Whisper Wolof Lengo AI V5
This model is a fine-tuned version of serge-wilson/whisper-small-wolof on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.3569
- Wer: 36.0472
- Cer: 22.5967
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: 0.0005
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-05
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 1990
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 1.2672 | 1.0 | 208 | 1.2009 | 85.3838 | 63.2065 |
| 0.875 | 2.0 | 416 | 0.8801 | 95.6117 | 69.2841 |
| 0.5964 | 3.0 | 624 | 0.6979 | 88.4681 | 63.1476 |
| 0.3953 | 4.0 | 832 | 0.6112 | 69.2255 | 57.6000 |
| 0.2465 | 5.0 | 1040 | 0.5015 | 55.4825 | 44.1314 |
| 0.161 | 6.0 | 1248 | 0.4401 | 53.7476 | 36.3715 |
| 0.0903 | 7.0 | 1456 | 0.4081 | 47.1822 | 31.0320 |
| 0.0553 | 8.0 | 1664 | 0.3751 | 44.7783 | 29.2044 |
| 0.024 | 9.0 | 1872 | 0.3604 | 38.7686 | 25.2606 |
| 0.011 | 9.57 | 1990 | 0.3569 | 36.0472 | 22.5967 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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