Fig. 3: Comparison of the model’s training performance with and without AtomRef refitting.
From: Cross-functional transferability in foundation machine learning interatomic potentials
a Gradient values recorded every 1/10 of an epoch for various model layers during the first transfer learning epoch, comparing models with and without AtomRef refitting. The layers include “AtomEmb” (atom embedding), “BondEmb” (bond embedding), “AngleEmb” (angle embedding), “AtomConv0_W0” and “AtomConv3_W3” (weights of the two-body atom convolution layers), “BondConv0_W0” and “BondConv2_W3” (weights of the two-body bond convolution layers), and “MLP_Layer0” (weights of the first layer in the multi-layer perceptron). b Energy training history for Method 3, showing the lowest energy MAE of 18.37 meV/atom at the last epoch. c Energy training history for Method 4, showing the lowest energy MAE of 11.82 meV/atom at the last epoch.
