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.
翻译：COVID-19的迅速爆发使人类陷入了停滞,并带来了大量其他问题。COVID-19是历史上人类技术最先进、严重依赖社交媒体平台连通和其他好处的第一种流行病,不幸的是,人们也可以获得有关这种病毒的假消息和错误消息,并造成一些大规模问题。因此,与这种病毒作斗争已成为一项重大挑战。我们提出我们在此工作中“限制@AAAI2021-COVID19假新闻探测”的挑战的解决方案。在对众多建筑和技术进行广泛实验之后,我们使用八种基于不同变异器的预培训模型,加上额外的层,以建造堆叠的混合分类器,并为我们的目的对其进行微调。我们在竞赛的测试数据集上实现了0.799906542的精确度、0.7999119精确度、0.9799906542的精确度、0.97979906542的回顾和0.79799090901 f1 - TRC。
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