model_name: DPA3-v1-MPtrj model_key: dpa3-v1-mptrj model_version: v0.1 # 2025-01-10 date_added: '2025-01-10' date_published: '2025-01-10' authors: - name: Duo Zhang affiliation: AI for Science Institute, Beijing orcid: https://orcid.org/0000-0001-9591-2659 - name: Anyang Peng affiliation: AI for Science Institute, Beijing orcid: https://orcid.org/0000-0002-0630-2187 - name: Chun Cai affiliation: AI for Science Institute, Beijing orcid: https://orcid.org/0000-0001-6242-0439 - name: Linfeng Zhang affiliation: AI for Science Institute, Beijing; DP Technology email: linfeng.zhang.zlf@gmail.com corresponding: true - name: Han Wang affiliation: Beijing Institute of Applied Physics and Computational Mathematics (IAPCM) email: wang_han@iapcm.ac.cn corresponding: true trained_by: - name: Duo Zhang affiliation: AI for Science Institute, Beijing orcid: https://orcid.org/0000-0001-9591-2659 repo: https://github.com/deepmodeling/deepmd-kit/tree/dpa3-alpha url: https://github.com/deepmodeling/deepmd-kit/tree/dpa3-alpha doi: https://github.com/deepmodeling/deepmd-kit/tree/dpa3-alpha # to be released soon paper: https://github.com/deepmodeling/deepmd-kit/tree/dpa3-alpha # to be released soon pr_url: https://github.com/janosh/matbench-discovery/pull/192 # checkpoints reported in https://github.com/deepmodeling/deepmd-kit/discussions/4682 checkpoint_url: https://bohrium-api.dp.tech/ds-dl/matbench-submit-DPA3mptraj-ictz-v2.zip license: code: LGPL-3.0 code_url: https://github.com/deepmodeling/deepmd-kit/blob/70bc6d89/LICENSE checkpoint: LGPL-3.0 checkpoint_url: https://github.com/deepmodeling/deepmd-kit/blob/70bc6d89/LICENSE openness: OSOD train_task: S2EFS test_task: IS2RE-SR targets: EFS_G model_type: UIP model_params: 3_374_647 n_estimators: 1 trained_for_benchmark: true status: superseded superseded_by: dpa3-v2-mptrj hyperparams: max_force: 0.05 max_steps: 500 ase_optimizer: FIRE cell_filter: ExpCellFilter n_layers: 16 e_rcut: 6.0 a_rcut: 4.0 n_dim: 128 e_dim: 64 a_dim: 32 optimizer: Adam round1: loss: MSE loss_weights: energy: 0.2 -> 20 force: 100 -> 20 virial: 0.02 -> 1 initial_learning_rate: 0.001 learning_rate_schedule: ExpLR - start_lr=0.001, decay_steps=5000, stop_lr=0.00001 training_steps: 2_000_000 round2: loss: Huber loss_weights: energy: 15 force: 1 virial: 2.5 initial_learning_rate: 0.0002 learning_rate_schedule: ExpLR - start_lr=0.0002, decay_steps=5000, stop_lr=0.00001 training_steps: 2_000_000 batch_size: 64 # 16 (gpus) * 4 (batch per gpu) = 64 (total batch size) epochs: 160 # round1 80 + round2 80 graph_construction_radius: 6.0 # Å max_neighbors: 120 # from https://github.com/deepmodeling/deepmd-kit/discussions/4682#discussioncomment-12836651 requirements: torch: 2.3.1 torch-geometric: 2.5.2 ase: 3.23.0 pymatgen: 2024.6.10 numpy: 1.26.4 training_set: [MPtrj] training_cost: missing notes: Description: | DPA3 is an advanced interatomic potential leveraging the message passing architecture, implemented within the DeePMD-kit framework, available on [GitHub](https://github.com/deepmodeling/deepmd-kit/tree/dpa3-alpha). Designed