Dataset: energy_efficiency (regression)
Penalty: 0.1
Seed: 19
Best fitness: -4.486017592383109
Final val loss: 3.27911747
Final penalty: 0.05137553
Model saved to: logs/regression/energy_efficiency/models/best_model_penalty_0.1_seed_19.pth

Final architecture & hyperparameters:
  num_layers: 3
  layer_sizes: [11, 3, 11]
  activations: [3, 2, 2]
  dropout_rates: [0.033, 0.172, 0.016]
  batch_norms: [0, 0, 1]
  learning_rate: 0.0152
  batch_size: 16
  patience: 28
  optimizer_type: 0
  init_type: 0
  l2_penalty: 0.0001

Validation metrics (final):
  mae: 1.3361748456954956
  mse: 3.2791171073913574
  rmse: 1.8108332632772564
  r2_score: 0.9699166417121887
  mape: 7.274171710014343
  residual_std: 1.7752561569213867
  prediction_std: 10.537402153015137
  target_std: 10.440352439880371
  normalized_mae: 0.03720899452281223
  normalized_rmse: 0.05042699702967232
  num_samples: 115
  target_range: 35.909996032714844
  prediction_range: 27.87824249267578

Test metrics (final):
  mae: 1.4478670358657837
  mse: 3.9164011478424072
  rmse: 1.978989931212993
  r2_score: 0.9649871587753296
  mape: 6.7061446607112885
  residual_std: 1.9737718105316162
  prediction_std: 10.652251243591309
  target_std: 10.576210021972656
  normalized_mae: 0.03941919558699862
  normalized_rmse: 0.05387938894301715
  num_samples: 116
  target_range: 36.72999954223633
  prediction_range: 27.876924514770508
