In this study, we choose to treat the tasks of RP and HILIC chromatography as analogous but fundamentally different tasks. While they share an underlying analytical technique brand, the fundamental interactions that dictate the retention times of molecules are intrinsically different from one another and attempting to predict both at the same time with a single model is akin to pulling the models latent description of molecular graph in two opposite directions at once. However, due to the similarity of the principles and input descriptions of these chromatographic methods they present an excellent use case for the principles of transfer learning. As such, we attempt to transfer the knowledge learned from our RP model to improve learning of HILIC columns and see if it is sufficient overcome the relative dataset paucity.