Inno at SemEval-2020 Task 11: Leveraging Pure Transfomer for Multi-Class Propaganda Detection
The paper presents the solution of team {''}Inno{''} to a SEMEVAL 2020 task 11 {''}Detection of propaganda techniques in news articles{''}. The goal of the second subtask is to classify textual segments that correspond to one of the 18 given propaganda techniques in news articles dataset. We tested a pure Transformer-based model with an optimized learning scheme on the ability to distinguish propaganda techniques between each other. Our model showed 0:6 and 0:58 overall F1 score on validation set and test set accordingly and non-zero F1 score on each class on both sets.
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