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

Loss: 0.1643
Accuracy: 0.9620

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: 32
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5507	2.5	100	0.3762	0.8861
0.4735	5.0	200	0.3380	0.8987
0.368	7.5	300	0.3424	0.8987
0.3182	10.0	400	0.2979	0.9082
0.2952	12.5	500	0.2110	0.9462
0.2493	15.0	600	0.1675	0.9620
0.2716	17.5	700	0.1705	0.9462
0.2866	20.0	800	0.1643	0.9620

Framework versions

Transformers 4.30.0
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.13.3

amanvvip2/finetuned-breast_cancer_images

finetuned-breast_cancer_images

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

amanvvip2/
finetuned-breast_cancer_images