whisper-cv-1
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: 0.3732
- Wer: 0.2347
- Cer: 0.2844
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: 8
- eval_batch_size: 2
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 12
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.2043 | 1.0 | 500 | 0.2237 | 0.2451 | 0.2885 |
| 0.1082 | 2.0 | 1000 | 0.2422 | 0.2451 | 0.2887 |
| 0.0315 | 3.0 | 1500 | 0.2712 | 0.2440 | 0.2838 |
| 0.0188 | 4.0 | 2000 | 0.2902 | 0.2429 | 0.2873 |
| 0.0214 | 5.0 | 2500 | 0.3111 | 0.2429 | 0.2863 |
| 0.0054 | 6.0 | 3000 | 0.3255 | 0.2395 | 0.2818 |
| 0.0004 | 7.0 | 3500 | 0.3459 | 0.2436 | 0.2879 |
| 0.0003 | 8.0 | 4000 | 0.3520 | 0.2365 | 0.2858 |
| 0.0002 | 9.0 | 4500 | 0.3713 | 0.2354 | 0.2830 |
| 0.0002 | 10.0 | 5000 | 0.3752 | 0.2351 | 0.2847 |
| 0.0002 | 11.0 | 5500 | 0.3838 | 0.2343 | 0.2853 |
| 0.0001 | 12.0 | 6000 | 0.3787 | 0.2354 | 0.2829 |
Framework versions
- Transformers 4.55.2
- Pytorch 2.7.0+cu126
- Datasets 2.19.1
- Tokenizers 0.21.4