English Whisper Model
This model is a fine-tuned version of openai/whisper-base.en on the Medical dataset. It achieves the following results on the evaluation set:
- Loss: 0.1241
- Wer: 8.2186
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: 3000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0573 | 3.0030 | 1000 | 0.1333 | 8.6703 |
| 0.0073 | 6.0060 | 2000 | 0.1185 | 8.2914 |
| 0.0009 | 9.0090 | 3000 | 0.1241 | 8.2186 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
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