Whisper Small - Medical
This model is a fine-tuned version of openai/whisper-small on the Voice Medical New dataset. It achieves the following results on the evaluation set:
- Loss: 0.2751
- Cer: 9.3062
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 6000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 0.2248 | 1.5444 | 2000 | 0.2707 | 10.4378 |
| 0.1215 | 3.0888 | 4000 | 0.2678 | 9.3233 |
| 0.075 | 4.6332 | 6000 | 0.2751 | 9.3062 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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