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@@ -4,7 +4,7 @@ Fine-tuned KoR-SRoBERTa for Corporate News Relevance Classification
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  Overview
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- This model is a fine-tuned version of the base model jhgan/ko-sroberta-multitask, adapted specifically for sentiment classification of Korean corporate-related news articles. The goal of this model is to improve performance in distinguishing positive, neutral, and negative sentiments within firm-specific news contexts, which often contain domain-specific financial language.
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  This work is based on the methodology and dataset presented in the following academic paper:
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  Overview
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+ This model is a fine-tuned version of the base model jhgan/ko-sroberta-multitask, adapted specifically for relevance classification of Korean corporate-related news articles. The goal of this model is to improve performance in distinguishing significant news within firm-specific news contexts, which often contain domain-specific financial language.
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  This work is based on the methodology and dataset presented in the following academic paper:
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