Optimization started at 2023-03-09 12:24:52.629795--------------------------------
Loading column definition...
Checking column definition...
Loading data...
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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)
		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: 57159 (68.64%)
	Val: 16704 (20.06%)
	Test: 19521 (23.44%)
Scaling data...
	No scaling applied
Data formatting complete.
--------------------------------
Current value: 0.07060396671295166, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'kernel_sizes': 2, 'dropout': 0.04371649564385423, 'lr': 0.0007328838503064512, 'batch_size': 48, 'lr_epochs': 2}
Best value: 0.07060396671295166, Best params: {'in_len': 132, 'max_samples_per_ts': 100, 'kernel_sizes': 2, 'dropout': 0.04371649564385423, 'lr': 0.0007328838503064512, 'batch_size': 48, 'lr_epochs': 2}
Current value: 0.07079513370990753, Current params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 3, 'dropout': 0.19210100509853764, 'lr': 0.00017332232961707398, 'batch_size': 32, 'lr_epochs': 4}
Best value: 0.07060396671295166, Best params: {'in_len': 132, 'max_samples_per_ts': 100, 'kernel_sizes': 2, 'dropout': 0.04371649564385423, 'lr': 0.0007328838503064512, 'batch_size': 48, 'lr_epochs': 2}
Current value: 0.04884055629372597, Current params: {'in_len': 144, 'max_samples_per_ts': 100, 'kernel_sizes': 5, 'dropout': 0.1411271024658593, 'lr': 0.00030511787810710416, 'batch_size': 48, 'lr_epochs': 10}
Best value: 0.04884055629372597, Best params: {'in_len': 144, 'max_samples_per_ts': 100, 'kernel_sizes': 5, 'dropout': 0.1411271024658593, 'lr': 0.00030511787810710416, 'batch_size': 48, 'lr_epochs': 10}
Current value: 0.07261332869529724, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'kernel_sizes': 3, 'dropout': 0.029501140380196824, 'lr': 0.00098800036640461, 'batch_size': 32, 'lr_epochs': 6}
Best value: 0.04884055629372597, Best params: {'in_len': 144, 'max_samples_per_ts': 100, 'kernel_sizes': 5, 'dropout': 0.1411271024658593, 'lr': 0.00030511787810710416, 'batch_size': 48, 'lr_epochs': 10}
Current value: 0.07275306433439255, Current params: {'in_len': 120, 'max_samples_per_ts': 100, 'kernel_sizes': 2, 'dropout': 0.03717554919270347, 'lr': 0.0009541090227778986, 'batch_size': 64, 'lr_epochs': 2}
Best value: 0.04884055629372597, Best params: {'in_len': 144, 'max_samples_per_ts': 100, 'kernel_sizes': 5, 'dropout': 0.1411271024658593, 'lr': 0.00030511787810710416, 'batch_size': 48, 'lr_epochs': 10}
Current value: 0.04680798575282097, Current params: {'in_len': 108, 'max_samples_per_ts': 100, 'kernel_sizes': 4, 'dropout': 0.011163868408077616, 'lr': 0.0003858735480461263, 'batch_size': 48, 'lr_epochs': 2}
Best value: 0.04680798575282097, Best params: {'in_len': 108, 'max_samples_per_ts': 100, 'kernel_sizes': 4, 'dropout': 0.011163868408077616, 'lr': 0.0003858735480461263, 'batch_size': 48, 'lr_epochs': 2}
Current value: 0.04994136840105057, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 4, 'dropout': 0.06424061413589226, 'lr': 0.000615597797544268, 'batch_size': 32, 'lr_epochs': 10}
Best value: 0.04680798575282097, Best params: {'in_len': 108, 'max_samples_per_ts': 100, 'kernel_sizes': 4, 'dropout': 0.011163868408077616, 'lr': 0.0003858735480461263, 'batch_size': 48, 'lr_epochs': 2}
Current value: 0.05395612493157387, Current params: {'in_len': 132, 'max_samples_per_ts': 200, 'kernel_sizes': 4, 'dropout': 0.015131979453811662, 'lr': 0.0008583807509520055, 'batch_size': 32, 'lr_epochs': 8}
Best value: 0.04680798575282097, Best params: {'in_len': 108, 'max_samples_per_ts': 100, 'kernel_sizes': 4, 'dropout': 0.011163868408077616, 'lr': 0.0003858735480461263, 'batch_size': 48, 'lr_epochs': 2}
Current value: 0.0470786988735199, Current params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 4, 'dropout': 0.10136443263809819, 'lr': 0.0008514870636514033, 'batch_size': 48, 'lr_epochs': 10}
Best value: 0.04680798575282097, Best params: {'in_len': 108, 'max_samples_per_ts': 100, 'kernel_sizes': 4, 'dropout': 0.011163868408077616, 'lr': 0.0003858735480461263, 'batch_size': 48, 'lr_epochs': 2}
Current value: 0.008294825442135334, Current params: {'in_len': 132, 'max_samples_per_ts': 150, 'kernel_sizes': 1, 'dropout': 0.0705939189625654, 'lr': 0.0006202425363682003, 'batch_size': 48, 'lr_epochs': 14}
Best value: 0.04680798575282097, Best params: {'in_len': 108, 'max_samples_per_ts': 100, 'kernel_sizes': 4, 'dropout': 0.011163868408077616, 'lr': 0.0003858735480461263, 'batch_size': 48, 'lr_epochs': 2}
Current value: 0.04908644035458565, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.10904636407433106, 'lr': 0.00038626207578874454, 'batch_size': 64, 'lr_epochs': 18}
Best value: 0.04680798575282097, Best params: {'in_len': 108, 'max_samples_per_ts': 100, 'kernel_sizes': 4, 'dropout': 0.011163868408077616, 'lr': 0.0003858735480461263, 'batch_size': 48, 'lr_epochs': 2}
Current value: 0.004965878091752529, Current params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 4, 'dropout': 0.11488384443901603, 'lr': 0.0004365095104243861, 'batch_size': 48, 'lr_epochs': 14}
Best value: 0.04680798575282097, Best params: {'in_len': 108, 'max_samples_per_ts': 100, 'kernel_sizes': 4, 'dropout': 0.011163868408077616, 'lr': 0.0003858735480461263, 'batch_size': 48, 'lr_epochs': 2}
Current value: 0.046844493597745895, Current params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 4, 'dropout': 0.15043253994972594, 'lr': 0.0005109594833757501, 'batch_size': 64, 'lr_epochs': 18}
Best value: 0.04680798575282097, Best params: {'in_len': 108, 'max_samples_per_ts': 100, 'kernel_sizes': 4, 'dropout': 0.011163868408077616, 'lr': 0.0003858735480461263, 'batch_size': 48, 'lr_epochs': 2}
Current value: 0.004044560249894857, Current params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 5, 'dropout': 0.16013991339705522, 'lr': 0.0004836680753528526, 'batch_size': 64, 'lr_epochs': 18}
Best value: 0.04680798575282097, Best params: {'in_len': 108, 'max_samples_per_ts': 100, 'kernel_sizes': 4, 'dropout': 0.011163868408077616, 'lr': 0.0003858735480461263, 'batch_size': 48, 'lr_epochs': 2}
Current value: 0.008859827183187008, Current params: {'in_len': 108, 'max_samples_per_ts': 200, 'kernel_sizes': 3, 'dropout': 0.15030948854032222, 'lr': 0.0002548026558233189, 'batch_size': 64, 'lr_epochs': 20}
Best value: 0.04680798575282097, Best params: {'in_len': 108, 'max_samples_per_ts': 100, 'kernel_sizes': 4, 'dropout': 0.011163868408077616, 'lr': 0.0003858735480461263, 'batch_size': 48, 'lr_epochs': 2}
Current value: 0.05498739704489708, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 4, 'dropout': 0.0053197425384890265, 'lr': 0.00012281377592471965, 'batch_size': 64, 'lr_epochs': 14}
