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

ahishamm/vit-base-16-thesis-demo-PH2

vit-base-16-thesis-demo-PH2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

ahishamm/
vit-base-16-thesis-demo-PH2