--------------------------------
Loading column definition...
Checking column definition...
Loading data...
Dropping columns / rows...
Checking for NA values...
Setting data types...
Dropping columns / rows...
Encoding data...
	Updated column definition:
		id: REAL_VALUED (ID)
		time: DATE (TIME)
		gl: REAL_VALUED (TARGET)
		Height: REAL_VALUED (STATIC_INPUT)
		Weight: REAL_VALUED (STATIC_INPUT)
		Gender: REAL_VALUED (STATIC_INPUT)
		Race: REAL_VALUED (STATIC_INPUT)
		EduLevel: REAL_VALUED (STATIC_INPUT)
		AnnualInc: REAL_VALUED (STATIC_INPUT)
		MaritalStatus: REAL_VALUED (STATIC_INPUT)
		DaysWkEx: REAL_VALUED (STATIC_INPUT)
		DaysWkDrinkAlc: REAL_VALUED (STATIC_INPUT)
		DaysMonBingeAlc: REAL_VALUED (STATIC_INPUT)
		T1DDiagAge: REAL_VALUED (STATIC_INPUT)
		NumHospDKA: REAL_VALUED (STATIC_INPUT)
		NumSHSinceT1DDiag: REAL_VALUED (STATIC_INPUT)
		InsDeliveryMethod: REAL_VALUED (STATIC_INPUT)
		UnitsInsTotal: REAL_VALUED (STATIC_INPUT)
		NumMeterCheckDay: REAL_VALUED (STATIC_INPUT)
		Aspirin: REAL_VALUED (STATIC_INPUT)
		Simvastatin: REAL_VALUED (STATIC_INPUT)
		Lisinopril: REAL_VALUED (STATIC_INPUT)
		Vitamin D: REAL_VALUED (STATIC_INPUT)
		Multivitamin preparation: REAL_VALUED (STATIC_INPUT)
		Omeprazole: REAL_VALUED (STATIC_INPUT)
		atorvastatin: REAL_VALUED (STATIC_INPUT)
		Synthroid: REAL_VALUED (STATIC_INPUT)
		vitamin D3: REAL_VALUED (STATIC_INPUT)
		Hypertension: REAL_VALUED (STATIC_INPUT)
		Hyperlipidemia: REAL_VALUED (STATIC_INPUT)
		Hypothyroidism: REAL_VALUED (STATIC_INPUT)
		Depression: REAL_VALUED (STATIC_INPUT)
		Coronary artery disease: REAL_VALUED (STATIC_INPUT)
		Diabetic peripheral neuropathy: REAL_VALUED (STATIC_INPUT)
		Dyslipidemia: REAL_VALUED (STATIC_INPUT)
		Chronic kidney disease: REAL_VALUED (STATIC_INPUT)
		Osteoporosis: REAL_VALUED (STATIC_INPUT)
		Proliferative diabetic retinopathy: REAL_VALUED (STATIC_INPUT)
		Hypercholesterolemia: REAL_VALUED (STATIC_INPUT)
		Erectile dysfunction: REAL_VALUED (STATIC_INPUT)
		Type I diabetes mellitus: REAL_VALUED (STATIC_INPUT)
		time_year: REAL_VALUED (KNOWN_INPUT)
		time_month: REAL_VALUED (KNOWN_INPUT)
		time_day: REAL_VALUED (KNOWN_INPUT)
		time_hour: REAL_VALUED (KNOWN_INPUT)
		time_minute: REAL_VALUED (KNOWN_INPUT)
Interpolating data...
	Dropped segments: 1416
	Extracted segments: 681
	Interpolated values: 140564
	Percent of values interpolated: 24.24%
Splitting data...
	Train: 357814 (68.58%)
	Val: 96960 (18.58%)
	Test: 125008 (23.96%)
Scaling data...
	No scaling applied
Data formatting complete.
--------------------------------
Current value: 0.05952414870262146, Current params: {'in_len': 60, 'max_samples_per_ts': 150, 'lr': 0.89, 'subsample': 0.8, 'min_child_weight': 2.0, 'colsample_bytree': 1.0, 'max_depth': 4, 'gamma': 4.5, 'alpha': 0.29, 'lambda_': 0.05, 'n_estimators': 256}
Best value: 0.05952414870262146, Best params: {'in_len': 60, 'max_samples_per_ts': 150, 'lr': 0.89, 'subsample': 0.8, 'min_child_weight': 2.0, 'colsample_bytree': 1.0, 'max_depth': 4, 'gamma': 4.5, 'alpha': 0.29, 'lambda_': 0.05, 'n_estimators': 256}
Current value: 0.0661640465259552, Current params: {'in_len': 120, 'max_samples_per_ts': 100, 'lr': 0.968, 'subsample': 0.9, 'min_child_weight': 2.0, 'colsample_bytree': 1.0, 'max_depth': 9, 'gamma': 8.5, 'alpha': 0.069, 'lambda_': 0.267, 'n_estimators': 416}
Best value: 0.05952414870262146, Best params: {'in_len': 60, 'max_samples_per_ts': 150, 'lr': 0.89, 'subsample': 0.8, 'min_child_weight': 2.0, 'colsample_bytree': 1.0, 'max_depth': 4, 'gamma': 4.5, 'alpha': 0.29, 'lambda_': 0.05, 'n_estimators': 256}
Current value: 0.06051206216216087, Current params: {'in_len': 156, 'max_samples_per_ts': 100, 'lr': 0.343, 'subsample': 0.9, 'min_child_weight': 5.0, 'colsample_bytree': 0.9, 'max_depth': 4, 'gamma': 0.5, 'alpha': 0.043000000000000003, 'lambda_': 0.096, 'n_estimators': 512}
Best value: 0.05952414870262146, Best params: {'in_len': 60, 'max_samples_per_ts': 150, 'lr': 0.89, 'subsample': 0.8, 'min_child_weight': 2.0, 'colsample_bytree': 1.0, 'max_depth': 4, 'gamma': 4.5, 'alpha': 0.29, 'lambda_': 0.05, 'n_estimators': 256}
Current value: 0.06322728842496872, Current params: {'in_len': 72, 'max_samples_per_ts': 200, 'lr': 0.23700000000000002, 'subsample': 0.6, 'min_child_weight': 1.0, 'colsample_bytree': 1.0, 'max_depth': 7, 'gamma': 9.0, 'alpha': 0.192, 'lambda_': 0.166, 'n_estimators': 512}
Best value: 0.05952414870262146, Best params: {'in_len': 60, 'max_samples_per_ts': 150, 'lr': 0.89, 'subsample': 0.8, 'min_child_weight': 2.0, 'colsample_bytree': 1.0, 'max_depth': 4, 'gamma': 4.5, 'alpha': 0.29, 'lambda_': 0.05, 'n_estimators': 256}
Current value: 0.05941688269376755, Current params: {'in_len': 84, 'max_samples_per_ts': 100, 'lr': 0.88, 'subsample': 0.7, 'min_child_weight': 4.0, 'colsample_bytree': 0.9, 'max_depth': 9, 'gamma': 4.0, 'alpha': 0.139, 'lambda_': 0.264, 'n_estimators': 384}
Best value: 0.05941688269376755, Best params: {'in_len': 84, 'max_samples_per_ts': 100, 'lr': 0.88, 'subsample': 0.7, 'min_child_weight': 4.0, 'colsample_bytree': 0.9, 'max_depth': 9, 'gamma': 4.0, 'alpha': 0.139, 'lambda_': 0.264, 'n_estimators': 384}
Current value: 0.06297119706869125, Current params: {'in_len': 180, 'max_samples_per_ts': 100, 'lr': 0.242, 'subsample': 0.7, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 0.5, 'alpha': 0.226, 'lambda_': 0.10200000000000001, 'n_estimators': 288}
Best value: 0.05941688269376755, Best params: {'in_len': 84, 'max_samples_per_ts': 100, 'lr': 0.88, 'subsample': 0.7, 'min_child_weight': 4.0, 'colsample_bytree': 0.9, 'max_depth': 9, 'gamma': 4.0, 'alpha': 0.139, 'lambda_': 0.264, 'n_estimators': 384}
Current value: 0.0642552301287651, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'lr': 0.323, 'subsample': 0.8, 'min_child_weight': 5.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 10.0, 'alpha': 0.060000000000000005, 'lambda_': 0.065, 'n_estimators': 480}
Best value: 0.05941688269376755, Best params: {'in_len': 84, 'max_samples_per_ts': 100, 'lr': 0.88, 'subsample': 0.7, 'min_child_weight': 4.0, 'colsample_bytree': 0.9, 'max_depth': 9, 'gamma': 4.0, 'alpha': 0.139, 'lambda_': 0.264, 'n_estimators': 384}
Current value: 0.05863405764102936, Current params: {'in_len': 24, 'max_samples_per_ts': 50, 'lr': 0.592, 'subsample': 0.9, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 3.5, 'alpha': 0.054, 'lambda_': 0.063, 'n_estimators': 448}
Best value: 0.05863405764102936, Best params: {'in_len': 24, 'max_samples_per_ts': 50, 'lr': 0.592, 'subsample': 0.9, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 3.5, 'alpha': 0.054, 'lambda_': 0.063, 'n_estimators': 448}
Current value: 0.06259122490882874, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'lr': 0.671, 'subsample': 0.7, 'min_child_weight': 3.0, 'colsample_bytree': 0.8, 'max_depth': 4, 'gamma': 5.0, 'alpha': 0.14300000000000002, 'lambda_': 0.126, 'n_estimators': 256}
Best value: 0.05863405764102936, Best params: {'in_len': 24, 'max_samples_per_ts': 50, 'lr': 0.592, 'subsample': 0.9, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 3.5, 'alpha': 0.054, 'lambda_': 0.063, 'n_estimators': 448}
Current value: 0.06225401163101196, Current params: {'in_len': 84, 'max_samples_per_ts': 100, 'lr': 0.551, 'subsample': 0.9, 'min_child_weight': 1.0, 'colsample_bytree': 1.0, 'max_depth': 10, 'gamma': 10.0, 'alpha': 0.032, 'lambda_': 0.08600000000000001, 'n_estimators': 512}
