The trained ChemMLM models were assessed on the reaction test dataset. The model used KL divergence loss, determined in Eq. 2 between predicted tokens and the true masked tokens to backpropagate the model parameters and validate the models. However, this assessment could only conclude on the model predictability of a masked token, which is usually part of a molecule. The purpose for the model testing was to assess whether the model could infer an entire missing molecule, rather than a masked token. Moreover, since the model predicts the missing molecule for the incomplete reactions following the LHS and RHS species insufficient scenarios, as discussed in the "Missing molecule prediction" section, the ChemMLM models were tested, with respect to its LHS and RHS predictability.