To estimate the coverage of the chemical space during transfer learning, we computed the Fréchet ChemNet Distance (FCD), a distance metric to evaluate the similarity between two populations of molecules based on chemical structure and bioactivity . An FCD value of 0 indicates that the compared molecular spaces are identical, while higher values indicate greater dissimilarity. The FCD curves evolved continuously as a function of the number of training epochs (Fig. ). This observation indicates that chemical language models are able to sample the chemical space between a source and a target space in a continuous fashion although molecules are discrete entities.