Korean Simple Contrastive Learning of Sentence Embeddings using SKT KoBERT and kakaobrain KorNLU dataset

Overview

KoSimCSE

  • Korean Simple Contrastive Learning of Sentence Embeddings implementation using pytorch

Installation

git clone https://github.com/BM-K/KoSimCSE.git
cd KoSimCSE
git clone https://github.com/SKTBrain/KoBERT.git
cd KoBERT
pip install -r requirements.txt
pip install .
cd ..
pip install -r requirements.txt

Training - only supervised

  • Model

  • Dataset

  • Setting

    • epochs: 3
    • dropout: 0.1
    • batch size: 256
    • temperature: 0.05
    • learning rate: 5e-5
    • warm-up ratio: 0.05
    • max sequence length: 50
    • evaluation steps during training: 250
  • Run train -> test -> semantic_search

bash run_example.sh

Pre-Trained Models

  • Using BERT [CLS] token representation
  • Pre-Trained model check point

Performance

Model Cosine Pearson Cosine Spearman Euclidean Pearson Euclidean Spearman Manhattan Pearson Manhattan Spearman Dot Pearson Dot Spearman
KoSBERT_SKT* 78.81 78.47 77.68 77.78 77.71 77.83 75.75 75.22
KoSimCSE_SKT 81.55 82.11 81.70 81.69 81.65 81.60 78.19 77.18

Example Downstream Task

Semantic Search

python SemanticSearch.py
import numpy as np
from model.utils import pytorch_cos_sim
from data.dataloader import convert_to_tensor, example_model_setting


def main():
    model_ckpt = './output/nli_checkpoint.pt'
    model, transform, device = example_model_setting(model_ckpt)

    # Corpus with example sentences
    corpus = ['한 남자가 음식을 먹는다.',
              '한 남자가 빵 한 조각을 먹는다.',
              '그 여자가 아이를 돌본다.',
              '한 남자가 말을 탄다.',
              '한 여자가 바이올린을 연주한다.',
              '두 남자가 수레를 숲 속으로 밀었다.',
              '한 남자가 담으로 싸인 땅에서 백마를 타고 있다.',
              '원숭이 한 마리가 드럼을 연주한다.',
              '치타 한 마리가 먹이 뒤에서 달리고 있다.']

    inputs_corpus = convert_to_tensor(corpus, transform)

    corpus_embeddings = model.encode(inputs_corpus, device)

    # Query sentences:
    queries = ['한 남자가 파스타를 먹는다.',
               '고릴라 의상을 입은 누군가가 드럼을 연주하고 있다.',
               '치타가 들판을 가로 질러 먹이를 쫓는다.']

    # Find the closest 5 sentences of the corpus for each query sentence based on cosine similarity
    top_k = 5
    for query in queries:
        query_embedding = model.encode(convert_to_tensor([query], transform), device)
        cos_scores = pytorch_cos_sim(query_embedding, corpus_embeddings)[0]
        cos_scores = cos_scores.cpu().detach().numpy()

        top_results = np.argpartition(-cos_scores, range(top_k))[0:top_k]

        print("\n\n======================\n\n")
        print("Query:", query)
        print("\nTop 5 most similar sentences in corpus:")

        for idx in top_results[0:top_k]:
            print(corpus[idx].strip(), "(Score: %.4f)" % (cos_scores[idx]))

Result

Query: 한 남자가 파스타를 먹는다.

Top 5 most similar sentences in corpus:
한 남자가 음식을 먹는다. (Score: 0.6002)
한 남자가 빵 한 조각을 먹는다. (Score: 0.5938)
치타 한 마리가 먹이 뒤에서 달리고 있다. (Score: 0.0696)
한 남자가 말을 탄다. (Score: 0.0328)
원숭이 한 마리가 드럼을 연주한다. (Score: -0.0048)


======================


Query: 고릴라 의상을 입은 누군가가 드럼을 연주하고 있다.

Top 5 most similar sentences in corpus:
원숭이 한 마리가 드럼을 연주한다. (Score: 0.6489)
한 여자가 바이올린을 연주한다. (Score: 0.3670)
한 남자가 말을 탄다. (Score: 0.2322)
그 여자가 아이를 돌본다. (Score: 0.1980)
한 남자가 담으로 싸인 땅에서 백마를 타고 있다. (Score: 0.1628)


======================


Query: 치타가 들판을 가로 질러 먹이를 쫓는다.

Top 5 most similar sentences in corpus:
치타 한 마리가 먹이 뒤에서 달리고 있다. (Score: 0.7756)
두 남자가 수레를 숲 속으로 밀었다. (Score: 0.1814)
한 남자가 말을 탄다. (Score: 0.1666)
원숭이 한 마리가 드럼을 연주한다. (Score: 0.1530)
한 남자가 담으로 싸인 땅에서 백마를 타고 있다. (Score: 0.1270)

Citing

SimCSE

@article{gao2021simcse,
   title={{SimCSE}: Simple Contrastive Learning of Sentence Embeddings},
   author={Gao, Tianyu and Yao, Xingcheng and Chen, Danqi},
   journal={arXiv preprint arXiv:2104.08821},
   year={2021}
}

KorNLU Datasets

@article{ham2020kornli,
  title={KorNLI and KorSTS: New Benchmark Datasets for Korean Natural Language Understanding},
  author={Ham, Jiyeon and Choe, Yo Joong and Park, Kyubyong and Choi, Ilji and Soh, Hyungjoon},
  journal={arXiv preprint arXiv:2004.03289},
  year={2020}
}
Owner
Self-softmax
A python package for deep multilingual punctuation prediction.

