Optimization started at 2023-03-05 02:32:44.686729--------------------------------
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)
		gender: REAL_VALUED (STATIC_INPUT)
		age: REAL_VALUED (STATIC_INPUT)
		BMI: REAL_VALUED (STATIC_INPUT)
		glycaemia: REAL_VALUED (STATIC_INPUT)
		HbA1c: REAL_VALUED (STATIC_INPUT)
		follow.up: REAL_VALUED (STATIC_INPUT)
		T2DM: 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: 63
	Extracted segments: 205
	Interpolated values: 241
	Percent of values interpolated: 0.22%
Splitting data...
	Train: 37857 (38.80%)
	Val: 31296 (32.08%)
	Test: 39658 (40.65%)
Scaling data...
	No scaling applied
Data formatting complete.
--------------------------------
Current value: 0.03513933718204498, Current params: {'in_len': 96, 'max_samples_per_ts': 150, 'kernel_sizes': 1, 'dropout': 0.0925808695777687, 'lr': 0.0008885475788992303, 'batch_size': 64, 'lr_epochs': 20}
Best value: 0.03513933718204498, Best params: {'in_len': 96, 'max_samples_per_ts': 150, 'kernel_sizes': 1, 'dropout': 0.0925808695777687, 'lr': 0.0008885475788992303, 'batch_size': 64, 'lr_epochs': 20}
Current value: 0.03298381716012955, Current params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 4, 'dropout': 0.07749545729973839, 'lr': 0.00018284041386657613, 'batch_size': 32, 'lr_epochs': 4}
Best value: 0.03298381716012955, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 4, 'dropout': 0.07749545729973839, 'lr': 0.00018284041386657613, 'batch_size': 32, 'lr_epochs': 4}
Current value: 0.03191572427749634, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.17761521872707853, 'lr': 0.00017099501275565852, 'batch_size': 48, 'lr_epochs': 6}
Best value: 0.03191572427749634, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.17761521872707853, 'lr': 0.00017099501275565852, 'batch_size': 48, 'lr_epochs': 6}
Current value: 0.04306570813059807, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'kernel_sizes': 4, 'dropout': 0.16122082838578544, 'lr': 0.00038569959798453665, 'batch_size': 48, 'lr_epochs': 6}
Best value: 0.03191572427749634, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.17761521872707853, 'lr': 0.00017099501275565852, 'batch_size': 48, 'lr_epochs': 6}
Current value: 0.035375822335481644, Current params: {'in_len': 96, 'max_samples_per_ts': 150, 'kernel_sizes': 5, 'dropout': 0.0022358234795182732, 'lr': 0.0006851882540562331, 'batch_size': 64, 'lr_epochs': 2}
Best value: 0.03191572427749634, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.17761521872707853, 'lr': 0.00017099501275565852, 'batch_size': 48, 'lr_epochs': 6}
Current value: 0.0028936550952494144, Current params: {'in_len': 108, 'max_samples_per_ts': 200, 'kernel_sizes': 2, 'dropout': 0.09925811326802914, 'lr': 0.0008609788953877102, 'batch_size': 64, 'lr_epochs': 12}
Best value: 0.03191572427749634, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.17761521872707853, 'lr': 0.00017099501275565852, 'batch_size': 48, 'lr_epochs': 6}
Current value: 0.0029569424223154783, Current params: {'in_len': 144, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.007976945153223959, 'lr': 0.0004418837232781088, 'batch_size': 32, 'lr_epochs': 16}
Best value: 0.03191572427749634, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.17761521872707853, 'lr': 0.00017099501275565852, 'batch_size': 48, 'lr_epochs': 6}
Current value: 0.0034587050322443247, Current params: {'in_len': 108, 'max_samples_per_ts': 200, 'kernel_sizes': 2, 'dropout': 0.1516472338385667, 'lr': 0.0005873537761914501, 'batch_size': 64, 'lr_epochs': 16}
Best value: 0.03191572427749634, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.17761521872707853, 'lr': 0.00017099501275565852, 'batch_size': 48, 'lr_epochs': 6}
Current value: 0.003206957131624222, Current params: {'in_len': 144, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.17469863238569902, 'lr': 0.0006977052560780903, 'batch_size': 48, 'lr_epochs': 8}
Best value: 0.03191572427749634, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.17761521872707853, 'lr': 0.00017099501275565852, 'batch_size': 48, 'lr_epochs': 6}
Current value: 0.002451896434649825, Current params: {'in_len': 108, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.08441099259977883, 'lr': 0.0004258847050154004, 'batch_size': 48, 'lr_epochs': 12}
Best value: 0.03191572427749634, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.17761521872707853, 'lr': 0.00017099501275565852, 'batch_size': 48, 'lr_epochs': 6}
Current value: 0.0027127095963805914, Current params: {'in_len': 132, 'max_samples_per_ts': 50, 'kernel_sizes': 3, 'dropout': 0.18618539883540253, 'lr': 0.00010832611341096534, 'batch_size': 32, 'lr_epochs': 8}
Best value: 0.03191572427749634, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.17761521872707853, 'lr': 0.00017099501275565852, 'batch_size': 48, 'lr_epochs': 6}
Current value: 0.003377359127625823, Current params: {'in_len': 120, 'max_samples_per_ts': 100, 'kernel_sizes': 4, 'dropout': 0.1286360287307169, 'lr': 0.00012144462427739612, 'batch_size': 32, 'lr_epochs': 2}
Best value: 0.03191572427749634, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.17761521872707853, 'lr': 0.00017099501275565852, 'batch_size': 48, 'lr_epochs': 6}
Current value: 0.0035392818972468376, Current params: {'in_len': 96, 'max_samples_per_ts': 100, 'kernel_sizes': 4, 'dropout': 0.19563229467272625, 'lr': 0.00025246932747033016, 'batch_size': 32, 'lr_epochs': 6}
Best value: 0.03191572427749634, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.17761521872707853, 'lr': 0.00017099501275565852, 'batch_size': 48, 'lr_epochs': 6}
Current value: 0.002693561604246497, Current params: {'in_len': 120, 'max_samples_per_ts': 100, 'kernel_sizes': 3, 'dropout': 0.06253070353217499, 'lr': 0.0002730754983146052, 'batch_size': 48, 'lr_epochs': 4}
Best value: 0.03191572427749634, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.17761521872707853, 'lr': 0.00017099501275565852, 'batch_size': 48, 'lr_epochs': 6}
Current value: 0.0028703061398118734, Current params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 4, 'dropout': 0.13098562578462414, 'lr': 0.00023609642745355065, 'batch_size': 32, 'lr_epochs': 8}
Best value: 0.03191572427749634, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.17761521872707853, 'lr': 0.00017099501275565852, 'batch_size': 48, 'lr_epochs': 6}
Current value: 0.0020674539264291525, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 4, 'dropout': 0.12852894643281176, 'lr': 0.00017605083610781154, 'batch_size': 48, 'lr_epochs': 4}
Best value: 0.03191572427749634, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.17761521872707853, 'lr': 0.00017099501275565852, 'batch_size': 48, 'lr_epochs': 6}
Current value: 0.0027391479816287756, Current params: {'in_len': 108, 'max_samples_per_ts': 100, 'kernel_sizes': 5, 'dropout': 0.19797747797873844, 'lr': 0.00032054422635508536, 'batch_size': 32, 'lr_epochs': 10}
Best value: 0.03191572427749634, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.17761521872707853, 'lr': 0.00017099501275565852, 'batch_size': 48, 'lr_epochs': 6}
