Whisper large Ps - ZFA
This model is a fine-tuned version of openai/whisper-large on a custom Pashto speech dataset. It achieves the following results on the evaluation set:
- Loss: 0.7591
- Wer: 24.1861
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: SchedulerType.LINEAR
- lr_scheduler_warmup_steps: 500
- training_steps: 3000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 14.2763 | 12.8298 | 500 | 0.639 | 28.7915 |
| 0.574 | 25.6483 | 1000 | 0.6891 | 25.7107 |
| 0.0377 | 38.4668 | 1500 | 0.7166 | 24.8849 |
| 0.0033 | 51.2853 | 2000 | 0.7313 | 24.3132 |
| 0.0023 | 64.1037 | 2500 | 0.7548 | 24.202 |
| 0.0019 | 76.9335 | 3000 | 0.7591 | 24.1861 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cpu
- Datasets 4.0.0
- Tokenizers 0.22.2