Whisper Small WO - Team
This model is a fine-tuned version of openai/whisper-small on the ASR Wolof Dataset dataset. It achieves the following results on the evaluation set:
- Loss: 0.1726
- Wer: 78.4437
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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0965 | 1.5408 | 1000 | 0.1751 | 83.2067 |
| 0.0406 | 3.0817 | 2000 | 0.1761 | 78.6749 |
| 0.0192 | 4.6225 | 3000 | 0.1772 | 78.8612 |
| 0.0037 | 6.1633 | 4000 | 0.1726 | 78.4437 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.0
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Base model
openai/whisper-small