newsSweeper at SemEval-2020 Task 11: Context-Aware Rich Feature Representations For Propaganda Classification
Table 2: Task TC Results on development set trained with 90 percent of training data. Baseline refers to model without contextual features. System 1 (Figure 2(b)) - including context by concatenating text. System 2 (Figure 2(c)) - including context by concatenating embeddings, with and without hidden layer above context vector.
['[BOLD] Model BERT Baseline', '[BOLD] F1 0.583', '[BOLD] Model RoBERTa Baseline', '[BOLD] F1 0.602']
In this we experiment with the following, ( (iii) context to include: sentence level or document level (from article headline), and (iv) methods to combine the embeddings in System 2: default method, without hidden layer concatenation, and weighted average. The evaluation metric used to compare is micro-averaged F1 score. The Baseline model is the one not using contextual features.