Dataset: energy_efficiency (regression)
Penalty: 0.2
Seed: 73
Best fitness: -0.8124461445304008
Final val loss: 7.54897972
Final penalty: 0.10202201
Model saved to: logs/regression/energy_efficiency/models/best_model_penalty_0.2_seed_73.pth

Final architecture & hyperparameters:
  num_layers: 3
  layer_sizes: [12, 5, 7]
  activations: [3, 1, 4]
  dropout_rates: [0.008, 0.453, 0.001]
  batch_norms: [0, 0, 1]
  learning_rate: 0.0272
  batch_size: 16
  patience: 26
  optimizer_type: 1
  init_type: 0
  l2_penalty: 0.0

Validation metrics (final):
  mae: 2.284757614135742
  mse: 7.54897928237915
  rmse: 2.7475405879402675
  r2_score: 0.9168389439582825
  mape: 11.615336686372757
  residual_std: 2.6868550777435303
  prediction_std: 7.261002063751221
  target_std: 9.52761459350586
  normalized_mae: 0.06240801901242585
  normalized_rmse: 0.07504890855323816
  num_samples: 115
  target_range: 36.61000061035156
  prediction_range: 26.703449249267578

Test metrics (final):
  mae: 1.9529201984405518
  mse: 5.681227207183838
  rmse: 2.383532506005286
  r2_score: 0.9365489482879639
  mape: 9.167025983333588
  residual_std: 2.3000807762145996
  prediction_std: 7.52901554107666
  target_std: 9.462409019470215
  normalized_mae: 0.0552296426677334
  normalized_rmse: 0.06740759233209719
  num_samples: 116
  target_range: 35.36000061035156
  prediction_range: 26.969341278076172
