  This paper describes the BERT-based models proposed for two subtasks in
SemEval-2020 Task 11: Detection of Propaganda Techniques in News Articles. We
first build the model for Span Identification (SI) based on SpanBERT, and
facilitate the detection by a deeper model and a sentence-level representation.
We then develop a hybrid model for the Technique Classification (TC). The
hybrid model is composed of three submodels including two BERT models with
different training methods, and a feature-based Logistic Regression model. We
endeavor to deal with imbalanced dataset by adjusting cost function. We are in
the seventh place in SI subtask (0.4711 of F1-measure), and in the third place
in TC subtask (0.6783 of F1-measure) on the development set.
