Dataset: energy_efficiency (regression)
Penalty: 0.2
Seed: 37
Best fitness: -4.736179650315918
Final val loss: 3.38202131
Final penalty: 0.10202201
Model saved to: logs/regression/energy_efficiency/models/best_model_penalty_0.2_seed_37.pth

Final architecture & hyperparameters:
  num_layers: 3
  layer_sizes: [11, 6, 7]
  activations: [3, 1, 4]
  dropout_rates: [0.14, 0.167, 0.021]
  batch_norms: [0, 1, 1]
  learning_rate: 0.0213
  batch_size: 32
  patience: 14
  optimizer_type: 2
  init_type: 1
  l2_penalty: 0.0

Validation metrics (final):
  mae: 1.4242480993270874
  mse: 3.382021188735962
  rmse: 1.839027239802598
  r2_score: 0.9633365273475647
  mape: 8.339240401983261
  residual_std: 1.725257158279419
  prediction_std: 9.09368896484375
  target_std: 9.604421615600586
  normalized_mae: 0.039289602740057585
  normalized_rmse: 0.05073178592558891
  num_samples: 115
  target_range: 36.25
  prediction_range: 29.55537223815918

Test metrics (final):
  mae: 1.3702479600906372
  mse: 3.278832197189331
  rmse: 1.8107545933089142
  r2_score: 0.9684053659439087
  mape: 7.002574950456619
  residual_std: 1.7149162292480469
  prediction_std: 9.863897323608398
  target_std: 10.187153816223145
  normalized_mae: 0.037644173149730425
  normalized_rmse: 0.04974600322534443
  num_samples: 116
  target_range: 36.400001525878906
  prediction_range: 29.518104553222656
