/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')
2023-10-14 22:17:49 | INFO | s3prl.upstream.hubert.hubconf | Converting a fairseq checkpoint: /home/tony/Data/MERT/hubert_d2v2_200k.pt
2023-10-14 22:17:49 | INFO | s3prl.upstream.hubert.hubconf | To: /home/tony/Data/MERT/hubert_d2v2_200k.converted.pt
2023-10-14 22:17:56 | INFO | fairseq.models.hubert.hubert | HubertModel Config: HubertConfig(_name='hubert', label_rate=50.0, extractor_mode='default', encoder_layers=12, encoder_embed_dim=768, encoder_ffn_embed_dim=3072, encoder_attention_heads=12, activation_fn='gelu', layer_type='transformer', dropout=0.1, attention_dropout=0.1, activation_dropout=0.0, encoder_layerdrop=0.05, dropout_input=0.1, dropout_features=0.1, final_dim=256, untie_final_proj=True, layer_norm_first=False, conv_feature_layers='[(512,10,5)] + [(512,3,2)] * 4 + [(512,2,2)] * 3', conv_bias=False, logit_temp=0.1, target_glu=False, feature_grad_mult=0.1, mask_length=10, mask_prob=0.8, mask_selection='static', mask_other=0.0, no_mask_overlap=False, mask_min_space=1, mask_channel_length=10, mask_channel_prob=0.0, mask_channel_selection='static', mask_channel_other=0.0, no_mask_channel_overlap=False, mask_channel_min_space=1, conv_pos=128, conv_pos_groups=16, conv_pos_batch_norm=False, latent_temp=[2.0, 0.5, 0.999995], skip_masked=False, skip_nomask=False, checkpoint_activations=False, required_seq_len_multiple=2, depthwise_conv_kernel_size=31, attn_type='', pos_enc_type='abs', fp16=False)
/home/tony/anaconda3/envs/suno_env/lib/python3.10/site-packages/torch/nn/utils/weight_norm.py:30: UserWarning: torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.
  warnings.warn("torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.")
2023-10-14 22:17:58 | INFO | fairseq.models.hubert.hubert | cannot find dictionary. assume will be used for fine-tuning
[Featurizer] - Take a list of 13 features and weighted sum them.
[Featurizer] - The selected feature hidden_states's downsample rate is 640
[Runner] - Start a new experiment
[(512, 10, 5), (512, 3, 2), (512, 3, 2), (512, 3, 2), (512, 3, 2), (512, 2, 2), (512, 2, 2), (512, 2, 2)] 640

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:  53%|█████▎    | 1848/3515 [00:00<00:00, 4662.94it/s]

word -> phonemes:  66%|██████▌   | 2327/3515 [00:00<00:00, 4708.44it/s]

word -> phonemes:  80%|███████▉  | 2799/3515 [00:00<00:00, 4658.51it/s]

word -> phonemes:  93%|█████████▎| 3266/3515 [00:00<00:00, 4495.93it/s]
word -> phonemes: 100%|██████████| 3515/3515 [00:00<00:00, 4526.60it/s]


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overall:  14%|█▍        | 555/4000 [02:17<12:05,  4.75it/s]

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overall:  16%|█▋        | 651/4000 [02:39<13:06,  4.26it/s]

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overall:  16%|█▋        | 654/4000 [02:40<13:22,  4.17it/s]

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overall:  16%|█▋        | 659/4000 [02:41<13:37,  4.09it/s]

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overall:  17%|█▋        | 661/4000 [02:42<13:54,  4.00it/s]

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overall:  17%|█▋        | 662/4000 [02:42<14:03,  3.96it/s]

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overall:  17%|█▋        | 663/4000 [02:42<13:57,  3.99it/s]

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overall:  17%|█▋        | 665/4000 [02:43<13:03,  4.26it/s]

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overall:  17%|█▋        | 668/4000 [02:43<11:21,  4.89it/s]

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overall:  17%|█▋        | 669/4000 [02:43<11:55,  4.66it/s]

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overall:  17%|█▋        | 671/4000 [02:44<13:00,  4.27it/s]

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overall:  17%|█▋        | 681/4000 [02:46<13:51,  3.99it/s]

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overall:  17%|█▋        | 682/4000 [02:47<13:24,  4.13it/s]

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overall:  17%|█▋        | 683/4000 [02:47<13:36,  4.06it/s]

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overall:  17%|█▋        | 684/4000 [02:47<13:44,  4.02it/s]

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overall:  17%|█▋        | 685/4000 [02:47<13:15,  4.17it/s]

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overall:  17%|█▋        | 686/4000 [02:48<13:40,  4.04it/s]

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overall:  17%|█▋        | 687/4000 [02:48<12:41,  4.35it/s]

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overall:  17%|█▋        | 688/4000 [02:48<13:12,  4.18it/s]

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overall:  17%|█▋        | 689/4000 [02:48<13:34,  4.07it/s]

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overall:  17%|█▋        | 690/4000 [02:49<13:40,  4.04it/s]

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overall:  17%|█▋        | 691/4000 [02:49<13:54,  3.97it/s]

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overall:  17%|█▋        | 692/4000 [02:49<14:11,  3.89it/s]

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overall:  17%|█▋        | 693/4000 [02:49<14:18,  3.85it/s]

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overall:  17%|█▋        | 695/4000 [02:50<13:24,  4.11it/s]

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overall:  17%|█▋        | 696/4000 [02:50<13:28,  4.09it/s]

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overall:  17%|█▋        | 698/4000 [02:50<10:46,  5.11it/s]

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overall:  17%|█▋        | 699/4000 [02:51<14:22,  3.83it/s]

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overall:  18%|█▊        | 705/4000 [02:53<15:09,  3.62it/s]

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overall:  18%|█▊        | 707/4000 [02:53<14:24,  3.81it/s]

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overall:  18%|█▊        | 708/4000 [02:53<14:13,  3.86it/s]

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overall:  18%|█▊        | 711/4000 [02:54<12:58,  4.22it/s]

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overall:  18%|█▊        | 712/4000 [02:54<12:10,  4.50it/s]

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overall:  18%|█▊        | 714/4000 [02:55<11:05,  4.94it/s]

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overall:  18%|█▊        | 715/4000 [02:55<12:03,  4.54it/s]

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overall:  18%|█▊        | 716/4000 [02:55<12:40,  4.32it/s]

