In addition to training models from scratch on tmQM wB97MV, GemNet-T 26 models were fine-tuned on all of tmQM wB97MV and the neutral subset of it, using the publicly available checkpoints from OC20 3 as the starting point. Compared to the models trained from scratch, the fine-tuned models show improvements in performance, with a 35.8% lower MAE on the full dataset, and a 14.2% reduction on the neutral subset. Parity plots of the test set predictions for the fine-tuned GemNet-T 26 models can be seen in Figures and. Figure shows a model fine-tuned on 80% of all of tmQM wB97MV, which has drastically lower MAE and higher EwT compared to an equivalent model trained from scratch, seen in Figure . This improvement in model performance (a MAE of 4.85 meV/atom, an R