Best value: 0.05863405764102936, Best params: {'in_len': 24, 'max_samples_per_ts': 50, 'lr': 0.592, 'subsample': 0.9, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 3.5, 'alpha': 0.054, 'lambda_': 0.063, 'n_estimators': 448}
Current value: 0.05880581587553024, Current params: {'in_len': 24, 'max_samples_per_ts': 50, 'lr': 0.074, 'subsample': 1.0, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 8, 'gamma': 2.5, 'alpha': 0.002, 'lambda_': 0.192, 'n_estimators': 416}
Best value: 0.05863405764102936, Best params: {'in_len': 24, 'max_samples_per_ts': 50, 'lr': 0.592, 'subsample': 0.9, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 3.5, 'alpha': 0.054, 'lambda_': 0.063, 'n_estimators': 448}
Current value: 0.05889708548784256, Current params: {'in_len': 36, 'max_samples_per_ts': 50, 'lr': 0.027000000000000003, 'subsample': 1.0, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 8, 'gamma': 2.5, 'alpha': 0.001, 'lambda_': 0.004, 'n_estimators': 416}
Best value: 0.05863405764102936, Best params: {'in_len': 24, 'max_samples_per_ts': 50, 'lr': 0.592, 'subsample': 0.9, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 3.5, 'alpha': 0.054, 'lambda_': 0.063, 'n_estimators': 448}
Current value: 0.059374842792749405, Current params: {'in_len': 24, 'max_samples_per_ts': 50, 'lr': 0.014000000000000002, 'subsample': 1.0, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 7, 'gamma': 2.5, 'alpha': 0.098, 'lambda_': 0.18, 'n_estimators': 352}
Best value: 0.05863405764102936, Best params: {'in_len': 24, 'max_samples_per_ts': 50, 'lr': 0.592, 'subsample': 0.9, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 3.5, 'alpha': 0.054, 'lambda_': 0.063, 'n_estimators': 448}
Current value: 0.06066262349486351, Current params: {'in_len': 36, 'max_samples_per_ts': 50, 'lr': 0.676, 'subsample': 1.0, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 8, 'gamma': 6.5, 'alpha': 0.009000000000000001, 'lambda_': 0.20500000000000002, 'n_estimators': 448}
Best value: 0.05863405764102936, Best params: {'in_len': 24, 'max_samples_per_ts': 50, 'lr': 0.592, 'subsample': 0.9, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 3.5, 'alpha': 0.054, 'lambda_': 0.063, 'n_estimators': 448}
Current value: 0.05888320505619049, Current params: {'in_len': 48, 'max_samples_per_ts': 150, 'lr': 0.506, 'subsample': 0.9, 'min_child_weight': 3.0, 'colsample_bytree': 0.8, 'max_depth': 6, 'gamma': 2.5, 'alpha': 0.08800000000000001, 'lambda_': 0.22, 'n_estimators': 352}
Best value: 0.05863405764102936, Best params: {'in_len': 24, 'max_samples_per_ts': 50, 'lr': 0.592, 'subsample': 0.9, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 3.5, 'alpha': 0.054, 'lambda_': 0.063, 'n_estimators': 448}
Current value: 0.05947405844926834, Current params: {'in_len': 24, 'max_samples_per_ts': 50, 'lr': 0.707, 'subsample': 1.0, 'min_child_weight': 5.0, 'colsample_bytree': 0.9, 'max_depth': 9, 'gamma': 6.5, 'alpha': 0.112, 'lambda_': 0.014000000000000002, 'n_estimators': 448}
Best value: 0.05863405764102936, Best params: {'in_len': 24, 'max_samples_per_ts': 50, 'lr': 0.592, 'subsample': 0.9, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 3.5, 'alpha': 0.054, 'lambda_': 0.063, 'n_estimators': 448}
Current value: 0.06128533184528351, Current params: {'in_len': 60, 'max_samples_per_ts': 200, 'lr': 0.14200000000000002, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 8, 'gamma': 3.5, 'alpha': 0.035, 'lambda_': 0.136, 'n_estimators': 352}
Best value: 0.05863405764102936, Best params: {'in_len': 24, 'max_samples_per_ts': 50, 'lr': 0.592, 'subsample': 0.9, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 3.5, 'alpha': 0.054, 'lambda_': 0.063, 'n_estimators': 448}
Current value: 0.05766060948371887, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'lr': 0.463, 'subsample': 1.0, 'min_child_weight': 5.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.188, 'lambda_': 0.215, 'n_estimators': 448}
Best value: 0.05766060948371887, Best params: {'in_len': 108, 'max_samples_per_ts': 50, 'lr': 0.463, 'subsample': 1.0, 'min_child_weight': 5.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.188, 'lambda_': 0.215, 'n_estimators': 448}
Current value: 0.06243472546339035, Current params: {'in_len': 192, 'max_samples_per_ts': 150, 'lr': 0.429, 'subsample': 0.8, 'min_child_weight': 5.0, 'colsample_bytree': 0.9, 'max_depth': 5, 'gamma': 1.5, 'alpha': 0.198, 'lambda_': 0.234, 'n_estimators': 448}
Best value: 0.05766060948371887, Best params: {'in_len': 108, 'max_samples_per_ts': 50, 'lr': 0.463, 'subsample': 1.0, 'min_child_weight': 5.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.188, 'lambda_': 0.215, 'n_estimators': 448}
Current value: 0.06202743947505951, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'lr': 0.595, 'subsample': 0.8, 'min_child_weight': 3.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 6.0, 'alpha': 0.251, 'lambda_': 0.299, 'n_estimators': 480}
Best value: 0.05766060948371887, Best params: {'in_len': 108, 'max_samples_per_ts': 50, 'lr': 0.463, 'subsample': 1.0, 'min_child_weight': 5.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.188, 'lambda_': 0.215, 'n_estimators': 448}
Current value: 0.05827566608786583, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'lr': 0.429, 'subsample': 0.9, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 7, 'gamma': 3.5, 'alpha': 0.181, 'lambda_': 0.038, 'n_estimators': 384}
Best value: 0.05766060948371887, Best params: {'in_len': 108, 'max_samples_per_ts': 50, 'lr': 0.463, 'subsample': 1.0, 'min_child_weight': 5.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.188, 'lambda_': 0.215, 'n_estimators': 448}
Current value: 0.05835704877972603, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'lr': 0.441, 'subsample': 0.9, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 7, 'gamma': 3.5, 'alpha': 0.178, 'lambda_': 0.04, 'n_estimators': 384}
Best value: 0.05766060948371887, Best params: {'in_len': 108, 'max_samples_per_ts': 50, 'lr': 0.463, 'subsample': 1.0, 'min_child_weight': 5.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.188, 'lambda_': 0.215, 'n_estimators': 448}
Current value: 0.05794587358832359, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'lr': 0.367, 'subsample': 1.0, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 7, 'gamma': 1.5, 'alpha': 0.178, 'lambda_': 0.037000000000000005, 'n_estimators': 384}
Best value: 0.05766060948371887, Best params: {'in_len': 108, 'max_samples_per_ts': 50, 'lr': 0.463, 'subsample': 1.0, 'min_child_weight': 5.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.188, 'lambda_': 0.215, 'n_estimators': 448}
Current value: 0.05794047191739082, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'lr': 0.368, 'subsample': 1.0, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 5, 'gamma': 1.5, 'alpha': 0.17500000000000002, 'lambda_': 0.026000000000000002, 'n_estimators': 320}
Best value: 0.05766060948371887, Best params: {'in_len': 108, 'max_samples_per_ts': 50, 'lr': 0.463, 'subsample': 1.0, 'min_child_weight': 5.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.188, 'lambda_': 0.215, 'n_estimators': 448}
Current value: 0.06091807037591934, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'lr': 0.353, 'subsample': 1.0, 'min_child_weight': 1.0, 'colsample_bytree': 0.9, 'max_depth': 5, 'gamma': 1.5, 'alpha': 0.221, 'lambda_': 0.019000000000000003, 'n_estimators': 320}
Best value: 0.05766060948371887, Best params: {'in_len': 108, 'max_samples_per_ts': 50, 'lr': 0.463, 'subsample': 1.0, 'min_child_weight': 5.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.188, 'lambda_': 0.215, 'n_estimators': 448}
