Optimization started at 2023-03-09 12:29:06.256604--------------------------------
Loading column definition...
Checking column definition...
Loading data...
Dropping columns / rows...
Checking for NA values...
Setting data types...
Dropping columns / rows...
Encoding data...
	Updated column definition:
		id: REAL_VALUED (ID)
		time: DATE (TIME)
		gl: REAL_VALUED (TARGET)
		Age: REAL_VALUED (STATIC_INPUT)
		BMI: REAL_VALUED (STATIC_INPUT)
		A1C: REAL_VALUED (STATIC_INPUT)
		FBG: REAL_VALUED (STATIC_INPUT)
		ogtt.2hr: REAL_VALUED (STATIC_INPUT)
		insulin: REAL_VALUED (STATIC_INPUT)
		hs.CRP: REAL_VALUED (STATIC_INPUT)
		Tchol: REAL_VALUED (STATIC_INPUT)
		Trg: REAL_VALUED (STATIC_INPUT)
		HDL: REAL_VALUED (STATIC_INPUT)
		LDL: REAL_VALUED (STATIC_INPUT)
		mean_glucose: REAL_VALUED (STATIC_INPUT)
		sd_glucose: REAL_VALUED (STATIC_INPUT)
		range_glucose: REAL_VALUED (STATIC_INPUT)
		min_glucose: REAL_VALUED (STATIC_INPUT)
		max_glucose: REAL_VALUED (STATIC_INPUT)
		quartile.25_glucose: REAL_VALUED (STATIC_INPUT)
		median_glucose: REAL_VALUED (STATIC_INPUT)
		quartile.75_glucose: REAL_VALUED (STATIC_INPUT)
		mean_slope: REAL_VALUED (STATIC_INPUT)
		max_slope: REAL_VALUED (STATIC_INPUT)
		number_Random140: REAL_VALUED (STATIC_INPUT)
		number_Random200: REAL_VALUED (STATIC_INPUT)
		percent_below.80: REAL_VALUED (STATIC_INPUT)
		se_glucose_mean: REAL_VALUED (STATIC_INPUT)
		numGE: REAL_VALUED (STATIC_INPUT)
		mage: REAL_VALUED (STATIC_INPUT)
		j_index: REAL_VALUED (STATIC_INPUT)
		IQR: REAL_VALUED (STATIC_INPUT)
		modd: REAL_VALUED (STATIC_INPUT)
		distance_traveled: REAL_VALUED (STATIC_INPUT)
		coef_variation: REAL_VALUED (STATIC_INPUT)
		number_Random140_normByDays: REAL_VALUED (STATIC_INPUT)
		number_Random200_normByDays: REAL_VALUED (STATIC_INPUT)
		numGE_normByDays: REAL_VALUED (STATIC_INPUT)
		distance_traveled_normByDays: REAL_VALUED (STATIC_INPUT)
		diagnosis: REAL_VALUED (STATIC_INPUT)
		freq_low: REAL_VALUED (STATIC_INPUT)
		freq_moderate: REAL_VALUED (STATIC_INPUT)
		freq_severe: REAL_VALUED (STATIC_INPUT)
		glucotype: REAL_VALUED (STATIC_INPUT)
		Height: REAL_VALUED (STATIC_INPUT)
		Weight: REAL_VALUED (STATIC_INPUT)
		Insulin_rate_dd: REAL_VALUED (STATIC_INPUT)
		perc_cgm_prediabetic_range: REAL_VALUED (STATIC_INPUT)
		perc_cgm_diabetic_range: REAL_VALUED (STATIC_INPUT)
		SSPG: REAL_VALUED (STATIC_INPUT)
		time_year: REAL_VALUED (KNOWN_INPUT)
		time_month: REAL_VALUED (KNOWN_INPUT)
		time_day: REAL_VALUED (KNOWN_INPUT)
		time_hour: REAL_VALUED (KNOWN_INPUT)
		time_minute: REAL_VALUED (KNOWN_INPUT)
Interpolating data...
	Dropped segments: 160
	Extracted segments: 152
	Interpolated values: 8003
	Percent of values interpolated: 8.57%
Splitting data...
	Train: 57159 (68.64%)
	Val: 16704 (20.06%)
	Test: 19521 (23.44%)
Scaling data...
	No scaling applied
Data formatting complete.
--------------------------------
Current value: 0.042955994606018066, Current params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.04430016875267029, Current params: {'in_len': 120, 'max_samples_per_ts': 100, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 4, 'dim_feedforward': 288, 'dropout': 0.057776928984841214, 'lr': 0.00018048618080575198, 'batch_size': 64, 'lr_epochs': 14, 'max_grad_norm': 0.8486366521425668}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.05810992419719696, Current params: {'in_len': 132, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 3, 'dim_feedforward': 512, 'dropout': 0.11054412482731012, 'lr': 0.0009378289645869765, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.25684414137061046}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.04759480059146881, Current params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 128, 'n_heads': 2, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 512, 'dropout': 0.14942451133027926, 'lr': 0.00023527361418058018, 'batch_size': 64, 'lr_epochs': 6, 'max_grad_norm': 0.9719646330427882}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.04839235171675682, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 2, 'num_encoder_layers': 2, 'num_decoder_layers': 4, 'dim_feedforward': 224, 'dropout': 0.004367781353979506, 'lr': 0.000493111444669726, 'batch_size': 48, 'lr_epochs': 14, 'max_grad_norm': 0.39321036554153066}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.005287338513880968, Current params: {'in_len': 120, 'max_samples_per_ts': 100, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 192, 'dropout': 0.11328245990687996, 'lr': 0.000506748482537537, 'batch_size': 48, 'lr_epochs': 20, 'max_grad_norm': 0.47509171202888656}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.046090018004179, Current params: {'in_len': 120, 'max_samples_per_ts': 200, 'd_model': 32, 'n_heads': 2, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 256, 'dropout': 0.05417101056212448, 'lr': 0.0006185835601439613, 'batch_size': 48, 'lr_epochs': 10, 'max_grad_norm': 0.23147352678400063}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.051362134516239166, Current params: {'in_len': 132, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 3, 'num_decoder_layers': 4, 'dim_feedforward': 160, 'dropout': 0.047626769212323186, 'lr': 0.0006736566061357285, 'batch_size': 64, 'lr_epochs': 8, 'max_grad_norm': 0.17616192275307052}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.004302743822336197, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 2, 'num_encoder_layers': 2, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.11707118731998996, 'lr': 0.0005766414821459469, 'batch_size': 48, 'lr_epochs': 16, 'max_grad_norm': 0.46008119680180737}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.004221632611006498, Current params: {'in_len': 96, 'max_samples_per_ts': 150, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 512, 'dropout': 0.14770388713619784, 'lr': 0.00029873211816992714, 'batch_size': 48, 'lr_epochs': 12, 'max_grad_norm': 0.4941771766649492}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.0034508469980210066, Current params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 1, 'dim_feedforward': 32, 'dropout': 0.18349584535643695, 'lr': 0.000860242609613537, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.6912004738477766}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.007048389408737421, Current params: {'in_len': 108, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 352, 'dropout': 0.06709812005366332, 'lr': 0.00011081195242087886, 'batch_size': 64, 'lr_epochs': 18, 'max_grad_norm': 0.7434382286010316}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.006258906796574593, Current params: {'in_len': 120, 'max_samples_per_ts': 100, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 320, 'dropout': 0.0778078303493776, 'lr': 0.0007844520617192845, 'batch_size': 64, 'lr_epochs': 6, 'max_grad_norm': 0.998452398094894}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.005125046707689762, Current params: {'in_len': 108, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 2, 'dim_feedforward': 96, 'dropout': 0.02025072913068999, 'lr': 0.00039488002242700927, 'batch_size': 32, 'lr_epochs': 12, 'max_grad_norm': 0.6998704477380169}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.004212080501019955, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 3, 'num_decoder_layers': 4, 'dim_feedforward': 352, 'dropout': 0.08958246190213195, 'lr': 0.0007344753025989182, 'batch_size': 64, 'lr_epochs': 6, 'max_grad_norm': 0.8071259780077483}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.006271200720220804, Current params: {'in_len': 144, 'max_samples_per_ts': 200, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 128, 'dropout': 0.14677473965519644, 'lr': 0.00011607545361607717, 'batch_size': 48, 'lr_epochs': 16, 'max_grad_norm': 0.11363697218219736}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.004617502447217703, Current params: {'in_len': 96, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 1, 'dim_feedforward': 288, 'dropout': 0.19792566279319398, 'lr': 0.0003867825411877495, 'batch_size': 64, 'lr_epochs': 4, 'max_grad_norm': 0.35145995158920945}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.0035550969187170267, 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': 416, 'dropout': 0.035684693487340324, 'lr': 0.0002476718292836225, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.606352935001155}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.004646081477403641, Current params: {'in_len': 120, 'max_samples_per_ts': 100, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 3, 'dim_feedforward': 224, 'dropout': 0.12819644409884282, 'lr': 0.0008189637751595342, 'batch_size': 