480667481
train loss: 2.100238800048828
train per: 0.5595190822854622
train loss: 2.1101555824279785
train per: 0.5636662615285623
train loss: 2.104912042617798
train per: 0.564457304026454
train loss: 2.100039005279541
train per: 0.5635805221181949
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  18%|█▊        | 474/2703 [00:00<00:00, 4733.15it/s]


word -> phonemes:  37%|███▋      | 1011/2703 [00:00<00:00, 5106.87it/s]


word -> phonemes:  56%|█████▋    | 1522/2703 [00:00<00:00, 4436.38it/s]


word -> phonemes:  73%|███████▎  | 1975/2703 [00:00<00:00, 4320.82it/s]


word -> phonemes:  92%|█████████▏| 2483/2703 [00:00<00:00, 4572.29it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 4610.97it/s]



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overall: 100%|█████████▉| 3999/4000 [22:18<00:00,  4.65it/s]

train:  14%|█▍        | 484/3515 [03:49<10:51,  4.65it/s]
                                                            

                                                         

overall: 100%|█████████▉| 3999/4000 [22:18<00:00,  4.65it/s]

train:  14%|█▍        | 484/3515 [03:49<10:51,  4.65it/s]
overall: 100%|██████████| 4000/4000 [22:18<00:00, 34.14s/it]

train:  14%|█▍        | 485/3515 [03:49<28:44:07, 34.14s/it]403-128339-0009 Failed!!!

train:  14%|█▍        | 485/3515 [03:50<23:57,  2.11it/s]   

overall: 100%|██████████| 4000/4000 [22:18<00:00,  2.99it/s]
dev loss: 2.436171293258667
dev per: 0.6164047866805411
[Runner] - Save the checkpoint to:
1. result/downstream/grid/states-4000.ckpt