Dataset: energy_efficiency (regression)
Penalty: 0.0
Seed: 19
Best fitness: -0.9643186484018098
Final val loss: 2.82563088
Final penalty: 0.00000000
Model saved to: logs/regression/energy_efficiency/models/best_model_penalty_0.0_seed_19.pth

Final architecture & hyperparameters:
  num_layers: 3
  layer_sizes: [12, 11, 12]
  activations: [3, 2, 2]
  dropout_rates: [0.033, 0.431, 0.057]
  batch_norms: [0, 1, 1]
  learning_rate: 0.02
  batch_size: 16
  patience: 30
  optimizer_type: 2
  init_type: 1
  l2_penalty: 0.0001

Validation metrics (final):
  mae: 1.3464730978012085
  mse: 2.8256309032440186
  rmse: 1.6809613033154627
  r2_score: 0.9740769863128662
  mape: 7.529021054506302
  residual_std: 1.675837755203247
  prediction_std: 9.693568229675293
  target_std: 10.440352439880371
  normalized_mae: 0.037495774061755395
  normalized_rmse: 0.04681040069689976
  num_samples: 115
  target_range: 35.909996032714844
  prediction_range: 27.684181213378906

Test metrics (final):
  mae: 1.5316050052642822
  mse: 3.7034356594085693
  rmse: 1.9244312560880343
  r2_score: 0.9668911099433899
  mape: 7.446306943893433
  residual_std: 1.9239997863769531
  prediction_std: 9.527905464172363
  target_std: 10.576210021972656
  normalized_mae: 0.04169902053777781
  normalized_rmse: 0.05239399074522461
  num_samples: 116
  target_range: 36.72999954223633
  prediction_range: 27.689876556396484
