Optimization started at 2023-03-03 21:29:09.408189--------------------------------
Loading column definition...
Checking column definition...
Loading data...
Dropping columns / rows...
Checking for NA values...
Setting data types...
Dropping columns / rows...
Encoding data...
	Updated column definition:
		id: REAL_VALUED (ID)
		time: DATE (TIME)
		gl: REAL_VALUED (TARGET)
		Height: REAL_VALUED (STATIC_INPUT)
		Weight: REAL_VALUED (STATIC_INPUT)
		Gender: REAL_VALUED (STATIC_INPUT)
		Race: REAL_VALUED (STATIC_INPUT)
		EduLevel: REAL_VALUED (STATIC_INPUT)
		AnnualInc: REAL_VALUED (STATIC_INPUT)
		MaritalStatus: REAL_VALUED (STATIC_INPUT)
		DaysWkEx: REAL_VALUED (STATIC_INPUT)
		DaysWkDrinkAlc: REAL_VALUED (STATIC_INPUT)
		DaysMonBingeAlc: REAL_VALUED (STATIC_INPUT)
		T1DDiagAge: REAL_VALUED (STATIC_INPUT)
		NumHospDKA: REAL_VALUED (STATIC_INPUT)
		NumSHSinceT1DDiag: REAL_VALUED (STATIC_INPUT)
		InsDeliveryMethod: REAL_VALUED (STATIC_INPUT)
		UnitsInsTotal: REAL_VALUED (STATIC_INPUT)
		NumMeterCheckDay: REAL_VALUED (STATIC_INPUT)
		Aspirin: REAL_VALUED (STATIC_INPUT)
		Simvastatin: REAL_VALUED (STATIC_INPUT)
		Lisinopril: REAL_VALUED (STATIC_INPUT)
		Vitamin D: REAL_VALUED (STATIC_INPUT)
		Multivitamin preparation: REAL_VALUED (STATIC_INPUT)
		Omeprazole: REAL_VALUED (STATIC_INPUT)
		atorvastatin: REAL_VALUED (STATIC_INPUT)
		Synthroid: REAL_VALUED (STATIC_INPUT)
		vitamin D3: REAL_VALUED (STATIC_INPUT)
		Hypertension: REAL_VALUED (STATIC_INPUT)
		Hyperlipidemia: REAL_VALUED (STATIC_INPUT)
		Hypothyroidism: REAL_VALUED (STATIC_INPUT)
		Depression: REAL_VALUED (STATIC_INPUT)
		Coronary artery disease: REAL_VALUED (STATIC_INPUT)
		Diabetic peripheral neuropathy: REAL_VALUED (STATIC_INPUT)
		Dyslipidemia: REAL_VALUED (STATIC_INPUT)
		Chronic kidney disease: REAL_VALUED (STATIC_INPUT)
		Osteoporosis: REAL_VALUED (STATIC_INPUT)
		Proliferative diabetic retinopathy: REAL_VALUED (STATIC_INPUT)
		Hypercholesterolemia: REAL_VALUED (STATIC_INPUT)
		Erectile dysfunction: REAL_VALUED (STATIC_INPUT)
		Type I diabetes mellitus: REAL_VALUED (STATIC_INPUT)
		time_year: REAL_VALUED (KNOWN_INPUT)
		time_month: REAL_VALUED (KNOWN_INPUT)
		time_day: REAL_VALUED (KNOWN_INPUT)
		time_hour: REAL_VALUED (KNOWN_INPUT)
		time_minute: REAL_VALUED (KNOWN_INPUT)
Interpolating data...
	Dropped segments: 1416
	Extracted segments: 681
	Interpolated values: 140564
	Percent of values interpolated: 24.24%
Splitting data...
	Train: 357814 (68.58%)
	Val: 96960 (18.58%)
	Test: 125008 (23.96%)
Scaling data...
	No scaling applied
Data formatting complete.
--------------------------------
Current value: 0.06804655492305756, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 384, 'dropout': 0.14307633056735422, 'lr': 0.00018264357110226882, 'batch_size': 48, 'lr_epochs': 16, 'max_grad_norm': 0.4226448085822243}
Best value: 0.06804655492305756, Best params: {'in_len': 120, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 384, 'dropout': 0.14307633056735422, 'lr': 0.00018264357110226882, 'batch_size': 48, 'lr_epochs': 16, 'max_grad_norm': 0.4226448085822243}
Current value: 0.05785049870610237, Current params: {'in_len': 108, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 352, 'dropout': 0.1698966313987054, 'lr': 0.00030118257393612675, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8881655413053969}
Best value: 0.05785049870610237, Best params: {'in_len': 108, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 352, 'dropout': 0.1698966313987054, 'lr': 0.00030118257393612675, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8881655413053969}
Current value: 0.05688260868191719, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 4, 'dim_feedforward': 256, 'dropout': 0.0005803221175518791, 'lr': 0.00011858321245129909, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.47261131007685786}
Best value: 0.05688260868191719, Best params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 4, 'dim_feedforward': 256, 'dropout': 0.0005803221175518791, 'lr': 0.00011858321245129909, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.47261131007685786}
Current value: 0.05738823860883713, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 96, 'dropout': 0.09260244618843383, 'lr': 0.0009096592934749264, 'batch_size': 32, 'lr_epochs': 20, 'max_grad_norm': 0.6682643426121675}
Best value: 0.05688260868191719, Best params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 4, 'dim_feedforward': 256, 'dropout': 0.0005803221175518791, 'lr': 0.00011858321245129909, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.47261131007685786}
Current value: 0.060154009610414505, Current params: {'in_len': 132, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 3, 'num_decoder_layers': 1, 'dim_feedforward': 192, 'dropout': 0.051982448234579696, 'lr': 0.0005361870742818693, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.6278947517917648}
Best value: 0.05688260868191719, Best params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 4, 'dim_feedforward': 256, 'dropout': 0.0005803221175518791, 'lr': 0.00011858321245129909, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.47261131007685786}
Current value: 0.006378677673637867, Current params: {'in_len': 120, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 2, 'dim_feedforward': 512, 'dropout': 0.09955300593806692, 'lr': 0.00044147339719128177, 'batch_size': 32, 'lr_epochs': 6, 'max_grad_norm': 0.5588038573537674}
Best value: 0.05688260868191719, Best params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 4, 'dim_feedforward': 256, 'dropout': 0.0005803221175518791, 'lr': 0.00011858321245129909, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.47261131007685786}
Current value: 0.010338563472032547, Current params: {'in_len': 96, 'max_samples_per_ts': 150, 'd_model': 128, 'n_heads': 2, 'num_encoder_layers': 1, 'num_decoder_layers': 2, 'dim_feedforward': 160, 'dropout': 0.18538581745976893, 'lr': 0.0008405990751708585, 'batch_size': 64, 'lr_epochs': 16, 'max_grad_norm': 0.369489730865478}
Best value: 0.05688260868191719, Best params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 4, 'dim_feedforward': 256, 'dropout': 0.0005803221175518791, 'lr': 0.00011858321245129909, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.47261131007685786}
Current value: 0.0061470018699765205, Current params: {'in_len': 108, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 4, 'dim_feedforward': 352, 'dropout': 0.09613985321729127, 'lr': 0.0007506910544518274, 'batch_size': 64, 'lr_epochs': 12, 'max_grad_norm': 0.18506067985567637}
Best value: 0.05688260868191719, Best params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 4, 'dim_feedforward': 256, 'dropout': 0.0005803221175518791, 'lr': 0.00011858321245129909, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.47261131007685786}
Current value: 0.006998015101999044, Current params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 128, 'n_heads': 2, 'num_encoder_layers': 2, 'num_decoder_layers': 1, 'dim_feedforward': 256, 'dropout': 0.10591508958631204, 'lr': 0.0006935700752525353, 'batch_size': 64, 'lr_epochs': 10, 'max_grad_norm': 0.6662165728130834}
Best value: 0.05688260868191719, Best params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 4, 'dim_feedforward': 256, 'dropout': 0.0005803221175518791, 'lr': 0.00011858321245129909, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.47261131007685786}
Current value: 0.005769536830484867, Current params: {'in_len': 96, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 1, 'dim_feedforward': 96, 'dropout': 0.053337320290630076, 'lr': 0.0002377036884464411, 'batch_size': 64, 'lr_epochs': 14, 'max_grad_norm': 0.18017085517587725}
Best value: 0.05688260868191719, Best params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 4, 'dim_feedforward': 256, 'dropout': 0.0005803221175518791, 'lr': 0.00011858321245129909, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.47261131007685786}
Current value: 0.006633168552070856, Current params: {'in_len': 180, 'max_samples_per_ts': 100, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 4, 'dim_feedforward': 32, 'dropout': 0.004935186820782168, 'lr': 0.00010378003633434725, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.9528791325968679}
Best value: 0.05688260868191719, Best params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 4, 'dim_feedforward': 256, 'dropout': 0.0005803221175518791, 'lr': 0.00011858321245129909, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.47261131007685786}
Current value: 0.06441760063171387, Current params: {'in_len': 180, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 32, 'dropout': 0.0006531974808871716, 'lr': 0.0009753570291801553, 'batch_size': 32, 'lr_epochs': 20, 'max_grad_norm': 0.7457803917006464}
Best value: 0.05688260868191719, Best params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 4, 'dim_feedforward': 256, 'dropout': 0.0005803221175518791, 'lr': 0.00011858321245129909, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.47261131007685786}
Current value: 0.06836450845003128, Current params: {'in_len': 156, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 3, 'dim_feedforward': 224, 'dropout': 0.044927828026855625, 'lr': 0.0009937169185633137, 'batch_size': 48, 'lr_epochs': 20, 'max_grad_norm': 0.36035320551473693}
Best value: 0.05688260868191719, Best params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 4, 'dim_feedforward': 256, 'dropout': 0.0005803221175518791, 'lr': 0.00011858321245129909, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.47261131007685786}
Current value: 0.006878470070660114, Current params: {'in_len': 96, 'max_samples_per_ts': 100, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 2, 'dim_feedforward': 128, 'dropout': 0.13312651199334022, 'lr': 0.0003854969134354444, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.7859988111780534}
Best value: 0.05688260868191719, Best params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 4, 'dim_feedforward': 256, 'dropout': 0.0005803221175518791, 'lr': 0.00011858321245129909, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.47261131007685786}
Current value: 0.0660032406449318, Current params: {'in_len': 156, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 3, 'num_decoder_layers': 4, 'dim_feedforward': 288, 'dropout': 0.023344279134742504, 'lr': 0.0006104512829283845, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.46997716193164535}
