Doing More with Less: Data Augmentation for Sudanese Dialect
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openai/whisper-large-v2
This model is a fine-tuned version of openai/whisper-large-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9317
- Wer: 41.0267
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: 8
- 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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.5167 | 1.08 | 1000 | 0.7033 | 67.2465 |
| 0.0886 | 3.04 | 2000 | 0.7730 | 51.1880 |
| 0.0808 | 4.12 | 3000 | 0.7812 | 52.5880 |
| 0.0232 | 6.08 | 4000 | 0.8798 | 40.8570 |
| 0.001 | 8.04 | 5000 | 0.9317 | 41.0267 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
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