Current value: 0.05710780248045921, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'lr': 0.218, 'subsample': 1.0, 'min_child_weight': 3.0, 'colsample_bytree': 0.9, 'max_depth': 5, 'gamma': 1.5, 'alpha': 0.163, 'lambda_': 0.158, 'n_estimators': 320}
Best value: 0.05710780248045921, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'lr': 0.218, 'subsample': 1.0, 'min_child_weight': 3.0, 'colsample_bytree': 0.9, 'max_depth': 5, 'gamma': 1.5, 'alpha': 0.163, 'lambda_': 0.158, 'n_estimators': 320}
Current value: 0.06028362363576889, Current params: {'in_len': 84, 'max_samples_per_ts': 100, 'lr': 0.20900000000000002, 'subsample': 1.0, 'min_child_weight': 3.0, 'colsample_bytree': 0.9, 'max_depth': 5, 'gamma': 1.0, 'alpha': 0.129, 'lambda_': 0.155, 'n_estimators': 320}
Best value: 0.05710780248045921, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'lr': 0.218, 'subsample': 1.0, 'min_child_weight': 3.0, 'colsample_bytree': 0.9, 'max_depth': 5, 'gamma': 1.5, 'alpha': 0.163, 'lambda_': 0.158, 'n_estimators': 320}
Current value: 0.06089993193745613, Current params: {'in_len': 156, 'max_samples_per_ts': 50, 'lr': 0.149, 'subsample': 1.0, 'min_child_weight': 3.0, 'colsample_bytree': 1.0, 'max_depth': 5, 'gamma': 2.0, 'alpha': 0.163, 'lambda_': 0.122, 'n_estimators': 320}
Best value: 0.05710780248045921, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'lr': 0.218, 'subsample': 1.0, 'min_child_weight': 3.0, 'colsample_bytree': 0.9, 'max_depth': 5, 'gamma': 1.5, 'alpha': 0.163, 'lambda_': 0.158, 'n_estimators': 320}
Current value: 0.058593880385160446, Current params: {'in_len': 120, 'max_samples_per_ts': 150, 'lr': 0.272, 'subsample': 1.0, 'min_child_weight': 3.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 0.5, 'alpha': 0.214, 'lambda_': 0.233, 'n_estimators': 288}
Best value: 0.05710780248045921, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'lr': 0.218, 'subsample': 1.0, 'min_child_weight': 3.0, 'colsample_bytree': 0.9, 'max_depth': 5, 'gamma': 1.5, 'alpha': 0.163, 'lambda_': 0.158, 'n_estimators': 320}
Current value: 0.060462839901447296, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'lr': 0.127, 'subsample': 0.6, 'min_child_weight': 2.0, 'colsample_bytree': 1.0, 'max_depth': 4, 'gamma': 4.5, 'alpha': 0.278, 'lambda_': 0.149, 'n_estimators': 256}
Best value: 0.05710780248045921, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'lr': 0.218, 'subsample': 1.0, 'min_child_weight': 3.0, 'colsample_bytree': 0.9, 'max_depth': 5, 'gamma': 1.5, 'alpha': 0.163, 'lambda_': 0.158, 'n_estimators': 320}
Current value: 0.059161607176065445, Current params: {'in_len': 72, 'max_samples_per_ts': 100, 'lr': 0.28900000000000003, 'subsample': 1.0, 'min_child_weight': 3.0, 'colsample_bytree': 0.9, 'max_depth': 5, 'gamma': 2.0, 'alpha': 0.251, 'lambda_': 0.195, 'n_estimators': 288}
Best value: 0.05710780248045921, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'lr': 0.218, 'subsample': 1.0, 'min_child_weight': 3.0, 'colsample_bytree': 0.9, 'max_depth': 5, 'gamma': 1.5, 'alpha': 0.163, 'lambda_': 0.158, 'n_estimators': 320}
Current value: 0.05794708803296089, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.382, 'subsample': 1.0, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.161, 'lambda_': 0.068, 'n_estimators': 352}
Best value: 0.05710780248045921, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'lr': 0.218, 'subsample': 1.0, 'min_child_weight': 3.0, 'colsample_bytree': 0.9, 'max_depth': 5, 'gamma': 1.5, 'alpha': 0.163, 'lambda_': 0.158, 'n_estimators': 320}
Current value: 0.05669058486819267, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'lr': 0.48000000000000004, 'subsample': 1.0, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.159, 'lambda_': 0.025, 'n_estimators': 320}
Best value: 0.05669058486819267, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'lr': 0.48000000000000004, 'subsample': 1.0, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.159, 'lambda_': 0.025, 'n_estimators': 320}
Current value: 0.05677426978945732, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'lr': 0.505, 'subsample': 0.9, 'min_child_weight': 1.0, 'colsample_bytree': 0.9, 'max_depth': 5, 'gamma': 1.0, 'alpha': 0.121, 'lambda_': 0.258, 'n_estimators': 320}
Best value: 0.05669058486819267, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'lr': 0.48000000000000004, 'subsample': 1.0, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.159, 'lambda_': 0.025, 'n_estimators': 320}
Current value: 0.057333678007125854, Current params: {'in_len': 96, 'max_samples_per_ts': 100, 'lr': 0.775, 'subsample': 0.9, 'min_child_weight': 1.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 0.5, 'alpha': 0.121, 'lambda_': 0.261, 'n_estimators': 288}
Best value: 0.05669058486819267, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'lr': 0.48000000000000004, 'subsample': 1.0, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.159, 'lambda_': 0.025, 'n_estimators': 320}
Current value: 0.05877046659588814, Current params: {'in_len': 72, 'max_samples_per_ts': 100, 'lr': 0.8260000000000001, 'subsample': 0.9, 'min_child_weight': 1.0, 'colsample_bytree': 1.0, 'max_depth': 4, 'gamma': 0.5, 'alpha': 0.12000000000000001, 'lambda_': 0.263, 'n_estimators': 288}
Best value: 0.05669058486819267, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'lr': 0.48000000000000004, 'subsample': 1.0, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.159, 'lambda_': 0.025, 'n_estimators': 320}
Current value: 0.057504937052726746, Current params: {'in_len': 96, 'max_samples_per_ts': 100, 'lr': 0.801, 'subsample': 0.9, 'min_child_weight': 1.0, 'colsample_bytree': 0.9, 'max_depth': 5, 'gamma': 0.5, 'alpha': 0.085, 'lambda_': 0.297, 'n_estimators': 256}
Best value: 0.05669058486819267, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'lr': 0.48000000000000004, 'subsample': 1.0, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.159, 'lambda_': 0.025, 'n_estimators': 320}
Current value: 0.05822489410638809, Current params: {'in_len': 84, 'max_samples_per_ts': 150, 'lr': 0.769, 'subsample': 0.8, 'min_child_weight': 1.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.0, 'alpha': 0.149, 'lambda_': 0.253, 'n_estimators': 288}
Best value: 0.05669058486819267, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'lr': 0.48000000000000004, 'subsample': 1.0, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.159, 'lambda_': 0.025, 'n_estimators': 320}
Current value: 0.059497129172086716, Current params: {'in_len': 60, 'max_samples_per_ts': 200, 'lr': 0.986, 'subsample': 0.9, 'min_child_weight': 1.0, 'colsample_bytree': 1.0, 'max_depth': 4, 'gamma': 8.0, 'alpha': 0.10400000000000001, 'lambda_': 0.279, 'n_estimators': 320}
Best value: 0.05669058486819267, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'lr': 0.48000000000000004, 'subsample': 1.0, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.159, 'lambda_': 0.025, 'n_estimators': 320}
Current value: 0.06111600250005722, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'lr': 0.6, 'subsample': 0.8, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 5, 'gamma': 3.0, 'alpha': 0.133, 'lambda_': 0.245, 'n_estimators': 256}
Best value: 0.05669058486819267, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'lr': 0.48000000000000004, 'subsample': 1.0, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.159, 'lambda_': 0.025, 'n_estimators': 320}
