program: ./scripts/train.py
name: informer-btcusdt-5m-gmadl-sweep
project: wne-masters-thesis-testing
command:
  - ${env}
  - ${interpreter}
  - ${program}
  - "./configs/experiments/informer-btcusdt-5m-gmadl.yaml"
  - "--patience"
  - "15"
method: random
metric:
  goal: minimize
  name: val_loss
parameters:
  past_window:
    distribution: int_uniform
    min: 20
    max: 120
  batch_size:
    values: [64, 128, 256]
  model:
    parameters:
      name:
        value: "Informer"
      d_model:
        values: [256, 512, 1024]
      d_fully_connected:
        values: [256, 512, 1024]
      n_attention_heads:
        values: [1, 2, 4, 6]
      dropout:
        values: [0.05, 0.1, 0.2, 0.3]
      n_encoder_layers:
        values: [1, 2, 3]
      n_decoder_layers: 
        values: [1, 2, 3]
      learning_rate:
        values: [0.001, 0.0005, 0.0001]
      optimizer:
        value: "Adam"