--------------------------------
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)
		fast_insulin: REAL_VALUED (OBSERVED_INPUT)
		slow_insulin: REAL_VALUED (OBSERVED_INPUT)
		calories: REAL_VALUED (OBSERVED_INPUT)
		balance: REAL_VALUED (OBSERVED_INPUT)
		quality: REAL_VALUED (OBSERVED_INPUT)
		HR: REAL_VALUED (OBSERVED_INPUT)
		BR: REAL_VALUED (OBSERVED_INPUT)
		Posture: REAL_VALUED (OBSERVED_INPUT)
		Activity: REAL_VALUED (OBSERVED_INPUT)
		HRV: REAL_VALUED (OBSERVED_INPUT)
		CoreTemp: REAL_VALUED (OBSERVED_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: 1
	Extracted segments: 8
	Interpolated values: 0
	Percent of values interpolated: 0.00%
Splitting data...
	Train: 3975 (60.09%)
	Val: 1440 (21.77%)
	Test: 2340 (35.37%)
Scaling data...
	No scaling applied
Data formatting complete.
--------------------------------
Current value: 0.09210898727178574, Current params: {'in_len': 60, 'max_samples_per_ts': 50, 'lr': 0.867, 'subsample': 0.9, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 8, 'gamma': 9.0, 'alpha': 0.032, 'lambda_': 0.113, 'n_estimators': 416}
Best value: 0.09210898727178574, Best params: {'in_len': 60, 'max_samples_per_ts': 50, 'lr': 0.867, 'subsample': 0.9, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 8, 'gamma': 9.0, 'alpha': 0.032, 'lambda_': 0.113, 'n_estimators': 416}
Current value: 0.1499626785516739, Current params: {'in_len': 192, 'max_samples_per_ts': 100, 'lr': 0.9550000000000001, 'subsample': 0.8, 'min_child_weight': 2.0, 'colsample_bytree': 1.0, 'max_depth': 6, 'gamma': 9.5, 'alpha': 0.049, 'lambda_': 0.28400000000000003, 'n_estimators': 384}
Best value: 0.09210898727178574, Best params: {'in_len': 60, 'max_samples_per_ts': 50, 'lr': 0.867, 'subsample': 0.9, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 8, 'gamma': 9.0, 'alpha': 0.032, 'lambda_': 0.113, 'n_estimators': 416}
Current value: 0.10175923258066177, Current params: {'in_len': 180, 'max_samples_per_ts': 200, 'lr': 0.8160000000000001, 'subsample': 0.9, 'min_child_weight': 3.0, 'colsample_bytree': 1.0, 'max_depth': 8, 'gamma': 5.5, 'alpha': 0.28900000000000003, 'lambda_': 0.013000000000000001, 'n_estimators': 320}
Best value: 0.09210898727178574, Best params: {'in_len': 60, 'max_samples_per_ts': 50, 'lr': 0.867, 'subsample': 0.9, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 8, 'gamma': 9.0, 'alpha': 0.032, 'lambda_': 0.113, 'n_estimators': 416}
Current value: 0.09818428009748459, Current params: {'in_len': 60, 'max_samples_per_ts': 150, 'lr': 0.486, 'subsample': 0.7, 'min_child_weight': 3.0, 'colsample_bytree': 0.8, 'max_depth': 7, 'gamma': 7.5, 'alpha': 0.017, 'lambda_': 0.109, 'n_estimators': 288}
Best value: 0.09210898727178574, Best params: {'in_len': 60, 'max_samples_per_ts': 50, 'lr': 0.867, 'subsample': 0.9, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 8, 'gamma': 9.0, 'alpha': 0.032, 'lambda_': 0.113, 'n_estimators': 416}
Current value: 0.12401106208562851, Current params: {'in_len': 84, 'max_samples_per_ts': 100, 'lr': 0.229, 'subsample': 1.0, 'min_child_weight': 1.0, 'colsample_bytree': 1.0, 'max_depth': 8, 'gamma': 3.5, 'alpha': 0.035, 'lambda_': 0.041, 'n_estimators': 448}
Best value: 0.09210898727178574, Best params: {'in_len': 60, 'max_samples_per_ts': 50, 'lr': 0.867, 'subsample': 0.9, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 8, 'gamma': 9.0, 'alpha': 0.032, 'lambda_': 0.113, 'n_estimators': 416}
Current value: 0.15309222042560577, Current params: {'in_len': 180, 'max_samples_per_ts': 150, 'lr': 0.203, 'subsample': 0.7, 'min_child_weight': 3.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 8.0, 'alpha': 0.259, 'lambda_': 0.151, 'n_estimators': 416}
Best value: 0.09210898727178574, Best params: {'in_len': 60, 'max_samples_per_ts': 50, 'lr': 0.867, 'subsample': 0.9, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 8, 'gamma': 9.0, 'alpha': 0.032, 'lambda_': 0.113, 'n_estimators': 416}
Current value: 0.09440058469772339, Current params: {'in_len': 180, 'max_samples_per_ts': 100, 'lr': 0.6960000000000001, 'subsample': 0.8, 'min_child_weight': 4.0, 'colsample_bytree': 1.0, 'max_depth': 10, 'gamma': 5.0, 'alpha': 0.211, 'lambda_': 0.20400000000000001, 'n_estimators': 288}
Best value: 0.09210898727178574, Best params: {'in_len': 60, 'max_samples_per_ts': 50, 'lr': 0.867, 'subsample': 0.9, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 8, 'gamma': 9.0, 'alpha': 0.032, 'lambda_': 0.113, 'n_estimators': 416}
Current value: 0.1083349660038948, Current params: {'in_len': 132, 'max_samples_per_ts': 200, 'lr': 0.982, 'subsample': 0.7, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 7, 'gamma': 7.0, 'alpha': 0.031, 'lambda_': 0.033, 'n_estimators': 480}
Best value: 0.09210898727178574, Best params: {'in_len': 60, 'max_samples_per_ts': 50, 'lr': 0.867, 'subsample': 0.9, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 8, 'gamma': 9.0, 'alpha': 0.032, 'lambda_': 0.113, 'n_estimators': 416}
Current value: 0.1681949943304062, Current params: {'in_len': 192, 'max_samples_per_ts': 150, 'lr': 0.23700000000000002, 'subsample': 1.0, 'min_child_weight': 1.0, 'colsample_bytree': 0.8, 'max_depth': 4, 'gamma': 9.0, 'alpha': 0.14200000000000002, 'lambda_': 0.10400000000000001, 'n_estimators': 352}
Best value: 0.09210898727178574, Best params: {'in_len': 60, 'max_samples_per_ts': 50, 'lr': 0.867, 'subsample': 0.9, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 8, 'gamma': 9.0, 'alpha': 0.032, 'lambda_': 0.113, 'n_estimators': 416}
Current value: 0.09714937955141068, Current params: {'in_len': 60, 'max_samples_per_ts': 50, 'lr': 0.016, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.9, 'max_depth': 4, 'gamma': 1.5, 'alpha': 0.053000000000000005, 'lambda_': 0.02, 'n_estimators': 512}
Best value: 0.09210898727178574, Best params: {'in_len': 60, 'max_samples_per_ts': 50, 'lr': 0.867, 'subsample': 0.9, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 8, 'gamma': 9.0, 'alpha': 0.032, 'lambda_': 0.113, 'n_estimators': 416}
Current value: 0.08361048251390457, Current params: {'in_len': 24, 'max_samples_per_ts': 50, 'lr': 0.587, 'subsample': 0.6, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 10.0, 'alpha': 0.14100000000000001, 'lambda_': 0.215, 'n_estimators': 416}
Best value: 0.08361048251390457, Best params: {'in_len': 24, 'max_samples_per_ts': 50, 'lr': 0.587, 'subsample': 0.6, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 10.0, 'alpha': 0.14100000000000001, 'lambda_': 0.215, 'n_estimators': 416}
