Considering that the sizes of reactants and TSs in the experimental set are approximately twice as large as those in the training sets, the model demonstrates satisfactory extrapolation capability after fine-tuning. Specifically, when no additional features are used, the pretrained model predicts the log 10 (k rel ) values to be close to zero for nearly all reactions, whereas the fine-tuned model shows noticeable enhancement in capturing the trend. We expect the model to improve further as more diverse and larger reactions become available for training. It is also worth highlighting that the model was trained with the calculated data, which inherently carry some degrees of error. We previously found that the COSMO-RS method has a ∆G ‡ rel MAE/RMSE of around 0.4 kcal/mol (0.28 in log 10 k rel units) on these reactions. This implies that only a part of the prediction errors are attributed to the model's performance, and the rest stems from the intrinsic calculation errors within the training data.