Whisper Base Medical
This model is a fine-tuned version of openai/whisper-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2595
- Wer: 24.0503
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3836 | 1.0 | 184 | 0.5763 | 29.2094 |
| 0.2101 | 2.0 | 368 | 0.3948 | 30.2361 |
| 0.1197 | 3.0 | 552 | 0.3029 | 27.1047 |
| 0.0528 | 4.0 | 737 | 0.2583 | 24.1273 |
| 0.0261 | 4.99 | 920 | 0.2595 | 24.0503 |
Framework versions
- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
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openai/whisper-base