TheNorth @ HaSpeeDe 2: BERT-based Language Model Fine-tuning for Italian Hate Speech Detection (short paper)

Eric Lavergne, Rajkumar Saini, György Kovács, Killian Murphy
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引用次数: 10

Abstract

English. This report was written to describe the systems that were submitted by the team “TheNorth” for the HaSpeeDe 2 shared task organised within EVALITA 2020. To address the main task which is hate speech detection, we fine-tuned BERT-based models. We evaluated both multilingual and Italian language models trained with the data provided and additional data. We also studied the contributions of multitask learning considering both hate speech detection and stereotype detection tasks.
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TheNorth @ HaSpeeDe 2:基于bert的语言模型微调意大利语仇恨语音检测(短论文)
英语。本报告描述了由“the north”团队为EVALITA 2020组织的HaSpeeDe 2共享任务提交的系统。为了解决仇恨语音检测的主要任务,我们对基于bert的模型进行了微调。我们评估了用所提供的数据和附加数据训练的多语言和意大利语模型。我们还研究了多任务学习对仇恨言论检测和刻板印象检测任务的贡献。
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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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