vit-lr-step

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vit-lr-step

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

• Loss: 0.5312
• Accuracy: 0.8245
• Precision: 0.8216
• Recall: 0.8245
• F1: 0.8048

Training procedure

Early stopping is employed with a patience of 10 and validation loss as the stopping criteria.

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.0001
• train_batch_size: 16
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: StepLR(optimizer, step_size = 1600, gamma = 0.5, last_epoch=-1)
• num_epochs: 100
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 4.39.0.dev0
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2