Whisper medium ET medical (test5)
This model is a fine-tuned version of openai/whisper-medium on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0398
- Wer: 5.9880
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: 3
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.4808 | 1.0 | 11 | 0.4336 | 27.5449 |
| 0.7116 | 2.0 | 22 | 0.1104 | 9.5808 |
| 0.1563 | 3.0 | 33 | 0.0670 | 8.3832 |
| 0.0585 | 4.0 | 44 | 0.0487 | 5.3892 |
| 0.0483 | 5.0 | 55 | 0.0552 | 7.7844 |
| 0.0099 | 6.0 | 66 | 0.0433 | 6.5868 |
| 0.0033 | 7.0 | 77 | 0.0415 | 5.3892 |
| 0.0017 | 8.0 | 88 | 0.0413 | 5.9880 |
| 0.001 | 9.0 | 99 | 0.0406 | 5.9880 |
| 0.0009 | 10.0 | 110 | 0.0398 | 5.9880 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1
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Base model
openai/whisper-medium