BabelBot at AraFinNLP2024: Fine-tuning T5 for Multi-dialect Intent Detection with Synthetic Data and Model Ensembling
Murhaf Fares, Samia Touileb · 2024
This paper presents our results for the Arabic Financial NLP (AraFinNLP) shared task at the Second Arabic Natural Language Processing Conference (ArabicNLP 2024).We participated in the first sub-task, Multi-dialect Intent Detection, which focused on cross-dialect intent detection in the banking domain.Our approach involved fine-tuning an encoder-only T5 model, generating synthetic data, and model ensembling.Additionally, we conducted an indepth analysis of the dataset, addressing annotation errors and problematic translations.Our model was ranked third in the shared task with an F1-score of 0.871.