Current value: 0.08374150842428207, Current params: {'in_len': 24, 'max_samples_per_ts': 50, 'lr': 0.584, 'subsample': 0.6, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 10.0, 'alpha': 0.114, 'lambda_': 0.219, 'n_estimators': 416}
Best value: 0.08361048251390457, Best params: {'in_len': 24, 'max_samples_per_ts': 50, 'lr': 0.587, 'subsample': 0.6, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 10.0, 'alpha': 0.14100000000000001, 'lambda_': 0.215, 'n_estimators': 416}
Current value: 0.09982475638389587, Current params: {'in_len': 24, 'max_samples_per_ts': 50, 'lr': 0.536, 'subsample': 0.6, 'min_child_weight': 5.0, 'colsample_bytree': 0.9, 'max_depth': 10, 'gamma': 10.0, 'alpha': 0.123, 'lambda_': 0.244, 'n_estimators': 384}
Best value: 0.08361048251390457, Best params: {'in_len': 24, 'max_samples_per_ts': 50, 'lr': 0.587, 'subsample': 0.6, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 10.0, 'alpha': 0.14100000000000001, 'lambda_': 0.215, 'n_estimators': 416}
Current value: 0.07605191320180893, Current params: {'in_len': 24, 'max_samples_per_ts': 50, 'lr': 0.585, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 6.0, 'alpha': 0.1, 'lambda_': 0.203, 'n_estimators': 448}
Best value: 0.07605191320180893, Best params: {'in_len': 24, 'max_samples_per_ts': 50, 'lr': 0.585, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 6.0, 'alpha': 0.1, 'lambda_': 0.203, 'n_estimators': 448}
Current value: 0.0750429555773735, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.661, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.186, 'lambda_': 0.181, 'n_estimators': 480}
Best value: 0.0750429555773735, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.661, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.186, 'lambda_': 0.181, 'n_estimators': 480}
Current value: 0.08356675505638123, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'lr': 0.718, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.9, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.193, 'lambda_': 0.163, 'n_estimators': 512}
Best value: 0.0750429555773735, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.661, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.186, 'lambda_': 0.181, 'n_estimators': 480}
Current value: 0.07940604537725449, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.361, 'subsample': 0.7, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 3.0, 'alpha': 0.094, 'lambda_': 0.177, 'n_estimators': 480}
Best value: 0.0750429555773735, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.661, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.186, 'lambda_': 0.181, 'n_estimators': 480}
Current value: 0.10010790079832077, Current params: {'in_len': 96, 'max_samples_per_ts': 100, 'lr': 0.439, 'subsample': 0.6, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 9, 'gamma': 5.5, 'alpha': 0.185, 'lambda_': 0.299, 'n_estimators': 480}
Best value: 0.0750429555773735, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.661, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.186, 'lambda_': 0.181, 'n_estimators': 480}
Current value: 0.09497019648551941, Current params: {'in_len': 156, 'max_samples_per_ts': 50, 'lr': 0.7030000000000001, 'subsample': 0.7, 'min_child_weight': 3.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 4.0, 'alpha': 0.082, 'lambda_': 0.257, 'n_estimators': 448}
Best value: 0.0750429555773735, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.661, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.186, 'lambda_': 0.181, 'n_estimators': 480}
Current value: 0.09620034694671631, Current params: {'in_len': 84, 'max_samples_per_ts': 100, 'lr': 0.357, 'subsample': 0.8, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 7, 'gamma': 1.5, 'alpha': 0.169, 'lambda_': 0.187, 'n_estimators': 448}
Best value: 0.0750429555773735, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.661, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.186, 'lambda_': 0.181, 'n_estimators': 480}
Current value: 0.10561442375183105, Current params: {'in_len': 156, 'max_samples_per_ts': 50, 'lr': 0.792, 'subsample': 0.6, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 9, 'gamma': 6.5, 'alpha': 0.23, 'lambda_': 0.132, 'n_estimators': 256}
Best value: 0.0750429555773735, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.661, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.186, 'lambda_': 0.181, 'n_estimators': 480}
Current value: 0.07955505698919296, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.353, 'subsample': 0.7, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 3.0, 'alpha': 0.08, 'lambda_': 0.171, 'n_estimators': 480}
Best value: 0.0750429555773735, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.661, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.186, 'lambda_': 0.181, 'n_estimators': 480}
Current value: 0.0858198031783104, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'lr': 0.631, 'subsample': 0.7, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 2.5, 'alpha': 0.10300000000000001, 'lambda_': 0.188, 'n_estimators': 512}
Best value: 0.0750429555773735, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.661, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.186, 'lambda_': 0.181, 'n_estimators': 480}
Current value: 0.07962562888860703, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'lr': 0.125, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 8, 'gamma': 0.5, 'alpha': 0.083, 'lambda_': 0.074, 'n_estimators': 480}
Best value: 0.0750429555773735, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.661, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.186, 'lambda_': 0.181, 'n_estimators': 480}
Current value: 0.09917699545621872, Current params: {'in_len': 108, 'max_samples_per_ts': 100, 'lr': 0.385, 'subsample': 0.7, 'min_child_weight': 3.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 4.5, 'alpha': 0.162, 'lambda_': 0.225, 'n_estimators': 448}
Best value: 0.0750429555773735, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.661, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.186, 'lambda_': 0.181, 'n_estimators': 480}
Current value: 0.07695286720991135, Current params: {'in_len': 84, 'max_samples_per_ts': 50, 'lr': 0.46900000000000003, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 2.0, 'alpha': 0.127, 'lambda_': 0.136, 'n_estimators': 480}
Best value: 0.0750429555773735, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.661, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.186, 'lambda_': 0.181, 'n_estimators': 480}
Current value: 0.0903114303946495, Current params: {'in_len': 72, 'max_samples_per_ts': 100, 'lr': 0.47500000000000003, 'subsample': 0.6, 'min_child_weight': 3.0, 'colsample_bytree': 0.9, 'max_depth': 10, 'gamma': 2.0, 'alpha': 0.13, 'lambda_': 0.14, 'n_estimators': 512}
