APEACH: Attacking Pejorative Expressions with Analysis on Crowd-generated Hate Speech Evaluation Datasets

Related tags

Text Data & NLPAPEACH
Overview

APEACH - Korean Hate Speech Evaluation Datasets

APEACH is the first crowd-generated Korean evaluation dataset for hate speech detection. Sentences of the dataset are created by anonymous participants using an online crowdsourcing platform DeepNatural AI.

  • Sample Code : base

Download

You can download benchmark set APEACH. APEACH/test.csv in this repository.

Dataset Description

  • APEACH : A hate-speech evaluation dataset generated in 2021, using generation method followd by APEACH paper.

Guidelines

APEACH-GUIDELINE

Topics

Lengths

Paper

Experiment Code

base

Experiment Results

Name Beep! Dev Dataset Apeach (Ours)
SoongsilBERT-Base 0.8261 0.8424
SoongsilBERT-Small 0.8149 0.8228
KcBERT-base 0.8088 0.8086
KcBERT-large 0.8295 0.8116
DistillKoBERT 0.7570 0.7715
KoELECTRA-V3 0.7920 0.8101
KoBERT 0.8030 0.7885

We also share BEST model of our dataset which we trained in this experiment as checkpoint, demo webite and api.

Citation

@article{yang2022apeach,
  title={APEACH: Attacking Pejorative Expressions with Analysis on Crowd-Generated Hate Speech Evaluation Datasets},
  author={Yang, Kichang and Jang, Wonjun and Cho, Won Ik},
  journal={arXiv preprint arXiv:2202.12459},
  year={2022}
}

Contributors

The main contributors of the work ( * : equal contribution) :

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Owner
Kevin-Yang
Kevin-Yang
Header-only C++ HNSW implementation with python bindings

Hnswlib - fast approximate nearest neighbor search Header-only C++ HNSW implementation with python bindings. NEWS: version 0.6 Thanks to (@dyashuni) h

2.3k Jan 05, 2023
Exploring dimension-reduced embeddings

sleepwalk Exploring dimension-reduced embeddings This is the code repository. See here for the Sleepwalk web page. License and disclaimer This program

S. Anders's research group at ZMBH 91 Nov 29, 2022
Unofficial Implementation of Zero-Shot Text-to-Speech for Text-Based Insertion in Audio Narration

Zero-Shot Text-to-Speech for Text-Based Insertion in Audio Narration This repo contains only model Implementation of Zero-Shot Text-to-Speech for Text

Rishikesh (ऋषिकेश) 33 Sep 22, 2022
Random-Word-Generator - Generates meaningful words from dictionary with given no. of letters and words.

Random Word Generator Generates meaningful words from dictionary with given no. of letters and words. This might be useful for generating short links

Mohammed Rabil 1 Jan 01, 2022
Deduplication is the task to combine different representations of the same real world entity.

Deduplication is the task to combine different representations of the same real world entity. This package implements deduplication using active learning. Active learning allows for rapid training wi

63 Nov 17, 2022
Code for Findings at EMNLP 2021 paper: "Learn Continually, Generalize Rapidly: Lifelong Knowledge Accumulation for Few-shot Learning"

Learn Continually, Generalize Rapidly: Lifelong Knowledge Accumulation for Few-shot Learning This repo is for Findings at EMNLP 2021 paper: Learn Cont

INK Lab @ USC 6 Sep 02, 2022
Python library for parsing resumes using natural language processing and machine learning

CVParser Python library for parsing resumes using natural language processing and machine learning. Setup Installation on Linux and Mac OS Follow the

nafiu 0 Jul 29, 2021
Train 🤗transformers with DeepSpeed: ZeRO-2, ZeRO-3

Fork from https://github.com/huggingface/transformers/tree/86d5fb0b360e68de46d40265e7c707fe68c8015b/examples/pytorch/language-modeling at 2021.05.17.

Junbum Lee 12 Oct 26, 2022
This is the code for the EMNLP 2021 paper AEDA: An Easier Data Augmentation Technique for Text Classification

The baseline code is for EDA: Easy Data Augmentation techniques for boosting performance on text classification tasks

Akbar Karimi 81 Dec 09, 2022
The following links explain a bit the idea of semantic search and how search mechanisms work by doing retrieve and rerank

Main Idea The following links explain a bit the idea of semantic search and how search mechanisms work by doing retrieve and rerank Semantic Search Re

Sergio Arnaud Gomez 2 Jan 28, 2022
🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.

State-of-the-art Natural Language Processing for PyTorch and TensorFlow 2.0 🤗 Transformers provides thousands of pretrained models to perform tasks o

Hugging Face 77.3k Jan 03, 2023
Code for the paper "Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer"

T5: Text-To-Text Transfer Transformer The t5 library serves primarily as code for reproducing the experiments in Exploring the Limits of Transfer Lear

Google Research 4.6k Jan 01, 2023
Implementation of TF-IDF algorithm to find documents similarity with cosine similarity

NLP learning Trying to learn NLP to use in my projects! Table of Contents About The Project Built With Getting Started Requirements Run Usage License

Faraz Farangizadeh 3 Aug 25, 2022
Mednlp - Medical natural language parsing and utility library

Medical natural language parsing and utility library A natural language medical

Paul Landes 3 Aug 24, 2022
Twewy-discord-chatbot - Build a Discord AI Chatbot that Speaks like Your Favorite Character

Build a Discord AI Chatbot that Speaks like Your Favorite Character! This is a Discord AI Chatbot that uses the Microsoft DialoGPT conversational mode

Lynn Zheng 231 Dec 30, 2022
A multi-lingual approach to AllenNLP CoReference Resolution along with a wrapper for spaCy.

Crosslingual Coreference Coreference is amazing but the data required for training a model is very scarce. In our case, the available training for non

Pandora Intelligence 71 Jan 04, 2023
What are the best Systems? New Perspectives on NLP Benchmarking

What are the best Systems? New Perspectives on NLP Benchmarking In Machine Learning, a benchmark refers to an ensemble of datasets associated with one

Pierre Colombo 12 Nov 03, 2022
EasyTransfer is designed to make the development of transfer learning in NLP applications easier.

EasyTransfer is designed to make the development of transfer learning in NLP applications easier. The literature has witnessed the success of applying

Alibaba 819 Jan 03, 2023
Code for our paper "Transfer Learning for Sequence Generation: from Single-source to Multi-source" in ACL 2021.

TRICE: a task-agnostic transferring framework for multi-source sequence generation This is the source code of our work Transfer Learning for Sequence

THUNLP-MT 9 Jun 27, 2022
a test times augmentation toolkit based on paddle2.0.

Patta Image Test Time Augmentation with Paddle2.0! Input | # input batch of images / / /|\ \ \ # apply

AgentMaker 110 Dec 03, 2022