Dataset: energy_efficiency (regression)
Penalty: 0.1
Seed: 42
Best fitness: -0.05508530947345275
Final val loss: 0.10107064
Final penalty: 0.00962963
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: [2, 1, 4, 6]
  activations: [3, 2, 3, 4]
  dropout_rates: [0.173, 0.268, 0.281, 0.146]
  batch_norms: [1, 1, 1, 1]
  learning_rate: 0.0225
  batch_size: 16
  patience: 17
  optimizer_type: 2
  init_type: 0
  l2_penalty: 0.0

Validation metrics (final):
  mae: 4.383706092834473
  mse: 30.190324783325195
  rmse: 5.494572302129184
  r2_score: 0.704639196395874
  mape: 23.164714872837067
  residual_std: 5.462693691253662
  prediction_std: 5.622825622558594
  target_std: 10.110147476196289
  normalized_mae: 0.11954474654214409
  normalized_rmse: 0.14983834210263072
  num_samples: 115
  target_range: 36.67000198364258
  prediction_range: 12.361854553222656

Test metrics (final):
  mae: 4.042670726776123
  mse: 25.287172317504883
  rmse: 5.028635234087364
  r2_score: 0.7418429851531982
  mape: 24.23328161239624
  residual_std: 5.025513172149658
  prediction_std: 5.704010963439941
  target_std: 9.89710521697998
  normalized_mae: 0.11048567121938638
  normalized_rmse: 0.13743195444429931
  num_samples: 116
  target_range: 36.59000015258789
  prediction_range: 12.357280731201172
