Skip to content

Model for ALIGNN-FF Forces

  • Description: This is an AI benchmark to evaluate how accurately a machine learning force-field (MLFF) can predict forces using the relaxation trajectories (energy and forces of intermediate steps) of the JARVIS-DFT (dft_3d) dataset, calculated with the OPTB88vdw density functional. The dataset contains different types of chemical formula and atomic structures. Here we use multi-mean absolute error (multi-MAE) to compare MLFFs with respect to DFT (OPT) accuracy.


Reference(s): https://github.com/materialsvirtuallab/m3gnet, https://doi.org/10.1039/D2DD00096B, https://pubs.rsc.org/en/content/articlehtml/2023/dd/d2dd00096b

Model benchmarks

Model nameDataset Accuracy Team name Dataset size Date submitted Notes
alignnff_pretrained_wt10alignn_ff_db0.5782337321792528JARVIS30711101-14-2023CSV, JSON, run.sh, Info
m3gnet_pretrainedalignn_ff_db0.08448789649784973M3GNET30711101-14-2023CSV, JSON, run.sh, Info