Dataset: energy_efficiency (regression)
Penalty: 0.0
Seed: 42
Best fitness: -0.045900050550699234
Final val loss: 0.07244211
Final penalty: 0.00000000
Model saved to: exp_2/logs/regression/energy_efficiency/models/best_model_penalty_0.0_seed_42.pth

Final architecture & hyperparameters:
  num_layers: 4
  layer_sizes: [12, 8, 8, 11]
  activations: [4, 4, 1, 1]
  dropout_rates: [0.12, 0.47, 0.37, 0.188]
  batch_norms: [1, 1, 1, 1]
  learning_rate: 0.0296
  batch_size: 16
  patience: 26
  optimizer_type: 2
  init_type: 0
  l2_penalty: 0.0052

Validation metrics (final):
  mae: 3.584577798843384
  mse: 25.43871307373047
  rmse: 5.043680508689113
  r2_score: 0.7511256337165833
  mape: 13.955698907375336
  residual_std: 4.215910911560059
  prediction_std: 7.331510543823242
  target_std: 10.110147476196289
  normalized_mae: 0.09775232083277115
  normalized_rmse: 0.13754241166768827
  num_samples: 115
  target_range: 36.67000198364258
  prediction_range: 22.060571670532227

Test metrics (final):
  mae: 3.176309108734131
  mse: 20.748186111450195
  rmse: 4.555017685086436
  r2_score: 0.7881815433502197
  mape: 13.521404564380646
  residual_std: 3.7765839099884033
  prediction_std: 7.21762228012085
  target_std: 9.89710521697998
  normalized_mae: 0.0868081195815322
  normalized_rmse: 0.12448804772044458
  num_samples: 116
  target_range: 36.59000015258789
  prediction_range: 21.318614959716797