Best value: 0.0750429555773735, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'lr': 0.661, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.186, 'lambda_': 0.181, 'n_estimators': 480}
Current value: 0.07394475489854813, Current params: {'in_len': 48, 'max_samples_per_ts': 50, 'lr': 0.636, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 1.0, 'alpha': 0.24000000000000002, 'lambda_': 0.078, 'n_estimators': 448}
Best value: 0.07394475489854813, Best params: {'in_len': 48, 'max_samples_per_ts': 50, 'lr': 0.636, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 1.0, 'alpha': 0.24000000000000002, 'lambda_': 0.078, 'n_estimators': 448}
Current value: 0.08029846101999283, Current params: {'in_len': 36, 'max_samples_per_ts': 150, 'lr': 0.664, 'subsample': 0.6, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 5, 'gamma': 1.0, 'alpha': 0.245, 'lambda_': 0.067, 'n_estimators': 384}
Best value: 0.07394475489854813, Best params: {'in_len': 48, 'max_samples_per_ts': 50, 'lr': 0.636, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 1.0, 'alpha': 0.24000000000000002, 'lambda_': 0.078, 'n_estimators': 448}
Current value: 0.08203523606061935, Current params: {'in_len': 48, 'max_samples_per_ts': 50, 'lr': 0.773, 'subsample': 0.8, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 8, 'gamma': 6.0, 'alpha': 0.276, 'lambda_': 0.08800000000000001, 'n_estimators': 416}
Best value: 0.07394475489854813, Best params: {'in_len': 48, 'max_samples_per_ts': 50, 'lr': 0.636, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 1.0, 'alpha': 0.24000000000000002, 'lambda_': 0.078, 'n_estimators': 448}
Current value: 0.09008447080850601, Current params: {'in_len': 48, 'max_samples_per_ts': 50, 'lr': 0.895, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.9, 'max_depth': 8, 'gamma': 8.5, 'alpha': 0.21, 'lambda_': 0.253, 'n_estimators': 352}
Best value: 0.07394475489854813, Best params: {'in_len': 48, 'max_samples_per_ts': 50, 'lr': 0.636, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 1.0, 'alpha': 0.24000000000000002, 'lambda_': 0.078, 'n_estimators': 448}
Current value: 0.0735437348484993, Current params: {'in_len': 48, 'max_samples_per_ts': 50, 'lr': 0.543, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 1.5, 'alpha': 0.164, 'lambda_': 0.123, 'n_estimators': 448}
Best value: 0.0735437348484993, Best params: {'in_len': 48, 'max_samples_per_ts': 50, 'lr': 0.543, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 1.5, 'alpha': 0.164, 'lambda_': 0.123, 'n_estimators': 448}
Current value: 0.0758119747042656, Current params: {'in_len': 48, 'max_samples_per_ts': 50, 'lr': 0.5740000000000001, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 1.0, 'alpha': 0.18, 'lambda_': 0.11800000000000001, 'n_estimators': 448}
Best value: 0.0735437348484993, Best params: {'in_len': 48, 'max_samples_per_ts': 50, 'lr': 0.543, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 1.5, 'alpha': 0.164, 'lambda_': 0.123, 'n_estimators': 448}
Current value: 0.07845920324325562, Current params: {'in_len': 48, 'max_samples_per_ts': 50, 'lr': 0.878, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 1.0, 'alpha': 0.18, 'lambda_': 0.123, 'n_estimators': 416}
Best value: 0.0735437348484993, Best params: {'in_len': 48, 'max_samples_per_ts': 50, 'lr': 0.543, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 1.5, 'alpha': 0.164, 'lambda_': 0.123, 'n_estimators': 448}
Current value: 0.08079927414655685, Current params: {'in_len': 60, 'max_samples_per_ts': 100, 'lr': 0.557, 'subsample': 0.7, 'min_child_weight': 3.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.20800000000000002, 'lambda_': 0.08800000000000001, 'n_estimators': 448}
Best value: 0.0735437348484993, Best params: {'in_len': 48, 'max_samples_per_ts': 50, 'lr': 0.543, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 1.5, 'alpha': 0.164, 'lambda_': 0.123, 'n_estimators': 448}
Current value: 0.07973063737154007, Current params: {'in_len': 72, 'max_samples_per_ts': 50, 'lr': 0.636, 'subsample': 0.6, 'min_child_weight': 3.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 1.5, 'alpha': 0.225, 'lambda_': 0.111, 'n_estimators': 448}
Best value: 0.0735437348484993, Best params: {'in_len': 48, 'max_samples_per_ts': 50, 'lr': 0.543, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 1.5, 'alpha': 0.164, 'lambda_': 0.123, 'n_estimators': 448}
Current value: 0.09272199869155884, Current params: {'in_len': 36, 'max_samples_per_ts': 200, 'lr': 0.8230000000000001, 'subsample': 0.7, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 2.5, 'alpha': 0.158, 'lambda_': 0.058, 'n_estimators': 352}
Best value: 0.0735437348484993, Best params: {'in_len': 48, 'max_samples_per_ts': 50, 'lr': 0.543, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 1.5, 'alpha': 0.164, 'lambda_': 0.123, 'n_estimators': 448}
Current value: 0.10105878114700317, Current params: {'in_len': 72, 'max_samples_per_ts': 100, 'lr': 0.74, 'subsample': 0.8, 'min_child_weight': 2.0, 'colsample_bytree': 1.0, 'max_depth': 6, 'gamma': 1.0, 'alpha': 0.26, 'lambda_': 0.158, 'n_estimators': 384}
Best value: 0.0735437348484993, Best params: {'in_len': 48, 'max_samples_per_ts': 50, 'lr': 0.543, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 1.5, 'alpha': 0.164, 'lambda_': 0.123, 'n_estimators': 448}
Current value: 0.0753268375992775, Current params: {'in_len': 36, 'max_samples_per_ts': 50, 'lr': 0.509, 'subsample': 0.7, 'min_child_weight': 3.0, 'colsample_bytree': 0.8, 'max_depth': 8, 'gamma': 2.0, 'alpha': 0.197, 'lambda_': 0.099, 'n_estimators': 416}
Best value: 0.0735437348484993, Best params: {'in_len': 48, 'max_samples_per_ts': 50, 'lr': 0.543, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 1.5, 'alpha': 0.164, 'lambda_': 0.123, 'n_estimators': 448}
Current value: 0.08964519947767258, Current params: {'in_len': 36, 'max_samples_per_ts': 100, 'lr': 0.512, 'subsample': 0.7, 'min_child_weight': 3.0, 'colsample_bytree': 0.8, 'max_depth': 8, 'gamma': 3.5, 'alpha': 0.29, 'lambda_': 0.047, 'n_estimators': 416}
Best value: 0.0735437348484993, Best params: {'in_len': 48, 'max_samples_per_ts': 50, 'lr': 0.543, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 1.5, 'alpha': 0.164, 'lambda_': 0.123, 'n_estimators': 448}
Current value: 0.07478819787502289, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'lr': 0.41500000000000004, 'subsample': 0.8, 'min_child_weight': 3.0, 'colsample_bytree': 0.9, 'max_depth': 7, 'gamma': 2.0, 'alpha': 0.199, 'lambda_': 0.002, 'n_estimators': 416}
