Whisper Large Basque
This model is a fine-tuned version of openai/whisper-large on the mozilla-foundation/common_voice_13_0 eu dataset. It achieves the following results on the evaluation set:
- Loss: 0.4229
- Wer: 13.1677
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: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 20000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.067 | 5.85 | 1000 | 0.2644 | 15.8677 |
| 0.0123 | 11.7 | 2000 | 0.3077 | 14.6326 |
| 0.0052 | 17.54 | 3000 | 0.3317 | 14.1853 |
| 0.0037 | 23.39 | 4000 | 0.3387 | 14.0885 |
| 0.0026 | 29.24 | 5000 | 0.3559 | 14.2618 |
| 0.0026 | 35.09 | 6000 | 0.3604 | 14.2155 |
| 0.002 | 40.94 | 7000 | 0.3734 | 14.1228 |
| 0.0012 | 46.78 | 8000 | 0.3773 | 14.0301 |
| 0.0012 | 52.63 | 9000 | 0.3802 | 13.9072 |
| 0.0012 | 58.48 | 10000 | 0.3850 | 14.4734 |
| 0.0006 | 64.33 | 11000 | 0.3896 | 13.6513 |
| 0.0011 | 70.18 | 12000 | 0.3981 | 13.6311 |
| 0.001 | 76.02 | 13000 | 0.3947 | 13.5949 |
| 0.0002 | 81.87 | 14000 | 0.4039 | 13.6170 |
| 0.0001 | 87.72 | 15000 | 0.4057 | 13.4579 |
| 0.0008 | 93.57 | 16000 | 0.4119 | 13.2745 |
| 0.0001 | 99.42 | 17000 | 0.4203 | 13.1717 |
| 0.0001 | 105.26 | 18000 | 0.4166 | 13.0972 |
| 0.0001 | 111.11 | 19000 | 0.4243 | 13.0448 |
| 0.0 | 116.96 | 20000 | 0.4229 | 13.1677 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1