Best value: 0.05688260868191719, Best params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 4, 'dim_feedforward': 256, 'dropout': 0.0005803221175518791, 'lr': 0.00011858321245129909, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.47261131007685786}
Current value: 0.06333687156438828, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.06896132648352238, 'lr': 0.0008373451336250437, 'batch_size': 48, 'lr_epochs': 18, 'max_grad_norm': 0.5094295452932261}
Best value: 0.05688260868191719, Best params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 4, 'dim_feedforward': 256, 'dropout': 0.0005803221175518791, 'lr': 0.00011858321245129909, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.47261131007685786}
Current value: 0.006254589185118675, Current params: {'in_len': 108, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 288, 'dropout': 0.0799092359377953, 'lr': 0.0005211734002087468, 'batch_size': 32, 'lr_epochs': 12, 'max_grad_norm': 0.2938309891948364}
Best value: 0.05688260868191719, Best params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 4, 'dim_feedforward': 256, 'dropout': 0.0005803221175518791, 'lr': 0.00011858321245129909, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.47261131007685786}
Current value: 0.005887129809707403, Current params: {'in_len': 132, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 4, 'dim_feedforward': 96, 'dropout': 0.12736706407521667, 'lr': 0.0003386749593303992, 'batch_size': 48, 'lr_epochs': 8, 'max_grad_norm': 0.6400631055971514}
Best value: 0.05688260868191719, Best params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 4, 'dim_feedforward': 256, 'dropout': 0.0005803221175518791, 'lr': 0.00011858321245129909, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.47261131007685786}
Current value: 0.006157404277473688, Current params: {'in_len': 192, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 2, 'dim_feedforward': 416, 'dropout': 0.03057646276922104, 'lr': 0.0006278229895886476, 'batch_size': 32, 'lr_epochs': 4, 'max_grad_norm': 0.8039541419325452}
Best value: 0.05688260868191719, Best params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 4, 'dim_feedforward': 256, 'dropout': 0.0005803221175518791, 'lr': 0.00011858321245129909, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.47261131007685786}
Current value: 0.05421862751245499, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.16187034479600063, 'lr': 0.0008364850520892051, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.5610474420858522}
Best value: 0.05421862751245499, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.16187034479600063, 'lr': 0.0008364850520892051, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.5610474420858522}
Current value: 0.007455854676663876, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 224, 'dropout': 0.16083307681812745, 'lr': 0.0004495703516877408, 'batch_size': 48, 'lr_epochs': 14, 'max_grad_norm': 0.29936726348658976}
Best value: 0.05421862751245499, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.16187034479600063, 'lr': 0.0008364850520892051, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.5610474420858522}
Current value: 0.006552396807819605, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 160, 'dropout': 0.19609191023127068, 'lr': 0.000878327354585418, 'batch_size': 32, 'lr_epochs': 18, 'max_grad_norm': 0.555754401457434}
Best value: 0.05421862751245499, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.16187034479600063, 'lr': 0.0008364850520892051, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.5610474420858522}
Current value: 0.05509025603532791, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 3, 'dim_feedforward': 96, 'dropout': 0.1141854752970517, 'lr': 0.0007644199835748278, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.6982338586823853}
Best value: 0.05421862751245499, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.16187034479600063, 'lr': 0.0008364850520892051, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.5610474420858522}
Current value: 0.005581423174589872, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.11664499592059994, 'lr': 0.0007319466368657579, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.7233771477276021}
Best value: 0.05421862751245499, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.16187034479600063, 'lr': 0.0008364850520892051, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.5610474420858522}
Current value: 0.006137198302894831, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 256, 'dropout': 0.15202881415354505, 'lr': 0.0007723322283566087, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.5666661703735922}
Best value: 0.05421862751245499, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.16187034479600063, 'lr': 0.0008364850520892051, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.5610474420858522}
Current value: 0.007084484212100506, Current params: {'in_len': 108, 'max_samples_per_ts': 100, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 3, 'dim_feedforward': 320, 'dropout': 0.17420747192194036, 'lr': 0.0006500885473755731, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.4510061554629137}
Best value: 0.05421862751245499, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.16187034479600063, 'lr': 0.0008364850520892051, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.5610474420858522}
Current value: 0.0639679953455925, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 3, 'dim_feedforward': 64, 'dropout': 0.11799947745943083, 'lr': 0.000797942617582779, 'batch_size': 48, 'lr_epochs': 12, 'max_grad_norm': 0.8320606528861222}
Best value: 0.05421862751245499, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.16187034479600063, 'lr': 0.0008364850520892051, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.5610474420858522}
Current value: 0.00656802486628294, Current params: {'in_len': 108, 'max_samples_per_ts': 100, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 160, 'dropout': 0.07323834818856245, 'lr': 0.000935485637484823, 'batch_size': 32, 'lr_epochs': 18, 'max_grad_norm': 0.5952676996926901}
Best value: 0.05421862751245499, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.16187034479600063, 'lr': 0.0008364850520892051, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.5610474420858522}
Current value: 0.05893765017390251, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 3, 'dim_feedforward': 224, 'dropout': 0.1439840904893679, 'lr': 0.0006950608842378866, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.5116560262794724}
Best value: 0.05421862751245499, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.16187034479600063, 'lr': 0.0008364850520892051, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.5610474420858522}
Current value: 0.062249861657619476, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1367878494399022, 'lr': 0.00016972061275579342, 'batch_size': 48, 'lr_epochs': 16, 'max_grad_norm': 0.3948962147673058}
Best value: 0.05421862751245499, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.16187034479600063, 'lr': 0.0008364850520892051, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.5610474420858522}
Current value: 0.054354313760995865, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 416, 'dropout': 0.15613435978608337, 'lr': 0.000847286631216087, 'batch_size': 48, 'lr_epochs': 10, 'max_grad_norm': 0.11521801952992017}
Best value: 0.05421862751245499, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.16187034479600063, 'lr': 0.0008364850520892051, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.5610474420858522}
Current value: 0.05429970473051071, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 416, 'dropout': 0.1527884153316281, 'lr': 0.0008307801117488188, 'batch_size': 48, 'lr_epochs': 6, 'max_grad_norm': 0.28237729548843593}
Best value: 0.05421862751245499, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.16187034479600063, 'lr': 0.0008364850520892051, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.5610474420858522}
Current value: 0.05279618501663208, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 416, 'dropout': 0.15988694296807085, 'lr': 0.0008294951323071034, 'batch_size': 48, 'lr_epochs': 6, 'max_grad_norm': 0.1106168850327412}
Best value: 0.05279618501663208, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 416, 'dropout': 0.15988694296807085, 'lr': 0.0008294951323071034, 'batch_size': 48, 'lr_epochs': 6, 'max_grad_norm': 0.1106168850327412}
Current value: 0.05546274408698082, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 416, 'dropout': 0.16918982035425287, 'lr': 0.0008330301621884697, 'batch_size': 48, 'lr_epochs': 6, 'max_grad_norm': 0.10627457744128908}
Best value: 0.05279618501663208, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 416, 'dropout': 0.15988694296807085, 'lr': 0.0008294951323071034, 'batch_size': 48, 'lr_epochs': 6, 'max_grad_norm': 0.1106168850327412}
Current value: 0.05355929210782051, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 416, 'dropout': 0.15547602278883343, 'lr': 0.0009414969316342993, 'batch_size': 48, 'lr_epochs': 6, 'max_grad_norm': 0.12024886535907586}
Best value: 0.05279618501663208, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 416, 'dropout': 0.15988694296807085, 'lr': 0.0008294951323071034, 'batch_size': 48, 'lr_epochs': 6, 'max_grad_norm': 0.1106168850327412}
Current value: 0.00656478013843298, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1822054777663213, 'lr': 0.0009281999756700362, 'batch_size': 48, 'lr_epochs': 6, 'max_grad_norm': 0.21077434052040653}
Best value: 0.05279618501663208, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 416, 'dropout': 0.15988694296807085, 'lr': 0.0008294951323071034, 'batch_size': 48, 'lr_epochs': 6, 'max_grad_norm': 0.1106168850327412}
Current value: 0.006180781405419111, Current params: {'in_len': 108, 'max_samples_per_ts': 100, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 384, 'dropout': 0.16725444386480925, 'lr': 0.0009376465136853862, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.25543072456923677}
Best value: 0.05279618501663208, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 416, 'dropout': 0.15988694296807085, 'lr': 0.0008294951323071034, 'batch_size': 48, 'lr_epochs': 6, 'max_grad_norm': 0.1106168850327412}