Current value: 0.0030882128048688173, Current params: {'in_len': 120, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.051051613766224614, 'lr': 0.00019561168258338537, 'batch_size': 48, 'lr_epochs': 4}
Best value: 0.03191572427749634, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.17761521872707853, 'lr': 0.00017099501275565852, 'batch_size': 48, 'lr_epochs': 6}
Current value: 0.0023195950780063868, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 4, 'dropout': 0.11280683815537579, 'lr': 0.0003346453918920166, 'batch_size': 48, 'lr_epochs': 6}
Best value: 0.03191572427749634, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.17761521872707853, 'lr': 0.00017099501275565852, 'batch_size': 48, 'lr_epochs': 6}
Current value: 0.004468749742954969, Current params: {'in_len': 120, 'max_samples_per_ts': 100, 'kernel_sizes': 2, 'dropout': 0.16199551024881026, 'lr': 0.00010675668129618617, 'batch_size': 32, 'lr_epochs': 10}
Best value: 0.03191572427749634, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.17761521872707853, 'lr': 0.00017099501275565852, 'batch_size': 48, 'lr_epochs': 6}
Current value: 0.002583207795396447, Current params: {'in_len': 132, 'max_samples_per_ts': 150, 'kernel_sizes': 5, 'dropout': 0.1504721709084422, 'lr': 0.000490232357199339, 'batch_size': 48, 'lr_epochs': 2}
Best value: 0.03191572427749634, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.17761521872707853, 'lr': 0.00017099501275565852, 'batch_size': 48, 'lr_epochs': 6}
Current value: 0.03260118141770363, Current params: {'in_len': 96, 'max_samples_per_ts': 150, 'kernel_sizes': 1, 'dropout': 0.08335714484872275, 'lr': 0.0009930853913941698, 'batch_size': 64, 'lr_epochs': 20}
Best value: 0.03191572427749634, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.17761521872707853, 'lr': 0.00017099501275565852, 'batch_size': 48, 'lr_epochs': 6}
Current value: 0.0026396445464342833, Current params: {'in_len': 96, 'max_samples_per_ts': 150, 'kernel_sizes': 1, 'dropout': 0.07577839200944234, 'lr': 0.0009756337651601684, 'batch_size': 48, 'lr_epochs': 20}
Best value: 0.03191572427749634, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.17761521872707853, 'lr': 0.00017099501275565852, 'batch_size': 48, 'lr_epochs': 6}
Current value: 0.002369322581216693, Current params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 1, 'dropout': 0.07055574588663374, 'lr': 0.0003238245647573329, 'batch_size': 64, 'lr_epochs': 16}
Best value: 0.03191572427749634, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.17761521872707853, 'lr': 0.00017099501275565852, 'batch_size': 48, 'lr_epochs': 6}
Current value: 0.0038644729647785425, Current params: {'in_len': 96, 'max_samples_per_ts': 100, 'kernel_sizes': 3, 'dropout': 0.1088377476444492, 'lr': 0.00019107901139150864, 'batch_size': 64, 'lr_epochs': 14}
Best value: 0.03191572427749634, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.17761521872707853, 'lr': 0.00017099501275565852, 'batch_size': 48, 'lr_epochs': 6}
Current value: 0.0032393860165029764, Current params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 2, 'dropout': 0.054856116661024454, 'lr': 0.0005386310621533725, 'batch_size': 64, 'lr_epochs': 18}
Best value: 0.03191572427749634, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.17761521872707853, 'lr': 0.00017099501275565852, 'batch_size': 48, 'lr_epochs': 6}
Current value: 0.0034359339624643326, Current params: {'in_len': 96, 'max_samples_per_ts': 100, 'kernel_sizes': 4, 'dropout': 0.09130933960300208, 'lr': 0.0003873007895982932, 'batch_size': 48, 'lr_epochs': 6}
Best value: 0.03191572427749634, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 5, 'dropout': 0.17761521872707853, 'lr': 0.00017099501275565852, 'batch_size': 48, 'lr_epochs': 6}
Current value: 0.028532736003398895, Current params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.0025081548374146223, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 2, 'dropout': 0.03620229355656579, 'lr': 0.00029503630224551457, 'batch_size': 64, 'lr_epochs': 18}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.0018101666355505586, Current params: {'in_len': 96, 'max_samples_per_ts': 150, 'kernel_sizes': 1, 'dropout': 0.038675954898000416, 'lr': 0.000824128927274761, 'batch_size': 64, 'lr_epochs': 20}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.0024191837292164564, Current params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 1, 'dropout': 0.10330475721824975, 'lr': 0.0008078137373531806, 'batch_size': 64, 'lr_epochs': 14}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.002535580424591899, Current params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.08034431215941244, 'lr': 0.0002194000303737297, 'batch_size': 64, 'lr_epochs': 14}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.0028556790202856064, Current params: {'in_len': 96, 'max_samples_per_ts': 150, 'kernel_sizes': 4, 'dropout': 0.09299701021510898, 'lr': 0.000965417602984753, 'batch_size': 64, 'lr_epochs': 18}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.0027671444695442915, Current params: {'in_len': 132, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.07668087361592914, 'lr': 0.00035437085253049337, 'batch_size': 64, 'lr_epochs': 4}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.0031463117338716984, Current params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 4, 'dropout': 0.06830057445737416, 'lr': 0.00016661133084986416, 'batch_size': 48, 'lr_epochs': 10}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.002678191987797618, Current params: {'in_len': 96, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.09511503933130755, 'lr': 0.0002678597051299374, 'batch_size': 64, 'lr_epochs': 12}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.0027013591025024652, Current params: {'in_len': 108, 'max_samples_per_ts': 100, 'kernel_sizes': 5, 'dropout': 0.11528701064234102, 'lr': 0.00015796208281854986, 'batch_size': 32, 'lr_epochs': 6}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.0034885175991803408, Current params: {'in_len': 120, 'max_samples_per_ts': 200, 'kernel_sizes': 2, 'dropout': 0.08511861551710723, 'lr': 0.00023952605333069988, 'batch_size': 64, 'lr_epochs': 8}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.0023399796336889267, Current params: {'in_len': 96, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.018783883069519863, 'lr': 0.0006277988183729241, 'batch_size': 48, 'lr_epochs': 2}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.03494659811258316, Current params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.06134109360137843, 'lr': 0.0007575232595114673, 'batch_size': 64, 'lr_epochs': 16}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.002589905634522438, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'kernel_sizes': 2, 'dropout': 0.04594224332011598, 'lr': 0.0004065485927436601, 'batch_size': 32, 'lr_epochs': 20}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.002426959341391921, Current params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.06372537764804093, 'lr': 0.0008997447655358034, 'batch_size': 64, 'lr_epochs': 