48, 'lr_epochs': 14, 'max_grad_norm': 0.8288391373841795}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.005587300751358271, Current params: {'in_len': 108, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 3, 'num_decoder_layers': 2, 'dim_feedforward': 64, 'dropout': 0.0911894061416223, 'lr': 0.000980669586776961, 'batch_size': 64, 'lr_epochs': 8, 'max_grad_norm': 0.6049158631111332}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.048323627561330795, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 2, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 160, 'dropout': 0.16720684016760234, 'lr': 0.00042418260337649124, 'batch_size': 48, 'lr_epochs': 20, 'max_grad_norm': 0.8902426062470307}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.046439312398433685, Current params: {'in_len': 120, 'max_samples_per_ts': 200, 'd_model': 32, 'n_heads': 2, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 256, 'dropout': 0.0513952270503499, 'lr': 0.0006361065537652063, 'batch_size': 48, 'lr_epochs': 10, 'max_grad_norm': 0.270124667765655}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.04712263122200966, Current params: {'in_len': 120, 'max_samples_per_ts': 200, 'd_model': 32, 'n_heads': 2, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 288, 'dropout': 0.06513249696090967, 'lr': 0.0006068585973499223, 'batch_size': 48, 'lr_epochs': 14, 'max_grad_norm': 0.2540387812320105}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.04788465052843094, Current params: {'in_len': 132, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 1, 'dim_feedforward': 224, 'dropout': 0.027989150697693848, 'lr': 0.0007143870789888092, 'batch_size': 48, 'lr_epochs': 8, 'max_grad_norm': 0.3419969148885613}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.0034372881054878235, Current params: {'in_len': 120, 'max_samples_per_ts': 200, 'd_model': 32, 'n_heads': 2, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 384, 'dropout': 0.0753257027484773, 'lr': 0.0005347379043590915, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.11641574554494243}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.003284940728917718, Current params: {'in_len': 108, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 3, 'dim_feedforward': 256, 'dropout': 0.051237814471077524, 'lr': 0.0006812942932779749, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.20315167365372178}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.048153966665267944, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'd_model': 32, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 2, 'dim_feedforward': 320, 'dropout': 0.005605003719520177, 'lr': 0.0008775922179895662, 'batch_size': 48, 'lr_epochs': 12, 'max_grad_norm': 0.40758597738439856}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.003427550895139575, Current params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 3, 'dim_feedforward': 128, 'dropout': 0.13136348059942773, 'lr': 0.0004674447041709684, 'batch_size': 64, 'lr_epochs': 10, 'max_grad_norm': 0.5976803219764655}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.048146460205316544, Current params: {'in_len': 132, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 2, 'num_decoder_layers': 1, 'dim_feedforward': 192, 'dropout': 0.09137880496238474, 'lr': 0.0007625113406542891, 'batch_size': 64, 'lr_epochs': 18, 'max_grad_norm': 0.5321595709761092}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.045819830149412155, 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': 320, 'dropout': 0.10598377551438273, 'lr': 0.0003299739225638828, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.20438053073794746}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.04423381760716438, Current params: {'in_len': 132, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 320, 'dropout': 0.10426563681444495, 'lr': 0.0001799345264738928, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.28583043490686805}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.04371677339076996, Current params: {'in_len': 132, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 320, 'dropout': 0.10235055624790454, 'lr': 0.00018569583157253646, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.297878348534472}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.04386915639042854, Current params: {'in_len': 132, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 384, 'dropout': 0.1343618936515883, 'lr': 0.00018420265484915253, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.31148161235709176}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.04772774875164032, Current params: {'in_len': 132, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 448, 'dropout': 0.12827852664691358, 'lr': 0.0001855053418680577, 'batch_size': 32, 'lr_epochs': 4, 'max_grad_norm': 0.30796104696020765}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.0032234496902674437, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 384, 'dropout': 0.16154447408154335, 'lr': 0.00020773284892819082, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.412196630044247}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.003514744807034731, Current params: {'in_len': 132, 'max_samples_per_ts': 50, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 384, 'dropout': 0.11753161813129002, 'lr': 0.0002975134329748423, 'batch_size': 32, 'lr_epochs': 4, 'max_grad_norm': 0.29658262338010777}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.04373675957322121, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 448, 'dropout': 0.13832088097852532, 'lr': 0.00015064899996443046, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.16749600953634347}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.04941951856017113, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.13737544433231152, 'lr': 0.0002579690599757546, 'batch_size': 32, 'lr_epochs': 4, 'max_grad_norm': 0.1543036844721205}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.04454353079199791, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 416, 'dropout': 0.1614875263056717, 'lr': 0.00010010418902701575, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.36425668073360395}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.003024262608960271, Current params: {'in_len': 132, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.14296620949259847, 'lr': 0.00017506732211476723, 'batch_size': 32, 'lr_epochs': 6, 'max_grad_norm': 0.16558924972735922}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.045783936977386475, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 416, 'dropout': 0.17544120541575495, 'lr': 0.00014924183258120408, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.23506610921523155}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.003007650375366211, Current params: {'in_len': 132, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 352, 'dropout': 0.09995253574650259, 'lr': 0.00023056515531093833, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.20172418143046267}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.003160974709317088, Current params: {'in_len': 132, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 448, 'dropout': 0.12156211671280232, 'lr': 0.00015952003144782716, 'batch_size': 32, 'lr_epochs': 4, 'max_grad_norm': 0.2951988924231292}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.04577590152621269, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 320, 'dropout': 0.10814818609106822, 'lr': 0.0002928448265331106, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.4574855236412213}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.004344544839113951, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 352, 'dropout': 0.09983225272696579, 'lr': 0.00034616502678753037, 'batch_size': 32, 'lr_epochs': 4, 'max_grad_norm': 0.3225263291511656}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.0033871729392558336, Current params: {'in_len': 132, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 480, 'dropout': 0.12378138210547424, 'lr': 0.00014394242736811067, 'batch_size': 32, 'lr_epochs': 6, 'max_grad_norm': 0.13355645405944927}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.005673024337738752, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 288, 'dropout': 0.15290534195399516, 'lr': 0.0002121299379004927, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.256740972625742}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.055395130068063736, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 2, 'dim_feedforward': 192, 'dropout': 0.13953684333301414, 'lr': 0.00027262258869348364, 'batch_size': 32, 