Dataset: energy_efficiency (regression)
Penalty: 0.1
Seed: 37
Best fitness: -4.381555233296567
Final val loss: 2.81821048
Final penalty: 0.05276537
Model saved to: logs/regression/energy_efficiency/models/best_model_penalty_0.1_seed_37.pth

Final architecture & hyperparameters:
  num_layers: 3
  layer_sizes: [12, 10, 7]
  activations: [3, 1, 4]
  dropout_rates: [0.093, 0.19, 0.021]
  batch_norms: [0, 0, 1]
  learning_rate: 0.0213
  batch_size: 16
  patience: 11
  optimizer_type: 2
  init_type: 3
  l2_penalty: 0.0007

Validation metrics (final):
  mae: 1.217942714691162
  mse: 2.8182106018066406
  rmse: 1.678752692270854
  r2_score: 0.9694486260414124
  mape: 6.801476329565048
  residual_std: 1.6665338277816772
  prediction_std: 9.106804847717285
  target_std: 9.604421615600586
  normalized_mae: 0.03359841971561826
  normalized_rmse: 0.046310419097127006
  num_samples: 115
  target_range: 36.25
  prediction_range: 32.847049713134766

Test metrics (final):
  mae: 1.0692987442016602
  mse: 1.9766829013824463
  rmse: 1.4059455542027388
  r2_score: 0.980952799320221
  mape: 5.336294323205948
  residual_std: 1.4041247367858887
  prediction_std: 9.934138298034668
  target_std: 10.187153816223145
  normalized_mae: 0.02937633789497049
  normalized_rmse: 0.03862487624356744
  num_samples: 116
  target_range: 36.400001525878906
  prediction_range: 32.96519088745117
