Dataset: energy_efficiency (regression)
Penalty: 0.1
Seed: 42
Best fitness: -0.052469588015918375
Final val loss: 0.07726417
Final penalty: 0.01407407
Model saved to: exp_2/logs/regression/energy_efficiency/models/best_model_penalty_0.1_seed_42.pth

Final architecture & hyperparameters:
  num_layers: 4
  layer_sizes: [3, 6, 3, 4]
  activations: [3, 2, 1, 4]
  dropout_rates: [0.058, 0.499, 0.058, 0.137]
  batch_norms: [1, 0, 1, 1]
  learning_rate: 0.0225
  batch_size: 16
  patience: 20
  optimizer_type: 2
  init_type: 0
  l2_penalty: 0.0

Validation metrics (final):
  mae: 3.3553566932678223
  mse: 18.601457595825195
  rmse: 4.312940713228643
  r2_score: 0.8180164694786072
  mape: 17.1548068523407
  residual_std: 4.270897388458252
  prediction_std: 7.0892462730407715
  target_std: 10.110147476196289
  normalized_mae: 0.09150140473852576
  normalized_rmse: 0.11761495718359982
  num_samples: 115
  target_range: 36.67000198364258
  prediction_range: 16.92725372314453

Test metrics (final):
  mae: 3.036292791366577
  mse: 15.518545150756836
  rmse: 3.939358469441038
  r2_score: 0.841571033000946
  mape: 17.55138635635376
  residual_std: 3.9335126876831055
  prediction_std: 7.073483467102051
  target_std: 9.89710521697998
  normalized_mae: 0.08298149162898624
  normalized_rmse: 0.10766216050869352
  num_samples: 116
  target_range: 36.59000015258789
  prediction_range: 16.899070739746094
