program: metalearn/train_caml.py
method: random
metric:
  goal: maximize
  name: "best_Mean Val rate @ 0.998_value"

parameters:
  meta_batch_size:
    values: [1]

  n_layers:
    values: [2,4,6]

  dropout:
    values: [0, 0.1]

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

  model_dim:
    values: [128, 256]

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

  weight_decay:
    values: [0.005]

  caml_k:
    values: [1,10,50]

  deterministic_sample:
    values: ["false"]

  all_tasks_baseline:
    values: ["true"]

  task_sample_weighting:
    values: ["enable"]

  all_tasks_baseline_eval_prob:
    max: 0.5
    min: 0.05

  s_learner_h:
    values: ["true"]

  task_embedding_config:
    values: ["late_concat"]

  use_task_embeddings:
    values: ["true"]

  step:
    values: ["y0"]

  n_iterations:
    values: [10000]

  val_interval:
    values: [50]