Best value: 0.04680798575282097, Best params: {'in_len': 108, 'max_samples_per_ts': 100, 'kernel_sizes': 4, 'dropout': 0.011163868408077616, 'lr': 0.0003858735480461263, 'batch_size': 48, 'lr_epochs': 2}
Current value: 0.008174828253686428, Current params: {'in_len': 120, 'max_samples_per_ts': 100, 'kernel_sizes': 2, 'dropout': 0.19919778953059686, 'lr': 0.00033328774671928204, 'batch_size': 48, 'lr_epochs': 16}
Best value: 0.04680798575282097, Best params: {'in_len': 108, 'max_samples_per_ts': 100, 'kernel_sizes': 4, 'dropout': 0.011163868408077616, 'lr': 0.0003858735480461263, 'batch_size': 48, 'lr_epochs': 2}
Current value: 0.004089931026101112, Current params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 5, 'dropout': 0.17487497611995834, 'lr': 0.0005281261072547966, 'batch_size': 64, 'lr_epochs': 6}
Best value: 0.04680798575282097, Best params: {'in_len': 108, 'max_samples_per_ts': 100, 'kernel_sizes': 4, 'dropout': 0.011163868408077616, 'lr': 0.0003858735480461263, 'batch_size': 48, 'lr_epochs': 2}
Current value: 0.004072448238730431, Current params: {'in_len': 96, 'max_samples_per_ts': 100, 'kernel_sizes': 4, 'dropout': 0.0749473152965059, 'lr': 0.0006828637827311347, 'batch_size': 48, 'lr_epochs': 20}
Best value: 0.04680798575282097, Best params: {'in_len': 108, 'max_samples_per_ts': 100, 'kernel_sizes': 4, 'dropout': 0.011163868408077616, 'lr': 0.0003858735480461263, 'batch_size': 48, 'lr_epochs': 2}
Current value: 0.008239886723458767, Current params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.12887213281946489, 'lr': 0.00023778364772884342, 'batch_size': 64, 'lr_epochs': 12}
Best value: 0.04680798575282097, Best params: {'in_len': 108, 'max_samples_per_ts': 100, 'kernel_sizes': 4, 'dropout': 0.011163868408077616, 'lr': 0.0003858735480461263, 'batch_size': 48, 'lr_epochs': 2}
Current value: 0.007531848270446062, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'kernel_sizes': 3, 'dropout': 0.07955163192446758, 'lr': 0.00042912332404490875, 'batch_size': 48, 'lr_epochs': 6}
Best value: 0.04680798575282097, Best params: {'in_len': 108, 'max_samples_per_ts': 100, 'kernel_sizes': 4, 'dropout': 0.011163868408077616, 'lr': 0.0003858735480461263, 'batch_size': 48, 'lr_epochs': 2}
Current value: 0.0490940622985363, Current params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 4, 'dropout': 0.09941392959938658, 'lr': 0.0007758103293126232, 'batch_size': 48, 'lr_epochs': 12}
Best value: 0.04680798575282097, Best params: {'in_len': 108, 'max_samples_per_ts': 100, 'kernel_sizes': 4, 'dropout': 0.011163868408077616, 'lr': 0.0003858735480461263, 'batch_size': 48, 'lr_epochs': 2}
Current value: 0.004284900147467852, Current params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 4, 'dropout': 0.09319324104960212, 'lr': 0.0006025956987810051, 'batch_size': 48, 'lr_epochs': 8}
Best value: 0.04680798575282097, Best params: {'in_len': 108, 'max_samples_per_ts': 100, 'kernel_sizes': 4, 'dropout': 0.011163868408077616, 'lr': 0.0003858735480461263, 'batch_size': 48, 'lr_epochs': 2}
Current value: 0.04683038592338562, Current params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1267631747032051, 'lr': 0.0008572917415161675, 'batch_size': 48, 'lr_epochs': 16}
Best value: 0.04680798575282097, Best params: {'in_len': 108, 'max_samples_per_ts': 100, 'kernel_sizes': 4, 'dropout': 0.011163868408077616, 'lr': 0.0003858735480461263, 'batch_size': 48, 'lr_epochs': 2}
Current value: 0.0042753666639328, Current params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.13429922981717463, 'lr': 0.0005065201942108529, 'batch_size': 32, 'lr_epochs': 16}
Best value: 0.04680798575282097, Best params: {'in_len': 108, 'max_samples_per_ts': 100, 'kernel_sizes': 4, 'dropout': 0.011163868408077616, 'lr': 0.0003858735480461263, 'batch_size': 48, 'lr_epochs': 2}
Current value: 0.04662421718239784, Current params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1703313780264349, 'lr': 0.0003614984209125642, 'batch_size': 48, 'lr_epochs': 18}
Best value: 0.04662421718239784, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1703313780264349, 'lr': 0.0003614984209125642, 'batch_size': 48, 'lr_epochs': 18}
Current value: 0.045971158891916275, Current params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.047178003937006, Current params: {'in_len': 144, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.17056365639650015, 'lr': 0.00035909133269462464, 'batch_size': 48, 'lr_epochs': 20}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.04814258590340614, Current params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1805434556560649, 'lr': 0.0002591932939522733, 'batch_size': 48, 'lr_epochs': 18}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.003869217587634921, Current params: {'in_len': 132, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.18867745106035794, 'lr': 0.00042023781513024993, 'batch_size': 32, 'lr_epochs': 2}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.00475667230784893, Current params: {'in_len': 120, 'max_samples_per_ts': 100, 'kernel_sizes': 5, 'dropout': 0.054149047140819896, 'lr': 0.00018055359393481376, 'batch_size': 48, 'lr_epochs': 16}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.0038039074279367924, Current params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.16631510053777981, 'lr': 0.0003305103752414498, 'batch_size': 48, 'lr_epochs': 16}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.046069853007793427, Current params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1187428136142987, 'lr': 0.0004580274600920358, 'batch_size': 48, 'lr_epochs': 14}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.0037759991828352213, Current params: {'in_len': 132, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.15385364640931803, 'lr': 0.0002853969371291431, 'batch_size': 48, 'lr_epochs': 14}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.004166130907833576, Current params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.187484824807629, 'lr': 0.0003806473525213217, 'batch_size': 48, 'lr_epochs': 4}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.004159382078796625, Current params: {'in_len': 144, 'max_samples_per_ts': 200, 'kernel_sizes': 4, 'dropout': 0.14150453611539368, 'lr': 0.0001798130205035029, 'batch_size': 48, 'lr_epochs': 12}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.00428673205897212, Current params: {'in_len': 120, 'max_samples_per_ts': 100, 'kernel_sizes': 5, 'dropout': 0.05098283022022154, 'lr': 0.00046169287461154403, 'batch_size': 32, 'lr_epochs': 14}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.0070830038748681545, Current params: {'in_len': 132, 'max_samples_per_ts': 200, 'kernel_sizes': 1, 'dropout': 