Whisper Base Turkish
This model is a fine-tuned version of arun100/whisper-base-tr-1 on the google/fleurs tr_tr dataset. It achieves the following results on the evaluation set:
- Loss: 0.5195
- Wer: 28.3845
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-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3503 | 45.0 | 500 | 0.4874 | 29.1817 |
| 0.0695 | 90.0 | 1000 | 0.4960 | 28.4597 |
| 0.0243 | 136.0 | 1500 | 0.5195 | 28.3845 |
| 0.0145 | 181.0 | 2000 | 0.5334 | 28.6477 |
| 0.0101 | 227.0 | 2500 | 0.5454 | 28.6778 |
| 0.0077 | 272.0 | 3000 | 0.5548 | 28.6928 |
| 0.0063 | 318.0 | 3500 | 0.5625 | 28.7079 |
| 0.0054 | 363.0 | 4000 | 0.5684 | 29.0238 |
| 0.0048 | 409.0 | 4500 | 0.5727 | 28.9260 |
| 0.0046 | 454.0 | 5000 | 0.5743 | 28.9260 |
Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0