2024/10/07 by Bibiána Lajčinová, Lajčinová, Bibiána, Patrik Valábek +3
Business, Management and Accounting · #FinTech, Crowdfunding, Digital Finance
paper · pdf · doi:10.48550/arxiv.2410.04925
This study evaluates the application of large language models (LLMs) for intent classification within a chatbot with predetermined responses designed for banking industry websites. Specifically, the research examines the effectiveness of fine-tuning SlovakBERT compared to employing multilingual generative models, such as Llama 8b instruct and Gemma 7b instruct, in both their pre-trained and fine-tuned versions. The findings indicate that SlovakBERT outperforms the other models in terms of in-scope accuracy and out-of-scope false positive rate, establishing it as the benchmark for this application.