🦅 Pretrained BigBird Model for Korean (up to 4096 tokens)

Last update: Dec 14, 2022

Overview

Pretrained BigBird Model for Korean

What is BigBird • How to Use • Pretraining • Evaluation Result • Docs • Citation

한국어 | English

What is BigBird?

BigBird: Transformers for Longer Sequences에서 소개된 sparse-attention 기반의 모델로, 일반적인 BERT보다 더 긴 sequence를 다룰 수 있습니다.

🦅 Longer Sequence - 최대 512개의 token을 다룰 수 있는 BERT의 8배인 최대 4096개의 token을 다룸

⏱️ Computational Efficiency - Full attention이 아닌 Sparse Attention을 이용하여 O(n²)에서 O(n)으로 개선

How to Use

🤗 Huggingface Hub에 업로드된 모델을 곧바로 사용할 수 있습니다:)
일부 이슈가 해결된 transformers>=4.11.0 사용을 권장합니다. (MRC 이슈 관련 PR)
BigBirdTokenizer 대신에 BertTokenizer 를 사용해야 합니다. (AutoTokenizer 사용시 BertTokenizer가 로드됩니다.)
자세한 사용법은 BigBird Tranformers documentation을 참고해주세요.

from transformers import AutoModel, AutoTokenizer

model = AutoModel.from_pretrained("monologg/kobigbird-bert-base")  # BigBirdModel
tokenizer = AutoTokenizer.from_pretrained("monologg/kobigbird-bert-base")  # BertTokenizer

Pretraining

자세한 내용은 [Pretraining BigBird] 참고

	Hardware	Max len	LR	Batch	Train Step	Warmup Step
KoBigBird-BERT-Base	TPU v3-8	4096	1e-4	32	2M	20k

모두의 말뭉치, 한국어 위키, Common Crawl, 뉴스 데이터 등 다양한 데이터로 학습
ITC (Internal Transformer Construction) 모델로 학습 (ITC vs ETC)

Evaluation Result

1. Short Sequence (<=512)

자세한 내용은 [Finetune on Short Sequence Dataset] 참고

	NSMC (acc)	KLUE-NLI (acc)	KLUE-STS (pearsonr)	Korquad 1.0 (em/f1)	KLUE MRC (em/rouge-w)
KoELECTRA-Base-v3	91.13	86.87	93.14	85.66 / 93.94	59.54 / 65.64
KLUE-RoBERTa-Base	91.16	86.30	92.91	85.35 / 94.53	69.56 / 74.64
KoBigBird-BERT-Base	91.18	87.17	92.61	87.08 / 94.71	70.33 / 75.34

2. Long Sequence (>=1024)

자세한 내용은 [Finetune on Long Sequence Dataset] 참고

	TyDi QA (em/f1)	Korquad 2.1 (em/f1)	Fake News (f1)	Modu Sentiment (f1-macro)
KLUE-RoBERTa-Base	76.80 / 78.58	55.44 / 73.02	95.20	42.61
KoBigBird-BERT-Base	79.13 / 81.30	67.77 / 82.03	98.85	45.42

Docs

Citation

KoBigBird를 사용하신다면 아래와 같이 인용해주세요.

@software{jangwon_park_2021_5654154,
  author       = {Jangwon Park and Donggyu Kim},
  title        = {KoBigBird: Pretrained BigBird Model for Korean},
  month        = nov,
  year         = 2021,
  publisher    = {Zenodo},
  version      = {1.0.0},
  doi          = {10.5281/zenodo.5654154},
  url          = {https://doi.org/10.5281/zenodo.5654154}
}

Contributors

Jangwon Park and Donggyu Kim

Acknowledgements

KoBigBird는 Tensorflow Research Cloud (TFRC) 프로그램의 Cloud TPU 지원으로 제작되었습니다.

또한 멋진 로고를 제공해주신 Seyun Ahn님께 감사를 전합니다.

