Easy Language Model Pretraining leveraging Huggingface's Transformers and Datasets

Related tags

Text Data & NLPlassl
Overview

Easy Language Model Pretraining leveraging Huggingface's Transformers and Datasets

What is LASSL • How to Use

License Issues

What is LASSL

LASSL은 LAnguage Semi-Supervised Learning의 약자로, 데이터만 있다면 누구나 쉽게 자신만의 언어모델을 가질 수 있도록 Huggingface의 Transformers, Datasets 라이브러리를 이용해 언어 모델 사전학습을 제공합니다.

Environment setting

아래 명령어를 통해 필요한 패키지를 설치하거나,

pip3 install -r requirements.txt

poetry를 이용하여 환경설정을 할 수 있습니다.

# poetry 설치
curl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | python -
# poetry dependencies 환경 설정
poetry install

How to Use

1. Train Tokenizer

python3 train_tokenizer.py \
    --corpora_dir $CORPORA_DIR \
    --corpus_type $CORPUS_TYPE \
    --sampling_ratio $SAMPLING_RATIO \
    --model_type $MODEL_TYPE \
    --vocab_size $VOCAB_SIZE \
    --min_frequency $MIN_FREQUENCY
# poetry 이용
poetry run python3 train_tokenizer.py \
    --corpora_dir $CORPORA_DIR \
    --corpus_type $CORPUS_TYPE \
    --sampling_ratio $SAMPLING_RATIO \
    --model_type $MODEL_TYPE \
    --vocab_size $VOCAB_SIZE \
    --min_frequency $MIN_FREQUENCY

2. Serialize Corpora

python3 serialize_corpora.py \
    --model_type $MODEL_TYPE \
    --tokenizer_dir $TOKENIZER_DIR \
    --corpora_dir $CORPORA_DIR \
    --corpus_type $CORPUS_TYPE \
    --max_length $MAX_LENGTH \
    --num_proc $NUM_PROC
# poetry 이용
poetry run python3 serialize_corpora.py \
    --model_type $MODEL_TYPE \
    --tokenizer_dir $TOKENIZER_DIR \
    --corpora_dir $CORPORA_DIR \
    --corpus_type $CORPUS_TYPE \
    --max_length $MAX_LENGTH \
    --num_proc $NUM_PROC

3. Pretrain Language Model

python3 pretrain_language_model.py --config_path $CONFIG_PATH
# poetry 이용
poetry run python3 pretrain_language_model.py --config_path $CONFIG_PATH
# TPU를 사용할 때는 아래 명령어를 사용합니다. (poetry 환경은 PyTorch XLA를 기본으로 제공하지 않습니다.)
python3 xla_spawn.py --num_cores $NUM_CORES pretrain_language_model.py --config_path $CONFIG_PATH

Contributors

김보섭 류민호 류인제 박장원 김형석
image1 image2 image3 image4 image5
Github Github Github Github Github

Acknowledgements

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

Comments
  • Ready to release v0.1.0

    Ready to release v0.1.0

    Summary

    기본적으로 전체적인 틀은 잡혀있는 사항 v0.1.0을 release하기에 앞서 다음의 내용에 대해서 논의

    • serialize_corpora.py와 train_tokenizer.py가 지원하는 model_type에 이격이 존재
      • serialie_corpora.py: roberta, gpt2, albert
      • train_tokenizer.py: bert-uncased, bert-cased, gpt2, roberta, albert, electra
    • README.md
    help wanted 
    opened by seopbo 10
  • Refactor codes relevant to pretrain

    Refactor codes relevant to pretrain

    • 학습하고자하는 plm 별로 DataCollatorFor{MODEL}을 추가함.
    • pretrain_language_model.py에서 model_type_to_collator를 정의하여, model_type 별로 collator를 가져옴.
      • config 파일의 collator 항목에서 collator를 위한 args (e.g. mlm_probability)를 가져옴.
    • pretrain_language_model.py에서 eval_dataset을 사용하기위한 코드추가
      • config 파일의 data 항목에서 eval_dataset을 설정하기위한 test_size arg를 가져옴.
    • 그 의 isort, black 돌림.

