Fontana-Unipi @ HaSpeeDe2: Ensemble of transformers for the Hate Speech task at Evalita (short paper)

Michele Fontana, Giuseppe Attardi
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引用次数: 1

Abstract

We describe our approach and experiments to tackle Task A of the second edition of HaSpeeDe, within the Evalita 2020 evaluation campaign. The proposed model consists in an ensemble of classifiers built from three variants of a common neural architecture. Each classifier uses contextual representations from transformers trained on Italian texts, fine tuned on the training set of the challenge. We tested the proposed model on the two official test sets, the in-domain test set containing just tweets and the out-of-domain one including also news headlines. Our submissions ranked 4th on the tweets test set and 17th on the second test set.
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Fontana-Unipi @ HaSpeeDe2: Evalita仇恨言论任务的变形金刚集合(短文)
我们描述了我们在Evalita 2020评估活动中解决HaSpeeDe第二版任务A的方法和实验。提出的模型由由三种常见神经结构变体构建的分类器集成而成。每个分类器使用来自意大利语文本训练的转换器的上下文表示,并对挑战的训练集进行微调。我们在两个官方测试集上测试了提出的模型,域内测试集只包含tweet,域外测试集也包括新闻标题。我们的提交在推文测试集中排名第4,在第二个测试集中排名第17。
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DIACR-Ita @ EVALITA2020: Overview of the EVALITA2020 Diachronic Lexical Semantics (DIACR-Ita) Task QMUL-SDS @ DIACR-Ita: Evaluating Unsupervised Diachronic Lexical Semantics Classification in Italian (short paper) By1510 @ HaSpeeDe 2: Identification of Hate Speech for Italian Language in Social Media Data (short paper) HaSpeeDe 2 @ EVALITA2020: Overview of the EVALITA 2020 Hate Speech Detection Task KIPoS @ EVALITA2020: Overview of the Task on KIParla Part of Speech Tagging
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