Whisper Base TR
This model is a fine-tuned version of openai/whisper-base on the Common Voice 13 Turkish 30% dataset. It achieves the following results on the evaluation set:
- Loss: 0.4968
- Wer: 41.2122
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
- 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
- num_epochs: 3.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3817 | 0.5 | 33 | 0.5206 | 42.0632 |
| 0.2896 | 1.0 | 66 | 0.5182 | 44.3036 |
| 0.4421 | 1.5 | 99 | 0.5153 | 43.3137 |
| 0.187 | 2.0 | 132 | 0.5079 | 42.1501 |
| 0.2459 | 2.5 | 165 | 0.5001 | 41.7506 |
| 0.2297 | 3.0 | 198 | 0.4968 | 41.2122 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.0.0
- Datasets 2.14.6
- Tokenizers 0.14.1
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