    Refs: #30

    opened by seopbo 6
  • Add UL2 Language Modeling

    Add UL2 Language Modeling

    슬랙에서도 소개하긴 했는데 Universal Language Learning Paradigm 논문에 소개된 Mixture of Denoisers 를 활용한 목적함수가 기존 Span corruption, MLM, CLM 보다 전반적으로 좋다고 합니다. 저도 마침 회사에서 활용해 볼 생각이 있어서 lassl에 collator 및 processor를 구현하려고 하는데 어떻게 생각하시나요??

    opened by DaehanKim 4
  • Support training BART

    Support training BART

    Is your feature request related to a problem? Please describe. BART processor, collator 추가하기

    Describe the solution you'd like text_infilling 방법을 collator로 추가한다.

    enhancement 
    opened by bzantium 4
  • Add keep_in_memory option in load_dataset

    Add keep_in_memory option in load_dataset

    Is your feature request related to a problem? Please describe.

    • TPU VM에서 학습하는 과정에서 캐쉬로 인해 메모리가 충분함에도 disk 용량이 꽉차는 이슈가 발생함

    Describe the solution you'd like

    • load_dataset 단계에서 keep_in_memory 옵션을 추가하여 해결
    • Serialize과정이완료된 데이터는 disk에 저장되므로, train 단계에서는 필요가 없고 tokenizer, serialize과정에서만 추가
    opened by iron-ij 2
  • KoRobertaSmall training

    KoRobertaSmall training

    TODO

    Training tokenizer

    poetry run python3 train_tokenizer.py --corpora_dir corpora \
--corpus_type sent_text \
--model_type roberta \
--vocab_size 51200 \
--min_frequency 2

    Serializing corpora

    poetry run python3 serialize_corpora.py --model_type roberta \
--tokenizer_dir tokenizers/roberta \
--corpora_dir corpora \
--corpus_type sent_text \
--max_length 512 \
--num_proc 96 \
--batch_size 1000 \
--writer_batch_size 1000

    ref:

    • https://github.com/huggingface/blog/blob/master/notebooks/13_pytorch_xla.ipynb
    help wanted 
    opened by seopbo 2
  • Support corpus_type

    Support corpus_type

    • "docu_text", "docu_json", "sent_text", "sent_json"으로 corpus_type을 정의함.
      • 위에 대응하여 load_corpora 함수를 수정함.
      • "sent_text"에 대응되는 loading scripts의 이름과 class 명을 수정함
      • serialize_corpora.py에서 corpus_type에 대응되게 argument parser를 수정함.
      • train_tokenizer.py에서 corpus_type에 대응되게 refactoring을 수행함.
      • model_name -> model_type으로 수정함.

    Refs: #23

    enhancement 
    opened by seopbo 2
  • Support setting arguments of pretraining by a config file

    Support setting arguments of pretraining by a config file

    • config 파일하나로 pretrain_language_model.py에 실행에 필요한 arguments를 전달함.
    • nested dict 처리를 위한 Omegaconf library 추가
    • CONFIG_MAPPING을 활용하여 class 생성자 호출

    Refs: #16

    opened by seopbo 2
  • argument setting

    argument setting

    To Do

    • https://github.com/lassl/lassl/blob/c507a547e5e22a3bc89bf65e448712783e688211/pretrain_language_model.py#L47
    • set ModelArguments from config.json file
    • set TrainingArguments from config.json file
    enhancement 
    opened by alxiom 2
  • Single-stage Electra collator refactored

    Single-stage Electra collator refactored

    src/lassl/collators.py

    1. Simplified the main operation (all-in-tensor)
    2. change the function name pad_for_token_type_ids -> _token_type_ids_with_pad for clarity
    documentation 
    opened by Doohae 1
  • Add config files #82

    Add config files #82

    Add config files for following:

    • bert-small.yaml
    • albert-small.yaml
    • gpt2-small.yaml
    • roberta-small.yaml Also add readme file for brief explanation of config files in general For issue #82 @seopbo
    opened by Doohae 1
  • Can you give some examples or benchmarks, that use this pretrain framework make downstream task better ?

