A Dutch Dataset for Cross-lingual Multi-label Toxicity Detection
Ben Burtenshaw, Mike Kestemont · 2021
Multi-label toxicity detection is highly prominent, with many research groups, companies, and individuals engaging with it through shared tasks and dedicated venues.This paper describes a cross-lingual approach to annotating multi-label text classification on a newly developed Dutch language dataset, using a model trained on English data.We present an ensemble model of one Transformer model and an LSTM using Multilingual embeddings.The combination of multilingual embeddings and the Transformer model improves performance in a cross-lingual setting.