Best value: 0.0735437348484993, Best params: {'in_len': 48, 'max_samples_per_ts': 50, 'lr': 0.543, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 1.5, 'alpha': 0.164, 'lambda_': 0.123, 'n_estimators': 448}
Current value: 0.08470668643712997, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'lr': 0.28500000000000003, 'subsample': 0.9, 'min_child_weight': 3.0, 'colsample_bytree': 1.0, 'max_depth': 7, 'gamma': 2.0, 'alpha': 0.198, 'lambda_': 0.016, 'n_estimators': 416}
Best value: 0.0735437348484993, Best params: {'in_len': 48, 'max_samples_per_ts': 50, 'lr': 0.543, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 1.5, 'alpha': 0.164, 'lambda_': 0.123, 'n_estimators': 448}
Current value: 0.08035498857498169, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'lr': 0.422, 'subsample': 0.8, 'min_child_weight': 3.0, 'colsample_bytree': 0.9, 'max_depth': 7, 'gamma': 2.5, 'alpha': 0.229, 'lambda_': 0.08600000000000001, 'n_estimators': 384}
Best value: 0.0735437348484993, Best params: {'in_len': 48, 'max_samples_per_ts': 50, 'lr': 0.543, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 1.5, 'alpha': 0.164, 'lambda_': 0.123, 'n_estimators': 448}
Current value: 0.07277628034353256, Current params: {'in_len': 36, 'max_samples_per_ts': 50, 'lr': 0.651, 'subsample': 0.8, 'min_child_weight': 2.0, 'colsample_bytree': 1.0, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.148, 'lambda_': 0.094, 'n_estimators': 480}
Best value: 0.07277628034353256, Best params: {'in_len': 36, 'max_samples_per_ts': 50, 'lr': 0.651, 'subsample': 0.8, 'min_child_weight': 2.0, 'colsample_bytree': 1.0, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.148, 'lambda_': 0.094, 'n_estimators': 480}
Current value: 0.07807204127311707, Current params: {'in_len': 60, 'max_samples_per_ts': 50, 'lr': 0.649, 'subsample': 0.9, 'min_child_weight': 1.0, 'colsample_bytree': 1.0, 'max_depth': 5, 'gamma': 1.5, 'alpha': 0.147, 'lambda_': 0.032, 'n_estimators': 480}
Best value: 0.07277628034353256, Best params: {'in_len': 36, 'max_samples_per_ts': 50, 'lr': 0.651, 'subsample': 0.8, 'min_child_weight': 2.0, 'colsample_bytree': 1.0, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.148, 'lambda_': 0.094, 'n_estimators': 480}
Current value: 0.0799303650856018, Current params: {'in_len': 120, 'max_samples_per_ts': 150, 'lr': 0.614, 'subsample': 1.0, 'min_child_weight': 2.0, 'colsample_bytree': 1.0, 'max_depth': 6, 'gamma': 0.5, 'alpha': 0.171, 'lambda_': 0.005, 'n_estimators': 480}
Best value: 0.07277628034353256, Best params: {'in_len': 36, 'max_samples_per_ts': 50, 'lr': 0.651, 'subsample': 0.8, 'min_child_weight': 2.0, 'colsample_bytree': 1.0, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.148, 'lambda_': 0.094, 'n_estimators': 480}
Current value: 0.08286216109991074, Current params: {'in_len': 60, 'max_samples_per_ts': 50, 'lr': 0.6880000000000001, 'subsample': 0.8, 'min_child_weight': 1.0, 'colsample_bytree': 0.9, 'max_depth': 5, 'gamma': 3.0, 'alpha': 0.255, 'lambda_': 0.057, 'n_estimators': 512}
Best value: 0.07277628034353256, Best params: {'in_len': 36, 'max_samples_per_ts': 50, 'lr': 0.651, 'subsample': 0.8, 'min_child_weight': 2.0, 'colsample_bytree': 1.0, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.148, 'lambda_': 0.094, 'n_estimators': 480}
Current value: 0.09693402051925659, Current params: {'in_len': 168, 'max_samples_per_ts': 100, 'lr': 0.764, 'subsample': 0.8, 'min_child_weight': 2.0, 'colsample_bytree': 1.0, 'max_depth': 6, 'gamma': 1.0, 'alpha': 0.22, 'lambda_': 0.151, 'n_estimators': 448}
Best value: 0.07277628034353256, Best params: {'in_len': 36, 'max_samples_per_ts': 50, 'lr': 0.651, 'subsample': 0.8, 'min_child_weight': 2.0, 'colsample_bytree': 1.0, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.148, 'lambda_': 0.094, 'n_estimators': 480}
Current value: 0.09820974618196487, Current params: {'in_len': 132, 'max_samples_per_ts': 200, 'lr': 0.307, 'subsample': 0.9, 'min_child_weight': 1.0, 'colsample_bytree': 0.9, 'max_depth': 7, 'gamma': 1.5, 'alpha': 0.243, 'lambda_': 0.1, 'n_estimators': 480}
Best value: 0.07277628034353256, Best params: {'in_len': 36, 'max_samples_per_ts': 50, 'lr': 0.651, 'subsample': 0.8, 'min_child_weight': 2.0, 'colsample_bytree': 1.0, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.148, 'lambda_': 0.094, 'n_estimators': 480}
Current value: 0.0860128402709961, Current params: {'in_len': 72, 'max_samples_per_ts': 50, 'lr': 0.532, 'subsample': 0.8, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 7, 'gamma': 3.5, 'alpha': 0.001, 'lambda_': 0.034, 'n_estimators': 448}
Best value: 0.07277628034353256, Best params: {'in_len': 36, 'max_samples_per_ts': 50, 'lr': 0.651, 'subsample': 0.8, 'min_child_weight': 2.0, 'colsample_bytree': 1.0, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.148, 'lambda_': 0.094, 'n_estimators': 480}
--------------------------------
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)
		fast_insulin: REAL_VALUED (OBSERVED_INPUT)
		slow_insulin: REAL_VALUED (OBSERVED_INPUT)
		calories: REAL_VALUED (OBSERVED_INPUT)
		balance: REAL_VALUED (OBSERVED_INPUT)
		quality: REAL_VALUED (OBSERVED_INPUT)
		HR: REAL_VALUED (OBSERVED_INPUT)
		BR: REAL_VALUED (OBSERVED_INPUT)
		Posture: REAL_VALUED (OBSERVED_INPUT)
		Activity: REAL_VALUED (OBSERVED_INPUT)
		HRV: REAL_VALUED (OBSERVED_INPUT)
		CoreTemp: REAL_VALUED (OBSERVED_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: 1
	Extracted segments: 8
	Interpolated values: 0
	Percent of values interpolated: 0.00%
Splitting data...
	Train: 4654 (47.17%)
	Val: 2016 (20.43%)
	Test: 2057 (20.85%)
	Test OOD: 1140 (11.55%)
Scaling data...
	No scaling applied
Data formatting complete.
--------------------------------
	Train: 4654 (47.17%)
	Val: 2016 (20.43%)
	Test: 2057 (20.85%)
	Test OOD: 1140 (11.55%)
	No scaling applied
		Model Seed: 10 Seed: 1 ID mean of (MSE, MAE): [1403.1234     25.714746]
		Model Seed: 10 Seed: 1 OOD mean of (MSE, MAE) stats: [816.44336  21.43365]
		Model Seed: 10 Seed: 1 ID median of (MSE, MAE): [496.51962   20.294859]
		Model Seed: 10 Seed: 1 OOD median of (MSE, MAE) stats: [412.8298    17.955141]
		Model Seed: 10 Seed: 1 ID likelihoods: -10.542166466177909
		Model Seed: 10 Seed: 1 OOD likelihoods: -10.271417415330617
		Model Seed: 10 Seed: 1 ID calibration errors: [0.22835943 0.15368025 0.11405111 0.07280513 0.04960427 0.02817853
 0.01354797 0.00729549 0.00459325 0.00245633 0.00610832 0.00925151]
		Model Seed: 10 Seed: 1 OOD calibration errors: [0.20937565 0.16167534 0.09345473 0.06003122 0.03039542 0.02144641
 0.01740895 0.02098855 0.02556712 0.03326743 0.04209157 0.05603538]