KakaoBrain KoGPT (Korean Generative Pre-trained Transformer)

KoGPT KoGPT (Korean Generative Pre-trained Transformer) https://github.com/kakaobrain/kogpt https://huggingface.co/kakaobrain/kogpt Model Descriptions

797 Dec 26, 2022

Generating Korean Slogans with phonetic and structural repetition

LexPOS_ko Generating Korean Slogans with phonetic and structural repetition Generating Slogans with Linguistic Features LexPOS is a sequence-to-sequen

3 May 23, 2022

Korean extractive summarization. 2021 AI 텍스트 요약 온라인 해커톤 화성갈끄니까팀 코드

korean extractive summarization 2021 AI 텍스트 요약 온라인 해커톤 화성갈끄니까팀 코드 Leaderboard Notice Text Summarization with Pretrained Encoders에 나오는 bertsumext모델(ext

3 Aug 10, 2022

Training code for Korean multi-class sentiment analysis

KoSentimentAnalysis Bert implementation for the Korean multi-class sentiment analysis 왜 한국어 감정 다중분류 모델은 거의 없는 것일까?에서 시작된 프로젝트 Environment: Pytorch, Da

3 Dec 2, 2022

Korean Sentence Embedding Repository

Korean-Sentence-Embedding 🍭 Korean sentence embedding repository. You can download the pre-trained models and inference right away, also it provides

80 Jan 2, 2023

ProteinBERT is a universal protein language model pretrained on ~106M proteins from the UniRef90 dataset.

ProteinBERT is a universal protein language model pretrained on ~106M proteins from the UniRef90 dataset. Through its Python API, the pretrained model can be fine-tuned on any protein-related task in a matter of minutes. Based on our experiments with a wide range of benchmarks, ProteinBERT usually achieves state-of-the-art performance. ProteinBERT is built on TenforFlow/Keras.

241 Jan 4, 2023

IndoBERTweet is the first large-scale pretrained model for Indonesian Twitter. Published at EMNLP 2021 (main conference)

IndoBERTweet 🐦 🇮🇩 1. Paper Fajri Koto, Jey Han Lau, and Timothy Baldwin. IndoBERTweet: A Pretrained Language Model for Indonesian Twitter with Effe

40 Nov 30, 2022

BMInf (Big Model Inference) is a low-resource inference package for large-scale pretrained language models (PLMs).

377 Jan 2, 2023

Crie tokens de autenticação íntegros e seguros com UToken.

UToken - Tokens seguros. UToken (ou Unhandleable Token) é uma bilioteca criada para ser utilizada na geração de tokens seguros e íntegros, ou seja, nã

0 Nov 29, 2022

Comments

Pretraining Epoch 질문
Checklist

[x] I've searched the project's issues

❓ Question

안녕하세요 저는 현재 친구들과 함께 4096 토큰을 입력받아 요약 태스크를 수행할 수 있는 모델을 만들고 있습니다. 처음엔 빅버드 + 버트 조합으로 해보려고 했는데, 이미 monologg 님께서 만들어주셨더라구요 ㅎㅎ 그래서 롱포머 + 바트 + 페가수스 조합으로 학습을 진행하려 하고 있습니다. pretrained된 KoBart를 기반으로 어텐션을 롱포머로 바꾼 후, 페가수스 task를 수행하는 구조로 되어 있습니다.

현재 13GB의 데이터를 모아서 전처리와 데이터로더 작성, 모델 코드까지는 완료한 상태입니다. 이번 주 내로 학습을 진행하려 하고 있습니다.

저희가 가진 GPU로는 대략 이틀이면 1 에포크를 돌 수 있을 것 같은데, monologg님께서는 KoBirBird 모델 개발 시 에포크를 얼마나 도셨는지 여쭤보고 싶습니다.

아무래도 pretrained 된 모델을 가져다 쓰다보니 에포크를 많이 돌 필요는 없을 것 같은데, 기준점으로 삼고 싶어서요!

말이 길어졌는데 요약하자면, KoBirBird 학습 시 에포크를 얼마나 주셨는지 궁금합니다. 또한, 그 기준은 무엇으로 삼으셨는지도 궁금합니다.
question
opened by KimJaehee0725 2
Specific information about this model.
Checklist

[ x ] I've searched the project's issues

❓ Question

You mentioned "모두의 말뭉치, 한국어 위키, Common Crawl, 뉴스 데이터 등 다양한 데이터로 학습" and I want to know the size of total corpus for pre-training.

Also I want to know the vocab size of this model.

📎 Additional context
question
opened by midannii 2
Fix some minors

Description

코드와 주석 등을 읽다가 보인 작은 오타 등을 수정했습니다

다양한 노하우를 아낌없이 공유해주신 @monologg , @donggyukimc 에게 감사의 말씀드립니다.

이후에는 GPU 환경에서 finetuning을 테스트해 볼 예정입니다 고맙습니다.