Current value: 0.0589049868285656, Current params: {'in_len': 72, 'max_samples_per_ts': 100, 'lr': 0.868, 'subsample': 0.7, 'min_child_weight': 1.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.0, 'alpha': 0.08, 'lambda_': 0.274, 'n_estimators': 288}
Best value: 0.05669058486819267, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'lr': 0.48000000000000004, 'subsample': 1.0, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.159, 'lambda_': 0.025, 'n_estimators': 320}
Current value: 0.05769908055663109, Current params: {'in_len': 96, 'max_samples_per_ts': 100, 'lr': 0.747, 'subsample': 0.9, 'min_child_weight': 1.0, 'colsample_bytree': 0.9, 'max_depth': 5, 'gamma': 0.5, 'alpha': 0.078, 'lambda_': 0.3, 'n_estimators': 256}
Best value: 0.05669058486819267, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'lr': 0.48000000000000004, 'subsample': 1.0, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.159, 'lambda_': 0.025, 'n_estimators': 320}
Current value: 0.05778486281633377, Current params: {'in_len': 96, 'max_samples_per_ts': 150, 'lr': 0.931, 'subsample': 0.9, 'min_child_weight': 1.0, 'colsample_bytree': 0.9, 'max_depth': 5, 'gamma': 0.5, 'alpha': 0.16, 'lambda_': 0.28600000000000003, 'n_estimators': 256}
Best value: 0.05669058486819267, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'lr': 0.48000000000000004, 'subsample': 1.0, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.159, 'lambda_': 0.025, 'n_estimators': 320}
Current value: 0.058818552643060684, Current params: {'in_len': 96, 'max_samples_per_ts': 100, 'lr': 0.791, 'subsample': 0.9, 'min_child_weight': 1.0, 'colsample_bytree': 0.9, 'max_depth': 4, 'gamma': 2.0, 'alpha': 0.124, 'lambda_': 0.10500000000000001, 'n_estimators': 288}
Best value: 0.05669058486819267, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'lr': 0.48000000000000004, 'subsample': 1.0, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.159, 'lambda_': 0.025, 'n_estimators': 320}
Current value: 0.0600724071264267, Current params: {'in_len': 120, 'max_samples_per_ts': 100, 'lr': 0.63, 'subsample': 0.9, 'min_child_weight': 1.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.0, 'alpha': 0.059000000000000004, 'lambda_': 0.256, 'n_estimators': 320}
Best value: 0.05669058486819267, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'lr': 0.48000000000000004, 'subsample': 1.0, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.159, 'lambda_': 0.025, 'n_estimators': 320}
Current value: 0.05756431072950363, Current params: {'in_len': 84, 'max_samples_per_ts': 50, 'lr': 0.922, 'subsample': 0.8, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 5, 'gamma': 1.0, 'alpha': 0.097, 'lambda_': 0.17, 'n_estimators': 352}
Best value: 0.05669058486819267, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'lr': 0.48000000000000004, 'subsample': 1.0, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.159, 'lambda_': 0.025, 'n_estimators': 320}
Current value: 0.05878839269280434, Current params: {'in_len': 72, 'max_samples_per_ts': 100, 'lr': 0.531, 'subsample': 0.9, 'min_child_weight': 1.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 3.0, 'alpha': 0.14200000000000002, 'lambda_': 0.23900000000000002, 'n_estimators': 288}
Best value: 0.05669058486819267, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'lr': 0.48000000000000004, 'subsample': 1.0, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.159, 'lambda_': 0.025, 'n_estimators': 320}
Current value: 0.05843173712491989, Current params: {'in_len': 84, 'max_samples_per_ts': 50, 'lr': 0.837, 'subsample': 0.9, 'min_child_weight': 1.0, 'colsample_bytree': 0.9, 'max_depth': 4, 'gamma': 2.0, 'alpha': 0.115, 'lambda_': 0.29, 'n_estimators': 256}
Best value: 0.05669058486819267, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'lr': 0.48000000000000004, 'subsample': 1.0, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.159, 'lambda_': 0.025, 'n_estimators': 320}
Current value: 0.057647477835416794, Current params: {'in_len': 96, 'max_samples_per_ts': 100, 'lr': 0.6950000000000001, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 5, 'gamma': 0.5, 'alpha': 0.2, 'lambda_': 0.082, 'n_estimators': 320}
Best value: 0.05669058486819267, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'lr': 0.48000000000000004, 'subsample': 1.0, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.159, 'lambda_': 0.025, 'n_estimators': 320}
Current value: 0.058615751564502716, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.644, 'subsample': 0.9, 'min_child_weight': 1.0, 'colsample_bytree': 1.0, 'max_depth': 7, 'gamma': 3.0, 'alpha': 0.108, 'lambda_': 0.272, 'n_estimators': 352}
Best value: 0.05669058486819267, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'lr': 0.48000000000000004, 'subsample': 1.0, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.159, 'lambda_': 0.025, 'n_estimators': 320}
--------------------------------
Loading column definition...
Checking column definition...
Loading data...
Dropping columns / rows...
Checking for NA values...
Setting data types...
Dropping columns / rows...
Encoding data...
	Updated column definition:
		id: REAL_VALUED (ID)
		time: DATE (TIME)
		gl: REAL_VALUED (TARGET)
		Height: REAL_VALUED (STATIC_INPUT)
		Weight: REAL_VALUED (STATIC_INPUT)
		Gender: REAL_VALUED (STATIC_INPUT)
		Race: REAL_VALUED (STATIC_INPUT)
		EduLevel: REAL_VALUED (STATIC_INPUT)
		AnnualInc: REAL_VALUED (STATIC_INPUT)
		MaritalStatus: REAL_VALUED (STATIC_INPUT)
		DaysWkEx: REAL_VALUED (STATIC_INPUT)
		DaysWkDrinkAlc: REAL_VALUED (STATIC_INPUT)
		DaysMonBingeAlc: REAL_VALUED (STATIC_INPUT)
		T1DDiagAge: REAL_VALUED (STATIC_INPUT)
		NumHospDKA: REAL_VALUED (STATIC_INPUT)
		NumSHSinceT1DDiag: REAL_VALUED (STATIC_INPUT)
		InsDeliveryMethod: REAL_VALUED (STATIC_INPUT)
		UnitsInsTotal: REAL_VALUED (STATIC_INPUT)
		NumMeterCheckDay: REAL_VALUED (STATIC_INPUT)
		Aspirin: REAL_VALUED (STATIC_INPUT)
		Simvastatin: REAL_VALUED (STATIC_INPUT)
		Lisinopril: REAL_VALUED (STATIC_INPUT)
		Vitamin D: REAL_VALUED (STATIC_INPUT)
		Multivitamin preparation: REAL_VALUED (STATIC_INPUT)
		Omeprazole: REAL_VALUED (STATIC_INPUT)
		atorvastatin: REAL_VALUED (STATIC_INPUT)
		Synthroid: REAL_VALUED (STATIC_INPUT)
		vitamin D3: REAL_VALUED (STATIC_INPUT)
		Hypertension: REAL_VALUED (STATIC_INPUT)
		Hyperlipidemia: REAL_VALUED (STATIC_INPUT)
		Hypothyroidism: REAL_VALUED (STATIC_INPUT)
		Depression: REAL_VALUED (STATIC_INPUT)
		Coronary artery disease: REAL_VALUED (STATIC_INPUT)
		Diabetic peripheral neuropathy: REAL_VALUED (STATIC_INPUT)
		Dyslipidemia: REAL_VALUED (STATIC_INPUT)
		Chronic kidney disease: REAL_VALUED (STATIC_INPUT)
		Osteoporosis: REAL_VALUED (STATIC_INPUT)
		Proliferative diabetic retinopathy: REAL_VALUED (STATIC_INPUT)
		Hypercholesterolemia: REAL_VALUED (STATIC_INPUT)
		Erectile dysfunction: REAL_VALUED (STATIC_INPUT)
		Type I diabetes mellitus: REAL_VALUED (STATIC_INPUT)
		time_year: REAL_VALUED (KNOWN_INPUT)
		time_month: REAL_VALUED (KNOWN_INPUT)
		time_day: REAL_VALUED (KNOWN_INPUT)
		time_hour: REAL_VALUED (KNOWN_INPUT)
		time_minute: REAL_VALUED (KNOWN_INPUT)
Interpolating data...
	Dropped segments: 1416
	Extracted segments: 681
	Interpolated values: 140564
	Percent of values interpolated: 24.24%
Splitting data...
	Train: 431798 (69.72%)
	Val: 57067 (9.21%)
	Test: 72421 (11.69%)
	Test OOD: 58048 (9.37%)
Scaling data...
	No scaling applied
Data formatting complete.