	Train: 4514 (45.75%)
	Val: 2016 (20.43%)
	Test: 2057 (20.85%)
	Test OOD: 1280 (12.97%)
	No scaling applied
		Model Seed: 10 Seed: 2 ID mean of (MSE, MAE): [1440.4718     26.064297]
		Model Seed: 10 Seed: 2 OOD mean of (MSE, MAE) stats: [661.646     17.717302]
		Model Seed: 10 Seed: 2 ID median of (MSE, MAE): [491.93555   19.692339]
		Model Seed: 10 Seed: 2 OOD median of (MSE, MAE) stats: [204.27258   12.824995]
		Model Seed: 10 Seed: 2 ID likelihoods: -10.55530143797005
		Model Seed: 10 Seed: 2 OOD likelihoods: -10.166304003478139
		Model Seed: 10 Seed: 2 ID calibration errors: [0.20973769 0.15944655 0.11111143 0.0730991  0.04938945 0.03490587
 0.01613715 0.01100401 0.00689977 0.00654927 0.00938719 0.00814348]
		Model Seed: 10 Seed: 2 OOD calibration errors: [0.23929428 0.17771115 0.13454741 0.09776543 0.08057064 0.06793334
 0.05469006 0.05501831 0.05114884 0.04535412 0.0511236  0.05118672]
	Model Seed: 10 ID mean of (MSE, MAE): [1421.7976     25.889523]
	Model Seed: 10 OOD mean of (MSE, MAE): [739.0447    19.575476]
	Model Seed: 10 ID median of (MSE, MAE): [494.2276    19.993599]
	Model Seed: 10 OOD median of (MSE, MAE): [308.5512    15.390068]
	Model Seed: 10 ID likelihoods: -10.54873395207398
	Model Seed: 10 OOD likelihoods: -10.218860709404378
	Model Seed: 10 ID calibration errors: [0.21904856 0.1565634  0.11258127 0.07295212 0.04949686 0.0315422
 0.01484256 0.00914975 0.00574651 0.0045028  0.00774775 0.0086975 ]
	Model Seed: 10 OOD calibration errors: [0.22433497 0.16969324 0.11400107 0.07889833 0.05548303 0.04468988
 0.03604951 0.03800343 0.03835798 0.03931078 0.04660758 0.05361105]
	Train: 4654 (47.17%)
	Val: 2016 (20.43%)
	Test: 2057 (20.85%)
	Test OOD: 1140 (11.55%)
	No scaling applied
		Model Seed: 11 Seed: 1 ID mean of (MSE, MAE): [1348.4153     24.219364]
		Model Seed: 11 Seed: 1 OOD mean of (MSE, MAE) stats: [813.0555    20.860239]
		Model Seed: 11 Seed: 1 ID median of (MSE, MAE): [436.85507   17.008846]
		Model Seed: 11 Seed: 1 OOD median of (MSE, MAE) stats: [412.18576   18.049398]
		Model Seed: 11 Seed: 1 ID likelihoods: -10.522281282543462
		Model Seed: 11 Seed: 1 OOD likelihoods: -10.269338095340848
		Model Seed: 11 Seed: 1 ID calibration errors: [0.26080898 0.21530047 0.15068404 0.11117926 0.07416191 0.04868845
 0.02896998 0.01760699 0.01262084 0.00769122 0.00705806 0.01018995]
		Model Seed: 11 Seed: 1 OOD calibration errors: [0.26848075 0.19559834 0.11593132 0.0603642  0.02968783 0.01445369
 0.01087409 0.0117898  0.01978148 0.03176899 0.03797086 0.04845994]
	Train: 4514 (45.75%)
	Val: 2016 (20.43%)
	Test: 2057 (20.85%)
	Test OOD: 1280 (12.97%)
	No scaling applied
		Model Seed: 11 Seed: 2 ID mean of (MSE, MAE): [1397.3907     25.578407]
		Model Seed: 11 Seed: 2 OOD mean of (MSE, MAE) stats: [629.9107    16.881628]
		Model Seed: 11 Seed: 2 ID median of (MSE, MAE): [453.93167  18.68348]
		Model Seed: 11 Seed: 2 OOD median of (MSE, MAE) stats: [165.3778    11.718334]
		Model Seed: 11 Seed: 2 ID likelihoods: -10.540119545486576
		Model Seed: 11 Seed: 2 OOD likelihoods: -10.141727617724005
		Model Seed: 11 Seed: 2 ID calibration errors: [0.25853638 0.17256204 0.13301204 0.08344451 0.04874498 0.02716095
 0.01677031 0.00841483 0.00353044 0.00427667 0.00727288 0.00966985]
		Model Seed: 11 Seed: 2 OOD calibration errors: [0.27440348 0.18801288 0.12958591 0.08363212 0.05893195 0.04240626
 0.03180785 0.02352607 0.01848883 0.01680343 0.02002272 0.02868956]
	Model Seed: 11 ID mean of (MSE, MAE): [1372.9031     24.898886]
	Model Seed: 11 OOD mean of (MSE, MAE): [721.4831    18.870934]
	Model Seed: 11 ID median of (MSE, MAE): [445.39337   17.846163]
	Model Seed: 11 OOD median of (MSE, MAE): [288.7818    14.883866]
	Model Seed: 11 ID likelihoods: -10.531200414015018
	Model Seed: 11 OOD likelihoods: -10.205532856532425
	Model Seed: 11 ID calibration errors: [0.25967268 0.19393126 0.14184804 0.09731189 0.06145345 0.0379247
 0.02287015 0.01301091 0.00807564 0.00598394 0.00716547 0.0099299 ]
	Model Seed: 11 OOD calibration errors: [0.27144212 0.19180561 0.12275862 0.07199816 0.04430989 0.02842998
 0.02134097 0.01765794 0.01913515 0.02428621 0.02899679 0.03857475]
	Train: 4654 (47.17%)
	Val: 2016 (20.43%)
	Test: 2057 (20.85%)
	Test OOD: 1140 (11.55%)
	No scaling applied
		Model Seed: 12 Seed: 1 ID mean of (MSE, MAE): [1368.5426     24.997135]
		Model Seed: 12 Seed: 1 OOD mean of (MSE, MAE) stats: [812.5586    21.415848]
		Model Seed: 12 Seed: 1 ID median of (MSE, MAE): [448.72128   19.145792]
		Model Seed: 12 Seed: 1 OOD median of (MSE, MAE) stats: [393.7946  17.5392]
		Model Seed: 12 Seed: 1 ID likelihoods: -10.52968940721576
		Model Seed: 12 Seed: 1 OOD likelihoods: -10.269032396469258
		Model Seed: 12 Seed: 1 ID calibration errors: [0.23945107 0.15997795 0.1212081  0.07512296 0.05521228 0.03626265
 0.02233309 0.01171632 0.00913845 0.00497767 0.00936458 0.01298264]
		Model Seed: 12 Seed: 1 OOD calibration errors: [0.23139438 0.17216441 0.11222685 0.06452653 0.03401665 0.02007284
 0.02065557 0.02485952 0.03081165 0.03389178 0.03813736 0.0505411 ]
	Train: 4514 (45.75%)
	Val: 2016 (20.43%)
	Test: 2057 (20.85%)
	Test OOD: 1280 (12.97%)
	No scaling applied
		Model Seed: 12 Seed: 2 ID mean of (MSE, MAE): [1300.0847     24.508137]
		Model Seed: 12 Seed: 2 OOD mean of (MSE, MAE) stats: [646.2049    17.887693]
		Model Seed: 12 Seed: 2 ID median of (MSE, MAE): [456.26852   18.811502]
		Model Seed: 12 Seed: 2 OOD median of (MSE, MAE) stats: [220.95087  13.97369]
		Model Seed: 12 Seed: 2 ID likelihoods: -10.50403069946299
		Model Seed: 12 Seed: 2 OOD likelihoods: -10.154496989105262
		Model Seed: 12 Seed: 2 ID calibration errors: [0.25607157 0.17450676 0.1199983  0.07978122 0.05208039 0.03258805
 0.01726779 0.00789474 0.00432189 0.00507943 0.0060857  0.00522641]
		Model Seed: 12 Seed: 2 OOD calibration errors: [0.22370282 0.15400202 0.11152632 0.07607625 0.05882464 0.03897866
 0.03122712 0.02853806 0.02288852 0.02829188 0.03615705 0.04694483]
	Model Seed: 12 ID mean of (MSE, MAE): [1334.3137     24.752636]
	Model Seed: 12 OOD mean of (MSE, MAE): [729.3817    19.651772]
	Model Seed: 12 ID median of (MSE, MAE): [452.4949    18.978647]
	Model Seed: 12 OOD median of (MSE, MAE): [307.37274   15.756445]
	Model Seed: 12 ID likelihoods: -10.516860053339375
	Model Seed: 12 OOD likelihoods: -10.21176469278726
	Model Seed: 12 ID calibration errors: [0.24776132 0.16724235 0.1206032  0.07745209 0.05364633 0.03442535
 0.01980044 0.00980553 0.00673017 0.00502855 0.00772514 0.00910453]
	Model Seed: 12 OOD calibration errors: [0.2275486  0.16308322 0.11187658 0.07030139 0.04642065 0.02952575