0.033155424036706946, 'lr': 0.000306798158977769, 'batch_size': 32, 'lr_epochs': 4}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.004610080271959305, Current params: {'in_len': 120, 'max_samples_per_ts': 100, 'kernel_sizes': 4, 'dropout': 0.08848121564386285, 'lr': 0.0005753730886084328, 'batch_size': 48, 'lr_epochs': 8}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.007687477860599756, Current params: {'in_len': 132, 'max_samples_per_ts': 200, 'kernel_sizes': 3, 'dropout': 0.12277360550991435, 'lr': 0.00020855191522688025, 'batch_size': 48, 'lr_epochs': 18}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.00527838384732604, Current params: {'in_len': 120, 'max_samples_per_ts': 150, 'kernel_sizes': 5, 'dropout': 0.19966983782045633, 'lr': 0.0001207067353917441, 'batch_size': 48, 'lr_epochs': 12}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.004259992856532335, Current params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.12082705873407996, 'lr': 0.0009086698791946335, 'batch_size': 48, 'lr_epochs': 16}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.003996530547738075, Current params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.14021593056170623, 'lr': 0.00073663559448324, 'batch_size': 48, 'lr_epochs': 16}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.004101887345314026, Current params: {'in_len': 132, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.11248285812863512, 'lr': 0.0003968916541732567, 'batch_size': 48, 'lr_epochs': 14}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.05210541561245918, Current params: {'in_len': 108, 'max_samples_per_ts': 200, 'kernel_sizes': 4, 'dropout': 0.020288413205902793, 'lr': 0.000667248268198139, 'batch_size': 48, 'lr_epochs': 18}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.046025894582271576, Current params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.16155001791946655, 'lr': 0.00046234316210414964, 'batch_size': 48, 'lr_epochs': 10}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.003752143820747733, Current params: {'in_len': 132, 'max_samples_per_ts': 150, 'kernel_sizes': 4, 'dropout': 0.16267031997909465, 'lr': 0.00045615812245733336, 'batch_size': 48, 'lr_epochs': 10}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.007641675416380167, Current params: {'in_len': 108, 'max_samples_per_ts': 200, 'kernel_sizes': 2, 'dropout': 0.18074340371187356, 'lr': 0.0005402441622794165, 'batch_size': 48, 'lr_epochs': 10}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.0470588393509388, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.15455542023063476, 'lr': 0.0003499095380044337, 'batch_size': 48, 'lr_epochs': 2}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.004385995678603649, Current params: {'in_len': 96, 'max_samples_per_ts': 100, 'kernel_sizes': 4, 'dropout': 0.1755581069569047, 'lr': 0.00048536600408427766, 'batch_size': 32, 'lr_epochs': 8}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.004236649256199598, Current params: {'in_len': 108, 'max_samples_per_ts': 200, 'kernel_sizes': 4, 'dropout': 0.1460857765899191, 'lr': 0.0004032744524640221, 'batch_size': 48, 'lr_epochs': 20}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.004249748308211565, Current params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.12761282224569295, 'lr': 0.0002909508187906474, 'batch_size': 48, 'lr_epochs': 16}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.0041079455986619, Current params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.10594646823072151, 'lr': 0.00036906205716754324, 'batch_size': 48, 'lr_epochs': 18}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.004148371983319521, Current params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.16206066021455073, 'lr': 0.0009846921251148795, 'batch_size': 48, 'lr_epochs': 14}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.004383529536426067, Current params: {'in_len': 120, 'max_samples_per_ts': 150, 'kernel_sizes': 5, 'dropout': 0.13461062906010812, 'lr': 0.0004550293929202509, 'batch_size': 48, 'lr_epochs': 16}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.00495087681338191, Current params: {'in_len': 108, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.08664026281109657, 'lr': 0.0005719830418256001, 'batch_size': 64, 'lr_epochs': 6}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.0036680034827440977, Current params: {'in_len': 132, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.18295743552896668, 'lr': 0.0003214965921048105, 'batch_size': 48, 'lr_epochs': 18}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.004418857395648956, Current params: {'in_len': 120, 'max_samples_per_ts': 150, 'kernel_sizes': 4, 'dropout': 0.19228100564744088, 'lr': 0.0007776130699082881, 'batch_size': 48, 'lr_epochs': 12}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.0036590511444956064, Current params: {'in_len': 108, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.0042094843003175515, 'lr': 0.000497635956809348, 'batch_size': 48, 'lr_epochs': 18}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.0075425272807478905, Current params: {'in_len': 120, 'max_samples_per_ts': 100, 'kernel_sizes': 3, 'dropout': 0.11837597194819742, 'lr': 0.0008479831301613494, 'batch_size': 48, 'lr_epochs': 14}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.0043870024383068085, Current params: {'in_len': 120, 'max_samples_per_ts': 150, 'kernel_sizes': 4, 'dropout': 0.16946844160538876, 'lr': 0.000642016222466021, 'batch_size': 64, 'lr_epochs': 20}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.00787353329360485, Current params: {'in_len': 108, 'max_samples_per_ts': 200, 'kernel_sizes': 3, 'dropout': 0.14882143355671412, 'lr': 0.0005168563872169367, 'batch_size': 64, 'lr_epochs': 18}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.004432391375303268, Current params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 5, 'dropout': 0.15593536769947994, 'lr': 0.0004258453792772089, 'batch_size': 64, 'lr_epochs': 16}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.00433826120570302, Current params: {'in_len': 96, 'max_samples_per_ts': 200, 'kernel_sizes': 4, 'dropout': 0.17395695578738246, 'lr': 0.0005513646988296032, 'batch_size': 48, 'lr_epochs': 20}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.004525025840848684, Current params: {'in_len': 108, 'max_samples_per_ts': 100, 'kernel_sizes': 5, 'dropout': 0.13621266716118574, 'lr': 0.00047034005257703244, 'batch_size': 48, 'lr_epochs': 16}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.04951231926679611, Current params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.14399345753891002, 'lr': 0.0002602051321197705, 'batch_size': 48, 'lr_epochs': 