Training Config¶
Full config can be downloaded here.
n_epochs: <NUMBER OF EPOCHS>
seed: 1
ckpt_interval: 500
patience: null
data_parallel: True
weight_average: null
data:
directory: models/
experiment: apax
# Use either data_path for a single dataset file
# or the lines below to specify separate files
data_path: <PATH>
#train_data_path: <PATH>
#val_data_path: <PATH>
#test_data_path: <PATH>
dataset:
processing: cached
shuffle_buffer_size: 1000
n_train: 1000
n_valid: 100
batch_size: 4
valid_batch_size: 100
shift_method: "per_element_regression_shift"
shift_options: {"energy_regularisation": 1.0}
scale_method: "per_element_force_rms_scale"
scale_options: {}
pos_unit: Ang
energy_unit: eV
model:
name: gmnn
basis:
name: bessel
n_basis: 16
r_max: 5.0
ensemble: null
# if you would like to use emirical repulsion corrections
# with the following example.
# empirical_corrections:
# - name: exponential
# r_max: 1.5
# if you would like to train model ensembles, this can be
# achieved with the following example.
# Hint: loss type hase to be changed to a probabilistic loss like nll or crps
# ensemble:
# kind: shallow
# n_members: N
n_radial: 5
n_contr: 8
nn: [256, 256]
calc_stress: false
w_init: lecun
b_init: zeros
descriptor_dtype: fp32
readout_dtype: fp32
scale_shift_dtype: fp64
emb_init: uniform
use_ntk: false
loss:
- name: energy
loss_type: mse
weight: 1.0
atoms_exponent: 1
- name: forces
loss_type: mse
weight: 4.0
atoms_exponent: 1
metrics:
- name: energy
reductions:
- mae
- name: forces
reductions:
- mae
- mse
optimizer:
name: adam
kwargs: {}
emb_lr: 0.001
nn_lr: 0.001
scale_lr: 0.0001
shift_lr: 0.003
zbl_lr: 0.0001
schedule:
name: cyclic_cosine
period: 40
decay_factor: 0.93
callbacks:
- name: csv
transfer_learning:
# The options below are used for transfer learning
base_model_checkpoint: null
reset_layers: []
freeze_layers: []
progress_bar:
disable_epoch_pbar: false
disable_batch_pbar: true
Molecular Dynamics Config¶
Full config can be downloaded here.
ensemble:
name: nvt
dt: 0.5 # fs time step
temperature_schedule:
name: constant
T0: <T> # K
thermostat_chain:
chain_length: 3
chain_steps: 2
sy_steps: 3
tau: 100
duration: <DURATION> # fs
n_inner: 500 # compiled inner steps
sampling_rate: 10 # dump interval
buffer_size: 2500
dr_threshold: 0.5 # Neighborlist skin
extra_capacity: 0
sim_dir: md
initial_structure: <INITIAL_STRUCTURE>
load_momenta: false
traj_name: md.h5
restart: true
checkpoint_interval: 50_000
disable_pbar: false