--------------------------------
	Train: 425413 (68.73%)
	Val: 56593 (9.14%)
	Test: 72022 (11.64%)
	Test OOD: 64922 (10.49%)
	No scaling applied
		Model Seed: 10 Seed: 1 ID mean of (MSE, MAE): [721.0019   17.10986]
		Model Seed: 10 Seed: 1 OOD mean of (MSE, MAE) stats: [936.3475    19.635038]
		Model Seed: 10 Seed: 1 ID median of (MSE, MAE): [189.38911   11.826575]
		Model Seed: 10 Seed: 1 OOD median of (MSE, MAE) stats: [255.64197   13.678985]
		Model Seed: 10 Seed: 1 ID likelihoods: -10.209259413974305
		Model Seed: 10 Seed: 1 OOD likelihoods: -10.339931690033925
		Model Seed: 10 Seed: 1 ID calibration errors: [0.45757012 0.28705828 0.17891716 0.11197718 0.06796154 0.03897631
 0.02358837 0.01351875 0.00736    0.0042522  0.0039496  0.00594359]
		Model Seed: 10 Seed: 1 OOD calibration errors: [0.47647434 0.30117711 0.18368697 0.11349737 0.06748951 0.03927881
 0.02206739 0.01234143 0.00655133 0.00483788 0.00567365 0.00817813]
	Train: 429990 (69.47%)
	Val: 56876 (9.19%)
	Test: 72378 (11.69%)
	Test OOD: 59706 (9.65%)
	No scaling applied
		Model Seed: 10 Seed: 2 ID mean of (MSE, MAE): [724.7667    16.902403]
		Model Seed: 10 Seed: 2 OOD mean of (MSE, MAE) stats: [853.196    18.53533]
		Model Seed: 10 Seed: 2 ID median of (MSE, MAE): [183.05734   11.443659]
		Model Seed: 10 Seed: 2 OOD median of (MSE, MAE) stats: [227.77864    12.8398285]
		Model Seed: 10 Seed: 2 ID likelihoods: -10.211863496597527
		Model Seed: 10 Seed: 2 OOD likelihoods: -10.293433745234989
		Model Seed: 10 Seed: 2 ID calibration errors: [0.46596498 0.30372789 0.19447869 0.12561332 0.07805065 0.04756134
 0.02840117 0.01677302 0.00978702 0.00559883 0.00464311 0.0062448 ]
		Model Seed: 10 Seed: 2 OOD calibration errors: [0.47377697 0.30632362 0.19749853 0.12245144 0.07572421 0.04541151
 0.02805666 0.01665384 0.01056179 0.00803966 0.00806812 0.01051614]
	Model Seed: 10 ID mean of (MSE, MAE): [722.8843   17.00613]
	Model Seed: 10 OOD mean of (MSE, MAE): [894.7717    19.085184]
	Model Seed: 10 ID median of (MSE, MAE): [186.22324   11.635117]
	Model Seed: 10 OOD median of (MSE, MAE): [241.7103    13.259407]
	Model Seed: 10 ID likelihoods: -10.210561455285916
	Model Seed: 10 OOD likelihoods: -10.316682717634457
	Model Seed: 10 ID calibration errors: [0.46176755 0.29539309 0.18669793 0.11879525 0.0730061  0.04326883
 0.02599477 0.01514588 0.00857351 0.00492552 0.00429635 0.00609419]
	Model Seed: 10 OOD calibration errors: [0.47512566 0.30375037 0.19059275 0.1179744  0.07160686 0.04234516
 0.02506202 0.01449763 0.00855656 0.00643877 0.00687088 0.00934713]
	Train: 425413 (68.73%)
	Val: 56593 (9.14%)
	Test: 72022 (11.64%)
	Test OOD: 64922 (10.49%)
	No scaling applied
		Model Seed: 11 Seed: 1 ID mean of (MSE, MAE): [726.4072    17.182001]
		Model Seed: 11 Seed: 1 OOD mean of (MSE, MAE) stats: [938.716     19.680893]
		Model Seed: 11 Seed: 1 ID median of (MSE, MAE): [197.92847   12.055372]
		Model Seed: 11 Seed: 1 OOD median of (MSE, MAE) stats: [251.28496   14.071078]
		Model Seed: 11 Seed: 1 ID likelihoods: -10.212994215135847
		Model Seed: 11 Seed: 1 OOD likelihoods: -10.341194571909673
		Model Seed: 11 Seed: 1 ID calibration errors: [0.45831839 0.28284722 0.17800445 0.10818139 0.0652484  0.03823123
 0.02260891 0.01275792 0.0068038  0.00388038 0.00389557 0.00585615]
		Model Seed: 11 Seed: 1 OOD calibration errors: [0.47715005 0.30016718 0.18023671 0.10639866 0.06363224 0.03693693
 0.02070306 0.01163    0.00628699 0.00498062 0.00588662 0.00864855]
	Train: 429990 (69.47%)
	Val: 56876 (9.19%)
	Test: 72378 (11.69%)
	Test OOD: 59706 (9.65%)
	No scaling applied
		Model Seed: 11 Seed: 2 ID mean of (MSE, MAE): [726.82623   16.940325]
		Model Seed: 11 Seed: 2 OOD mean of (MSE, MAE) stats: [854.1117    18.544317]
		Model Seed: 11 Seed: 2 ID median of (MSE, MAE): [182.9243    11.484718]
		Model Seed: 11 Seed: 2 OOD median of (MSE, MAE) stats: [227.51318   12.833356]
		Model Seed: 11 Seed: 2 ID likelihoods: -10.21328304575705
		Model Seed: 11 Seed: 2 OOD likelihoods: -10.293969770744425
		Model Seed: 11 Seed: 2 ID calibration errors: [0.46620268 0.30223096 0.19385731 0.12434129 0.07724612 0.04736405
 0.02841262 0.01665442 0.0097518  0.005484   0.00450887 0.00626254]
		Model Seed: 11 Seed: 2 OOD calibration errors: [0.47366088 0.30637611 0.19704151 0.12340076 0.07606884 0.04543033
 0.02823909 0.01681478 0.0105661  0.00782902 0.00789828 0.0103497 ]
	Model Seed: 11 ID mean of (MSE, MAE): [726.6167    17.061163]
	Model Seed: 11 OOD mean of (MSE, MAE): [896.4138    19.112606]
	Model Seed: 11 ID median of (MSE, MAE): [190.42639   11.770045]
	Model Seed: 11 OOD median of (MSE, MAE): [239.39908   13.452217]
	Model Seed: 11 ID likelihoods: -10.213138630446448
	Model Seed: 11 OOD likelihoods: -10.31758217132705
	Model Seed: 11 ID calibration errors: [0.46226054 0.29253909 0.18593088 0.11626134 0.07124726 0.04279764
 0.02551076 0.01470617 0.0082778  0.00468219 0.00420222 0.00605934]
	Model Seed: 11 OOD calibration errors: [0.47540547 0.30327164 0.18863911 0.11489971 0.06985054 0.04118363
 0.02447108 0.01422239 0.00842654 0.00640482 0.00689245 0.00949913]
	Train: 425413 (68.73%)
	Val: 56593 (9.14%)
	Test: 72022 (11.64%)
	Test OOD: 64922 (10.49%)
	No scaling applied
		Model Seed: 12 Seed: 1 ID mean of (MSE, MAE): [726.1253    17.177248]
		Model Seed: 12 Seed: 1 OOD mean of (MSE, MAE) stats: [937.911     19.677814]
		Model Seed: 12 Seed: 1 ID median of (MSE, MAE): [197.3599    12.045164]
		Model Seed: 12 Seed: 1 OOD median of (MSE, MAE) stats: [252.2018    14.101392]
		Model Seed: 12 Seed: 1 ID likelihoods: -10.212799663389013
		Model Seed: 12 Seed: 1 OOD likelihoods: -10.340766134894643
		Model Seed: 12 Seed: 1 ID calibration errors: [0.45824458 0.28185584 0.17811114 0.108056   0.06555344 0.03817122
 0.02239099 0.01270227 0.00664103 0.00377911 0.00385237 0.00579343]
		Model Seed: 12 Seed: 1 OOD calibration errors: [0.47654988 0.29903855 0.18017725 0.10698742 0.06388901 0.03712943
 0.02063746 0.01161582 0.00637172 0.00501069 0.00589772 0.00861806]
	Train: 429990 (69.47%)
	Val: 56876 (9.19%)
	Test: 72378 (11.69%)
	Test OOD: 59706 (9.65%)
	No scaling applied
		Model Seed: 12 Seed: 2 ID mean of (MSE, MAE): [725.70703   16.913704]
		Model Seed: 12 Seed: 2 OOD mean of (MSE, MAE) stats: [853.03436  18.53555]
		Model Seed: 12 Seed: 2 ID median of (MSE, MAE): [182.91733   11.471003]
		Model Seed: 12 Seed: 2 OOD median of (MSE, MAE) stats: [227.49658   12.835208]
		Model Seed: 12 Seed: 2 ID likelihoods: -10.212511983096913
		Model Seed: 12 Seed: 2 OOD likelihoods: -10.293339307468873
		Model Seed: 12 Seed: 2 ID calibration errors: [0.46584147 0.30302503 0.19328005 0.12500153 0.07755403 0.04772271
 0.02857347 0.01677386 0.00969964 0.00557227 0.00458556 0.00613822]
		Model Seed: 12 Seed: 2 OOD calibration errors: [0.47420116 0.3066667  0.19677599 0.12235493 0.07563303 0.04517745
