vit-finetune-kidney-stone-Jonathan_El-Beze_-w256_1k_v1-_MIX
This model was trained from scratch on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4183
- Accuracy: 0.8721
- Precision: 0.8771
- Recall: 0.8721
- F1: 0.8709
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: 0.0002
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- 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
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|
| 0.1141 | 0.3333 | 100 | 0.4384 | 0.8675 | 0.8841 | 0.8675 | 0.8659 |
| 0.0513 | 0.6667 | 200 | 0.4183 | 0.8721 | 0.8771 | 0.8721 | 0.8709 |
| 0.028 | 1.0 | 300 | 0.4418 | 0.8812 | 0.8842 | 0.8812 | 0.8810 |
Framework versions
- Transformers 4.48.2
- Pytorch 2.6.0+cu126
- Datasets 3.2.0
- Tokenizers 0.21.0
