Korean stereoypte detector with TUNiB-Electra and K-StereoSet

Overview

Korean Stereotype Detector

Korean stereotype sentence classifier using K-StereoSet with TUNiB-Electra

Web demo

Dataset

  • There are 12,688 human-labeled comments in total.
  • They ar splitted into 10,688 train set, 1000 test set and 1000 valid set
stereotype, anti-stereotype, unrelated, profession, race, gender, religion, comment
1.0,    0.0,    0.0,    1.0,    0.0,    0.0,    0.0,    축구선수의 오랜 경력의 전형적인 결과는 부상을 입은 발목과 두개골이다.
1.0,    0.0,    0.0,    0.0,    1.0,    0.0,    0.0,    콜롬비아 사람들은 모두 마약 카르텔에 소속되어 있다.
0.0,    1.0,    0.0,    0.0,    1.0,    0.0,    0.0,    그는 무기를 소지한 적이 없다.
0.0,    1.0,    0.0,    0.0,    0.0,    1.0,    0.0,    그는 주말에만 지루할 수 있는 일을 한다.

Detail

stereotype anti-stereotype unrelated profession race gender religion Total
Train 3,550 3,556 3,581 4,140 4,896 1,268 383 10,688
Valid 341 347 312 410 435 110 45 1,000
Test 334 324 336 361 483 113 43 1,000

Score

precision recall F1
stereotype 0.814 0.601 0.691
anti-stereotype 0.894 0.509 0.648
unrelated 0.872 0.870 0.871
profession 0.943 0.711 0.811
race 0.787 0.907 0.843
gender 0.639 0.836 0.724
religion 0.724 1.0 0.840
total (macro score) 0.810 0.776 0.775

Usage

  • training
python3 train.py --model_name tunib/electra-ko-base \
                 --data_dir YOUR_PATH \
                 --batch_size BATCH_SIZE \
  • threshold optimizing
python3 threshold.py --model_name tunib/electra-ko-base \
                     --data_dir YOUR_CKPT_DIR_PATH \
                     --file_path YOUR_CKPT_FILE_NAME \
                     --batch_size BATCH_SIZE \
                     --data_path TEST_DATA_PATH
  • test
python3 score.py --model_name tunib/electra-ko-base \
                 --data_dir YOUR_CKPT_DIR_PATH \
                 --file_path YOUR_CKPT_FILE_NAME \
                 --batch_size BATCH_SIZE \
                 --data_path TEST_DATA_PATH
Owner
Sae_Chan_Oh
Schrödingers Katze
Sae_Chan_Oh
Few-shot Natural Language Generation for Task-Oriented Dialog

Few-shot Natural Language Generation for Task-Oriented Dialog This repository contains the dataset, source code and trained model for the following pa

172 Dec 13, 2022
Calibre recipe to convert latest issue of Analyse & Kritik into an ebook

Calibre Recipe für "Analyse & Kritik" Dies ist ein "Recipe" für die Konvertierung der aktuellen Ausgabe der Zeitung Analyse & Kritik in ein Ebook. Es

Henning 3 Jan 04, 2022
BERT has a Mouth, and It Must Speak: BERT as a Markov Random Field Language Model

BERT has a Mouth, and It Must Speak: BERT as a Markov Random Field Language Model

303 Dec 17, 2022
Python code for ICLR 2022 spotlight paper EViT: Expediting Vision Transformers via Token Reorganizations

Expediting Vision Transformers via Token Reorganizations This repository contain

Youwei Liang 101 Dec 26, 2022
Paddlespeech Streaming ASR GUI

Paddlespeech-Streaming-ASR-GUI Introduction A paddlespeech Streaming ASR GUI. Us

Niek Zhen 3 Jan 05, 2022
Transformation spoken text to written text

Transformation spoken text to written text This model is used for formatting raw asr text output from spoken text to written text (Eg. date, number, i

Nguyen Binh 16 Dec 28, 2022
AI and Machine Learning workflows on Anthos Bare Metal.

Hybrid and Sovereign AI on Anthos Bare Metal Table of Contents Overview Terraform as IaC Substrate ABM Cluster on GCE using Terraform TensorFlow ResNe

Google Cloud Platform 8 Nov 26, 2022
Optimal Transport Tools (OTT), A toolbox for all things Wasserstein.

Optimal Transport Tools (OTT), A toolbox for all things Wasserstein. See full documentation for detailed info on the toolbox. The goal of OTT is to pr

OTT-JAX 255 Dec 26, 2022
Generate vector graphics from a textual caption

VectorAscent: Generate vector graphics from a textual description Example "a painting of an evergreen tree" python text_to_painting.py --prompt "a pai

Ajay Jain 97 Dec 15, 2022
Baseline code for Korean open domain question answering(ODQA)

Open-Domain Question Answering(ODQA)는 다양한 주제에 대한 문서 집합으로부터 자연어 질의에 대한 답변을 찾아오는 task입니다. 이때 사용자 질의에 답변하기 위해 주어지는 지문이 따로 존재하지 않습니다. 따라서 사전에 구축되어있는 Knowl

VUMBLEB 69 Nov 04, 2022
An extension for asreview implements a version of the tf-idf feature extractor that saves the matrix and the vocabulary.

Extension - matrix and vocabulary extractor for TF-IDF and Doc2Vec An extension for ASReview that adds a tf-idf extractor that saves the matrix and th

ASReview 4 Jun 17, 2022
基于pytorch_rnn的古诗词生成

pytorch_peot_rnn 基于pytorch_rnn的古诗词生成 说明 config.py里面含有训练、测试、预测的参数,更改后运行: python main.py 预测结果 if config.do_predict: result = trainer.generate('丽日照残春')

西西嘛呦 3 May 26, 2022
Disfl-QA: A Benchmark Dataset for Understanding Disfluencies in Question Answering

Disfl-QA is a targeted dataset for contextual disfluencies in an information seeking setting, namely question answering over Wikipedia passages. Disfl-QA builds upon the SQuAD-v2 (Rajpurkar et al., 2

Google Research Datasets 52 Jun 21, 2022
XLNet: Generalized Autoregressive Pretraining for Language Understanding

Introduction XLNet is a new unsupervised language representation learning method based on a novel generalized permutation language modeling objective.

Zihang Dai 6k Jan 07, 2023
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
Training and evaluation codes for the BertGen paper (ACL-IJCNLP 2021)

BERTGEN This repository is the implementation of the paper "BERTGEN: Multi-task Generation through BERT" (https://arxiv.org/abs/2106.03484). The codeb

<a href=[email protected]"> 9 Oct 26, 2022
Stanford CoreNLP provides a set of natural language analysis tools written in Java

Stanford CoreNLP Stanford CoreNLP provides a set of natural language analysis tools written in Java. It can take raw human language text input and giv

Stanford NLP 8.8k Jan 07, 2023
🦆 Contextually-keyed word vectors

sense2vec: Contextually-keyed word vectors sense2vec (Trask et. al, 2015) is a nice twist on word2vec that lets you learn more interesting and detaile

Explosion 1.5k Dec 25, 2022
Sequence-to-Sequence Framework in PyTorch

nmtpytorch allows training of various end-to-end neural architectures including but not limited to neural machine translation, image captioning and au

LIUM 395 Nov 21, 2022
This project consists of data analysis and data visualization (done using python)of all IPL seasons from 2008 to 2019 and answering the most asked questions about the IPL.

IPL-data-analysis This project consists of data analysis and data visualization of all IPL seasons from 2008 to 2019 and answering the most asked ques

Sivateja A T 2 Feb 08, 2022