as a large atomic model (LAM), DPA3 is tailored to integrate and simultaneously train on datasets from various disciplines, encompassing diverse chemical and materials systems across different research domains. Its model design ensures exceptional fitting accuracy and robust generalization both within and beyond the training domain. Furthermore, DPA3 maintains energy conservation and respects the physical symmetries of the potential energy surface, making it a dependable tool for a wide range of scientific applications. metrics: phonons: kappa_103: κ_SRME: 0.964 pred_file: models/deepmd/dpa3-v1-mptrj/2025-01-10-kappa-103-FIRE-dist=0.01-fmax=1e-4-symprec=1e-5.json.gz pred_file_url: https://figshare.com/files/52134860 geo_opt: pred_file: models/deepmd/dpa3-v1-mptrj/2025-01-10-wbm-geo-opt.jsonl.gz struct_col: dpa2_structure pred_file_url: https://figshare.com/files/57754501 symprec=1e-5: analysis_file: models/deepmd/dpa3-v1-mptrj/2025-01-10-wbm-geo-opt-symprec=1e-5-moyo=0.3.3.csv.gz analysis_file_url: https://figshare.com/files/52291967 # deleted from Figshare (model superseded by dpa3-v2) rmsd: 0.0172 # unitless n_sym_ops_mae: 2.1671 # unitless symmetry_decrease: 0.0804 # fraction symmetry_match: 0.7128 # fraction symmetry_increase: 0.2001 # fraction n_structures: 256955 # count symprec=1e-2: analysis_file: models/deepmd/dpa3-v1-mptrj/2025-01-10-wbm-geo-opt-symprec=1e-2-moyo=0.3.3.csv.gz analysis_file_url: https://figshare.com/files/52291970 # deleted from Figshare (model superseded by dpa3-v2) rmsd: 0.0172 # unitless n_sym_ops_mae: 1.992 # unitless symmetry_decrease: 0.0609 # fraction symmetry_match: 0.8034 # fraction symmetry_increase: 0.1282 # fraction n_structures: 256955 # count discovery: pred_file: models/deepmd/dpa3-v1-mptrj/2025-01-10-wbm-IS2RE.csv.gz pred_file_url: https://figshare.com/files/52057529 pred_col: e_form_per_atom_dp full_test_set: F1: 0.757 # fraction DAF: 4.13 # dimensionless Precision: 0.709 # fraction Recall: 0.812 # fraction Accuracy: 0.911 # fraction TPR: 0.812 # fraction FPR: 0.069 # fraction TNR: 0.931 # fraction FNR: 0.188 # fraction TP: 35812.0 # count FP: 14718.0 # count TN: 198153.0 # count FN: 8280.0 # count MAE: 0.04 # eV/atom RMSE: 0.082 # eV/atom R2: 0.793 # dimensionless missing_preds: 14 # count most_stable_10k: F1: 0.971 # fraction DAF: 6.174 # dimensionless Precision: 0.944 # fraction Recall: 1.0 # fraction Accuracy: 0.944 # fraction TPR: 1.0 # fraction FPR: 1.0 # fraction TNR: 0.0 # fraction FNR: 0.0 # fraction TP: 9438.0 # count FP: 562.0 # count TN: 0.0 # count FN: 0.0 # count MAE: 0.038 # eV/atom RMSE: 0.084 # eV/atom R2: 0.849 # dimensionless missing_preds: 0 # count unique_prototypes: F1: 0.765 # fraction DAF: 4.654 # dimensionless Precision: 0.711 # fraction Recall: 0.828 # fraction Accuracy: 0.921 # fraction TPR: 0.828 # fraction FPR: 0.062 # fraction TNR: 0.938 # fraction FNR: 0.172 # fraction TP: 27630.0 # count FP: 11205.0 # count TN: 170909.0 # count FN: 5744.0 # count MAE: 0.042 # eV/atom RMSE: 0.083 # eV/atom R2: 0.798 # dimensionless missing_preds: 11 # count