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Whisper Small Ru ORD 0.7 - Mizoru

This model is a fine-tuned version of openai/whisper-small on the ORD_0.7 dataset. It achieves the following results on the evaluation set:

  • Loss: 1.2786
  • Wer: 69.8870
  • Cer: 37.3459
  • Clean Wer: 59.1663
  • Clean Cer: 29.9311

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: 1e-05
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 4000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer Clean Wer Clean Cer
1.4233 1.0 196 1.3027 78.2041 42.0168 63.1339 35.6190
1.0985 2.0 392 1.1179 73.8741 38.0220 60.4978 30.3044
0.9609 3.0 588 1.0756 70.6593 35.9327 59.5915 29.1679
0.7698 4.0 784 1.0846 71.1564 38.0252 57.5893 29.8950
0.6445 5.0 980 1.1128 68.3353 35.9205 57.1834 28.0442
0.53 6.0 1176 1.1503 66.4836 35.4504 57.6763 28.5774
0.4199 7.0 1372 1.2154 68.9370 37.0868 58.5459 28.9185
0.3219 8.0 1568 1.2786 69.8870 37.3459 59.1663 29.9311

Framework versions

  • Transformers 4.39.3
  • Pytorch 2.1.2
  • Datasets 2.17.0
  • Tokenizers 0.15.2
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