wisper-small-malagasy
This model is a fine-tuned version of openai/whisper-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8951
- Wer: 0.4742
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
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.3904 | 8.1983 | 500 | 0.6457 | 0.4847 |
| 0.0285 | 16.3967 | 1000 | 0.7599 | 0.4859 |
| 0.0038 | 24.5950 | 1500 | 0.7853 | 0.4771 |
| 0.0008 | 32.7934 | 2000 | 0.8225 | 0.4738 |
| 0.0003 | 40.9917 | 2500 | 0.8441 | 0.4738 |
| 0.0002 | 49.1818 | 3000 | 0.8617 | 0.4754 |
| 0.0002 | 57.3802 | 3500 | 0.8751 | 0.4758 |
| 0.0002 | 65.5785 | 4000 | 0.8857 | 0.4746 |
| 0.0001 | 73.7769 | 4500 | 0.8922 | 0.4734 |
| 0.0001 | 81.9752 | 5000 | 0.8951 | 0.4742 |
Framework versions
- Transformers 4.53.2
- Pytorch 2.6.0+cu124
- Datasets 2.18.0
- Tokenizers 0.21.2