whisper-small-coraa-l.1
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9314
- Wer: 0.3360
- Cer: 0.4440
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 |
|---|---|---|---|---|---|
| 0.9302 | 1.0 | 500 | 0.7463 | 0.3403 | 0.4312 |
| 0.4418 | 2.0 | 1000 | 0.7186 | 0.3548 | 0.4452 |
| 0.2068 | 3.0 | 1500 | 0.7844 | 0.3875 | 0.4514 |
| 0.0737 | 4.0 | 2000 | 0.8452 | 0.3796 | 0.4520 |
| 0.03 | 5.0 | 2500 | 0.8570 | 0.3869 | 0.4585 |
| 0.0118 | 6.0 | 3000 | 0.9240 | 0.3396 | 0.4447 |
| 0.0083 | 7.0 | 3500 | 0.9640 | 0.3495 | 0.4458 |
| 0.0024 | 8.0 | 4000 | 0.9781 | 0.3538 | 0.4473 |
| 0.0027 | 9.0 | 4500 | 1.0058 | 0.3697 | 0.4569 |
| 0.0006 | 10.0 | 5000 | 1.0003 | 0.3849 | 0.4550 |
| 0.0005 | 11.0 | 5500 | 1.0013 | 0.3555 | 0.4461 |
| 0.0004 | 12.0 | 6000 | 0.9906 | 0.3627 | 0.4481 |
Framework versions
- Transformers 4.55.2
- Pytorch 2.7.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4