Impact of data size. For GPT2, increasing the training dataset size from 80k to 1M led to substantial improvements in both consistency and accuracy for forward reaction prediction and retrosynthesis. The increase in overall consistency aligns with the improvement in accuracy, indicating that the larger dataset enhances the model's ability to make correct predictions for both SMILES and IUPAC inputs. However, the gap between overall consistency and false consistency widened, suggesting that the additional data results in limited improvement in false consistency.