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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)
		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: 160
	Extracted segments: 152
	Interpolated values: 8003
	Percent of values interpolated: 8.57%
Splitting data...
	Train: 57159 (68.64%)
	Val: 16704 (20.06%)
	Test: 19521 (23.44%)
Scaling data...
	No scaling applied
Data formatting complete.
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Current value: 0.04517090693116188, Current params: {'in_len': 72, 'max_samples_per_ts': 50, 'lr': 0.87, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.9, 'max_depth': 7, 'gamma': 0.5, 'alpha': 0.11900000000000001, 'lambda_': 0.166, 'n_estimators': 480}
Best value: 0.04517090693116188, Best params: {'in_len': 72, 'max_samples_per_ts': 50, 'lr': 0.87, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.9, 'max_depth': 7, 'gamma': 0.5, 'alpha': 0.11900000000000001, 'lambda_': 0.166, 'n_estimators': 480}
Current value: 0.050219688564538956, Current params: {'in_len': 24, 'max_samples_per_ts': 100, 'lr': 0.761, 'subsample': 0.6, 'min_child_weight': 1.0, 'colsample_bytree': 1.0, 'max_depth': 4, 'gamma': 5.0, 'alpha': 0.115, 'lambda_': 0.084, 'n_estimators': 256}
Best value: 0.04517090693116188, Best params: {'in_len': 72, 'max_samples_per_ts': 50, 'lr': 0.87, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.9, 'max_depth': 7, 'gamma': 0.5, 'alpha': 0.11900000000000001, 'lambda_': 0.166, 'n_estimators': 480}
Current value: 0.04669344425201416, Current params: {'in_len': 60, 'max_samples_per_ts': 200, 'lr': 0.8240000000000001, 'subsample': 1.0, 'min_child_weight': 3.0, 'colsample_bytree': 0.9, 'max_depth': 7, 'gamma': 4.5, 'alpha': 0.094, 'lambda_': 0.18, 'n_estimators': 384}
Best value: 0.04517090693116188, Best params: {'in_len': 72, 'max_samples_per_ts': 50, 'lr': 0.87, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.9, 'max_depth': 7, 'gamma': 0.5, 'alpha': 0.11900000000000001, 'lambda_': 0.166, 'n_estimators': 480}
Current value: 0.05668996274471283, Current params: {'in_len': 72, 'max_samples_per_ts': 200, 'lr': 0.022000000000000002, 'subsample': 0.8, 'min_child_weight': 1.0, 'colsample_bytree': 1.0, 'max_depth': 10, 'gamma': 5.0, 'alpha': 0.005, 'lambda_': 0.186, 'n_estimators': 512}
Best value: 0.04517090693116188, Best params: {'in_len': 72, 'max_samples_per_ts': 50, 'lr': 0.87, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.9, 'max_depth': 7, 'gamma': 0.5, 'alpha': 0.11900000000000001, 'lambda_': 0.166, 'n_estimators': 480}
Current value: 0.051304906606674194, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'lr': 0.155, 'subsample': 0.7, 'min_child_weight': 5.0, 'colsample_bytree': 0.9, 'max_depth': 5, 'gamma': 9.5, 'alpha': 0.097, 'lambda_': 0.244, 'n_estimators': 320}
Best value: 0.04517090693116188, Best params: {'in_len': 72, 'max_samples_per_ts': 50, 'lr': 0.87, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.9, 'max_depth': 7, 'gamma': 0.5, 'alpha': 0.11900000000000001, 'lambda_': 0.166, 'n_estimators': 480}
Current value: 0.04843432456254959, Current params: {'in_len': 24, 'max_samples_per_ts': 200, 'lr': 0.4, 'subsample': 0.7, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 5, 'gamma': 6.5, 'alpha': 0.127, 'lambda_': 0.257, 'n_estimators': 416}
Best value: 0.04517090693116188, Best params: {'in_len': 72, 'max_samples_per_ts': 50, 'lr': 0.87, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.9, 'max_depth': 7, 'gamma': 0.5, 'alpha': 0.11900000000000001, 'lambda_': 0.166, 'n_estimators': 480}
Current value: 0.04911249130964279, Current params: {'in_len': 120, 'max_samples_per_ts': 200, 'lr': 0.113, 'subsample': 1.0, 'min_child_weight': 5.0, 'colsample_bytree': 0.9, 'max_depth': 7, 'gamma': 4.0, 'alpha': 0.007, 'lambda_': 0.02, 'n_estimators': 352}
Best value: 0.04517090693116188, Best params: {'in_len': 72, 'max_samples_per_ts': 50, 'lr': 0.87, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.9, 'max_depth': 7, 'gamma': 0.5, 'alpha': 0.11900000000000001, 'lambda_': 0.166, 'n_estimators': 480}
Current value: 0.046504080295562744, Current params: {'in_len': 96, 'max_samples_per_ts': 200, 'lr': 0.782, 'subsample': 0.9, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 8, 'gamma': 5.0, 'alpha': 0.115, 'lambda_': 0.068, 'n_estimators': 320}
Best value: 0.04517090693116188, Best params: {'in_len': 72, 'max_samples_per_ts': 50, 'lr': 0.87, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.9, 'max_depth': 7, 'gamma': 0.5, 'alpha': 0.11900000000000001, 'lambda_': 0.166, 'n_estimators': 480}
Current value: 0.04770631343126297, Current params: {'in_len': 144, 'max_samples_per_ts': 150, 'lr': 0.153, 'subsample': 0.6, 'min_child_weight': 3.0, 'colsample_bytree': 0.9, 'max_depth': 5, 'gamma': 3.5, 'alpha': 0.14100000000000001, 'lambda_': 0.082, 'n_estimators': 320}
Best value: 0.04517090693116188, Best params: {'in_len': 72, 'max_samples_per_ts': 50, 'lr': 0.87, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.9, 'max_depth': 7, 'gamma': 0.5, 'alpha': 0.11900000000000001, 'lambda_': 0.166, 'n_estimators': 480}
Current value: 0.050958991050720215, Current params: {'in_len': 120, 'max_samples_per_ts': 100, 'lr': 0.9480000000000001, 'subsample': 0.7, 'min_child_weight': 2.0, 'colsample_bytree': 0.8, 'max_depth': 8, 'gamma': 7.0, 'alpha': 0.082, 'lambda_': 0.253, 'n_estimators': 320}
Best value: 0.04517090693116188, Best params: {'in_len': 72, 'max_samples_per_ts': 50, 'lr': 0.87, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.9, 'max_depth': 7, 'gamma': 0.5, 'alpha': 0.11900000000000001, 'lambda_': 0.166, 'n_estimators': 480}
Current value: 0.04446215182542801, Current params: {'in_len': 48, 'max_samples_per_ts': 50, 'lr': 0.538, 'subsample': 0.8, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 0.5, 'alpha': 0.255, 'lambda_': 0.14100000000000001, 'n_estimators': 512}
Best value: 0.04446215182542801, Best params: {'in_len': 48, 'max_samples_per_ts': 50, 'lr': 0.538, 'subsample': 0.8, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 0.5, 'alpha': 0.255, 'lambda_': 0.14100000000000001, 'n_estimators': 512}
Current value: 0.044828835874795914, Current params: {'in_len': 48, 'max_samples_per_ts': 50, 'lr': 0.532, 'subsample': 0.8, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 0.5, 'alpha': 0.28200000000000003, 'lambda_': 0.139, 'n_estimators': 512}
Best value: 0.04446215182542801, Best params: {'in_len': 48, 'max_samples_per_ts': 50, 'lr': 0.538, 'subsample': 0.8, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 0.5, 'alpha': 0.255, 'lambda_': 0.14100000000000001, 'n_estimators': 512}
Current value: 0.044545553624629974, Current params: {'in_len': 48, 'max_samples_per_ts': 50, 'lr': 0.552, 'subsample': 0.8, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 0.5, 'alpha': 0.3, 'lambda_': 0.122, 'n_estimators': 448}
