QURANIC Whisper Large V3 - revised
This model is a fine-tuned version of openai/whisper-large-v3 on the Common_voice_16_1 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2252
- Wer: 163.3859
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 20000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3095 | 0.21 | 2000 | 0.3293 | 155.0801 |
| 0.2412 | 0.41 | 4000 | 0.3059 | 287.9687 |
| 0.1762 | 0.62 | 6000 | 0.2843 | 152.7845 |
| 0.1906 | 0.82 | 8000 | 0.2645 | 124.8897 |
| 0.0952 | 1.03 | 10000 | 0.2535 | 129.0233 |
| 0.0955 | 1.24 | 12000 | 0.2567 | 141.4259 |
| 0.0865 | 1.44 | 14000 | 0.2360 | 205.5690 |
| 0.1363 | 1.65 | 16000 | 0.2288 | 187.0938 |
| 0.1038 | 1.86 | 18000 | 0.2197 | 178.2311 |
| 0.062 | 2.06 | 20000 | 0.2252 | 163.3859 |
Framework versions
- Transformers 4.39.2
- Pytorch 2.2.0
- Datasets 2.18.0
- Tokenizers 0.15.1
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