  The rapid outbreak of COVID-19 has caused humanity to come to a stand-still
and brought with it a plethora of other problems. COVID-19 is the first
pandemic in history when humanity is the most technologically advanced and
relies heavily on social media platforms for connectivity and other benefits.
Unfortunately, fake news and misinformation regarding this virus is also
available to people and causing some massive problems. So, fighting this
infodemic has become a significant challenge. We present our solution for the
"Constraint@AAAI2021 - COVID19 Fake News Detection in English" challenge in
this work. After extensive experimentation with numerous architectures and
techniques, we use eight different transformer-based pre-trained models with
additional layers to construct a stacking ensemble classifier and fine-tuned
them for our purpose. We achieved 0.979906542 accuracy, 0.979913119 precision,
0.979906542 recall, and 0.979907901 f1-score on the test dataset of the
competition.
