Whisper small medical
This model is a fine-tuned version of openai/whisper-small on the Medical ASR dataset. It achieves the following results on the evaluation set:
- Loss: 0.0847
- Wer: 16.7994
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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3323 | 0.5405 | 100 | 0.2351 | 17.3304 |
| 0.1496 | 1.0811 | 200 | 0.1295 | 12.5996 |
| 0.0838 | 1.6216 | 300 | 0.0972 | 16.8236 |
| 0.0475 | 2.1622 | 400 | 0.0890 | 16.1236 |
| 0.0277 | 2.7027 | 500 | 0.0847 | 16.7994 |
Framework versions
- Transformers 5.10.1
- Pytorch 2.11.0+cu128
- Datasets 4.8.5
- Tokenizers 0.22.2