WhisperTiny15hCommonVoice5hAugment
This model is a fine-tuned version of OpenAI/whisper-tiny on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: nan
- Wer: 1.0
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 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: 500
- training_steps: 5000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.8389 | 0.6693 | 500 | 1.0265 | 0.4802 |
| 0.6459 | 1.3387 | 1000 | 0.9529 | 0.4519 |
| 0.5606 | 2.0080 | 1500 | 0.9114 | 0.4389 |
| 0.4697 | 2.6774 | 2000 | 0.9071 | 0.4558 |
| 0.3579 | 3.3467 | 2500 | 0.8838 | 0.4251 |
| 0.349 | 4.0161 | 3000 | 0.8878 | 0.4238 |
| 0.2861 | 4.6854 | 3500 | 0.8860 | 0.4266 |
| 0.2444 | 5.3548 | 4000 | 0.8892 | 0.4266 |
| 0.2397 | 6.0241 | 4500 | 0.8875 | 0.4237 |
| 0.0 | 6.6934 | 5000 | nan | 1.0 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.6.0
- Datasets 3.3.0
- Tokenizers 0.21.0