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Whisper Small UZ - Bahriddin Mo'minov

This model is a fine-tuned version of openai/whisper-small on the Common Voice 16.1 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3379
  • Wer: 28.6925

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
0.5499 0.2641 1000 0.5142 39.8375
0.4419 0.5281 2000 0.4080 33.3644
0.3506 0.7922 3000 0.3544 29.7293
0.242 1.0562 4000 0.3379 28.6925

Framework versions

  • Transformers 4.41.0
  • Pytorch 2.2.2+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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Evaluation results