vit-base-16-thesis-demo-PH2

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the ahishamm/PH2_db_enhanced_balanced dataset. It achieves the following results on the evaluation set:

• Loss: 0.0761
• Accuracy: 0.9844
• Recall: 0.9844
• F1: 0.9844
• Precision: 0.9844

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: 16
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 4
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Recall	F1	Precision
0.044	2.5	50	0.0761	0.9844	0.9844	0.9844	0.9844

Framework versions

• Transformers 4.35.2
• Pytorch 2.1.0+cu118
• Datasets 2.15.0
• Tokenizers 0.15.0