melanoma-isic2019-multiclass
This model is a fine-tuned version of google/vit-base-patch16-384 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2977
- Auc Macro: 0.9701
- Accuracy: 0.8883
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Auc Macro | Accuracy |
|---|---|---|---|---|---|
| 2.7555 | 1.0 | 713 | 0.4393 | 0.9382 | 0.8157 |
| 1.7951 | 2.0 | 1426 | 0.3502 | 0.9577 | 0.8406 |
| 1.1444 | 3.0 | 2139 | 0.3266 | 0.9635 | 0.8528 |
| 0.9036 | 4.0 | 2852 | 0.3070 | 0.9685 | 0.8840 |
| 0.647 | 5.0 | 3565 | 0.2977 | 0.9701 | 0.8883 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.6.0+cu124
- Datasets 4.4.2
- Tokenizers 0.22.1