'lr_epochs': 6, 'max_grad_norm': 0.38282717940806854}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.049036167562007904, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 384, 'dropout': 0.08342332594900276, 'lr': 0.0001329722227931847, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.18341006656853912}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.004989004693925381, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 4, 'dim_feedforward': 320, 'dropout': 0.11704789801441311, 'lr': 0.0003461464713269607, 'batch_size': 32, 'lr_epochs': 4, 'max_grad_norm': 0.445590319620288}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.00591216329485178, Current params: {'in_len': 144, 'max_samples_per_ts': 100, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 416, 'dropout': 0.152513914816004, 'lr': 0.00019764069154587364, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.2301436784598371}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.002991524524986744, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 4, 'dim_feedforward': 288, 'dropout': 0.11156452725597879, 'lr': 0.000225696388472875, 'batch_size': 48, 'lr_epochs': 2, 'max_grad_norm': 0.9107914803513}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.006643956992775202, Current params: {'in_len': 120, 'max_samples_per_ts': 150, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 256, 'dropout': 0.10523368786070396, 'lr': 0.00017173635061513667, 'batch_size': 64, 'lr_epochs': 2, 'max_grad_norm': 0.5012555111195411}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.006875572260469198, Current params: {'in_len': 120, 'max_samples_per_ts': 150, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 224, 'dropout': 0.09401248898281357, 'lr': 0.00010140176676296268, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.27843006018870214}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.006727935746312141, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 3, 'dim_feedforward': 352, 'dropout': 0.06441722560512204, 'lr': 0.00025596148092422376, 'batch_size': 64, 'lr_epochs': 12, 'max_grad_norm': 0.33426057041261903}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.003029701765626669, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 2, 'dim_feedforward': 512, 'dropout': 0.1353033681140695, 'lr': 0.00045322892767508916, 'batch_size': 32, 'lr_epochs': 6, 'max_grad_norm': 0.7018930949700168}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.049131251871585846, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 288, 'dropout': 0.08044976494539172, 'lr': 0.0001398256547899831, 'batch_size': 48, 'lr_epochs': 14, 'max_grad_norm': 0.13723029403076523}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.0035072029568254948, Current params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 3, 'dim_feedforward': 352, 'dropout': 0.041755177993223945, 'lr': 0.0005812298708621631, 'batch_size': 32, 'lr_epochs': 4, 'max_grad_norm': 0.7687818733492633}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.0034985006786882877, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.1244740927697712, 'lr': 0.00032860598500855187, 'batch_size': 48, 'lr_epochs': 2, 'max_grad_norm': 0.9438212488635251}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.004480279982089996, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 160, 'dropout': 0.07383335212939907, 'lr': 0.0003959647489507403, 'batch_size': 64, 'lr_epochs': 16, 'max_grad_norm': 0.10793718094368944}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.004713078495115042, Current params: {'in_len': 120, 'max_samples_per_ts': 150, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 2, 'dim_feedforward': 256, 'dropout': 0.11595118708588759, 'lr': 0.0005312064013629585, 'batch_size': 48, 'lr_epochs': 14, 'max_grad_norm': 0.6422795390605102}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.04473792389035225, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 416, 'dropout': 0.16227648883327406, 'lr': 0.00011548967426830557, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.35291754141189674}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.047791432589292526, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 384, 'dropout': 0.17549907234689316, 'lr': 0.00018847610925830903, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.3703491725608896}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.04834657534956932, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 416, 'dropout': 0.1540837561490247, 'lr': 0.00011114438989176481, 'batch_size': 32, 'lr_epochs': 18, 'max_grad_norm': 0.24685522973655277}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.0031298098620027304, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 320, 'dropout': 0.13228523878253393, 'lr': 0.00022998454747752666, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.4322001765096968}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.04978054389357567, Current params: {'in_len': 132, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 192, 'dropout': 0.1435487135427205, 'lr': 0.00015904337669412814, 'batch_size': 32, 'lr_epochs': 4, 'max_grad_norm': 0.21770600199284668}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.04631077125668526, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 32, 'dropout': 0.18685836960467833, 'lr': 0.0006487672827757895, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.30085859129638276}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.003822174621745944, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 448, 'dropout': 0.0606847220413871, 'lr': 0.0008172046484216107, 'batch_size': 32, 'lr_epochs': 4, 'max_grad_norm': 0.276248968847709}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.003060717834159732, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 224, 'dropout': 0.15849822357104681, 'lr': 0.00027750015367125305, 'batch_size': 48, 'lr_epochs': 2, 'max_grad_norm': 0.17450508410788138}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.005858570337295532, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 384, 'dropout': 0.16855405386388003, 'lr': 0.00019741359432433767, 'batch_size': 32, 'lr_epochs': 4, 'max_grad_norm': 0.48631384238163566}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.0030160206370055676, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 352, 'dropout': 0.1490813437246274, 'lr': 0.00012276252406439252, 'batch_size': 64, 'lr_epochs': 8, 'max_grad_norm': 0.8510292425519295}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.04409179091453552, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 416, 'dropout': 0.16925167536410615, 'lr': 0.00011900774428557204, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.3479431395367428}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.04617607593536377, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 480, 'dropout': 0.19077979343173115, 'lr': 0.00016982568057449085, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.4013181595411543}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.003031511092558503, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 448, 'dropout': 0.17623498014629738, 'lr': 0.00010149921020968283, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.35611822663792325}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.046315740793943405, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 416, 'dropout': 0.1692237095595315, 'lr': 0.0001401375433915458, 'batch_size': 32, 'lr_epochs': 4, 'max_grad_norm': 0.319319065768281}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.04646562784910202, Current params: {'in_len': 132, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 384, 'dropout': 0.08565341979948368, 'lr': 0.00024425621422811684, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.2725009334341174}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.05520855635404587, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 320, 'dropout': 0.14327289285588918, 'lr': 0.000699306179741016, 'batch_size': 32, 'lr_epochs': 20, 'max_grad_norm': 0.3788080359317892}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.048562511801719666, Current params: {'in_len': 132, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 288, 'dropout': 0.01404708160408822, 'lr': 0.00020686008475510653, 'batch_size': 32, 'lr_epochs': 4, 'max_grad_norm': 0.1919865519395233}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.0034460604656487703, Current params: {'in_len': 108, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 2, 'dim_feedforward': 352, 'dropout': 0.09720484543384503, 'lr': 