Aschern at SemEval-2020 Task 11: It Takes Three to Tango: RoBERTa, CRF, and Transfer Learning
Anton Chernyavskiy, Dmitry Ilvovsky, Preslav Nakov · 2020
We describe our system for SemEval-2020 Task 11 on Detection of Propaganda Techniques in News Articles.We developed ensemble models using RoBERTa-based neural architectures, additional CRF layers, transfer learning between the two subtasks, and advanced post-processing to handle the multi-label nature of the task, the consistency between nested spans, repetitions, and labels from similar spans in training.We achieved sizable improvements over baseline fine-tuned RoBERTa models, and the official evaluation ranked our system 3 rd (almost tied with the 2nd) out of 36 teams on the span identification subtask with an F1 score of 0.491, and 2 nd (almost tied with the 1st) out of 31 teams on the technique classification subtask with an F1 score of 0.62.