JunaidMuzamal/hausa-sentiment-xlmr

Cross-lingual fine-tuning of XLM-R for Hausa-English code-switched sentiment analysis (ACM TALLIP 2026) # Cross-Lingual Fine-Tuning of XLM-R for Sentiment Analysis in Hausa-English Code-Switched Dialogues Reference implementation for the ACM **TALLIP** article: > **Cross-Lingual Fine-Tuning of XLM-R for Sentiment Analysis in Hausa-English Code-Switched Dialogues** > Osei Wusu Brempong Jnr, Junaid Hussain Muzamal, Liu Zhaobin. > *ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP)*, 2026. > DOI: **10.1145/3830015** This repository fine-tunes **XLM-R** for three-class sentiment classification (negative / neutral / positive) on **Hausa-English-Pidgin code-switched** social-media text. It implements a code-switch-aware pipeline with back-translation + Ghanaian Pidgin injection, self-attention pooling, an auxiliary token-level language-identification objective, adapter-based parameter-efficient fine-tuning, a fairness-aware loss, a full evaluation suite, and ONNX export for deployment. > **License & intended use.** The **code** is released under > **CC BY 4.0** and is intended > for **non-commercial, academic research use**. © 2026 Copyright is held by > the owner/author(s). The **datasets** this repo downloads (NaijaSenti / > AfriSenti) are licensed **CC BY-NC-SA 4.0** (non-commercial). Please cite the > ACM TALLIP article above and the dataset papers (see Citation). --- ## Table of contents - Requirements & installation - Datasets: where and how to download - Preprocessing - Quickstart (offline smoke run) - Reproducing the paper - Ablations, adapters & fairness - Inference & deployment - Repository layout - How each paper component maps to code - Testing - Citation - License --- ## Requirements & installation - Python **3.9+** - PyTorch **2.0+** (CPU is fine for the smoke run; a GPU is recommended for full training) ```bash # 1. Clone git clone github.com cd hausa-sentiment-xlmr # 2. (Recommended) create a virtual environment python -m venv .venv && source .venv/bin/activate # …