14}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.0022792420350015163, Current params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.05904824294307286, 'lr': 0.0007521855955474885, 'batch_size': 64, 'lr_epochs': 16}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.0025504755321890116, Current params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 4, 'dropout': 0.08477778147698423, 'lr': 0.0007161972056866216, 'batch_size': 64, 'lr_epochs': 18}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.0026148955803364515, Current params: {'in_len': 108, 'max_samples_per_ts': 200, 'kernel_sizes': 4, 'dropout': 0.07007749407817099, 'lr': 0.0009119910971908678, 'batch_size': 64, 'lr_epochs': 16}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.003391921753063798, Current params: {'in_len': 96, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.05532222526230657, 'lr': 0.00014200329678362104, 'batch_size': 64, 'lr_epochs': 12}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.002660568570718169, Current params: {'in_len': 120, 'max_samples_per_ts': 150, 'kernel_sizes': 5, 'dropout': 0.027266657045382836, 'lr': 0.0006386664531471383, 'batch_size': 48, 'lr_epochs': 12}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.004047919064760208, Current params: {'in_len': 108, 'max_samples_per_ts': 100, 'kernel_sizes': 2, 'dropout': 0.04521889568141632, 'lr': 0.00020839833552620078, 'batch_size': 32, 'lr_epochs': 18}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.002766093472018838, Current params: {'in_len': 96, 'max_samples_per_ts': 100, 'kernel_sizes': 3, 'dropout': 0.06407060069519338, 'lr': 0.0004416224701919694, 'batch_size': 64, 'lr_epochs': 14}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.002977814059704542, Current params: {'in_len': 96, 'max_samples_per_ts': 200, 'kernel_sizes': 4, 'dropout': 0.18189690613902096, 'lr': 0.00013487838275312152, 'batch_size': 48, 'lr_epochs': 16}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.002421076176688075, Current params: {'in_len': 144, 'max_samples_per_ts': 150, 'kernel_sizes': 5, 'dropout': 0.09918316370736541, 'lr': 0.0002682228543185332, 'batch_size': 48, 'lr_epochs': 4}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.003475214820355177, Current params: {'in_len': 96, 'max_samples_per_ts': 150, 'kernel_sizes': 1, 'dropout': 0.0768628295958737, 'lr': 0.0009402140712830124, 'batch_size': 64, 'lr_epochs': 20}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.0019745416939258575, Current params: {'in_len': 96, 'max_samples_per_ts': 150, 'kernel_sizes': 1, 'dropout': 0.10408091424720264, 'lr': 0.0008538952275083816, 'batch_size': 64, 'lr_epochs': 20}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.0024402490817010403, Current params: {'in_len': 120, 'max_samples_per_ts': 150, 'kernel_sizes': 1, 'dropout': 0.08778210973307067, 'lr': 0.0009633645277666335, 'batch_size': 64, 'lr_epochs': 18}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.003377474844455719, Current params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 2, 'dropout': 0.07472064735226511, 'lr': 0.0009958825673819995, 'batch_size': 64, 'lr_epochs': 20}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.002497222274541855, Current params: {'in_len': 96, 'max_samples_per_ts': 150, 'kernel_sizes': 1, 'dropout': 0.06386266340312641, 'lr': 0.00012292702744642507, 'batch_size': 32, 'lr_epochs': 8}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.004479685332626104, Current params: {'in_len': 96, 'max_samples_per_ts': 100, 'kernel_sizes': 3, 'dropout': 0.08380968159235741, 'lr': 0.00018077563987949338, 'batch_size': 48, 'lr_epochs': 16}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.0032867270056158304, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'kernel_sizes': 1, 'dropout': 0.11668221084420687, 'lr': 0.0002267658260547963, 'batch_size': 64, 'lr_epochs': 6}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.004539513494819403, Current params: {'in_len': 96, 'max_samples_per_ts': 150, 'kernel_sizes': 2, 'dropout': 0.0945925759713947, 'lr': 0.0008837119345507548, 'batch_size': 64, 'lr_epochs': 10}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.003121999092400074, Current params: {'in_len': 120, 'max_samples_per_ts': 150, 'kernel_sizes': 4, 'dropout': 0.05160470024199652, 'lr': 0.00010945945606743833, 'batch_size': 64, 'lr_epochs': 2}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.03101804293692112, Current params: {'in_len': 96, 'max_samples_per_ts': 200, 'kernel_sizes': 3, 'dropout': 0.14321974310807514, 'lr': 0.0009256791514277612, 'batch_size': 32, 'lr_epochs': 18}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.0017077689990401268, Current params: {'in_len': 96, 'max_samples_per_ts': 200, 'kernel_sizes': 3, 'dropout': 0.16796136571866643, 'lr': 0.0009368826268761469, 'batch_size': 32, 'lr_epochs': 18}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.03264786675572395, Current params: {'in_len': 96, 'max_samples_per_ts': 200, 'kernel_sizes': 3, 'dropout': 0.14980111170827862, 'lr': 0.0008564355750897836, 'batch_size': 32, 'lr_epochs': 20}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.03186124563217163, Current params: {'in_len': 96, 'max_samples_per_ts': 200, 'kernel_sizes': 3, 'dropout': 0.14771625967932583, 'lr': 0.0008361775515335077, 'batch_size': 32, 'lr_epochs': 20}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.0019700920674949884, Current params: {'in_len': 96, 'max_samples_per_ts': 200, 'kernel_sizes': 3, 'dropout': 0.15490163783591668, 'lr': 0.0008491265328518958, 'batch_size': 32, 'lr_epochs': 20}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.0020441014785319567, Current params: {'in_len': 96, 'max_samples_per_ts': 200, 'kernel_sizes': 3, 'dropout': 0.1379437670276747, 'lr': 0.0009953692238728682, 'batch_size': 32, 'lr_epochs': 20}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.030004722997546196, Current params: {'in_len': 96, 'max_samples_per_ts': 200, 'kernel_sizes': 3, 'dropout': 0.17570115561895366, 'lr': 0.0008828679755583722, 'batch_size': 32, 'lr_epochs': 20}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.002102137776091695, Current params: {'in_len': 96, 'max_samples_per_ts': 200, 'kernel_sizes': 3, 'dropout': 0.17381570868086477, 'lr': 0.0008793262359554505, 'batch_size': 32, 'lr_epochs': 20}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.002116637770086527, Current params: {'in_len': 96, 'max_samples_per_ts': 200, 'kernel_sizes': 3, 'dropout': 0.14826351451253816, 'lr': 0.0009232117670984601, 'batch_size': 32, 'lr_epochs': 18}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.0021517733111977577, Current params: {'in_len': 96, 'max_samples_per_ts': 200, 'kernel_sizes': 3, 'dropout': 0.1615035023488022, 'lr': 0.000912718780657009, 'batch_size': 32, 'lr_epochs': 20}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.03596833720803261, Current params: {'in_len': 96, 'max_samples_per_ts': 200, 'kernel_sizes': 3, 'dropout': 0.1810003942121271, 'lr': 0.0009489515611468104, 'batch_size': 32, 'lr_epochs': 18}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.033082008361816406, Current