Work

Arabic Mini-ClimateGPT : A Climate Change and Sustainability Tailored Arabic LLM

Year: 2023

Type: conference-paper

Abstract: Climate change is one of the most significant challenges we face together as a society.Creating awareness and educating policy makers the wide-ranging impact of climate change is an essential step towards a sustainable future.Recently, Large Language Models (LLMs) like ChatGPT and Bard have shown impressive conversational abilities and excel in a wide variety of NLP tasks.While these models are close-source, recently alternative open-source LLMs such as Stanford Alpaca and Vicuna have shown promising results.However, these open-source models are not specifically tailored for climate related domain specific information and also struggle to generate meaningful responses in other languages such as, Arabic.To this end, we propose a light-weight Arabic Mini-ClimateGPT that is built on an open-source LLM and is specifically fine-tuned on a conversational-style instruction tuning curated Arabic dataset Clima500-Instruct with over 500k instructions about climate change and sustainability.Further, our model also utilizes a vector embedding based retrieval mechanism during inference.We validate our proposed model through quantitative and qualitative evaluations on climate-related queries.Our model surpasses the baseline LLM in 88.3% of cases during ChatGPT-based evaluation.Furthermore, our human expert evaluation reveals an 81.6% preference for our model's responses over multiple popular open-source models.Our open-source demos, models and curated instruction sets are available here https:// github.com/mbzuai-oryx/ClimateGPT.Recently, large language models (LLMs) such

Source: Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP)

DOI: 10.18653/v1/2023.findings-emnlp.941