This python library predicts the punctuation of English, Italian, French and German texts. We developed it to restore the punctuation of transcribed spoken language.

Oliver Guhr 27 Dec 22, 2022
TFIDF-based QA system for AIO2 competition

AIO2 TF-IDF Baseline This is a very simple question answering system, which is developed as a lightweight baseline for AIO2 competition. In the traini

Masatoshi Suzuki 4 Feb 19, 2022
This repository contains the codes for LipGAN. LipGAN was published as a part of the paper titled "Towards Automatic Face-to-Face Translation".

LipGAN Generate realistic talking faces for any human speech and face identity. [Paper] | [Project Page] | [Demonstration Video] Important Update: A n

Rudrabha Mukhopadhyay 438 Dec 31, 2022
This script just scrapes the most recent Nepali news from Kathmandu Post and notifies the user about current events at regular intervals.It sends out the most recent news at random!

Nepali-news-notifier This script just scrapes the most recent Nepali news from Kathmandu Post and notifies the user about current events at regular in

Sachit Yadav 1 Feb 11, 2022
Officile code repository for "A Game-Theoretic Perspective on Risk-Sensitive Reinforcement Learning"

CvarAdversarialRL Official code repository for "A Game-Theoretic Perspective on Risk-Sensitive Reinforcement Learning". Initial setup Create a virtual

Mathieu Godbout 1 Nov 19, 2021
Fast, general, and tested differentiable structured prediction in PyTorch

Torch-Struct: Structured Prediction Library A library of tested, GPU implementations of core structured prediction algorithms for deep learning applic

HNLP 1.1k Dec 16, 2022
Awesome Treasure of Transformers Models Collection

💁 Awesome Treasure of Transformers Models for Natural Language processing contains papers, videos, blogs, official repo along with colab Notebooks. 🛫☑️

Ashish Patel 577 Jan 07, 2023
Natural language processing summarizer using 3 state of the art Transformer models: BERT, GPT2, and T5

NLP-Summarizer Natural language processing summarizer using 3 state of the art Transformer models: BERT, GPT2, and T5 This project aimed to provide in

Samuel Sharkey 1 Feb 07, 2022
An ActivityWatch watcher to pose questions to the user and record her answers.

aw-watcher-ask An ActivityWatch watcher to pose questions to the user and record her answers. This watcher uses Zenity to present dialog boxes to the

Bernardo Chrispim Baron 33 Dec 03, 2022
端到端的长本文摘要模型(法研杯2020司法摘要赛道)

端到端的长文本摘要模型(法研杯2020司法摘要赛道)

苏剑林(Jianlin Su) 334 Jan 08, 2023
Grading tools for Advanced NLP (11-711)Grading tools for Advanced NLP (11-711)

Grading tools for Advanced NLP (11-711) Installation You'll need docker and unzip to use this repo. For docker, visit the official guide to get starte

Hao Zhu 2 Sep 27, 2022
原神抽卡记录数据集-Genshin Impact gacha data

提要 持续收集原神抽卡记录中 可以使用抽卡记录导出工具导出抽卡记录的json,将json文件发送至[email protected],我会在清除个人信息后

117 Dec 27, 2022
Package for controllable summarization

summarizers summarizers is package for controllable summarization based CTRLsum. currently, we only supports English. It doesn't work in other languag

Hyunwoong Ko 72 Dec 07, 2022
Use Tensorflow2.7.0 Build OpenAI'GPT-2

TF2_GPT-2 Use Tensorflow2.7.0 Build OpenAI'GPT-2 使用最新tensorflow2.7.0构建openai官方的GPT-2 NLP模型 优点 使用无监督技术 拥有大量词汇量 可实现续写(堪比“xx梦续写”) 实现对话后续将应用于FloatTech的Bot

Watermelon 9 Sep 13, 2022
Tools to download and cleanup Common Crawl data

cc_net Tools to download and clean Common Crawl as introduced in our paper CCNet. If you found these resources useful, please consider citing: @inproc

Meta Research 483 Jan 02, 2023
Example code for "Real-World Natural Language Processing"

Real-World Natural Language Processing This repository contains example code for the book "Real-World Natural Language Processing." AllenNLP (2.5.0 or

Masato Hagiwara 303 Dec 17, 2022
PUA Programming Language written in Python.

pua-lang PUA Programming Language written in Python. Installation git clone https://github.com/zhaoyang97/pua-lang.git cd pua-lang pip install . Try

zy 4 Feb 19, 2022
Dé op-de-vlucht Pieton vertaler. Wereldwijd gebruikt door meer dan 1.000+ succesvolle bedrijven!

Dé op-de-vlucht Pieton vertaler. Wereldwijd gebruikt door meer dan 1.000+ succesvolle bedrijven!

Lau 1 Dec 17, 2021
Chinese named entity recognization (bert/roberta/macbert/bert_wwm with Keras)

Chinese named entity recognization (bert/roberta/macbert/bert_wwm with Keras)

2 Jul 05, 2022
The official code for “DocTr: Document Image Transformer for Geometric Unwarping and Illumination Correction”, ACM MM, Oral Paper, 2021.

Good news! Our new work exhibits state-of-the-art performances on DocUNet benchmark dataset: DocScanner: Robust Document Image Rectification with Prog

Hao Feng 231 Dec 26, 2022