Building on the above understanding regarding Stage 2 failures, we now investigate four reactions which failed during the DFT-refinement in Stage 3. Hypothesizing that suboptimal model fitting of the DFT data could be a possible cause, we first used hyperparameter optimization to improve the model performance. Specifically, in addition to exploring different sizes of the fitting and embedding nets, we created two different models with varying values of key hyperparameters (Tables ). Although this approach reduced the mean squared error for forces on the training data from 0.018 eV/Å to 0.013 eV/Å, the hyperparamteroptimized model still failed during the DFT-refinement stage for all four reactions. Thus, this suggests that similar to the above total model analysis, data bias could also be a contributing factor to these failures.