Whisper Tiny Basque
This model is a fine-tuned version of openai/whisper-tiny on the mozilla-foundation/common_voice_13_0 eu dataset. It achieves the following results on the evaluation set:
- Loss: 0.6509
- Wer: 34.0869
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: 256
- eval_batch_size: 128
- 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 |
|---|---|---|---|---|
| 0.3011 | 23.26 | 1000 | 0.6017 | 41.4677 |
| 0.0904 | 46.51 | 2000 | 0.5919 | 35.6284 |
| 0.0408 | 69.77 | 3000 | 0.6267 | 34.7095 |
| 0.0265 | 93.02 | 4000 | 0.6420 | 34.3932 |
| 0.0212 | 116.28 | 5000 | 0.6509 | 34.0869 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1