Cross-validation scheme for training the model was one-compound-out . This approach involves excluding one compound from each fold so that the fold has all the combinations except those containing that compound. As 32 compounds constituted the combinations (or training data), a total of 32 folds were performed within this scheme. The cross validation of the nested hyperparameter tuning in DNN split each 32 folds into three smaller folds.