0.0009261273860937754, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.5331396524774393}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.003026302671059966, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 512, 'dropout': 0.10452824016736864, 'lr': 0.0001560483019356235, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.24573555162920724}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.04306700453162193, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 1, 'dim_feedforward': 64, 'dropout': 0.12751312720608174, 'lr': 0.00018488941605566001, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22217834676393672}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.04580993205308914, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 1, 'dim_feedforward': 96, 'dropout': 0.1291543224274309, 'lr': 0.00018174934051178184, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.3296089064125385}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.045677244663238525, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 1, 'dim_feedforward': 128, 'dropout': 0.1217155931265685, 'lr': 0.00021268035270179326, 'batch_size': 48, 'lr_epochs': 6, 'max_grad_norm': 0.2241268402173464}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.002970660338178277, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 2, 'dim_feedforward': 64, 'dropout': 0.13327548911421033, 'lr': 0.00013214347804685746, 'batch_size': 48, 'lr_epochs': 2, 'max_grad_norm': 0.15276030580040967}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.0030900149140506983, Current params: {'in_len': 132, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 64, 'dropout': 0.11082362132095674, 'lr': 0.00017619754493772074, 'batch_size': 48, 'lr_epochs': 2, 'max_grad_norm': 0.27612257826800307}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.05228382349014282, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 416, 'dropout': 0.13817303233128275, 'lr': 0.000741711435464878, 'batch_size': 64, 'lr_epochs': 4, 'max_grad_norm': 0.3011930573757239}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.050759900361299515, Current params: {'in_len': 132, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 1, 'dim_feedforward': 256, 'dropout': 0.12624380137043828, 'lr': 0.0002632109472352078, 'batch_size': 32, 'lr_epochs': 6, 'max_grad_norm': 0.4244682412240165}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.0029870776925235987, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 448, 'dropout': 0.19899074535191702, 'lr': 0.0002347059934403917, 'batch_size': 48, 'lr_epochs': 10, 'max_grad_norm': 0.2110504013367632}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.006860410328954458, Current params: {'in_len': 120, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 4, 'dim_feedforward': 96, 'dropout': 0.11997514660749464, 'lr': 0.00012755121210886883, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.9968314746567604}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.005823710933327675, Current params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 2, 'dim_feedforward': 320, 'dropout': 0.15815411182739092, 'lr': 0.0003084353067378955, 'batch_size': 48, 'lr_epochs': 12, 'max_grad_norm': 0.25146333988177294}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.0031313945073634386, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 160, 'dropout': 0.181014756837346, 'lr': 0.00016042287025694384, 'batch_size': 32, 'lr_epochs': 4, 'max_grad_norm': 0.19084093256463727}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.0034270365722477436, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 416, 'dropout': 0.1635824809595795, 'lr': 0.00012359561887283316, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.3521197326545249}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.04499299079179764, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 416, 'dropout': 0.16445226004111652, 'lr': 0.00010720742373807081, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.3644287414863933}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.044485289603471756, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 480, 'dropout': 0.15581615534485696, 'lr': 0.00015172476029266823, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.3921087433355233}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.003167186165228486, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 480, 'dropout': 0.14867398712275243, 'lr': 0.0001483292578378402, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.3858316831655727}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.05105547606945038, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 480, 'dropout': 0.15682817397413962, 'lr': 0.00020627302897979074, 'batch_size': 32, 'lr_epochs': 4, 'max_grad_norm': 0.31605677581570474}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.003002312034368515, Current params: {'in_len': 132, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 288, 'dropout': 0.11366594680087658, 'lr': 0.00018821780138532476, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.2866874690262127}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.04494105279445648, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 384, 'dropout': 0.14331142811206304, 'lr': 0.00022243779121334983, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.5738966033907948}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.0031040797475725412, Current params: {'in_len': 144, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.10370575380373652, 'lr': 0.0001705218562183008, 'batch_size': 32, 'lr_epochs': 4, 'max_grad_norm': 0.2639243763648014}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
Current value: 0.0037662237882614136, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 512, 'dropout': 0.08940650457260026, 'lr': 0.00014102765861280812, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.23231767987412805}
Best value: 0.042955994606018066, Best params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.1260638882066075, 'lr': 0.0006944648317764303, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.22914229299130273}
--------------------------------
Loading column definition...
Checking column definition...
Loading data...
Dropping columns / rows...
Checking for NA values...
Setting data types...
Dropping columns / rows...
Encoding data...
	Updated column definition:
		id: REAL_VALUED (ID)
		time: DATE (TIME)
		gl: REAL_VALUED (TARGET)
		Age: REAL_VALUED (STATIC_INPUT)
		BMI: REAL_VALUED (STATIC_INPUT)
		A1C: REAL_VALUED (STATIC_INPUT)
		FBG: REAL_VALUED (STATIC_INPUT)
		ogtt.2hr: REAL_VALUED (STATIC_INPUT)
		insulin: REAL_VALUED (STATIC_INPUT)
		hs.CRP: REAL_VALUED (STATIC_INPUT)
		Tchol: REAL_VALUED (STATIC_INPUT)
		Trg: REAL_VALUED (STATIC_INPUT)
		HDL: REAL_VALUED (STATIC_INPUT)
		LDL: REAL_VALUED (STATIC_INPUT)
		mean_glucose: REAL_VALUED (STATIC_INPUT)
		sd_glucose: REAL_VALUED (STATIC_INPUT)
		range_glucose: REAL_VALUED (STATIC_INPUT)
		min_glucose: REAL_VALUED (STATIC_INPUT)
		max_glucose: REAL_VALUED (STATIC_INPUT)
		quartile.25_glucose: REAL_VALUED (STATIC_INPUT)
		median_glucose: REAL_VALUED (STATIC_INPUT)
		quartile.75_glucose: REAL_VALUED (STATIC_INPUT)
		mean_slope: REAL_VALUED (STATIC_INPUT)
		max_slope: REAL_VALUED (STATIC_INPUT)
		number_Random140: REAL_VALUED (STATIC_INPUT)
		number_Random200: REAL_VALUED (STATIC_INPUT)
		percent_below.80: REAL_VALUED (STATIC_INPUT)
		se_glucose_mean: REAL_VALUED (STATIC_INPUT)
		numGE: REAL_VALUED (STATIC_INPUT)
		mage: REAL_VALUED (STATIC_INPUT)
		j_index: REAL_VALUED (STATIC_INPUT)
		IQR: REAL_VALUED (STATIC_INPUT)
		modd: REAL_VALUED (STATIC_INPUT)
		distance_traveled: REAL_VALUED (STATIC_INPUT)
		coef_variation: REAL_VALUED (STATIC_INPUT)
		number_Random140_normByDays: REAL_VALUED (STATIC_INPUT)
		number_Random200_normByDays: REAL_VALUED (STATIC_INPUT)
		numGE_normByDays: REAL_VALUED (STATIC_INPUT)
		distance_traveled_normByDays: REAL_VALUED (STATIC_INPUT)
		diagnosis: REAL_VALUED (STATIC_INPUT)
		freq_low: REAL_VALUED (STATIC_INPUT)
		freq_moderate: REAL_VALUED (STATIC_INPUT)
		freq_severe: REAL_VALUED (STATIC_INPUT)
		glucotype: REAL_VALUED (STATIC_INPUT)
		Height: REAL_VALUED (STATIC_INPUT)
		Weight: REAL_VALUED (STATIC_INPUT)
		Insulin_rate_dd: REAL_VALUED (STATIC_INPUT)
		perc_cgm_prediabetic_range: REAL_VALUED (STATIC_INPUT)
		perc_cgm_diabetic_range: REAL_VALUED (STATIC_INPUT)
		SSPG: REAL_VALUED (STATIC_INPUT)
		time_year: REAL_VALUED (KNOWN_INPUT)
		time_month: REAL_VALUED (KNOWN_INPUT)
		time_day: REAL_VALUED (KNOWN_INPUT)
		time_hour: REAL_VALUED (KNOWN_INPUT)
		time_minute: REAL_VALUED (KNOWN_INPUT)
Interpolating data...
