the accuracy (percentage of correct predictions) would be two out of five, i.e. 20 %. We furthermore report the top-1 accuracy to identify the correct products given the reactants, i.e. the fraction of test data points where the reaction labeled "1" had a higher raw predicted value than all reactions labeled "0" originating from the same reactants and template. For the example above, if the raw scores from the model (prior to applying a threshold to create binary labels from the continuous predictions) were [0.8 0.6 0.1 0.4 0.6], then the model scored the correct products at rank 1 for reactants1, and at rank 2 for reactants2, leading to a top-1-accuracy of 50%.