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train:  28%|██▊       | 999/3515 [04:03<10:31,  3.99it/s]train loss: 3.5448737144470215
train per: 0.7919806429312133
train loss: 1.5400373935699463
train per: 0.4115545116069867
train loss: 1.2451138496398926
train per: 0.3499626802783329
train loss: 1.1026710271835327
train per: 0.31575178408277155
train loss: 1.0703821182250977
train per: 0.30814173109370674
train loss: 1.058211088180542
train per: 0.3029741477922672
train loss: 1.0070768594741821
train per: 0.2929483903934594
train loss: 1.011008381843567
train per: 0.28774862805936974
train loss: 1.0294983386993408
train per: 0.29304794436389553
train loss: 1.0061410665512085
train per: 0.28937548587717027
train loss: 0.98304283618927
train per: 0.28056145382345643
train loss: 1.0134226083755493
train per: 0.28990188752018897
train loss: 1.0201047658920288
train per: 0.2905223051277981
train loss: 0.9853445291519165
train per: 0.2830891347486884
train loss: 0.9633904695510864
train per: 0.2753285595145659
train loss: 0.9710370898246765
train per: 0.27973421926910297
train loss: 0.9727193713188171
train per: 0.27873238462070715
train loss: 0.93926602602005
train per: 0.2726719985033441
train loss: 0.9143854975700378
train per: 0.2660220591807978
train loss: 0.91283118724823
train per: 0.2630563232631278
train loss: 0.9599329233169556
train per: 0.27406444906444904
train loss: 0.9771621823310852
train per: 0.2797425327258263
train loss: 0.9612043499946594
train per: 0.28031643330131933
train loss: 0.9441956281661987
train per: 0.26611500305609104
train loss: 0.9102571606636047
train per: 0.2658488192024777
train loss: 0.9223260879516602
train per: 0.26614264479883104
train loss: 0.9304312467575073
train per: 0.2681036447911654
train loss: 0.9102901220321655
train per: 0.2658021914924159
train loss: 0.9483431577682495
train per: 0.2688520688937145
train loss: 0.9358804821968079
train per: 0.27394343378234504
train loss: 0.8931044340133667
train per: 0.2663870102445567
train loss: 0.9145206212997437
train per: 0.26783883150338894
train loss: 0.8981534242630005
train per: 0.2624286441722724
train loss: 0.8730266690254211
train per: 0.262236965384518
train loss: 0.8618391752243042
train per: 0.2580273762312908
train loss: 0.9275531768798828
train per: 0.26922985978104086
train loss: 0.8827446103096008
train per: 0.2605515195696438
train loss: 0.8712614178657532
train per: 0.2617316197204001
train loss: 0.9100020527839661
train per: 0.2665675497818616
train loss: 0.9258159399032593
train per: 0.2687705423171734
train loss: 0.8965616226196289
train per: 0.2632505677903386
train loss: 0.891924262046814
train per: 0.2606361729751323
train loss: 0.8691579699516296
train per: 0.25789070357775756
train loss: 0.9046819806098938
train per: 0.26349657578498514
train loss: 0.9003384709358215
train per: 0.2665990175503333
train loss: 0.8897439241409302
train per: 0.2572610046734689
train loss: 0.8770025372505188
train per: 0.25381438289601554
train loss: 0.8784455060958862
train per: 0.2604480827229642
train loss: 0.8534954190254211
train per: 0.2527046126172427
train loss: 0.8815305829048157
train per: 0.2573722071363918
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  20%|██        | 553/2703 [00:00<00:00, 5527.49it/s]


word -> phonemes:  41%|████      | 1106/2703 [00:00<00:00, 5245.15it/s]


word -> phonemes:  60%|██████    | 1632/2703 [00:00<00:00, 5201.97it/s]


word -> phonemes:  81%|████████  | 2193/2703 [00:00<00:00, 5359.15it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 5308.00it/s]



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overall:  48%|████▊     | 1913/4000 [09:16<06:08,  5.67it/s]

train:  54%|█████▍    | 1913/3515 [09:14<04:42,  5.67it/s]
overall:  48%|████▊     | 1914/4000 [09:16<06:44,  5.16it/s]

train:  54%|█████▍    | 1914/3515 [09:14<05:10,  5.16it/s]
overall:  48%|████▊     | 1915/4000 [09:16<07:21,  4.72it/s]

train:  54%|█████▍    | 1915/3515 [09:14<05:38,  4.72it/s]
overall:  48%|████▊     | 1916/4000 [09:17<07:42,  4.51it/s]

train:  55%|█████▍    | 1916/3515 [09:14<05:54,  4.51it/s]
overall:  48%|████▊     | 1917/4000 [09:17<08:02,  4.31it/s]

train:  55%|█████▍    | 1917/3515 [09:15<06:10,  4.31it/s]
overall:  48%|████▊     | 1918/4000 [09:17<08:06,  4.28it/s]

train:  55%|█████▍    | 1918/3515 [09:15<06:12,  4.28it/s]
overall:  48%|████▊     | 1919/4000 [09:17<08:18,  4.17it/s]

train:  55%|█████▍    | 1919/3515 [09:15<06:22,  4.17it/s]
overall:  48%|████▊     | 1920/4000 [09:18<08:29,  4.09it/s]

train:  55%|█████▍    | 1920/3515 [09:15<06:30,  4.09it/s]
overall:  48%|████▊     | 1921/4000 [09:18<08:25,  4.11it/s]

train:  55%|█████▍    | 1921/3515 [09:16<06:27,  4.11it/s]
overall:  48%|████▊     | 1922/4000 [09:18<06:58,  4.96it/s]

train:  55%|█████▍    | 1922/3515 [09:16<05:21,  4.96it/s]
overall:  48%|████▊     | 1923/4000 [09:18<07:30,  4.61it/s]

train:  55%|█████▍    | 1923/3515 [09:16<05:45,  4.61it/s]
overall:  48%|████▊     | 1924/4000 [09:18<07:49,  4.43it/s]

train:  55%|█████▍    | 1924/3515 [09:16<05:59,  4.43it/s]
overall:  48%|████▊     | 1925/4000 [09:19<08:12,  4.21it/s]

train:  55%|█████▍    | 1925/3515 [09:17<06:17,  4.21it/s]
overall:  48%|████▊     | 1926/4000 [09:19<08:29,  4.07it/s]

train:  55%|█████▍    | 1926/3515 [09:17<06:30,  4.07it/s]
overall:  48%|████▊     | 1927/4000 [09:19<10:35,  3.26it/s]

train:  55%|█████▍    | 1927/3515 [09:17<08:06,  3.26it/s]
overall:  48%|████▊     | 1928/4000 [09:20<08:51,  3.90it/s]

