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Whisper small v5-en finetuned

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

  • Loss: 0.1560
  • Wer: 5.6915

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: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 300
  • training_steps: 3000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.1138 5.8309 1000 0.1326 6.3035
0.004 11.6618 2000 0.1507 5.7015
0.0014 17.4927 3000 0.1560 5.6915

Framework versions

  • Transformers 4.40.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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