    Can you give some examples or benchmarks, that use this pretrain framework make downstream task better ?

    I think if you can give a evidence that use this framework will improve the performance in some self build corpus in some downstream task, will make this project more attractive.

    opened by svjack 1
  • Change default save format to parquet

    Change default save format to parquet

    TODO

    • Currently, serialize_corpora.py saves encoded dataset with save_to_disk.
    • In this issue, we replace calling save_to_disk with calling `to_parquet``

    cc: @Doohae @DaehanKim

    enhancement 
    opened by seopbo 0
Releases(v1.0.0)

  • v1.0.0(Nov 2, 2022)

    What's Changed

    • [mixed] refactor: Refactor for v1.0.0 by @seopbo in https://github.com/lassl/lassl/pull/102
    • Currently, lassl suports to train bert, albert, roberta, gpt2, bart, t5, ul2
    • In next, lassl will suport to train electra. Moreover train_universal_tokenizer.py will be added to lassl.
      • train_universal_tokenizer.py will train tokenizer used to train all types of model which are supported by lassl.

    Full Changelog: https://github.com/lassl/lassl/compare/v0.2.0...v1.0.0

    Source code(tar.gz)
    Source code(zip)

  • v0.2.0(Sep 22, 2022)

    What's Changed

    • Support training BART by @seopbo in https://github.com/lassl/lassl/pull/81
    • Support training T5 model by @DaehanKim in https://github.com/lassl/lassl/pull/87
    • Add config files #82 by @Doohae in https://github.com/lassl/lassl/pull/88
    • Support Electra pretrain by @Doohae in https://github.com/lassl/lassl/pull/91
    • Add UL2 Language Modeling by @DaehanKim in https://github.com/lassl/lassl/pull/98

    New Contributors

    • @DaehanKim made their first contribution in https://github.com/lassl/lassl/pull/87

    Full Changelog: https://github.com/lassl/lassl/compare/v0.1.4...v0.2.0

    Source code(tar.gz)
    Source code(zip)

  • v0.1.3(Mar 18, 2022)

    Summary

    • Refactor lassl for packaging modules to library
    • Add a function of dataset blending

    What's Changed

    • Add dataset blender by @hyunwoongko in https://github.com/lassl/lassl/pull/73
    • Remove poetry dependencies by @seopbo in https://github.com/lassl/lassl/pull/76

    New Contributors

    • @hyunwoongko made their first contribution in https://github.com/lassl/lassl/pull/73

    Full Changelog: https://github.com/lassl/lassl/compare/v0.1.2...v0.1.3

    Source code(tar.gz)
    Source code(zip)

  • v0.1.2(Dec 30, 2021)

    Summary

    • Fix bugs in src/collators.py

    What's Changed

    • [python] fix: Fix importing a invalid module by @seopbo in https://github.com/lassl/lassl/pull/72

    Full Changelog: https://github.com/lassl/lassl/compare/v0.1.1...v0.1.2

    Source code(tar.gz)
    Source code(zip)

  • v0.1.1(Dec 20, 2021)

    Summary

    • Update README.md
      • Support README.md in english.
      • Support README_ko.md in korean.
    • Fix bugs of training GPT2
    • Add examples configs for gpu, tpu environments.

