whisper-tiny-ml-2
This model is a fine-tuned version of openai/whisper-tiny on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2696
- Wer: 63.2536
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: 3.75e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- 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 |
|---|---|---|---|---|
| 1.25 | 1.0316 | 500 | 0.5131 | 99.8569 |
| 0.29 | 2.0632 | 1000 | 0.1842 | 75.1277 |
| 0.1325 | 4.0264 | 1500 | 0.1808 | 73.6562 |
| 0.0741 | 5.058 | 2000 | 0.1953 | 71.7147 |
| 0.0424 | 7.0212 | 2500 | 0.2104 | 66.1353 |
| 0.0241 | 8.0528 | 3000 | 0.2327 | 66.1762 |
| 0.0122 | 10.016 | 3500 | 0.2463 | 66.4623 |
| 0.0054 | 11.0476 | 4000 | 0.2554 | 64.4186 |
| 0.002 | 13.0108 | 4500 | 0.2660 | 64.0507 |
| 0.0007 | 14.0424 | 5000 | 0.2696 | 63.2536 |
Framework versions
- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1