  From an environmental standpoint, there are a few crucial aspects of training
a neural network that have a major impact on the quantity of carbon that it
emits. These factors include: the location of the server used for training and
the energy grid that it uses, the length of the training procedure, and even
the make and model of hardware on which the training takes place. In order to
approximate these emissions, we present our Machine Learning Emissions
Calculator, a tool for our community to better understand the environmental
impact of training ML models. We accompany this tool with an explanation of the
factors cited above, as well as concrete actions that individual practitioners
and organizations can take to mitigate their carbon emissions.
