Solvability and exploration Furthermore, there is also a relation between the percentage of solved targets and the number of calls, which can be interpreted as higher exploration resulting in more solved routes. However, there also is a slight inverse relationship between the percentage solved and the single-step top-1 accuracy, meaning that the accuracy of the solved routes might not be as precise as routes from higher-accuracy single-step models. However, top-10 is positively related to number of calls and solvability, especially when looking at using optimal validation loss. This indicates that future research interested in multi-step solvability should focus on top-10 accuracy, not top-1 accuracy in single-step models. Finally, we observe that the models trained on the larger USPTO-full model have increased percentage solved, which is expected due to their higher chemical space coverage. But this is also paired with a significant decreased inference speed, even with identical model parameters. In previous research, the original Chemformer has been shown to under-perform on USPTO-50k compared to other models, but outperform on larger, more complex datasets . This can likely be explained with the increase in the percentage of unique predictions from beam search, which might also translate to better solvability for more difficult targets.