params: {'in_len': 96, 'max_samples_per_ts': 200, 'kernel_sizes': 3, 'dropout': 0.17149302352757378, 'lr': 0.00081641590930397, 'batch_size': 32, 'lr_epochs': 20}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.002329782349988818, Current params: {'in_len': 96, 'max_samples_per_ts': 200, 'kernel_sizes': 4, 'dropout': 0.15468057437441016, 'lr': 0.0009712708514021583, 'batch_size': 32, 'lr_epochs': 4}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.0019197027431800961, Current params: {'in_len': 96, 'max_samples_per_ts': 200, 'kernel_sizes': 3, 'dropout': 0.195700645479752, 'lr': 0.0008912727532243812, 'batch_size': 32, 'lr_epochs': 20}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.00257728504948318, Current params: {'in_len': 96, 'max_samples_per_ts': 200, 'kernel_sizes': 4, 'dropout': 0.1910191599767646, 'lr': 0.0008414040255965375, 'batch_size': 32, 'lr_epochs': 18}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.002934817224740982, Current params: {'in_len': 96, 'max_samples_per_ts': 200, 'kernel_sizes': 4, 'dropout': 0.16321061941094023, 'lr': 0.000866626287636359, 'batch_size': 32, 'lr_epochs': 20}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.0023512071929872036, Current params: {'in_len': 96, 'max_samples_per_ts': 200, 'kernel_sizes': 3, 'dropout': 0.14434176840465301, 'lr': 0.0002033116679107542, 'batch_size': 32, 'lr_epochs': 4}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.002844406757503748, Current params: {'in_len': 132, 'max_samples_per_ts': 200, 'kernel_sizes': 2, 'dropout': 0.16703120146290065, 'lr': 0.0009250127531366572, 'batch_size': 32, 'lr_epochs': 18}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.031385574489831924, Current params: {'in_len': 108, 'max_samples_per_ts': 200, 'kernel_sizes': 3, 'dropout': 0.17882805499235277, 'lr': 0.0007964684219660058, 'batch_size': 32, 'lr_epochs': 20}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.033967919647693634, Current params: {'in_len': 108, 'max_samples_per_ts': 200, 'kernel_sizes': 3, 'dropout': 0.17725026313384623, 'lr': 0.0007882598827283776, 'batch_size': 32, 'lr_epochs': 20}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.002349558752030134, Current params: {'in_len': 96, 'max_samples_per_ts': 200, 'kernel_sizes': 3, 'dropout': 0.18888083069839803, 'lr': 0.0008693842389344863, 'batch_size': 32, 'lr_epochs': 20}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.0019853217527270317, Current params: {'in_len': 108, 'max_samples_per_ts': 200, 'kernel_sizes': 3, 'dropout': 0.18359728113329088, 'lr': 0.0009039886429208776, 'batch_size': 32, 'lr_epochs': 18}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.0020886061247438192, Current params: {'in_len': 108, 'max_samples_per_ts': 200, 'kernel_sizes': 3, 'dropout': 0.17743455432874705, 'lr': 0.00016077950465551706, 'batch_size': 32, 'lr_epochs': 20}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.003144739428535104, Current params: {'in_len': 108, 'max_samples_per_ts': 200, 'kernel_sizes': 3, 'dropout': 0.16866952707070962, 'lr': 0.0008392747293107684, 'batch_size': 32, 'lr_epochs': 20}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.002577198902145028, Current params: {'in_len': 96, 'max_samples_per_ts': 200, 'kernel_sizes': 5, 'dropout': 0.16020804415000942, 'lr': 0.0007875793448150974, 'batch_size': 32, 'lr_epochs': 18}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.030340006574988365, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 3, 'dropout': 0.12221070970048445, 'lr': 0.0009473153306820261, 'batch_size': 32, 'lr_epochs': 20}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.0018480372382327914, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 2, 'dropout': 0.12638578401137113, 'lr': 0.0009468791727393998, 'batch_size': 32, 'lr_epochs': 20}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.002320322208106518, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 3, 'dropout': 0.1338255674208683, 'lr': 0.0009063054480269953, 'batch_size': 32, 'lr_epochs': 20}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.030282827094197273, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 3, 'dropout': 0.14215767884867775, 'lr': 0.0008772815090278996, 'batch_size': 48, 'lr_epochs': 18}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.03214104101061821, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 3, 'dropout': 0.14287913655667586, 'lr': 0.0008768440685340476, 'batch_size': 48, 'lr_epochs': 18}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.0019013610435649753, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 3, 'dropout': 0.14068992025831625, 'lr': 0.000874788753853233, 'batch_size': 48, 'lr_epochs': 16}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.0018716673366725445, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 3, 'dropout': 0.14469415723889675, 'lr': 0.0009275664655955475, 'batch_size': 48, 'lr_epochs': 18}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.03137806057929993, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 3, 'dropout': 0.12410865490908152, 'lr': 0.0008902304735222445, 'batch_size': 48, 'lr_epochs': 18}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.0023264747578650713, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 3, 'dropout': 0.12780702767618554, 'lr': 0.0008316653186984979, 'batch_size': 48, 'lr_epochs': 18}
Best value: 0.028532736003398895, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'kernel_sizes': 3, 'dropout': 0.041637898715748474, 'lr': 0.0002592717774235545, 'batch_size': 64, 'lr_epochs': 14}
Current value: 0.027212470769882202, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 3, 'dropout': 0.13142967835347927, 'lr': 0.0008921763677516184, 'batch_size': 48, 'lr_epochs': 16}
Best value: 0.027212470769882202, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 3, 'dropout': 0.13142967835347927, 'lr': 0.0008921763677516184, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.0018316205823794007, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 3, 'dropout': 0.13335461847793278, 'lr': 0.0009070890843221803, 'batch_size': 48, 'lr_epochs': 16}
Best value: 0.027212470769882202, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 3, 'dropout': 0.13142967835347927, 'lr': 0.0008921763677516184, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.03061210922896862, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 3, 'dropout': 0.12180134954814917, 'lr': 0.000967216379869497, 'batch_size': 48, 'lr_epochs': 14}
Best value: 0.027212470769882202, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 3, 'dropout': 0.13142967835347927, 'lr': 0.0008921763677516184, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.0018378086388111115, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 3, 'dropout': 0.12289679086945159, 'lr': 0.0009751336506664503, 'batch_size': 48, 'lr_epochs': 14}
Best value: 0.027212470769882202, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 3, 'dropout': 0.13142967835347927, 'lr': 0.0008921763677516184, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.0018406007438898087, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 3, 'dropout': 0.12233329205566683, 'lr': 0.000957807860610675, 'batch_size': 48, 'lr_epochs': 16}
