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Whisper Small Ru - v4

This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2167
  • Wer Ortho: 16.3879
  • Wer: 11.9935

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: 32
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 50
  • training_steps: 5000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Ortho Wer
0.1695 0.4921 500 0.2079 17.6749 13.3434
0.1548 0.9843 1000 0.1894 16.4416 12.2240
0.0704 1.4764 1500 0.1878 16.1107 12.0106
0.0722 1.9685 2000 0.1854 15.7395 11.7887
0.0328 2.4606 2500 0.1927 15.7822 11.6404
0.0344 2.9528 3000 0.1929 15.5746 11.6060
0.0147 3.4449 3500 0.2059 15.6992 11.5141
0.0148 3.9370 4000 0.2046 15.7859 11.5962
0.0067 4.4291 4500 0.2169 16.0374 11.6784
0.0078 4.9213 5000 0.2167 16.3879 11.9935

Framework versions

  • Transformers 4.42.3
  • Pytorch 2.3.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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Evaluation results