Current value: 0.0061540547758340836, Current params: {'in_len': 96, 'max_samples_per_ts': 200, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 512, 'dropout': 0.19847159888130234, 'lr': 0.0008879902991562514, 'batch_size': 64, 'lr_epochs': 6, 'max_grad_norm': 0.14594529504069814}
Best value: 0.05279618501663208, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 416, 'dropout': 0.15988694296807085, 'lr': 0.0008294951323071034, 'batch_size': 48, 'lr_epochs': 6, 'max_grad_norm': 0.1106168850327412}
Current value: 0.005511647090315819, Current params: {'in_len': 132, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 352, 'dropout': 0.14832957367353716, 'lr': 0.0009971929902962084, 'batch_size': 48, 'lr_epochs': 8, 'max_grad_norm': 0.2529159892338931}
Best value: 0.05279618501663208, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 416, 'dropout': 0.15988694296807085, 'lr': 0.0008294951323071034, 'batch_size': 48, 'lr_epochs': 6, 'max_grad_norm': 0.1106168850327412}
Current value: 0.00627398956567049, Current params: {'in_len': 108, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 480, 'dropout': 0.18288505633348642, 'lr': 0.0008094610641552014, 'batch_size': 64, 'lr_epochs': 4, 'max_grad_norm': 0.23593722506737563}
Best value: 0.05279618501663208, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 416, 'dropout': 0.15988694296807085, 'lr': 0.0008294951323071034, 'batch_size': 48, 'lr_epochs': 6, 'max_grad_norm': 0.1106168850327412}
Current value: 0.005880360957235098, Current params: {'in_len': 96, 'max_samples_per_ts': 100, 'd_model': 128, 'n_heads': 2, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 384, 'dropout': 0.14088923920376223, 'lr': 0.0007041409787456441, 'batch_size': 48, 'lr_epochs': 6, 'max_grad_norm': 0.1580010588438115}
Best value: 0.05279618501663208, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 416, 'dropout': 0.15988694296807085, 'lr': 0.0008294951323071034, 'batch_size': 48, 'lr_epochs': 6, 'max_grad_norm': 0.1106168850327412}
Current value: 0.005477985367178917, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 416, 'dropout': 0.1577604390361549, 'lr': 0.0008722282141019136, 'batch_size': 48, 'lr_epochs': 10, 'max_grad_norm': 0.11580270515809461}
Best value: 0.05279618501663208, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 416, 'dropout': 0.15988694296807085, 'lr': 0.0008294951323071034, 'batch_size': 48, 'lr_epochs': 6, 'max_grad_norm': 0.1106168850327412}
Current value: 0.05377715826034546, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1588316189528253, 'lr': 0.0008615612556746231, 'batch_size': 48, 'lr_epochs': 8, 'max_grad_norm': 0.31268561194160743}
Best value: 0.05279618501663208, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 416, 'dropout': 0.15988694296807085, 'lr': 0.0008294951323071034, 'batch_size': 48, 'lr_epochs': 6, 'max_grad_norm': 0.1106168850327412}
Current value: 0.005498473532497883, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.17573505121533176, 'lr': 0.000920470325791503, 'batch_size': 48, 'lr_epochs': 8, 'max_grad_norm': 0.3028796871555659}
Best value: 0.05279618501663208, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 416, 'dropout': 0.15988694296807085, 'lr': 0.0008294951323071034, 'batch_size': 48, 'lr_epochs': 6, 'max_grad_norm': 0.1106168850327412}
Current value: 0.05434774234890938, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 352, 'dropout': 0.1254410204431651, 'lr': 0.0008000885332149769, 'batch_size': 64, 'lr_epochs': 6, 'max_grad_norm': 0.3499587557690171}
Best value: 0.05279618501663208, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 416, 'dropout': 0.15988694296807085, 'lr': 0.0008294951323071034, 'batch_size': 48, 'lr_epochs': 6, 'max_grad_norm': 0.1106168850327412}
Current value: 0.05261079967021942, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.005416885018348694, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 480, 'dropout': 0.19148949277061805, 'lr': 0.0009380859410766914, 'batch_size': 48, 'lr_epochs': 2, 'max_grad_norm': 0.19434664187104517}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.005827943328768015, Current params: {'in_len': 96, 'max_samples_per_ts': 100, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 448, 'dropout': 0.16551050648819027, 'lr': 0.0008909758321826146, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.15962886739276833}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.006046920549124479, Current params: {'in_len': 120, 'max_samples_per_ts': 150, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 512, 'dropout': 0.18488890346920614, 'lr': 0.0009654136751386648, 'batch_size': 64, 'lr_epochs': 8, 'max_grad_norm': 0.4199105153315408}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.005500838626176119, Current params: {'in_len': 168, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 2, 'dim_feedforward': 320, 'dropout': 0.17313824796314856, 'lr': 0.000954762613750887, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.33655970723175677}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.006247067824006081, Current params: {'in_len': 96, 'max_samples_per_ts': 200, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 1, 'dim_feedforward': 480, 'dropout': 0.19254809855882854, 'lr': 0.0007317545695115751, 'batch_size': 48, 'lr_epochs': 2, 'max_grad_norm': 0.1529595286160435}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.05447206273674965, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.15108194391815083, 'lr': 0.0008441858360924755, 'batch_size': 48, 'lr_epochs': 6, 'max_grad_norm': 0.21536004237843498}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.005259520374238491, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 384, 'dropout': 0.1619965630813765, 'lr': 0.0008994076996969928, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.253278822776812}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.005257071927189827, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 416, 'dropout': 0.1437616317770346, 'lr': 0.0008654094822944162, 'batch_size': 48, 'lr_epochs': 8, 'max_grad_norm': 0.2751060206007982}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.006383561063557863, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1800980843850096, 'lr': 0.000997526003904634, 'batch_size': 48, 'lr_epochs': 6, 'max_grad_norm': 0.1882239336683192}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.05583672598004341, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 320, 'dropout': 0.1331052573026675, 'lr': 0.0007887609814263319, 'batch_size': 48, 'lr_epochs': 12, 'max_grad_norm': 0.3220122374181361}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.00563474977388978, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 384, 'dropout': 0.1546423230585624, 'lr': 0.0008274303106407924, 'batch_size': 48, 'lr_epochs': 8, 'max_grad_norm': 0.13130108883873615}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.006676897872239351, Current params: {'in_len': 108, 'max_samples_per_ts': 100, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.08691588897105729, 'lr': 0.0005788104915570102, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.5223601602165804}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.005480432417243719, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 128, 'dropout': 0.18875625940664312, 'lr': 0.0006540821027717377, 'batch_size': 48, 'lr_epochs': 6, 'max_grad_norm': 0.21332195932439774}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.005298893433064222, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 352, 'dropout': 0.16372149186076632, 'lr': 0.000758815333133331, 'batch_size': 64, 'lr_epochs': 8, 'max_grad_norm': 0.6046946746664887}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.006443016231060028, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 2, 'num_encoder_layers': 2, 'num_decoder_layers': 4, 'dim_feedforward': 512, 'dropout': 0.12686842059423592, 'lr': 0.0009676004102221176, 'batch_size': 48, 'lr_epochs': 10, 'max_grad_norm': 0.17870141179719298}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.056647639721632004, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 352, 'dropout': 0.12579569341604133, 'lr': 0.0008087107699766508, 'batch_size': 64, 'lr_epochs': 6, 'max_grad_norm': 0.3555226967825725}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.055637162178754807, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 416, 'dropout': 0.10644031224448175, 'lr': 0.000855803155346092, 'batch_size': 64, 'lr_epochs': 6, 'max_grad_norm': 0.38922651650785584}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.05292828753590584, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 384, 'dropout': 0.1474231776963809, 'lr': 0.0009065003927920725, 'batch_size': 64, 'lr_epochs': 4, 'max_grad_norm': 0.47572659628001884}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.052726395428180695, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 2, 'dim_feedforward': 384, 'dropout': 0.14774071005434508, 'lr': 0.0009144937260026591, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.4424167434850634}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.006510813720524311, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 384, 'dropout': 0.1359486682164368, 'lr': 0.0009089071135204139, 'batch_size': 48, 'lr_epochs': 2, 'max_grad_norm': 0.47173670196483464}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.00559281837195158, Current params: {'in_len': 192, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 2, 'dim_feedforward': 288, 'dropout': 0.14716534029836245, 'lr': 0.0009680033744448947, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.5357922128086708}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.005243972409516573, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 2, 'dim_feedforward': 448, 'dropout': 0.17400571679690502, 'lr': 0.000507123388402176, 'batch_size': 48, 'lr_epochs': 2, 'max_grad_norm': 0.42367405434316896}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.0062263645231723785, Current params: {'in_len': 156, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 1, 'dim_feedforward': 256, 'dropout': 0.1596190297987247, 'lr': 0.0009067953275543566, 'batch_size': 32, 'lr_epochs': 4, 'max_grad_norm': 0.48871587961194085}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.055658236145973206, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 2, 'dim_feedforward': 384, 'dropout': 0.13864129392303867, 'lr': 0.0008783930528550926, 'batch_size': 64, 'lr_epochs': 4, 'max_grad_norm': 