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SJ_AJ@DravidianLangTech-EACL2021: Task-Adaptive Pre-Training of Multilingual BERT models for Offensive Language Identification

2021-02-01 · EACL (DravidianLangTech) 2021 4 · Sai Muralidhar Jayanthi, Akshat Gupta

In this paper we present our submission for the EACL 2021-Shared Task on Offensive Language Identification in Dravidian languages. Our final system is an ensemble of mBERT and XLM-RoBERTa models which leverage task-adaptive pre-training of multilingual BERT models with a masked language modeling objective. Our system was ranked 1st for Kannada, 2nd for Malayalam and 3rd for Tamil.

📄 PDF Abstract BibTeX arXiv:2102.01051

Code (1)

murali1996/eacl2021-OffensEval-Dravidian 공식 구현 pytorch

Tasks

Language IdentificationLanguage ModelingLanguage ModellingMasked Language Modeling

Methods 이 논문이 사용한 방법론

Linear Layer A Linear Layer is a projection $\mathbf{XW + b}$.
mBERT mBERT
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Softmax The Softmax output function transforms a previous layer's output into a vector of probabilities. It is commonly used for multiclass classification. Given an input vector $x$…
Attention 설명 없음
Dense Connections Dense Connections, or Fully Connected Connections, are a type of layer in a deep neural network that use a linear operation where every input is connected to every output…
Residual Connection 설명 없음
WordPiece 설명 없음

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