 0.02766044 0.01646035 0.01024193 0.00777191 0.00786787 0.01026521]
	Model Seed: 12 ID mean of (MSE, MAE): [725.91614   17.045475]
	Model Seed: 12 OOD mean of (MSE, MAE): [895.47266   19.106682]
	Model Seed: 12 ID median of (MSE, MAE): [190.13861   11.758083]
	Model Seed: 12 OOD median of (MSE, MAE): [239.84918  13.4683 ]
	Model Seed: 12 ID likelihoods: -10.212655823242963
	Model Seed: 12 OOD likelihoods: -10.317052721181758
	Model Seed: 12 ID calibration errors: [0.46204302 0.29244043 0.18569559 0.11652877 0.07155373 0.04294697
 0.02548223 0.01473806 0.00817033 0.00467569 0.00421897 0.00596582]
	Model Seed: 12 OOD calibration errors: [0.47537552 0.30285263 0.18847662 0.11467117 0.06976102 0.04115344
 0.02414895 0.01403808 0.00830683 0.0063913  0.00688279 0.00944164]
	Train: 425413 (68.73%)
	Val: 56593 (9.14%)
	Test: 72022 (11.64%)
	Test OOD: 64922 (10.49%)
	No scaling applied
		Model Seed: 13 Seed: 1 ID mean of (MSE, MAE): [720.3341    17.073063]
		Model Seed: 13 Seed: 1 OOD mean of (MSE, MAE) stats: [935.23444   19.565657]
		Model Seed: 13 Seed: 1 ID median of (MSE, MAE): [191.89917  11.84922]
		Model Seed: 13 Seed: 1 OOD median of (MSE, MAE) stats: [254.46466   13.703044]
		Model Seed: 13 Seed: 1 ID likelihoods: -10.20879555300209
		Model Seed: 13 Seed: 1 OOD likelihoods: -10.339336202700377
		Model Seed: 13 Seed: 1 ID calibration errors: [0.45379913 0.28953623 0.18094975 0.11269759 0.06850988 0.04051211
 0.02351821 0.01300145 0.00720375 0.00399104 0.00376864 0.00574965]
		Model Seed: 13 Seed: 1 OOD calibration errors: [0.47182565 0.29984704 0.18866982 0.11490698 0.06895103 0.03996861
 0.02240075 0.01260853 0.0065324  0.00479468 0.00525849 0.00785116]
	Train: 429990 (69.47%)
	Val: 56876 (9.19%)
	Test: 72378 (11.69%)
	Test OOD: 59706 (9.65%)
	No scaling applied
		Model Seed: 13 Seed: 2 ID mean of (MSE, MAE): [725.2856    16.941118]
		Model Seed: 13 Seed: 2 OOD mean of (MSE, MAE) stats: [853.4612    18.513401]
		Model Seed: 13 Seed: 2 ID median of (MSE, MAE): [186.32239  11.6466 ]
		Model Seed: 13 Seed: 2 OOD median of (MSE, MAE) stats: [235.0731    13.037777]
		Model Seed: 13 Seed: 2 ID likelihoods: -10.212221107679923
		Model Seed: 13 Seed: 2 OOD likelihoods: -10.293587418874804
		Model Seed: 13 Seed: 2 ID calibration errors: [0.45819425 0.29987656 0.1915686  0.12239719 0.07636129 0.04712037
 0.02730343 0.01616061 0.00896787 0.00506041 0.004298   0.00556982]
		Model Seed: 13 Seed: 2 OOD calibration errors: [0.47046404 0.3068743  0.19580905 0.12171719 0.07436997 0.04491235
 0.02640694 0.01510259 0.00953697 0.00709418 0.00704253 0.0098694 ]
	Model Seed: 13 ID mean of (MSE, MAE): [722.8098    17.007092]
	Model Seed: 13 OOD mean of (MSE, MAE): [894.3478    19.039528]
	Model Seed: 13 ID median of (MSE, MAE): [189.11078  11.74791]
	Model Seed: 13 OOD median of (MSE, MAE): [244.76889   13.370411]
	Model Seed: 13 ID likelihoods: -10.210508330341007
	Model Seed: 13 OOD likelihoods: -10.31646181078759
	Model Seed: 13 ID calibration errors: [0.45599669 0.29470639 0.18625917 0.11754739 0.07243559 0.04381624
 0.02541082 0.01458103 0.00808581 0.00452572 0.00403332 0.00565973]
	Model Seed: 13 OOD calibration errors: [0.47114485 0.30336067 0.19223944 0.11831209 0.0716605  0.04244048
 0.02440385 0.01385556 0.00803468 0.00594443 0.00615051 0.00886028]
	Train: 425413 (68.73%)
	Val: 56593 (9.14%)
	Test: 72022 (11.64%)
	Test OOD: 64922 (10.49%)
	No scaling applied
		Model Seed: 14 Seed: 1 ID mean of (MSE, MAE): [725.4418    17.168081]
		Model Seed: 14 Seed: 1 OOD mean of (MSE, MAE) stats: [937.26      19.666872]
		Model Seed: 14 Seed: 1 ID median of (MSE, MAE): [196.64044   12.034254]
		Model Seed: 14 Seed: 1 OOD median of (MSE, MAE) stats: [250.5044   14.07618]
		Model Seed: 14 Seed: 1 ID likelihoods: -10.212329737791542
		Model Seed: 14 Seed: 1 OOD likelihoods: -10.340418705587277
		Model Seed: 14 Seed: 1 ID calibration errors: [0.45812584 0.28241545 0.178037   0.1084101  0.06578445 0.03846088
 0.02254212 0.01288143 0.00674717 0.00388955 0.00387482 0.00587184]
		Model Seed: 14 Seed: 1 OOD calibration errors: [0.47611988 0.29973184 0.18046565 0.10724816 0.06423484 0.03722357
 0.02085694 0.01174179 0.00642736 0.00505263 0.00592384 0.00864799]
	Train: 429990 (69.47%)
	Val: 56876 (9.19%)
	Test: 72378 (11.69%)
	Test OOD: 59706 (9.65%)
	No scaling applied
		Model Seed: 14 Seed: 2 ID mean of (MSE, MAE): [724.8883    16.904207]
		Model Seed: 14 Seed: 2 OOD mean of (MSE, MAE) stats: [854.7782   18.54014]
		Model Seed: 14 Seed: 2 ID median of (MSE, MAE): [182.40115   11.439161]
		Model Seed: 14 Seed: 2 OOD median of (MSE, MAE) stats: [228.64061   12.855728]
		Model Seed: 14 Seed: 2 ID likelihoods: -10.211948713409257
		Model Seed: 14 Seed: 2 OOD likelihoods: -10.294360613284436
		Model Seed: 14 Seed: 2 ID calibration errors: [0.46621917 0.30371738 0.19370302 0.12457133 0.07771194 0.04808816
 0.02870884 0.01685458 0.0098212  0.0056922  0.00475486 0.00628143]
		Model Seed: 14 Seed: 2 OOD calibration errors: [0.47413177 0.30641509 0.19686561 0.12246179 0.07582776 0.04542034
 0.02815923 0.01678778 0.0105378  0.00798036 0.00792926 0.01043917]
	Model Seed: 14 ID mean of (MSE, MAE): [725.16504   17.036144]
	Model Seed: 14 OOD mean of (MSE, MAE): [896.0191    19.103506]
	Model Seed: 14 ID median of (MSE, MAE): [189.5208    11.736708]
	Model Seed: 14 OOD median of (MSE, MAE): [239.57251   13.465954]
	Model Seed: 14 ID likelihoods: -10.2121392256004
	Model Seed: 14 OOD likelihoods: -10.317389659435857
	Model Seed: 14 ID calibration errors: [0.46217251 0.29306641 0.18587001 0.11649072 0.07174819 0.04327452
 0.02562548 0.01486801 0.00828419 0.00479087 0.00431484 0.00607663]
	Model Seed: 14 OOD calibration errors: [0.47512582 0.30307346 0.18866563 0.11485497 0.0700313  0.04132195
 0.02450808 0.01426478 0.00848258 0.00651649 0.00692655 0.00954358]
	Train: 425413 (68.73%)
	Val: 56593 (9.14%)
	Test: 72022 (11.64%)
	Test OOD: 64922 (10.49%)
	No scaling applied
		Model Seed: 15 Seed: 1 ID mean of (MSE, MAE): [719.4775    17.022545]
		Model Seed: 15 Seed: 1 OOD mean of (MSE, MAE) stats: [924.83673   19.454428]
		Model Seed: 15 Seed: 1 ID median of (MSE, MAE): [190.35675   11.755672]
		Model Seed: 15 Seed: 1 OOD median of (MSE, MAE) stats: [258.8773    13.844628]
		Model Seed: 15 Seed: 1 ID likelihoods: -10.2082012722447
		Model Seed: 15 Seed: 1 OOD likelihoods: -10.333746777658604
		Model Seed: 15 Seed: 1 ID calibration errors: [0.42788959 0.28731751 0.18681625 0.1161184  0.07322527 0.0428933
 0.02567337 0.01446855 0.00752159 0.00397959 0.00328594 0.0049393 ]
		Model Seed: 15 Seed: 1 OOD calibration errors: [0.44352393 0.30027156 0.18783477 0.1162275  0.06878128 0.04044149
 0.02151252 0.01086212 0.00520808 0.00325625 0.00382904 0.00672758]
	Train: 429990 (69.47%)
	Val: 56876 (9.19%)
	Test: 72378 (11.69%)
	Test OOD: 59706 (9.65%)
	No scaling applied
