ViT

an implementation of the paper Vision Transformer for Small-Size Datasets

for running an instance -

1. clone the repository

   git clone https://github.com/KaranjotSV/ViT.git
   cd ViT
   

   change the current working directory to ViT
2. create a virtual environment

   virtualenv env
   

   a virtual environment named 'env' will be created
3. activate the environment

   source env/bin/activate
   

4. install the requirements

   pip install -r requirements.txt
   

5. run

   python3 run.py
   

performance of ViT extended with SPT and LSA on CIFAR-100, trained for 20 epochs

model	top-1 accuracy (%)
ViT	45.05
T-ViT	45.92
M-ViT	44.99
L-ViT	46.01
S-ViT	47.39
SL-ViT	47.98