    What's Changed

    • [docs] fix: Change a license by @seopbo in https://github.com/lassl/lassl/pull/64
    • [etc] docs: Add English version of README by @bzantium in https://github.com/lassl/lassl/pull/66
    • Add example configs for gpu, tpu by @seopbo in https://github.com/lassl/lassl/pull/65
    • [python] fix: debug GPT2 processor and collator by @bzantium in https://github.com/lassl/lassl/pull/69
    • Update README.md by @bzantium in https://github.com/lassl/lassl/pull/70

    Full Changelog: https://github.com/lassl/lassl/compare/v0.1.0...v0.1.1

    Source code(tar.gz)
    Source code(zip)

  • v0.1.0(Dec 15, 2021)

    Summary

    • First release

    What's Changed

    • Feature/#2 by @seopbo in https://github.com/lassl/lassl/pull/4
    • feat: TPU compatibility by @monologg in https://github.com/lassl/lassl/pull/8
    • Feature/#3 GPT2Preprocessor 추가 by @iron-ij in https://github.com/lassl/lassl/pull/10
    • [docs] chore: Add authors by @seopbo in https://github.com/lassl/lassl/pull/13
    • Feature/#9 ALBERT용 Processor, Collator 추가 by @bzantium in https://github.com/lassl/lassl/pull/14
    • [python] feat: Save tokenizer by @seopbo in https://github.com/lassl/lassl/pull/19
    • [python] mixed: Support sentence per line type doc by @seopbo in https://github.com/lassl/lassl/pull/20
    • Support setting arguments of pretraining by a config file by @seopbo in https://github.com/lassl/lassl/pull/22
    • Support corpus_type by @seopbo in https://github.com/lassl/lassl/pull/25
    • Support adding additional special tokens by @seopbo in https://github.com/lassl/lassl/pull/26
    • [python] feat: Add bert processor by @bzantium in https://github.com/lassl/lassl/pull/29
    • Refactor codes relevant to pretrain by @seopbo in https://github.com/lassl/lassl/pull/31
    • Update issue templates by @seopbo in https://github.com/lassl/lassl/pull/34
    • [python] fix: sampling_ratio 조건 추가하기 by @bzantium in https://github.com/lassl/lassl/pull/36
    • [python] chore: Update dependencies by @seopbo in https://github.com/lassl/lassl/pull/38
    • [python] fix: Fix a buffer in processing.py by @seopbo in https://github.com/lassl/lassl/pull/41
    • [mixed] fix: xla_spawn 변경, config 추가 및 주석 by @bzantium in https://github.com/lassl/lassl/pull/44
    • [python] feat: add keep_in_memory option in serialize_corpora by @iron-ij in https://github.com/lassl/lassl/pull/43
    • [chore] fix: Fix a requirements.txt by @seopbo in https://github.com/lassl/lassl/pull/46
    • [python] fix: sampling할 때 중복샘플링 옵션 제거 by @bzantium in https://github.com/lassl/lassl/pull/48
    • [etc] docs: README 추가 by @bzantium in https://github.com/lassl/lassl/pull/39
    • [etc] docs: README에 LASSL 약자소개 추가하기 by @bzantium in https://github.com/lassl/lassl/pull/52
    • [python] chore: Update dependencies by @seopbo in https://github.com/lassl/lassl/pull/54
    • [python] fix: GPT2 Collator CollatorForLM 상속하기 by @bzantium in https://github.com/lassl/lassl/pull/57
    • [etc] docs: Add additional information to doc by @seopbo in https://github.com/lassl/lassl/pull/59

    New Contributors

    • @seopbo made their first contribution in https://github.com/lassl/lassl/pull/4
    • @monologg made their first contribution in https://github.com/lassl/lassl/pull/8
    • @iron-ij made their first contribution in https://github.com/lassl/lassl/pull/10
    • @bzantium made their first contribution in https://github.com/lassl/lassl/pull/14

    Full Changelog: https://github.com/lassl/lassl/commits/v0.1.0

    Source code(tar.gz)
    Source code(zip)
Owner
LASSL: LAnguage Self-Supervised Learning
LASSL: LAnguage Self-Supervised Learning
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