train:  55%|█████▍    | 1928/3515 [09:17<06:47,  3.90it/s]
overall:  48%|████▊     | 1929/4000 [09:20<08:51,  3.90it/s]

train:  55%|█████▍    | 1929/3515 [09:18<06:46,  3.90it/s]
overall:  48%|████▊     | 1930/4000 [09:20<08:46,  3.93it/s]

train:  55%|█████▍    | 1930/3515 [09:18<06:42,  3.93it/s]
overall:  48%|████▊     | 1931/4000 [09:20<08:42,  3.96it/s]

train:  55%|█████▍    | 1931/3515 [09:18<06:40,  3.96it/s]
overall:  48%|████▊     | 1932/4000 [09:21<08:43,  3.95it/s]

train:  55%|█████▍    | 1932/3515 [09:18<06:41,  3.95it/s]
overall:  48%|████▊     | 1933/4000 [09:21<08:40,  3.97it/s]

train:  55%|█████▍    | 1933/3515 [09:19<06:38,  3.97it/s]
overall:  48%|████▊     | 1934/4000 [09:21<08:43,  3.95it/s]

train:  55%|█████▌    | 1934/3515 [09:19<06:40,  3.95it/s]
overall:  48%|████▊     | 1935/4000 [09:21<08:34,  4.01it/s]

train:  55%|█████▌    | 1935/3515 [09:19<06:33,  4.01it/s]
overall:  48%|████▊     | 1936/4000 [09:22<08:42,  3.95it/s]

train:  55%|█████▌    | 1936/3515 [09:19<06:39,  3.95it/s]
overall:  48%|████▊     | 1937/4000 [09:22<08:50,  3.89it/s]

train:  55%|█████▌    | 1937/3515 [09:20<06:45,  3.89it/s]
overall:  48%|████▊     | 1938/4000 [09:22<08:34,  4.01it/s]

train:  55%|█████▌    | 1938/3515 [09:20<06:33,  4.01it/s]
overall:  48%|████▊     | 1939/4000 [09:22<07:31,  4.57it/s]

train:  55%|█████▌    | 1939/3515 [09:20<05:45,  4.57it/s]
overall:  48%|████▊     | 1940/4000 [09:22<07:45,  4.42it/s]

train:  55%|█████▌    | 1940/3515 [09:20<05:56,  4.42it/s]
overall:  49%|████▊     | 1941/4000 [09:23<08:04,  4.25it/s]

train:  55%|█████▌    | 1941/3515 [09:21<06:09,  4.25it/s]
overall:  49%|████▊     | 1942/4000 [09:23<07:04,  4.84it/s]

train:  55%|█████▌    | 1942/3515 [09:21<05:24,  4.84it/s]
overall:  49%|████▊     | 1943/4000 [09:23<07:37,  4.50it/s]

train:  55%|█████▌    | 1943/3515 [09:21<05:49,  4.50it/s]
overall:  49%|████▊     | 1944/4000 [09:23<07:56,  4.32it/s]

train:  55%|█████▌    | 1944/3515 [09:21<06:04,  4.32it/s]
overall:  49%|████▊     | 1945/4000 [09:24<07:50,  4.37it/s]

train:  55%|█████▌    | 1945/3515 [09:21<05:59,  4.37it/s]
overall:  49%|████▊     | 1946/4000 [09:24<07:54,  4.33it/s]

train:  55%|█████▌    | 1946/3515 [09:22<06:02,  4.33it/s]
overall:  49%|████▊     | 1947/4000 [09:24<08:20,  4.10it/s]

train:  55%|█████▌    | 1947/3515 [09:22<06:22,  4.10it/s]
overall:  49%|████▊     | 1948/4000 [09:24<07:56,  4.30it/s]

train:  55%|█████▌    | 1948/3515 [09:22<06:04,  4.30it/s]
overall:  49%|████▊     | 1949/4000 [09:25<08:12,  4.16it/s]

train:  55%|█████▌    | 1949/3515 [09:22<06:16,  4.16it/s]
overall:  49%|████▉     | 1951/4000 [09:25<10:05,  3.39it/s]

train:  56%|█████▌    | 1951/3515 [09:23<07:41,  3.39it/s]
overall:  49%|████▉     | 1952/4000 [09:25<08:39,  3.94it/s]

train:  56%|█████▌    | 1952/3515 [09:23<06:36,  3.94it/s]
overall:  49%|████▉     | 1954/4000 [09:26<07:32,  4.52it/s]

train:  56%|█████▌    | 1954/3515 [09:24<05:45,  4.52it/s]
overall:  49%|████▉     | 1955/4000 [09:26<07:56,  4.29it/s]

train:  56%|█████▌    | 1955/3515 [09:24<06:03,  4.29it/s]
overall:  49%|████▉     | 1956/4000 [09:26<08:06,  4.20it/s]

train:  56%|█████▌    | 1956/3515 [09:24<06:11,  4.20it/s]
overall:  49%|████▉     | 1957/4000 [09:27<08:11,  4.16it/s]

train:  56%|█████▌    | 1957/3515 [09:24<06:14,  4.16it/s]
overall:  49%|████▉     | 1958/4000 [09:27<08:03,  4.22it/s]

train:  56%|█████▌    | 1958/3515 [09:25<06:08,  4.22it/s]
overall:  49%|████▉     | 1959/4000 [09:27<08:16,  4.11it/s]

train:  56%|█████▌    | 1959/3515 [09:25<06:18,  4.11it/s]
overall:  49%|████▉     | 1960/4000 [09:27<08:24,  4.04it/s]

train:  56%|█████▌    | 1960/3515 [09:25<06:24,  4.04it/s]
overall:  49%|████▉     | 1961/4000 [09:28<08:23,  4.05it/s]

train:  56%|█████▌    | 1961/3515 [09:25<06:23,  4.05it/s]
overall:  49%|████▉     | 1962/4000 [09:28<07:11,  4.73it/s]

train:  56%|█████▌    | 1962/3515 [09:26<05:28,  4.73it/s]
overall:  49%|████▉     | 1963/4000 [09:28<07:34,  4.48it/s]

train:  56%|█████▌    | 1963/3515 [09:26<05:46,  4.48it/s]
overall:  49%|████▉     | 1964/4000 [09:28<06:46,  5.00it/s]

train:  56%|█████▌    | 1964/3515 [09:26<05:09,  5.00it/s]
overall:  49%|████▉     | 1965/4000 [09:28<07:23,  4.58it/s]

train:  56%|█████▌    | 1965/3515 [09:26<05:38,  4.58it/s]
overall:  49%|████▉     | 1966/4000 [09:29<07:55,  4.28it/s]

