config_tabular.yml

---
seed: 100
experiment_name: bank_spd
dataset: bank
protected: age
metric: spd
modelpath: bank_age.pt
objective:
  sharpness: 500.
  epsilon: 0.05
models:
  - default
  - ROC
  - EqOdds
  - CalibEqOdds
  - random
  - layerwiseOpt
  - adversarial
  - mitigating
CalibEqOdds:
  cost_constraint: fpr
random:
  num_trials: 101
  stddev: 0.1
  margin: 0.01
layerwiseOpt:
  max_sparsity: 100000
  num_layers: 5
  n_calls: 20
  margin: 0.01
fairBO:
  hyperparameters:
    T0:
      start: 100
      end: 501
      step: 100
      log_scale: false
    alpha:
      start: -6
      end: -0.9
      step: 1
      log_scale: true
    lr:
      start: -6
      end: -3.9
      step: 1
      log_scale: true
    beta1:
      start: -3
      end: -0.9
      step: 1
      log_scale: true
    beta2:
      start: -3
      end: -0.9
      step: 1
      log_scale: true
  initial_budget: 10
  total_budget: 30
  margin: 0.01
adversarial:
  num_deep: 3
  lr: 0.0001
  epochs: 32
  critic_steps: 201
  batch_size: 64
  actor_steps: 301
  sharpness: 300.
  margin: 0.02
mitigating:
  epochs: 24
  lr: 0.0001
  critic_steps: 201
  batch_size: 64
  actor_steps: 201
  alpha: 0.8
  margin: 0.01