Whisper
This model is a fine-tuned version of openai/whisper-small on the immunology dataset dataset. It achieves the following results on the evaluation set:
- Loss: 0.3058
- Wer: 9.3378
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 |
|---|---|---|---|---|
| 0.0259 | 4.55 | 1000 | 0.2254 | 9.5610 |
| 0.0135 | 9.09 | 2000 | 0.2853 | 9.375 |
| 0.0022 | 13.64 | 3000 | 0.2989 | 9.375 |
| 0.0004 | 18.18 | 4000 | 0.3058 | 9.3378 |
Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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Base model
openai/whisper-small