Best value: 0.027212470769882202, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 3, 'dropout': 0.13142967835347927, 'lr': 0.0008921763677516184, 'batch_size': 48, 'lr_epochs': 16}
Current value: 0.0017856479389593005, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 3, 'dropout': 0.1371105073572808, 'lr': 0.0008900534041013186, 'batch_size': 48, 'lr_epochs': 14}
Best value: 0.027212470769882202, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'kernel_sizes': 3, 'dropout': 0.13142967835347927, 'lr': 0.0008921763677516184, 'batch_size': 48, 'lr_epochs': 16}
--------------------------------
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)
		gender: REAL_VALUED (STATIC_INPUT)
		age: REAL_VALUED (STATIC_INPUT)
		BMI: REAL_VALUED (STATIC_INPUT)
		glycaemia: REAL_VALUED (STATIC_INPUT)
		HbA1c: REAL_VALUED (STATIC_INPUT)
		follow.up: REAL_VALUED (STATIC_INPUT)
		T2DM: 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: 63
	Extracted segments: 205
	Interpolated values: 241
	Percent of values interpolated: 0.22%
Splitting data...
	Train: 72275 (45.89%)
	Val: 35713 (22.68%)
	Test: 38253 (24.29%)
	Test OOD: 11242 (7.14%)
Scaling data...
	No scaling applied
Data formatting complete.
--------------------------------
	Train: 72152 (45.77%)
	Val: 35929 (22.79%)
	Test: 38024 (24.12%)
	Test OOD: 11522 (7.31%)
	No scaling applied
		Model Seed: 10 Seed: 1 ID mean of (MSE, MAE): [192.49002   10.392965]
		Model Seed: 10 Seed: 1 OOD mean of (MSE, MAE) stats: [155.48973    9.122008]
		Model Seed: 10 Seed: 1 ID median of (MSE, MAE): [92.00459  8.83758]
		Model Seed: 10 Seed: 1 OOD median of (MSE, MAE) stats: [64.109985   7.2609158]
		Model Seed: 10 Seed: 1 ID likelihoods: -9.548959658753757
		Model Seed: 10 Seed: 1 OOD likelihoods: -9.44222931037036
		Model Seed: 10 Seed: 1 ID calibration errors: [0.3439505  0.25907364 0.20117096 0.16840133 0.14837918 0.14002005
 0.13495464 0.12776294 0.11964795 0.11621076 0.11849377 0.12656903]
		Model Seed: 10 Seed: 1 OOD calibration errors: [0.28762027 0.2075885  0.15178193 0.11666989 0.09041626 0.07479252
 0.0621692  0.05226228 0.04474306 0.04044675 0.04071305 0.04402003]
	Train: 72134 (45.80%)
	Val: 35684 (22.66%)
	Test: 38037 (24.15%)
	Test OOD: 11628 (7.38%)
	No scaling applied
		Model Seed: 10 Seed: 2 ID mean of (MSE, MAE): [134.19373     7.9612517]
		Model Seed: 10 Seed: 2 OOD mean of (MSE, MAE) stats: [107.03015    6.997271]
		Model Seed: 10 Seed: 2 ID median of (MSE, MAE): [58.723904  6.437544]
		Model Seed: 10 Seed: 2 OOD median of (MSE, MAE) stats: [40.99414  5.46575]
		Model Seed: 10 Seed: 2 ID likelihoods: -9.368580938386113
		Model Seed: 10 Seed: 2 OOD likelihoods: -9.25549332584845
		Model Seed: 10 Seed: 2 ID calibration errors: [0.53145076 0.37430043 0.22574302 0.13657398 0.10397687 0.10799422
 0.12648115 0.16134553 0.17855063 0.19057738 0.19257173 0.18018502]
		Model Seed: 10 Seed: 2 OOD calibration errors: [0.4617369  0.33062904 0.19641906 0.10001237 0.05232554 0.03428314
 0.03264639 0.04237709 0.04434375 0.04583349 0.0450685  0.03686549]
	Model Seed: 10 ID mean of (MSE, MAE): [163.34187    9.177109]
	Model Seed: 10 OOD mean of (MSE, MAE): [131.25995   8.05964]
	Model Seed: 10 ID median of (MSE, MAE): [75.36425   7.637562]
	Model Seed: 10 OOD median of (MSE, MAE): [52.552063   6.3633327]
	Model Seed: 10 ID likelihoods: -9.458770298569934
	Model Seed: 10 OOD likelihoods: -9.348861318109405
	Model Seed: 10 ID calibration errors: [0.43770063 0.31668704 0.21345699 0.15248766 0.12617803 0.12400713
 0.13071789 0.14455424 0.14909929 0.15339407 0.15553275 0.15337703]
	Model Seed: 10 OOD calibration errors: [0.37467858 0.26910877 0.1741005  0.10834113 0.0713709  0.05453783
 0.04740779 0.04731969 0.0445434  0.04314012 0.04289077 0.04044276]
	Train: 72152 (45.77%)
	Val: 35929 (22.79%)
	Test: 38024 (24.12%)
	Test OOD: 11522 (7.31%)
	No scaling applied
		Model Seed: 11 Seed: 1 ID mean of (MSE, MAE): [198.63425   10.728363]
		Model Seed: 11 Seed: 1 OOD mean of (MSE, MAE) stats: [161.99539    9.429786]
		Model Seed: 11 Seed: 1 ID median of (MSE, MAE): [100.11395    9.270832]
		Model Seed: 11 Seed: 1 OOD median of (MSE, MAE) stats: [69.81647  7.6368 ]
		Model Seed: 11 Seed: 1 ID likelihoods: -9.564673503555248
		Model Seed: 11 Seed: 1 OOD likelihoods: -9.46272313726884
		Model Seed: 11 Seed: 1 ID calibration errors: [0.46503126 0.34680736 0.26455138 0.21731327 0.1901073  0.17722827
 0.16822779 0.15978469 0.15304394 0.14849737 0.14960121 0.15856136]
		Model Seed: 11 Seed: 1 OOD calibration errors: [0.39138889 0.28890689 0.21022907 0.15929783 0.12622896 0.10417071
 0.08938194 0.07603258 0.06720239 0.06333633 0.06333863 0.06550941]
	Train: 72134 (45.80%)
	Val: 35684 (22.66%)
	Test: 38037 (24.15%)
	Test OOD: 11628 (7.38%)
	No scaling applied
		Model Seed: 11 Seed: 2 ID mean of (MSE, MAE): [133.47061     7.8479595]
		Model Seed: 11 Seed: 2 OOD mean of (MSE, MAE) stats: [108.41194     7.0683336]
		Model Seed: 11 Seed: 2 ID median of (MSE, MAE): [54.211323  6.197153]
		Model Seed: 11 Seed: 2 OOD median of (MSE, MAE) stats: [40.26117    5.4426756]
		Model Seed: 11 Seed: 2 ID likelihoods: -9.365878790858723
		Model Seed: 11 Seed: 2 OOD likelihoods: -9.26190793702034
		Model Seed: 11 Seed: 2 ID calibration errors: [0.5405027  0.372873   0.22044257 0.11963295 0.07157934 0.0627928
 0.07209956 0.09767987 0.11684042 0.13115876 0.14068615 0.13770793]
		Model Seed: 11 Seed: 2 OOD calibration errors: [0.5181231  0.37337201 0.22462764 0.11936955 0.05334896 0.02317673
 0.01212414 0.01252805 0.01532378 0.01610611 0.01732303 0.01649025]
	Model Seed: 11 ID mean of (MSE, MAE): [166.05243    9.288161]
	Model Seed: 11 OOD mean of (MSE, MAE): [135.20367   8.24906]
	Model Seed: 11 ID median of (MSE, MAE): [77.162636   7.7339926]
	Model Seed: 11 OOD median of (MSE, MAE): [55.03882    6.5397377]
	Model Seed: 11 ID likelihoods: -9.465276147206986
	Model Seed: 11 OOD likelihoods: -9.362315537144589
	Model Seed: 11 ID calibration errors: [0.50276698 0.35984018 0.24249698 0.16847311 0.13084332 0.12001053
 0.12016368 0.12873228 0.13494218 0.13982806 0.14514368 0.14813465]
	Model Seed: 11 OOD calibration errors: [0.454756   0.33113945 0.21742835 0.13933369 0.08978896 0.06367372
 0.05075304 0.04428032 0.04126308 0.03972122 0.04033083 0.04099983]
	Train: 72152 (45.77%)
	Val: 35929 (22.79%)
	Test: 38024 (24.12%)
	Test OOD: 11522 (7.31%)
	No scaling applied
		Model Seed: 12 Seed: 1 ID mean of (MSE, MAE): [196.0751  10.5208]
		Model Seed: 12 Seed: 1 OOD mean of (MSE, MAE) stats: [159.527      9.292994]
		Model Seed: 12 Seed: 1 ID median of (MSE, MAE): [93.72562   8.924984]
		Model Seed: 12 Seed: 1 OOD median of (MSE, MAE) stats: [67.71083    7.4534855]
		Model Seed: 12 Seed: 1 ID likelihoods: -9.558186444580743
		Model Seed: 12 Seed: 1 OOD likelihoods: -9.455045391029595
		Model Seed: 12 Seed: 1 ID calibration errors: [0.37219575 0.28281284 0.21715994 0.17596946 0.15232592 0.14664564
 0.14042015 0.14172296 0.13746874 0.13671027 0.14168123 0.1524282 ]