0.6734069443229357}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.005365515127778053, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 2, 'dim_feedforward': 416, 'dropout': 0.16950604556654417, 'lr': 0.0009270495992390274, 'batch_size': 48, 'lr_epochs': 2, 'max_grad_norm': 0.43021171637739564}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.05936352536082268, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 416, 'dropout': 0.15068420110565062, 'lr': 0.00027137463733515563, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.5808086651857312}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.005318747367709875, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.15523989486936596, 'lr': 0.000951649635733243, 'batch_size': 48, 'lr_epochs': 6, 'max_grad_norm': 0.10317113885550097}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.054478999227285385, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.17848631685545355, 'lr': 0.0008276272403355869, 'batch_size': 48, 'lr_epochs': 6, 'max_grad_norm': 0.45028292852978186}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.05400595813989639, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 384, 'dropout': 0.145549832702481, 'lr': 0.0008700405335000309, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.2795424253873826}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.00574130704626441, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 384, 'dropout': 0.14595631761055317, 'lr': 0.0008683610023308531, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.3881492351228648}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.005557161755859852, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 224, 'dropout': 0.16351586239143268, 'lr': 0.0009831353823383765, 'batch_size': 48, 'lr_epochs': 14, 'max_grad_norm': 0.9998734028137266}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.005337823182344437, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 352, 'dropout': 0.13229947423948735, 'lr': 0.0009072692453007063, 'batch_size': 48, 'lr_epochs': 2, 'max_grad_norm': 0.23509351525307143}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.0060856034979224205, Current params: {'in_len': 108, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 320, 'dropout': 0.1416208290287388, 'lr': 0.0007830511913299292, 'batch_size': 32, 'lr_epochs': 4, 'max_grad_norm': 0.1333624550418432}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.005223562475293875, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 3, 'num_decoder_layers': 4, 'dim_feedforward': 416, 'dropout': 0.10979925714442115, 'lr': 0.0008888017020796806, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.6282100072891768}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.052748218178749084, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 384, 'dropout': 0.12203334602929683, 'lr': 0.0007372789007182527, 'batch_size': 48, 'lr_epochs': 12, 'max_grad_norm': 0.3068195846436781}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.05443774536252022, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 384, 'dropout': 0.09909131847373007, 'lr': 0.0007423700738366612, 'batch_size': 48, 'lr_epochs': 12, 'max_grad_norm': 0.5001912679003759}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.005341776646673679, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 384, 'dropout': 0.12216891132561424, 'lr': 0.0009439461762948513, 'batch_size': 48, 'lr_epochs': 14, 'max_grad_norm': 0.3217373229099223}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.05350624769926071, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.15701932687859457, 'lr': 0.0009183064258877007, 'batch_size': 48, 'lr_epochs': 12, 'max_grad_norm': 0.17353332660114174}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.05386374145746231, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1324439600557541, 'lr': 0.0009209190433056147, 'batch_size': 48, 'lr_epochs': 12, 'max_grad_norm': 0.16673757598039823}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.005196281708776951, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.11904966543162794, 'lr': 0.0009242731927108966, 'batch_size': 48, 'lr_epochs': 12, 'max_grad_norm': 0.1778438427578271}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.005279940087348223, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 480, 'dropout': 0.13157832434930886, 'lr': 0.0009739519999981716, 'batch_size': 48, 'lr_epochs': 12, 'max_grad_norm': 0.16282921457887684}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.05425097048282623, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.15833388414939512, 'lr': 0.0009998203597281511, 'batch_size': 48, 'lr_epochs': 10, 'max_grad_norm': 0.13063566430157605}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.006911266129463911, Current params: {'in_len': 96, 'max_samples_per_ts': 100, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 416, 'dropout': 0.11395956429054778, 'lr': 0.0009429016620257131, 'batch_size': 48, 'lr_epochs': 10, 'max_grad_norm': 0.22843299277993573}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.005653021857142448, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 480, 'dropout': 0.13724309674129534, 'lr': 0.0008517715836750695, 'batch_size': 48, 'lr_epochs': 12, 'max_grad_norm': 0.20359408460572967}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.005255566444247961, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1710115902204146, 'lr': 0.0008995738043374813, 'batch_size': 48, 'lr_epochs': 12, 'max_grad_norm': 0.1725206318417123}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.005232795141637325, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 416, 'dropout': 0.14699078913536764, 'lr': 0.0008642635255214251, 'batch_size': 48, 'lr_epochs': 10, 'max_grad_norm': 0.3143248551628537}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.005328154657036066, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 416, 'dropout': 0.1424873353633863, 'lr': 0.0008207678662636808, 'batch_size': 48, 'lr_epochs': 14, 'max_grad_norm': 0.14088415219361447}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.055083949118852615, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.15064212231613072, 'lr': 0.0009145120201142031, 'batch_size': 48, 'lr_epochs': 12, 'max_grad_norm': 0.12027774556915413}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.005355385132133961, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 352, 'dropout': 0.12884685543116495, 'lr': 0.0008802365497283064, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.2577895671452999}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.005453312769532204, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 384, 'dropout': 0.16682108502530774, 'lr': 0.0009547495013690017, 'batch_size': 48, 'lr_epochs': 8, 'max_grad_norm': 0.2270602586691312}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.005822450388222933, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 480, 'dropout': 0.13854826364233563, 'lr': 0.000925494213099787, 'batch_size': 48, 'lr_epochs': 12, 'max_grad_norm': 0.2707952089526092}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.005273838061839342, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 512, 'dropout': 0.15636602597123136, 'lr': 0.00037576965044948233, 'batch_size': 48, 'lr_epochs': 10, 'max_grad_norm': 0.3732534009860731}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.0052073439583182335, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 416, 'dropout': 0.12182676220592718, 'lr': 0.000980326664114309, 'batch_size': 48, 'lr_epochs': 6, 'max_grad_norm': 0.2815828570228107}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
Current value: 0.0052359881810843945, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.153622677122451, 'lr': 0.0008881012011414838, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.10127234563091686}
Best value: 0.05261079967021942, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1901296977134417, 'lr': 0.000965351785309486, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.19219462323820113}
--------------------------------
Loading column definition...
Checking column definition...
Loading data...
Dropping columns / rows...
Checking for NA values...
Setting data types...
Dropping columns / rows...
Encoding data...
	Updated column definition:
		id: REAL_VALUED (ID)
		time: DATE (TIME)
		gl: REAL_VALUED (TARGET)
		Height: REAL_VALUED (STATIC_INPUT)
		Weight: REAL_VALUED (STATIC_INPUT)
		Gender: REAL_VALUED (STATIC_INPUT)
		Race: REAL_VALUED (STATIC_INPUT)
		EduLevel: REAL_VALUED (STATIC_INPUT)
		AnnualInc: REAL_VALUED (STATIC_INPUT)
		MaritalStatus: REAL_VALUED (STATIC_INPUT)
		DaysWkEx: REAL_VALUED (STATIC_INPUT)
		DaysWkDrinkAlc: REAL_VALUED (STATIC_INPUT)
		DaysMonBingeAlc: REAL_VALUED (STATIC_INPUT)
		T1DDiagAge: REAL_VALUED (STATIC_INPUT)
		NumHospDKA: REAL_VALUED (STATIC_INPUT)
		NumSHSinceT1DDiag: REAL_VALUED (STATIC_INPUT)
		InsDeliveryMethod: REAL_VALUED (STATIC_INPUT)
		UnitsInsTotal: REAL_VALUED (STATIC_INPUT)
		NumMeterCheckDay: REAL_VALUED (STATIC_INPUT)
		Aspirin: REAL_VALUED (STATIC_INPUT)
		Simvastatin: REAL_VALUED (STATIC_INPUT)
		Lisinopril: REAL_VALUED (STATIC_INPUT)
		Vitamin D: REAL_VALUED (STATIC_INPUT)
		Multivitamin preparation: REAL_VALUED (STATIC_INPUT)
		Omeprazole: REAL_VALUED (STATIC_INPUT)
		atorvastatin: REAL_VALUED (STATIC_INPUT)
		Synthroid: REAL_VALUED (STATIC_INPUT)
		vitamin D3: REAL_VALUED (STATIC_INPUT)
		Hypertension: REAL_VALUED (STATIC_INPUT)
		Hyperlipidemia: REAL_VALUED (STATIC_INPUT)
		Hypothyroidism: REAL_VALUED (STATIC_INPUT)
		Depression: REAL_VALUED (STATIC_INPUT)
		Coronary artery disease: REAL_VALUED (STATIC_INPUT)
		Diabetic peripheral neuropathy: REAL_VALUED (STATIC_INPUT)
		Dyslipidemia: REAL_VALUED (STATIC_INPUT)
		Chronic kidney disease: REAL_VALUED (STATIC_INPUT)
		Osteoporosis: REAL_VALUED (STATIC_INPUT)
		Proliferative diabetic retinopathy: REAL_VALUED (STATIC_INPUT)
		Hypercholesterolemia: REAL_VALUED (STATIC_INPUT)
		Erectile dysfunction: REAL_VALUED (STATIC_INPUT)
		Type I diabetes mellitus: REAL_VALUED (STATIC_INPUT)
		time_year: REAL_VALUED (KNOWN_INPUT)
		time_month: REAL_VALUED (KNOWN_INPUT)
		time_day: REAL_VALUED (KNOWN_INPUT)
		time_hour: REAL_VALUED (KNOWN_INPUT)
		time_minute: REAL_VALUED (KNOWN_INPUT)
Interpolating data...
	Dropped segments: 1416
	Extracted segments: 681
	Interpolated values: 140564
	Percent of values interpolated: 24.24%
Splitting data...