Best value: 0.04446215182542801, Best params: {'in_len': 48, 'max_samples_per_ts': 50, 'lr': 0.538, 'subsample': 0.8, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 0.5, 'alpha': 0.255, 'lambda_': 0.14100000000000001, 'n_estimators': 512}
Current value: 0.048034459352493286, Current params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.5750000000000001, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 2.5, 'alpha': 0.28800000000000003, 'lambda_': 0.126, 'n_estimators': 448}
Best value: 0.04446215182542801, Best params: {'in_len': 48, 'max_samples_per_ts': 50, 'lr': 0.538, 'subsample': 0.8, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 0.5, 'alpha': 0.255, 'lambda_': 0.14100000000000001, 'n_estimators': 512}
Current value: 0.04522078484296799, Current params: {'in_len': 36, 'max_samples_per_ts': 50, 'lr': 0.362, 'subsample': 0.9, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 2.0, 'alpha': 0.226, 'lambda_': 0.117, 'n_estimators': 448}
Best value: 0.04446215182542801, Best params: {'in_len': 48, 'max_samples_per_ts': 50, 'lr': 0.538, 'subsample': 0.8, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 0.5, 'alpha': 0.255, 'lambda_': 0.14100000000000001, 'n_estimators': 512}
Current value: 0.04487219825387001, Current params: {'in_len': 96, 'max_samples_per_ts': 150, 'lr': 0.651, 'subsample': 0.8, 'min_child_weight': 3.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 2.0, 'alpha': 0.214, 'lambda_': 0.211, 'n_estimators': 480}
Best value: 0.04446215182542801, Best params: {'in_len': 48, 'max_samples_per_ts': 50, 'lr': 0.538, 'subsample': 0.8, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 0.5, 'alpha': 0.255, 'lambda_': 0.14100000000000001, 'n_estimators': 512}
Current value: 0.04423605278134346, Current params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.365, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.23600000000000002, 'lambda_': 0.019000000000000003, 'n_estimators': 448}
Best value: 0.04423605278134346, Best params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.365, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.23600000000000002, 'lambda_': 0.019000000000000003, 'n_estimators': 448}
Current value: 0.04916473478078842, Current params: {'in_len': 72, 'max_samples_per_ts': 100, 'lr': 0.331, 'subsample': 0.9, 'min_child_weight': 2.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 3.0, 'alpha': 0.213, 'lambda_': 0.004, 'n_estimators': 512}
Best value: 0.04423605278134346, Best params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.365, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.23600000000000002, 'lambda_': 0.019000000000000003, 'n_estimators': 448}
Current value: 0.04645368456840515, Current params: {'in_len': 36, 'max_samples_per_ts': 150, 'lr': 0.265, 'subsample': 1.0, 'min_child_weight': 3.0, 'colsample_bytree': 1.0, 'max_depth': 8, 'gamma': 1.5, 'alpha': 0.25, 'lambda_': 0.04, 'n_estimators': 480}
Best value: 0.04423605278134346, Best params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.365, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.23600000000000002, 'lambda_': 0.019000000000000003, 'n_estimators': 448}
Current value: 0.04820360988378525, Current params: {'in_len': 84, 'max_samples_per_ts': 100, 'lr': 0.45, 'subsample': 0.9, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 6.5, 'alpha': 0.177, 'lambda_': 0.3, 'n_estimators': 416}
Best value: 0.04423605278134346, Best params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.365, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.23600000000000002, 'lambda_': 0.019000000000000003, 'n_estimators': 448}
Current value: 0.04660094529390335, Current params: {'in_len': 60, 'max_samples_per_ts': 50, 'lr': 0.665, 'subsample': 0.7, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 8, 'gamma': 9.5, 'alpha': 0.181, 'lambda_': 0.054, 'n_estimators': 416}
Best value: 0.04423605278134346, Best params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.365, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.23600000000000002, 'lambda_': 0.019000000000000003, 'n_estimators': 448}
Current value: 0.044632311910390854, Current params: {'in_len': 48, 'max_samples_per_ts': 50, 'lr': 0.497, 'subsample': 0.8, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 1.0, 'alpha': 0.258, 'lambda_': 0.107, 'n_estimators': 448}
Best value: 0.04423605278134346, Best params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.365, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.23600000000000002, 'lambda_': 0.019000000000000003, 'n_estimators': 448}
Current value: 0.04491453617811203, Current params: {'in_len': 36, 'max_samples_per_ts': 50, 'lr': 0.623, 'subsample': 0.8, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 0.5, 'alpha': 0.267, 'lambda_': 0.10500000000000001, 'n_estimators': 480}
Best value: 0.04423605278134346, Best params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.365, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.23600000000000002, 'lambda_': 0.019000000000000003, 'n_estimators': 448}
Current value: 0.04728105291724205, Current params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.272, 'subsample': 0.9, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 1.5, 'alpha': 0.292, 'lambda_': 0.20600000000000002, 'n_estimators': 384}
Best value: 0.04423605278134346, Best params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.365, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.23600000000000002, 'lambda_': 0.019000000000000003, 'n_estimators': 448}
Current value: 0.0448058620095253, Current params: {'in_len': 60, 'max_samples_per_ts': 50, 'lr': 0.454, 'subsample': 0.8, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 3.0, 'alpha': 0.244, 'lambda_': 0.151, 'n_estimators': 448}
Best value: 0.04423605278134346, Best params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.365, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.23600000000000002, 'lambda_': 0.019000000000000003, 'n_estimators': 448}
Current value: 0.047072574496269226, Current params: {'in_len': 24, 'max_samples_per_ts': 100, 'lr': 0.584, 'subsample': 0.8, 'min_child_weight': 3.0, 'colsample_bytree': 0.9, 'max_depth': 9, 'gamma': 1.5, 'alpha': 0.3, 'lambda_': 0.033, 'n_estimators': 512}
Best value: 0.04423605278134346, Best params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.365, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.23600000000000002, 'lambda_': 0.019000000000000003, 'n_estimators': 448}
Current value: 0.04449852555990219, Current params: {'in_len': 84, 'max_samples_per_ts': 50, 'lr': 0.714, 'subsample': 0.7, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 0.5, 'alpha': 0.189, 'lambda_': 0.08700000000000001, 'n_estimators': 416}