	Dropped segments: 160
	Extracted segments: 152
	Interpolated values: 8003
	Percent of values interpolated: 8.57%
Splitting data...
	Train: 62461 (61.57%)
	Val: 12357 (12.18%)
	Test: 16517 (16.28%)
	Test OOD: 10113 (9.97%)
Scaling data...
	No scaling applied
Data formatting complete.
--------------------------------
	Train: 62090 (61.20%)
	Val: 12502 (12.32%)
	Test: 16648 (16.41%)
	Test OOD: 10208 (10.06%)
	No scaling applied
		Model Seed: 10 Seed: 1 ID mean of (MSE, MAE): [210.07312   9.16257]
		Model Seed: 10 Seed: 1 OOD mean of (MSE, MAE) stats: [162.04483    8.353693]
		Model Seed: 10 Seed: 1 ID median of (MSE, MAE): [57.761513   6.5221977]
		Model Seed: 10 Seed: 1 OOD median of (MSE, MAE) stats: [52.119823   6.1763673]
		Model Seed: 10 Seed: 1 ID likelihoods: -9.592665891646622
		Model Seed: 10 Seed: 1 OOD likelihoods: -9.462874246477025
		Model Seed: 10 Seed: 1 ID calibration errors: [0.41399417 0.25869652 0.15376482 0.09746485 0.06605577 0.04499067
 0.02658605 0.01849882 0.01428915 0.01154711 0.0094604  0.00948914]
		Model Seed: 10 Seed: 1 OOD calibration errors: [0.33459899 0.20438867 0.12042451 0.07294328 0.0527977  0.03073174
 0.01948723 0.01351278 0.0125986  0.01181499 0.00900278 0.01320604]
	Train: 64804 (63.70%)
	Val: 12349 (12.14%)
	Test: 16419 (16.14%)
	Test OOD: 8164 (8.02%)
	No scaling applied
		Model Seed: 10 Seed: 2 ID mean of (MSE, MAE): [212.11511    9.043722]
		Model Seed: 10 Seed: 2 OOD mean of (MSE, MAE) stats: [178.09016    8.834377]
		Model Seed: 10 Seed: 2 ID median of (MSE, MAE): [54.40263    6.3131394]
		Model Seed: 10 Seed: 2 OOD median of (MSE, MAE) stats: [57.41255    6.4086003]
		Model Seed: 10 Seed: 2 ID likelihoods: -9.597502584589698
		Model Seed: 10 Seed: 2 OOD likelihoods: -9.510082529085453
		Model Seed: 10 Seed: 2 ID calibration errors: [0.40543156 0.26476678 0.17030007 0.10925195 0.06712617 0.04776706
 0.03142846 0.02298064 0.01746996 0.01288794 0.01059768 0.00790803]
		Model Seed: 10 Seed: 2 OOD calibration errors: [0.38531559 0.23830716 0.14191856 0.09139689 0.05593118 0.04191057
 0.03057206 0.02099966 0.01892405 0.01569858 0.01519399 0.01201692]
	Model Seed: 10 ID mean of (MSE, MAE): [211.09412    9.103146]
	Model Seed: 10 OOD mean of (MSE, MAE): [170.0675     8.594035]
	Model Seed: 10 ID median of (MSE, MAE): [56.08207    6.4176683]
	Model Seed: 10 OOD median of (MSE, MAE): [54.76619   6.292484]
	Model Seed: 10 ID likelihoods: -9.59508423811816
	Model Seed: 10 OOD likelihoods: -9.48647838778124
	Model Seed: 10 ID calibration errors: [0.40971287 0.26173165 0.16203244 0.1033584  0.06659097 0.04637886
 0.02900725 0.02073973 0.01587956 0.01221752 0.01002904 0.00869859]
	Model Seed: 10 OOD calibration errors: [0.35995729 0.22134792 0.13117154 0.08217009 0.05436444 0.03632115
 0.02502965 0.01725622 0.01576133 0.01375679 0.01209838 0.01261148]
	Train: 62090 (61.20%)
	Val: 12502 (12.32%)
	Test: 16648 (16.41%)
	Test OOD: 10208 (10.06%)
	No scaling applied
		Model Seed: 11 Seed: 1 ID mean of (MSE, MAE): [210.07312   9.16257]
		Model Seed: 11 Seed: 1 OOD mean of (MSE, MAE) stats: [162.04483    8.353693]
		Model Seed: 11 Seed: 1 ID median of (MSE, MAE): [57.761513   6.5221977]
		Model Seed: 11 Seed: 1 OOD median of (MSE, MAE) stats: [52.119823   6.1763673]
		Model Seed: 11 Seed: 1 ID likelihoods: -9.592665891646622
		Model Seed: 11 Seed: 1 OOD likelihoods: -9.462874246477025
		Model Seed: 11 Seed: 1 ID calibration errors: [0.41399417 0.25869652 0.15376482 0.09746485 0.06605577 0.04499067
 0.02658605 0.01849882 0.01428915 0.01154711 0.0094604  0.00948914]
		Model Seed: 11 Seed: 1 OOD calibration errors: [0.33459899 0.20438867 0.12042451 0.07294328 0.0527977  0.03073174
 0.01948723 0.01351278 0.0125986  0.01181499 0.00900278 0.01320604]
	Train: 64804 (63.70%)
	Val: 12349 (12.14%)
	Test: 16419 (16.14%)
	Test OOD: 8164 (8.02%)
	No scaling applied
		Model Seed: 11 Seed: 2 ID mean of (MSE, MAE): [212.11511    9.043722]
		Model Seed: 11 Seed: 2 OOD mean of (MSE, MAE) stats: [178.09016    8.834377]
		Model Seed: 11 Seed: 2 ID median of (MSE, MAE): [54.40263    6.3131394]
		Model Seed: 11 Seed: 2 OOD median of (MSE, MAE) stats: [57.41255    6.4086003]
		Model Seed: 11 Seed: 2 ID likelihoods: -9.597502584589698
		Model Seed: 11 Seed: 2 OOD likelihoods: -9.510082529085453
		Model Seed: 11 Seed: 2 ID calibration errors: [0.40543156 0.26476678 0.17030007 0.10925195 0.06712617 0.04776706
 0.03142846 0.02298064 0.01746996 0.01288794 0.01059768 0.00790803]
		Model Seed: 11 Seed: 2 OOD calibration errors: [0.38531559 0.23830716 0.14191856 0.09139689 0.05593118 0.04191057
 0.03057206 0.02099966 0.01892405 0.01569858 0.01519399 0.01201692]
	Model Seed: 11 ID mean of (MSE, MAE): [211.09412    9.103146]
