This project uses ViT to perform image classification tasks on DATA set CIFAR10. The implement of Vit and pretrained weight are from https://github.com/asyml/vision-transformer-pytorch.
pytorch 1.7.1 python 3.7.3
Download the CIFAR10 from http://www.cs.toronto.edu/~kriz/cifar.html or you can get it from https://pan.baidu.com/s/1ogAFopdVzswge2Aaru_lvw (code: k5v8), creat data floder and unzip the cifar-10-python.tar.gz under './data'.
You can download the pretrained file from https://pan.baidu.com/s/1CuUj-XIXwecxWMEcLoJzPg (code: ox9n), creat Vit_weights floder and pretrained file under ./Vit_weights
python main.py
Base on the pretrained weight, after one epoch, we get 98.1 Accuracy
| model | dataset | acc |
|---|---|---|
| ViT-B_16 | CIFAR10 | 98.1 |
reference：https://blog.csdn.net/VOR234/article/details/125521250