Best value: 0.04423605278134346, Best params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.365, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.23600000000000002, 'lambda_': 0.019000000000000003, 'n_estimators': 448}
Current value: 0.046472422778606415, Current params: {'in_len': 96, 'max_samples_per_ts': 150, 'lr': 0.728, 'subsample': 0.7, 'min_child_weight': 5.0, 'colsample_bytree': 0.8, 'max_depth': 6, 'gamma': 2.5, 'alpha': 0.182, 'lambda_': 0.09, 'n_estimators': 416}
Best value: 0.04423605278134346, Best params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.365, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.23600000000000002, 'lambda_': 0.019000000000000003, 'n_estimators': 448}
Current value: 0.04816770181059837, Current params: {'in_len': 108, 'max_samples_per_ts': 100, 'lr': 0.682, 'subsample': 0.7, 'min_child_weight': 3.0, 'colsample_bytree': 0.9, 'max_depth': 9, 'gamma': 7.5, 'alpha': 0.203, 'lambda_': 0.062, 'n_estimators': 352}
Best value: 0.04423605278134346, Best params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.365, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.23600000000000002, 'lambda_': 0.019000000000000003, 'n_estimators': 448}
Current value: 0.04528051242232323, Current params: {'in_len': 72, 'max_samples_per_ts': 50, 'lr': 0.908, 'subsample': 0.6, 'min_child_weight': 4.0, 'colsample_bytree': 0.9, 'max_depth': 8, 'gamma': 0.5, 'alpha': 0.234, 'lambda_': 0.155, 'n_estimators': 480}
Best value: 0.04423605278134346, Best params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.365, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.23600000000000002, 'lambda_': 0.019000000000000003, 'n_estimators': 448}
Current value: 0.051329273730516434, Current params: {'in_len': 84, 'max_samples_per_ts': 50, 'lr': 0.267, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 8.5, 'alpha': 0.16, 'lambda_': 0.010000000000000002, 'n_estimators': 384}
Best value: 0.04423605278134346, Best params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.365, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.23600000000000002, 'lambda_': 0.019000000000000003, 'n_estimators': 448}
Current value: 0.044687025249004364, Current params: {'in_len': 60, 'max_samples_per_ts': 50, 'lr': 0.54, 'subsample': 0.7, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 1.0, 'alpha': 0.269, 'lambda_': 0.125, 'n_estimators': 448}
Best value: 0.04423605278134346, Best params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.365, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.23600000000000002, 'lambda_': 0.019000000000000003, 'n_estimators': 448}
Current value: 0.04435184597969055, Current params: {'in_len': 48, 'max_samples_per_ts': 50, 'lr': 0.446, 'subsample': 0.8, 'min_child_weight': 3.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 0.5, 'alpha': 0.195, 'lambda_': 0.17200000000000001, 'n_estimators': 480}
Best value: 0.04423605278134346, Best params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.365, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.23600000000000002, 'lambda_': 0.019000000000000003, 'n_estimators': 448}
Current value: 0.04520749673247337, Current params: {'in_len': 36, 'max_samples_per_ts': 50, 'lr': 0.463, 'subsample': 0.6, 'min_child_weight': 3.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 1.0, 'alpha': 0.196, 'lambda_': 0.17500000000000002, 'n_estimators': 480}
Best value: 0.04423605278134346, Best params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.365, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.23600000000000002, 'lambda_': 0.019000000000000003, 'n_estimators': 448}
Current value: 0.046825654804706573, Current params: {'in_len': 72, 'max_samples_per_ts': 100, 'lr': 0.838, 'subsample': 0.8, 'min_child_weight': 2.0, 'colsample_bytree': 0.8, 'max_depth': 10, 'gamma': 2.0, 'alpha': 0.164, 'lambda_': 0.202, 'n_estimators': 512}
Best value: 0.04423605278134346, Best params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.365, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.23600000000000002, 'lambda_': 0.019000000000000003, 'n_estimators': 448}
Current value: 0.04430435597896576, Current params: {'in_len': 60, 'max_samples_per_ts': 50, 'lr': 0.386, 'subsample': 1.0, 'min_child_weight': 3.0, 'colsample_bytree': 1.0, 'max_depth': 7, 'gamma': 1.0, 'alpha': 0.229, 'lambda_': 0.166, 'n_estimators': 480}
Best value: 0.04423605278134346, Best params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.365, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.23600000000000002, 'lambda_': 0.019000000000000003, 'n_estimators': 448}
Current value: 0.04448242858052254, Current params: {'in_len': 60, 'max_samples_per_ts': 50, 'lr': 0.41000000000000003, 'subsample': 1.0, 'min_child_weight': 3.0, 'colsample_bytree': 1.0, 'max_depth': 7, 'gamma': 1.5, 'alpha': 0.233, 'lambda_': 0.167, 'n_estimators': 480}
Best value: 0.04423605278134346, Best params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.365, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.23600000000000002, 'lambda_': 0.019000000000000003, 'n_estimators': 448}
Current value: 0.04919012263417244, Current params: {'in_len': 24, 'max_samples_per_ts': 100, 'lr': 0.327, 'subsample': 1.0, 'min_child_weight': 1.0, 'colsample_bytree': 1.0, 'max_depth': 6, 'gamma': 4.0, 'alpha': 0.216, 'lambda_': 0.23600000000000002, 'n_estimators': 512}
Best value: 0.04423605278134346, Best params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.365, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.23600000000000002, 'lambda_': 0.019000000000000003, 'n_estimators': 448}
Current value: 0.044545575976371765, Current params: {'in_len': 60, 'max_samples_per_ts': 50, 'lr': 0.388, 'subsample': 1.0, 'min_child_weight': 2.0, 'colsample_bytree': 1.0, 'max_depth': 6, 'gamma': 2.5, 'alpha': 0.244, 'lambda_': 0.223, 'n_estimators': 480}
Best value: 0.04423605278134346, Best params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.365, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.23600000000000002, 'lambda_': 0.019000000000000003, 'n_estimators': 448}
Current value: 0.04429057613015175, Current params: {'in_len': 36, 'max_samples_per_ts': 50, 'lr': 0.493, 'subsample': 0.9, 'min_child_weight': 3.0, 'colsample_bytree': 0.9, 'max_depth': 7, 'gamma': 1.0, 'alpha': 0.267, 'lambda_': 0.183, 'n_estimators': 256}
Best value: 0.04423605278134346, Best params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.365, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.23600000000000002, 'lambda_': 0.019000000000000003, 'n_estimators': 448}
Current value: 0.04963444173336029, Current params: {'in_len': 36, 'max_samples_per_ts': 150, 'lr': 0.222, 'subsample': 1.0, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 7, 'gamma': 5.5, 'alpha': 0.275, 'lambda_': 0.189, 'n_estimators': 256}
