Whisper Small Basque
This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_13_0 eu dataset. It achieves the following results on the evaluation set:
- Loss: 0.3485
- Wer: 19.3516
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: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.337 | 5.85 | 1000 | 0.3838 | 26.8815 |
| 0.1384 | 11.7 | 2000 | 0.3431 | 22.1544 |
| 0.0732 | 17.54 | 3000 | 0.3376 | 20.0447 |
| 0.0432 | 23.39 | 4000 | 0.3458 | 19.5349 |
| 0.0378 | 29.24 | 5000 | 0.3485 | 19.3516 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1