  This paper presents the system that we propose for the Reliable Intelligence
Indentification on Vietnamese Social Network Sites (ReINTEL) task of the
Vietnamese Language and Speech Processing 2020 (VLSP 2020) Shared Task. In this
task, the VLSP 2020 provides a dataset with approximately 6,000 trainning
news/posts annotated with reliable or unreliable labels, and a test set
consists of 2,000 examples without labels. In this paper, we conduct
experiments on different transfer learning models, which are bert4news and
PhoBERT fine-tuned to predict whether the news is reliable or not. In our
experiments, we achieve the AUC score of 94.52% on the private test set from
ReINTEL's organizers.