		Model Seed: 15 Seed: 2 ID mean of (MSE, MAE): [717.4147    16.969412]
		Model Seed: 15 Seed: 2 OOD mean of (MSE, MAE) stats: [833.07825   18.382593]
		Model Seed: 15 Seed: 2 ID median of (MSE, MAE): [185.84056   11.630439]
		Model Seed: 15 Seed: 2 OOD median of (MSE, MAE) stats: [227.44344   12.911064]
		Model Seed: 15 Seed: 2 ID likelihoods: -10.206766562975544
		Model Seed: 15 Seed: 2 OOD likelihoods: -10.28150209931744
		Model Seed: 15 Seed: 2 ID calibration errors: [0.43660263 0.28999097 0.18201831 0.11381361 0.069486   0.04369899
 0.02600245 0.01594298 0.00849017 0.00464555 0.00368655 0.00519623]
		Model Seed: 15 Seed: 2 OOD calibration errors: [0.44532515 0.30203679 0.19077993 0.11977793 0.07218776 0.04272872
 0.02304712 0.01298313 0.00690673 0.0045178  0.00504901 0.0075677 ]
	Model Seed: 15 ID mean of (MSE, MAE): [718.44604  16.99598]
	Model Seed: 15 OOD mean of (MSE, MAE): [878.9575   18.91851]
	Model Seed: 15 ID median of (MSE, MAE): [188.09866   11.693056]
	Model Seed: 15 OOD median of (MSE, MAE): [243.16037   13.377846]
	Model Seed: 15 ID likelihoods: -10.207483917610123
	Model Seed: 15 OOD likelihoods: -10.307624438488022
	Model Seed: 15 ID calibration errors: [0.43224611 0.28865424 0.18441728 0.114966   0.07135564 0.04329614
 0.02583791 0.01520576 0.00800588 0.00431257 0.00348624 0.00506776]
	Model Seed: 15 OOD calibration errors: [0.44442454 0.30115418 0.18930735 0.11800271 0.07048452 0.04158511
 0.02227982 0.01192262 0.00605741 0.00388703 0.00443902 0.00714764]
	Train: 425413 (68.73%)
	Val: 56593 (9.14%)
	Test: 72022 (11.64%)
	Test OOD: 64922 (10.49%)
	No scaling applied
		Model Seed: 16 Seed: 1 ID mean of (MSE, MAE): [725.4415    17.168081]
		Model Seed: 16 Seed: 1 OOD mean of (MSE, MAE) stats: [937.25995  19.66687]
		Model Seed: 16 Seed: 1 ID median of (MSE, MAE): [196.64044   12.034254]
		Model Seed: 16 Seed: 1 OOD median of (MSE, MAE) stats: [250.50398   14.076165]
		Model Seed: 16 Seed: 1 ID likelihoods: -10.212329737791542
		Model Seed: 16 Seed: 1 OOD likelihoods: -10.340418705587277
		Model Seed: 16 Seed: 1 ID calibration errors: [0.45812584 0.28241545 0.178037   0.1084101  0.06578445 0.03846088
 0.02254212 0.01288143 0.00674717 0.00388955 0.00387482 0.00587184]
		Model Seed: 16 Seed: 1 OOD calibration errors: [0.47611988 0.29973184 0.18046565 0.10724816 0.06423484 0.03722357
 0.02085694 0.01174179 0.00642736 0.00505263 0.00592384 0.00864799]
	Train: 429990 (69.47%)
	Val: 56876 (9.19%)
	Test: 72378 (11.69%)
	Test OOD: 59706 (9.65%)
	No scaling applied
		Model Seed: 16 Seed: 2 ID mean of (MSE, MAE): [725.6094    16.911566]
		Model Seed: 16 Seed: 2 OOD mean of (MSE, MAE) stats: [853.0701    18.537104]
		Model Seed: 16 Seed: 2 ID median of (MSE, MAE): [182.87634   11.467894]
		Model Seed: 16 Seed: 2 OOD median of (MSE, MAE) stats: [227.7639    12.835624]
		Model Seed: 16 Seed: 2 ID likelihoods: -10.21244477919707
		Model Seed: 16 Seed: 2 OOD likelihoods: -10.293360199783947
		Model Seed: 16 Seed: 2 ID calibration errors: [0.46595695 0.30322734 0.19374311 0.12482846 0.07792227 0.04781834
 0.0286281  0.01674992 0.00973241 0.00559584 0.00461608 0.00615929]
		Model Seed: 16 Seed: 2 OOD calibration errors: [0.47392517 0.30608735 0.19658012 0.12192809 0.07550203 0.04517301
 0.02776514 0.01650164 0.01034194 0.00779629 0.00787901 0.0102705 ]
	Model Seed: 16 ID mean of (MSE, MAE): [725.52545   17.039824]
	Model Seed: 16 OOD mean of (MSE, MAE): [895.16504   19.101986]
	Model Seed: 16 ID median of (MSE, MAE): [189.75839   11.751074]
	Model Seed: 16 OOD median of (MSE, MAE): [239.13394   13.455894]
	Model Seed: 16 ID likelihoods: -10.212387258494307
	Model Seed: 16 OOD likelihoods: -10.316889452685611
	Model Seed: 16 ID calibration errors: [0.46204139 0.2928214  0.18589005 0.11661928 0.07185336 0.04313961
 0.02558511 0.01481568 0.00823979 0.00474269 0.00424545 0.00601556]
	Model Seed: 16 OOD calibration errors: [0.47502253 0.30290959 0.18852289 0.11458812 0.06986843 0.04119829
 0.02431104 0.01412172 0.00838465 0.00642446 0.00690143 0.00945924]
	Train: 425413 (68.73%)
	Val: 56593 (9.14%)
	Test: 72022 (11.64%)
	Test OOD: 64922 (10.49%)
	No scaling applied
		Model Seed: 17 Seed: 1 ID mean of (MSE, MAE): [721.9826    17.100615]
		Model Seed: 17 Seed: 1 OOD mean of (MSE, MAE) stats: [938.4871    19.629356]
		Model Seed: 17 Seed: 1 ID median of (MSE, MAE): [189.4672    11.768888]
		Model Seed: 17 Seed: 1 OOD median of (MSE, MAE) stats: [253.23723   13.667642]
		Model Seed: 17 Seed: 1 ID likelihoods: -10.209939436515594
		Model Seed: 17 Seed: 1 OOD likelihoods: -10.34107241712468
		Model Seed: 17 Seed: 1 ID calibration errors: [0.45803449 0.28551768 0.17987726 0.11223903 0.06837751 0.04070448
 0.02356227 0.01354936 0.00747414 0.00441435 0.00423107 0.00611498]
		Model Seed: 17 Seed: 1 OOD calibration errors: [0.47734582 0.30115525 0.18436178 0.11336219 0.06828186 0.03984832
 0.02214621 0.0120881  0.00652875 0.00483445 0.00550229 0.00828287]
	Train: 429990 (69.47%)
	Val: 56876 (9.19%)
	Test: 72378 (11.69%)
	Test OOD: 59706 (9.65%)
	No scaling applied
		Model Seed: 17 Seed: 2 ID mean of (MSE, MAE): [725.6094    16.911566]
		Model Seed: 17 Seed: 2 OOD mean of (MSE, MAE) stats: [853.0701    18.537104]
		Model Seed: 17 Seed: 2 ID median of (MSE, MAE): [182.87634   11.467894]
		Model Seed: 17 Seed: 2 OOD median of (MSE, MAE) stats: [227.7639    12.835624]
		Model Seed: 17 Seed: 2 ID likelihoods: -10.21244477919707
		Model Seed: 17 Seed: 2 OOD likelihoods: -10.293360199783947
		Model Seed: 17 Seed: 2 ID calibration errors: [0.46595695 0.30322734 0.19374311 0.12482846 0.07792227 0.04781834
 0.0286281  0.01674992 0.00973241 0.00559584 0.00461608 0.00615929]
		Model Seed: 17 Seed: 2 OOD calibration errors: [0.47392517 0.30608735 0.19658012 0.12192809 0.07550203 0.04517301
 0.02776514 0.01650164 0.01034194 0.00779629 0.00787901 0.0102705 ]
	Model Seed: 17 ID mean of (MSE, MAE): [723.796    17.00609]
	Model Seed: 17 OOD mean of (MSE, MAE): [895.7786   19.08323]
	Model Seed: 17 ID median of (MSE, MAE): [186.17177   11.618391]
	Model Seed: 17 OOD median of (MSE, MAE): [240.50056   13.251633]
	Model Seed: 17 ID likelihoods: -10.21119210785633
	Model Seed: 17 OOD likelihoods: -10.317216308454313
	Model Seed: 17 ID calibration errors: [0.46199572 0.29437251 0.18681019 0.11853374 0.07314989 0.04426141
 0.02609518 0.01514964 0.00860328 0.0050051  0.00442357 0.00613713]
	Model Seed: 17 OOD calibration errors: [0.47563549 0.3036213  0.19047095 0.11764514 0.07189194 0.04251066
 0.02495567 0.01429487 0.00843534 0.00631537 0.00669065 0.00927668]
	Train: 425413 (68.73%)
	Val: 56593 (9.14%)
	Test: 72022 (11.64%)
	Test OOD: 64922 (10.49%)
	No scaling applied
		Model Seed: 18 Seed: 1 ID mean of (MSE, MAE): [725.4415    17.168081]
		Model Seed: 18 Seed: 1 OOD mean of (MSE, MAE) stats: [937.25995  19.66687]
		Model Seed: 18 Seed: 1 ID median of (MSE, MAE): [196.64044   12.034254]
