vit-base-patch16-224-finetuned-ISIC-dec2024

This model is a fine-tuned version of google/vit-base-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

• Loss: 0.1523
• Accuracy: 0.9380

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: 5e-05
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 128
• 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: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.8152	0.9985	486	0.1791	0.9223
0.6467	1.9985	972	0.1590	0.9361
0.5399	2.9985	1458	0.1523	0.9380

Testing data confusion values: True positive: 1301 False positive: 301 True negative: 14912 False negative: 792

Framework versions

• Transformers 4.47.1
• Pytorch 2.6.0.dev20241225+cu126
• Datasets 3.2.0
• Tokenizers 0.21.0