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79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>파인튜닝 완료!</span></h1> <div class="flex space-x-1 absolute z-10 right-0 top-0" style=""><a href="https://discuss.huggingface.co/t/chapter-3-questions" target="_blank"><img alt="Ask a Question" class="!m-0" src="https://img.shields.io/badge/Ask%20a%20question-ffcb4c.svg?logo=data:image/svg+xml;base64,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"></a>  </div> <p data-svelte-h="svelte-dqibe8">정말 광범위한 내용을 다뤘습니다! 처음 두 챕터에서 모델과 토크나이저에 대해 배웠고, 이제 최신 모범 사례를 사용하여 여러분의 데이터 세트로 파인튜닝하는 방법을 알게 되었습니다. 요약하자면, 이 챕터에서는 다음을 배웠습니다.</p> <ul data-svelte-h="svelte-2jlfqx"><li><a href="https://huggingface.co/datasets" rel="nofollow">Hub</a>의 데이터 세트와 최신 데이터 처리 기법에 대해 학습했습니다.</li> <li>동적 패딩과 데이터 콜레이터 사용을 포함하여 데이터 세트를 효율적으로 로드하고 전처리하는 방법을 배웠습니다.</li> <li>최신 기능을 포함한 고수준 <code>Trainer</code> API를 사용하여 파인튜닝과 평가를 구현했습니다.</li> <li>PyTorch를 사용하여 완전한 커스텀 훈련 루프를 처음부터 구현했습니다.</li> <li>🤗 Accelerate를 사용하여 훈련 코드가 다중 GPU 또는 TPU에서 원활하게 작동하도록 했습니다.</li> <li>혼합 정밀도 훈련과 그래디언트 누적과 같은 최신 최적화 기법을 적용했습니다.</li></ul> <blockquote class="tip"><p data-svelte-h="svelte-w80fqd">🎉 <strong>축하합니다!</strong> 트랜스포머 모델 파인튜닝의 기초를 마스터했습니다. 이제 실제 ML 프로젝트에 도전할 준비가 되었습니다!</p> <p data-svelte-h="svelte-1o5fdrm">📖 <strong>계속 학습하기</strong>: 지식을 더 깊이 쌓기 위해 다음 리소스를 탐색해보세요.</p> <ul data-svelte-h="svelte-ciozur"><li>특정 NLP 작업을 위한 <a href="https://huggingface.co/docs/transformers/main/en/tasks/sequence_classification" rel="nofollow">🤗 Transformers 작업 가이드</a></li> <li>포괄적인 노트북을 위한 <a href="https://huggingface.co/docs/transformers/main/en/notebooks" rel="nofollow">🤗 Transformers 예제</a></li></ul> <p data-svelte-h="svelte-imjxfc">🚀 <strong>다음 단계</strong></p> <ul data-svelte-h="svelte-peb42e"><li>배운 기법을 사용하여 자신만의 데이터 세트로 파인튜닝을 시도해보세요.</li> <li><a href="https://huggingface.co/models" rel="nofollow">Hugging Face Hub</a>에서 사용 가능한 다양한 모델 아키텍처를 실험해보세요.</li> <li><a href="https://discuss.huggingface.co/" rel="nofollow">Hugging Face 커뮤니티</a>에 참여하여 프로젝트를 공유하고 도움을 받으세요.</li></ul></blockquote> <p data-svelte-h="svelte-4cmln8">이것은 🤗 Transformers와의 여정의 시작일 뿐입니다. 다음 챕터에서는 모델과 토크나이저를 커뮤니티와 공유하고 계속 성장하는 사전훈련된 모델 생태계에 기여하는 방법을 탐색할 것입니다.</p> <p data-svelte-h="svelte-cpskwu">여기서 여러분이 익힌 데이터 전처리, 훈련 구성, 평가, 최적화와 같은 기법들은 모든 기계학습 프로젝트의 기초입니다. 텍스트 분류, 개체 인식, 질의 응답 또는 어떤 NLP 작업을 하든 상관없이, 이러한 기법들이 큰 도움이 될 것입니다.</p> <blockquote class="tip"><p data-svelte-h="svelte-4289nw">💡 <strong>성공을 위한 전문가 팁</strong></p> <ul data-svelte-h="svelte-ftddo3"><li>커스텀 훈련 루프를 구현하기 전에 항상 <code>Trainer</code> API를 사용한 강력한 기준선부터 시작하세요.</li> <li>더 나은 출발점을 🤗 Hub을 사용하여 위해 자신의 작업과 유사한 사전훈련된 모델을 찾으세요.</li> <li>적절한 평가 지표로 훈련을 모니터링하고 체크포인트 저장을 잊지 마세요.</li> <li>커뮤니티를 활용하세요 - 모델과 데이터 세트를 공유하여 다른 사람들을 돕고 자신의 작업에 대한 피드백을 받으세요.</li></ul></blockquote> <a class="!text-gray-400 !no-underline text-sm flex items-center not-prose mt-4" href="https://github.com/huggingface/course/blob/main/chapters/ko/chapter3/6.mdx" target="_blank"><svg class="mr-1" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M31,16l-7,7l-1.41-1.41L28.17,16l-5.58-5.59L24,9l7,7z"></path><path d="M1,16l7-7l1.41,1.41L3.83,16l5.58,5.59L8,23l-7-7z"></path><path d="M12.419,25.484L17.639,6.552l1.932,0.518L14.351,26.002z"></path></svg> <span 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