Dataset: energy_efficiency (regression)
Penalty: 0.2
Seed: 42
Best fitness: -0.0489021740577839
Final val loss: 0.09456856
Final penalty: 0.00814815
Model saved to: exp_2/logs/regression/energy_efficiency/models/best_model_penalty_0.2_seed_42.pth

Final architecture & hyperparameters:
  num_layers: 4
  layer_sizes: [1, 6, 1, 1]
  activations: [3, 3, 1, 1]
  dropout_rates: [0.016, 0.114, 0.313, 0.016]
  batch_norms: [1, 1, 0, 1]
  learning_rate: 0.0218
  batch_size: 16
  patience: 16
  optimizer_type: 2
  init_type: 2
  l2_penalty: 0.0

Validation metrics (final):
  mae: 3.942831516265869
  mse: 23.486591339111328
  rmse: 4.84629666230941
  r2_score: 0.7702237963676453
  mape: 22.34877645969391
  residual_std: 4.843719005584717
  prediction_std: 6.113360404968262
  target_std: 10.110147476196289
  normalized_mae: 0.10752198808237456
  normalized_rmse: 0.13215970548545924
  num_samples: 115
  target_range: 36.67000198364258
  prediction_range: 15.85943603515625

Test metrics (final):
  mae: 3.792931079864502
  mse: 21.35179901123047
  rmse: 4.620800689407678
  r2_score: 0.7820192575454712
  mape: 24.03259128332138
  residual_std: 4.561100482940674
  prediction_std: 6.059295654296875
  target_std: 9.89710521697998
  normalized_mae: 0.10366031877691152
  normalized_rmse: 0.1262858887711938
  num_samples: 116
  target_range: 36.59000015258789
  prediction_range: 15.792842864990234
