model_name: MACE-MPA-0
model_key: mace-mpa-0
model_version: v0.3.9
date_added: '2024-12-09'
date_published: '2024-12-09'
authors:
  - name: Ilyes Batatia
    affiliation: University of Cambridge
    email: ilyes.batatia@ens-paris-saclay.fr
    orcid: https://orcid.org/0000-0001-6915-9851
  - name: David P Kovacs
    affiliation: University of Cambridge
    orcid: https://orcid.org/0000-0002-0854-2635
  - name: Gregor Simm
    affiliation: University of Cambridge
    orcid: https://orcid.org/0000-0001-6815-352X
  - name: Christoph Ortner
    affiliation: University of Cambridge
    orcid: https://orcid.org/0000-0003-1498-8120
  - name: Gabor Csanyi
    affiliation: University of Cambridge
    orcid: https://orcid.org/0000-0002-8180-2034
trained_by:
  - name: Chen Lin
    affiliation: University of Oxford
    github: https://github.com/birdyLinch
    email: will.c.lynch@gmail.com
    orcid: https://orcid.org/0000-0002-0854-2635
  - name: Ilyes Batatia
    affiliation: University of Cambridge
    email: ilyes.batatia@ens-paris-saclay.fr
    orcid: https://orcid.org/0000-0001-6915-9851

repo: https://github.com/ACEsuit/mace
doi: https://doi.org/10.48550/arXiv.2401.00096
paper: https://arxiv.org/abs/2401.00096
pypi: https://pypi.org/project/mace-torch
pr_url: https://github.com/janosh/matbench-discovery/pull/175
# checkpoint URL copied from https://github.com/ACEsuit/mace-foundations/releases/tag/mace_mpa_0
checkpoint_url: https://github.com/ACEsuit/mace-foundations/releases/download/mace_mpa_0/mace-mpa-0-medium.model

license:
  code: MIT
  code_url: https://github.com/ACEsuit/mace/blob/b0fa4ef7c/LICENSE.md
  checkpoint: MIT
  checkpoint_url: https://github.com/ACEsuit/mace-foundations/blob/1ff8786eb/LICENSE

requirements:
  mace-torch: 0.3.9
  torch: 2.5.1
  ase: 3.23.0
  pymatgen: 2024.11.13
  numpy: 1.26.4

openness: OSOD
trained_for_benchmark: false
train_task: S2EFS
test_task: IS2RE-SR
targets: EFS_G
model_type: UIP
model_params: 9_063_204
n_estimators: 1

training_set: [MPtrj, sAlex]
training_cost: missing

hyperparams:
  max_force: 0.05
  max_steps: 500
  ase_optimizer: FIRE
  cell_filter: FrechetCellFilter
  graph_construction_radius: 6.0 # Å
  max_neighbors: .inf

notes:
  Description: |
    MACE is a higher-order equivariant message-passing neural network for fast and accurate force fields.
  Training: Using model pre-trained on MPTraj and Alexandria.

metrics:
  phonons:
    kappa_103:
      κ_SRME: 0.4123
      pred_file: models/mace/mace-mpa-0/2024-11-25-kappa-103-FIRE-dist=0.01-fmax=1e-4-symprec=1e-5.json.gz
      pred_file_url: https://figshare.com/files/52134875
      κ_SRE: 0.2048
  geo_opt:
    pred_file: models/mace/mace-mpa-0/2025-01-30-wbm-IS2RE-FIRE.jsonl.gz
    pred_file_url: https://figshare.com/files/57751036
    struct_col: mace_structure
    symprec=1e-2:
      rmsd: 0.0731 # unitless
      n_sym_ops_mae: 1.8086 # unitless
      symmetry_decrease: 0.0556 # fraction
      symmetry_match: 0.8144 # fraction
      symmetry_increase: 0.1231 # fraction
      n_structures: 256963 # count
      analysis_file: models/mace/mace-mpa-0/2025-01-30-wbm-IS2RE-FIRE-symprec=1e-2-moyo=0.4.2.csv.gz
      analysis_file_url: https://figshare.com/files/53504660
    symprec=1e-5:
      rmsd: 0.0731 # unitless
      n_sym_ops_mae: 1.8808 # unitless
      symmetry_decrease: 0.0328 # fraction
      symmetry_match: 0.7324 # fraction
      symmetry_increase: 0.2305 # fraction
      n_structures: 256963 # count
      analysis_file: models/mace/mace-mpa-0/2025-01-30-wbm-IS2RE-FIRE-symprec=1e-5-moyo=0.4.2.csv.gz
      analysis_file_url: https://figshare.com/files/53504663
  discovery:
    pred_file: models/mace/mace-mpa-0/2024-12-09-wbm-IS2RE-FIRE.csv.gz
    pred_file_url: https://figshare.com/files/52057541
    pred_col: e_form_per_atom_mace
    full_test_set:
      F1: 0.836 # fraction
      DAF: 4.869 # dimensionless
      Precision: 0.836 # fraction
      Recall: 0.836 # fraction
      Accuracy: 0.944 # fraction
      TPR: 0.836 # fraction
      FPR: 0.034 # fraction
      TNR: 0.966 # fraction
      FNR: 0.164 # fraction
      TP: 36844.0 # count
      FP: 7253.0 # count
      TN: 205618.0 # count
      FN: 7248.0 # count
      MAE: 0.028 # eV/atom
      RMSE: 0.073 # eV/atom
      R2: 0.837 # dimensionless
      missing_preds: 4 # count
    most_stable_10k:
      F1: 0.978 # fraction
      DAF: 6.258 # dimensionless
      Precision: 0.957 # fraction
      Recall: 1.0 # fraction
      Accuracy: 0.957 # fraction
      TPR: 1.0 # fraction
      FPR: 1.0 # fraction
      TNR: 0.0 # fraction
      FNR: 0.0 # fraction
      TP: 9566.0 # count
      FP: 434.0 # count
      TN: 0.0 # count
      FN: 0.0 # count
      MAE: 0.032 # eV/atom
      RMSE: 0.105 # eV/atom
      R2: 0.776 # dimensionless
      missing_preds: 0 # count
    unique_prototypes:
      F1: 0.852 # fraction
      DAF: 5.582 # dimensionless
      Precision: 0.853 # fraction
      Recall: 0.851 # fraction
      Accuracy: 0.954 # fraction
      TPR: 0.851 # fraction
      FPR: 0.027 # fraction
      TNR: 0.973 # fraction
      FNR: 0.149 # fraction
      TP: 28417.0 # count
      FP: 4886.0 # count
      TN: 177228.0 # count
      FN: 4957.0 # count
      MAE: 0.028 # eV/atom
      RMSE: 0.073 # eV/atom
      R2: 0.842 # dimensionless
      missing_preds: 2 # count
  diatomics:
    pred_file: models/mace/mace-mpa-0/2025-02-13-diatomics.json.gz
    pred_file_url: https://figshare.com/files/52449437