  COVID-19 is a global pandemic, and detecting them is a momentous task for
medical professionals today due to its rapid mutations. Current methods of
examining chest X-rays and CT scan requires profound knowledge and are time
consuming, which suggests that it shrinks the precious time of medical
practitioners when people's lives are at stake. This study tries to assist this
process by achieving state-of-the-art performance in classifying chest X-rays
by fine-tuning Vision Transformer(ViT). The proposed approach uses pretrained
models, fine-tuned for detecting the presence of COVID-19 disease on chest
X-rays. This approach achieves an accuracy score of 97.61%, precision score of
95.34%, recall score of 93.84% and, f1-score of 94.58%. This result signifies
the performance of transformer-based models on chest X-ray.
