This repo contains implementation for the paper "IIITT@DravidianLangTech-EACL2021: Transfer Learning for Offensive Language Detection in Dravidian Languages" to be presented at EACL-2021
In this paper, we propose to use several pretrained multilingual models (transformers) embeddings, then to be fed into a Bidirectional LSTM Layers.
To replicate the results, run the Colab files. If you find this repo useful, please cite our paper :
@inproceedings{yasaswini-etal-2021-iiitt,
title = "{IIITT}@{D}ravidian{L}ang{T}ech-{EACL}2021: Transfer Learning for Offensive Language Detection in {D}ravidian Languages",
author = "Yasaswini, Konthala and
Puranik, Karthik and
Hande, Adeep and
Priyadharshini, Ruba and
Thavareesan, Sajeetha and
Chakravarthi, Bharathi Raja",
booktitle = "Proceedings of the First Workshop on Speech and Language Technologies for Dravidian Languages",
month = apr,
year = "2021",
address = "Kyiv",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/2021.dravidianlangtech-1.25",
pages = "187--194",
abstract = "This paper demonstrates our work for the shared task on Offensive Language Identification in Dravidian Languages-EACL 2021. Offensive language detection in the various social media platforms was identified previously. But with the increase in diversity of users, there is a need to identify the offensive language in multilingual posts that are largely code-mixed or written in a non-native script. We approach this challenge with various transfer learning-based models to classify a given post or comment in Dravidian languages (Malayalam, Tamil, and Kannada) into 6 categories. The source codes for our systems are published.",
}