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

A transformer based approach for fighting COVID-19 fake news