This paper presents our participation under the team name `Finance Wizard' in the FinNLP-AgentScen 2024 shared task #2: Financial Text Summarization. It documents our pipeline approach of fine-tuning a foundation model into a task-specific model for Financial Text Summarization. It involves (1) adapting Llama3 8B, a foundation model, to the Finance domain via continued pre-training, (2) multi-task instruction-tuning to further equip the model with more finance-related capabilities, (3) finally fine-tuning the model into a task-specific `expert'. Our model, FinLlama3\_sum, yielded commendable results, securing the third position in its category with a ROUGE-1 score of 0.521.
Cite
@article{arxiv.2408.03762,
title = {'Finance Wizard' at the FinLLM Challenge Task: Financial Text Summarization},
author = {Meisin Lee and Soon Lay-Ki},
journal= {arXiv preprint arXiv:2408.03762},
year = {2024}
}