train:  56%|█████▌    | 1966/3515 [09:26<06:01,  4.28it/s]
overall:  49%|████▉     | 1967/4000 [09:29<08:01,  4.22it/s]

train:  56%|█████▌    | 1967/3515 [09:27<06:06,  4.22it/s]
overall:  49%|████▉     | 1968/4000 [09:29<08:14,  4.11it/s]

train:  56%|█████▌    | 1968/3515 [09:27<06:16,  4.11it/s]
overall:  49%|████▉     | 1969/4000 [09:29<08:30,  3.98it/s]

train:  56%|█████▌    | 1969/3515 [09:27<06:28,  3.98it/s]
overall:  49%|████▉     | 1970/4000 [09:30<08:37,  3.93it/s]

train:  56%|█████▌    | 1970/3515 [09:27<06:33,  3.93it/s]
overall:  49%|████▉     | 1971/4000 [09:30<07:08,  4.74it/s]

train:  56%|█████▌    | 1971/3515 [09:28<05:26,  4.74it/s]
overall:  49%|████▉     | 1972/4000 [09:30<07:30,  4.51it/s]

train:  56%|█████▌    | 1972/3515 [09:28<05:42,  4.51it/s]
overall:  49%|████▉     | 1973/4000 [09:30<07:57,  4.24it/s]

train:  56%|█████▌    | 1973/3515 [09:28<06:03,  4.24it/s]
overall:  49%|████▉     | 1974/4000 [09:31<08:12,  4.11it/s]

train:  56%|█████▌    | 1974/3515 [09:28<06:14,  4.11it/s]
overall:  49%|████▉     | 1975/4000 [09:31<12:13,  2.76it/s]

train:  56%|█████▌    | 1975/3515 [09:29<09:17,  2.76it/s]
overall:  49%|████▉     | 1976/4000 [09:31<11:13,  3.01it/s]

train:  56%|█████▌    | 1976/3515 [09:29<08:31,  3.01it/s]
overall:  49%|████▉     | 1977/4000 [09:32<10:29,  3.21it/s]

train:  56%|█████▌    | 1977/3515 [09:30<07:58,  3.21it/s]
overall:  49%|████▉     | 1978/4000 [09:32<10:09,  3.32it/s]

train:  56%|█████▋    | 1978/3515 [09:30<07:43,  3.32it/s]
overall:  49%|████▉     | 1979/4000 [09:32<09:29,  3.55it/s]

train:  56%|█████▋    | 1979/3515 [09:30<07:12,  3.55it/s]
overall:  50%|████▉     | 1980/4000 [09:32<09:23,  3.59it/s]

train:  56%|█████▋    | 1980/3515 [09:30<07:08,  3.59it/s]
overall:  50%|████▉     | 1981/4000 [09:33<09:06,  3.69it/s]

train:  56%|█████▋    | 1981/3515 [09:31<06:55,  3.69it/s]
overall:  50%|████▉     | 1982/4000 [09:33<08:44,  3.84it/s]

train:  56%|█████▋    | 1982/3515 [09:31<06:38,  3.84it/s]
overall:  50%|████▉     | 1983/4000 [09:33<08:43,  3.85it/s]

train:  56%|█████▋    | 1983/3515 [09:31<06:37,  3.85it/s]
overall:  50%|████▉     | 1984/4000 [09:33<08:46,  3.83it/s]

train:  56%|█████▋    | 1984/3515 [09:31<06:39,  3.83it/s]
overall:  50%|████▉     | 1985/4000 [09:34<08:51,  3.79it/s]

train:  56%|█████▋    | 1985/3515 [09:32<06:43,  3.79it/s]
overall:  50%|████▉     | 1986/4000 [09:34<08:45,  3.83it/s]

train:  57%|█████▋    | 1986/3515 [09:32<06:38,  3.83it/s]
overall:  50%|████▉     | 1987/4000 [09:34<08:50,  3.79it/s]

train:  57%|█████▋    | 1987/3515 [09:32<06:42,  3.79it/s]
overall:  50%|████▉     | 1988/4000 [09:35<08:45,  3.83it/s]

train:  57%|█████▋    | 1988/3515 [09:32<06:38,  3.83it/s]
overall:  50%|████▉     | 1989/4000 [09:35<08:33,  3.92it/s]

train:  57%|█████▋    | 1989/3515 [09:33<06:29,  3.92it/s]
overall:  50%|████▉     | 1990/4000 [09:35<08:37,  3.89it/s]

train:  57%|█████▋    | 1990/3515 [09:33<06:32,  3.89it/s]
overall:  50%|████▉     | 1991/4000 [09:35<08:34,  3.90it/s]

train:  57%|█████▋    | 1991/3515 [09:33<06:30,  3.90it/s]
overall:  50%|████▉     | 1992/4000 [09:35<07:42,  4.34it/s]

train:  57%|█████▋    | 1992/3515 [09:33<05:50,  4.34it/s]
overall:  50%|████▉     | 1993/4000 [09:36<07:56,  4.21it/s]

train:  57%|█████▋    | 1993/3515 [09:34<06:01,  4.21it/s]
overall:  50%|████▉     | 1994/4000 [09:36<08:12,  4.07it/s]

train:  57%|█████▋    | 1994/3515 [09:34<06:13,  4.07it/s]
overall:  50%|████▉     | 1995/4000 [09:36<08:17,  4.03it/s]

train:  57%|█████▋    | 1995/3515 [09:34<06:17,  4.03it/s]
overall:  50%|████▉     | 1996/4000 [09:36<08:07,  4.11it/s]

train:  57%|█████▋    | 1996/3515 [09:34<06:09,  4.11it/s]
overall:  50%|████▉     | 1998/4000 [09:37<07:04,  4.71it/s]

train:  57%|█████▋    | 1998/3515 [09:35<05:21,  4.71it/s]
overall:  50%|████▉     | 1999/4000 [09:37<10:28,  3.18it/s]

