Dataset: energy_efficiency (regression)
Penalty: 0.3
Seed: 3
Best fitness: -0.6404726956201636
Final val loss: 2.67505217
Final penalty: 0.27912659
Model saved to: logs/regression/energy_efficiency/models/best_model_penalty_0.3_seed_3.pth

Final architecture & hyperparameters:
  num_layers: 4
  layer_sizes: [10, 5, 2, 8]
  activations: [3, 2, 3, 4]
  dropout_rates: [0.011, 0.162, 0.115, 0.0]
  batch_norms: [0, 0, 1, 1]
  learning_rate: 0.0164
  batch_size: 32
  patience: 19
  optimizer_type: 2
  init_type: 1
  l2_penalty: 0.0

Validation metrics (final):
  mae: 1.2880523204803467
  mse: 2.675051689147949
  rmse: 1.6355585251368872
  r2_score: 0.9746831655502319
  mape: 8.07289108633995
  residual_std: 1.5826629400253296
  prediction_std: 9.895402908325195
  target_std: 10.279247283935547
  normalized_mae: 0.03585891943596852
  normalized_rmse: 0.045533368833824486
  num_samples: 115
  target_range: 35.91999816894531
  prediction_range: 28.530183792114258

Test metrics (final):
  mae: 1.2295777797698975
  mse: 2.457793951034546
  rmse: 1.5677352936750981
  r2_score: 0.9768765568733215
  mape: 5.972031131386757
  residual_std: 1.433197021484375
  prediction_std: 10.02429485321045
  target_std: 10.309714317321777
  normalized_mae: 0.03531240064751255
  normalized_rmse: 0.04502398929969355
  num_samples: 116
  target_range: 34.81999969482422
  prediction_range: 28.4001407623291