Best value: 0.04423605278134346, Best params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.365, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.23600000000000002, 'lambda_': 0.019000000000000003, 'n_estimators': 448}
Current value: 0.04441375657916069, Current params: {'in_len': 48, 'max_samples_per_ts': 50, 'lr': 0.49, 'subsample': 0.9, 'min_child_weight': 3.0, 'colsample_bytree': 1.0, 'max_depth': 7, 'gamma': 1.0, 'alpha': 0.257, 'lambda_': 0.14300000000000002, 'n_estimators': 256}
Best value: 0.04423605278134346, Best params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.365, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.23600000000000002, 'lambda_': 0.019000000000000003, 'n_estimators': 448}
Current value: 0.04442570358514786, Current params: {'in_len': 24, 'max_samples_per_ts': 50, 'lr': 0.43, 'subsample': 0.9, 'min_child_weight': 3.0, 'colsample_bytree': 1.0, 'max_depth': 7, 'gamma': 1.0, 'alpha': 0.23, 'lambda_': 0.188, 'n_estimators': 256}
Best value: 0.04423605278134346, Best params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.365, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.23600000000000002, 'lambda_': 0.019000000000000003, 'n_estimators': 448}
Current value: 0.04432349652051926, Current params: {'in_len': 36, 'max_samples_per_ts': 50, 'lr': 0.495, 'subsample': 0.9, 'min_child_weight': 3.0, 'colsample_bytree': 1.0, 'max_depth': 6, 'gamma': 1.5, 'alpha': 0.064, 'lambda_': 0.169, 'n_estimators': 288}
Best value: 0.04423605278134346, Best params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.365, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.23600000000000002, 'lambda_': 0.019000000000000003, 'n_estimators': 448}
Current value: 0.04662061482667923, Current params: {'in_len': 36, 'max_samples_per_ts': 100, 'lr': 0.339, 'subsample': 0.9, 'min_child_weight': 3.0, 'colsample_bytree': 1.0, 'max_depth': 6, 'gamma': 2.0, 'alpha': 0.045, 'lambda_': 0.16, 'n_estimators': 288}
Best value: 0.04423605278134346, Best params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.365, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.23600000000000002, 'lambda_': 0.019000000000000003, 'n_estimators': 448}
Current value: 0.04598869010806084, Current params: {'in_len': 24, 'max_samples_per_ts': 50, 'lr': 0.20700000000000002, 'subsample': 1.0, 'min_child_weight': 3.0, 'colsample_bytree': 1.0, 'max_depth': 5, 'gamma': 3.0, 'alpha': 0.068, 'lambda_': 0.183, 'n_estimators': 288}
Best value: 0.04423605278134346, Best params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.365, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.23600000000000002, 'lambda_': 0.019000000000000003, 'n_estimators': 448}
Current value: 0.046204064041376114, Current params: {'in_len': 36, 'max_samples_per_ts': 50, 'lr': 0.045, 'subsample': 0.9, 'min_child_weight': 2.0, 'colsample_bytree': 0.9, 'max_depth': 4, 'gamma': 1.5, 'alpha': 0.046, 'lambda_': 0.27, 'n_estimators': 288}
Best value: 0.04423605278134346, Best params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.365, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.23600000000000002, 'lambda_': 0.019000000000000003, 'n_estimators': 448}
Current value: 0.04674453288316727, Current params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.605, 'subsample': 1.0, 'min_child_weight': 3.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 3.5, 'alpha': 0.138, 'lambda_': 0.169, 'n_estimators': 352}
Best value: 0.04423605278134346, Best params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.365, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.23600000000000002, 'lambda_': 0.019000000000000003, 'n_estimators': 448}
Current value: 0.04442616179585457, Current params: {'in_len': 72, 'max_samples_per_ts': 50, 'lr': 0.387, 'subsample': 0.9, 'min_child_weight': 3.0, 'colsample_bytree': 1.0, 'max_depth': 8, 'gamma': 0.5, 'alpha': 0.022000000000000002, 'lambda_': 0.195, 'n_estimators': 288}
Best value: 0.04423605278134346, Best params: {'in_len': 48, 'max_samples_per_ts': 100, 'lr': 0.365, 'subsample': 0.9, 'min_child_weight': 4.0, 'colsample_bytree': 0.8, 'max_depth': 9, 'gamma': 0.5, 'alpha': 0.23600000000000002, 'lambda_': 0.019000000000000003, 'n_estimators': 448}
Current value: 0.044133659452199936, Current params: {'in_len': 60, 'max_samples_per_ts': 50, 'lr': 0.515, 'subsample': 0.9, 'min_child_weight': 3.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 2.0, 'alpha': 0.099, 'lambda_': 0.134, 'n_estimators': 256}
Best value: 0.044133659452199936, Best params: {'in_len': 60, 'max_samples_per_ts': 50, 'lr': 0.515, 'subsample': 0.9, 'min_child_weight': 3.0, 'colsample_bytree': 0.9, 'max_depth': 6, 'gamma': 2.0, 'alpha': 0.099, 'lambda_': 0.134, 'n_estimators': 256}
--------------------------------
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)
		Age: REAL_VALUED (STATIC_INPUT)
		BMI: REAL_VALUED (STATIC_INPUT)
		A1C: REAL_VALUED (STATIC_INPUT)
		FBG: REAL_VALUED (STATIC_INPUT)
		ogtt.2hr: REAL_VALUED (STATIC_INPUT)
		insulin: REAL_VALUED (STATIC_INPUT)
		hs.CRP: REAL_VALUED (STATIC_INPUT)
		Tchol: REAL_VALUED (STATIC_INPUT)
		Trg: REAL_VALUED (STATIC_INPUT)
		HDL: REAL_VALUED (STATIC_INPUT)
		LDL: REAL_VALUED (STATIC_INPUT)
		mean_glucose: REAL_VALUED (STATIC_INPUT)
		sd_glucose: REAL_VALUED (STATIC_INPUT)
		range_glucose: REAL_VALUED (STATIC_INPUT)
		min_glucose: REAL_VALUED (STATIC_INPUT)
		max_glucose: REAL_VALUED (STATIC_INPUT)
		quartile.25_glucose: REAL_VALUED (STATIC_INPUT)
		median_glucose: REAL_VALUED (STATIC_INPUT)
		quartile.75_glucose: REAL_VALUED (STATIC_INPUT)
		mean_slope: REAL_VALUED (STATIC_INPUT)
		max_slope: REAL_VALUED (STATIC_INPUT)
		number_Random140: REAL_VALUED (STATIC_INPUT)
		number_Random200: REAL_VALUED (STATIC_INPUT)
		percent_below.80: REAL_VALUED (STATIC_INPUT)
		se_glucose_mean: REAL_VALUED (STATIC_INPUT)
		numGE: REAL_VALUED (STATIC_INPUT)
		mage: REAL_VALUED (STATIC_INPUT)
		j_index: REAL_VALUED (STATIC_INPUT)
		IQR: REAL_VALUED (STATIC_INPUT)
		modd: REAL_VALUED (STATIC_INPUT)
		distance_traveled: REAL_VALUED (STATIC_INPUT)
		coef_variation: REAL_VALUED (STATIC_INPUT)
		number_Random140_normByDays: REAL_VALUED (STATIC_INPUT)
		number_Random200_normByDays: REAL_VALUED (STATIC_INPUT)
		numGE_normByDays: REAL_VALUED (STATIC_INPUT)
		distance_traveled_normByDays: REAL_VALUED (STATIC_INPUT)
		diagnosis: REAL_VALUED (STATIC_INPUT)
		freq_low: REAL_VALUED (STATIC_INPUT)
		freq_moderate: REAL_VALUED (STATIC_INPUT)
		freq_severe: REAL_VALUED (STATIC_INPUT)
		glucotype: REAL_VALUED (STATIC_INPUT)
		Height: REAL_VALUED (STATIC_INPUT)
		Weight: REAL_VALUED (STATIC_INPUT)
		Insulin_rate_dd: REAL_VALUED (STATIC_INPUT)
		perc_cgm_prediabetic_range: REAL_VALUED (STATIC_INPUT)
		perc_cgm_diabetic_range: REAL_VALUED (STATIC_INPUT)
		SSPG: 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: 160
	Extracted segments: 152
	Interpolated values: 8003
	Percent of values interpolated: 8.57%
Splitting data...
