whisper-small-turkish-0
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2766
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: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 45000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.3721 | 0.0556 | 2500 | 0.3822 |
| 0.344 | 0.1111 | 5000 | 0.3584 |
| 0.3255 | 0.1667 | 7500 | 0.3362 |
| 0.2995 | 0.2222 | 10000 | 0.3249 |
| 0.2803 | 0.2778 | 12500 | 0.3112 |
| 0.2739 | 0.3333 | 15000 | 0.3050 |
| 0.2543 | 0.3889 | 17500 | 0.2985 |
| 0.2491 | 0.4444 | 20000 | 0.2923 |
| 0.2403 | 0.5 | 22500 | 0.2885 |
| 0.2231 | 0.5556 | 25000 | 0.2837 |
| 0.2131 | 0.6111 | 27500 | 0.2806 |
| 0.199 | 0.6667 | 30000 | 0.2795 |
| 0.1911 | 0.7222 | 32500 | 0.2774 |
| 0.181 | 0.7778 | 35000 | 0.2766 |
| 0.1855 | 0.8333 | 37500 | 0.2761 |
| 0.175 | 0.8889 | 40000 | 0.2766 |
| 0.1664 | 1.0394 | 42500 | 0.2770 |
| 0.1675 | 1.095 | 45000 | 0.2766 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.20.3