train:  57%|█████▋    | 1999/3515 [09:35<07:56,  3.18it/s]dev loss: 1.0460702180862427
dev per: 0.28655046826222685
[Runner] - Save the checkpoint to:
1. result/downstream/grid/dev-best.ckpt
train loss: 0.8900290727615356
train per: 0.2610971263365152
train loss: 0.9063049554824829
train per: 0.2671360580933222
train loss: 0.9003211855888367
train per: 0.2664541317254603
train loss: 0.8911951184272766
train per: 0.26723215650313314
train loss: 0.9050987958908081
train per: 0.2632768081038806
train loss: 0.8821932673454285
train per: 0.25686147524509256
train loss: 0.8775244951248169
train per: 0.2601685099811505
train loss: 0.8468084335327148
train per: 0.25003481215361906
train loss: 0.8657500147819519
train per: 0.2558793280767912
train loss: 0.8619853258132935
train per: 0.2556687235149803
train loss: 0.8607937693595886
train per: 0.25655503319924394
train loss: 0.8732742071151733
train per: 0.254645613322502
train loss: 0.8830522298812866
train per: 0.2608328304164152
train loss: 0.8501849174499512
train per: 0.2506202864372221
train loss: 0.8829679489135742
train per: 0.2583118300913061
train loss: 0.8516728281974792
train per: 0.25487816049835105
train loss: 0.8997389078140259
train per: 0.25994505784774685
train loss: 0.8776944875717163
train per: 0.25906250860146984
train loss: 0.8781536221504211
train per: 0.2583554245224587
train loss: 0.9053810238838196
train per: 0.26685730098699384
train loss: 0.870424747467041
train per: 0.2513165206806213
train loss: 0.8760845065116882
train per: 0.25643012085528355
train loss: 0.8641112446784973
train per: 0.2555976331360947
train loss: 0.8736929893493652
train per: 0.25698682942499196
train loss: 0.8751653432846069
train per: 0.2623725375046714
train loss: 0.8678798675537109
train per: 0.25333496812162826
train loss: 0.8767017126083374
train per: 0.25407519555892
train loss: 0.8300369381904602
train per: 0.2497115586322635
train loss: 0.8541816473007202
train per: 0.2542648666514123
train loss: 0.8878049850463867
train per: 0.2578987298401899
train loss: 0.8642560839653015
train per: 0.2555894081276043
train loss: 0.8577030897140503
train per: 0.2543397788149817
train loss: 0.8672100901603699
train per: 0.252950082914754
train loss: 0.8665674328804016
train per: 0.25017346572556526
train loss: 0.8450590372085571
train per: 0.2500170838933054
train loss: 0.8745278120040894
train per: 0.25495437118634917
train loss: 0.8565934896469116
train per: 0.25298144285790686
train loss: 0.875024676322937
train per: 0.2638597778243555
train loss: 0.8246845006942749
train per: 0.24261549468520033
train loss: 0.8589624166488647
train per: 0.2518515068237924
train loss: 0.845667839050293
train per: 0.24777348135212673
train loss: 0.8811696171760559
train per: 0.25849839400428265
train loss: 0.8588875532150269
train per: 0.25484387898800565
train loss: 0.8967459797859192
train per: 0.26629842465074804
train loss: 0.8564632534980774
train per: 0.24950465986644163
train loss: 0.8630447387695312
train per: 0.250731981981982
train loss: 0.8369328379631042
train per: 0.24620708011711473
train loss: 0.8503729104995728
train per: 0.24980330448465776
train loss: 0.8694412112236023
train per: 0.25461884054489103
train loss: 0.8735042810440063
train per: 0.2563850227283378
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  13%|█▎        | 349/2703 [00:00<00:01, 1313.18it/s]


word -> phonemes:  32%|███▏      | 874/2703 [00:00<00:00, 2689.32it/s]


word -> phonemes:  49%|████▉     | 1322/2703 [00:00<00:00, 3284.34it/s]


word -> phonemes:  70%|██████▉   | 1882/2703 [00:00<00:00, 4029.75it/s]


word -> phonemes:  90%|█████████ | 2441/2703 [00:00<00:00, 4520.60it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 3776.49it/s]



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


dev:   0%|          | 1/2703 [00:01<45:46,  1.02s/it]


dev:   0%|          | 3/2703 [00:01<13:56,  3.23it/s]


dev:   0%|          | 5/2703 [00:01<08:13,  5.47it/s]


dev:   0%|          | 7/2703 [00:01<05:51,  7.66it/s]


dev:   0%|          | 9/2703 [00:01<04:37,  9.71it/s]


dev:   0%|          | 11/2703 [00:01<03:48, 11.78it/s]


dev:   0%|          | 13/2703 [00:01<03:27, 12.94it/s]


dev:   1%|          | 15/2703 [00:01<03:08, 14.29it/s]


dev:   1%|          | 17/2703 [00:01<02:57, 15.11it/s]


dev:   1%|          | 19/2703 [00:02<02:44, 16.34it/s]


dev:   1%|          | 21/2703 [00:02<02:41, 16.56it/s]


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overall:  50%|████▉     | 1999/4000 [11:05<10:28,  3.18it/s]

train:  57%|█████▋    | 1999/3515 [11:03<07:56,  3.18it/s]
                                                            

                                                          

overall:  50%|████▉     | 1999/4000 [11:05<10:28,  3.18it/s]

train:  57%|█████▋    | 1999/3515 [11:03<07:56,  3.18it/s]
overall:  50%|█████     | 2000/4000 [11:05<12:51:14, 23.14s/it]

train:  57%|█████▋    | 2000/3515 [11:03<9:44:13, 23.14s/it]
overall:  50%|█████     | 2001/4000 [11:05<9:23:22, 16.91s/it] 

train:  57%|█████▋    | 2001/3515 [11:03<7:06:40, 16.91s/it]
overall:  50%|█████     | 2002/4000 [11:05<6:47:45, 12.24s/it]

train:  57%|█████▋    | 2002/3515 [11:03<5:08:46, 12.24s/it]
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train:  57%|█████▋    | 2003/3515 [11:04<3:42:18,  8.82s/it]
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train:  57%|█████▋    | 2004/3515 [11:04<2:39:34,  6.34s/it]
overall:  50%|█████     | 2005/4000 [11:06<2:30:26,  4.52s/it]

train:  57%|█████▋    | 2005/3515 [11:04<1:53:52,  4.52s/it]
overall:  50%|█████     | 2006/4000 [11:06<1:48:17,  3.26s/it]

train:  57%|█████▋    | 2006/3515 [11:04<1:21:57,  3.26s/it]
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train:  57%|█████▋    | 2007/3515 [11:04<59:34,  2.37s/it]  
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overall:  73%|███████▎  | 2938/4000 [15:00<04:39,  3.79it/s]

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overall:  73%|███████▎  | 2939/4000 [15:01<04:28,  3.96it/s]

