quran-recitation-errors-test
This model is a fine-tuned version of openai/whisper-small on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0732
- Wer: 9.6192
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: 0.001
- 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: 100
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.7162 | 1.6949 | 100 | 0.7662 | 89.5792 |
| 0.5519 | 3.3898 | 200 | 0.5851 | 96.9940 |
| 0.3149 | 5.0847 | 300 | 0.2195 | 59.9198 |
| 0.0931 | 6.7797 | 400 | 0.1326 | 36.6733 |
| 0.0072 | 8.4746 | 500 | 0.0732 | 9.6192 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Base model
openai/whisper-small