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61 lines
3.4 KiB
Markdown
61 lines
3.4 KiB
Markdown
<!--Copyright 2020 The HuggingFace Team. All rights reserved.
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Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
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an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
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specific language governing permissions and limitations under the License.
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⚠️ Note that this file is in Markdown but contain specific syntax for our doc-builder (similar to MDX) that may not be
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rendered properly in your Markdown viewer.
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-->
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# BARThez [[barthez]]
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## 개요 [[overview]]
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BARThez 모델은 2020년 10월 23일, Moussa Kamal Eddine, Antoine J.-P. Tixier, Michalis Vazirgiannis에 의해 [BARThez: a Skilled Pretrained French Sequence-to-Sequence Model](https://huggingface.co/papers/2010.12321)에서 제안되었습니다.
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이 논문의 초록:
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*자기지도 학습에 의해 가능해진 귀납적 전이 학습은 자연어 처리(NLP) 분야 전반에 걸쳐 큰 반향을 일으켰으며,
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BERT와 BART와 같은 모델들은 수많은 자연어 이해 작업에서 새로운 최첨단 성과를 기록했습니다. 일부 주목할 만한 예외가 있지만,
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대부분의 사용 가능한 모델과 연구는 영어에 집중되어 있었습니다. 본 연구에서는 BARThez를 소개합니다.
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이는 (우리가 아는 한) 프랑스어를 위한 첫 번째 BART 모델입니다.
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BARThez는 과거 연구에서 얻은 매우 큰 프랑스어 단일 언어 말뭉치로 사전훈련되었으며,
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BART의 변형 방식에 맞게 조정되었습니다.
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CamemBERT 및 FlauBERT와 같은 기존의 BERT 기반 프랑스어 모델과 달리, BARThez는 생성 작업에 특히 적합합니다.
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이는 인코더뿐만 아니라 디코더도 사전훈련되었기 때문입니다.
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우리는 FLUE 벤치마크에서의 판별 작업 외에도 이 논문과 함께 공개하는 새로운 요약 데이터셋인 OrangeSum에서 BARThez를 평가했습니다.
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또한 이미 사전훈련된 다국어 BART의 사전훈련을 BARThez의 말뭉치로 계속 진행하였으며,
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결과적으로 얻어진 모델인 mBARTHez가 기본 BARThez보다 유의미한 성능 향상을 보였고,
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CamemBERT 및 FlauBERT와 동등하거나 이를 능가함을 보였습니다.*
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이 모델은 [moussakam](https://huggingface.co/moussakam)이 기여했습니다. 저자의 코드는 [여기](https://github.com/moussaKam/BARThez)에서 찾을 수 있습니다.
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<Tip>
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BARThez 구현은 🤗 BART와 동일하나, 토큰화에서 차이가 있습니다. 구성 클래스와 그 매개변수에 대한 정보는 [BART 문서](bart)를 참조하십시오.
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BARThez 전용 토크나이저는 아래에 문서화되어 있습니다.
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</Tip>
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## 리소스 [[resources]]
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- BARThez는 🤗 BART와 유사한 방식으로 시퀀스-투-시퀀스 작업에 맞춰 미세 조정될 수 있습니다. 다음을 확인하세요:
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[examples/pytorch/summarization/](https://github.com/huggingface/transformers/tree/main/examples/pytorch/summarization/README.md).
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## BarthezTokenizer [[bartheztokenizer]]
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[[autodoc]] BarthezTokenizer
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## BarthezTokenizerFast [[bartheztokenizerfast]]
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[[autodoc]] BarthezTokenizerFast
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