 0.02594134 0.02669879 0.02685009 0.03109183 0.0371472  0.04874297]
	Train: 4654 (47.17%)
	Val: 2016 (20.43%)
	Test: 2057 (20.85%)
	Test OOD: 1140 (11.55%)
	No scaling applied
		Model Seed: 13 Seed: 1 ID mean of (MSE, MAE): [1473.1737     25.707512]
		Model Seed: 13 Seed: 1 OOD mean of (MSE, MAE) stats: [829.7127    21.251276]
		Model Seed: 13 Seed: 1 ID median of (MSE, MAE): [335.45206   16.634674]
		Model Seed: 13 Seed: 1 OOD median of (MSE, MAE) stats: [425.01962   18.976707]
		Model Seed: 13 Seed: 1 ID likelihoods: -10.566525659887201
		Model Seed: 13 Seed: 1 OOD likelihoods: -10.279478138757701
		Model Seed: 13 Seed: 1 ID calibration errors: [0.23522245 0.18824411 0.1339844  0.09051105 0.07249986 0.05312058
 0.04120357 0.02774888 0.02093109 0.01943863 0.01681554 0.01663463]
		Model Seed: 13 Seed: 1 OOD calibration errors: [0.27701353 0.2008845  0.12895942 0.06431842 0.03792924 0.02219563
 0.02257024 0.02111342 0.03135276 0.04034339 0.04238293 0.0548283 ]
	Train: 4514 (45.75%)
	Val: 2016 (20.43%)
	Test: 2057 (20.85%)
	Test OOD: 1280 (12.97%)
	No scaling applied
		Model Seed: 13 Seed: 2 ID mean of (MSE, MAE): [1357.1621     24.985485]
		Model Seed: 13 Seed: 2 OOD mean of (MSE, MAE) stats: [613.83875   17.664803]
		Model Seed: 13 Seed: 2 ID median of (MSE, MAE): [470.84546  18.74842]
		Model Seed: 13 Seed: 2 OOD median of (MSE, MAE) stats: [202.47925   13.126583]
		Model Seed: 13 Seed: 2 ID likelihoods: -10.525514360184392
		Model Seed: 13 Seed: 2 OOD likelihoods: -10.128804714696383
		Model Seed: 13 Seed: 2 ID calibration errors: [0.2143055  0.14890893 0.09368817 0.07325739 0.04909548 0.03272373
 0.01987959 0.01501781 0.01087964 0.00942111 0.00966985 0.0071372 ]
		Model Seed: 13 Seed: 2 OOD calibration errors: [0.20561167 0.15712663 0.12376594 0.07442873 0.04710264 0.0273261
 0.02820351 0.02354501 0.02332408 0.02041409 0.03211716 0.04121323]
	Model Seed: 13 ID mean of (MSE, MAE): [1415.168      25.346498]
	Model Seed: 13 OOD mean of (MSE, MAE): [721.77576   19.458038]
	Model Seed: 13 ID median of (MSE, MAE): [403.14874   17.691547]
	Model Seed: 13 OOD median of (MSE, MAE): [313.74945   16.051645]
	Model Seed: 13 ID likelihoods: -10.546020010035797
	Model Seed: 13 OOD likelihoods: -10.204141426727041
	Model Seed: 13 ID calibration errors: [0.22476398 0.16857652 0.11383628 0.08188422 0.06079767 0.04292216
 0.03054158 0.02138335 0.01590536 0.01442987 0.01324269 0.01188592]
	Model Seed: 13 OOD calibration errors: [0.2413126  0.17900556 0.12636268 0.06937358 0.04251594 0.02476086
 0.02538687 0.02232922 0.02733842 0.03037874 0.03725005 0.04802077]
	Train: 4654 (47.17%)
	Val: 2016 (20.43%)
	Test: 2057 (20.85%)
	Test OOD: 1140 (11.55%)
	No scaling applied
		Model Seed: 14 Seed: 1 ID mean of (MSE, MAE): [1400.5812     25.676512]
		Model Seed: 14 Seed: 1 OOD mean of (MSE, MAE) stats: [822.4576   21.57343]
		Model Seed: 14 Seed: 1 ID median of (MSE, MAE): [500.082     20.384174]
		Model Seed: 14 Seed: 1 OOD median of (MSE, MAE) stats: [413.13623   18.173643]
		Model Seed: 14 Seed: 1 ID likelihoods: -10.541259854642053
		Model Seed: 14 Seed: 1 OOD likelihoods: -10.27508709828577
		Model Seed: 14 Seed: 1 ID calibration errors: [0.22232178 0.15378201 0.11015038 0.07863927 0.04622364 0.02309062
 0.01706428 0.00746509 0.00401662 0.00270507 0.00574651 0.01120753]
		Model Seed: 14 Seed: 1 OOD calibration errors: [0.21894901 0.16288241 0.09545265 0.06319459 0.0353486  0.02398543
 0.01978148 0.02252862 0.02864724 0.03522373 0.03784599 0.05815817]
	Train: 4514 (45.75%)
	Val: 2016 (20.43%)
	Test: 2057 (20.85%)
	Test OOD: 1280 (12.97%)
	No scaling applied
		Model Seed: 14 Seed: 2 ID mean of (MSE, MAE): [1392.3193     25.306898]
		Model Seed: 14 Seed: 2 OOD mean of (MSE, MAE) stats: [606.87036   17.091564]
		Model Seed: 14 Seed: 2 ID median of (MSE, MAE): [433.07962   18.493462]
		Model Seed: 14 Seed: 2 OOD median of (MSE, MAE) stats: [199.83391   12.542295]
		Model Seed: 14 Seed: 2 ID likelihoods: -10.538301556823313
		Model Seed: 14 Seed: 2 OOD likelihoods: -10.12309633209129
		Model Seed: 14 Seed: 2 ID calibration errors: [0.24312567 0.17805698 0.11216293 0.08319577 0.05296229 0.03083555
 0.01297134 0.00990729 0.0025807  0.00273899 0.00388094 0.0066058 ]
		Model Seed: 14 Seed: 2 OOD calibration errors: [0.21454993 0.15816185 0.10871102 0.07087489 0.05741068 0.04330261
 0.03283676 0.03214872 0.02170181 0.02759121 0.03591087 0.04751925]
	Model Seed: 14 ID mean of (MSE, MAE): [1396.4502     25.491705]
	Model Seed: 14 OOD mean of (MSE, MAE): [714.66394   19.332497]
	Model Seed: 14 ID median of (MSE, MAE): [466.5808    19.438818]
	Model Seed: 14 OOD median of (MSE, MAE): [306.48508   15.357969]
	Model Seed: 14 ID likelihoods: -10.539780705732683
	Model Seed: 14 OOD likelihoods: -10.19909171518853
	Model Seed: 14 ID calibration errors: [0.23272373 0.1659195  0.11115665 0.08091752 0.04959297 0.02696308
 0.01501781 0.00868619 0.00329866 0.00272203 0.00481373 0.00890667]
	Model Seed: 14 OOD calibration errors: [0.21674947 0.16052213 0.10208184 0.06703474 0.04637964 0.03364402
 0.02630912 0.02733867 0.02517452 0.03140747 0.03687843 0.05283871]
	Train: 4654 (47.17%)
	Val: 2016 (20.43%)
	Test: 2057 (20.85%)
	Test OOD: 1140 (11.55%)
	No scaling applied
		Model Seed: 15 Seed: 1 ID mean of (MSE, MAE): [1314.384      24.254242]
		Model Seed: 15 Seed: 1 OOD mean of (MSE, MAE) stats: [802.6341    20.737669]
		Model Seed: 15 Seed: 1 ID median of (MSE, MAE): [435.93423   18.554592]
		Model Seed: 15 Seed: 1 OOD median of (MSE, MAE) stats: [401.99008   18.287214]
		Model Seed: 15 Seed: 1 ID likelihoods: -10.509500149859921
		Model Seed: 15 Seed: 1 OOD likelihoods: -10.262888001539313
		Model Seed: 15 Seed: 1 ID calibration errors: [0.26044717 0.20853921 0.13745548 0.09720448 0.05988185 0.03672621
 0.02054667 0.01271129 0.00679801 0.00530556 0.00617615 0.00986206]
		Model Seed: 15 Seed: 1 OOD calibration errors: [0.29349636 0.20654527 0.12700312 0.07189386 0.03522373 0.0173257
 0.0148283  0.01291363 0.02082206 0.02873049 0.04013528 0.04887617]
	Train: 4514 (45.75%)
	Val: 2016 (20.43%)
	Test: 2057 (20.85%)
	Test OOD: 1280 (12.97%)
	No scaling applied
		Model Seed: 15 Seed: 2 ID mean of (MSE, MAE): [1365.967     24.62563]
		Model Seed: 15 Seed: 2 OOD mean of (MSE, MAE) stats: [623.0279    17.311893]
		Model Seed: 15 Seed: 2 ID median of (MSE, MAE): [379.07422   17.472345]
		Model Seed: 15 Seed: 2 OOD median of (MSE, MAE) stats: [183.24939  12.24139]
		Model Seed: 15 Seed: 2 ID likelihoods: -10.528747533757322
		Model Seed: 15 Seed: 2 OOD likelihoods: -10.136234325133916