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train:  84%|████████▍ | 2945/3515 [15:00<02:08,  4.44it/s]
overall:  74%|███████▎  | 2946/4000 [15:02<04:12,  4.18it/s]

train:  84%|████████▍ | 2946/3515 [15:00<02:16,  4.18it/s]
overall:  74%|███████▎  | 2947/4000 [15:02<04:15,  4.13it/s]

train:  84%|████████▍ | 2947/3515 [15:00<02:17,  4.13it/s]
overall:  74%|███████▎  | 2948/4000 [15:03<04:13,  4.15it/s]

train:  84%|████████▍ | 2948/3515 [15:00<02:16,  4.15it/s]
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overall:  74%|███████▍  | 2951/4000 [15:03<04:23,  3.99it/s]

train:  84%|████████▍ | 2951/3515 [15:01<02:21,  3.99it/s]
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train:  84%|████████▍ | 2952/3515 [15:02<02:21,  3.98it/s]
overall:  74%|███████▍  | 2953/4000 [15:04<04:52,  3.58it/s]

train:  84%|████████▍ | 2953/3515 [15:02<02:37,  3.58it/s]
overall:  74%|███████▍  | 2954/4000 [15:04<04:42,  3.70it/s]

train:  84%|████████▍ | 2954/3515 [15:02<02:31,  3.70it/s]
overall:  74%|███████▍  | 2956/4000 [15:05<03:49,  4.56it/s]

train:  84%|████████▍ | 2956/3515 [15:02<02:02,  4.56it/s]
overall:  74%|███████▍  | 2957/4000 [15:05<03:50,  4.52it/s]

train:  84%|████████▍ | 2957/3515 [15:03<02:03,  4.52it/s]
overall:  74%|███████▍  | 2958/4000 [15:05<04:02,  4.29it/s]

train:  84%|████████▍ | 2958/3515 [15:03<02:09,  4.29it/s]
overall:  74%|███████▍  | 2959/4000 [15:05<04:08,  4.19it/s]

train:  84%|████████▍ | 2959/3515 [15:03<02:12,  4.19it/s]
overall:  74%|███████▍  | 2960/4000 [15:06<04:19,  4.02it/s]

train:  84%|████████▍ | 2960/3515 [15:03<02:18,  4.01it/s]
overall:  74%|███████▍  | 2961/4000 [15:06<04:23,  3.95it/s]

train:  84%|████████▍ | 2961/3515 [15:04<02:20,  3.95it/s]
overall:  74%|███████▍  | 2963/4000 [15:06<03:48,  4.54it/s]

train:  84%|████████▍ | 2963/3515 [15:04<02:01,  4.54it/s]
overall:  74%|███████▍  | 2964/4000 [15:06<03:57,  4.36it/s]

train:  84%|████████▍ | 2964/3515 [15:04<02:06,  4.36it/s]
overall:  74%|███████▍  | 2965/4000 [15:07<04:04,  4.23it/s]

train:  84%|████████▍ | 2965/3515 [15:05<02:09,  4.23it/s]
overall:  74%|███████▍  | 2966/4000 [15:07<04:08,  4.17it/s]

train:  84%|████████▍ | 2966/3515 [15:05<02:11,  4.17it/s]
overall:  74%|███████▍  | 2967/4000 [15:07<04:14,  4.07it/s]

train:  84%|████████▍ | 2967/3515 [15:05<02:14,  4.07it/s]
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train:  84%|████████▍ | 2970/3515 [15:06<02:29,  3.65it/s]
overall:  74%|███████▍  | 2971/4000 [15:08<04:09,  4.12it/s]

train:  85%|████████▍ | 2971/3515 [15:06<02:11,  4.12it/s]
overall:  74%|███████▍  | 2972/4000 [15:09<04:12,  4.08it/s]

train:  85%|████████▍ | 2972/3515 [15:06<02:13,  4.08it/s]
overall:  74%|███████▍  | 2973/4000 [15:09<04:16,  4.00it/s]

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overall:  74%|███████▍  | 2974/4000 [15:09<04:22,  3.91it/s]

train:  85%|████████▍ | 2974/3515 [15:07<02:18,  3.91it/s]
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train:  85%|████████▍ | 2975/3515 [15:07<02:14,  4.01it/s]
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overall:  75%|███████▍  | 2991/4000 [15:13<04:19,  3.88it/s]

train:  85%|████████▌ | 2991/3515 [15:11<02:14,  3.88it/s]
overall:  75%|███████▍  | 2992/4000 [15:14<04:42,  3.56it/s]

train:  85%|████████▌ | 2992/3515 [15:12<02:26,  3.56it/s]
overall:  75%|███████▍  | 2993/4000 [15:14<04:36,  3.64it/s]

train:  85%|████████▌ | 2993/3515 [15:12<02:23,  3.64it/s]
overall:  75%|███████▍  | 2994/4000 [15:14<04:43,  3.55it/s]

train:  85%|████████▌ | 2994/3515 [15:12<02:26,  3.55it/s]
overall:  75%|███████▍  | 2995/4000 [15:15<04:29,  3.73it/s]

train:  85%|████████▌ | 2995/3515 [15:12<02:19,  3.73it/s]
overall:  75%|███████▍  | 2996/4000 [15:15<03:53,  4.30it/s]

train:  85%|████████▌ | 2996/3515 [15:13<02:00,  4.30it/s]
overall:  75%|███████▍  | 2997/4000 [15:15<04:01,  4.15it/s]

train:  85%|████████▌ | 2997/3515 [15:13<02:04,  4.15it/s]
overall:  75%|███████▍  | 2998/4000 [15:15<04:06,  4.07it/s]

train:  85%|████████▌ | 2998/3515 [15:13<02:07,  4.07it/s]
overall:  75%|███████▍  | 2999/4000 [15:16<04:08,  4.03it/s]

