composite_eu+faktoria+Dialektoak_54377
This model is a fine-tuned version of openai/whisper-large-v3 on the composite_eu, faktoria, Dialektoak dataset. It achieves the following results on the evaluation set:
- Loss: 0.2101
- Wer: 12.0919
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: 2e-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 |
|---|---|---|---|---|
| 0.1589 | 0.42 | 500 | 0.2720 | 18.1932 |
| 0.1276 | 0.84 | 1000 | 0.2271 | 15.1271 |
| 0.0953 | 1.26 | 1500 | 0.2117 | 13.5962 |
| 0.093 | 1.68 | 2000 | 0.2053 | 13.0462 |
| 0.0644 | 2.1 | 2500 | 0.2015 | 12.1739 |
| 0.0654 | 2.52 | 3000 | 0.2008 | 12.3197 |
| 0.0636 | 2.94 | 3500 | 0.1982 | 11.7142 |
| 0.0442 | 3.36 | 4000 | 0.2101 | 12.0919 |
| 0.0439 | 3.78 | 4500 | 0.2072 | 12.1945 |
| 0.0313 | 4.2 | 5000 | 0.2195 | 12.1370 |
Framework versions
- Transformers 4.38.0
- Pytorch 2.1.1+cu121
- Datasets 2.8.0
- Tokenizers 0.15.2