	Train: 431798 (69.72%)
	Val: 57067 (9.21%)
	Test: 72421 (11.69%)
	Test OOD: 58048 (9.37%)
Scaling data...
	No scaling applied
Data formatting complete.
--------------------------------
	Train: 425413 (68.73%)
	Val: 56593 (9.14%)
	Test: 72022 (11.64%)
	Test OOD: 64922 (10.49%)
	No scaling applied
		Model Seed: 10 Seed: 1 ID mean of (MSE, MAE): [636.5527   16.44323]
		Model Seed: 10 Seed: 1 OOD mean of (MSE, MAE) stats: [755.8531    18.002888]
		Model Seed: 10 Seed: 1 ID median of (MSE, MAE): [199.112     12.177971]
		Model Seed: 10 Seed: 1 OOD median of (MSE, MAE) stats: [244.33319   13.518054]
		Model Seed: 10 Seed: 1 ID likelihoods: -10.146972165762385
		Model Seed: 10 Seed: 1 OOD likelihoods: -10.232861159830783
		Model Seed: 10 Seed: 1 ID calibration errors: [0.47926695 0.31570483 0.19515067 0.1172163  0.06982479 0.03764458
 0.01980011 0.00987863 0.00509246 0.00377883 0.00534728 0.01120592]
		Model Seed: 10 Seed: 1 OOD calibration errors: [0.4980224  0.33352613 0.21212595 0.13077667 0.08078462 0.04479822
 0.02539239 0.01351184 0.00896968 0.0093696  0.01260555 0.01560049]
	Train: 429990 (69.47%)
	Val: 56876 (9.19%)
	Test: 72378 (11.69%)
	Test OOD: 59706 (9.65%)
	No scaling applied
		Model Seed: 10 Seed: 2 ID mean of (MSE, MAE): [645.9669   17.09731]
		Model Seed: 10 Seed: 2 OOD mean of (MSE, MAE) stats: [674.4684    17.577312]
		Model Seed: 10 Seed: 2 ID median of (MSE, MAE): [218.93158   13.034854]
		Model Seed: 10 Seed: 2 OOD median of (MSE, MAE) stats: [242.05174   13.643668]
		Model Seed: 10 Seed: 2 ID likelihoods: -10.154312396449274
		Model Seed: 10 Seed: 2 OOD likelihoods: -10.175901793392839
		Model Seed: 10 Seed: 2 ID calibration errors: [0.4801574  0.30886032 0.19151792 0.11626131 0.06971426 0.04213812
 0.02328157 0.01508948 0.01132389 0.0114119  0.01676552 0.02305322]
		Model Seed: 10 Seed: 2 OOD calibration errors: [0.4933125  0.3221353  0.20460599 0.12778534 0.08049271 0.05302917
 0.03528814 0.029409   0.02748837 0.0308577  0.04028811 0.05091165]
	Model Seed: 10 ID mean of (MSE, MAE): [641.25977  16.77027]
	Model Seed: 10 OOD mean of (MSE, MAE): [715.16077  17.7901 ]
	Model Seed: 10 ID median of (MSE, MAE): [209.02179   12.606413]
	Model Seed: 10 OOD median of (MSE, MAE): [243.19247   13.580861]
	Model Seed: 10 ID likelihoods: -10.15064228110583
	Model Seed: 10 OOD likelihoods: -10.204381476611811
	Model Seed: 10 ID calibration errors: [0.47971218 0.31228258 0.19333429 0.1167388  0.06976953 0.03989135
 0.02154084 0.01248405 0.00820817 0.00759536 0.0110564  0.01712957]
	Model Seed: 10 OOD calibration errors: [0.49566745 0.32783072 0.20836597 0.129281   0.08063866 0.0489137
 0.03034027 0.02146042 0.01822903 0.02011365 0.02644683 0.03325607]
	Train: 425413 (68.73%)
	Val: 56593 (9.14%)
	Test: 72022 (11.64%)
	Test OOD: 64922 (10.49%)
	No scaling applied
		Model Seed: 11 Seed: 1 ID mean of (MSE, MAE): [636.5527   16.44323]
		Model Seed: 11 Seed: 1 OOD mean of (MSE, MAE) stats: [755.8531    18.002888]
		Model Seed: 11 Seed: 1 ID median of (MSE, MAE): [199.112     12.177971]
		Model Seed: 11 Seed: 1 OOD median of (MSE, MAE) stats: [244.33319   13.518054]
		Model Seed: 11 Seed: 1 ID likelihoods: -10.146972165762385
		Model Seed: 11 Seed: 1 OOD likelihoods: -10.232861159830783
		Model Seed: 11 Seed: 1 ID calibration errors: [0.47926695 0.31570483 0.19515067 0.1172163  0.06982479 0.03764458
 0.01980011 0.00987863 0.00509246 0.00377883 0.00534728 0.01120592]
		Model Seed: 11 Seed: 1 OOD calibration errors: [0.4980224  0.33352613 0.21212595 0.13077667 0.08078462 0.04479822
 0.02539239 0.01351184 0.00896968 0.0093696  0.01260555 0.01560049]
	Train: 429990 (69.47%)
	Val: 56876 (9.19%)
	Test: 72378 (11.69%)
	Test OOD: 59706 (9.65%)
	No scaling applied
		Model Seed: 11 Seed: 2 ID mean of (MSE, MAE): [645.9669   17.09731]
		Model Seed: 11 Seed: 2 OOD mean of (MSE, MAE) stats: [674.4684    17.577312]
		Model Seed: 11 Seed: 2 ID median of (MSE, MAE): [218.93158   13.034854]
		Model Seed: 11 Seed: 2 OOD median of (MSE, MAE) stats: [242.05174   13.643668]
		Model Seed: 11 Seed: 2 ID likelihoods: -10.154312396449274
		Model Seed: 11 Seed: 2 OOD likelihoods: -10.175901793392839
		Model Seed: 11 Seed: 2 ID calibration errors: [0.4801574  0.30886032 0.19151792 0.11626131 0.06971426 0.04213812
 0.02328157 0.01508948 0.01132389 0.0114119  0.01676552 0.02305322]
		Model Seed: 11 Seed: 2 OOD calibration errors: [0.4933125  0.3221353  0.20460599 0.12778534 0.08049271 0.05302917
 0.03528814 0.029409   0.02748837 0.0308577  0.04028811 0.05091165]
	Model Seed: 11 ID mean of (MSE, MAE): [641.25977  16.77027]
	Model Seed: 11 OOD mean of (MSE, MAE): [715.16077  17.7901 ]
	Model Seed: 11 ID median of (MSE, MAE): [209.02179   12.606413]
	Model Seed: 11 OOD median of (MSE, MAE): [243.19247   13.580861]
	Model Seed: 11 ID likelihoods: -10.15064228110583
	Model Seed: 11 OOD likelihoods: -10.204381476611811
	Model Seed: 11 ID calibration errors: [0.47971218 0.31228258 0.19333429 0.1167388  0.06976953 0.03989135
 0.02154084 0.01248405 0.00820817 0.00759536 0.0110564  0.01712957]
	Model Seed: 11 OOD calibration errors: [0.49566745 0.32783072 0.20836597 0.129281   0.08063866 0.0489137
 0.03034027 0.02146042 0.01822903 0.02011365 0.02644683 0.03325607]
	Train: 425413 (68.73%)
	Val: 56593 (9.14%)
	Test: 72022 (11.64%)
	Test OOD: 64922 (10.49%)
	No scaling applied
		Model Seed: 12 Seed: 1 ID mean of (MSE, MAE): [636.5527   16.44323]
		Model Seed: 12 Seed: 1 OOD mean of (MSE, MAE) stats: [755.8531    18.002888]
		Model Seed: 12 Seed: 1 ID median of (MSE, MAE): [199.112     12.177971]
		Model Seed: 12 Seed: 1 OOD median of (MSE, MAE) stats: [244.33319   13.518054]
		Model Seed: 12 Seed: 1 ID likelihoods: -10.146972165762385
		Model Seed: 12 Seed: 1 OOD likelihoods: -10.232861159830783
		Model Seed: 12 Seed: 1 ID calibration errors: [0.47926695 0.31570483 0.19515067 0.1172163  0.06982479 0.03764458
 0.01980011 0.00987863 0.00509246 0.00377883 0.00534728 0.01120592]
		Model Seed: 12 Seed: 1 OOD calibration errors: [0.4980224  0.33352613 0.21212595 0.13077667 0.08078462 0.04479822
 0.02539239 0.01351184 0.00896968 0.0093696  0.01260555 0.01560049]
	Train: 429990 (69.47%)
	Val: 56876 (9.19%)
	Test: 72378 (11.69%)
	Test OOD: 59706 (9.65%)
	No scaling applied
		Model Seed: 12 Seed: 2 ID mean of (MSE, MAE): [645.9669   17.09731]
		Model Seed: 12 Seed: 2 OOD mean of (MSE, MAE) stats: [674.4684    17.577312]
		Model Seed: 12 Seed: 2 ID median of (MSE, MAE): [218.93158   13.034854]
		Model Seed: 12 Seed: 2 OOD median of (MSE, MAE) stats: [242.05174   13.643668]
		Model Seed: 12 Seed: 2 ID likelihoods: -10.154312396449274
		Model Seed: 12 Seed: 2 OOD likelihoods: -10.175901793392839
		Model Seed: 12 Seed: 2 ID calibration errors: [0.4801574  0.30886032 0.19151792 0.11626131 0.06971426 0.04213812
