whisper-tiny-ga-IE
This model is a fine-tuned version of openai/whisper-tiny on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4171
- Wer: 41.6175
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 OptimizerNames.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
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.1212 | 1.0 | 1586 | 0.7721 | 59.7573 |
| 0.7512 | 2.0 | 3172 | 0.5721 | 50.4880 |
| 0.5476 | 3.0 | 4758 | 0.4855 | 45.7250 |
| 0.4115 | 4.0 | 6344 | 0.4463 | 44.4064 |
| 0.315 | 5.0 | 7930 | 0.4237 | 43.0046 |
| 0.2525 | 6.0 | 9516 | 0.4170 | 41.9502 |
| 0.1916 | 7.0 | 11102 | 0.4120 | 41.7399 |
| 0.1596 | 8.0 | 12688 | 0.4129 | 41.3484 |
| 0.1322 | 9.0 | 14274 | 0.4158 | 41.1992 |
| 0.1158 | 10.0 | 15860 | 0.4171 | 41.6175 |
Framework versions
- Transformers 4.48.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0