Whisper Medium Basque
This model is a fine-tuned version of openai/whisper-medium on the common_voice_21_0_eu dataset. It achieves the following results on the evaluation set:
- Loss: 0.3958
- Wer: 8.3789
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: 3.75e-05
- train_batch_size: 64
- eval_batch_size: 32
- 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: 100000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0102 | 11.1111 | 5000 | 0.2346 | 10.0851 |
| 0.0045 | 22.2222 | 10000 | 0.2662 | 10.2880 |
| 0.0035 | 33.3333 | 15000 | 0.2865 | 10.0383 |
| 0.0046 | 44.4444 | 20000 | 0.2913 | 9.9889 |
| 0.0018 | 55.5556 | 25000 | 0.3080 | 9.8797 |
| 0.0016 | 66.6667 | 30000 | 0.3096 | 9.8380 |
| 0.0031 | 77.7778 | 35000 | 0.3158 | 9.9612 |
| 0.0018 | 88.8889 | 40000 | 0.3317 | 10.2646 |
| 0.001 | 100.0 | 45000 | 0.3321 | 10.1380 |
| 0.0003 | 111.1111 | 50000 | 0.3275 | 9.7904 |
| 0.0007 | 122.2222 | 55000 | 0.3265 | 10.0401 |
| 0.0 | 133.3333 | 60000 | 0.3307 | 9.5641 |
| 0.0 | 144.4444 | 65000 | 0.3337 | 9.7461 |
| 0.0 | 155.5556 | 70000 | 0.3444 | 9.6820 |
| 0.0002 | 166.6667 | 75000 | 0.3503 | 9.8346 |
| 0.0 | 177.7778 | 80000 | 0.3586 | 9.1531 |
| 0.0 | 188.8889 | 85000 | 0.3744 | 8.7881 |
| 0.0 | 200.0 | 90000 | 0.3871 | 8.5323 |
| 0.0 | 211.1111 | 95000 | 0.3938 | 8.4040 |
| 0.0 | 222.2222 | 100000 | 0.3958 | 8.3789 |
Framework versions
- Transformers 4.52.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1