Dataset: energy_efficiency (regression)
Penalty: 0.3
Seed: 19
Best fitness: -6.3168870674762845
Final val loss: 10.72879772
Final penalty: 0.27912659
Model saved to: logs/regression/energy_efficiency/models/best_model_penalty_0.3_seed_19.pth

Final architecture & hyperparameters:
  num_layers: 4
  layer_sizes: [7, 1, 5, 12]
  activations: [1, 1, 4, 2]
  dropout_rates: [0.098, 0.141, 0.208, 0.076]
  batch_norms: [0, 0, 0, 1]
  learning_rate: 0.0158
  batch_size: 16
  patience: 28
  optimizer_type: 0
  init_type: 0
  l2_penalty: 0.0012

Validation metrics (final):
  mae: 2.4717509746551514
  mse: 10.728798866271973
  rmse: 3.275484523894438
  r2_score: 0.90157151222229
  mape: 13.393789529800415
  residual_std: 3.1868040561676025
  prediction_std: 9.188947677612305
  target_std: 10.440352439880371
  normalized_mae: 0.0688318364725891
  normalized_rmse: 0.09121372558522133
  num_samples: 115
  target_range: 35.909996032714844
  prediction_range: 20.92367172241211

Test metrics (final):
  mae: 3.154217481613159
  mse: 16.777788162231445
  rmse: 4.096069843426921
  r2_score: 0.8500057458877563
  mape: 14.297915995121002
  residual_std: 4.047156810760498
  prediction_std: 9.007003784179688
  target_std: 10.576210021972656
  normalized_mae: 0.08587578330857536
  normalized_rmse: 0.11151837447525134
  num_samples: 116
  target_range: 36.72999954223633
  prediction_range: 20.880229949951172
