Exploring Text-transformers in AAAI 2021 Shared Task: COVID-19 Fake News Detection in English

Abstract

In this paper, we describe our system for the AAAI 2021 shared task of COVID-19 Fake News Detection in English, where we achieved the 3rd position with the weighted F1 score of 0.9859 on the test set. Specifically, we proposed an ensemble method of different pre-trained language models such as BERT, Roberta, Ernie, etc. with various training strategies including warm-up,learning rate schedule and k-fold cross-validation. We also conduct an extensive analysis of the samples that are not correctly classified. The code is available at:https://github.com/archersama/3rd-solution-COVID19-Fake-News-Detection-in-English.

arXiv comment3rd solution of 'Constraint@AAAI2021 - COVID19 Fake News Detection in English'

References in corpus (4)

• SGDR: Stochastic Gradient Descent with Warm Restarts
• ERNIE: Enhanced Representation through Knowledge Integration
• Fake News Detection in Social Media using Graph Neural Networks and NLP Techniques: A COVID-19 Use-case
• Early Detection of Fake News by Utilizing the Credibility of News, Publishers, and Users Based on Weakly Supervised Learning