		Model Seed: 15 Seed: 2 ID calibration errors: [0.21665724 0.16177568 0.12369552 0.08484651 0.06352253 0.03904404
 0.02104415 0.01474645 0.01310702 0.00883317 0.00754424 0.00640228]
		Model Seed: 15 Seed: 2 OOD calibration errors: [0.21629845 0.15431764 0.11450574 0.07586795 0.05455751 0.04750032
 0.03923747 0.03093044 0.02335564 0.02176493 0.02446661 0.03138493]
	Model Seed: 15 ID mean of (MSE, MAE): [1340.1755     24.439936]
	Model Seed: 15 OOD mean of (MSE, MAE): [712.831    19.02478]
	Model Seed: 15 ID median of (MSE, MAE): [407.5042   18.01347]
	Model Seed: 15 OOD median of (MSE, MAE): [292.61975   15.264302]
	Model Seed: 15 ID likelihoods: -10.519123841808621
	Model Seed: 15 OOD likelihoods: -10.199561163336615
	Model Seed: 15 ID calibration errors: [0.23855221 0.18515744 0.1305755  0.0910255  0.06170219 0.03788513
 0.02079541 0.01372887 0.00995251 0.00706937 0.0068602  0.00813217]
	Model Seed: 15 OOD calibration errors: [0.2548974  0.18043145 0.12075443 0.0738809  0.04489062 0.03241301
 0.02703289 0.02192203 0.02208885 0.02524771 0.03230094 0.04013055]
	Train: 4654 (47.17%)
	Val: 2016 (20.43%)
	Test: 2057 (20.85%)
	Test OOD: 1140 (11.55%)
	No scaling applied
		Model Seed: 16 Seed: 1 ID mean of (MSE, MAE): [1346.9108     25.324806]
		Model Seed: 16 Seed: 1 OOD mean of (MSE, MAE) stats: [808.8713    21.382711]
		Model Seed: 16 Seed: 1 ID median of (MSE, MAE): [490.55942   19.794012]
		Model Seed: 16 Seed: 1 OOD median of (MSE, MAE) stats: [411.93265  17.95461]
		Model Seed: 16 Seed: 1 ID likelihoods: -10.521722951984223
		Model Seed: 16 Seed: 1 OOD likelihoods: -10.26675835299709
		Model Seed: 16 Seed: 1 ID calibration errors: [0.24017468 0.15787495 0.11129233 0.06141953 0.04337441 0.02622251
 0.01379671 0.00723896 0.00549777 0.00365481 0.00888971 0.01230426]
		Model Seed: 16 Seed: 1 OOD calibration errors: [0.20575442 0.15888658 0.09387097 0.06023933 0.0353486  0.02344433
 0.01815817 0.02103018 0.02560874 0.03335068 0.04508845 0.05511967]
	Train: 4514 (45.75%)
	Val: 2016 (20.43%)
	Test: 2057 (20.85%)
	Test OOD: 1280 (12.97%)
	No scaling applied
		Model Seed: 16 Seed: 2 ID mean of (MSE, MAE): [1433.8022     25.361658]
		Model Seed: 16 Seed: 2 OOD mean of (MSE, MAE) stats: [626.80853   17.358501]
		Model Seed: 16 Seed: 2 ID median of (MSE, MAE): [382.7517    18.797573]
		Model Seed: 16 Seed: 2 OOD median of (MSE, MAE) stats: [225.04576    13.5511875]
		Model Seed: 16 Seed: 2 ID likelihoods: -10.552981300023163
		Model Seed: 16 Seed: 2 OOD likelihoods: -10.13925904628099
		Model Seed: 16 Seed: 2 ID calibration errors: [0.21297134 0.16561988 0.11889027 0.07736164 0.05573238 0.04393974
 0.01980044 0.01184069 0.00937588 0.0069563  0.00633445 0.00579173]
		Model Seed: 16 Seed: 2 OOD calibration errors: [0.22595632 0.1662227  0.11532635 0.07966166 0.05709506 0.04761394
 0.03854943 0.03545638 0.02552708 0.02335564 0.02697892 0.03363212]
	Model Seed: 16 ID mean of (MSE, MAE): [1390.3564     25.343231]
	Model Seed: 16 OOD mean of (MSE, MAE): [717.8399    19.370605]
	Model Seed: 16 ID median of (MSE, MAE): [436.65558   19.295792]
	Model Seed: 16 OOD median of (MSE, MAE): [318.4892    15.752899]
	Model Seed: 16 ID likelihoods: -10.537352126003693
	Model Seed: 16 OOD likelihoods: -10.20300869963904
	Model Seed: 16 ID calibration errors: [0.22657301 0.16174741 0.1150913  0.06939058 0.04955339 0.03508112
 0.01679858 0.00953983 0.00743683 0.00530556 0.00761208 0.009048  ]
	Model Seed: 16 OOD calibration errors: [0.21585537 0.16255464 0.10459866 0.0699505  0.04622183 0.03552913
 0.0283538  0.02824328 0.02556791 0.02835316 0.03603368 0.04437589]
	Train: 4654 (47.17%)
	Val: 2016 (20.43%)
	Test: 2057 (20.85%)
	Test OOD: 1140 (11.55%)
	No scaling applied
		Model Seed: 17 Seed: 1 ID mean of (MSE, MAE): [1339.5598    24.05317]
		Model Seed: 17 Seed: 1 OOD mean of (MSE, MAE) stats: [810.2815    20.886303]
		Model Seed: 17 Seed: 1 ID median of (MSE, MAE): [398.09262   16.694773]
		Model Seed: 17 Seed: 1 OOD median of (MSE, MAE) stats: [400.46848   18.220152]
		Model Seed: 17 Seed: 1 ID likelihoods: -10.518986795482514
		Model Seed: 17 Seed: 1 OOD likelihoods: -10.267629313341068
		Model Seed: 17 Seed: 1 ID calibration errors: [0.27138052 0.22163209 0.15013002 0.11393804 0.06428006 0.04675505
 0.02650517 0.0195517  0.01267737 0.00994121 0.0071259  0.01024648]
		Model Seed: 17 Seed: 1 OOD calibration errors: [0.25524454 0.17166493 0.10390219 0.05391259 0.02306972 0.01029136
 0.00845994 0.01008325 0.01720083 0.02739854 0.03484912 0.0408845 ]
	Train: 4514 (45.75%)
	Val: 2016 (20.43%)
	Test: 2057 (20.85%)
	Test OOD: 1280 (12.97%)
	No scaling applied
		Model Seed: 17 Seed: 2 ID mean of (MSE, MAE): [1358.4801     25.055023]
		Model Seed: 17 Seed: 2 OOD mean of (MSE, MAE) stats: [608.2383   17.52839]
		Model Seed: 17 Seed: 2 ID median of (MSE, MAE): [465.04834   18.590563]
		Model Seed: 17 Seed: 2 OOD median of (MSE, MAE) stats: [209.97675   13.099119]
		Model Seed: 17 Seed: 2 ID likelihoods: -10.525999379335055
		Model Seed: 17 Seed: 2 OOD likelihoods: -10.12422179042731
		Model Seed: 17 Seed: 2 ID calibration errors: [0.22846119 0.15487874 0.09769066 0.08130759 0.05410425 0.03368478
 0.02327152 0.0162276  0.01016734 0.00895754 0.01090226 0.00744248]
		Model Seed: 17 Seed: 2 OOD calibration errors: [0.21189875 0.1594685  0.12079283 0.07502209 0.04581492 0.02888524
 0.02452342 0.02447923 0.01995329 0.01917687 0.0289168  0.03675041]
	Model Seed: 17 ID mean of (MSE, MAE): [1349.02       24.554096]
	Model Seed: 17 OOD mean of (MSE, MAE): [709.2599    19.207348]
	Model Seed: 17 ID median of (MSE, MAE): [431.5705    17.642668]
	Model Seed: 17 OOD median of (MSE, MAE): [305.2226    15.659636]
	Model Seed: 17 ID likelihoods: -10.522493087408783
	Model Seed: 17 OOD likelihoods: -10.195925551884189
	Model Seed: 17 ID calibration errors: [0.24992085 0.18825541 0.12391034 0.09762282 0.05919215 0.04021991
 0.02488835 0.01788965 0.01142235 0.00944938 0.00901408 0.00884448]
	Model Seed: 17 OOD calibration errors: [0.23357164 0.16556672 0.11234751 0.06446734 0.03444232 0.0195883
 0.01649168 0.01728124 0.01857706 0.02328771 0.03188296 0.03881745]
	Train: 4654 (47.17%)
	Val: 2016 (20.43%)
	Test: 2057 (20.85%)
	Test OOD: 1140 (11.55%)
	No scaling applied
		Model Seed: 18 Seed: 1 ID mean of (MSE, MAE): [1402.9812     25.315601]
		Model Seed: 18 Seed: 1 OOD mean of (MSE, MAE) stats: [805.26953   21.361216]
		Model Seed: 18 Seed: 1 ID median of (MSE, MAE): [457.11343   19.081213]
		Model Seed: 18 Seed: 1 OOD median of (MSE, MAE) stats: [397.08926   17.256336]
		Model Seed: 18 Seed: 1 ID likelihoods: -10.542115786692115
		Model Seed: 18 Seed: 1 OOD likelihoods: -10.26452686512138
