program: metalearn/train_caml_lincs.py
method: random
metric:
  goal: minimize
  name: "best_val_mse_diff_20_value"

parameters:
  meta_batch_size:
    values: [1] ## add 4

  batch_size:
    values: [20] ## add 4

  n_layers:
    values: [2,4,6]

  meta_learning_rate:
    values: [0.1,0.5,0.9]

  dropout:
    values: [0, 0.1]

  l1_reg:
    values: [0, 1e-7, 5e-7]

  model_dim:
    values: [512, 1024]

  learning_rate:
    values: [0.003, 0.001, 0.0003, 0.0001]

  weight_decay:
    values: [0.1]

  caml_k:
    values: [1,2,3]

  task_embedding_config:
    values: ["late_concat"]

  use_task_embeddings:
    values: ["true"]

  step:
    values: ["tau"]

  n_iterations:
    values: [50000] ## make lower 1000

  val_interval:
    values: [100]

  batch_norm:
    values: ['false']

  s_learner_h:
    values: ['true']

  impute_y0:
    values: ['false']

  use_random_sampler:
    values: ['true']


