Whisper large tr - baki
This model is a fine-tuned version of openai/whisper-large on the custom dataset. It achieves the following results on the evaluation set:
- Loss: 2.0105
- Wer: 90.9349
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 40
- training_steps: 300
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 2.1523 | 0.9615 | 100 | 2.1371 | 117.2773 |
| 1.5102 | 1.9231 | 200 | 1.9995 | 93.6829 |
| 1.1534 | 2.8846 | 300 | 2.0105 | 90.9349 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.1.0+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for notlober/whisper-large-en-tr-multi
Base model
openai/whisper-large