whisper-small-burmese-v2
This model is a fine-tuned version of myatsu/whisper-small-burmese on the Myanmar Speech Dataset (OpenSLR-80) dataset. It achieves the following results on the evaluation set:
- Loss: 0.1623
- Wer: 67.3642
- Cer: 24.9554
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: 5e-06
- 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: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.2344 | 1.4 | 200 | 0.2328 | 81.5227 | 33.3180 |
| 0.1545 | 2.8 | 400 | 0.1866 | 73.7756 | 28.1360 |
| 0.0954 | 4.1965 | 600 | 0.1688 | 70.5699 | 26.8591 |
| 0.0747 | 5.5965 | 800 | 0.1629 | 68.8780 | 25.2430 |
| 0.0654 | 6.9965 | 1000 | 0.1623 | 67.3642 | 24.9554 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.4.2
- Tokenizers 0.22.1