Related Issue
chore

opened by sackoh 0

Releases(v1.0.0)

v1.0.0(Nov 8, 2021)

Initial release for KoBigBird - Pretrained BigBird Model for Korean
Source code(tar.gz)
Source code(zip)

Owner

Jangwon Park

GitHub Repository https://huggingface.co/monologg/kobigbird-bert-base

LCG T-TEST USING EUCLIDEAN METHOD

This project has been created for statistical usage, purposing for determining ATL takers and nontakers using LCG ttest and Euclidean Method, especially for internal business case in Telkomsel.

2 Jan 21, 2022

Under the hood working of transformers, fine-tuning GPT-3 models, DeBERTa, vision models, and the start of Metaverse, using a variety of NLP platforms: Hugging Face, OpenAI API, Trax, and AllenNLP

150 Dec 23, 2022

Code for EMNLP 2021 main conference paper "Text AutoAugment: Learning Compositional Augmentation Policy for Text Classification"

105 Jan 03, 2023

A unified tokenization tool for Images, Chinese and English.

ICE Tokenizer Token id [0, 20000) are image tokens. Token id [20000, 20100) are common tokens, mainly punctuations. E.g., icetk[20000] == 'unk', ice

42 Dec 27, 2022

基于GRU网络的句子判断程序/A program based on GRU network for judging sentences

SentencesJudger SentencesJudger 是一个基于GRU神经网络的句子判断程序，基本的功能是判断文章中的某一句话是否为一个优美的句子。 English 如何使用SentencesJudger 确认Python运行环境安装pyTorch与LTP python3 -m pip

8 Mar 24, 2022

Python library for processing Chinese text

SnowNLP: Simplified Chinese Text Processing SnowNLP是一个python写的类库，可以方便的处理中文文本内容，是受到了TextBlob的启发而写的，由于现在大部分的自然语言处理库基本都是针对英文的，于是写了一个方便处理中文的类库，并且和TextBlob

6k Jan 02, 2023

Research code for the paper "Fine-tuning wav2vec2 for speaker recognition"

Fine-tuning wav2vec2 for speaker recognition This is the code used to run the experiments in https://arxiv.org/abs/2109.15053. Detailed logs of each t

103 Dec 26, 2022

Words_And_Phrases - Just a repo for useful words and phrases that might come handy in some scenarios. Feel free to add yours

Words_And_Phrases Just a repo for useful words and phrases that might come handy in some scenarios. Feel free to add yours Abbreviations Abbreviation

1 Feb 01, 2022

[ICLR 2021 Spotlight] Pytorch implementation for "Long-tailed Recognition by Routing Diverse Distribution-Aware Experts."

RIDE: Long-tailed Recognition by Routing Diverse Distribution-Aware Experts. by Xudong Wang, Long Lian, Zhongqi Miao, Ziwei Liu and Stella X. Yu at UC

205 Dec 16, 2022

Kestrel Threat Hunting Language

Kestrel Threat Hunting Language What is Kestrel? Why we need it? How to hunt with XDR support? What is the science behind it? You can find all the ans

201 Dec 16, 2022

Use AutoModelForSeq2SeqLM in Huggingface Transformers to train COMET

Training COMET using seq2seq setting Use AutoModelForSeq2SeqLM in Huggingface Transformers to train COMET. The codes are modified from run_summarizati

9 Dec 17, 2022

Data and evaluation code for the paper WikiNEuRal: Combined Neural and Knowledge-based Silver Data Creation for Multilingual NER (EMNLP 2021).

Data and evaluation code for the paper WikiNEuRal: Combined Neural and Knowledge-based Silver Data Creation for Multilingual NER. @inproceedings{tedes

40 Dec 11, 2022

BERT Attention Analysis

BERT Attention Analysis This repository contains code for What Does BERT Look At? An Analysis of BERT's Attention. It includes code for getting attent

401 Dec 11, 2022

Machine learning models from Singapore's NLP research community

SG-NLP Machine learning models from Singapore's natural language processing (NLP) research community. sgnlp is a Python package that allows you to eas

21 Dec 17, 2022

Code to use Augmented Shapiro Wilks Stopping, as well as code for the paper "Statistically Signifigant Stopping of Neural Network Training"

This codebase is being actively maintained, please create and issue if you have issues using it Basics All data files are included under losses and ea

32 Nov 09, 2021