Whisper

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

  • Loss: 0.3058
  • Wer: 9.3378

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
0.0259 4.55 1000 0.2254 9.5610
0.0135 9.09 2000 0.2853 9.375
0.0022 13.64 3000 0.2989 9.375
0.0004 18.18 4000 0.3058 9.3378

Framework versions

  • Transformers 4.39.0.dev0
  • Pytorch 2.1.0+cu121
  • Datasets 2.17.1
  • Tokenizers 0.15.2
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