14}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.0037862155586481094, Current params: {'in_len': 108, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.12842021050920574, 'lr': 0.0003501789143874244, 'batch_size': 48, 'lr_epochs': 18}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.007326133549213409, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'kernel_sizes': 3, 'dropout': 0.1573386710068987, 'lr': 0.00041709173155079094, 'batch_size': 48, 'lr_epochs': 18}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.004421174991875887, Current params: {'in_len': 96, 'max_samples_per_ts': 150, 'kernel_sizes': 4, 'dropout': 0.1665307375430297, 'lr': 0.00038585730752622993, 'batch_size': 64, 'lr_epochs': 16}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.004871687386184931, Current params: {'in_len': 108, 'max_samples_per_ts': 100, 'kernel_sizes': 4, 'dropout': 0.10196589561283946, 'lr': 0.0006026537255576589, 'batch_size': 48, 'lr_epochs': 6}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.007581584621220827, Current params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 2, 'dropout': 0.1500305093830665, 'lr': 0.00044694046974670486, 'batch_size': 48, 'lr_epochs': 20}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.050436656922101974, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.06598796492972553, 'lr': 0.0003631309789717371, 'batch_size': 48, 'lr_epochs': 2}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.04704255238175392, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.15916004508928872, 'lr': 0.00033723273285166144, 'batch_size': 48, 'lr_epochs': 2}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.046952374279499054, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.17701074517342377, 'lr': 0.0002315603460000194, 'batch_size': 48, 'lr_epochs': 2}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.04740756005048752, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.19362900254477405, 'lr': 0.00028942159342694283, 'batch_size': 48, 'lr_epochs': 4}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.004639897029846907, Current params: {'in_len': 132, 'max_samples_per_ts': 150, 'kernel_sizes': 5, 'dropout': 0.18453090853721887, 'lr': 0.0004998399705224863, 'batch_size': 48, 'lr_epochs': 4}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.004004431422799826, Current params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.17793520341160401, 'lr': 0.0005630896566326874, 'batch_size': 48, 'lr_epochs': 2}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.004794026724994183, Current params: {'in_len': 144, 'max_samples_per_ts': 100, 'kernel_sizes': 5, 'dropout': 0.17269745267075748, 'lr': 0.0002295833933517076, 'batch_size': 48, 'lr_epochs': 4}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.004198837094008923, Current params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.023301549185957886, 'lr': 0.00020249463224769246, 'batch_size': 48, 'lr_epochs': 14}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.0075785452499985695, Current params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 1, 'dropout': 0.1653934377291835, 'lr': 0.00027066800162868325, 'batch_size': 48, 'lr_epochs': 16}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.003966636955738068, Current params: {'in_len': 108, 'max_samples_per_ts': 200, 'kernel_sizes': 4, 'dropout': 0.11397103054386384, 'lr': 0.0004064004807818706, 'batch_size': 48, 'lr_epochs': 12}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.003748260671272874, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.1595629448499438, 'lr': 0.000328846363530757, 'batch_size': 48, 'lr_epochs': 2}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.046686287969350815, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.1700257084647615, 'lr': 0.00014606922693464954, 'batch_size': 48, 'lr_epochs': 2}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.04740945249795914, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.188400627584086, 'lr': 0.0001537458519518045, 'batch_size': 48, 'lr_epochs': 2}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.04849981889128685, Current params: {'in_len': 132, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.16821040616342545, 'lr': 0.00010741529484817406, 'batch_size': 48, 'lr_epochs': 4}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.05181160569190979, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.044498840660041, 'lr': 0.00022124844804560884, 'batch_size': 48, 'lr_epochs': 2}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.048844218254089355, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.1772120161223895, 'lr': 0.00015629462247057326, 'batch_size': 48, 'lr_epochs': 8}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.004864899907261133, Current params: {'in_len': 120, 'max_samples_per_ts': 100, 'kernel_sizes': 5, 'dropout': 0.15163767711061024, 'lr': 0.0003083063948504916, 'batch_size': 48, 'lr_epochs': 10}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.00416342169046402, Current params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.13989449752494612, 'lr': 0.0001423584795316218, 'batch_size': 32, 'lr_epochs': 6}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.05207165330648422, Current params: {'in_len': 108, 'max_samples_per_ts': 200, 'kernel_sizes': 4, 'dropout': 0.009770127817501358, 'lr': 0.00043679384708890124, 'batch_size': 48, 'lr_epochs': 18}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.04685831069946289, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.1949403085604703, 'lr': 0.0005314370134917619, 'batch_size': 48, 'lr_epochs': 4}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.046191904693841934, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.19911426896497925, 'lr': 0.0005177312748574583, 'batch_size': 48, 'lr_epochs': 2}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.04656841605901718, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.1964188287388707, 'lr': 0.000533228853192627, 'batch_size': 48, 'lr_epochs': 4}
Best value: 0.045971158891916275, Best params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.1813978243143695, 'lr': 0.0003256805707671397, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.04536088928580284, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.18679300209273494, 'lr': 0.0004763622305085654, 'batch_size': 48, 'lr_epochs': 4}
Best value: 0.04536088928580284, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.18679300209273494, 'lr': 0.0004763622305085654, 'batch_size': 48, 'lr_epochs': 4}
Current value: 0.04637635871767998, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.19683906934818982, 'lr': 0.0004773481492509485, 'batch_size': 48, 'lr_epochs': 4}
