Avstract-A code clone is a code snippet identical or similar to another in the source code. The presence of code clones causes the spread of bugs, which means that efficient code clone detection and appropriate refactoring are necessary. Code clone detection using large language models (in short, LLMs) is more accurate than conventional tools that do not use LLMs for code clones with low syntactic similarity. However, even for LLM-based clone detection tools, detecting such code clones is still difficult, and there is room for improvement. In this study, we improved the accuracy of LLM-based code clone detection through fine-tuning using FEMPDataset. The results showed that our fine-tuning improved the accuracy of code clone detection.