config_simclr.yaml

batch_size: 256 #64 #256 for simclr and sup_simclr
epochs: 15
eval_every_n_epochs: 1
fine_tune_from: None
log_every_n_steps: 50
gpu: cuda:3 #:0

optim:
  optimizer: Adam
  lr: 0.00001
  weight_decay: 1e-6

model: 
  atom_fea_len: 64
  h_fea_len: 128
  n_conv: 3
  n_h: 1

dataset:
  root_dir: pre_train_mp #pre-train-- supervison is-metal
  max_num_nbr: 12
  radius: 8
  dmin: 0
  step: 0.2
  random_seed: 666

dataloader:
  val_ratio: 0.05
  num_workers: 0

loss:
  #embed_size: 128 #origianlly given 64 for BT-loss should be similar as batch size in sup-BT
  #lambd: 0.0051 # for BT-loss
  batch_size: 256 #64 for BT-loss #256 for sup_simclr and simclr
  temperature: 0.1 #for simclr 
  #use_cosine_similarity: True #for simclr unsupervised loss
  contrast_mode: 'all' #required for simclr and sup_simclr
  base_temperature: 0.1 #required for simclr and sup_simclr