Figure shows the top-1 accuracy computed for the hold out test set for a range of library sizes using templates obtained from the USPTO dataset, as compared to the ability to predict full synthetic routes to 1,731 compounds in a series of 41 virtual libraries designed at AstraZeneca. We observed that the accuracy decreases with increasing template library size, where the size of the template library reflects the top N templates in the USPTO dataset. In comparison the average predictive ability of the model increases, reflecting a more task specific measure of model performance. Of note is the increasing difference between the accuracy and overall predictive performance as the library size increases.