Whisper Large
This model is a fine-tuned version of openai/whisper-large-v3 on the Medical STT Combined dataset. It achieves the following results on the evaluation set:
- Loss: 0.0969
- Wer Ortho: 4.8761
- Wer: 2.7322
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: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.0787 | 1.1364 | 500 | 0.0969 | 4.8761 | 2.7322 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3
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Model tree for bqtsio/whisper-large-rad
Base model
openai/whisper-large-v3Datasets used to train bqtsio/whisper-large-rad
Evaluation results
- Wer on Medical STT Combinedself-reported2.732