Whisper Small am - Bedru Yimam
This model is a fine-tuned version of openai/whisper-small on the wello dataset. It achieves the following results on the evaluation set:
- Loss: 0.2421
- Wer Ortho: 74.3127
- Wer: 72.7915
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: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.3265 | 2.4631 | 500 | 0.4823 | 95.6186 | 94.3463 |
| 0.1231 | 4.9261 | 1000 | 0.2909 | 87.2852 | 86.0424 |
| 0.0340 | 7.3892 | 1500 | 0.2527 | 76.8900 | 76.5018 |
| 0.0274 | 9.8522 | 2000 | 0.2421 | 74.3127 | 72.7915 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2