| Fine-tuned KoR-SRoBERTa for Corporate News Relevance Classification | |
| ⸻ | |
| Overview | |
| 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. | |
| This work is based on the methodology and dataset presented in the following academic paper: | |
| Hyun Ji-won, Lee Jun-il, and Cho Hyun-kwon (2022). | |
| “A Study on Sentiment Classification of Corporate-related News Articles Using KoBERT.” | |
| Accounting Research 47(4), 33–54. | |
| https://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART002873618 | |
| This model card includes proper attribution to the original authors of the base model as required under the CC-BY-SA-4.0 license. | |
| ⸻ | |
| Model Details | |
| • Base model: jhgan/ko-sroberta-multitask | |
| • Architecture: RoBERTa (Korean SRoBERTa variant) | |
| • Task: Relevance classification (1/0) | |
| • Language: Korean | |
| • Domain: Corporate & financial news (Korean) | |
| • Fine-tuning: Conducted on a curated dataset of company-related news headlines and lead sentences derived from the methodology of the 2022 study. | |
| ⸻ | |
| Intended Use | |
| This model is intended for: | |
| • Identifying relevance of firm-specific and finance-related Korean news | |
| • Downstream applications requiring corporate textual analytsis | |
| Not intended for: | |
| • General-purpose Korean analysis without domain adaptation | |
| • High-stakes financial decision-making without human oversight | |
| ⸻ | |
| Licensing | |
| This model is published under CC-BY-SA-4.0, inherited from the base model: | |
| • Original base model: jhgan/ko-sroberta-multitask | |
| • Original license: CC-BY-SA-4.0 | |
| ⸻ | |
| Attribution | |
| If you use this model, please cite both: | |
| 1. Base Model | |
| jhgan/ko-sroberta-multitask | |
| (Original authors as listed on the model card) | |
| 2. Fine-tuned Model / Academic Basis | |
| Hyun Ji-won, Lee Jun-il, and Cho Hyun-kwon (2022). | |
| A Study on Sentiment Classification of Corporate-related News Articles Using KoBERT. | |
| Accounting Research 47(4), 33–54. | |
| https://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART002873618 | |