Dataset: energy_efficiency (regression)
Penalty: 0.3
Seed: 42
Best fitness: -0.06514053091406823
Final val loss: 0.05701436
Final penalty: 0.05722222
Model saved to: exp_2/logs/regression/energy_efficiency/models/best_model_penalty_0.3_seed_42.pth

Final architecture & hyperparameters:
  num_layers: 4
  layer_sizes: [2, 12, 4, 3]
  activations: [3, 4, 1, 1]
  dropout_rates: [0.173, 0.125, 0.016, 0.016]
  batch_norms: [1, 0, 0, 0]
  learning_rate: 0.0248
  batch_size: 16
  patience: 17
  optimizer_type: 2
  init_type: 2
  l2_penalty: 0.0001

Validation metrics (final):
  mae: 2.5175106525421143
  mse: 11.465692520141602
  rmse: 3.3861028513826334
  r2_score: 0.8878277540206909
  mape: 12.193538248538971
  residual_std: 3.3767168521881104
  prediction_std: 9.401460647583008
  target_std: 10.110147476196289
  normalized_mae: 0.06865313652464766
  normalized_rmse: 0.0923398600549047
  num_samples: 115
  target_range: 36.67000198364258
  prediction_range: 28.221712112426758

Test metrics (final):
  mae: 2.1381242275238037
  mse: 8.184436798095703
  rmse: 2.8608454691044924
  r2_score: 0.9164450168609619
  mape: 11.557814478874207
  residual_std: 2.860804319381714
  prediction_std: 9.137710571289062
  target_std: 9.89710521697998
  normalized_mae: 0.05843466025163657
  normalized_rmse: 0.07818653886783748
  num_samples: 116
  target_range: 36.59000015258789
  prediction_range: 27.30862045288086