 0.02328157 0.01508948 0.01132389 0.0114119  0.01676552 0.02305322]
		Model Seed: 12 Seed: 2 OOD calibration errors: [0.4933125  0.3221353  0.20460599 0.12778534 0.08049271 0.05302917
 0.03528814 0.029409   0.02748837 0.0308577  0.04028811 0.05091165]
	Model Seed: 12 ID mean of (MSE, MAE): [641.25977  16.77027]
	Model Seed: 12 OOD mean of (MSE, MAE): [715.16077  17.7901 ]
	Model Seed: 12 ID median of (MSE, MAE): [209.02179   12.606413]
	Model Seed: 12 OOD median of (MSE, MAE): [243.19247   13.580861]
	Model Seed: 12 ID likelihoods: -10.15064228110583
	Model Seed: 12 OOD likelihoods: -10.204381476611811
	Model Seed: 12 ID calibration errors: [0.47971218 0.31228258 0.19333429 0.1167388  0.06976953 0.03989135
 0.02154084 0.01248405 0.00820817 0.00759536 0.0110564  0.01712957]
	Model Seed: 12 OOD calibration errors: [0.49566745 0.32783072 0.20836597 0.129281   0.08063866 0.0489137
 0.03034027 0.02146042 0.01822903 0.02011365 0.02644683 0.03325607]
	Train: 425413 (68.73%)
	Val: 56593 (9.14%)
	Test: 72022 (11.64%)
	Test OOD: 64922 (10.49%)
	No scaling applied
		Model Seed: 13 Seed: 1 ID mean of (MSE, MAE): [636.5527   16.44323]
		Model Seed: 13 Seed: 1 OOD mean of (MSE, MAE) stats: [755.8531    18.002888]
		Model Seed: 13 Seed: 1 ID median of (MSE, MAE): [199.112     12.177971]
		Model Seed: 13 Seed: 1 OOD median of (MSE, MAE) stats: [244.33319   13.518054]
		Model Seed: 13 Seed: 1 ID likelihoods: -10.146972165762385
		Model Seed: 13 Seed: 1 OOD likelihoods: -10.232861159830783
		Model Seed: 13 Seed: 1 ID calibration errors: [0.47926695 0.31570483 0.19515067 0.1172163  0.06982479 0.03764458
 0.01980011 0.00987863 0.00509246 0.00377883 0.00534728 0.01120592]
		Model Seed: 13 Seed: 1 OOD calibration errors: [0.4980224  0.33352613 0.21212595 0.13077667 0.08078462 0.04479822
 0.02539239 0.01351184 0.00896968 0.0093696  0.01260555 0.01560049]
	Train: 429990 (69.47%)
	Val: 56876 (9.19%)
	Test: 72378 (11.69%)
	Test OOD: 59706 (9.65%)
	No scaling applied
		Model Seed: 13 Seed: 2 ID mean of (MSE, MAE): [645.9669   17.09731]
		Model Seed: 13 Seed: 2 OOD mean of (MSE, MAE) stats: [674.4684    17.577312]
		Model Seed: 13 Seed: 2 ID median of (MSE, MAE): [218.93158   13.034854]
		Model Seed: 13 Seed: 2 OOD median of (MSE, MAE) stats: [242.05174   13.643668]
		Model Seed: 13 Seed: 2 ID likelihoods: -10.154312396449274
		Model Seed: 13 Seed: 2 OOD likelihoods: -10.175901793392839
		Model Seed: 13 Seed: 2 ID calibration errors: [0.4801574  0.30886032 0.19151792 0.11626131 0.06971426 0.04213812
 0.02328157 0.01508948 0.01132389 0.0114119  0.01676552 0.02305322]
		Model Seed: 13 Seed: 2 OOD calibration errors: [0.4933125  0.3221353  0.20460599 0.12778534 0.08049271 0.05302917
 0.03528814 0.029409   0.02748837 0.0308577  0.04028811 0.05091165]
	Model Seed: 13 ID mean of (MSE, MAE): [641.25977  16.77027]
	Model Seed: 13 OOD mean of (MSE, MAE): [715.16077  17.7901 ]
	Model Seed: 13 ID median of (MSE, MAE): [209.02179   12.606413]
	Model Seed: 13 OOD median of (MSE, MAE): [243.19247   13.580861]
	Model Seed: 13 ID likelihoods: -10.15064228110583
	Model Seed: 13 OOD likelihoods: -10.204381476611811
	Model Seed: 13 ID calibration errors: [0.47971218 0.31228258 0.19333429 0.1167388  0.06976953 0.03989135
 0.02154084 0.01248405 0.00820817 0.00759536 0.0110564  0.01712957]
	Model Seed: 13 OOD calibration errors: [0.49566745 0.32783072 0.20836597 0.129281   0.08063866 0.0489137
 0.03034027 0.02146042 0.01822903 0.02011365 0.02644683 0.03325607]
	Train: 425413 (68.73%)
	Val: 56593 (9.14%)
	Test: 72022 (11.64%)
	Test OOD: 64922 (10.49%)
	No scaling applied
		Model Seed: 14 Seed: 1 ID mean of (MSE, MAE): [636.5527   16.44323]
		Model Seed: 14 Seed: 1 OOD mean of (MSE, MAE) stats: [755.8531    18.002888]
		Model Seed: 14 Seed: 1 ID median of (MSE, MAE): [199.112     12.177971]
		Model Seed: 14 Seed: 1 OOD median of (MSE, MAE) stats: [244.33319   13.518054]
		Model Seed: 14 Seed: 1 ID likelihoods: -10.146972165762385
		Model Seed: 14 Seed: 1 OOD likelihoods: -10.232861159830783
		Model Seed: 14 Seed: 1 ID calibration errors: [0.47926695 0.31570483 0.19515067 0.1172163  0.06982479 0.03764458
 0.01980011 0.00987863 0.00509246 0.00377883 0.00534728 0.01120592]
		Model Seed: 14 Seed: 1 OOD calibration errors: [0.4980224  0.33352613 0.21212595 0.13077667 0.08078462 0.04479822
 0.02539239 0.01351184 0.00896968 0.0093696  0.01260555 0.01560049]
	Train: 429990 (69.47%)
	Val: 56876 (9.19%)
	Test: 72378 (11.69%)
	Test OOD: 59706 (9.65%)
	No scaling applied
		Model Seed: 14 Seed: 2 ID mean of (MSE, MAE): [645.9669   17.09731]
		Model Seed: 14 Seed: 2 OOD mean of (MSE, MAE) stats: [674.4684    17.577312]
		Model Seed: 14 Seed: 2 ID median of (MSE, MAE): [218.93158   13.034854]
		Model Seed: 14 Seed: 2 OOD median of (MSE, MAE) stats: [242.05174   13.643668]
		Model Seed: 14 Seed: 2 ID likelihoods: -10.154312396449274
		Model Seed: 14 Seed: 2 OOD likelihoods: -10.175901793392839
		Model Seed: 14 Seed: 2 ID calibration errors: [0.4801574  0.30886032 0.19151792 0.11626131 0.06971426 0.04213812
 0.02328157 0.01508948 0.01132389 0.0114119  0.01676552 0.02305322]
		Model Seed: 14 Seed: 2 OOD calibration errors: [0.4933125  0.3221353  0.20460599 0.12778534 0.08049271 0.05302917
 0.03528814 0.029409   0.02748837 0.0308577  0.04028811 0.05091165]
	Model Seed: 14 ID mean of (MSE, MAE): [641.25977  16.77027]
	Model Seed: 14 OOD mean of (MSE, MAE): [715.16077  17.7901 ]
	Model Seed: 14 ID median of (MSE, MAE): [209.02179   12.606413]
	Model Seed: 14 OOD median of (MSE, MAE): [243.19247   13.580861]
	Model Seed: 14 ID likelihoods: -10.15064228110583
	Model Seed: 14 OOD likelihoods: -10.204381476611811
	Model Seed: 14 ID calibration errors: [0.47971218 0.31228258 0.19333429 0.1167388  0.06976953 0.03989135
 0.02154084 0.01248405 0.00820817 0.00759536 0.0110564  0.01712957]
	Model Seed: 14 OOD calibration errors: [0.49566745 0.32783072 0.20836597 0.129281   0.08063866 0.0489137
 0.03034027 0.02146042 0.01822903 0.02011365 0.02644683 0.03325607]
	Train: 425413 (68.73%)
	Val: 56593 (9.14%)
	Test: 72022 (11.64%)
	Test OOD: 64922 (10.49%)
	No scaling applied
		Model Seed: 15 Seed: 1 ID mean of (MSE, MAE): [636.5527   16.44323]
		Model Seed: 15 Seed: 1 OOD mean of (MSE, MAE) stats: [755.8531    18.002888]
		Model Seed: 15 Seed: 1 ID median of (MSE, MAE): [199.112     12.177971]
		Model Seed: 15 Seed: 1 OOD median of (MSE, MAE) stats: [244.33319   13.518054]
		Model Seed: 15 Seed: 1 ID likelihoods: -10.146972165762385
		Model Seed: 15 Seed: 1 OOD likelihoods: -10.232861159830783
		Model Seed: 15 Seed: 1 ID calibration errors: [0.47926695 0.31570483 0.19515067 0.1172163  0.06982479 0.03764458
 0.01980011 0.00987863 0.00509246 0.00377883 0.00534728 0.01120592]
		Model Seed: 15 Seed: 1 OOD calibration errors: [0.4980224  0.33352613 0.21212595 0.13077667 0.08078462 0.04479822
