whisper-base-turkish-1
This model is a fine-tuned version of openai/whisper-base on the multiple dataset. It achieves the following results on the evaluation set:
- Loss: 0.2586
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 16
- 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: 40000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.3966 | 0.0625 | 2500 | 0.4053 |
| 0.3632 | 0.125 | 5000 | 0.3775 |
| 0.3093 | 0.1875 | 7500 | 0.3485 |
| 0.2731 | 0.25 | 10000 | 0.3204 |
| 0.244 | 0.3125 | 12500 | 0.3061 |
| 0.2226 | 0.375 | 15000 | 0.2942 |
| 0.2025 | 0.4375 | 17500 | 0.2819 |
| 0.1873 | 0.5 | 20000 | 0.2763 |
| 0.1713 | 0.5625 | 22500 | 0.2687 |
| 0.1517 | 0.625 | 25000 | 0.2635 |
| 0.1465 | 0.6875 | 27500 | 0.2588 |
| 0.1016 | 1.0228 | 30000 | 0.2616 |
| 0.1025 | 1.0853 | 32500 | 0.2612 |
| 0.1033 | 1.1478 | 35000 | 0.2576 |
| 0.0804 | 1.2103 | 37500 | 0.2609 |
| 0.0918 | 1.2728 | 40000 | 0.2586 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.20.3