Dataset: energy_efficiency (regression)
Penalty: 0.3
Seed: 37
Best fitness: -0.9849546613643603
Final val loss: 2.52728247
Final penalty: 0.29431585
Model saved to: logs/regression/energy_efficiency/models/best_model_penalty_0.3_seed_37.pth

Final architecture & hyperparameters:
  num_layers: 4
  layer_sizes: [12, 7, 12, 10]
  activations: [3, 4, 1, 4]
  dropout_rates: [0.003, 0.335, 0.242, 0.021]
  batch_norms: [0, 0, 1, 1]
  learning_rate: 0.0153
  batch_size: 16
  patience: 29
  optimizer_type: 1
  init_type: 0
  l2_penalty: 0.0

Validation metrics (final):
  mae: 1.232947826385498
  mse: 2.527282476425171
  rmse: 1.5897428963279474
  r2_score: 0.9726024866104126
  mape: 7.601746171712875
  residual_std: 1.5703260898590088
  prediction_std: 8.996746063232422
  target_std: 9.604421615600586
  normalized_mae: 0.03401235383132408
  normalized_rmse: 0.04385497645042614
  num_samples: 115
  target_range: 36.25
  prediction_range: 34.217281341552734

Test metrics (final):
  mae: 1.2207212448120117
  mse: 2.441690444946289
  rmse: 1.562590939736401
  r2_score: 0.976472020149231
  mape: 6.712000072002411
  residual_std: 1.5501759052276611
  prediction_std: 9.72615909576416
  target_std: 10.187153816223145
  normalized_mae: 0.033536296528562756
  normalized_rmse: 0.042928320720686315
  num_samples: 116
  target_range: 36.400001525878906
  prediction_range: 33.78920364379883
