Also observable is with an increasing number of fragments there is an increasing delay in learning while the model adapts to the new type of task. As shown in Figure , the baseline approach starts increasing similarity immediately, however, on average linking two, three, or four fragments first sees a dip in Atorvastatin similarity at approximately 30, 40 and 50 Epochs before an increase, respectively. In the context of using specially curated grammars, datasets or architectures, we think that this initial delay in learning is a worthwhile trade-off and still more efficient overall.