	Train: 62461 (61.57%)
	Val: 12357 (12.18%)
	Test: 16517 (16.28%)
	Test OOD: 10113 (9.97%)
Scaling data...
	No scaling applied
Data formatting complete.
--------------------------------
	Train: 62090 (61.20%)
	Val: 12502 (12.32%)
	Test: 16648 (16.41%)
	Test OOD: 10208 (10.06%)
	No scaling applied
		Model Seed: 10 Seed: 1 ID mean of (MSE, MAE): [248.27441    9.721242]
		Model Seed: 10 Seed: 1 OOD mean of (MSE, MAE) stats: [199.87634    8.999042]
		Model Seed: 10 Seed: 1 ID median of (MSE, MAE): [58.44371   6.594284]
		Model Seed: 10 Seed: 1 OOD median of (MSE, MAE) stats: [57.295467  6.609444]
		Model Seed: 10 Seed: 1 ID likelihoods: -9.676205823851188
		Model Seed: 10 Seed: 1 OOD likelihoods: -9.567788168656268
		Model Seed: 10 Seed: 1 ID calibration errors: [0.36148078 0.23801333 0.14277208 0.10378589 0.06948271 0.05097461
 0.03643781 0.03256118 0.02565583 0.02095336 0.01767789 0.01375484]
		Model Seed: 10 Seed: 1 OOD calibration errors: [0.28165617 0.19719359 0.12310864 0.09330017 0.06772939 0.0582993
 0.04759474 0.04256331 0.04063892 0.04212512 0.03351146 0.0295703 ]
	Train: 64804 (63.70%)
	Val: 12349 (12.14%)
	Test: 16419 (16.14%)
	Test OOD: 8164 (8.02%)
	No scaling applied
		Model Seed: 10 Seed: 2 ID mean of (MSE, MAE): [254.76892   9.64046]
		Model Seed: 10 Seed: 2 OOD mean of (MSE, MAE) stats: [200.26341    9.214825]
		Model Seed: 10 Seed: 2 ID median of (MSE, MAE): [55.41252   6.355793]
		Model Seed: 10 Seed: 2 OOD median of (MSE, MAE) stats: [55.607166   6.4082565]
		Model Seed: 10 Seed: 2 ID likelihoods: -9.68911751317334
		Model Seed: 10 Seed: 2 OOD likelihoods: -9.568754933416614
		Model Seed: 10 Seed: 2 ID calibration errors: [0.38062294 0.25605414 0.16297462 0.11753788 0.08202422 0.0614103
 0.04310375 0.03346342 0.02684469 0.02026425 0.01631772 0.01237763]
		Model Seed: 10 Seed: 2 OOD calibration errors: [0.34693495 0.21107637 0.13271154 0.08083214 0.04872718 0.03235532
 0.0222957  0.01935129 0.01623046 0.01362592 0.01176883 0.00765251]
	Model Seed: 10 ID mean of (MSE, MAE): [251.52167    9.680851]
	Model Seed: 10 OOD mean of (MSE, MAE): [200.06989    9.106934]
	Model Seed: 10 ID median of (MSE, MAE): [56.928116   6.4750385]
	Model Seed: 10 OOD median of (MSE, MAE): [56.451317  6.50885 ]
	Model Seed: 10 ID likelihoods: -9.682661668512264
	Model Seed: 10 OOD likelihoods: -9.56827155103644
	Model Seed: 10 ID calibration errors: [0.37105186 0.24703373 0.15287335 0.11066188 0.07575347 0.05619245
 0.03977078 0.0330123  0.02625026 0.0206088  0.01699781 0.01306624]
	Model Seed: 10 OOD calibration errors: [0.31429556 0.20413498 0.12791009 0.08706615 0.05822828 0.04532731
 0.03494522 0.0309573  0.02843469 0.02787552 0.02264014 0.01861141]
	Train: 62090 (61.20%)
	Val: 12502 (12.32%)
	Test: 16648 (16.41%)
	Test OOD: 10208 (10.06%)
	No scaling applied
		Model Seed: 11 Seed: 1 ID mean of (MSE, MAE): [235.58955   9.52412]
		Model Seed: 11 Seed: 1 OOD mean of (MSE, MAE) stats: [195.18875    9.050379]
		Model Seed: 11 Seed: 1 ID median of (MSE, MAE): [58.90818    6.7373486]
		Model Seed: 11 Seed: 1 OOD median of (MSE, MAE) stats: [58.536713   6.7839756]
		Model Seed: 11 Seed: 1 ID likelihoods: -9.649984413159654
		Model Seed: 11 Seed: 1 OOD likelihoods: -9.555922134066886
		Model Seed: 11 Seed: 1 ID calibration errors: [0.37029504 0.20085726 0.13422282 0.09652124 0.06887788 0.04738094
 0.03411462 0.02790774 0.02025612 0.01839764 0.01506494 0.01213884]
		Model Seed: 11 Seed: 1 OOD calibration errors: [0.30638419 0.15907299 0.11492385 0.08103433 0.06469473 0.05560871
 0.04366858 0.04030065 0.03949368 0.04017129 0.03298671 0.03014191]
	Train: 64804 (63.70%)
	Val: 12349 (12.14%)
	Test: 16419 (16.14%)
	Test OOD: 8164 (8.02%)
	No scaling applied
		Model Seed: 11 Seed: 2 ID mean of (MSE, MAE): [253.18869    9.670842]
		Model Seed: 11 Seed: 2 OOD mean of (MSE, MAE) stats: [198.33572    9.259074]
		Model Seed: 11 Seed: 2 ID median of (MSE, MAE): [55.898857  6.374017]
		Model Seed: 11 Seed: 2 OOD median of (MSE, MAE) stats: [56.81901   6.518635]
		Model Seed: 11 Seed: 2 ID likelihoods: -9.686005742751602
		Model Seed: 11 Seed: 2 OOD likelihoods: -9.563919002786438
		Model Seed: 11 Seed: 2 ID calibration errors: [0.3579753  0.24347813 0.1515164  0.11135099 0.0772209  0.05868696
 0.04144404 0.03384559 0.02642203 0.02266233 0.01787342 0.014946  ]
		Model Seed: 11 Seed: 2 OOD calibration errors: [0.31543579 0.20538992 0.12118347 0.07194494 0.04369088 0.02948381
 0.01910404 0.01827305 0.01609451 0.01291011 0.0108408  0.00749036]
	Model Seed: 11 ID mean of (MSE, MAE): [244.38913    9.597481]
	Model Seed: 11 OOD mean of (MSE, MAE): [196.76224    9.154726]
	Model Seed: 11 ID median of (MSE, MAE): [57.40352    6.5556827]
	Model Seed: 11 OOD median of (MSE, MAE): [57.677864  6.651305]
	Model Seed: 11 ID likelihoods: -9.667995077955627
	Model Seed: 11 OOD likelihoods: -9.559920568426662
	Model Seed: 11 ID calibration errors: [0.36413517 0.22216769 0.14286961 0.10393612 0.07304939 0.05303395
 0.03777933 0.03087667 0.02333908 0.02052998 0.01646918 0.01354242]
	Model Seed: 11 OOD calibration errors: [0.31090999 0.18223145 0.11805366 0.07648963 0.0541928  0.04254626
 0.03138631 0.02928685 0.02779409 0.0265407  0.02191375 0.01881614]
	Train: 62090 (61.20%)
	Val: 12502 (12.32%)
	Test: 16648 (16.41%)
	Test OOD: 10208 (10.06%)
	No scaling applied
		Model Seed: 12 Seed: 1 ID mean of (MSE, MAE): [235.72623    9.520805]
		Model Seed: 12 Seed: 1 OOD mean of (MSE, MAE) stats: [194.01373    9.022826]
		Model Seed: 12 Seed: 1 ID median of (MSE, MAE): [59.68738    6.7147164]
		Model Seed: 12 Seed: 1 OOD median of (MSE, MAE) stats: [57.834064   6.7689056]
		Model Seed: 12 Seed: 1 ID likelihoods: -9.65027397397613
		Model Seed: 12 Seed: 1 OOD likelihoods: -9.552903202201918
		Model Seed: 12 Seed: 1 ID calibration errors: [0.37771508 0.20328061 0.13652279 0.09760212 0.07100449 0.04916927
 0.03577347 0.02858525 0.02075905 0.01894297 0.01539956 0.0123397 ]
		Model Seed: 12 Seed: 1 OOD calibration errors: [0.30034809 0.1506635  0.10909368 0.07762616 0.05947181 0.0501083
 0.03928383 0.03497957 0.03526166 0.03470909 0.0296173  0.02619346]
	Train: 64804 (63.70%)
	Val: 12349 (12.14%)
	Test: 16419 (16.14%)
	Test OOD: 8164 (8.02%)
	No scaling applied
		Model Seed: 12 Seed: 2 ID mean of (MSE, MAE): [249.49294    9.548201]
		Model Seed: 12 Seed: 2 OOD mean of (MSE, MAE) stats: [199.95119    9.170156]
		Model Seed: 12 Seed: 2 ID median of (MSE, MAE): [55.123337  6.335981]
		Model Seed: 12 Seed: 2 OOD median of (MSE, MAE) stats: [54.728355  6.394911]
		Model Seed: 12 Seed: 2 ID likelihoods: -9.678653740906615
		Model Seed: 12 Seed: 2 OOD likelihoods: -9.567974902324822
		Model Seed: 12 Seed: 2 ID calibration errors: [0.38850644 0.2484657  0.16478204 0.1175791  0.08430259 0.05884201
 0.04257212 0.03310759 0.02766514 0.0208539  0.01735005 0.01339581]
