The motivation beyond the inclusion of such long-range corrections comes from many works demonstrating poor description of physisorbed species with RPBE and the enhanced description with D3 corrections. We fine-tuned the eq31M and eq153M models on 15,234 DFT/SPEs generated in the study of adsorbate diffusion on Ag(111) from our base DP 0 model. Details on our train-test-validation split are provided in SI. Given the similar performance and faster inference time of the eq31M model on our test reaction, we ran Pynta with the eq31M model on our 53 reactions. After MLP auditing, we identified 47 valid MLP/TSs. The maximum residual forces (S13) for the OCP model align closely with those from the reaction class approach, suggesting these transition states would succeed during DFT refinement. However, since we have already obtained these transition states, further refinement was not conducted. Figure shows that when compared to the DFT-calculated barriers, the tuned eq31M model achieves great parity with DFT. When investigating the five reactions for which we failed to find an MLP/TS with the eq31M model, we found that many Sella saddle point optimizations failed to converge due to an inability of the model to continuously reduce the forces. Recent work has suggested that fine-tuning of the OCP model on finite-difference data can improve the model's accuracy in calculating Hessians.