Digital Library

1. 1. Fine-tuning BERT-based NLP Models for Sentiment Analysis of Korean Reviews: Optimizing the sequence length
   Sunga Hwang, Seyeon Park, Beakcheol Jang, Vol. 25, No. 4, pp. 47-56, Aug. 2024
   10.7472/jksii.2024.25.4.47
   Keywords: BERT, hyperparameter fine-tuning, input sequence length, topic modeling, sentiment analysis, Korean review analysis
2. 2. Optimizing Language Models through Dataset-Specific Post-Training: A Focus on Financial Sentiment Analysis
   Hui Do Jung, Jae Heon Kim, Beakcheol Jang, Vol. 25, No. 1, pp. 57-67, Feb. 2024
   10.7472/jksii.2024.25.1.57
   Keywords: BERT, FinBERT, Financial Sentiment Analysis, post-training, Pre-training Dataset
3. 3. FinBERT Fine-Tuning for Sentiment Analysis: Exploring the Effectiveness of Datasets and Hyperparameters
   Jae Heon Kim, Hui Do Jung, Beakcheol Jang, Vol. 24, No. 4, pp. 127-135, Aug. 2023
   10.7472/jksii.2023.24.4.127
   Keywords: FinBERT, Financial Sentiment Analysis, Fine-Tuning hyperparameters