SubmissionNumber#=%=#30 FinalPaperTitle#=%=#HausaNLP at SemEval-2024 Task 1: Textual Relatedness Analysis for Semantic Representation of Sentences ShortPaperTitle#=%=# NumberOfPages#=%=#5 CopyrightSigned#=%=#Saheed Abdullahi Salahudeen JobTitle#==# Organization#==# Abstract#==#Semantic Text Relatedness (STR), a measure of meaning similarity between text elements, has become a key focus in the field of Natural Language Processing (NLP). We describe SemEval-2024 task 1 on Semantic Textual Relatedness featuring three tracks: supervised learning, unsupervised learning and cross-lingual learning across African and Asian languages including Afrikaans, Algerian Arabic, Amharic, Hausa, Hindi, Indonesian, Kinyarwanda, Marathi, Moroccan Arabic, Modern Standard Arabic, Punjabi, Spanish, and Telugu. Our goal is to analyse the semantic representation of sentences textual relatedness trained on mBert, all-MiniLM-L6-v2 and Bert-Based-uncased. The effectiveness of these models is evaluated using the Spearman Correlation metric, which assesses the strength of the relationship between paired data. The finding reveals the viability of transformer models in multilingual STR tasks. Author{1}{Firstname}#=%=#Saheed Abdullahi Author{1}{Lastname}#=%=#Salahudeen Author{1}{Username}#=%=#saseedorf Author{1}{Email}#=%=#a.salahudeen@kasu.edu.ng Author{1}{Affiliation}#=%=#Kaduna State University Author{2}{Firstname}#=%=#Falalu Ibrahim Author{2}{Lastname}#=%=#Lawan Author{2}{Username}#=%=#falalu Author{2}{Email}#=%=#falalu.ng@gmail.com Author{2}{Affiliation}#=%=#Kaduna State University Author{3}{Firstname}#=%=#Yusuf Author{3}{Lastname}#=%=#Aliyu Author{3}{Username}#=%=#yusuf003 Author{3}{Email}#=%=#yaliyu003@gmail.com Author{3}{Affiliation}#=%=#Universiti Teknologi Petronas Author{4}{Firstname}#=%=#Amina Imam Author{4}{Lastname}#=%=#Abubakar Author{4}{Username}#=%=#meenahimam Author{4}{Email}#=%=#amina.imam@uniabuja.edu.ng Author{4}{Affiliation}#=%=#University of Abuja Author{5}{Firstname}#=%=#Lukman Jibril Author{5}{Lastname}#=%=#Aliyu Author{5}{Username}#=%=#lukmanaj Author{5}{Email}#=%=#lukman.j.aliyu@gmail.com Author{5}{Affiliation}#=%=#HausaNLP Author{6}{Firstname}#=%=#Nur Bala Author{6}{Lastname}#=%=#Rabiu Author{6}{Email}#=%=#nurbashir2008@gmail.com Author{6}{Affiliation}#=%=#HausaNLP Author{7}{Firstname}#=%=#Mahmoud Said Author{7}{Lastname}#=%=#Ahmad Author{7}{Email}#=%=#msahmad.cs@futb.edu.ng Author{7}{Affiliation}#=%=#HausaNLP Author{8}{Firstname}#=%=#Idi Mohammed Author{8}{Email}#=%=#mohammed@aust.edu.ng Author{8}{Affiliation}#=%=#African University of Science and Technology Author{9}{Firstname}#=%=#Aliyu Rabiu Author{9}{Lastname}#=%=#Shuaibu Author{9}{Username}#=%=#aliyurszain Author{9}{Email}#=%=#aliyursringim@gmail.com Author{9}{Affiliation}#=%=#Nile University of Nigeria Author{10}{Firstname}#=%=#Alamin Magaga Author{10}{Lastname}#=%=#Musa Author{10}{Username}#=%=#magaga Author{10}{Email}#=%=#alaminmusamagaga@gmail.com Author{10}{Affiliation}#=%=#HausaNLP Author{11}{Firstname}#=%=#Auwal Shehu Author{11}{Lastname}#=%=#Ali Author{11}{Email}#=%=#asali.cs@buk.edu.ng Author{11}{Affiliation}#=%=#Bayero University Kano Author{12}{Firstname}#=%=#Zedong Author{12}{Lastname}#=%=#Nie Author{12}{Email}#=%=#zd.nie@siat.ac.cn Author{12}{Affiliation}#=%=#Shenzhen Institute of Advanced Technology ========== èéáğö