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

Loss: 0.2989
Accuracy: 0.9574

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: 1e-05
train_batch_size: 256
eval_batch_size: 256
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 100
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5283	3.6765	125	0.2948	0.9606
0.516	7.3529	250	0.2843	0.9601
0.4878	11.0294	375	0.2756	0.9601
0.459	14.7059	500	0.2801	0.9601
0.4462	18.3824	625	0.2761	0.9595

Framework versions

Transformers 4.46.2
Pytorch 2.5.1+cu121
Datasets 3.1.0
Tokenizers 0.20.3

zubairsalman7/xray_vit

vit-xray-tumor

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

zubairsalman7/
xray_vit