		Model Seed: 12 Seed: 2 OOD calibration errors: [0.3566355  0.21132466 0.13465995 0.08610504 0.05246782 0.03359053
 0.02271522 0.01950255 0.01564801 0.01407683 0.01032373 0.00769999]
	Model Seed: 12 ID mean of (MSE, MAE): [242.60959    9.534503]
	Model Seed: 12 OOD mean of (MSE, MAE): [196.98245    9.096491]
	Model Seed: 12 ID median of (MSE, MAE): [57.405357   6.5253487]
	Model Seed: 12 OOD median of (MSE, MAE): [56.28121   6.581908]
	Model Seed: 12 ID likelihoods: -9.664463857441373
	Model Seed: 12 OOD likelihoods: -9.56043905226337
	Model Seed: 12 ID calibration errors: [0.38311076 0.22587315 0.15065242 0.10759061 0.07765354 0.05400564
 0.03917279 0.03084642 0.02421209 0.01989843 0.0163748  0.01286775]
	Model Seed: 12 OOD calibration errors: [0.32849179 0.18099408 0.12187681 0.0818656  0.05596982 0.04184941
 0.03099953 0.02724106 0.02545483 0.02439296 0.01997051 0.01694673]
	Train: 62090 (61.20%)
	Val: 12502 (12.32%)
	Test: 16648 (16.41%)
	Test OOD: 10208 (10.06%)
	No scaling applied
		Model Seed: 13 Seed: 1 ID mean of (MSE, MAE): [259.14124    9.953541]
		Model Seed: 13 Seed: 1 OOD mean of (MSE, MAE) stats: [198.08813    8.850965]
		Model Seed: 13 Seed: 1 ID median of (MSE, MAE): [62.916603   6.8461685]
		Model Seed: 13 Seed: 1 OOD median of (MSE, MAE) stats: [54.903534  6.336552]
		Model Seed: 13 Seed: 1 ID likelihoods: -9.697624791566557
		Model Seed: 13 Seed: 1 OOD likelihoods: -9.563295062268727
		Model Seed: 13 Seed: 1 ID calibration errors: [0.31624573 0.24945275 0.12876918 0.11281732 0.06627479 0.05425382
 0.03523992 0.03256798 0.02324409 0.0201577  0.01470197 0.01304173]
		Model Seed: 13 Seed: 1 OOD calibration errors: [0.26662628 0.20321645 0.11402573 0.09465525 0.06057978 0.05549798
 0.03932272 0.03437825 0.02888824 0.03029882 0.02349734 0.01798005]
	Train: 64804 (63.70%)
	Val: 12349 (12.14%)
	Test: 16419 (16.14%)
	Test OOD: 8164 (8.02%)
	No scaling applied
		Model Seed: 13 Seed: 2 ID mean of (MSE, MAE): [265.38562  10.03705]
		Model Seed: 13 Seed: 2 OOD mean of (MSE, MAE) stats: [209.23943    9.463287]
		Model Seed: 13 Seed: 2 ID median of (MSE, MAE): [60.39038    6.7686224]
		Model Seed: 13 Seed: 2 OOD median of (MSE, MAE) stats: [58.09333    6.4160776]
		Model Seed: 13 Seed: 2 ID likelihoods: -9.70953061745076
		Model Seed: 13 Seed: 2 OOD likelihoods: -9.590678120008906
		Model Seed: 13 Seed: 2 ID calibration errors: [0.30379477 0.23885575 0.12914647 0.11051641 0.0679632  0.05728182
 0.03618602 0.03410797 0.0244927  0.02152525 0.01587413 0.01340472]
		Model Seed: 13 Seed: 2 OOD calibration errors: [0.28591461 0.21994749 0.11473088 0.08729173 0.05028435 0.0379035
 0.02228584 0.01936348 0.01720544 0.01529621 0.01264834 0.00925301]
	Model Seed: 13 ID mean of (MSE, MAE): [262.26343    9.995296]
	Model Seed: 13 OOD mean of (MSE, MAE): [203.66379    9.157125]
	Model Seed: 13 ID median of (MSE, MAE): [61.653492   6.8073955]
	Model Seed: 13 OOD median of (MSE, MAE): [56.498432  6.376315]
	Model Seed: 13 ID likelihoods: -9.703577704508659
	Model Seed: 13 OOD likelihoods: -9.576986591138816
	Model Seed: 13 ID calibration errors: [0.31002025 0.24415425 0.12895783 0.11166686 0.06711899 0.05576782
 0.03571297 0.03333798 0.02386839 0.02084148 0.01528805 0.01322322]
	Model Seed: 13 OOD calibration errors: [0.27627045 0.21158197 0.1143783  0.09097349 0.05543207 0.04670074
 0.03080428 0.02687087 0.02304684 0.02279751 0.01807284 0.01361653]
	Train: 62090 (61.20%)
	Val: 12502 (12.32%)
	Test: 16648 (16.41%)
	Test OOD: 10208 (10.06%)
	No scaling applied
		Model Seed: 14 Seed: 1 ID mean of (MSE, MAE): [235.7228     9.523744]
		Model Seed: 14 Seed: 1 OOD mean of (MSE, MAE) stats: [194.86859    9.048724]
		Model Seed: 14 Seed: 1 ID median of (MSE, MAE): [58.33608   6.729618]
		Model Seed: 14 Seed: 1 OOD median of (MSE, MAE) stats: [58.513638  6.786567]
		Model Seed: 14 Seed: 1 ID likelihoods: -9.650266885882488
		Model Seed: 14 Seed: 1 OOD likelihoods: -9.555100627116621
		Model Seed: 14 Seed: 1 ID calibration errors: [0.37422027 0.20109441 0.13583158 0.09719457 0.07004654 0.0478925
 0.034546   0.0278436  0.02056116 0.01885231 0.0153602  0.01261943]
		Model Seed: 14 Seed: 1 OOD calibration errors: [0.30561327 0.15832003 0.11440788 0.08094763 0.06446152 0.05532284
 0.04320446 0.04006245 0.03938821 0.04010215 0.03301169 0.03009843]
	Train: 64804 (63.70%)
	Val: 12349 (12.14%)
	Test: 16419 (16.14%)
	Test OOD: 8164 (8.02%)
	No scaling applied
		Model Seed: 14 Seed: 2 ID mean of (MSE, MAE): [252.5153    9.64929]
		Model Seed: 14 Seed: 2 OOD mean of (MSE, MAE) stats: [197.71266    9.223301]
		Model Seed: 14 Seed: 2 ID median of (MSE, MAE): [55.96233    6.3859987]
		Model Seed: 14 Seed: 2 OOD median of (MSE, MAE) stats: [56.945198   6.5206866]
		Model Seed: 14 Seed: 2 ID likelihoods: -9.68467467420922
		Model Seed: 14 Seed: 2 OOD likelihoods: -9.562345688355748
		Model Seed: 14 Seed: 2 ID calibration errors: [0.35126174 0.24509983 0.1524146  0.11159243 0.07759555 0.05789185
 0.04046928 0.03280978 0.02564345 0.02118604 0.01773158 0.01371327]
		Model Seed: 14 Seed: 2 OOD calibration errors: [0.31438738 0.20445566 0.12244774 0.07431131 0.04323582 0.02760727
 0.01953861 0.01587113 0.01566124 0.01245661 0.00894454 0.00661993]
	Model Seed: 14 ID mean of (MSE, MAE): [244.11905    9.586517]
	Model Seed: 14 OOD mean of (MSE, MAE): [196.29062    9.136013]
	Model Seed: 14 ID median of (MSE, MAE): [57.149204   6.5578084]
	Model Seed: 14 OOD median of (MSE, MAE): [57.729416  6.653627]
	Model Seed: 14 ID likelihoods: -9.667470780045853
	Model Seed: 14 OOD likelihoods: -9.558723157736186
	Model Seed: 14 ID calibration errors: [0.362741   0.22309712 0.14412309 0.1043935  0.07382104 0.05289218
 0.03750764 0.03032669 0.0231023  0.02001918 0.01654589 0.01316635]
	Model Seed: 14 OOD calibration errors: [0.31000032 0.18138785 0.11842781 0.07762947 0.05384867 0.04146505
 0.03137153 0.02796679 0.02752473 0.02627938 0.02097811 0.01835918]
	Train: 62090 (61.20%)
	Val: 12502 (12.32%)
	Test: 16648 (16.41%)
	Test OOD: 10208 (10.06%)
	No scaling applied
		Model Seed: 15 Seed: 1 ID mean of (MSE, MAE): [240.93773    9.594775]
		Model Seed: 15 Seed: 1 OOD mean of (MSE, MAE) stats: [193.50441    8.925234]
		Model Seed: 15 Seed: 1 ID median of (MSE, MAE): [56.404858  6.574821]
		Model Seed: 15 Seed: 1 OOD median of (MSE, MAE) stats: [55.032703   6.5452075]
		Model Seed: 15 Seed: 1 ID likelihoods: -9.661207821730452
		Model Seed: 15 Seed: 1 OOD likelihoods: -9.551589078390869
		Model Seed: 15 Seed: 1 ID calibration errors: [0.38972531 0.22176638 0.14198751 0.10068764 0.0716683  0.0511506
 0.03691909 0.02939365 0.02394577 0.01876698 0.01455591 0.01130959]
		Model Seed: 15 Seed: 1 OOD calibration errors: [0.31544455 0.16634493 0.11801846 0.08102487 0.06326092 0.05178058
 0.04221492 0.03184282 0.03235474 0.03300143 0.02903826 0.02172945]
	Train: 64804 (63.70%)
	Val: 12349 (12.14%)
