beit-base-patch16-224-pt22k-ft22k-finetuned-ISIC-dec2024testepo7

This model is a fine-tuned version of microsoft/beit-base-patch16-224-pt22k-ft22k on the imagefolder dataset. It achieves the following results on the evaluation set:

• Loss: 0.1532
• Accuracy: 0.9442

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: 7

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.7021	0.9985	486	0.1905	0.9214
0.7584	1.9985	972	0.1713	0.9291
0.5877	2.9985	1458	0.1655	0.9333
0.6842	3.9985	1944	0.1591	0.9383
0.5674	4.9985	2430	0.1506	0.9406
0.5275	5.9985	2916	0.1450	0.9439
0.3942	6.9985	3402	0.1532	0.9442

Framework versions

• Transformers 4.47.1
• Pytorch 2.5.1+cpu
• Datasets 3.2.0
• Tokenizers 0.21.0