vit-finetune-kidney-stone-Jonathan_El-Beze_-w256_1k_v1-_SEC
This model was trained from scratch on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.1649
- Accuracy: 0.9533
- Precision: 0.9601
- Recall: 0.9533
- F1: 0.9534
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 |
---|---|---|---|---|---|---|---|
0.0293 | 0.6667 | 100 | 0.1649 | 0.9533 | 0.9601 | 0.9533 | 0.9534 |
Framework versions
- Transformers 4.48.2
- Pytorch 2.6.0+cu126
- Datasets 3.2.0
- Tokenizers 0.21.0
- Downloads last month
- 10
Inference Providers
NEW
This model is not currently available via any of the supported Inference Providers.
Evaluation results
- Accuracy on imagefoldertest set self-reported0.953
- Precision on imagefoldertest set self-reported0.960
- Recall on imagefoldertest set self-reported0.953
- F1 on imagefoldertest set self-reported0.953