Best value: 0.04536088928580284, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.18679300209273494, 'lr': 0.0004763622305085654, 'batch_size': 48, 'lr_epochs': 4}
Current value: 0.04613994061946869, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.19660022391519, 'lr': 0.00047755220363729383, 'batch_size': 48, 'lr_epochs': 4}
Best value: 0.04536088928580284, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.18679300209273494, 'lr': 0.0004763622305085654, 'batch_size': 48, 'lr_epochs': 4}
Current value: 0.04593032971024513, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.19747532389664052, 'lr': 0.000486369399876011, 'batch_size': 48, 'lr_epochs': 4}
Best value: 0.04536088928580284, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.18679300209273494, 'lr': 0.0004763622305085654, 'batch_size': 48, 'lr_epochs': 4}
Current value: 0.04673643037676811, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.19806528053719744, 'lr': 0.00052272485691244, 'batch_size': 48, 'lr_epochs': 6}
Best value: 0.04536088928580284, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.18679300209273494, 'lr': 0.0004763622305085654, 'batch_size': 48, 'lr_epochs': 4}
Current value: 0.045821696519851685, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.18624009950209233, 'lr': 0.0004911462680217272, 'batch_size': 48, 'lr_epochs': 4}
Best value: 0.04536088928580284, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.18679300209273494, 'lr': 0.0004763622305085654, 'batch_size': 48, 'lr_epochs': 4}
Current value: 0.0469784140586853, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.18890245614209128, 'lr': 0.00046944589420752755, 'batch_size': 48, 'lr_epochs': 4}
Best value: 0.04536088928580284, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.18679300209273494, 'lr': 0.0004763622305085654, 'batch_size': 48, 'lr_epochs': 4}
--------------------------------
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): [217.44373    9.747708]
		Model Seed: 10 Seed: 1 OOD mean of (MSE, MAE) stats: [208.3212   10.10107]
		Model Seed: 10 Seed: 1 ID median of (MSE, MAE): [68.5973     7.2117205]
		Model Seed: 10 Seed: 1 OOD median of (MSE, MAE) stats: [79.2137     7.9492946]
		Model Seed: 10 Seed: 1 ID likelihoods: -9.609908961215508
		Model Seed: 10 Seed: 1 OOD likelihoods: -9.588479746131554
		Model Seed: 10 Seed: 1 ID calibration errors: [0.25962102 0.16297152 0.10206756 0.06572873 0.0440523  0.02976214
 0.02192674 0.01603228 0.01325976 0.01126206 0.01034744 0.00964779]
		Model Seed: 10 Seed: 1 OOD calibration errors: [0.23693779 0.15511806 0.10183126 0.07193464 0.05612434 0.04322979
 0.03765537 0.03587659 0.03772837 0.03888929 0.04256204 0.04464174]
	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): [229.40396    9.787046]
		Model Seed: 10 Seed: 2 OOD mean of (MSE, MAE) stats: [199.46985    9.609941]
		Model Seed: 10 Seed: 2 ID median of (MSE, MAE): [65.76928    7.0417733]
		Model Seed: 10 Seed: 2 OOD median of (MSE, MAE) stats: [69.76365    7.3333893]
		Model Seed: 10 Seed: 2 ID likelihoods: -9.636680104115356
		Model Seed: 10 Seed: 2 OOD likelihoods: -9.56676988708049
		Model Seed: 10 Seed: 2 ID calibration errors: [0.29178383 0.19249506 0.12205435 0.07665402 0.05060785 0.032889
 0.02247014 0.01574265 0.01195974 0.00928137 0.00762933 0.00699427]
		Model Seed: 10 Seed: 2 OOD calibration errors: [0.28804472 0.16911994 0.09902035 0.06158087 0.04301277 0.03357793
 0.02648296 0.02414278 0.02108872 0.01851345 0.02005445 0.01805043]
	Model Seed: 10 ID mean of (MSE, MAE): [223.42384    9.767378]
	Model Seed: 10 OOD mean of (MSE, MAE): [203.89552    9.855505]
	Model Seed: 10 ID median of (MSE, MAE): [67.18329   7.126747]
	Model Seed: 10 OOD median of (MSE, MAE): [74.48868   7.641342]
	Model Seed: 10 ID likelihoods: -9.623294532665433
	Model Seed: 10 OOD likelihoods: -9.577624816606022
	Model Seed: 10 ID calibration errors: [0.27570242 0.17773329 0.11206095 0.07119137 0.04733007 0.03132557
 0.02219844 0.01588747 0.01260975 0.01027171 0.00898839 0.00832103]
	Model Seed: 10 OOD calibration errors: [0.26249125 0.162119   0.1004258  0.06675775 0.04956856 0.03840386
 0.03206916 0.03000968 0.02940854 0.02870137 0.03130825 0.03134608]
	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): [215.91013    9.581701]
		Model Seed: 11 Seed: 1 OOD mean of (MSE, MAE) stats: [201.93689    9.908084]
		Model Seed: 11 Seed: 1 ID median of (MSE, MAE): [65.53765   7.007328]
		Model Seed: 11 Seed: 1 OOD median of (MSE, MAE) stats: [78.08805    7.7354827]
		Model Seed: 11 Seed: 1 ID likelihoods: -9.606369333443228
		Model Seed: 11 Seed: 1 OOD likelihoods: -9.572917050501154
		Model Seed: 11 Seed: 1 ID calibration errors: [0.26054498 0.16861356 0.10578412 0.067187   0.04499753 0.03084624
 0.02148135 0.01626653 0.01224795 0.01048359 0.00880832 0.00795658]
		Model Seed: 11 Seed: 1 OOD calibration errors: [0.21422255 0.13421818 0.08610917 0.06098592 0.04503979 0.04027603
 0.03486098 0.0373689  0.04074678 0.04830435 0.04536562 0.04966074]
	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): [225.27911    9.668426]
		Model Seed: 11 Seed: 2 OOD mean of (MSE, MAE) stats: [201.05855   9.58944]
		Model Seed: 11 Seed: 2 ID median of (MSE, MAE): [64.00935    6.9595885]
		Model Seed: 11 Seed: 2 OOD median of (MSE, MAE) stats: [68.07726    7.1503663]
		Model Seed: 11 Seed: 2 ID likelihoods: -9.627607519006112
		Model Seed: 11 Seed: 2 OOD likelihoods: -9.57073683542902
		Model Seed: 11 Seed: 2 ID calibration errors: [0.28275449 0.185087   0.11956084 0.07782277 0.05035388 0.03452364
 0.02454363 0.01705299 0.0120344  0.00908513 0.00674405 0.00531772]
		Model Seed: 11 Seed: 2 OOD calibration errors: [0.27820762 0.17034137 0.10455292 0.06815472 0.04737363 0.03458956
 0.02812146 0.02256026 0.01898113 0.01538192 0.01562188 0.01555021]
	Model Seed: 11 ID mean of (MSE, MAE): [220.59462    9.625063]
	Model Seed: 11 OOD mean of (MSE, MAE): [201.49771    9.748762]
	Model Seed: 11 ID median of (MSE, MAE): [64.7735     6.9834585]
	Model Seed: 11 OOD median of (MSE, MAE): [73.08266    7.4429245]
	Model Seed: 11 ID likelihoods: -9.616988426224669
	Model Seed: 11 OOD likelihoods: -9.571826942965087
	Model Seed: 11 ID calibration errors: [0.27164973 0.17685028 0.11267248 0.07250489 0.0476757  0.03268494
 0.02301249 0.01665976 0.01214118 0.00978436 0.00777618 0.00663715]
	Model Seed: 11 OOD calibration errors: [0.24621508 0.15227978 0.09533105 0.06457032 0.04620671 0.03743279
 0.03149122 0.02996458 0.02986396 0.03184313 0.03049375 0.03260547]
	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): [224.93315    9.772561]
		Model Seed: 12 Seed: 1 OOD mean of (MSE, MAE) stats: [212.36314   10.080599]
		Model Seed: 12 Seed: 1 ID median of (MSE, MAE): [67.668465   7.1457977]
