whisper-small-turkish-1
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: 0.2199
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: 40000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.295 | 0.05 | 2000 | 0.2957 |
| 0.2732 | 0.1 | 4000 | 0.2737 |
| 0.2334 | 0.15 | 6000 | 0.2588 |
| 0.2148 | 0.2 | 8000 | 0.2413 |
| 0.194 | 0.25 | 10000 | 0.2314 |
| 0.1816 | 0.3 | 12000 | 0.2264 |
| 0.1654 | 0.35 | 14000 | 0.2226 |
| 0.1537 | 0.4 | 16000 | 0.2174 |
| 0.1456 | 0.45 | 18000 | 0.2152 |
| 0.1366 | 0.5 | 20000 | 0.2139 |
| 0.1291 | 0.55 | 22000 | 0.2136 |
| 0.1186 | 0.6 | 24000 | 0.2109 |
| 0.1192 | 0.65 | 26000 | 0.2128 |
| 0.1056 | 0.7 | 28000 | 0.2129 |
| 0.0779 | 1.0228 | 30000 | 0.2182 |
| 0.0907 | 1.0728 | 32000 | 0.2144 |
| 0.0748 | 1.1228 | 34000 | 0.2189 |
| 0.0746 | 1.1728 | 36000 | 0.2199 |
| 0.0785 | 1.2228 | 38000 | 0.2206 |
| 0.0739 | 1.2728 | 40000 | 0.2199 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.20.3