		Model Seed: 18 Seed: 1 OOD median of (MSE, MAE) stats: [250.50398   14.076165]
		Model Seed: 18 Seed: 1 ID likelihoods: -10.212329737791542
		Model Seed: 18 Seed: 1 OOD likelihoods: -10.340418705587277
		Model Seed: 18 Seed: 1 ID calibration errors: [0.45812584 0.28241545 0.178037   0.1084101  0.06578445 0.03846088
 0.02254212 0.01288143 0.00674717 0.00388955 0.00387482 0.00587184]
		Model Seed: 18 Seed: 1 OOD calibration errors: [0.47611988 0.29973184 0.18046565 0.10724816 0.06423484 0.03722357
 0.02085694 0.01174179 0.00642736 0.00505263 0.00592384 0.00864799]
	Train: 429990 (69.47%)
	Val: 56876 (9.19%)
	Test: 72378 (11.69%)
	Test OOD: 59706 (9.65%)
	No scaling applied
		Model Seed: 18 Seed: 2 ID mean of (MSE, MAE): [725.6094    16.911566]
		Model Seed: 18 Seed: 2 OOD mean of (MSE, MAE) stats: [853.0701    18.537104]
		Model Seed: 18 Seed: 2 ID median of (MSE, MAE): [182.87634   11.467894]
		Model Seed: 18 Seed: 2 OOD median of (MSE, MAE) stats: [227.7639    12.835624]
		Model Seed: 18 Seed: 2 ID likelihoods: -10.21244477919707
		Model Seed: 18 Seed: 2 OOD likelihoods: -10.293360199783947
		Model Seed: 18 Seed: 2 ID calibration errors: [0.46595695 0.30322734 0.19374311 0.12482846 0.07792227 0.04781834
 0.0286281  0.01674992 0.00973241 0.00559584 0.00461608 0.00615929]
		Model Seed: 18 Seed: 2 OOD calibration errors: [0.47392517 0.30608735 0.19658012 0.12192809 0.07550203 0.04517301
 0.02776514 0.01650164 0.01034194 0.00779629 0.00787901 0.0102705 ]
	Model Seed: 18 ID mean of (MSE, MAE): [725.52545   17.039824]
	Model Seed: 18 OOD mean of (MSE, MAE): [895.16504   19.101986]
	Model Seed: 18 ID median of (MSE, MAE): [189.75839   11.751074]
	Model Seed: 18 OOD median of (MSE, MAE): [239.13394   13.455894]
	Model Seed: 18 ID likelihoods: -10.212387258494307
	Model Seed: 18 OOD likelihoods: -10.316889452685611
	Model Seed: 18 ID calibration errors: [0.46204139 0.2928214  0.18589005 0.11661928 0.07185336 0.04313961
 0.02558511 0.01481568 0.00823979 0.00474269 0.00424545 0.00601556]
	Model Seed: 18 OOD calibration errors: [0.47502253 0.30290959 0.18852289 0.11458812 0.06986843 0.04119829
 0.02431104 0.01412172 0.00838465 0.00642446 0.00690143 0.00945924]
	Train: 425413 (68.73%)
	Val: 56593 (9.14%)
	Test: 72022 (11.64%)
	Test OOD: 64922 (10.49%)
	No scaling applied
		Model Seed: 19 Seed: 1 ID mean of (MSE, MAE): [709.7468    17.104698]
		Model Seed: 19 Seed: 1 OOD mean of (MSE, MAE) stats: [913.7649   19.57194]
		Model Seed: 19 Seed: 1 ID median of (MSE, MAE): [196.72046   12.494246]
		Model Seed: 19 Seed: 1 OOD median of (MSE, MAE) stats: [271.44528   14.148339]
		Model Seed: 19 Seed: 1 ID likelihoods: -10.201392007032844
		Model Seed: 19 Seed: 1 OOD likelihoods: -10.327725521799964
		Model Seed: 19 Seed: 1 ID calibration errors: [0.4191477  0.29153365 0.17594503 0.10439777 0.06043844 0.03523798
 0.01868011 0.01036548 0.00492319 0.00224998 0.00268916 0.00479088]
		Model Seed: 19 Seed: 1 OOD calibration errors: [0.43368142 0.29853643 0.17760286 0.11002262 0.06286513 0.03653278
 0.0195239  0.00933951 0.00462199 0.00368882 0.00517952 0.00792902]
	Train: 429990 (69.47%)
	Val: 56876 (9.19%)
	Test: 72378 (11.69%)
	Test OOD: 59706 (9.65%)
	No scaling applied
		Model Seed: 19 Seed: 2 ID mean of (MSE, MAE): [708.9955   16.88123]
		Model Seed: 19 Seed: 2 OOD mean of (MSE, MAE) stats: [825.79156  18.37316]
		Model Seed: 19 Seed: 2 ID median of (MSE, MAE): [196.67972   11.949055]
		Model Seed: 19 Seed: 2 OOD median of (MSE, MAE) stats: [227.18011   13.349719]
		Model Seed: 19 Seed: 2 ID likelihoods: -10.20086311126908
		Model Seed: 19 Seed: 2 OOD likelihoods: -10.277109917477997
		Model Seed: 19 Seed: 2 ID calibration errors: [0.42964706 0.30088132 0.18821389 0.11435052 0.07035525 0.04269264
 0.02414849 0.01364605 0.00710554 0.00370871 0.00311545 0.00477784]
		Model Seed: 19 Seed: 2 OOD calibration errors: [0.43540767 0.30405534 0.1887586  0.11427819 0.06684514 0.03974364
 0.02087238 0.01089315 0.00545901 0.00328187 0.00413388 0.00697787]
	Model Seed: 19 ID mean of (MSE, MAE): [709.37115   16.992964]
	Model Seed: 19 OOD mean of (MSE, MAE): [869.7782   18.97255]
	Model Seed: 19 ID median of (MSE, MAE): [196.70009  12.22165]
	Model Seed: 19 OOD median of (MSE, MAE): [249.3127    13.749029]
	Model Seed: 19 ID likelihoods: -10.201127559150962
	Model Seed: 19 OOD likelihoods: -10.302417719638981
	Model Seed: 19 ID calibration errors: [0.42439738 0.29620749 0.18207946 0.10937415 0.06539685 0.03896531
 0.0214143  0.01200576 0.00601436 0.00297935 0.0029023  0.00478436]
	Model Seed: 19 OOD calibration errors: [0.43454454 0.30129589 0.18318073 0.1121504  0.06485514 0.03813821
 0.02019814 0.01011633 0.0050405  0.00348535 0.0046567  0.00745344]
ID mean of (MSE, MAE): [722.6055908203125, 17.023069381713867] +- [4.946102142333984, 0.02270732820034027] +- [0.465603  0.1043588] 
OOD mean of (MSE, MAE): [891.1868896484375, 19.062578201293945] +- [8.674711227416992, 0.0628955066204071] +- [42.5208      0.55899675] 
ID median of (MSE, MAE): [189.59071350097656, 11.768311500549316] +- [2.776482105255127, 0.15922099351882935] +- [4.7135285 0.2214791] 
OOD median of (MSE, MAE): [241.65414428710938, 13.430658340454102] +- [3.119887113571167, 0.13174113631248474] +- [13.21241     0.51370328] 
ID likelihoods: -10.210358156652275 +- 0.003444438398859087 +- 0.0003210791853742734 
OOD likelihoods: -10.314620645231924 +- 0.004948594214666578 +- 0.023882298056444817 
ID calibration errors: [0.4546962298224567, 0.2933022450094289, 0.18555406197085336, 0.11617359206903836, 0.0713599957603496, 0.04289062854141763, 0.025254166349255664, 0.014603167655597871, 0.008049474812465447, 0.004538239154882695, 0.00403687206905721, 0.005787610822265937] +- [0.013423849570773925, 0.001984345820281108, 0.001312866629525007, 0.002503061205130639, 0.0020812781892919794, 0.0013687439149709388, 0.0012977077768399842, 0.0008884011608858844, 0.0007014610153146296, 0.0005510174596900194, 0.00045078727206459857, 0.0004527984487050512] +- [0.00395808 0.00801097 0.00628086 0.00628383 0.00469321 0.0038797
 0.00248931 0.00170236 0.00123257 0.00071671 0.00030719 0.00010726] 
OOD calibration errors: [0.4676826949962137, 0.3028199320965946, 0.18886183499228665, 0.11576868553913773, 0.06998786855209689, 0.04130752144448608, 0.023864968700699804, 0.01354557102849796, 0.00781097407158228, 0.00582324807911023, 0.006331241942966484, 0.008948800664400517] +- [0.014323677121980322, 0.0008475389025081918, 0.0022345747987155165, 0.0019626514848066104, 0.0018904138800965617, 0.0011829042157283315, 0.0014188321148059665, 0.001335642713898669, 0.0011610500926656905, 0.0010823532057990652, 0.0009198602423155272, 0.0008470472121272129] +- [0.00080838 0.00288107 0.00646512 0.00545396 0.00432841 0.00312681
 0.00270876 0.00197448 0.00167264 0.00116712 0.00083136 0.00073087] 
