arabic
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: 0.1384
- Wer: 9.3775
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
- optimizer: Use 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_ratio: 0.1
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1656 | 0.4963 | 875 | 0.1865 | 14.2234 |
| 0.1473 | 0.9926 | 1750 | 0.1515 | 14.5240 |
| 0.0949 | 1.4889 | 2625 | 0.1441 | 11.1473 |
| 0.0762 | 1.9853 | 3500 | 0.1347 | 12.8537 |
| 0.0459 | 2.4816 | 4375 | 0.1380 | 11.4366 |
| 0.0433 | 2.9779 | 5250 | 0.1312 | 10.1302 |
| 0.0106 | 3.4742 | 6125 | 0.1406 | 9.6804 |
| 0.0124 | 3.9705 | 7000 | 0.1384 | 9.3775 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.1.0+cu118
- Datasets 3.5.0
- Tokenizers 0.21.1