		Model Seed: 12 Seed: 1 OOD median of (MSE, MAE) stats: [75.90571    7.7374973]
		Model Seed: 12 Seed: 1 ID likelihoods: -9.626840396875377
		Model Seed: 12 Seed: 1 OOD likelihoods: -9.59808791231152
		Model Seed: 12 Seed: 1 ID calibration errors: [0.26212534 0.17280055 0.11079975 0.07314296 0.04968501 0.0343072
 0.02479123 0.01774577 0.013189   0.01013741 0.00841469 0.00678113]
		Model Seed: 12 Seed: 1 OOD calibration errors: [0.20168051 0.12805845 0.07587067 0.04731865 0.03035571 0.02218354
 0.01873773 0.01581696 0.01633198 0.01725128 0.01975618 0.02706033]
	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): [230.3473     9.860741]
		Model Seed: 12 Seed: 2 OOD mean of (MSE, MAE) stats: [192.78555    9.565398]
		Model Seed: 12 Seed: 2 ID median of (MSE, MAE): [66.672844   7.1151757]
		Model Seed: 12 Seed: 2 OOD median of (MSE, MAE) stats: [73.176216   7.3667703]
		Model Seed: 12 Seed: 2 ID likelihoods: -9.638732331622661
		Model Seed: 12 Seed: 2 OOD likelihoods: -9.549728904206658
		Model Seed: 12 Seed: 2 ID calibration errors: [0.30194051 0.19776672 0.12713365 0.08204108 0.0551982  0.03872809
 0.03001844 0.02493411 0.02177112 0.02038896 0.01933141 0.01918078]
		Model Seed: 12 Seed: 2 OOD calibration errors: [0.27773112 0.16673582 0.09607574 0.05393524 0.03103816 0.01817581
 0.01157131 0.00792682 0.00613505 0.00615937 0.00560716 0.00656808]
	Model Seed: 12 ID mean of (MSE, MAE): [227.64023   9.81665]
	Model Seed: 12 OOD mean of (MSE, MAE): [202.57434    9.822998]
	Model Seed: 12 ID median of (MSE, MAE): [67.170654   7.1304865]
	Model Seed: 12 OOD median of (MSE, MAE): [74.54096    7.5521336]
	Model Seed: 12 ID likelihoods: -9.632786364249018
	Model Seed: 12 OOD likelihoods: -9.57390840825909
	Model Seed: 12 ID calibration errors: [0.28203292 0.18528363 0.1189667  0.07759202 0.0524416  0.03651765
 0.02740483 0.02133994 0.01748006 0.01526319 0.01387305 0.01298095]
	Model Seed: 12 OOD calibration errors: [0.23970581 0.14739713 0.08597321 0.05062695 0.03069693 0.02017967
 0.01515452 0.01187189 0.01123351 0.01170532 0.01268167 0.01681421]
	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): [226.2403     9.801553]
		Model Seed: 13 Seed: 1 OOD mean of (MSE, MAE) stats: [204.05539    9.774461]
		Model Seed: 13 Seed: 1 ID median of (MSE, MAE): [65.96408   7.040182]
		Model Seed: 13 Seed: 1 OOD median of (MSE, MAE) stats: [72.823235   7.5008283]
		Model Seed: 13 Seed: 1 ID likelihoods: -9.62973656808602
		Model Seed: 13 Seed: 1 OOD likelihoods: -9.57813393354397
		Model Seed: 13 Seed: 1 ID calibration errors: [0.24919803 0.16441357 0.10505603 0.06879552 0.04705654 0.03332336
 0.0234501  0.0175922  0.0129235  0.01072977 0.00904753 0.00774378]
		Model Seed: 13 Seed: 1 OOD calibration errors: [0.23263524 0.14338714 0.08869383 0.05701745 0.03796071 0.028569
 0.02334188 0.02437916 0.02384686 0.0262966  0.02985021 0.03290129]
	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): [226.84256    9.710869]
		Model Seed: 13 Seed: 2 OOD mean of (MSE, MAE) stats: [200.90926    9.531217]
		Model Seed: 13 Seed: 2 ID median of (MSE, MAE): [64.12251    6.9780993]
		Model Seed: 13 Seed: 2 OOD median of (MSE, MAE) stats: [66.12247   7.083794]
		Model Seed: 13 Seed: 2 ID likelihoods: -9.631065695355824
		Model Seed: 13 Seed: 2 OOD likelihoods: -9.570365470695014
		Model Seed: 13 Seed: 2 ID calibration errors: [0.29010293 0.1898813  0.12042084 0.07797721 0.05066933 0.03454645
 0.02393763 0.01653907 0.01147851 0.00873121 0.00675515 0.00574322]
		Model Seed: 13 Seed: 2 OOD calibration errors: [0.29375795 0.17197031 0.10179061 0.06560333 0.04928373 0.04038597
 0.03454046 0.03274109 0.02979387 0.02446282 0.02529605 0.02424655]
	Model Seed: 13 ID mean of (MSE, MAE): [226.54143   9.75621]
	Model Seed: 13 OOD mean of (MSE, MAE): [202.48233    9.652839]
	Model Seed: 13 ID median of (MSE, MAE): [65.0433    7.009141]
	Model Seed: 13 OOD median of (MSE, MAE): [69.472855  7.292311]
	Model Seed: 13 ID likelihoods: -9.630401131720923
	Model Seed: 13 OOD likelihoods: -9.574249702119491
	Model Seed: 13 ID calibration errors: [0.26965048 0.17714743 0.11273844 0.07338637 0.04886294 0.03393491
 0.02369387 0.01706564 0.012201   0.00973049 0.00790134 0.0067435 ]
	Model Seed: 13 OOD calibration errors: [0.26319659 0.15767873 0.09524222 0.06131039 0.04362222 0.03447748
 0.02894117 0.02856013 0.02682037 0.02537971 0.02757313 0.02857392]
	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): [221.75807   9.73551]
		Model Seed: 14 Seed: 1 OOD mean of (MSE, MAE) stats: [203.48698    9.873545]
		Model Seed: 14 Seed: 1 ID median of (MSE, MAE): [67.03853    7.0971937]
		Model Seed: 14 Seed: 1 OOD median of (MSE, MAE) stats: [74.25645   7.664362]
		Model Seed: 14 Seed: 1 ID likelihoods: -9.619732043917907
		Model Seed: 14 Seed: 1 OOD likelihoods: -9.57673906748784
		Model Seed: 14 Seed: 1 ID calibration errors: [0.25695987 0.16667863 0.10523634 0.06793121 0.04521679 0.0307792
 0.02246532 0.01592262 0.01149937 0.00896275 0.00755798 0.00625933]
		Model Seed: 14 Seed: 1 OOD calibration errors: [0.23144532 0.14578357 0.09041418 0.05811976 0.0393919  0.02922761
 0.0257301  0.02381338 0.02505469 0.02594297 0.02831269 0.03170263]
	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): [230.62843    9.780765]
		Model Seed: 14 Seed: 2 OOD mean of (MSE, MAE) stats: [203.42078   9.6244 ]
		Model Seed: 14 Seed: 2 ID median of (MSE, MAE): [64.38261   7.051168]
		Model Seed: 14 Seed: 2 OOD median of (MSE, MAE) stats: [67.58069    7.0956903]
		Model Seed: 14 Seed: 2 ID likelihoods: -9.63934321163752
		Model Seed: 14 Seed: 2 OOD likelihoods: -9.576577107624344
		Model Seed: 14 Seed: 2 ID calibration errors: [0.27904742 0.18336877 0.12025224 0.07756862 0.05263595 0.03505565
 0.02444727 0.01738071 0.01276889 0.00869409 0.00748057 0.00591782]
		Model Seed: 14 Seed: 2 OOD calibration errors: [0.2620927  0.16588134 0.11074222 0.08026605 0.06082938 0.05108382
 0.0435964  0.03940868 0.03524143 0.02689546 0.02738852 0.0256038 ]
	Model Seed: 14 ID mean of (MSE, MAE): [226.19325    9.758137]
	Model Seed: 14 OOD mean of (MSE, MAE): [203.45389    9.748972]
	Model Seed: 14 ID median of (MSE, MAE): [65.71057    7.0741806]
	Model Seed: 14 OOD median of (MSE, MAE): [70.918564  7.380026]
	Model Seed: 14 ID likelihoods: -9.629537627777713
	Model Seed: 14 OOD likelihoods: -9.57665808755609
	Model Seed: 14 ID calibration errors: [0.26800364 0.1750237  0.11274429 0.07274991 0.04892637 0.03291742
 0.02345629 0.01665167 0.01213413 0.00882842 0.00751927 0.00608857]
	Model Seed: 14 OOD calibration errors: [0.24676901 0.15583246 0.1005782  0.0691929  0.05011064 0.04015571
 0.03466325 0.03161103 0.03014806 0.02641922 0.0278506  0.02865322]
	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): [221.9471     9.773529]
