Whisper Small-nan

This model is a fine-tuned version of openai/whisper-small on the Common Voice 15, 16 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7181
  • Cer: 29.5966

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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • 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 Cer
0.2916 1.5552 1000 0.6323 31.6827
0.0274 3.1104 2000 0.6579 29.3462
0.0063 4.6656 3000 0.6931 29.0304
0.0018 6.2208 4000 0.7181 29.5966

Framework versions

  • Transformers 4.48.3
  • Pytorch 2.5.1+cu121
  • Datasets 3.2.0
  • Tokenizers 0.21.0
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