Inno at SemEval-2020 Task 11: Leveraging Pure Transformer for Multi-Class Propaganda Detection

August 26, 2020 ยท Declared Dead ยท ๐Ÿ› International Workshop on Semantic Evaluation

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Authors Dmitry Grigorev, Vladimir Ivanov arXiv ID 2008.11584 Category cs.CL: Computation & Language Citations 2 Venue International Workshop on Semantic Evaluation Last Checked 5 months ago
Abstract
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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