	Model Seed: 11 OOD mean of (MSE, MAE): [170.0675     8.594035]
	Model Seed: 11 ID median of (MSE, MAE): [56.08207    6.4176683]
	Model Seed: 11 OOD median of (MSE, MAE): [54.76619   6.292484]
	Model Seed: 11 ID likelihoods: -9.59508423811816
	Model Seed: 11 OOD likelihoods: -9.48647838778124
	Model Seed: 11 ID calibration errors: [0.40971287 0.26173165 0.16203244 0.1033584  0.06659097 0.04637886
 0.02900725 0.02073973 0.01587956 0.01221752 0.01002904 0.00869859]
	Model Seed: 11 OOD calibration errors: [0.35995729 0.22134792 0.13117154 0.08217009 0.05436444 0.03632115
 0.02502965 0.01725622 0.01576133 0.01375679 0.01209838 0.01261148]
	Train: 62090 (61.20%)
	Val: 12502 (12.32%)
	Test: 16648 (16.41%)
	Test OOD: 10208 (10.06%)
	No scaling applied
		Model Seed: 12 Seed: 1 ID mean of (MSE, MAE): [210.07312   9.16257]
		Model Seed: 12 Seed: 1 OOD mean of (MSE, MAE) stats: [162.04483    8.353693]
		Model Seed: 12 Seed: 1 ID median of (MSE, MAE): [57.761513   6.5221977]
		Model Seed: 12 Seed: 1 OOD median of (MSE, MAE) stats: [52.119823   6.1763673]
		Model Seed: 12 Seed: 1 ID likelihoods: -9.592665891646622
		Model Seed: 12 Seed: 1 OOD likelihoods: -9.462874246477025
		Model Seed: 12 Seed: 1 ID calibration errors: [0.41399417 0.25869652 0.15376482 0.09746485 0.06605577 0.04499067
 0.02658605 0.01849882 0.01428915 0.01154711 0.0094604  0.00948914]
		Model Seed: 12 Seed: 1 OOD calibration errors: [0.33459899 0.20438867 0.12042451 0.07294328 0.0527977  0.03073174
 0.01948723 0.01351278 0.0125986  0.01181499 0.00900278 0.01320604]
	Train: 64804 (63.70%)
	Val: 12349 (12.14%)
	Test: 16419 (16.14%)
	Test OOD: 8164 (8.02%)
	No scaling applied
		Model Seed: 12 Seed: 2 ID mean of (MSE, MAE): [212.11511    9.043722]
		Model Seed: 12 Seed: 2 OOD mean of (MSE, MAE) stats: [178.09016    8.834377]
		Model Seed: 12 Seed: 2 ID median of (MSE, MAE): [54.40263    6.3131394]
		Model Seed: 12 Seed: 2 OOD median of (MSE, MAE) stats: [57.41255    6.4086003]
		Model Seed: 12 Seed: 2 ID likelihoods: -9.597502584589698
		Model Seed: 12 Seed: 2 OOD likelihoods: -9.510082529085453
		Model Seed: 12 Seed: 2 ID calibration errors: [0.40543156 0.26476678 0.17030007 0.10925195 0.06712617 0.04776706
 0.03142846 0.02298064 0.01746996 0.01288794 0.01059768 0.00790803]
		Model Seed: 12 Seed: 2 OOD calibration errors: [0.38531559 0.23830716 0.14191856 0.09139689 0.05593118 0.04191057
 0.03057206 0.02099966 0.01892405 0.01569858 0.01519399 0.01201692]
	Model Seed: 12 ID mean of (MSE, MAE): [211.09412    9.103146]
	Model Seed: 12 OOD mean of (MSE, MAE): [170.0675     8.594035]
	Model Seed: 12 ID median of (MSE, MAE): [56.08207    6.4176683]
	Model Seed: 12 OOD median of (MSE, MAE): [54.76619   6.292484]
	Model Seed: 12 ID likelihoods: -9.59508423811816
	Model Seed: 12 OOD likelihoods: -9.48647838778124
	Model Seed: 12 ID calibration errors: [0.40971287 0.26173165 0.16203244 0.1033584  0.06659097 0.04637886
 0.02900725 0.02073973 0.01587956 0.01221752 0.01002904 0.00869859]
	Model Seed: 12 OOD calibration errors: [0.35995729 0.22134792 0.13117154 0.08217009 0.05436444 0.03632115
 0.02502965 0.01725622 0.01576133 0.01375679 0.01209838 0.01261148]
	Train: 62090 (61.20%)
	Val: 12502 (12.32%)
	Test: 16648 (16.41%)
	Test OOD: 10208 (10.06%)
	No scaling applied
		Model Seed: 13 Seed: 1 ID mean of (MSE, MAE): [210.07312   9.16257]
		Model Seed: 13 Seed: 1 OOD mean of (MSE, MAE) stats: [162.04483    8.353693]
		Model Seed: 13 Seed: 1 ID median of (MSE, MAE): [57.761513   6.5221977]
		Model Seed: 13 Seed: 1 OOD median of (MSE, MAE) stats: [52.119823   6.1763673]
		Model Seed: 13 Seed: 1 ID likelihoods: -9.592665891646622
		Model Seed: 13 Seed: 1 OOD likelihoods: -9.462874246477025
		Model Seed: 13 Seed: 1 ID calibration errors: [0.41399417 0.25869652 0.15376482 0.09746485 0.06605577 0.04499067
 0.02658605 0.01849882 0.01428915 0.01154711 0.0094604  0.00948914]
		Model Seed: 13 Seed: 1 OOD calibration errors: [0.33459899 0.20438867 0.12042451 0.07294328 0.0527977  0.03073174
 0.01948723 0.01351278 0.0125986  0.01181499 0.00900278 0.01320604]
	Train: 64804 (63.70%)
	Val: 12349 (12.14%)
	Test: 16419 (16.14%)
	Test OOD: 8164 (8.02%)
	No scaling applied
		Model Seed: 13 Seed: 2 ID mean of (MSE, MAE): [212.11511    9.043722]
		Model Seed: 13 Seed: 2 OOD mean of (MSE, MAE) stats: [178.09016    8.834377]
		Model Seed: 13 Seed: 2 ID median of (MSE, MAE): [54.40263    6.3131394]
		Model Seed: 13 Seed: 2 OOD median of (MSE, MAE) stats: [57.41255    6.4086003]
		Model Seed: 13 Seed: 2 ID likelihoods: -9.597502584589698
		Model Seed: 13 Seed: 2 OOD likelihoods: -9.510082529085453
		Model Seed: 13 Seed: 2 ID calibration errors: [0.40543156 0.26476678 0.17030007 0.10925195 0.06712617 0.04776706
 0.03142846 0.02298064 0.01746996 0.01288794 0.01059768 0.00790803]
