Dataset: energy_efficiency (regression)
Penalty: 0.2
Seed: 42
Best fitness: -0.048239548675439975
Final val loss: 0.04783656
Final penalty: 0.00740741
Model saved to: exp_2/logs/regression/energy_efficiency/models/best_model_penalty_0.2_seed_42.pth

Final architecture & hyperparameters:
  num_layers: 3
  layer_sizes: [2, 1, 1]
  activations: [1, 1, 1]
  dropout_rates: [0.013, 0.013, 0.013]
  batch_norms: [0, 0, 0]
  learning_rate: 0.023
  batch_size: 16
  patience: 11
  optimizer_type: 2
  init_type: 2
  l2_penalty: 0.0001

Validation metrics (final):
  mae: 2.221470355987549
  mse: 10.315779685974121
  rmse: 3.2118187504861044
  r2_score: 0.8990777134895325
  mape: 10.2801114320755
  residual_std: 3.1915414333343506
  prediction_std: 9.482319831848145
  target_std: 10.110147476196289
  normalized_mae: 0.06058004460917352
  normalized_rmse: 0.08758708963034154
  num_samples: 115
  target_range: 36.67000198364258
  prediction_range: 29.591106414794922

Test metrics (final):
  mae: 1.9232759475708008
  mse: 7.67202615737915
  rmse: 2.769842262183742
  r2_score: 0.9216762185096741
  mape: 9.906093031167984
  residual_std: 2.769714593887329
  prediction_std: 9.299508094787598
  target_std: 9.89710521697998
  normalized_mae: 0.05256288438235423
  normalized_rmse: 0.0756994329224631
  num_samples: 116
  target_range: 36.59000015258789
  prediction_range: 29.578296661376953
