The climate impact of AI, and NLP research in particular, has become a serious issue given the enormous amount of energy that is increasingly being used for training and running computational models. Consequently, increasing focus is placed on efficient NLP. However, this important initiative lacks simple guidelines that would allow for systematic climate reporting of NLP research. We argue that this deficiency is one of the reasons why very few publications in NLP report key figures that would allow a more thorough examination of environmental impact. As a remedy, we propose a climate performance model card with the primary purpose of being practically usable with only limited information about experiments and the underlying computer hardware. We describe why this step is essential to increase awareness about the environmental impact of NLP research and, thereby, paving the way for more thorough discussions.

翻译：AI,特别是NLP研究的气候影响已成为一个严重问题,因为大量能源正越来越多地用于培训和运行计算模型,因此,越来越重视高效NLP。然而,这一重要举措缺乏简单的准则,无法系统地报告NLP研究的气候报告。我们认为,这一缺陷是为什么国家LP中只有极少数出版物报告关键数字,以便能够更彻底地审查环境影响的原因之一。作为一种补救措施,我们提议使用气候性能模型卡,其主要目的是实际使用有关实验和基本计算机硬件的有限信息。我们说明为什么这一步骤对于提高对NLP研究的环境影响的认识至关重要,从而为更彻底的讨论铺平道路。