	Test: 16419 (16.14%)
	Test OOD: 8164 (8.02%)
	No scaling applied
		Model Seed: 15 Seed: 2 ID mean of (MSE, MAE): [253.00711    9.635793]
		Model Seed: 15 Seed: 2 OOD mean of (MSE, MAE) stats: [200.60614     9.1831875]
		Model Seed: 15 Seed: 2 ID median of (MSE, MAE): [55.20612   6.392331]
		Model Seed: 15 Seed: 2 OOD median of (MSE, MAE) stats: [51.639572   6.1280003]
		Model Seed: 15 Seed: 2 ID likelihoods: -9.685646907763392
		Model Seed: 15 Seed: 2 OOD likelihoods: -9.569610693511516
		Model Seed: 15 Seed: 2 ID calibration errors: [0.3771526  0.24381945 0.15993603 0.11262118 0.08317525 0.05732001
 0.04044422 0.03214072 0.02618132 0.01911533 0.01634389 0.01252616]
		Model Seed: 15 Seed: 2 OOD calibration errors: [0.35920813 0.22000898 0.13777274 0.08197809 0.05076043 0.03200404
 0.02323514 0.02045262 0.01672755 0.01333067 0.01094925 0.00733288]
	Model Seed: 15 ID mean of (MSE, MAE): [246.97241    9.615284]
	Model Seed: 15 OOD mean of (MSE, MAE): [197.05527    9.054211]
	Model Seed: 15 ID median of (MSE, MAE): [55.80549   6.483576]
	Model Seed: 15 OOD median of (MSE, MAE): [53.336136  6.336604]
	Model Seed: 15 ID likelihoods: -9.67342736474692
	Model Seed: 15 OOD likelihoods: -9.560599885951191
	Model Seed: 15 ID calibration errors: [0.38343896 0.23279291 0.15096177 0.10665441 0.07742178 0.05423531
 0.03868166 0.03076718 0.02506355 0.01894116 0.0154499  0.01191788]
	Model Seed: 15 OOD calibration errors: [0.33732634 0.19317695 0.1278956  0.08150148 0.05701067 0.04189231
 0.03272503 0.02614772 0.02454114 0.02316605 0.01999375 0.01453117]
	Train: 62090 (61.20%)
	Val: 12502 (12.32%)
	Test: 16648 (16.41%)
	Test OOD: 10208 (10.06%)
	No scaling applied
		Model Seed: 16 Seed: 1 ID mean of (MSE, MAE): [241.55238     9.6162195]
		Model Seed: 16 Seed: 1 OOD mean of (MSE, MAE) stats: [195.85611    9.007556]
		Model Seed: 16 Seed: 1 ID median of (MSE, MAE): [60.13385   6.776716]
		Model Seed: 16 Seed: 1 OOD median of (MSE, MAE) stats: [58.00432   6.668417]
		Model Seed: 16 Seed: 1 ID likelihoods: -9.662481617527428
		Model Seed: 16 Seed: 1 OOD likelihoods: -9.557628388038806
		Model Seed: 16 Seed: 1 ID calibration errors: [0.3787232  0.21379594 0.14050387 0.09937108 0.06903816 0.04886423
 0.03491761 0.02845141 0.02261831 0.01840296 0.01488119 0.01330017]
		Model Seed: 16 Seed: 1 OOD calibration errors: [0.30439484 0.16424121 0.12367012 0.09019853 0.06931376 0.06047337
 0.04719895 0.04062798 0.04339189 0.04451336 0.03577493 0.03123502]
	Train: 64804 (63.70%)
	Val: 12349 (12.14%)
	Test: 16419 (16.14%)
	Test OOD: 8164 (8.02%)
	No scaling applied
		Model Seed: 16 Seed: 2 ID mean of (MSE, MAE): [248.6216     9.531709]
		Model Seed: 16 Seed: 2 OOD mean of (MSE, MAE) stats: [196.40273    9.112962]
		Model Seed: 16 Seed: 2 ID median of (MSE, MAE): [54.751717  6.352172]
		Model Seed: 16 Seed: 2 OOD median of (MSE, MAE) stats: [54.72573   6.413931]
		Model Seed: 16 Seed: 2 ID likelihoods: -9.676904374567506
		Model Seed: 16 Seed: 2 OOD likelihoods: -9.559021702900614
		Model Seed: 16 Seed: 2 ID calibration errors: [0.38584709 0.24381431 0.16215941 0.11660966 0.08414285 0.05844607
 0.04240908 0.0329047  0.02623071 0.02029417 0.01716663 0.01313115]
		Model Seed: 16 Seed: 2 OOD calibration errors: [0.35575677 0.2075547  0.13248219 0.08283711 0.05056351 0.03149112
 0.02099667 0.01741196 0.01404362 0.01268544 0.00957939 0.00692244]
	Model Seed: 16 ID mean of (MSE, MAE): [245.08699    9.573964]
	Model Seed: 16 OOD mean of (MSE, MAE): [196.12943    9.060259]
	Model Seed: 16 ID median of (MSE, MAE): [57.442783  6.564444]
	Model Seed: 16 OOD median of (MSE, MAE): [56.365025  6.541174]
	Model Seed: 16 ID likelihoods: -9.669692996047466
	Model Seed: 16 OOD likelihoods: -9.55832504546971
	Model Seed: 16 ID calibration errors: [0.38228514 0.22880512 0.15133164 0.10799037 0.07659051 0.05365515
 0.03866334 0.03067806 0.02442451 0.01934857 0.01602391 0.01321566]
	Model Seed: 16 OOD calibration errors: [0.3300758  0.18589796 0.12807615 0.08651782 0.05993864 0.04598225
 0.03409781 0.02901997 0.02871775 0.0285994  0.02267716 0.01907873]
	Train: 62090 (61.20%)
	Val: 12502 (12.32%)
	Test: 16648 (16.41%)
	Test OOD: 10208 (10.06%)
	No scaling applied
		Model Seed: 17 Seed: 1 ID mean of (MSE, MAE): [241.38571    9.602433]
		Model Seed: 17 Seed: 1 OOD mean of (MSE, MAE) stats: [193.35213    8.928589]
		Model Seed: 17 Seed: 1 ID median of (MSE, MAE): [56.721275   6.5367866]
		Model Seed: 17 Seed: 1 OOD median of (MSE, MAE) stats: [55.350918  6.553972]
		Model Seed: 17 Seed: 1 ID likelihoods: -9.66213681318856
		Model Seed: 17 Seed: 1 OOD likelihoods: -9.551195397910243
		Model Seed: 17 Seed: 1 ID calibration errors: [0.38895513 0.22274701 0.14310949 0.10120487 0.07172764 0.05085167
 0.03709674 0.02964598 0.02343185 0.01879979 0.01430253 0.01139562]
		Model Seed: 17 Seed: 1 OOD calibration errors: [0.31624018 0.16617384 0.11713668 0.07987464 0.06311873 0.05121316
 0.04173068 0.03116062 0.03195706 0.0325577  0.02854471 0.02117459]
	Train: 64804 (63.70%)
	Val: 12349 (12.14%)
	Test: 16419 (16.14%)
	Test OOD: 8164 (8.02%)
	No scaling applied
		Model Seed: 17 Seed: 2 ID mean of (MSE, MAE): [253.42827    9.642158]
		Model Seed: 17 Seed: 2 OOD mean of (MSE, MAE) stats: [199.15454    9.150684]
		Model Seed: 17 Seed: 2 ID median of (MSE, MAE): [55.86022    6.4868674]
		Model Seed: 17 Seed: 2 OOD median of (MSE, MAE) stats: [53.539352  6.232766]
		Model Seed: 17 Seed: 2 ID likelihoods: -9.686479153051026
		Model Seed: 17 Seed: 2 OOD likelihoods: -9.565978859028256
		Model Seed: 17 Seed: 2 ID calibration errors: [0.38443304 0.24631034 0.16229399 0.11454537 0.08582781 0.06195019
 0.04488189 0.03556497 0.02796405 0.02165598 0.01780962 0.01372474]
		Model Seed: 17 Seed: 2 OOD calibration errors: [0.35015852 0.21239434 0.13180479 0.08279144 0.05153227 0.03475179
 0.02361497 0.01944858 0.01712683 0.01458689 0.01094224 0.00762501]
	Model Seed: 17 ID mean of (MSE, MAE): [247.40698    9.622295]
	Model Seed: 17 OOD mean of (MSE, MAE): [196.25333    9.039637]
	Model Seed: 17 ID median of (MSE, MAE): [56.29075   6.511827]
	Model Seed: 17 OOD median of (MSE, MAE): [54.445137   6.3933687]
	Model Seed: 17 ID likelihoods: -9.674307983119792
	Model Seed: 17 OOD likelihoods: -9.558587128469249
	Model Seed: 17 ID calibration errors: [0.38669409 0.23452867 0.15270174 0.10787512 0.07877772 0.05640093
 0.04098931 0.03260548 0.02569795 0.02022788 0.01605607 0.01256018]
	Model Seed: 17 OOD calibration errors: [0.33319935 0.18928409 0.12447073 0.08133304 0.0573255  0.04298248
 0.03267282 0.0253046  0.02454195 0.02357229 0.01974347 0.0143998 ]
	Train: 62090 (61.20%)
	Val: 12502 (12.32%)
	Test: 16648 (16.41%)
	Test OOD: 10208 (10.06%)
	No scaling applied
		Model Seed: 18 Seed: 1 ID mean of (MSE, MAE): [239.91925    9.578401]
		Model Seed: 18 Seed: 1 OOD mean of (MSE, MAE) stats: [196.02556    9.015201]