		Model Seed: 18 Seed: 1 ID calibration errors: [0.23397874 0.16164    0.11513653 0.07936288 0.05170728 0.03526768
 0.02185822 0.01462208 0.01094748 0.00545254 0.00809825 0.01269998]
		Model Seed: 18 Seed: 1 OOD calibration errors: [0.2230281  0.16629553 0.10240375 0.06689906 0.03976067 0.02698231
 0.02456816 0.02510926 0.03097815 0.03580645 0.03747138 0.05308012]
	Train: 4514 (45.75%)
	Val: 2016 (20.43%)
	Test: 2057 (20.85%)
	Test OOD: 1280 (12.97%)
	No scaling applied
		Model Seed: 18 Seed: 2 ID mean of (MSE, MAE): [1446.1666     25.773071]
		Model Seed: 18 Seed: 2 OOD mean of (MSE, MAE) stats: [610.4334   17.10723]
		Model Seed: 18 Seed: 2 ID median of (MSE, MAE): [435.62317   18.697681]
		Model Seed: 18 Seed: 2 OOD median of (MSE, MAE) stats: [189.99277   12.607067]
		Model Seed: 18 Seed: 2 ID likelihoods: -10.557274431828697
		Model Seed: 18 Seed: 2 OOD likelihoods: -10.12602319026221
		Model Seed: 18 Seed: 2 ID calibration errors: [0.2384448  0.1668862  0.10812652 0.08190683 0.05590197 0.0291848
 0.01268868 0.00862966 0.00390356 0.00289728 0.00545254 0.00704675]
		Model Seed: 18 Seed: 2 OOD calibration errors: [0.20768211 0.15379371 0.10809872 0.08130918 0.05916551 0.0408408
 0.02665699 0.0352607  0.02459285 0.02471279 0.03755208 0.0462631 ]
	Model Seed: 18 ID mean of (MSE, MAE): [1424.574      25.544336]
	Model Seed: 18 OOD mean of (MSE, MAE): [707.85144   19.234222]
	Model Seed: 18 ID median of (MSE, MAE): [446.3683    18.889446]
	Model Seed: 18 OOD median of (MSE, MAE): [293.54102   14.931702]
	Model Seed: 18 ID likelihoods: -10.549695109260405
	Model Seed: 18 OOD likelihoods: -10.195275027691796
	Model Seed: 18 ID calibration errors: [0.23621177 0.1642631  0.11163152 0.08063486 0.05380462 0.03222624
 0.01727345 0.01162587 0.00742552 0.00417491 0.0067754  0.00987337]
	Model Seed: 18 OOD calibration errors: [0.2153551  0.16004462 0.10525124 0.07410412 0.04946309 0.03391156
 0.02561257 0.03018498 0.0277855  0.03025962 0.03751173 0.04967161]
	Train: 4654 (47.17%)
	Val: 2016 (20.43%)
	Test: 2057 (20.85%)
	Test OOD: 1140 (11.55%)
	No scaling applied
		Model Seed: 19 Seed: 1 ID mean of (MSE, MAE): [1477.95      25.75953]
		Model Seed: 19 Seed: 1 OOD mean of (MSE, MAE) stats: [831.99524  21.2765 ]
		Model Seed: 19 Seed: 1 ID median of (MSE, MAE): [328.9658    16.467264]
		Model Seed: 19 Seed: 1 OOD median of (MSE, MAE) stats: [431.71924   19.044918]
		Model Seed: 19 Seed: 1 ID likelihoods: -10.568144234998442
		Model Seed: 19 Seed: 1 OOD likelihoods: -10.28085196594412
		Model Seed: 19 Seed: 1 ID calibration errors: [0.22447001 0.19345639 0.1350359  0.09262536 0.07511165 0.05202386
 0.03988072 0.02774888 0.02168862 0.01892984 0.01723387 0.01665724]
		Model Seed: 19 Seed: 1 OOD calibration errors: [0.27443288 0.19896982 0.12550468 0.06548387 0.03934443 0.02381894
 0.02248699 0.02406868 0.03543184 0.0432154  0.04146722 0.0598231 ]
	Train: 4514 (45.75%)
	Val: 2016 (20.43%)
	Test: 2057 (20.85%)
	Test OOD: 1280 (12.97%)
	No scaling applied
		Model Seed: 19 Seed: 2 ID mean of (MSE, MAE): [1397.7302     25.551195]
		Model Seed: 19 Seed: 2 OOD mean of (MSE, MAE) stats: [592.175     16.670216]
		Model Seed: 19 Seed: 2 ID median of (MSE, MAE): [428.8982   19.01925]
		Model Seed: 19 Seed: 2 OOD median of (MSE, MAE) stats: [181.7679    11.986641]
		Model Seed: 19 Seed: 2 ID likelihoods: -10.540241130101549
		Model Seed: 19 Seed: 2 OOD likelihoods: -10.110839571017317
		Model Seed: 19 Seed: 2 ID calibration errors: [0.2451043  0.16400305 0.12405732 0.07952117 0.04959297 0.02906043
 0.0137741  0.0081887  0.00506812 0.00492114 0.00739725 0.00996382]
		Model Seed: 19 Seed: 2 OOD calibration errors: [0.26309178 0.17654968 0.12254766 0.07897993 0.05719606 0.04612423
 0.03558263 0.02828557 0.01687918 0.01858351 0.02549552 0.0322434 ]
	Model Seed: 19 ID mean of (MSE, MAE): [1437.8401     25.655361]
	Model Seed: 19 OOD mean of (MSE, MAE): [712.0851    18.973358]
	Model Seed: 19 ID median of (MSE, MAE): [378.932     17.743258]
	Model Seed: 19 OOD median of (MSE, MAE): [306.74356    15.5157795]
	Model Seed: 19 ID likelihoods: -10.554192682549996
	Model Seed: 19 OOD likelihoods: -10.19584576848072
	Model Seed: 19 ID calibration errors: [0.23478716 0.17872972 0.12954661 0.08607327 0.06235231 0.04054214
 0.02682741 0.01796879 0.01337837 0.01192549 0.01231556 0.01331053]
	Model Seed: 19 OOD calibration errors: [0.26876233 0.18775975 0.12402617 0.0722319  0.04827025 0.03497158
 0.02903481 0.02617712 0.02615551 0.03089946 0.03348137 0.04603325]
ID mean of (MSE, MAE): [1388.260009765625, 25.191621780395508] +- [35.630184173583984, 0.4704703092575073] +- [0.697635   0.08935915] 
OOD mean of (MSE, MAE): [718.6217041015625, 19.2699031829834] +- [9.204283714294434, 0.24516096711158752] +- [96.7062795  1.9479811] 
ID median of (MSE, MAE): [436.28759765625, 18.553340911865234] +- [31.56049919128418, 0.8199579119682312] +- [3.458046  0.1473208] 
OOD median of (MSE, MAE): [304.1556701660156, 15.45643138885498] +- [9.069326400756836, 0.3508816659450531] +- [105.860937     2.68930088] 
ID likelihoods: -10.536545198222834 +- 0.01284853458161825 +- 0.0003059392744759748 
OOD likelihoods: -10.202900761167198 +- 0.007238840249507387 +- 0.0678000031455177 
ID calibration errors: [0.2370015263723217, 0.1730386115665102, 0.12107807111764368, 0.08352648538639831, 0.05615919497993103, 0.03597320368590649, 0.020965571824297584, 0.013278873876420377, 0.00893719260557409, 0.007059189326700216, 0.008327208999943474, 0.009773305444061289] +- [0.011847848518455202, 0.011947511870351774, 0.009745299942452625, 0.009043614983897084, 0.005204036026776856, 0.004612037088921914, 0.005003258398654325, 0.004196793621912703, 0.003572245377708076, 0.003545997132908213, 0.002449589013114544, 0.0015312557062222302] +- [0.00465996 0.00837413 0.00683476 0.00375431 0.00304653 0.00266041
 0.00360507 0.0020917  0.00195376 0.0009961  0.00093448 0.00243032] 
OOD calibration errors: [0.23698295998163962, 0.1720466932104374, 0.11440587902309496, 0.07122409568421562, 0.04583972411749161, 0.03174640751983587, 0.026155356071486863, 0.025583669892635115, 0.025703099586039592, 0.0294522678489627, 0.035809074351678585, 0.04608169993198966] +- [0.020300700214219255, 0.011184283513303226, 0.008296123107457327, 0.003807415158960936, 0.005069458086222255, 0.006430588505245827, 0.004788614362099547, 0.005855923218402681, 0.0052531494251523946, 0.004369004251867064, 0.004517903736876939, 0.005230009763684108] +- [0.008734   0.00751002 0.00453491 0.00813773 0.01182724 0.01134474
 0.00817617 0.00613518 0.00091709 0.00484742 0.00393494 0.00649895] 
