Dataset: energy_efficiency (regression)
Penalty: 0.3
Seed: 73
Best fitness: -1.0431861213304223
Final val loss: 2.56488737
Final penalty: 0.28995191
Model saved to: logs/regression/energy_efficiency/models/best_model_penalty_0.3_seed_73.pth

Final architecture & hyperparameters:
  num_layers: 4
  layer_sizes: [10, 8, 10, 8]
  activations: [3, 4, 4, 4]
  dropout_rates: [0.015, 0.123, 0.109, 0.037]
  batch_norms: [0, 0, 1, 1]
  learning_rate: 0.018
  batch_size: 16
  patience: 17
  optimizer_type: 2
  init_type: 0
  l2_penalty: 0.0

Validation metrics (final):
  mae: 1.32410728931427
  mse: 2.564887523651123
  rmse: 1.6015266228355753
  r2_score: 0.97174471616745
  mape: 6.935612112283707
  residual_std: 1.6013851165771484
  prediction_std: 8.956998825073242
  target_std: 9.52761459350586
  normalized_mae: 0.036167912243625464
  normalized_rmse: 0.043745604920387246
  num_samples: 115
  target_range: 36.61000061035156
  prediction_range: 33.321170806884766

Test metrics (final):
  mae: 1.2394499778747559
  mse: 2.5274064540863037
  rmse: 1.5897818888408257
  r2_score: 0.9717725515365601
  mape: 6.441906094551086
  residual_std: 1.5879261493682861
  prediction_std: 9.199875831604004
  target_std: 9.462409019470215
  normalized_mae: 0.03505231777377033
  normalized_rmse: 0.0449598942703474
  num_samples: 116
  target_range: 35.36000061035156
  prediction_range: 32.33174133300781
