YNUtaoxin at SemEval-2020 Task 11: Identification Fragments of Propaganda Technique by Neural Sequence Labeling Models with Different Tagging Schemes and Pre-trained Language Model

SEMEVAL 2020 · Xin Tao, Xiaobing Zhou ·

We only participated in the first subtask, and a neural sequence model was used to perform the sequence tagging task. We investigated the effects of different markup strategies on model performance. Bert that performed very well in NLP was used as a feature extractor.

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Language Modelling

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Adam • Attention Dropout • BERT • Dense Connections • Dropout • GELU • Layer Normalization • Linear Layer • Linear Warmup With Linear Decay • Multi-Head Attention • Residual Connection • Scaled Dot-Product Attention • Softmax • Weight Decay • WordPiece

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YNUtaoxin at SemEval-2020 Task 11: Identification Fragments of Propaganda Technique by Neural Sequence Labeling Models with Different Tagging Schemes and Pre-trained Language Model

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