Dataset: energy_efficiency (regression)
Penalty: 0.3
Seed: 7
Best fitness: -4.8468014341987455
Final val loss: 3.86478638
Final penalty: 0.27912659
Model saved to: logs/regression/energy_efficiency/models/best_model_penalty_0.3_seed_7.pth

Final architecture & hyperparameters:
  num_layers: 4
  layer_sizes: [10, 3, 7, 5]
  activations: [3, 4, 1, 1]
  dropout_rates: [0.084, 0.188, 0.223, 0.052]
  batch_norms: [0, 0, 1, 1]
  learning_rate: 0.0287
  batch_size: 16
  patience: 24
  optimizer_type: 2
  init_type: 2
  l2_penalty: 0.0001

Validation metrics (final):
  mae: 1.5474132299423218
  mse: 3.864786386489868
  rmse: 1.965905996351267
  r2_score: 0.9649143218994141
  mape: 9.300722181797028
  residual_std: 1.9614945650100708
  prediction_std: 9.808958053588867
  target_std: 10.495369911193848
  normalized_mae: 0.042175337339198406
  normalized_rmse: 0.05358151718552783
  num_samples: 115
  target_range: 36.69000244140625
  prediction_range: 26.6186580657959

Test metrics (final):
  mae: 1.728938341140747
  mse: 4.7947282791137695
  rmse: 2.1896867993194298
  r2_score: 0.9490223526954651
  mape: 11.089420318603516
  residual_std: 2.1124138832092285
  prediction_std: 8.927440643310547
  target_std: 9.698221206665039
  normalized_mae: 0.04745919095957594
  normalized_rmse: 0.0601066917643789
  num_samples: 116
  target_range: 36.43000030517578
  prediction_range: 26.485998153686523