		Model Seed: 12 Seed: 1 OOD calibration errors: [0.34617424 0.25587515 0.18405407 0.13911675 0.10939759 0.09395271
 0.08357949 0.0765586  0.06937933 0.06646319 0.06647983 0.07208044]
	Train: 72134 (45.80%)
	Val: 35684 (22.66%)
	Test: 38037 (24.15%)
	Test OOD: 11628 (7.38%)
	No scaling applied
		Model Seed: 12 Seed: 2 ID mean of (MSE, MAE): [134.92552   8.01103]
		Model Seed: 12 Seed: 2 OOD mean of (MSE, MAE) stats: [106.94992    7.008677]
		Model Seed: 12 Seed: 2 ID median of (MSE, MAE): [60.568695   6.5387244]
		Model Seed: 12 Seed: 2 OOD median of (MSE, MAE) stats: [42.244568  5.515341]
		Model Seed: 12 Seed: 2 ID likelihoods: -9.371299435854988
		Model Seed: 12 Seed: 2 OOD likelihoods: -9.255119308037747
		Model Seed: 12 Seed: 2 ID calibration errors: [0.52077644 0.37228628 0.22326536 0.13210284 0.0985836  0.1029333
 0.12505745 0.15930058 0.17985999 0.19610486 0.20398969 0.19524071]
		Model Seed: 12 Seed: 2 OOD calibration errors: [0.4840195  0.3467935  0.20699423 0.10531205 0.05102308 0.0315821
 0.02782487 0.03618994 0.03996539 0.04284466 0.0425655  0.03696575]
	Model Seed: 12 ID mean of (MSE, MAE): [165.5003     9.265915]
	Model Seed: 12 OOD mean of (MSE, MAE): [133.23846    8.150835]
	Model Seed: 12 ID median of (MSE, MAE): [77.147156   7.7318544]
	Model Seed: 12 OOD median of (MSE, MAE): [54.9777    6.484413]
	Model Seed: 12 ID likelihoods: -9.464742940217866
	Model Seed: 12 OOD likelihoods: -9.35508234953367
	Model Seed: 12 ID calibration errors: [0.4464861  0.32754956 0.22021265 0.15403615 0.12545476 0.12478947
 0.1327388  0.15051177 0.15866436 0.16640756 0.17283546 0.17383446]
	Model Seed: 12 OOD calibration errors: [0.41509687 0.30133433 0.19552415 0.1222144  0.08021033 0.06276741
 0.05570218 0.05637427 0.05467236 0.05465392 0.05452266 0.05452309]
	Train: 72152 (45.77%)
	Val: 35929 (22.79%)
	Test: 38024 (24.12%)
	Test OOD: 11522 (7.31%)
	No scaling applied
		Model Seed: 13 Seed: 1 ID mean of (MSE, MAE): [228.6601    11.887224]
		Model Seed: 13 Seed: 1 OOD mean of (MSE, MAE) stats: [174.34537   10.071154]
		Model Seed: 13 Seed: 1 ID median of (MSE, MAE): [125.212524  10.537977]
		Model Seed: 13 Seed: 1 OOD median of (MSE, MAE) stats: [83.272484   8.4543295]
		Model Seed: 13 Seed: 1 ID likelihoods: -9.635056700000684
		Model Seed: 13 Seed: 1 OOD likelihoods: -9.499457590573932
		Model Seed: 13 Seed: 1 ID calibration errors: [0.75941311 0.59831133 0.46239216 0.3604073  0.29421064 0.24416987
 0.20161724 0.17615651 0.16426904 0.1623339  0.16799938 0.16751052]
		Model Seed: 13 Seed: 1 OOD calibration errors: [0.68961426 0.5348253  0.40415294 0.29997167 0.22800241 0.16997727
 0.12695949 0.10038005 0.08515023 0.07798715 0.07840693 0.07519778]
	Train: 72134 (45.80%)
	Val: 35684 (22.66%)
	Test: 38037 (24.15%)
	Test OOD: 11628 (7.38%)
	No scaling applied
		Model Seed: 13 Seed: 2 ID mean of (MSE, MAE): [132.09988     7.8022356]
		Model Seed: 13 Seed: 2 OOD mean of (MSE, MAE) stats: [105.4081     6.881964]
		Model Seed: 13 Seed: 2 ID median of (MSE, MAE): [53.466     6.158549]
		Model Seed: 13 Seed: 2 OOD median of (MSE, MAE) stats: [38.701168  5.281719]
		Model Seed: 13 Seed: 2 ID likelihoods: -9.360717122485237
		Model Seed: 13 Seed: 2 OOD likelihoods: -9.247857786874885
		Model Seed: 13 Seed: 2 ID calibration errors: [0.51527066 0.36175544 0.21649154 0.12693453 0.08434418 0.08000299
 0.09047504 0.11715357 0.13263168 0.1456893  0.15374734 0.14843138]
		Model Seed: 13 Seed: 2 OOD calibration errors: [0.4704043  0.34416847 0.20608474 0.11101302 0.05573094 0.03387286
 0.02765976 0.03231453 0.03465876 0.0356665  0.03621034 0.03026228]
	Model Seed: 13 ID mean of (MSE, MAE): [180.37999   9.84473]
	Model Seed: 13 OOD mean of (MSE, MAE): [139.87674    8.476559]
	Model Seed: 13 ID median of (MSE, MAE): [89.339264  8.348263]
	Model Seed: 13 OOD median of (MSE, MAE): [60.986824   6.8680243]
	Model Seed: 13 ID likelihoods: -9.497886911242961
	Model Seed: 13 OOD likelihoods: -9.373657688724409
	Model Seed: 13 ID calibration errors: [0.63734189 0.48003339 0.33944185 0.24367091 0.18927741 0.16208643
 0.14604614 0.14665504 0.14845036 0.1540116  0.16087336 0.15797095]
	Model Seed: 13 OOD calibration errors: [0.58000928 0.43949689 0.30511884 0.20549235 0.14186667 0.10192507
 0.07730963 0.06634729 0.05990449 0.05682682 0.05730864 0.05273003]
	Train: 72152 (45.77%)
	Val: 35929 (22.79%)
	Test: 38024 (24.12%)
	Test OOD: 11522 (7.31%)
	No scaling applied
		Model Seed: 14 Seed: 1 ID mean of (MSE, MAE): [209.48798   11.225819]
		Model Seed: 14 Seed: 1 OOD mean of (MSE, MAE) stats: [162.27429    9.457804]
		Model Seed: 14 Seed: 1 ID median of (MSE, MAE): [113.565994   9.861436]
		Model Seed: 14 Seed: 1 OOD median of (MSE, MAE) stats: [70.40706    7.6684456]
		Model Seed: 14 Seed: 1 ID likelihoods: -9.59127174176124
		Model Seed: 14 Seed: 1 OOD likelihoods: -9.46358289426141
		Model Seed: 14 Seed: 1 ID calibration errors: [0.52460318 0.40307692 0.31440685 0.25991432 0.22761584 0.21398413
 0.20390522 0.19533285 0.18792555 0.18122204 0.18223802 0.18701548]
		Model Seed: 14 Seed: 1 OOD calibration errors: [0.38910915 0.28982928 0.21525766 0.16813984 0.13383547 0.11665493
 0.10628607 0.09936748 0.09288483 0.08927344 0.09136752 0.09284418]
	Train: 72134 (45.80%)
	Val: 35684 (22.66%)
	Test: 38037 (24.15%)
	Test OOD: 11628 (7.38%)
	No scaling applied
		Model Seed: 14 Seed: 2 ID mean of (MSE, MAE): [136.90019    8.170759]
		Model Seed: 14 Seed: 2 OOD mean of (MSE, MAE) stats: [107.94848    7.089377]
		Model Seed: 14 Seed: 2 ID median of (MSE, MAE): [63.661865  6.795666]
		Model Seed: 14 Seed: 2 OOD median of (MSE, MAE) stats: [43.33328   5.586907]
		Model Seed: 14 Seed: 2 ID likelihoods: -9.378565883324894
		Model Seed: 14 Seed: 2 OOD likelihoods: -9.25976517659224
		Model Seed: 14 Seed: 2 ID calibration errors: [0.50499379 0.36537019 0.22610055 0.15695412 0.13071465 0.13915055
 0.15710076 0.187673   0.20479339 0.21207634 0.20910452 0.19704075]
		Model Seed: 14 Seed: 2 OOD calibration errors: [0.44789809 0.31476469 0.1825057  0.09520349 0.04884533 0.03357922
 0.03043104 0.03666322 0.0399061  0.03926857 0.03422708 0.028355  ]
	Model Seed: 14 ID mean of (MSE, MAE): [173.19409    9.698289]
	Model Seed: 14 OOD mean of (MSE, MAE): [135.11139   8.27359]
	Model Seed: 14 ID median of (MSE, MAE): [88.61393   8.328551]
	Model Seed: 14 OOD median of (MSE, MAE): [56.87017   6.627676]
	Model Seed: 14 ID likelihoods: -9.484918812543068
	Model Seed: 14 OOD likelihoods: -9.361674035426825
	Model Seed: 14 ID calibration errors: [0.51479849 0.38422355 0.2702537  0.20843422 0.17916524 0.17656734
 0.18050299 0.19150293 0.19635947 0.19664919 0.19567127 0.19202812]
	Model Seed: 14 OOD calibration errors: [0.41850362 0.30229699 0.19888168 0.13167166 0.0913404  0.07511707
 0.06835855 0.06801535 0.06639547 0.064271   0.0627973  0.06059959]
	Train: 72152 (45.77%)
	Val: 35929 (22.79%)
	Test: 38024 (24.12%)
	Test OOD: 11522 (7.31%)
	No scaling applied
		Model Seed: 15 Seed: 1 ID mean of (MSE, MAE): [202.30711   10.746752]
		Model Seed: 15 Seed: 1 OOD mean of (MSE, MAE) stats: [160.5796     9.378623]
		Model Seed: 15 Seed: 1 ID median of (MSE, MAE): [100.85415    9.259257]
