The parity plots and error histograms of the best pre-trained and fine-tuned models are provided in Figure for the ∆∆G ‡ solv predictions on the pre-training set reaction split. The corresponding plots for all models on the ∆∆H ‡ solv predictions and for the solvent split are presented in Supporting Information Figure rare for neutral reactions, and thus, it is possible that the COSMO-RS method overpredicted the magnitude of the target values on some of these extreme data points. a. Error vs. number of data points for each reaction type solv MAE for the 10 most frequent reaction types. The reaction type is specified by the bond changes. For example, +C-H,-C-H,-C-C indicates that one carbon-hydrogen bond is formed, one carbonhydrogen bond is broken, and one carbon-carbon bond is broken. Outliers are not shown in the plots. types have fewer than 5 reactions matching each type and are mostly unique. In Figure , the ∆∆G ‡ solv errors of reaction types are plotted against the number of the corresponding reactions in each type. The error distribution appears larger for the reaction types with fewer than 20 reactions, but the mean error values remain similar across all ranges. The test set error distributions of the 10 most frequent reaction types are also examined in Figure . The examples of the reactions corresponding to the 10 types are provided in the Supporting Information Table . The results show that the +C=C,+C-H,-C-C,-C-H type exhibits the highest mean error of 0.88 kcal/mol. However, the error is still close to the overall ∆∆G ‡ solv MAE of the fine-tuned model. It appears that a few outliers contribute to the higher errors of the +C=C,+C-H,-C-C,-C-H type (see Table ), but it is not obvious which chemical functionalities are associated with higher errors in these reactions. Table reveals that the reactions within the same type are also diverse and unique, making it challenge to establish a clear correlation between reaction type and prediction error. This observation aligns with the findings of Grambow et al., who also did not see a clear correlation between reaction type and test set error in their study on predicting activation barriers.