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wav2vec2-base-960h-paper

This model is a fine-tuned version of facebook/wav2vec2-base-960h on the HTS98/ORIGINAL_VER1.2 - NA dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8214
  • Wer: 0.9640

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 5e-05
  • train_batch_size: 8
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 420
  • num_epochs: 50.0

Training results

Training Loss Epoch Step Validation Loss Wer
No log 0.99 104 5.6840 1.0
No log 2.0 209 3.9772 1.0
No log 3.0 314 3.4204 1.0
No log 4.0 419 3.3692 1.0
5.5612 4.99 523 3.3945 1.0
5.5612 6.0 628 3.3426 1.0
5.5612 7.0 733 3.3333 1.0
5.5612 8.0 838 3.3296 1.0001
5.5612 8.99 942 3.1853 0.9999
3.2743 10.0 1047 2.1381 1.0245
3.2743 11.0 1152 1.6965 1.0142
3.2743 12.0 1257 1.4230 1.0011
3.2743 12.99 1361 1.2679 0.9873
3.2743 14.0 1466 1.1570 0.9836
1.5432 15.0 1571 1.0858 0.9784
1.5432 16.0 1676 1.0303 0.9769
1.5432 16.99 1780 0.9855 0.9746
1.5432 18.0 1885 0.9559 0.9709
1.5432 19.0 1990 0.9328 0.9728
0.902 20.0 2095 0.9166 0.9738
0.902 20.99 2199 0.8991 0.9698
0.902 22.0 2304 0.8717 0.9681
0.902 23.0 2409 0.8665 0.9669
0.7003 24.0 2514 0.8589 0.9670
0.7003 24.99 2618 0.8420 0.9659
0.7003 26.0 2723 0.8473 0.9661
0.7003 27.0 2828 0.8543 0.9666
0.7003 28.0 2933 0.8315 0.9623
0.5914 28.99 3037 0.8281 0.9626
0.5914 30.0 3142 0.8315 0.9625
0.5914 31.0 3247 0.8261 0.9620
0.5914 32.0 3352 0.8214 0.9640
0.5914 32.99 3456 0.8310 0.9634
0.5157 34.0 3561 0.8252 0.9635
0.5157 35.0 3666 0.8373 0.9638
0.5157 36.0 3771 0.8422 0.9629
0.5157 36.99 3875 0.8294 0.9632
0.5157 38.0 3980 0.8332 0.9576
0.4655 39.0 4085 0.8330 0.9595
0.4655 40.0 4190 0.8297 0.9625
0.4655 40.99 4294 0.8365 0.9621
0.4655 42.0 4399 0.8361 0.9621
0.4266 43.0 4504 0.8416 0.9625
0.4266 44.0 4609 0.8381 0.9634
0.4266 44.99 4713 0.8448 0.9645
0.4266 46.0 4818 0.8447 0.9625
0.4266 47.0 4923 0.8464 0.9641
0.4019 48.0 5028 0.8449 0.9628
0.4019 48.99 5132 0.8487 0.9626
0.4019 49.64 5200 0.8465 0.9629

Framework versions

  • Transformers 4.31.0.dev0
  • Pytorch 2.0.1+cu118
  • Datasets 2.7.0
  • Tokenizers 0.13.3
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