whisper-large-v3-farsi-cv17
This model is a fine-tuned version of openai/whisper-large-v3 on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3402
- Wer Ortho: 27.5624
- Wer: 23.4723
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: 64
- eval_batch_size: 64
- 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: constant_with_warmup
- lr_scheduler_warmup_steps: 100
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.0288 | 3.2415 | 2000 | 0.2866 | 28.6439 | 24.3097 |
| 0.0107 | 6.4830 | 4000 | 0.3402 | 27.5624 | 23.4723 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1