train:  85%|████████▌ | 2999/3515 [15:13<02:07,  4.03it/s]dev loss: 1.0216132402420044
dev per: 0.28090010405827265
[Runner] - Save the checkpoint to:
1. result/downstream/grid/dev-best.ckpt
train loss: 0.8235309720039368
train per: 0.2443820224719101
train loss: 0.8429147601127625
train per: 0.24826899249289375
train loss: 0.8851356506347656
train per: 0.258714520290875
train loss: 0.8479436039924622
train per: 0.24941164165054128
train loss: 0.8252846002578735
train per: 0.2486220421975543
train loss: 0.8631057739257812
train per: 0.2529602464764445
train loss: 0.8501699566841125
train per: 0.2508046096345515
train loss: 0.8542024493217468
train per: 0.253979111309884
train loss: 0.8439118266105652
train per: 0.2501849244792288
train loss: 0.8797544240951538
train per: 0.25816398037841626
train loss: 0.8888859748840332
train per: 0.2591074329027767
train loss: 0.8132640719413757
train per: 0.24228395061728394
train loss: 0.8440977334976196
train per: 0.24962887725603564
train loss: 0.8223316073417664
train per: 0.24381485367844236
train loss: 0.8271969556808472
train per: 0.2444675299574797
train loss: 0.8309270739555359
train per: 0.24583415988891094
train loss: 0.8644918203353882
train per: 0.253087852897474
train loss: 0.8517700433731079
train per: 0.2546600608260571
train loss: 0.8294167518615723
train per: 0.24446188511101546
train loss: 0.8360344171524048
train per: 0.24887690925426775
train loss: 0.8543415069580078
train per: 0.24830603425278772
train loss: 0.8804815411567688
train per: 0.2608647028562482
train loss: 0.8284683227539062
train per: 0.24585704816110082
train loss: 0.8898048400878906
train per: 0.25813866333541535
train loss: 0.8354763984680176
train per: 0.24783252273207867
train loss: 0.8370656967163086
train per: 0.24858490566037736
train loss: 0.8464760780334473
train per: 0.2458335346118545
train loss: 0.8667206764221191
train per: 0.25517907526499073
train loss: 0.8618817329406738
train per: 0.2551550633655451
train loss: 0.8431704640388489
train per: 0.24649381566009418
train loss: 0.8387596011161804
train per: 0.2487957908257787
train loss: 0.8614460825920105
train per: 0.2566127549088549
train loss: 0.8686887621879578
train per: 0.2523252536640361
train loss: 0.8509849309921265
train per: 0.25070468092971676
train loss: 0.8551648259162903
train per: 0.25077585343878267
train loss: 0.8633002042770386
train per: 0.2537403696984039
train loss: 0.8618642687797546
train per: 0.2554371103602532
train loss: 0.8572988510131836
train per: 0.2546442807102307
train loss: 0.86158287525177
train per: 0.25586270142800993
train loss: 0.8459924459457397
train per: 0.2506060193381452
train loss: 0.8468343615531921
train per: 0.25357857472679696
train loss: 0.8274510502815247
train per: 0.24665096609182305
train loss: 0.8415024876594543
train per: 0.24790319320937754
train loss: 0.8548046946525574
train per: 0.2509439644189117
train loss: 0.8352664113044739
train per: 0.24871599771732927
train loss: 0.8224264979362488
train per: 0.24436899845448326
train loss: 0.8317379951477051
train per: 0.24594115561857496
train loss: 0.8157154321670532
train per: 0.24768859003992436
train loss: 0.8699988126754761
train per: 0.25386259838694003
train loss: 0.8307652473449707
train per: 0.24564734210038897
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  19%|█▊        | 505/2703 [00:00<00:00, 4915.26it/s]


word -> phonemes:  40%|███▉      | 1075/2703 [00:00<00:00, 5368.75it/s]


word -> phonemes:  60%|█████▉    | 1616/2703 [00:00<00:00, 5383.65it/s]


word -> phonemes:  82%|████████▏ | 2206/2703 [00:00<00:00, 5583.77it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 5469.47it/s]



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


dev:   0%|          | 1/2703 [00:01<49:27,  1.10s/it]


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dev:   0%|          | 13/2703 [00:01<03:45, 11.95it/s]


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dev:   1%|          | 17/2703 [00:02<03:12, 13.97it/s]


dev:   1%|          | 19/2703 [00:02<02:56, 15.20it/s]


dev:   1%|          | 21/2703 [00:02<02:45, 16.16it/s]


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dev:   1%|          | 25/2703 [00:02<02:39, 16.82it/s]


dev:   1%|          | 27/2703 [00:02<02:34, 17.36it/s]


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overall:  75%|███████▍  | 2999/4000 [16:45<04:08,  4.03it/s]

train:  85%|████████▌ | 2999/3515 [16:42<02:07,  4.03it/s]
                                                            

                                                          

overall:  75%|███████▍  | 2999/4000 [16:45<04:08,  4.03it/s]

train:  85%|████████▌ | 2999/3515 [16:42<02:07,  4.03it/s]
overall:  75%|███████▌  | 3000/4000 [16:45<7:28:21, 26.90s/it]

train:  85%|████████▌ | 3000/3515 [16:42<3:50:54, 26.90s/it]
overall:  75%|███████▌  | 3001/4000 [16:45<5:15:13, 18.93s/it]

train:  85%|████████▌ | 3001/3515 [16:43<2:42:11, 18.93s/it]
overall:  75%|███████▌  | 3002/4000 [16:45<3:41:41, 13.33s/it]

train:  85%|████████▌ | 3002/3515 [16:43<1:53:57, 13.33s/it]
overall:  75%|███████▌  | 3003/4000 [16:45<2:36:14,  9.40s/it]

train:  85%|████████▌ | 3003/3515 [16:43<1:20:14,  9.40s/it]
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overall:  88%|████████▊ | 3515/4000 [18:51<01:59,  4.07it/s]

train: 100%|██████████| 3515/3515 [18:48<00:00,  4.07it/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 [18:49<00:00,  3.11it/s]
dev loss: 1.0149264335632324
dev per: 0.27793964620187306
[Runner] - Save the checkpoint to:
1. result/downstream/grid/dev-best.ckpt
train loss: 0.8486075401306152
train per: 0.24740949894781705
train loss: 0.83482825756073
train per: 0.24810692823843272
train loss: 0.8257010579109192
train per: 0.24444444444444444
train loss: 0.8359716534614563
train per: 0.2510144927536232
train loss: 0.837324321269989
train per: 0.2463715964975411
train loss: 0.830721378326416
train per: 0.2462056074766355
train loss: 0.8121089935302734
train per: 0.24254833860349387
train loss: 0.8371685147285461
train per: 0.24737371198793667
train loss: 0.8102909326553345
train per: 0.24199574367462756
train loss: 0.8348379135131836
train per: 0.24557212489744704
train loss: 0.8524516224861145
train per: 0.25013166144200627
train loss: 0.8428910374641418
train per: 0.250164744645799
train loss: 0.8328350782394409
train per: 0.2484375793912911
train loss: 0.8439832925796509
train per: 0.2507937212761706
train loss: 0.8385028839111328
train per: 0.2450970299068307
train loss: 0.861059308052063
train per: 0.2568612629375509
train loss: 0.8404048681259155
train per: 0.24774133493949516
train loss: 0.8231690526008606
train per: 0.2467565942091245
train loss: 0.8426567316055298
train per: 0.24725941016686068
train loss: 0.8442398905754089
train per: 0.24790669122160836
train loss: 0.8565614819526672
train per: 0.25236177595420817
train loss: 0.8152626752853394
train per: 0.2422110552763819
train loss: 0.8331926465034485
train per: 0.24802050553243327
train loss: 0.8357321619987488
train per: 0.24923017239289091
train loss: 0.8437017202377319
train per: 0.25018438520703823
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.


