Dataset: energy_efficiency (regression)
Penalty: 0.0
Seed: 42
Best fitness: -0.030434519052505493
Final val loss: 0.02488591
Final penalty: 0.00000000
Model saved to: exp_2/logs/regression/energy_efficiency/models/best_model_penalty_0.0_seed_42.pth

Final architecture & hyperparameters:
  num_layers: 3
  layer_sizes: [9, 3, 3]
  activations: [3, 1, 1]
  dropout_rates: [0.028, 0.016, 0.016]
  batch_norms: [0, 0, 0]
  learning_rate: 0.0225
  batch_size: 16
  patience: 27
  optimizer_type: 2
  init_type: 3
  l2_penalty: 0.0069

Validation metrics (final):
  mae: 1.0417811870574951
  mse: 1.9347069263458252
  rmse: 1.3909374271856463
  r2_score: 0.981072187423706
  mape: 5.044224113225937
  residual_std: 1.3729619979858398
  prediction_std: 10.117560386657715
  target_std: 10.110147476196289
  normalized_mae: 0.02840962996190192
  normalized_rmse: 0.037931206761485946
  num_samples: 115
  target_range: 36.67000198364258
  prediction_range: 35.637733459472656

Test metrics (final):
  mae: 0.8562889099121094
  mse: 1.376936435699463
  rmse: 1.1734293484055454
  r2_score: 0.9859428405761719
  mape: 4.898153617978096
  residual_std: 1.1573573350906372
  prediction_std: 9.868637084960938
  target_std: 9.89710521697998
  normalized_mae: 0.023402265819655835
  normalized_rmse: 0.03206967323072155
  num_samples: 116
  target_range: 36.59000015258789
  prediction_range: 35.1024169921875
