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# bespin-global/klue-sroberta-base-continue-learning-by-mnr
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This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
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<!--- Describe your model here -->
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# bespin-global/klue-sroberta-base-continue-learning-by-mnr
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ํด๋น ๋ชจ๋ธ์ KLUE/NLI, KLUE/STS ๋ฐ์ดํฐ์
์ ํ์ฉํ์์ผ๋ฉฐ, sentence-transformers์ ๊ณต์ ๋ฌธ์ ๋ด ์๊ฐ๋ [continue-learning](https://github.com/UKPLab/sentence-transformers/blob/master/examples/training/sts/training_stsbenchmark_continue_training.py) ๋ฐฉ๋ฒ์ ํตํด ์๋์ ๊ฐ์ด ํ์ต๋์์ต๋๋ค.
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1. NLI ๋ฐ์ดํฐ์
์ ํตํด nagative sampling ํ, MultipleNegativeRankingLoss๋ฅผ ํ์ฉํ์ฌ 1์ฐจ NLI training ์ํ
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2. 1์์ ํ์ต์๋ฃ ๋ ๋ชจ๋ธ์ STS ๋ฐ์ดํฐ์
์ ํตํด, CosineSimilarityLoss๋ฅผ ํ์ฉํ์ฌ 2์ฐจ STS training ์ํ
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ํ์ต์ ๊ดํ ์์ธํ ๋ด์ฉ์ [Blog](https://velog.io/@jaehyeong/Basic-NLP-sentence-transformers-%EB%9D%BC%EC%9D%B4%EB%B8%8C%EB%9F%AC%EB%A6%AC%EB%A5%BC-%ED%99%9C%EC%9A%A9%ED%95%9C-SBERT-%ED%95%99%EC%8A%B5-%EB%B0%A9%EB%B2%95#225-continue-learning-by-sts)์ [Colab ์ค์ต ์ฝ๋](https://colab.research.google.com/drive/1uDt3o_Nv2cTiVbIAIUkst_eOSD37Wkmf)๋ฅผ ์ฐธ๊ณ ํด์ฃผ์ธ์.
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---
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This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.
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<!--- Describe your model here -->
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