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This paper describes our method for tuning a transformer-based pretrainedmodel, to adaptation with Reliable Intelligence Identification on VietnameseSNSs problem. We also proposed a model that combines bert-base pretrainedmodels with some metadata features, such as the number of comments, number oflikes, images of SNS documents,... to improved results for VLSP shared task:Reliable Intelligence Identification on Vietnamese SNSs. With appropriatetraining techniques, our model is able to achieve 0.9392 ROC-AUC on public testset and the final version settles at top 2 ROC-AUC (0.9513) on private testset.

NLPBK at VLSP-2020 shared task: Compose transformer pretrained models for Reliable Intelligence Identification on Social network