snoels/FinGEITje-sft

Citation text from the card

@inproceedings{10.1145/3677052.3698628,
author = {Noels, Sander and De Blaere, Jorne and De Bie, Tijl},
title = {A Dutch Financial Large Language Model},
year = {2024},
isbn = {9798400710810},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3677052.3698628},
doi = {10.1145/3677052.3698628},
abstract = {This paper presents FinGEITje, the first Dutch financial Large Language Model (LLM) specifically designed and optimized for various financial tasks. Together with the model, we release a specialized Dutch financial instruction tuning dataset with over 140,000 samples, constructed employing an automated translation and data processing method. The open-source data construction method is provided, facilitating the creation of financial instruction datasets in different languages. To evaluate model performance, the study introduces the first Dutch financial evaluation benchmark, along with an automated evaluation method that utilizes an LLM as an independent evaluator, reducing manual intervention in performance evaluation. The experimental results highlight the superior performance of FinGEITje across five critical Dutch and English financial tasks.},
booktitle = {Proceedings of the 5th ACM International Conference on AI in Finance},
pages = {283–291},
numpages = {9},
keywords = {Financial Large Language Model, Instruction Tuning., Natural Language Processing},
location = {Brooklyn, NY, USA},
series = {ICAIF '24}
}

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