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: 0.1956
  • Wer: 12.6737

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
0.5559 0.2825 100 0.5252 15.9811
0.1575 0.5650 200 0.2096 11.5990
0.1228 0.8475 300 0.2005 11.1729
0.0528 1.1299 400 0.1967 11.6732
0.0402 1.4124 500 0.1960 12.3680
0.0583 1.6949 600 0.1956 12.6737

Framework versions

  • Transformers 4.44.0
  • Pytorch 2.3.1+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1
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Evaluation results

  • Wer on Medical Speech, Transcription, and Intent
    self-reported
    12.674