		Model Seed: 18 Seed: 1 ID median of (MSE, MAE): [59.7726    6.706526]
		Model Seed: 18 Seed: 1 OOD median of (MSE, MAE) stats: [57.683422  6.676707]
		Model Seed: 18 Seed: 1 ID likelihoods: -9.659089484020384
		Model Seed: 18 Seed: 1 OOD likelihoods: -9.558060825229596
		Model Seed: 18 Seed: 1 ID calibration errors: [0.38336512 0.20935103 0.13660978 0.09734578 0.06885711 0.0478439
 0.03350132 0.02806645 0.02140122 0.01814461 0.01462763 0.01246019]
		Model Seed: 18 Seed: 1 OOD calibration errors: [0.30958967 0.16258851 0.1180926  0.08353046 0.06507094 0.05587676
 0.04406113 0.03621393 0.03780884 0.03832103 0.03143069 0.02819564]
	Train: 64804 (63.70%)
	Val: 12349 (12.14%)
	Test: 16419 (16.14%)
	Test OOD: 8164 (8.02%)
	No scaling applied
		Model Seed: 18 Seed: 2 ID mean of (MSE, MAE): [253.25679    9.670785]
		Model Seed: 18 Seed: 2 OOD mean of (MSE, MAE) stats: [200.1316     9.264356]
		Model Seed: 18 Seed: 2 ID median of (MSE, MAE): [55.678703  6.378267]
		Model Seed: 18 Seed: 2 OOD median of (MSE, MAE) stats: [57.0074    6.539262]
		Model Seed: 18 Seed: 2 ID likelihoods: -9.686140239506775
		Model Seed: 18 Seed: 2 OOD likelihoods: -9.568426087790822
		Model Seed: 18 Seed: 2 ID calibration errors: [0.3506261  0.24867647 0.15281725 0.11133502 0.07647133 0.05677011
 0.04020911 0.03324438 0.02566888 0.02109057 0.01802857 0.0138899 ]
		Model Seed: 18 Seed: 2 OOD calibration errors: [0.31817368 0.21046124 0.12381266 0.0800302  0.04817327 0.030478
 0.0220635  0.01806134 0.01625822 0.01312649 0.0095493  0.00710353]
	Model Seed: 18 ID mean of (MSE, MAE): [246.58801    9.624593]
	Model Seed: 18 OOD mean of (MSE, MAE): [198.07858    9.139778]
	Model Seed: 18 ID median of (MSE, MAE): [57.72565    6.5423965]
	Model Seed: 18 OOD median of (MSE, MAE): [57.345413   6.6079845]
	Model Seed: 18 ID likelihoods: -9.67261486176358
	Model Seed: 18 OOD likelihoods: -9.56324345651021
	Model Seed: 18 ID calibration errors: [0.36699561 0.22901375 0.14471352 0.1043404  0.07266422 0.05230701
 0.03685522 0.03065541 0.02353505 0.01961759 0.0163281  0.01317504]
	Model Seed: 18 OOD calibration errors: [0.31388167 0.18652487 0.12095263 0.08178033 0.0566221  0.04317738
 0.03306231 0.02713764 0.02703353 0.02572376 0.02048999 0.01764959]
	Train: 62090 (61.20%)
	Val: 12502 (12.32%)
	Test: 16648 (16.41%)
	Test OOD: 10208 (10.06%)
	No scaling applied
		Model Seed: 19 Seed: 1 ID mean of (MSE, MAE): [242.01414    9.660004]
		Model Seed: 19 Seed: 1 OOD mean of (MSE, MAE) stats: [194.67043    9.008461]
		Model Seed: 19 Seed: 1 ID median of (MSE, MAE): [58.16024    6.6015086]
		Model Seed: 19 Seed: 1 OOD median of (MSE, MAE) stats: [58.15381   6.667061]
		Model Seed: 19 Seed: 1 ID likelihoods: -9.663436651948283
		Model Seed: 19 Seed: 1 OOD likelihoods: -9.554592612893646
		Model Seed: 19 Seed: 1 ID calibration errors: [0.36615228 0.21546718 0.13936487 0.09774766 0.0702535  0.04969418
 0.03488969 0.02880705 0.02206399 0.01745985 0.01484507 0.01184715]
		Model Seed: 19 Seed: 1 OOD calibration errors: [0.29720864 0.15870636 0.1127148  0.08296385 0.06409625 0.05688723
 0.04549872 0.03937336 0.0387973  0.03905738 0.03281859 0.02827112]
	Train: 64804 (63.70%)
	Val: 12349 (12.14%)
	Test: 16419 (16.14%)
	Test OOD: 8164 (8.02%)
	No scaling applied
		Model Seed: 19 Seed: 2 ID mean of (MSE, MAE): [253.20322    9.630483]
		Model Seed: 19 Seed: 2 OOD mean of (MSE, MAE) stats: [199.11375    9.164599]
		Model Seed: 19 Seed: 2 ID median of (MSE, MAE): [55.207657  6.382409]
		Model Seed: 19 Seed: 2 OOD median of (MSE, MAE) stats: [52.575638   6.3467264]
		Model Seed: 19 Seed: 2 ID likelihoods: -9.686035061548205
		Model Seed: 19 Seed: 2 OOD likelihoods: -9.565876793613166
		Model Seed: 19 Seed: 2 ID calibration errors: [0.38145945 0.24083007 0.15988361 0.1142807  0.07953645 0.0549592
 0.0404959  0.0311834  0.0256193  0.0195536  0.01680896 0.01284509]
		Model Seed: 19 Seed: 2 OOD calibration errors: [0.35726231 0.21522693 0.13527353 0.08192231 0.04885949 0.03096679
 0.02204638 0.01838357 0.0148165  0.01223842 0.01003108 0.00724519]
	Model Seed: 19 ID mean of (MSE, MAE): [247.60867    9.645243]
	Model Seed: 19 OOD mean of (MSE, MAE): [196.89209    9.086531]
	Model Seed: 19 ID median of (MSE, MAE): [56.68395    6.4919586]
	Model Seed: 19 OOD median of (MSE, MAE): [55.364723   6.5068936]
	Model Seed: 19 ID likelihoods: -9.674735856748244
	Model Seed: 19 OOD likelihoods: -9.560234703253407
	Model Seed: 19 ID calibration errors: [0.37380587 0.22814862 0.14962424 0.10601418 0.07489498 0.05232669
 0.03769279 0.02999522 0.02384165 0.01850672 0.01582701 0.01234612]
	Model Seed: 19 OOD calibration errors: [0.32723548 0.18696665 0.12399416 0.08244308 0.05647787 0.04392701
 0.03377255 0.02887846 0.0268069  0.0256479  0.02142483 0.01775816]
ID mean of (MSE, MAE): [247.85659790039062, 9.647603034973145] +- [5.337027549743652, 0.1219317689538002] +- [5.830251   0.01807433] 
OOD mean of (MSE, MAE): [197.81777954101562, 9.103170394897461] +- [2.2404541969299316, 0.04074132442474365] +- [2.2733495  0.11747272] 
ID median of (MSE, MAE): [57.44883346557617, 6.551548004150391] +- [1.5082266330718994, 0.09058324247598648] +- [1.49964675 0.13030176] 
OOD median of (MSE, MAE): [56.14946746826172, 6.51580286026001] +- [1.3406950235366821, 0.10842245072126389] +- [0.9813919  0.12387782] 
ID likelihoods: -9.675094815088977 +- 0.010625158174656162 +- 0.011823987403865033 
OOD likelihoods: -9.562533114025523 +- 0.0055710161405287395 +- 0.005725564348167289 
ID calibration errors: [0.3684278704940938, 0.23156150307506285, 0.14688092063558547, 0.10711234573709769, 0.07477456373726085, 0.054081712902356374, 0.03828258392679822, 0.03131014027544561, 0.02433348281705821, 0.019853979425524134, 0.016136072655767254, 0.012908086987844852] +- [0.02113451145403105, 0.00791372818526059, 0.006911111682766884, 0.002480005078034748, 0.00320216527983214, 0.0014707411696394301, 0.0014310753935781147, 0.0011361985705310167, 0.0009844890412729324, 0.0007162837599436467, 0.0004919190272127554, 0.000466717393359904] +- [0.00225992 0.01397891 0.00891152 0.00668453 0.00505145 0.00427414
 0.00293896 0.00192711 0.00193974 0.00096616 0.00099438 0.00048736] 
OOD calibration errors: [0.3181686749387946, 0.19021808509076654, 0.12260359573653372, 0.08276001040943022, 0.056504641109137346, 0.043585019580967235, 0.03258374020393863, 0.027881124986471467, 0.026389644549544854, 0.025459546093729947, 0.020790457673752576, 0.016976742124375267] +- [0.016827781143802383, 0.00964074523501629, 0.004478631421926733, 0.004138183479363628, 0.0017188039241368496, 0.0017489152971970736, 0.0013460572579705387, 0.0015926127930689662, 0.0017980828993794731, 0.0018624654354282572, 0.0013623278999997997, 0.0019329181511360677] +- [0.01781809 0.02156594 0.00608435 0.00175558 0.00767514 0.0115218
 0.01079413 0.00926917 0.01040841 0.01202619 0.01023271 0.00948226] 
