Whisper Base Shona - Uncleaned Data Extended
This model is a fine-tuned version of openai/whisper-base on the Google WAXAL Shona dataset. It achieves the following results on the evaluation set:
- Loss: 0.4706
- Wer: 41.4760
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_fused 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: 200
- training_steps: 4500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.6454 | 0.5269 | 450 | 0.6835 | 54.7544 |
| 0.5069 | 1.0539 | 900 | 0.5653 | 48.1483 |
| 0.4578 | 1.5808 | 1350 | 0.5204 | 45.6777 |
| 0.3822 | 2.1077 | 1800 | 0.4981 | 43.4642 |
| 0.4036 | 2.6347 | 2250 | 0.4861 | 43.4907 |
| 0.3300 | 3.1616 | 2700 | 0.4768 | 41.8365 |
| 0.3245 | 3.6885 | 3150 | 0.4729 | 40.2274 |
| 0.2943 | 4.2155 | 3600 | 0.4721 | 40.2327 |
| 0.2856 | 4.7424 | 4050 | 0.4709 | 40.6569 |
| 0.2750 | 5.2693 | 4500 | 0.4706 | 41.4760 |
Framework versions
- Transformers 5.14.1
- Pytorch 2.13.0+cu130
- Datasets 5.0.1
- Tokenizers 0.22.2