		Model Seed: 15 Seed: 1 OOD median of (MSE, MAE) stats: [70.744255   7.6446495]
		Model Seed: 15 Seed: 1 ID likelihoods: -9.57383225089244
		Model Seed: 15 Seed: 1 OOD likelihoods: -9.458334764307283
		Model Seed: 15 Seed: 1 ID calibration errors: [0.3476168  0.27325475 0.2152278  0.17978266 0.16085138 0.15389261
 0.15348628 0.15255484 0.14828037 0.15004871 0.15387494 0.16039605]
		Model Seed: 15 Seed: 1 OOD calibration errors: [0.34919612 0.26191271 0.19099718 0.14599971 0.11637539 0.09775186
 0.0874149  0.07952144 0.07053237 0.06830521 0.06999187 0.0740409 ]
	Train: 72134 (45.80%)
	Val: 35684 (22.66%)
	Test: 38037 (24.15%)
	Test OOD: 11628 (7.38%)
	No scaling applied
		Model Seed: 15 Seed: 2 ID mean of (MSE, MAE): [161.26984   9.3847 ]
		Model Seed: 15 Seed: 2 OOD mean of (MSE, MAE) stats: [128.3177     8.219061]
		Model Seed: 15 Seed: 2 ID median of (MSE, MAE): [86.45489   8.256083]
		Model Seed: 15 Seed: 2 OOD median of (MSE, MAE) stats: [63.027977  6.96762 ]
		Model Seed: 15 Seed: 2 ID likelihoods: -9.460478346714325
		Model Seed: 15 Seed: 2 OOD likelihoods: -9.346192799123305
		Model Seed: 15 Seed: 2 ID calibration errors: [0.46143159 0.40298756 0.31974996 0.25829386 0.24151126 0.25221044
 0.27778041 0.31033646 0.33570535 0.36103138 0.36767464 0.36878702]
		Model Seed: 15 Seed: 2 OOD calibration errors: [0.46341375 0.38946575 0.29767404 0.22859538 0.20383499 0.20428461
 0.21402073 0.23381798 0.24691395 0.26051413 0.25681248 0.25104846]
	Model Seed: 15 ID mean of (MSE, MAE): [181.78848   10.065725]
	Model Seed: 15 OOD mean of (MSE, MAE): [144.44865    8.798841]
	Model Seed: 15 ID median of (MSE, MAE): [93.65452   8.757669]
	Model Seed: 15 OOD median of (MSE, MAE): [66.886116   7.3061347]
	Model Seed: 15 ID likelihoods: -9.517155298803383
	Model Seed: 15 OOD likelihoods: -9.402263781715295
	Model Seed: 15 ID calibration errors: [0.40452419 0.33812115 0.26748888 0.21903826 0.20118132 0.20305153
 0.21563334 0.23144565 0.24199286 0.25554004 0.26077479 0.26459154]
	Model Seed: 15 OOD calibration errors: [0.40630494 0.32568923 0.24433561 0.18729755 0.16010519 0.15101824
 0.15071781 0.15666971 0.15872316 0.16440967 0.16340218 0.16254468]
	Train: 72152 (45.77%)
	Val: 35929 (22.79%)
	Test: 38024 (24.12%)
	Test OOD: 11522 (7.31%)
	No scaling applied
		Model Seed: 16 Seed: 1 ID mean of (MSE, MAE): [205.03236   10.776383]
		Model Seed: 16 Seed: 1 OOD mean of (MSE, MAE) stats: [159.7062    9.29658]
		Model Seed: 16 Seed: 1 ID median of (MSE, MAE): [100.629684   9.186196]
		Model Seed: 16 Seed: 1 OOD median of (MSE, MAE) stats: [68.73529    7.5064316]
		Model Seed: 16 Seed: 1 ID likelihoods: -9.58052129933203
		Model Seed: 16 Seed: 1 OOD likelihoods: -9.455605586954084
		Model Seed: 16 Seed: 1 ID calibration errors: [0.26535949 0.20215875 0.15703732 0.13398392 0.12471974 0.12452361
 0.12861008 0.13276471 0.13555437 0.14082819 0.14995126 0.16227144]
		Model Seed: 16 Seed: 1 OOD calibration errors: [0.26603871 0.19093857 0.13801303 0.10481952 0.0831275  0.06991766
 0.0609038  0.05688408 0.05200595 0.05039546 0.05089427 0.05328871]
	Train: 72134 (45.80%)
	Val: 35684 (22.66%)
	Test: 38037 (24.15%)
	Test OOD: 11628 (7.38%)
	No scaling applied
		Model Seed: 16 Seed: 2 ID mean of (MSE, MAE): [134.00017    7.930038]
		Model Seed: 16 Seed: 2 OOD mean of (MSE, MAE) stats: [105.32878     6.9505715]
		Model Seed: 16 Seed: 2 ID median of (MSE, MAE): [57.38825  6.39006]
		Model Seed: 16 Seed: 2 OOD median of (MSE, MAE) stats: [41.604713  5.48233 ]
		Model Seed: 16 Seed: 2 ID likelihoods: -9.367858490115905
		Model Seed: 16 Seed: 2 OOD likelihoods: -9.24748181419308
		Model Seed: 16 Seed: 2 ID calibration errors: [0.52793414 0.37567929 0.22745117 0.13875197 0.10341067 0.1032523
 0.11875415 0.14605567 0.15984019 0.16837514 0.17047996 0.16190048]
		Model Seed: 16 Seed: 2 OOD calibration errors: [0.48284295 0.34011626 0.20049851 0.10540659 0.05670131 0.04094753
 0.03908656 0.04753476 0.04785377 0.04848791 0.0453705  0.03974995]
	Model Seed: 16 ID mean of (MSE, MAE): [169.51627   9.35321]
	Model Seed: 16 OOD mean of (MSE, MAE): [132.51749    8.123576]
	Model Seed: 16 ID median of (MSE, MAE): [79.008965  7.788128]
	Model Seed: 16 OOD median of (MSE, MAE): [55.170002  6.494381]
	Model Seed: 16 ID likelihoods: -9.474189894723967
	Model Seed: 16 OOD likelihoods: -9.351543700573583
	Model Seed: 16 ID calibration errors: [0.39664682 0.28891902 0.19224425 0.13636795 0.1140652  0.11388796
 0.12368211 0.13941019 0.14769728 0.15460167 0.16021561 0.16208596]
	Model Seed: 16 OOD calibration errors: [0.37444083 0.26552742 0.16925577 0.10511305 0.0699144  0.0554326
 0.04999518 0.05220942 0.04992986 0.04944169 0.04813239 0.04651933]
	Train: 72152 (45.77%)
	Val: 35929 (22.79%)
	Test: 38024 (24.12%)
	Test OOD: 11522 (7.31%)
	No scaling applied
		Model Seed: 17 Seed: 1 ID mean of (MSE, MAE): [204.5792    10.926685]
		Model Seed: 17 Seed: 1 OOD mean of (MSE, MAE) stats: [162.12177    9.427905]
		Model Seed: 17 Seed: 1 ID median of (MSE, MAE): [104.148895   9.454211]
		Model Seed: 17 Seed: 1 OOD median of (MSE, MAE) stats: [69.116394  7.600137]
		Model Seed: 17 Seed: 1 ID likelihoods: -9.579416370714998
		Model Seed: 17 Seed: 1 OOD likelihoods: -9.463111154422833
		Model Seed: 17 Seed: 1 ID calibration errors: [0.45874877 0.35660085 0.27609149 0.23138073 0.20297765 0.18804074
 0.17675778 0.1708843  0.16337505 0.16167308 0.16350237 0.17501057]
		Model Seed: 17 Seed: 1 OOD calibration errors: [0.41201411 0.30371737 0.22159179 0.16757936 0.1319436  0.10812938
 0.09217541 0.08049314 0.07004794 0.06696681 0.06636605 0.07092304]
	Train: 72134 (45.80%)
	Val: 35684 (22.66%)
	Test: 38037 (24.15%)
	Test OOD: 11628 (7.38%)
	No scaling applied
		Model Seed: 17 Seed: 2 ID mean of (MSE, MAE): [136.7503     8.125794]
		Model Seed: 17 Seed: 2 OOD mean of (MSE, MAE) stats: [107.56565     7.0441833]
		Model Seed: 17 Seed: 2 ID median of (MSE, MAE): [61.05356   6.723778]
		Model Seed: 17 Seed: 2 OOD median of (MSE, MAE) stats: [42.98918   5.596685]
		Model Seed: 17 Seed: 2 ID likelihoods: -9.378017483368122
		Model Seed: 17 Seed: 2 OOD likelihoods: -9.257988862355818
		Model Seed: 17 Seed: 2 ID calibration errors: [0.51897868 0.37405537 0.23750968 0.16411076 0.14141907 0.14582534
 0.1595271  0.1840987  0.19291128 0.19846384 0.19548815 0.18136924]
		Model Seed: 17 Seed: 2 OOD calibration errors: [0.46427358 0.32384089 0.19100776 0.10717013 0.06545759 0.05190093
 0.04890812 0.05620075 0.05448491 0.05187569 0.04742989 0.03971412]
	Model Seed: 17 ID mean of (MSE, MAE): [170.66475    9.526239]
	Model Seed: 17 OOD mean of (MSE, MAE): [134.8437     8.236044]
	Model Seed: 17 ID median of (MSE, MAE): [82.60123   8.088995]
	Model Seed: 17 OOD median of (MSE, MAE): [56.052788  6.598411]
	Model Seed: 17 ID likelihoods: -9.47871692704156
	Model Seed: 17 OOD likelihoods: -9.360550008389325
	Model Seed: 17 ID calibration errors: [0.48886373 0.36532811 0.25680058 0.19774575 0.17219836 0.16693304
 0.16814244 0.1774915  0.17814316 0.18006846 0.17949526 0.17818991]
	Model Seed: 17 OOD calibration errors: [0.43814384 0.31377913 0.20629977 0.13737474 0.0987006  0.08001516
