%0 Conference Proceedings %T Fighting the COVID-19 Infodemic with a Holistic BERT Ensemble %A Tziafas, Georgios %A Kogkalidis, Konstantinos %A Caselli, Tommaso %Y Feldman, Anna %Y Da San Martino, Giovanni %Y Leberknight, Chris %Y Nakov, Preslav %S Proceedings of the Fourth Workshop on NLP for Internet Freedom: Censorship, Disinformation, and Propaganda %D 2021 %8 June %I Association for Computational Linguistics %C Online %F tziafas-etal-2021-fighting %X This paper describes the TOKOFOU system, an ensemble model for misinformation detection tasks based on six different transformer-based pre-trained encoders, implemented in the context of the COVID-19 Infodemic Shared Task for English. We fine tune each model on each of the task’s questions and aggregate their prediction scores using a majority voting approach. TOKOFOU obtains an overall F1 score of 89.7%, ranking first. %R 10.18653/v1/2021.nlp4if-1.18 %U https://aclanthology.org/2021.nlp4if-1.18 %U https://doi.org/10.18653/v1/2021.nlp4if-1.18 %P 119-124