		Model Seed: 15 Seed: 1 OOD mean of (MSE, MAE) stats: [206.00972    9.988373]
		Model Seed: 15 Seed: 1 ID median of (MSE, MAE): [66.66284   7.164132]
		Model Seed: 15 Seed: 1 OOD median of (MSE, MAE) stats: [75.65624    7.7449155]
		Model Seed: 15 Seed: 1 ID likelihoods: -9.620158335792702
		Model Seed: 15 Seed: 1 OOD likelihoods: -9.582900431113359
		Model Seed: 15 Seed: 1 ID calibration errors: [0.26260078 0.16858602 0.10887396 0.06788378 0.0442057  0.03146203
 0.02167689 0.01438534 0.01116044 0.00935509 0.00799233 0.00716568]
		Model Seed: 15 Seed: 1 OOD calibration errors: [0.20973401 0.13132727 0.08333971 0.0553284  0.04189735 0.03112558
 0.02987576 0.03037549 0.03237245 0.03228392 0.03783889 0.04186014]
	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): [223.01224    9.720377]
		Model Seed: 15 Seed: 2 OOD mean of (MSE, MAE) stats: [194.36548    9.545561]
		Model Seed: 15 Seed: 2 ID median of (MSE, MAE): [65.54561  7.05547]
		Model Seed: 15 Seed: 2 OOD median of (MSE, MAE) stats: [72.372734   7.3353505]
		Model Seed: 15 Seed: 2 ID likelihoods: -9.622551856632178
		Model Seed: 15 Seed: 2 OOD likelihoods: -9.553808760012856
		Model Seed: 15 Seed: 2 ID calibration errors: [0.30675052 0.19923596 0.12505126 0.07800512 0.05031825 0.0337415
 0.02460679 0.01820855 0.01538842 0.01392403 0.01268719 0.01321658]
		Model Seed: 15 Seed: 2 OOD calibration errors: [0.28824363 0.1718702  0.09671898 0.05565196 0.03216181 0.01958836
 0.0135967  0.00950524 0.00835731 0.00767888 0.0085288  0.00898527]
	Model Seed: 15 ID mean of (MSE, MAE): [222.47968    9.746953]
	Model Seed: 15 OOD mean of (MSE, MAE): [200.18759    9.766967]
	Model Seed: 15 ID median of (MSE, MAE): [66.104225   7.1098013]
	Model Seed: 15 OOD median of (MSE, MAE): [74.01449   7.540133]
	Model Seed: 15 ID likelihoods: -9.62135509621244
	Model Seed: 15 OOD likelihoods: -9.568354595563108
	Model Seed: 15 ID calibration errors: [0.28467565 0.18391099 0.11696261 0.07294445 0.04726198 0.03260176
 0.02314184 0.01629694 0.01327443 0.01163956 0.01033976 0.01019113]
	Model Seed: 15 OOD calibration errors: [0.24898882 0.15159874 0.09002935 0.05549018 0.03702958 0.02535697
 0.02173623 0.01994036 0.02036488 0.0199814  0.02318384 0.0254227 ]
	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): [225.76901    9.829074]
		Model Seed: 16 Seed: 1 OOD mean of (MSE, MAE) stats: [208.39397   10.018512]
		Model Seed: 16 Seed: 1 ID median of (MSE, MAE): [68.57065    7.1425824]
		Model Seed: 16 Seed: 1 OOD median of (MSE, MAE) stats: [78.3323     7.8660493]
		Model Seed: 16 Seed: 1 ID likelihoods: -9.62869409504059
		Model Seed: 16 Seed: 1 OOD likelihoods: -9.588654957339745
		Model Seed: 16 Seed: 1 ID calibration errors: [0.25768217 0.1673192  0.10696465 0.0674557  0.04493641 0.03017653
 0.02201364 0.01600305 0.012043   0.01017283 0.00920786 0.00846386]
		Model Seed: 16 Seed: 1 OOD calibration errors: [0.21045349 0.13407207 0.08078849 0.05153291 0.03626722 0.02984466
 0.02518295 0.02945065 0.03043797 0.03111124 0.03820555 0.04297179]
	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): [227.87537     9.8754425]
		Model Seed: 16 Seed: 2 OOD mean of (MSE, MAE) stats: [199.3096     9.646022]
		Model Seed: 16 Seed: 2 ID median of (MSE, MAE): [67.70581   7.193213]
		Model Seed: 16 Seed: 2 OOD median of (MSE, MAE) stats: [72.49808    7.3508625]
		Model Seed: 16 Seed: 2 ID likelihoods: -9.63333872329039
		Model Seed: 16 Seed: 2 OOD likelihoods: -9.566368002936704
		Model Seed: 16 Seed: 2 ID calibration errors: [0.30048566 0.19115111 0.12005709 0.07607055 0.04880334 0.03204311
 0.02334011 0.01888919 0.01521784 0.01467987 0.01390828 0.01405848]
		Model Seed: 16 Seed: 2 OOD calibration errors: [0.27474499 0.17053717 0.10013189 0.06051627 0.03533666 0.02374133
 0.01453073 0.01019189 0.00770556 0.00638454 0.0063893  0.0068939 ]
	Model Seed: 16 ID mean of (MSE, MAE): [226.82219    9.852259]
	Model Seed: 16 OOD mean of (MSE, MAE): [203.85178    9.832267]
	Model Seed: 16 ID median of (MSE, MAE): [68.13823    7.1678977]
	Model Seed: 16 OOD median of (MSE, MAE): [75.41519    7.6084557]
	Model Seed: 16 ID likelihoods: -9.63101640916549
	Model Seed: 16 OOD likelihoods: -9.577511480138224
	Model Seed: 16 ID calibration errors: [0.27908391 0.17923516 0.11351087 0.07176313 0.04686988 0.03110982
 0.02267688 0.01744612 0.01363042 0.01242635 0.01155807 0.01126117]
	Model Seed: 16 OOD calibration errors: [0.24259924 0.15230462 0.09046019 0.05602459 0.03580194 0.026793
 0.01985684 0.01982127 0.01907176 0.01874789 0.02229742 0.02493284]
	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): [222.61618    9.846051]
		Model Seed: 17 Seed: 1 OOD mean of (MSE, MAE) stats: [200.07042    9.802138]
		Model Seed: 17 Seed: 1 ID median of (MSE, MAE): [70.97052   7.320345]
		Model Seed: 17 Seed: 1 OOD median of (MSE, MAE) stats: [75.755135  7.643706]
		Model Seed: 17 Seed: 1 ID likelihoods: -9.62166295837822
		Model Seed: 17 Seed: 1 OOD likelihoods: -9.568274263376457
		Model Seed: 17 Seed: 1 ID calibration errors: [0.25010401 0.16140729 0.1016486  0.06406357 0.04134511 0.02840748
 0.01928295 0.01338611 0.00976092 0.00740265 0.00597731 0.00489608]
		Model Seed: 17 Seed: 1 OOD calibration errors: [0.20440346 0.12672558 0.07945573 0.05029169 0.0355597  0.02811536
 0.02306829 0.023479   0.02567923 0.02960612 0.0352783  0.03972259]
	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): [226.27199    9.808691]
		Model Seed: 17 Seed: 2 OOD mean of (MSE, MAE) stats: [198.76839    9.695124]
		Model Seed: 17 Seed: 2 ID median of (MSE, MAE): [68.42878   7.148067]
		Model Seed: 17 Seed: 2 OOD median of (MSE, MAE) stats: [74.552826   7.5492454]
		Model Seed: 17 Seed: 2 ID likelihoods: -9.629807414211088
		Model Seed: 17 Seed: 2 OOD likelihoods: -9.565009163018878
		Model Seed: 17 Seed: 2 ID calibration errors: [0.29202006 0.1905365  0.1203173  0.07446865 0.04684982 0.03037
 0.02110884 0.01542318 0.01215509 0.01088855 0.01081649 0.01088575]
		Model Seed: 17 Seed: 2 OOD calibration errors: [0.29025943 0.17436716 0.09948502 0.05854593 0.03385742 0.0210762
 0.01328337 0.00949739 0.00752438 0.00685223 0.00703847 0.00823214]
	Model Seed: 17 ID mean of (MSE, MAE): [224.44409    9.827372]
	Model Seed: 17 OOD mean of (MSE, MAE): [199.4194     9.748631]
	Model Seed: 17 ID median of (MSE, MAE): [69.699646  7.234206]
	Model Seed: 17 OOD median of (MSE, MAE): [75.15398    7.5964756]
	Model Seed: 17 ID likelihoods: -9.625735186294655
	Model Seed: 17 OOD likelihoods: -9.566641713197669
	Model Seed: 17 ID calibration errors: [0.27106203 0.1759719  0.11098295 0.06926611 0.04409747 0.02938874
 0.0201959  0.01440465 0.01095801 0.0091456  0.0083969  0.00789091]
	Model Seed: 17 OOD calibration errors: [0.24733145 0.15054637 0.08947038 0.05441881 0.03470856 0.02459578
