Sharif-STR at SemEval-2024 Task 1: Transformer as a Regression Model for Fine-Grained Scoring of Textual Semantic Relations

Seyedeh Fatemeh Ebrahimi, Karim Akhavan Azari, Amirmasoud Iravani, Hadi Alizadeh, Zeinab Taghavi, Hossein Sameti

Abstract: This paper explores semantic textual relatedness (STR) using fine-tuning techniques on the RoBERTa transformer model, focusing on sentence-level STR within Track A (Supervised). The study evaluates the effectiveness of this approach across different languages, with promising results in English and Spanish but encountering challenges in Arabic.