whisper-large-v3-basque · Model Card
whisper-large-v3-basque: Model Card
Written by Andoni Sudupe, published under apache-2.0, revision 51f752b4fc3d, read 2026-09-30. Shown as written; SAVRN's own facts about this model are on its page.
This model is a fine-tuned version of openai/whisper-large-v3 on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.2181 - Wer: 14.7372
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: 256 - eval_batch_size: 32 - seed: 42 - distributed_type: multi-GPU - num_devices: 2 - total_train_batch_size: 512 - total_eval_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: 5000 - mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1741 | 0.42 | 500 | 0.2910 | 23.2171 |
| 0.1388 | 0.84 | 1000 | 0.2418 | 18.3800 |
| 0.1084 | 1.26 | 1500 | 0.2245 | 16.7258 |
| 0.1041 | 1.68 | 2000 | 0.2155 | 15.6607 |
| 0.0793 | 2.1 | 2500 | 0.2108 | 15.0738 |
| 0.0794 | 2.52 | 3000 | 0.2102 | 15.1867 |
| 0.0774 | 2.94 | 3500 | 0.2072 | 14.7105 |
| 0.0607 | 3.36 | 4000 | 0.2142 | 14.7454 |
| 0.0608 | 3.78 | 4500 | 0.2117 | 14.6900 |
| 0.0506 | 4.2 | 5000 | 0.2181 | 14.7372 |
Framework versions
- Transformers 4.38.0
- Pytorch 2.1.1+cu121
- Datasets 2.8.0
- Tokenizers 0.15.2