 0.01817583 0.01648819 0.0166018  0.01822917 0.02115838 0.02397736]
	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): [216.98888   9.65437]
		Model Seed: 18 Seed: 1 OOD mean of (MSE, MAE) stats: [209.88547   10.114409]
		Model Seed: 18 Seed: 1 ID median of (MSE, MAE): [66.24161    7.0426927]
		Model Seed: 18 Seed: 1 OOD median of (MSE, MAE) stats: [80.542114  7.949495]
		Model Seed: 18 Seed: 1 ID likelihoods: -9.608861824893406
		Model Seed: 18 Seed: 1 OOD likelihoods: -9.592219055260435
		Model Seed: 18 Seed: 1 ID calibration errors: [0.26164688 0.16462017 0.10293707 0.0650673  0.04339655 0.02960601
 0.02072925 0.01528237 0.01202681 0.01004151 0.00876359 0.00785409]
		Model Seed: 18 Seed: 1 OOD calibration errors: [0.23346197 0.14574049 0.10299226 0.07629586 0.05752189 0.04941907
 0.04405904 0.04240914 0.04593653 0.04443891 0.05001237 0.05260108]
	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): [226.88583    9.754916]
		Model Seed: 18 Seed: 2 OOD mean of (MSE, MAE) stats: [203.36945    9.768736]
		Model Seed: 18 Seed: 2 ID median of (MSE, MAE): [65.76254    7.0659256]
		Model Seed: 18 Seed: 2 OOD median of (MSE, MAE) stats: [68.91778  7.26769]
		Model Seed: 18 Seed: 2 ID likelihoods: -9.631162044782299
		Model Seed: 18 Seed: 2 OOD likelihoods: -9.576450248054432
		Model Seed: 18 Seed: 2 ID calibration errors: [0.28464318 0.18601687 0.11504821 0.07302317 0.04728825 0.03192023
 0.02172595 0.01522733 0.01097707 0.00892465 0.00726464 0.00647303]
		Model Seed: 18 Seed: 2 OOD calibration errors: [0.27488183 0.16348952 0.09596803 0.05719967 0.03803405 0.02596333
 0.01969691 0.01657901 0.01357705 0.01175252 0.01171684 0.01063796]
	Model Seed: 18 ID mean of (MSE, MAE): [221.93735    9.704643]
	Model Seed: 18 OOD mean of (MSE, MAE): [206.62746    9.941572]
	Model Seed: 18 ID median of (MSE, MAE): [66.002075  7.054309]
	Model Seed: 18 OOD median of (MSE, MAE): [74.72995    7.6085925]
	Model Seed: 18 ID likelihoods: -9.620011934837851
	Model Seed: 18 OOD likelihoods: -9.584334651657432
	Model Seed: 18 ID calibration errors: [0.27314503 0.17531852 0.10899264 0.06904523 0.0453424  0.03076312
 0.0212276  0.01525485 0.01150194 0.00948308 0.00801411 0.00716356]
	Model Seed: 18 OOD calibration errors: [0.2541719  0.154615   0.09948014 0.06674777 0.04777797 0.0376912
 0.03187798 0.02949407 0.02975679 0.02809571 0.0308646  0.03161952]
	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): [221.3873     9.723465]
		Model Seed: 19 Seed: 1 OOD mean of (MSE, MAE) stats: [204.75525    9.798554]
		Model Seed: 19 Seed: 1 ID median of (MSE, MAE): [65.830574   7.0593243]
		Model Seed: 19 Seed: 1 OOD median of (MSE, MAE) stats: [71.83187   7.436695]
		Model Seed: 19 Seed: 1 ID likelihoods: -9.618895358201108
		Model Seed: 19 Seed: 1 OOD likelihoods: -9.57984595170763
		Model Seed: 19 Seed: 1 ID calibration errors: [0.2587867  0.16631091 0.10712617 0.06800499 0.04572272 0.03208129
 0.0230447  0.01614319 0.01245482 0.01009287 0.00912518 0.00836342]
		Model Seed: 19 Seed: 1 OOD calibration errors: [0.23399293 0.14694559 0.0921816  0.05884729 0.03970001 0.02908636
 0.02165446 0.02173202 0.02220875 0.02406794 0.02528098 0.02905506]
	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): [233.87534    9.859663]
		Model Seed: 19 Seed: 2 OOD mean of (MSE, MAE) stats: [211.57832   10.118002]
		Model Seed: 19 Seed: 2 ID median of (MSE, MAE): [66.08779    7.0913033]
		Model Seed: 19 Seed: 2 OOD median of (MSE, MAE) stats: [79.89257   7.802216]
		Model Seed: 19 Seed: 2 ID likelihoods: -9.646334111149331
		Model Seed: 19 Seed: 2 OOD likelihoods: -9.59623623190797
		Model Seed: 19 Seed: 2 ID calibration errors: [0.29543925 0.19170584 0.12229352 0.07907866 0.05236234 0.03689987
 0.02616033 0.01933365 0.01514052 0.01200671 0.01016935 0.00903499]
		Model Seed: 19 Seed: 2 OOD calibration errors: [0.29265426 0.17345539 0.10031633 0.05637494 0.03180635 0.01903671
 0.01231668 0.00890233 0.007457   0.00681633 0.00733012 0.00844477]
	Model Seed: 19 ID mean of (MSE, MAE): [227.63132    9.791564]
	Model Seed: 19 OOD mean of (MSE, MAE): [208.16678    9.958279]
	Model Seed: 19 ID median of (MSE, MAE): [65.95918    7.0753136]
	Model Seed: 19 OOD median of (MSE, MAE): [75.86222    7.6194553]
	Model Seed: 19 ID likelihoods: -9.632614734675219
	Model Seed: 19 OOD likelihoods: -9.5880410918078
	Model Seed: 19 ID calibration errors: [0.27711297 0.17900838 0.11470984 0.07354182 0.04904253 0.03449058
 0.02460251 0.01773842 0.01379767 0.01104979 0.00964727 0.0086992 ]
	Model Seed: 19 OOD calibration errors: [0.2633236  0.16020049 0.09624897 0.05761111 0.03575318 0.02406153
 0.01698557 0.01531718 0.01483287 0.01544213 0.01630555 0.01874992]
ID mean of (MSE, MAE): [224.7707977294922, 9.764622688293457] +- [2.4170658588409424, 0.06209452450275421] +- [3.271414   0.01807072] 
OOD mean of (MSE, MAE): [203.21568298339844, 9.807680130004883] +- [2.5408406257629395, 0.08931496739387512] +- [2.71216   0.1382952] 
ID median of (MSE, MAE): [66.5784683227539, 7.096554756164551] +- [1.4212549924850464, 0.070316843688488] +- [0.72975475 0.02657573] 
OOD median of (MSE, MAE): [73.76795959472656, 7.528184413909912] +- [1.95346200466156, 0.11148111522197723] +- [2.4725264  0.19464755] 
ID likelihoods: -9.626374144382341 +- 0.00539897159907972 +- 0.007288156797934597 
OOD likelihoods: -9.575915148987 +- 0.006249979505963064 +- 0.006710087890365202 
ID calibration errors: [0.275211879891225, 0.17854832698887477, 0.11343417720483615, 0.07239853065333926, 0.0477850929581342, 0.032573450838825194, 0.02316106535507303, 0.016874545349877652, 0.012972857949511191, 0.010762255020091514, 0.009401434144303309, 0.008597718646597747] +- [0.0052154268830230935, 0.003313740265644241, 0.002717601586116421, 0.0022935934475901663, 0.002159260881000392, 0.001957964579442443, 0.0018485788483857386, 0.0017656957029484391, 0.001728134070842497, 0.0018474567638504156, 0.0019268100690612762, 0.002122892206905507] +- [0.0172849  0.01217619 0.00778475 0.00487245 0.00272363 0.0014983
 0.00107485 0.0009986  0.0009163  0.0008982  0.00087721 0.00108455] 
OOD calibration errors: [0.25147927580291285, 0.1544572309005839, 0.09432395009133103, 0.060275076815661334, 0.041127628257307744, 0.03091479957478751, 0.02509517665507387, 0.02330783892094237, 0.022810254270617555, 0.022454506444756717, 0.02437172067000533, 0.026269525025112022] +- [0.0083478853428249, 0.004320505685130611, 0.004849351151918497, 0.0059867375398844815, 0.0067248522969604796, 0.007018518378947849, 0.007021925542211604, 0.00699043027344458, 0.0068383580748770535, 0.0062104397164021935, 0.006065174417957032, 0.005091519218493949] +- [0.03058255 0.01531959 0.00615626 0.00150782 0.00085423 0.0021929
 0.00332148 0.00516229 0.00722411 0.00936476 0.01087456 0.01294821] 