 0.07054177 0.06834694 0.06226643 0.05942125 0.05689797 0.05531858]
	Train: 72152 (45.77%)
	Val: 35929 (22.79%)
	Test: 38024 (24.12%)
	Test OOD: 11522 (7.31%)
	No scaling applied
		Model Seed: 18 Seed: 1 ID mean of (MSE, MAE): [218.23198   11.510391]
		Model Seed: 18 Seed: 1 OOD mean of (MSE, MAE) stats: [169.80305    9.882501]
		Model Seed: 18 Seed: 1 ID median of (MSE, MAE): [117.24968   10.150982]
		Model Seed: 18 Seed: 1 OOD median of (MSE, MAE) stats: [79.76619   8.251141]
		Model Seed: 18 Seed: 1 ID likelihoods: -9.611718858324162
		Model Seed: 18 Seed: 1 OOD likelihoods: -9.486258704548973
		Model Seed: 18 Seed: 1 ID calibration errors: [0.67805249 0.53293037 0.41596785 0.3266287  0.27003171 0.22667111
 0.19092136 0.16994599 0.15911459 0.15469203 0.16178081 0.16123428]
		Model Seed: 18 Seed: 1 OOD calibration errors: [0.60601471 0.47045862 0.36134769 0.26965309 0.21263808 0.16764147
 0.13103009 0.10892091 0.09577625 0.08904119 0.09257328 0.09009791]
	Train: 72134 (45.80%)
	Val: 35684 (22.66%)
	Test: 38037 (24.15%)
	Test OOD: 11628 (7.38%)
	No scaling applied
		Model Seed: 18 Seed: 2 ID mean of (MSE, MAE): [132.59212    7.922399]
		Model Seed: 18 Seed: 2 OOD mean of (MSE, MAE) stats: [104.832115   6.902271]
		Model Seed: 18 Seed: 2 ID median of (MSE, MAE): [56.245647  6.399236]
		Model Seed: 18 Seed: 2 OOD median of (MSE, MAE) stats: [39.60743   5.355174]
		Model Seed: 18 Seed: 2 ID likelihoods: -9.362578038111803
		Model Seed: 18 Seed: 2 OOD likelihoods: -9.245118726088922
		Model Seed: 18 Seed: 2 ID calibration errors: [0.49909057 0.35429063 0.21301359 0.13745697 0.10822864 0.11350251
 0.12186993 0.1437762  0.16046844 0.15633183 0.1631959  0.14154933]
		Model Seed: 18 Seed: 2 OOD calibration errors: [0.48379454 0.330931   0.19133511 0.10148854 0.05855918 0.04537542
 0.040737   0.04475761 0.04650799 0.04042481 0.04080574 0.030399  ]
	Model Seed: 18 ID mean of (MSE, MAE): [175.41205    9.716395]
	Model Seed: 18 OOD mean of (MSE, MAE): [137.31758     8.3923855]
	Model Seed: 18 ID median of (MSE, MAE): [86.747665  8.275109]
	Model Seed: 18 OOD median of (MSE, MAE): [59.68681    6.8031573]
	Model Seed: 18 ID likelihoods: -9.487148448217983
	Model Seed: 18 OOD likelihoods: -9.365688715318948
	Model Seed: 18 ID calibration errors: [0.58857153 0.4436105  0.31449072 0.23204283 0.18913018 0.17008681
 0.15639564 0.15686109 0.15979151 0.15551193 0.16248836 0.15139181]
	Model Seed: 18 OOD calibration errors: [0.54490463 0.40069481 0.2763414  0.18557082 0.13559863 0.10650844
 0.08588355 0.07683926 0.07114212 0.064733   0.06668951 0.06024845]
	Train: 72152 (45.77%)
	Val: 35929 (22.79%)
	Test: 38024 (24.12%)
	Test OOD: 11522 (7.31%)
	No scaling applied
		Model Seed: 19 Seed: 1 ID mean of (MSE, MAE): [196.87393   10.474543]
		Model Seed: 19 Seed: 1 OOD mean of (MSE, MAE) stats: [156.81288    9.148678]
		Model Seed: 19 Seed: 1 ID median of (MSE, MAE): [92.8745    8.859734]
		Model Seed: 19 Seed: 1 OOD median of (MSE, MAE) stats: [64.89607   7.302455]
		Model Seed: 19 Seed: 1 ID likelihoods: -9.560221139119488
		Model Seed: 19 Seed: 1 OOD likelihoods: -9.446464723714977
		Model Seed: 19 Seed: 1 ID calibration errors: [0.29278827 0.22013754 0.167159   0.13905299 0.12277589 0.12070921
 0.12034322 0.12058607 0.11874674 0.120818   0.12540379 0.13506953]
		Model Seed: 19 Seed: 1 OOD calibration errors: [0.27709266 0.20038723 0.14390528 0.10836959 0.08484721 0.07205983
 0.06493322 0.05904528 0.05458174 0.05429948 0.05592698 0.06096151]
	Train: 72134 (45.80%)
	Val: 35684 (22.66%)
	Test: 38037 (24.15%)
	Test OOD: 11628 (7.38%)
	No scaling applied
		Model Seed: 19 Seed: 2 ID mean of (MSE, MAE): [136.48369    8.019884]
		Model Seed: 19 Seed: 2 OOD mean of (MSE, MAE) stats: [108.090485   7.05645 ]
		Model Seed: 19 Seed: 2 ID median of (MSE, MAE): [58.941936   6.4551277]
		Model Seed: 19 Seed: 2 OOD median of (MSE, MAE) stats: [42.223774   5.5224905]
		Model Seed: 19 Seed: 2 ID likelihoods: -9.3770428761162
		Model Seed: 19 Seed: 2 OOD likelihoods: -9.260423693361227
		Model Seed: 19 Seed: 2 ID calibration errors: [0.48919065 0.36640555 0.22664328 0.12888794 0.08617794 0.08611347
 0.10687433 0.14616136 0.1734624  0.19366492 0.20633674 0.19969352]
		Model Seed: 19 Seed: 2 OOD calibration errors: [0.50942057 0.37536838 0.2295174  0.1181739  0.05341349 0.02449454
 0.01612732 0.02118138 0.02531225 0.02935257 0.03117186 0.02763432]
	Model Seed: 19 ID mean of (MSE, MAE): [166.6788     9.247213]
	Model Seed: 19 OOD mean of (MSE, MAE): [132.45169    8.102564]
	Model Seed: 19 ID median of (MSE, MAE): [75.90822    7.6574306]
	Model Seed: 19 OOD median of (MSE, MAE): [53.55992    6.4124727]
	Model Seed: 19 ID likelihoods: -9.468632007617844
	Model Seed: 19 OOD likelihoods: -9.353444208538102
	Model Seed: 19 ID calibration errors: [0.39098946 0.29327154 0.19690114 0.13397046 0.10447691 0.10341134
 0.11360877 0.13337372 0.14610457 0.15724146 0.16587026 0.16738153]
	Model Seed: 19 OOD calibration errors: [0.39325661 0.28787781 0.18671134 0.11327174 0.06913035 0.04827719
 0.04053027 0.04011333 0.039947   0.04182603 0.04354942 0.04429791]
ID mean of (MSE, MAE): [171.25291442871094, 9.518298149108887] +- [6.019757270812988, 0.2849119305610657] +- [33.984299    1.40069371] 
OOD mean of (MSE, MAE): [135.62693786621094, 8.286310195922852] +- [3.799032211303711, 0.21075789630413055] +- [26.638598    1.16449368] 
ID median of (MSE, MAE): [82.5547866821289, 8.03475570678711] +- [6.247399806976318, 0.3620895743370056] +- [21.48317585  1.39956339] 
OOD median of (MSE, MAE): [57.178123474121094, 6.649774074554443] +- [4.053996562957764, 0.26590508222579956] +- [13.6793814   1.02810492] 
ID likelihoods: -9.479743768618555 +- 0.016852302792035968 +- 0.10064202808492428 
OOD likelihoods: -9.363508134347416 +- 0.014673986030770131 +- 0.09977319139781482 
ID calibration errors: [0.4808689806025718, 0.35975840479200605, 0.2513787728411926, 0.18462673050918393, 0.1531970735548506, 0.14648315822323174, 0.14876318077704148, 0.16005384015663598, 0.1661245053102994, 0.17132540402344715, 0.17589007939300655, 0.17489859309581635] +- [0.0786283518904993, 0.05909844434458048, 0.04619133902281432, 0.03844758958169576, 0.03440228666122598, 0.031492930520067845, 0.03030753033221008, 0.030049870961425005, 0.030373179339757875, 0.0318990838915585, 0.03119293657201646, 0.03254148211184964] +- [0.03009302 0.01224197 0.0177377  0.03465674 0.03620245 0.02710537
 0.01316119 0.00530425 0.01738187 0.02402197 0.0244374  0.01629195] 
OOD calibration errors: [0.4400095211427207, 0.32369448148752, 0.21739974165062503, 0.14356811311320855, 0.10080264343195411, 0.0799272715682621, 0.06971997781542692, 0.06765155770648792, 0.06487873763789911, 0.06384447169686204, 0.06365216714622354, 0.06182242633093964] +- [0.0661787113559264, 0.053010036480358555, 0.04239506481305397, 0.03435476364070066, 0.03142697817467074, 0.030120612060879657, 0.030293935843132454, 0.031771925411271884, 0.032863852389006305, 0.03459835562925732, 0.034277008028098056, 0.0342916331692389] +- [0.03858321 0.02325052 0.00473332 0.02439361 0.0308786  0.02757756
 0.02076338 0.01129503 0.00535167 0.00280703 0.00395367 0.00807396] 
