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This paper presents the CUNLP submission for the NLP4IF 2019 shared-task onFineGrained Propaganda Detection. Our system finished 5th out of 26 teams onthe sentence-level classification task and 5th out of 11 teams on thefragment-level classification task based on our scores on the blind test set.We present our models, a discussion of our ablation studies and experiments,and an analysis of our performance on all eighteen propaganda techniquespresent in the corpus of the shared task.

Fine-Tuned Neural Models for Propaganda Detection at the Sentence and Fragment levels