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: 0.2608
- Wer Ortho: 81.4433
- Wer: 80.2120
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: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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: cosine
- lr_scheduler_warmup_steps: 500
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 1.5181 | 2.4642 | 500 | 0.8604 | 117.0962 | 107.6855 |
| 0.3944 | 4.9284 | 1000 | 0.3722 | 94.3299 | 93.2862 |
| 0.1123 | 7.3901 | 1500 | 0.2744 | 82.5601 | 81.6254 |
| 0.0734 | 9.8543 | 2000 | 0.2608 | 81.4433 | 80.2120 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2