TeamUNCC@LT-EDI-EACL2021: Hope Speech Detection using Transfer Learning with Transformers

2021-04-19 · Khyati Mahajan, Erfan Al-Hossami, Samira Shaikh

In this paper, we describe our approach towards utilizing pre-trained models for the task of hope speech detection. We participated in Task 2: Hope Speech Detection for Equality, Diversity and Inclusion at LT-EDI-2021 @ EACL2021. The goal of this task is to predict the presence of hope speech, along with the presence of samples that do not belong to the same language in the dataset. We describe our approach to fine-tuning RoBERTa for Hope Speech detection in English and our approach to fine-tuning XLM-RoBERTa for Hope Speech detection in Tamil and Malayalam, two low resource Indic languages. We demonstrate the performance of our approach on classifying text into hope-speech, non-hope and not-language. Our approach ranked 1st in English (F1 = 0.93), 1st in Tamil (F1 = 0.61) and 3rd in Malayalam (F1 = 0.83).

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Code (1)

SoLID-UNCC/TeamUNCC-HopeSpeech

Tasks

DiversityHope Speech Detection Hope Speech Detection for English Hope Speech Detection for Malayalam Hope Speech Detection for TamilTask 2Text Classification Transfer Learning

Methods 이 논문이 사용한 방법론

Linear Layer A Linear Layer is a projection $\mathbf{XW + b}$.

Linear Warmup With Linear Decay Linear Warmup With Linear Decay is a learning rate schedule in which we increase the learning rate linearly for $n$ updates and then linearly decay afterwards.

WordPiece 설명 없음

Weight Decay 설명 없음

Residual Connection 설명 없음

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

Multi-Head Attention 설명 없음

IIITT@LT-EDI-EACL2021-Hope Speech Detection: There is always Hope in Transformers

2021-04-19 · Karthik Puranik, Adeep Hande, Ruba Priyadharshini, Sajeetha Thavareesan 외

In a world filled with serious challenges like climate change, religious and political conflicts, global pandemics, terrorism, and racial discrimination, an internet full of hate speech, abusive and offensive content is …

Diversity Hope Speech Detection

cs_english@LT-EDI-EACL2021: Hope Speech Detection Based On Fine-tuning ALBERT Model

2021-04-01 · EACL (LTEDI) 2021 4 · Shi Chen, Bing Kong

This paper mainly introduces the relevant content of the task “Hope Speech Detection for Equality, Diversity, and Inclusion at LT-EDI 2021-EACL 2021”. A total of three language datasets were provided, and we chose the En…

Diversity Hope Speech Detection

GCDH@LT-EDI-EACL2021: XLM-RoBERTa for Hope Speech Detection in English, Malayalam, and Tamil

2021-04-01 · EACL (LTEDI) 2021 4 · Stefan Ziehe, Franziska Pannach, Aravind Krishnan

This paper describes approaches to identify Hope Speech in short, informal texts in English, Malayalam and Tamil using different machine learning techniques. We demonstrate that even very simple baseline algorithms perfo…

BIG-bench Machine Learning Cross-Lingual Transfer Hope Speech Detection Transfer Learning

IRNLP_DAIICT@LT-EDI-EACL2021: Hope Speech detection in Code Mixed text using TF-IDF Char N-grams and MuRIL

2021-04-01 · EACL (LTEDI) 2021 4 · Bhargav Dave, Shripad Bhat, Prasenjit Majumder

This paper presents the participation of the IRNLP_DAIICT team from Information Retrieval and Natural Language Processing lab at DA-IICT, India in LT-EDI@EACL2021 Hope Speech Detection task. The aim of this shared task i…

Hope Speech Detection Information Retrieval regression Retrieval

dhivya-hope-detection@LT-EDI-EACL2021: Multilingual Hope Speech Detection for Code-mixed and Transliterated Texts

2021-04-01 · EACL (LTEDI) 2021 4 · Dhivya Chinnappa

In this paper we work with a hope speech detection corpora that includes English, Tamil, and Malayalam datasets. We present a two phase mechanism to detect hope speech. In the first phase we build a classifier to identif…

Hope Speech Detection