NLP-CUET@DravidianLangTech-EACL2021: Offensive Language Detection from Multilingual Code-Mixed Text using Transformers

The increasing accessibility of the internet facilitated social media usage and encouraged individuals to express their opinions liberally. Nevertheless, it also creates a place for content polluters to disseminate offensive posts or contents... (read more)

PDF Abstract

Datasets


  Add Datasets introduced or used in this paper

Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper


METHOD TYPE
Residual Connection
Skip Connections
Weight Decay
Regularization
Attention Dropout
Regularization
Linear Warmup With Linear Decay
Learning Rate Schedules
WordPiece
Subword Segmentation
Adam
Stochastic Optimization
Dropout
Regularization
Softmax
Output Functions
Dense Connections
Feedforward Networks
GELU
Activation Functions
Multi-Head Attention
Attention Modules
Layer Normalization
Normalization
Scaled Dot-Product Attention
Attention Mechanisms
BERT
Language Models