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Whisper Small Medication Corpus

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

  • Loss: 0.6189
  • Wer: 20.0

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
0.0 500.0 1000 0.5205 18.6047
0.0 1000.0 2000 0.5735 20.9302
0.0 1500.0 3000 0.6033 21.8605
0.0 2000.0 4000 0.6189 20.0

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.0+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1
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Dataset used to train DereAbdulhameed/whisper-small-PharmaSpeak

Evaluation results