Improving this description is the aim of the on-the-fly training and comparing the correlations before and after on-the-fly training there is a clear improvement. Not only are all outliers eliminated, but also the errors across the test set are significantly reduced, resulting in notably lower MAEs. Considering the α polymorph was not among the initial structures in the on-the-fly training, the improved accuracy for these structures is particularly impressive. For comparison, if we do include an on-the-fly simulation initiated from the α polymorph, the resulting model achieves an MAE of just 0.5 kJ mol -1 on the same structures (Figure ). The possibility to further improve the accuracy with further sampling is also evident in the subtle trend of larger errors at higher energies, which suggests the sampling at these energies could be insufficient. However, this is not unexpected considering the on-the-fly training trajectories were shorter than the trajectories the test structures were sampled from, and moreover, may have sampled different regions due to the different energy models.