sweep.yaml

program: train.py
method: bayes
metric:
  name: val_acc
  goal: maximize
parameters:
  kernel_size:
    distribution: int_uniform
    min: 2
    max: 16
  batch_size:
    distribution: int_uniform
    min: 16
    max: 44
  learning_rate:
    distribution: uniform
    min: 0.00028
    max: 0.0035
#  use_class_weight:
#    distribution: categorical
#    values: [True, False]

  conv_1_nodes:
    distribution: int_uniform
    min: 3
    max: 16
  pool_1:
    distribution: int_uniform
    min: 1
    max: 4

  conv_2_nodes:
    distribution: int_uniform
    min: 5
    max: 36
  pool_2:
    distribution: int_uniform
    min: 1
    max: 4

  conv_3_nodes:
    distribution: int_uniform
    min: 6
    max: 42
  pool_3:
    distribution: int_uniform
    min: 1
    max: 4

  dense_1_nodes:
    distribution: int_uniform
    min: 12
    max: 256
  dense_2_nodes:
    distribution: int_uniform
    min: 16
    max: 256