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

word -> phonemes:  11%|█         | 386/3515 [00:00<00:00, 3859.20it/s]

word -> phonemes:  23%|██▎       | 812/3515 [00:00<00:00, 4093.51it/s]

word -> phonemes:  37%|███▋      | 1296/3515 [00:00<00:00, 4433.12it/s]

word -> phonemes:  50%|█████     | 1770/3515 [00:00<00:00, 4553.37it/s]

word -> phonemes:  64%|██████▍   | 2262/3515 [00:00<00:00, 4683.91it/s]

word -> phonemes:  78%|███████▊  | 2731/3515 [00:00<00:00, 4452.46it/s]

word -> phonemes:  90%|█████████ | 3179/3515 [00:00<00:00, 4458.49it/s]
word -> phonemes: 100%|██████████| 3515/3515 [00:00<00:00, 4381.90it/s]


train:   0%|          | 0/3515 [00:00<?, ?it/s]
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overall:  88%|████████▊ | 3526/4000 [18:57<02:14,  3.53it/s]

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overall:  88%|████████▊ | 3527/4000 [18:57<02:10,  3.61it/s]

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overall:  88%|████████▊ | 3528/4000 [18:57<02:09,  3.63it/s]

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overall:  88%|████████▊ | 3529/4000 [18:57<01:59,  3.95it/s]

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overall:  88%|████████▊ | 3530/4000 [18:57<01:43,  4.55it/s]

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overall:  88%|████████▊ | 3531/4000 [18:58<01:44,  4.49it/s]

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overall:  88%|████████▊ | 3532/4000 [18:58<01:49,  4.29it/s]

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overall:  88%|████████▊ | 3533/4000 [18:58<01:51,  4.19it/s]

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overall:  88%|████████▊ | 3534/4000 [18:58<01:52,  4.15it/s]

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overall:  88%|████████▊ | 3535/4000 [18:59<01:52,  4.12it/s]

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overall:  88%|████████▊ | 3536/4000 [18:59<01:56,  3.99it/s]

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overall:  88%|████████▊ | 3537/4000 [18:59<02:02,  3.77it/s]

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overall:  88%|████████▊ | 3538/4000 [18:59<02:00,  3.82it/s]

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overall:  88%|████████▊ | 3539/4000 [19:00<01:59,  3.84it/s]

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overall:  88%|████████▊ | 3540/4000 [19:00<02:04,  3.70it/s]

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overall:  89%|████████▊ | 3544/4000 [19:01<02:00,  3.77it/s]

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overall:  89%|████████▊ | 3545/4000 [19:01<01:58,  3.83it/s]

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overall:  89%|████████▊ | 3546/4000 [19:02<01:59,  3.80it/s]

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train:  14%|█▍        | 484/3515 [02:03<13:40,  3.69it/s]train loss: 0.8321474194526672
train per: 0.2480429736003887
train loss: 0.8556857109069824
train per: 0.25407174137676525
train loss: 0.8191622495651245
train per: 0.24267361025817386
train loss: 0.849446177482605
train per: 0.25045179945267726
train loss: 0.8606926202774048
train per: 0.2524232723690985
train loss: 0.8426772952079773
train per: 0.25070856857810125
train loss: 0.8189352750778198
train per: 0.24410476279243173
train loss: 0.8242263793945312
train per: 0.24664091163107127
train loss: 0.8153969049453735
train per: 0.24690097710368966
train loss: 0.7977187037467957
train per: 0.2421273783107502
train loss: 0.8241093754768372
train per: 0.24558233925654605
train loss: 0.8378252983093262
train per: 0.2491618985204043
train loss: 0.8306447863578796
train per: 0.24431831291386907
train loss: 0.8434308171272278
train per: 0.24912224704755825
train loss: 0.8642501831054688
train per: 0.2583745546812928
train loss: 0.8518298864364624
train per: 0.2530660855463207
train loss: 0.8406542539596558
train per: 0.2533702284660139
train loss: 0.8055108785629272
train per: 0.2393921155582305
train loss: 0.8452467918395996
train per: 0.2516039452264675
train loss: 0.8173409700393677
train per: 0.24418761827520952
train loss: 0.8177928924560547
train per: 0.24108958185336699
train loss: 0.7978615760803223
train per: 0.2353533657881484
train loss: 0.819888710975647
train per: 0.250967996839194
train loss: 0.8526610136032104
train per: 0.2614769969852202
train loss: 0.8484606742858887
train per: 0.251051598429613
[LibriPhone] - Taking the first phoneme sequences for a deterministic behavior.



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


word -> phonemes:  22%|██▏       | 582/2703 [00:00<00:00, 5812.92it/s]


word -> phonemes:  43%|████▎     | 1164/2703 [00:00<00:00, 5625.46it/s]


word -> phonemes:  64%|██████▍   | 1742/2703 [00:00<00:00, 5693.46it/s]


word -> phonemes:  86%|████████▌ | 2312/2703 [00:00<00:00, 5694.50it/s]
word -> phonemes: 100%|██████████| 2703/2703 [00:00<00:00, 5625.61it/s]



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


dev:   0%|          | 1/2703 [00:01<46:38,  1.04s/it]


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overall: 100%|█████████▉| 3999/4000 [22:26<00:00,  3.69it/s]

train:  14%|█▍        | 484/3515 [03:33<13:40,  3.69it/s]
                                                            

                                                         

overall: 100%|█████████▉| 3999/4000 [22:26<00:00,  3.69it/s]

train:  14%|█▍        | 484/3515 [03:33<13:40,  3.69it/s]
overall: 100%|██████████| 4000/4000 [22:26<00:00, 27.27s/it]

train:  14%|█▍        | 485/3515 [03:33<22:57:06, 27.27s/it]403-128339-0009 Failed!!!
403-128339-0009 Failed!!!

train:  14%|█▍        | 485/3515 [03:33<22:15,  2.27it/s]   

overall: 100%|██████████| 4000/4000 [22:27<00:00,  2.97it/s]
dev loss: 1.0317485332489014
dev per: 0.2795525494276795
[Runner] - Save the checkpoint to:
1. result/downstream/grid/states-4000.ckpt