whisper_fine_tune_Nataraj

This model is a fine-tuned version of openai/whisper-small on the Medical Speech, Transcription, and Intent dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1107
  • Wer: 7.1807

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: 100
  • training_steps: 600
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.6938 0.28 100 0.6197 45.9080
0.1912 0.56 200 0.2053 12.1040
0.1152 0.85 300 0.1555 9.5495
0.0519 1.13 400 0.1268 8.3883
0.0557 1.41 500 0.1156 7.6173
0.0536 1.69 600 0.1107 7.1807

Framework versions

  • Transformers 4.28.0
  • Pytorch 2.3.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.13.3
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Evaluation results

  • Wer on Medical Speech, Transcription, and Intent
    self-reported
    7.181