openai/whisper-medium
This model is a fine-tuned version of openai/whisper-medium on the pphuc25/EngMed dataset. It achieves the following results on the evaluation set:
- Loss: 1.3644
- Wer: 27.0471
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: 0.0001
- train_batch_size: 8
- 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: 100
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.9369 | 1.0 | 3491 | 1.0416 | 45.5524 |
| 0.6193 | 2.0 | 6982 | 0.9804 | 37.6418 |
| 0.3774 | 3.0 | 10473 | 0.9933 | 42.7926 |
| 0.268 | 4.0 | 13964 | 1.0419 | 34.9683 |
| 0.2095 | 5.0 | 17455 | 1.1003 | 32.7617 |
| 0.1284 | 6.0 | 20946 | 1.1458 | 31.5065 |
| 0.0925 | 7.0 | 24437 | 1.1670 | 31.7984 |
| 0.0932 | 8.0 | 27928 | 1.2259 | 30.5314 |
| 0.0612 | 9.0 | 31419 | 1.2532 | 32.1152 |
| 0.0489 | 10.0 | 34910 | 1.2556 | 30.6472 |
| 0.0313 | 11.0 | 38401 | 1.3001 | 30.0870 |
| 0.0241 | 12.0 | 41892 | 1.2982 | 30.4427 |
| 0.0237 | 13.0 | 45383 | 1.3242 | 29.9322 |
| 0.0186 | 14.0 | 48874 | 1.3390 | 28.2798 |
| 0.0063 | 15.0 | 52365 | 1.3588 | 29.5764 |
| 0.0041 | 16.0 | 55856 | 1.3580 | 28.5777 |
| 0.0014 | 17.0 | 59347 | 1.3533 | 27.6901 |
| 0.0014 | 18.0 | 62838 | 1.3609 | 28.0742 |
| 0.0001 | 19.0 | 66329 | 1.3597 | 28.3330 |
| 0.0002 | 20.0 | 69820 | 1.3644 | 27.0471 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1