  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.