 0.02539239 0.01351184 0.00896968 0.0093696  0.01260555 0.01560049]
	Train: 429990 (69.47%)
	Val: 56876 (9.19%)
	Test: 72378 (11.69%)
	Test OOD: 59706 (9.65%)
	No scaling applied
		Model Seed: 15 Seed: 2 ID mean of (MSE, MAE): [645.9669   17.09731]
		Model Seed: 15 Seed: 2 OOD mean of (MSE, MAE) stats: [674.4684    17.577312]
		Model Seed: 15 Seed: 2 ID median of (MSE, MAE): [218.93158   13.034854]
		Model Seed: 15 Seed: 2 OOD median of (MSE, MAE) stats: [242.05174   13.643668]
		Model Seed: 15 Seed: 2 ID likelihoods: -10.154312396449274
		Model Seed: 15 Seed: 2 OOD likelihoods: -10.175901793392839
		Model Seed: 15 Seed: 2 ID calibration errors: [0.4801574  0.30886032 0.19151792 0.11626131 0.06971426 0.04213812
 0.02328157 0.01508948 0.01132389 0.0114119  0.01676552 0.02305322]
		Model Seed: 15 Seed: 2 OOD calibration errors: [0.4933125  0.3221353  0.20460599 0.12778534 0.08049271 0.05302917
 0.03528814 0.029409   0.02748837 0.0308577  0.04028811 0.05091165]
	Model Seed: 15 ID mean of (MSE, MAE): [641.25977  16.77027]
	Model Seed: 15 OOD mean of (MSE, MAE): [715.16077  17.7901 ]
	Model Seed: 15 ID median of (MSE, MAE): [209.02179   12.606413]
	Model Seed: 15 OOD median of (MSE, MAE): [243.19247   13.580861]
	Model Seed: 15 ID likelihoods: -10.15064228110583
	Model Seed: 15 OOD likelihoods: -10.204381476611811
	Model Seed: 15 ID calibration errors: [0.47971218 0.31228258 0.19333429 0.1167388  0.06976953 0.03989135
 0.02154084 0.01248405 0.00820817 0.00759536 0.0110564  0.01712957]
	Model Seed: 15 OOD calibration errors: [0.49566745 0.32783072 0.20836597 0.129281   0.08063866 0.0489137
 0.03034027 0.02146042 0.01822903 0.02011365 0.02644683 0.03325607]
	Train: 425413 (68.73%)
	Val: 56593 (9.14%)
	Test: 72022 (11.64%)
	Test OOD: 64922 (10.49%)
	No scaling applied
		Model Seed: 16 Seed: 1 ID mean of (MSE, MAE): [636.5527   16.44323]
		Model Seed: 16 Seed: 1 OOD mean of (MSE, MAE) stats: [755.8531    18.002888]
		Model Seed: 16 Seed: 1 ID median of (MSE, MAE): [199.112     12.177971]
		Model Seed: 16 Seed: 1 OOD median of (MSE, MAE) stats: [244.33319   13.518054]
		Model Seed: 16 Seed: 1 ID likelihoods: -10.146972165762385
		Model Seed: 16 Seed: 1 OOD likelihoods: -10.232861159830783
		Model Seed: 16 Seed: 1 ID calibration errors: [0.47926695 0.31570483 0.19515067 0.1172163  0.06982479 0.03764458
 0.01980011 0.00987863 0.00509246 0.00377883 0.00534728 0.01120592]
		Model Seed: 16 Seed: 1 OOD calibration errors: [0.4980224  0.33352613 0.21212595 0.13077667 0.08078462 0.04479822
 0.02539239 0.01351184 0.00896968 0.0093696  0.01260555 0.01560049]
	Train: 429990 (69.47%)
	Val: 56876 (9.19%)
	Test: 72378 (11.69%)
	Test OOD: 59706 (9.65%)
	No scaling applied
		Model Seed: 16 Seed: 2 ID mean of (MSE, MAE): [645.9669   17.09731]
		Model Seed: 16 Seed: 2 OOD mean of (MSE, MAE) stats: [674.4684    17.577312]
		Model Seed: 16 Seed: 2 ID median of (MSE, MAE): [218.93158   13.034854]
		Model Seed: 16 Seed: 2 OOD median of (MSE, MAE) stats: [242.05174   13.643668]
		Model Seed: 16 Seed: 2 ID likelihoods: -10.154312396449274
		Model Seed: 16 Seed: 2 OOD likelihoods: -10.175901793392839
		Model Seed: 16 Seed: 2 ID calibration errors: [0.4801574  0.30886032 0.19151792 0.11626131 0.06971426 0.04213812
 0.02328157 0.01508948 0.01132389 0.0114119  0.01676552 0.02305322]
		Model Seed: 16 Seed: 2 OOD calibration errors: [0.4933125  0.3221353  0.20460599 0.12778534 0.08049271 0.05302917
 0.03528814 0.029409   0.02748837 0.0308577  0.04028811 0.05091165]
	Model Seed: 16 ID mean of (MSE, MAE): [641.25977  16.77027]
	Model Seed: 16 OOD mean of (MSE, MAE): [715.16077  17.7901 ]
	Model Seed: 16 ID median of (MSE, MAE): [209.02179   12.606413]
	Model Seed: 16 OOD median of (MSE, MAE): [243.19247   13.580861]
	Model Seed: 16 ID likelihoods: -10.15064228110583
	Model Seed: 16 OOD likelihoods: -10.204381476611811
	Model Seed: 16 ID calibration errors: [0.47971218 0.31228258 0.19333429 0.1167388  0.06976953 0.03989135
 0.02154084 0.01248405 0.00820817 0.00759536 0.0110564  0.01712957]
	Model Seed: 16 OOD calibration errors: [0.49566745 0.32783072 0.20836597 0.129281   0.08063866 0.0489137
 0.03034027 0.02146042 0.01822903 0.02011365 0.02644683 0.03325607]
	Train: 425413 (68.73%)
	Val: 56593 (9.14%)
	Test: 72022 (11.64%)
	Test OOD: 64922 (10.49%)
	No scaling applied
		Model Seed: 17 Seed: 1 ID mean of (MSE, MAE): [636.5527   16.44323]
		Model Seed: 17 Seed: 1 OOD mean of (MSE, MAE) stats: [755.8531    18.002888]
		Model Seed: 17 Seed: 1 ID median of (MSE, MAE): [199.112     12.177971]
		Model Seed: 17 Seed: 1 OOD median of (MSE, MAE) stats: [244.33319   13.518054]
		Model Seed: 17 Seed: 1 ID likelihoods: -10.146972165762385
		Model Seed: 17 Seed: 1 OOD likelihoods: -10.232861159830783
		Model Seed: 17 Seed: 1 ID calibration errors: [0.47926695 0.31570483 0.19515067 0.1172163  0.06982479 0.03764458
 0.01980011 0.00987863 0.00509246 0.00377883 0.00534728 0.01120592]
		Model Seed: 17 Seed: 1 OOD calibration errors: [0.4980224  0.33352613 0.21212595 0.13077667 0.08078462 0.04479822
 0.02539239 0.01351184 0.00896968 0.0093696  0.01260555 0.01560049]
	Train: 429990 (69.47%)
	Val: 56876 (9.19%)
	Test: 72378 (11.69%)
	Test OOD: 59706 (9.65%)
	No scaling applied
		Model Seed: 17 Seed: 2 ID mean of (MSE, MAE): [645.9669   17.09731]
		Model Seed: 17 Seed: 2 OOD mean of (MSE, MAE) stats: [674.4684    17.577312]
		Model Seed: 17 Seed: 2 ID median of (MSE, MAE): [218.93158   13.034854]
		Model Seed: 17 Seed: 2 OOD median of (MSE, MAE) stats: [242.05174   13.643668]
		Model Seed: 17 Seed: 2 ID likelihoods: -10.154312396449274
		Model Seed: 17 Seed: 2 OOD likelihoods: -10.175901793392839
		Model Seed: 17 Seed: 2 ID calibration errors: [0.4801574  0.30886032 0.19151792 0.11626131 0.06971426 0.04213812
 0.02328157 0.01508948 0.01132389 0.0114119  0.01676552 0.02305322]
		Model Seed: 17 Seed: 2 OOD calibration errors: [0.4933125  0.3221353  0.20460599 0.12778534 0.08049271 0.05302917
 0.03528814 0.029409   0.02748837 0.0308577  0.04028811 0.05091165]
	Model Seed: 17 ID mean of (MSE, MAE): [641.25977  16.77027]
	Model Seed: 17 OOD mean of (MSE, MAE): [715.16077  17.7901 ]
	Model Seed: 17 ID median of (MSE, MAE): [209.02179   12.606413]
	Model Seed: 17 OOD median of (MSE, MAE): [243.19247   13.580861]
	Model Seed: 17 ID likelihoods: -10.15064228110583
	Model Seed: 17 OOD likelihoods: -10.204381476611811
	Model Seed: 17 ID calibration errors: [0.47971218 0.31228258 0.19333429 0.1167388  0.06976953 0.03989135
 0.02154084 0.01248405 0.00820817 0.00759536 0.0110564  0.01712957]
	Model Seed: 17 OOD calibration errors: [0.49566745 0.32783072 0.20836597 0.129281   0.08063866 0.0489137
 0.03034027 0.02146042 0.01822903 0.02011365 0.02644683 0.03325607]
	Train: 425413 (68.73%)
	Val: 56593 (9.14%)
	Test: 72022 (11.64%)
	Test OOD: 64922 (10.49%)