		Model Seed: 13 Seed: 2 OOD calibration errors: [0.38531559 0.23830716 0.14191856 0.09139689 0.05593118 0.04191057
 0.03057206 0.02099966 0.01892405 0.01569858 0.01519399 0.01201692]
	Model Seed: 13 ID mean of (MSE, MAE): [211.09412    9.103146]
	Model Seed: 13 OOD mean of (MSE, MAE): [170.0675     8.594035]
	Model Seed: 13 ID median of (MSE, MAE): [56.08207    6.4176683]
	Model Seed: 13 OOD median of (MSE, MAE): [54.76619   6.292484]
	Model Seed: 13 ID likelihoods: -9.59508423811816
	Model Seed: 13 OOD likelihoods: -9.48647838778124
	Model Seed: 13 ID calibration errors: [0.40971287 0.26173165 0.16203244 0.1033584  0.06659097 0.04637886
 0.02900725 0.02073973 0.01587956 0.01221752 0.01002904 0.00869859]
	Model Seed: 13 OOD calibration errors: [0.35995729 0.22134792 0.13117154 0.08217009 0.05436444 0.03632115
 0.02502965 0.01725622 0.01576133 0.01375679 0.01209838 0.01261148]
	Train: 62090 (61.20%)
	Val: 12502 (12.32%)
	Test: 16648 (16.41%)
	Test OOD: 10208 (10.06%)
	No scaling applied
		Model Seed: 14 Seed: 1 ID mean of (MSE, MAE): [210.07312   9.16257]
		Model Seed: 14 Seed: 1 OOD mean of (MSE, MAE) stats: [162.04483    8.353693]
		Model Seed: 14 Seed: 1 ID median of (MSE, MAE): [57.761513   6.5221977]
		Model Seed: 14 Seed: 1 OOD median of (MSE, MAE) stats: [52.119823   6.1763673]
		Model Seed: 14 Seed: 1 ID likelihoods: -9.592665891646622
		Model Seed: 14 Seed: 1 OOD likelihoods: -9.462874246477025
		Model Seed: 14 Seed: 1 ID calibration errors: [0.41399417 0.25869652 0.15376482 0.09746485 0.06605577 0.04499067
 0.02658605 0.01849882 0.01428915 0.01154711 0.0094604  0.00948914]
		Model Seed: 14 Seed: 1 OOD calibration errors: [0.33459899 0.20438867 0.12042451 0.07294328 0.0527977  0.03073174
 0.01948723 0.01351278 0.0125986  0.01181499 0.00900278 0.01320604]
	Train: 64804 (63.70%)
	Val: 12349 (12.14%)
	Test: 16419 (16.14%)
	Test OOD: 8164 (8.02%)
	No scaling applied
		Model Seed: 14 Seed: 2 ID mean of (MSE, MAE): [212.11511    9.043722]
		Model Seed: 14 Seed: 2 OOD mean of (MSE, MAE) stats: [178.09016    8.834377]
		Model Seed: 14 Seed: 2 ID median of (MSE, MAE): [54.40263    6.3131394]
		Model Seed: 14 Seed: 2 OOD median of (MSE, MAE) stats: [57.41255    6.4086003]
		Model Seed: 14 Seed: 2 ID likelihoods: -9.597502584589698
		Model Seed: 14 Seed: 2 OOD likelihoods: -9.510082529085453
		Model Seed: 14 Seed: 2 ID calibration errors: [0.40543156 0.26476678 0.17030007 0.10925195 0.06712617 0.04776706
 0.03142846 0.02298064 0.01746996 0.01288794 0.01059768 0.00790803]
		Model Seed: 14 Seed: 2 OOD calibration errors: [0.38531559 0.23830716 0.14191856 0.09139689 0.05593118 0.04191057
 0.03057206 0.02099966 0.01892405 0.01569858 0.01519399 0.01201692]
	Model Seed: 14 ID mean of (MSE, MAE): [211.09412    9.103146]
	Model Seed: 14 OOD mean of (MSE, MAE): [170.0675     8.594035]
	Model Seed: 14 ID median of (MSE, MAE): [56.08207    6.4176683]
	Model Seed: 14 OOD median of (MSE, MAE): [54.76619   6.292484]
	Model Seed: 14 ID likelihoods: -9.59508423811816
	Model Seed: 14 OOD likelihoods: -9.48647838778124
	Model Seed: 14 ID calibration errors: [0.40971287 0.26173165 0.16203244 0.1033584  0.06659097 0.04637886
 0.02900725 0.02073973 0.01587956 0.01221752 0.01002904 0.00869859]
	Model Seed: 14 OOD calibration errors: [0.35995729 0.22134792 0.13117154 0.08217009 0.05436444 0.03632115
 0.02502965 0.01725622 0.01576133 0.01375679 0.01209838 0.01261148]
	Train: 62090 (61.20%)
	Val: 12502 (12.32%)
	Test: 16648 (16.41%)
	Test OOD: 10208 (10.06%)
	No scaling applied
		Model Seed: 15 Seed: 1 ID mean of (MSE, MAE): [210.07312   9.16257]
		Model Seed: 15 Seed: 1 OOD mean of (MSE, MAE) stats: [162.04483    8.353693]
		Model Seed: 15 Seed: 1 ID median of (MSE, MAE): [57.761513   6.5221977]
		Model Seed: 15 Seed: 1 OOD median of (MSE, MAE) stats: [52.119823   6.1763673]
		Model Seed: 15 Seed: 1 ID likelihoods: -9.592665891646622
		Model Seed: 15 Seed: 1 OOD likelihoods: -9.462874246477025
		Model Seed: 15 Seed: 1 ID calibration errors: [0.41399417 0.25869652 0.15376482 0.09746485 0.06605577 0.04499067
 0.02658605 0.01849882 0.01428915 0.01154711 0.0094604  0.00948914]
		Model Seed: 15 Seed: 1 OOD calibration errors: [0.33459899 0.20438867 0.12042451 0.07294328 0.0527977  0.03073174
 0.01948723 0.01351278 0.0125986  0.01181499 0.00900278 0.01320604]
	Train: 64804 (63.70%)
	Val: 12349 (12.14%)
	Test: 16419 (16.14%)
	Test OOD: 8164 (8.02%)
	No scaling applied
		Model Seed: 15 Seed: 2 ID mean of (MSE, MAE): [212.11511    9.043722]
		Model Seed: 15 Seed: 2 OOD mean of (MSE, MAE) stats: [178.09016    8.834377]
		Model Seed: 15 Seed: 2 ID median of (MSE, MAE): [54.40263    6.3131394]
		Model Seed: 15 Seed: 2 OOD median of (MSE, MAE) stats: [57.41255    6.4086003]
