We evaluate the generalizability of our model when applied to unseen data by training our Siamese CNN on all of the data available from the BindingDB Docked Congeneric Series dataset and evaluating on the datasets provided by Mobley et al., Wang et al. Jiménez-Luna et al. . We evaluate performance when including the two-permutations of up to seven ligands from the external dataset in the finetuning dataset, see Figure . Identical test sets are used for both no-shot and few-shot learning for each congeneric series. The test set only includes pairs of ligands where at least one ligand in the pair was not utilized for the seven external ligands finetuning. We train and evaluate on both orderings of pairs of ligands.