	No scaling applied
		Model Seed: 18 Seed: 1 ID mean of (MSE, MAE): [636.5527   16.44323]
		Model Seed: 18 Seed: 1 OOD mean of (MSE, MAE) stats: [755.8531    18.002888]
		Model Seed: 18 Seed: 1 ID median of (MSE, MAE): [199.112     12.177971]
		Model Seed: 18 Seed: 1 OOD median of (MSE, MAE) stats: [244.33319   13.518054]
		Model Seed: 18 Seed: 1 ID likelihoods: -10.146972165762385
		Model Seed: 18 Seed: 1 OOD likelihoods: -10.232861159830783
		Model Seed: 18 Seed: 1 ID calibration errors: [0.47926695 0.31570483 0.19515067 0.1172163  0.06982479 0.03764458
 0.01980011 0.00987863 0.00509246 0.00377883 0.00534728 0.01120592]
		Model Seed: 18 Seed: 1 OOD calibration errors: [0.4980224  0.33352613 0.21212595 0.13077667 0.08078462 0.04479822
 0.02539239 0.01351184 0.00896968 0.0093696  0.01260555 0.01560049]
	Train: 429990 (69.47%)
	Val: 56876 (9.19%)
	Test: 72378 (11.69%)
	Test OOD: 59706 (9.65%)
	No scaling applied
		Model Seed: 18 Seed: 2 ID mean of (MSE, MAE): [645.9669   17.09731]
		Model Seed: 18 Seed: 2 OOD mean of (MSE, MAE) stats: [674.4684    17.577312]
		Model Seed: 18 Seed: 2 ID median of (MSE, MAE): [218.93158   13.034854]
		Model Seed: 18 Seed: 2 OOD median of (MSE, MAE) stats: [242.05174   13.643668]
		Model Seed: 18 Seed: 2 ID likelihoods: -10.154312396449274
		Model Seed: 18 Seed: 2 OOD likelihoods: -10.175901793392839
		Model Seed: 18 Seed: 2 ID calibration errors: [0.4801574  0.30886032 0.19151792 0.11626131 0.06971426 0.04213812
 0.02328157 0.01508948 0.01132389 0.0114119  0.01676552 0.02305322]
		Model Seed: 18 Seed: 2 OOD calibration errors: [0.4933125  0.3221353  0.20460599 0.12778534 0.08049271 0.05302917
 0.03528814 0.029409   0.02748837 0.0308577  0.04028811 0.05091165]
	Model Seed: 18 ID mean of (MSE, MAE): [641.25977  16.77027]
	Model Seed: 18 OOD mean of (MSE, MAE): [715.16077  17.7901 ]
	Model Seed: 18 ID median of (MSE, MAE): [209.02179   12.606413]
	Model Seed: 18 OOD median of (MSE, MAE): [243.19247   13.580861]
	Model Seed: 18 ID likelihoods: -10.15064228110583
	Model Seed: 18 OOD likelihoods: -10.204381476611811
	Model Seed: 18 ID calibration errors: [0.47971218 0.31228258 0.19333429 0.1167388  0.06976953 0.03989135
 0.02154084 0.01248405 0.00820817 0.00759536 0.0110564  0.01712957]
	Model Seed: 18 OOD calibration errors: [0.49566745 0.32783072 0.20836597 0.129281   0.08063866 0.0489137
 0.03034027 0.02146042 0.01822903 0.02011365 0.02644683 0.03325607]
	Train: 425413 (68.73%)
	Val: 56593 (9.14%)
	Test: 72022 (11.64%)
	Test OOD: 64922 (10.49%)
	No scaling applied
		Model Seed: 19 Seed: 1 ID mean of (MSE, MAE): [636.5527   16.44323]
		Model Seed: 19 Seed: 1 OOD mean of (MSE, MAE) stats: [755.8531    18.002888]
		Model Seed: 19 Seed: 1 ID median of (MSE, MAE): [199.112     12.177971]
		Model Seed: 19 Seed: 1 OOD median of (MSE, MAE) stats: [244.33319   13.518054]
		Model Seed: 19 Seed: 1 ID likelihoods: -10.146972165762385
		Model Seed: 19 Seed: 1 OOD likelihoods: -10.232861159830783
		Model Seed: 19 Seed: 1 ID calibration errors: [0.47926695 0.31570483 0.19515067 0.1172163  0.06982479 0.03764458
 0.01980011 0.00987863 0.00509246 0.00377883 0.00534728 0.01120592]
		Model Seed: 19 Seed: 1 OOD calibration errors: [0.4980224  0.33352613 0.21212595 0.13077667 0.08078462 0.04479822
 0.02539239 0.01351184 0.00896968 0.0093696  0.01260555 0.01560049]
	Train: 429990 (69.47%)
	Val: 56876 (9.19%)
	Test: 72378 (11.69%)
	Test OOD: 59706 (9.65%)
	No scaling applied
		Model Seed: 19 Seed: 2 ID mean of (MSE, MAE): [645.9669   17.09731]
		Model Seed: 19 Seed: 2 OOD mean of (MSE, MAE) stats: [674.4684    17.577312]
		Model Seed: 19 Seed: 2 ID median of (MSE, MAE): [218.93158   13.034854]
		Model Seed: 19 Seed: 2 OOD median of (MSE, MAE) stats: [242.05174   13.643668]
		Model Seed: 19 Seed: 2 ID likelihoods: -10.154312396449274
		Model Seed: 19 Seed: 2 OOD likelihoods: -10.175901793392839
		Model Seed: 19 Seed: 2 ID calibration errors: [0.4801574  0.30886032 0.19151792 0.11626131 0.06971426 0.04213812
 0.02328157 0.01508948 0.01132389 0.0114119  0.01676552 0.02305322]
		Model Seed: 19 Seed: 2 OOD calibration errors: [0.4933125  0.3221353  0.20460599 0.12778534 0.08049271 0.05302917
 0.03528814 0.029409   0.02748837 0.0308577  0.04028811 0.05091165]
	Model Seed: 19 ID mean of (MSE, MAE): [641.25977  16.77027]
	Model Seed: 19 OOD mean of (MSE, MAE): [715.16077  17.7901 ]
	Model Seed: 19 ID median of (MSE, MAE): [209.02179   12.606413]
	Model Seed: 19 OOD median of (MSE, MAE): [243.19247   13.580861]
	Model Seed: 19 ID likelihoods: -10.15064228110583
	Model Seed: 19 OOD likelihoods: -10.204381476611811
	Model Seed: 19 ID calibration errors: [0.47971218 0.31228258 0.19333429 0.1167388  0.06976953 0.03989135
 0.02154084 0.01248405 0.00820817 0.00759536 0.0110564  0.01712957]
	Model Seed: 19 OOD calibration errors: [0.49566745 0.32783072 0.20836597 0.129281   0.08063866 0.0489137
 0.03034027 0.02146042 0.01822903 0.02011365 0.02644683 0.03325607]
ID mean of (MSE, MAE): [641.259765625, 16.770267486572266] +- [0.0, 1.9073486328125e-06] +- [4.7071  0.32704] 
OOD mean of (MSE, MAE): [715.1607055664062, 17.79010009765625] +- [6.103515625e-05, 0.0] +- [40.69235   0.212788] 
ID median of (MSE, MAE): [209.02175903320312, 12.606413841247559] +- [3.0517578125e-05, 9.5367431640625e-07] +- [9.90979   0.4284415] 
OOD median of (MSE, MAE): [243.19247436523438, 13.580862045288086] +- [0.0, 9.5367431640625e-07] +- [1.140725 0.062807] 
ID likelihoods: -10.15064228110583 +- 0.0 +- 0.0036701153434455236 
OOD likelihoods: -10.204381476611811 +- 0.0 +- 0.028479683218971097 
ID calibration errors: [0.47971217601272687, 0.31228257595354325, 0.193334294464065, 0.11673880470566642, 0.06976952555017735, 0.039891350657366646, 0.021540837935298904, 0.012484051229017442, 0.008208174932910152, 0.007595364407936877, 0.011056398693039175, 0.017129570177554756] +- [0.0, 0.0, 0.0, 2.7755575615628914e-17, 0.0, 6.938893903907228e-18, 0.0, 1.734723475976807e-18, 1.734723475976807e-18, 8.673617379884035e-19, 0.0, 3.469446951953614e-18] +- [4.452250e-04 3.422255e-03 1.816375e-03 4.774950e-04 5.526500e-05
 2.246770e-03 1.740730e-03 2.605425e-03 3.115715e-03 3.816535e-03
 5.709120e-03 5.923650e-03] 
OOD calibration errors: [0.4956674492571346, 0.32783071816252546, 0.20836597075339758, 0.12928100459089079, 0.0806386630337002, 0.04891369630585656, 0.030340265653651444, 0.02146042186401295, 0.018229028722524142, 0.020113653736493375, 0.026446827735231666, 0.033256068934139994] +- [1.1102230246251565e-16, 5.551115123125783e-17, 0.0, 2.7755575615628914e-17, 1.3877787807814457e-17, 6.938893903907228e-18, 0.0, 3.469446951953614e-18, 3.469446951953614e-18, 0.0, 0.0, 6.938893903907228e-18] +- [0.00235495 0.00569541 0.00375998 0.00149566 0.00014595 0.00411548
 0.00494788 0.00794858 0.00925935 0.01074405 0.01384128 0.01765558] 
