material-demo/configs/potnet.yaml

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YAML

process_dir: processed # directory for torch geometric processed dataset
cache_dir: cache # directory for infinite summation processed files
checkpoint_dir: checkpoint # directory for checkpoints
dataset: dft_3d
# JARVIS dataset: dft_3d
# MP dataset: megnet
target: formation_energy_peratom
# JARVIS dataset entries: formation_energy_peratom, mbj_bandgap, optb88vdw_bandgap, optb88vdw_total_energy, ehull
# MP dataset entries: e_form, gap pbe
# If using custom dataset, please set this to the corresponding entry name, e.g., target
atom_features: cgcnn
epochs: 2
batch_size: 64
num_workers: 8
weight_decay: 0.0
learning_rate: 1e-3
criterion: mse
optimizer: adamw
scheduler: onecycle
pin_memory: False
write_checkpoint: True
write_predictions: True
store_outputs: True
progress: True
log_tensorboard: False
normalize: False # scaling the targets by their mean and std
euclidean: False # disable infinite summation or not
cutoff: 4.0 # local graph cutoff
max_neighbors: 16
infinite_funcs: ["zeta", "zeta", "exp"]
infinite_params: [0.5, 3.0, 3.0] # Coulomb, London dispersion, Pauli
R: 3 # half of the grid length
model:
name: potnet
conv_layers: 3
rbf_min: -4.0
rbf_max: 4.0
potentials: [-0.801, -0.074, 0.145] # coefficients for infinite summations; should be negative, negative, positive w.r.t. their mathematical form
# potentials: [ -0.703, -0.0617, 0.142 ]
# potentials: [-0.816, -0.052, 0.149]
charge_map: False # if including information of periodic table
transformer: False # enable transformer structure for infinite potential summation; only works when euclidean is False