Korean stereoypte detector with TUNiB-Electra and K-StereoSet

Related tags

Text Data & NLPStereotype-Detector
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
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