Sequence to Sequence Multi-Label Text Classification

Student: Yarullin Ramil

Educational Programme: Data Science (Master)

Year of Graduation: 2019

We study the BERT language representation model and the sequence generation model with BERT encoder for multi-label task. We experiment with both models and explore their special qualities for this setting. We also introduce and examine experimentally a mixed model, which is an ensemble of multi-label BERT and sequence-to-sequence BERT models. Our experiments demonstrated that BERT-based models and the mixed model, in particular, outperform current baselines in several metrics achieving state-of-the-art results on three well-studied multi-label classification datasets with English texts and two private Yandex Taxi datasets with Russian texts.

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