To test how the replicates of the embeddings perform on real chemical properties we employed our pre-trained transfer learning model on 1 H-NMR and 13 C-NMR, see section on the transfer learning model. If it is true that the replicates are getting closer to the true embedding space, they should then perform successively more accurately on such properties as the replicates incorporate further neighborhood layers into the prediction. Using a neighborhood depth of one and the 'non-linear 2' model for replicating the embedding space based on neighborhood composition, Figures and for 1 H-NMR and 13 C-NMR confirm this effect revealing how the embedding space works to make finer predictions based on layered chemical composition.