whisper-small-br
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: 0.5767
- Wer: 39.9748
- Cer: 15.0329
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: 2e-05
- 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: 200
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.782 | 0.58 | 500 | 0.7847 | 61.4497 | 24.5285 |
| 0.3209 | 1.16 | 1000 | 0.6244 | 47.0028 | 17.7797 |
| 0.3041 | 1.74 | 1500 | 0.5578 | 45.1182 | 18.4874 |
| 0.1177 | 2.33 | 2000 | 0.5479 | 42.1620 | 16.4081 |
| 0.1234 | 2.91 | 2500 | 0.5353 | 41.6136 | 15.9008 |
| 0.0371 | 3.49 | 3000 | 0.5593 | 39.1428 | 14.7689 |
| 0.02 | 4.07 | 3500 | 0.5714 | 38.8591 | 14.7176 |
| 0.0115 | 4.65 | 4000 | 0.5767 | 39.9748 | 15.0329 |
Framework versions
- Transformers 4.39.1
- Pytorch 2.0.1+cu117
- Datasets 2.18.0
- Tokenizers 0.15.2