/
config_seml.yaml
91 lines (77 loc) · 1.49 KB
/
config_seml.yaml
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seml:
executable: 'train_seml.py'
name: "gemnet"
output_dir: "slurm_logs"
project_root_dir: "."
slurm:
experiments_per_job: 1
sbatch_options:
gres: 'gpu:1'
mem: 40G
cpus-per-task: 2
time: 07-00:00
partition: gpu_all
fixed:
num_spherical: 7
num_radial: 6
num_blocks: 4
emb_size_atom: 128
emb_size_edge: 128
emb_size_trip: 64
emb_size_quad: 32
emb_size_rbf: 16
emb_size_cbf: 16
emb_size_sbf: 32
emb_size_bil_trip: 64
emb_size_bil_quad: 32
num_before_skip: 1
num_after_skip: 1
num_concat: 1
num_atom: 2
cutoff: 5.0
int_cutoff: 10.0
mve: False
loss: "rmse"
forces_coupled: False
envelope_exponent: 5
extensive: True
rho_force: 0.999
ema_decay: 0.999
weight_decay: 0.000002
learning_rate: 0.001
decay_steps: 4500000
decay_rate: 0.01
staircase: False
decay_patience: 5
decay_factor: 0.5
decay_cooldown: 5
agc: False
grad_clip_max: 10.0
restart: null
tfseed: 1234
data_seed: 42
scale_file: "scaling_factors.json"
comment: "GemNet"
output_init: "HeOrthogonal"
logdir: "logs"
dataset: "data/coll_v1.2_train.npz"
val_dataset: "data/coll_v1.2_val.npz"
num_train: 0 # derived from dataset
num_val: 0 # derived from dataset
patience: 5
evaluation_interval: 7500
save_interval: 7500
warmup_steps: 3750
batch_size: 32
num_steps: 1500000
grid:
triplets_only:
type: choice
options:
- True
- False
direct_forces:
type: choice
options:
- True
- False