Dataset: energy_efficiency (regression)
Penalty: 0.1
Seed: 7
Best fitness: -0.7638922136601631
Final val loss: 5.93440741
Final penalty: 0.05173284
Model saved to: logs/regression/energy_efficiency/models/best_model_penalty_0.1_seed_7.pth

Final architecture & hyperparameters:
  num_layers: 3
  layer_sizes: [11, 6, 9]
  activations: [3, 3, 4]
  dropout_rates: [0.017, 0.469, 0.125]
  batch_norms: [0, 0, 1]
  learning_rate: 0.0287
  batch_size: 64
  patience: 21
  optimizer_type: 2
  init_type: 0
  l2_penalty: 0.0

Validation metrics (final):
  mae: 1.847145676612854
  mse: 5.934407711029053
  rmse: 2.4360639792560974
  r2_score: 0.9461256861686707
  mape: 8.54993537068367
  residual_std: 2.3322906494140625
  prediction_std: 9.156180381774902
  target_std: 10.495369911193848
  normalized_mae: 0.05034465940858784
  normalized_rmse: 0.0663958521983333
  num_samples: 115
  target_range: 36.69000244140625
  prediction_range: 24.48479461669922

Test metrics (final):
  mae: 1.4101346731185913
  mse: 3.6271438598632812
  rmse: 1.9045061984313103
  r2_score: 0.9614361524581909
  mape: 7.304590940475464
  residual_std: 1.8670716285705566
  prediction_std: 8.858260154724121
  target_std: 9.698221206665039
  normalized_mae: 0.03870806097463158
  normalized_rmse: 0.052278511734207375
  num_samples: 116
  target_range: 36.43000030517578
  prediction_range: 24.38021469116211
