Whisper Small zh-TW - Fine-tune-16
This model is a fine-tuned version of openai/whisper-small on the Common Voice 16 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2186
- Cer: 9.2827
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use 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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 0.0462 | 2.2523 | 1000 | 0.1969 | 9.6684 |
| 0.0075 | 4.5045 | 2000 | 0.2071 | 9.5586 |
| 0.0015 | 6.7568 | 3000 | 0.2146 | 9.1627 |
| 0.0007 | 9.0090 | 4000 | 0.2186 | 9.2827 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0