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

Loss: 0.4037
Accuracy: 0.875

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

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.0996	0.3067	100	1.0429	0.5625
0.0481	0.6135	200	0.5665	0.8125
0.0391	0.9202	300	1.0037	0.6875
0.0711	1.2270	400	0.5200	0.875
0.0258	1.5337	500	0.3818	0.9375
0.0547	1.8405	600	0.3415	0.9375
0.0029	2.1472	700	0.0637	0.9375
0.0543	2.4540	800	0.7362	0.8125
0.0265	2.7607	900	1.0917	0.75
0.0017	3.0675	1000	0.0030	1.0
0.0054	3.3742	1100	0.0364	1.0
0.0234	3.6810	1200	0.2310	0.875
0.0076	3.9877	1300	0.4037	0.875

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1

m-faraz-ali/Vit_Classification_Pneumonia

Tb_Dataset

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

m-faraz-ali/
Vit_Classification_Pneumonia