Dataset: energy_efficiency (regression)
Penalty: 0.2
Seed: 7
Best fitness: -0.9242242946141007
Final val loss: 1.46458761
Final penalty: 0.10416667
Model saved to: logs/regression/energy_efficiency/models/best_model_penalty_0.2_seed_7.pth

Final architecture & hyperparameters:
  num_layers: 3
  layer_sizes: [12, 10, 5]
  activations: [3, 4, 1]
  dropout_rates: [0.016, 0.233, 0.052]
  batch_norms: [0, 0, 1]
  learning_rate: 0.0252
  batch_size: 16
  patience: 20
  optimizer_type: 2
  init_type: 2
  l2_penalty: 0.0001

Validation metrics (final):
  mae: 0.979439914226532
  mse: 1.4645875692367554
  rmse: 1.2102014581204055
  r2_score: 0.9867040514945984
  mape: 5.264821276068687
  residual_std: 1.2070801258087158
  prediction_std: 10.266569137573242
  target_std: 10.495369911193848
  normalized_mae: 0.02669500815080873
  normalized_rmse: 0.032984501978518294
  num_samples: 115
  target_range: 36.69000244140625
  prediction_range: 32.24115753173828

Test metrics (final):
  mae: 0.9078441262245178
  mse: 1.3158628940582275
  rmse: 1.1471106721054545
  r2_score: 0.9860097169876099
  mape: 5.561754107475281
  residual_std: 1.1471065282821655
  prediction_std: 9.54926586151123
  target_std: 9.698221206665039
  normalized_mae: 0.024920233835285917
  normalized_rmse: 0.03148807747724556
  num_samples: 116
  target_range: 36.43000030517578
  prediction_range: 30.68454360961914
