whisper-tiny-finetuning
This model is a fine-tuned version of openai/whisper-tiny on the PolyAI/minds14 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6195
- Wer: 0.3374
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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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: 50
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 12.7444 | 1.0 | 29 | 1.8826 | 0.4948 |
| 4.5635 | 2.0 | 58 | 0.5162 | 0.4090 |
| 1.6167 | 3.0 | 87 | 0.4736 | 0.3640 |
| 1.0818 | 4.0 | 116 | 0.4711 | 0.3738 |
| 0.7325 | 5.0 | 145 | 0.4878 | 0.3387 |
| 0.5243 | 6.0 | 174 | 0.4995 | 0.3337 |
| 0.1949 | 7.0 | 203 | 0.5141 | 0.3362 |
| 0.1124 | 8.0 | 232 | 0.5422 | 0.3337 |
| 0.0617 | 9.0 | 261 | 0.5497 | 0.3350 |
| 0.0507 | 10.0 | 290 | 0.5687 | 0.3374 |
| 0.0314 | 11.0 | 319 | 0.5725 | 0.3313 |
| 0.0136 | 12.0 | 348 | 0.5918 | 0.3399 |
| 0.0085 | 13.0 | 377 | 0.6056 | 0.3418 |
| 0.0062 | 14.0 | 406 | 0.6109 | 0.3381 |
| 0.0049 | 15.0 | 435 | 0.6145 | 0.3387 |
| 0.0053 | 16.0 | 464 | 0.6186 | 0.3393 |
| 0.0042 | 17.0 | 493 | 0.6197 | 0.3350 |
| 0.0041 | 17.2478 | 500 | 0.6195 | 0.3374 |
Framework versions
- Transformers 5.0.1.dev0
- Pytorch 2.9.0+cu126
- Datasets 2.18.0
- Tokenizers 0.22.2