Natural Language Processing

Korean Simple Contrastive Learning of Sentence Embeddings implementation using pytorch

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

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)


 


 




 


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