All Projects → monologg → KoBERT-nsmc

monologg / KoBERT-nsmc

Licence: Apache-2.0 License
Naver movie review sentiment classification with KoBERT

Programming Languages

python
139335 projects - #7 most used programming language

Projects that are alternatives of or similar to KoBERT-nsmc

bert-movie-reviews-sentiment-classifier
Build a Movie Reviews Sentiment Classifier with Google's BERT Language Model
Stars: ✭ 12 (-78.95%)
Mutual labels:  movie-reviews, bert, sentiment-classification
KoBERT-NER
NER Task with KoBERT (with Naver NLP Challenge dataset)
Stars: ✭ 76 (+33.33%)
Mutual labels:  kobert, distilkobert
Pytorch Sentiment Analysis
Tutorials on getting started with PyTorch and TorchText for sentiment analysis.
Stars: ✭ 3,209 (+5529.82%)
Mutual labels:  bert, sentiment-classification
banglabert
This repository contains the official release of the model "BanglaBERT" and associated downstream finetuning code and datasets introduced in the paper titled "BanglaBERT: Language Model Pretraining and Benchmarks for Low-Resource Language Understanding Evaluation in Bangla" accpeted in Findings of the Annual Conference of the North American Chap…
Stars: ✭ 186 (+226.32%)
Mutual labels:  bert, sentiment-classification
tensorflow-ml-nlp-tf2
텐서플로2와 머신러닝으로 시작하는 자연어처리 (로지스틱회귀부터 BERT와 GPT3까지) 실습자료
Stars: ✭ 245 (+329.82%)
Mutual labels:  bert, nsmc
COVID-19-Tweet-Classification-using-Roberta-and-Bert-Simple-Transformers
Rank 1 / 216
Stars: ✭ 24 (-57.89%)
Mutual labels:  bert, sentiment-classification
KLUE
📖 Korean NLU Benchmark
Stars: ✭ 420 (+636.84%)
Mutual labels:  bert
Mengzi
Mengzi Pretrained Models
Stars: ✭ 238 (+317.54%)
Mutual labels:  bert
classy
classy is a simple-to-use library for building high-performance Machine Learning models in NLP.
Stars: ✭ 61 (+7.02%)
Mutual labels:  bert
text2text
Text2Text: Cross-lingual natural language processing and generation toolkit
Stars: ✭ 188 (+229.82%)
Mutual labels:  bert
knowledge-graph-nlp-in-action
从模型训练到部署,实战知识图谱(Knowledge Graph)&自然语言处理(NLP)。涉及 Tensorflow, Bert+Bi-LSTM+CRF,Neo4j等 涵盖 Named Entity Recognition,Text Classify,Information Extraction,Relation Extraction 等任务。
Stars: ✭ 58 (+1.75%)
Mutual labels:  bert
HugsVision
HugsVision is a easy to use huggingface wrapper for state-of-the-art computer vision
Stars: ✭ 154 (+170.18%)
Mutual labels:  bert
semantic-document-relations
Implementation, trained models and result data for the paper "Pairwise Multi-Class Document Classification for Semantic Relations between Wikipedia Articles"
Stars: ✭ 21 (-63.16%)
Mutual labels:  bert
cdQA-ui
⛔ [NOT MAINTAINED] A web interface for cdQA and other question answering systems.
Stars: ✭ 19 (-66.67%)
Mutual labels:  bert
billboard
🎤 Lyrics/associated NLP data for Billboard's Top 100, 1950-2015.
Stars: ✭ 53 (-7.02%)
Mutual labels:  sentiment-classification
OpenDialog
An Open-Source Package for Chinese Open-domain Conversational Chatbot (中文闲聊对话系统,一键部署微信闲聊机器人)
Stars: ✭ 94 (+64.91%)
Mutual labels:  bert
Filipino-Text-Benchmarks
Open-source benchmark datasets and pretrained transformer models in the Filipino language.
Stars: ✭ 22 (-61.4%)
Mutual labels:  bert
TextPair
文本对关系比较 - 语义相似度、字面相似度、文本蕴含等等
Stars: ✭ 44 (-22.81%)
Mutual labels:  bert
bangla-bert
Bangla-Bert is a pretrained bert model for Bengali language
Stars: ✭ 41 (-28.07%)
Mutual labels:  bert
erc
Emotion recognition in conversation
Stars: ✭ 34 (-40.35%)
Mutual labels:  bert

KoBERT-nsmc

  • KoBERT를 이용한 네이버 영화 리뷰 감정 분석 (sentiment classification)
  • 🤗Huggingface Tranformers🤗 라이브러리를 이용하여 구현

Dependencies

  • torch==1.4.0
  • transformers==2.10.0

How to use KoBERT on Huggingface Transformers Library

  • 기존의 KoBERT를 transformers 라이브러리에서 곧바로 사용할 수 있도록 맞췄습니다.
    • transformers v2.2.2부터 개인이 만든 모델을 transformers를 통해 직접 업로드/다운로드하여 사용할 수 있습니다
  • Tokenizer를 사용하려면 tokenization_kobert.py에서 KoBertTokenizer를 임포트해야 합니다.
from transformers import BertModel
from tokenization_kobert import KoBertTokenizer

model = BertModel.from_pretrained('monologg/kobert')
tokenizer = KoBertTokenizer.from_pretrained('monologg/kobert')

Usage

$ python3 main.py --model_type kobert --do_train --do_eval

Prediction

$ python3 predict.py --input_file {INPUT_FILE_PATH} --output_file {OUTPUT_FILE_PATH} --model_dir {SAVED_CKPT_PATH}

Results

Accuracy (%)
KoBERT 89.63
DistilKoBERT 88.41
Bert-Multilingual 87.07
FastText 85.50

References

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].