		Model Seed: 15 Seed: 2 ID likelihoods: -9.597502584589698
		Model Seed: 15 Seed: 2 OOD likelihoods: -9.510082529085453
		Model Seed: 15 Seed: 2 ID calibration errors: [0.40543156 0.26476678 0.17030007 0.10925195 0.06712617 0.04776706
 0.03142846 0.02298064 0.01746996 0.01288794 0.01059768 0.00790803]
		Model Seed: 15 Seed: 2 OOD calibration errors: [0.38531559 0.23830716 0.14191856 0.09139689 0.05593118 0.04191057
 0.03057206 0.02099966 0.01892405 0.01569858 0.01519399 0.01201692]
	Model Seed: 15 ID mean of (MSE, MAE): [211.09412    9.103146]
	Model Seed: 15 OOD mean of (MSE, MAE): [170.0675     8.594035]
	Model Seed: 15 ID median of (MSE, MAE): [56.08207    6.4176683]
	Model Seed: 15 OOD median of (MSE, MAE): [54.76619   6.292484]
	Model Seed: 15 ID likelihoods: -9.59508423811816
	Model Seed: 15 OOD likelihoods: -9.48647838778124
	Model Seed: 15 ID calibration errors: [0.40971287 0.26173165 0.16203244 0.1033584  0.06659097 0.04637886
 0.02900725 0.02073973 0.01587956 0.01221752 0.01002904 0.00869859]
	Model Seed: 15 OOD calibration errors: [0.35995729 0.22134792 0.13117154 0.08217009 0.05436444 0.03632115
 0.02502965 0.01725622 0.01576133 0.01375679 0.01209838 0.01261148]
	Train: 62090 (61.20%)
	Val: 12502 (12.32%)
	Test: 16648 (16.41%)
	Test OOD: 10208 (10.06%)
	No scaling applied
		Model Seed: 16 Seed: 1 ID mean of (MSE, MAE): [210.07312   9.16257]
		Model Seed: 16 Seed: 1 OOD mean of (MSE, MAE) stats: [162.04483    8.353693]
		Model Seed: 16 Seed: 1 ID median of (MSE, MAE): [57.761513   6.5221977]
		Model Seed: 16 Seed: 1 OOD median of (MSE, MAE) stats: [52.119823   6.1763673]
		Model Seed: 16 Seed: 1 ID likelihoods: -9.592665891646622
		Model Seed: 16 Seed: 1 OOD likelihoods: -9.462874246477025
		Model Seed: 16 Seed: 1 ID calibration errors: [0.41399417 0.25869652 0.15376482 0.09746485 0.06605577 0.04499067
 0.02658605 0.01849882 0.01428915 0.01154711 0.0094604  0.00948914]
		Model Seed: 16 Seed: 1 OOD calibration errors: [0.33459899 0.20438867 0.12042451 0.07294328 0.0527977  0.03073174
 0.01948723 0.01351278 0.0125986  0.01181499 0.00900278 0.01320604]
	Train: 64804 (63.70%)
	Val: 12349 (12.14%)
	Test: 16419 (16.14%)
	Test OOD: 8164 (8.02%)
	No scaling applied
		Model Seed: 16 Seed: 2 ID mean of (MSE, MAE): [212.11511    9.043722]
		Model Seed: 16 Seed: 2 OOD mean of (MSE, MAE) stats: [178.09016    8.834377]
		Model Seed: 16 Seed: 2 ID median of (MSE, MAE): [54.40263    6.3131394]
		Model Seed: 16 Seed: 2 OOD median of (MSE, MAE) stats: [57.41255    6.4086003]
		Model Seed: 16 Seed: 2 ID likelihoods: -9.597502584589698
		Model Seed: 16 Seed: 2 OOD likelihoods: -9.510082529085453
		Model Seed: 16 Seed: 2 ID calibration errors: [0.40543156 0.26476678 0.17030007 0.10925195 0.06712617 0.04776706
 0.03142846 0.02298064 0.01746996 0.01288794 0.01059768 0.00790803]
		Model Seed: 16 Seed: 2 OOD calibration errors: [0.38531559 0.23830716 0.14191856 0.09139689 0.05593118 0.04191057
 0.03057206 0.02099966 0.01892405 0.01569858 0.01519399 0.01201692]
	Model Seed: 16 ID mean of (MSE, MAE): [211.09412    9.103146]
	Model Seed: 16 OOD mean of (MSE, MAE): [170.0675     8.594035]
	Model Seed: 16 ID median of (MSE, MAE): [56.08207    6.4176683]
	Model Seed: 16 OOD median of (MSE, MAE): [54.76619   6.292484]
	Model Seed: 16 ID likelihoods: -9.59508423811816
	Model Seed: 16 OOD likelihoods: -9.48647838778124
	Model Seed: 16 ID calibration errors: [0.40971287 0.26173165 0.16203244 0.1033584  0.06659097 0.04637886
 0.02900725 0.02073973 0.01587956 0.01221752 0.01002904 0.00869859]
	Model Seed: 16 OOD calibration errors: [0.35995729 0.22134792 0.13117154 0.08217009 0.05436444 0.03632115
 0.02502965 0.01725622 0.01576133 0.01375679 0.01209838 0.01261148]
	Train: 62090 (61.20%)
	Val: 12502 (12.32%)
	Test: 16648 (16.41%)
	Test OOD: 10208 (10.06%)
	No scaling applied
		Model Seed: 17 Seed: 1 ID mean of (MSE, MAE): [210.07312   9.16257]
		Model Seed: 17 Seed: 1 OOD mean of (MSE, MAE) stats: [162.04483    8.353693]
		Model Seed: 17 Seed: 1 ID median of (MSE, MAE): [57.761513   6.5221977]
		Model Seed: 17 Seed: 1 OOD median of (MSE, MAE) stats: [52.119823   6.1763673]
		Model Seed: 17 Seed: 1 ID likelihoods: -9.592665891646622
		Model Seed: 17 Seed: 1 OOD likelihoods: -9.462874246477025
		Model Seed: 17 Seed: 1 ID calibration errors: [0.41399417 0.25869652 0.15376482 0.09746485 0.06605577 0.04499067
 0.02658605 0.01849882 0.01428915 0.01154711 0.0094604  0.00948914]
		Model Seed: 17 Seed: 1 OOD calibration errors: [0.33459899 0.20438867 0.12042451 0.07294328 0.0527977  0.03073174
 0.01948723 0.01351278 0.0125986  0.01181499 0.00900278 0.01320604]
	Train: 64804 (63.70%)
	Val: 12349 (12.14%)
	Test: 16419 (16.14%)
	Test OOD: 8164 (8.02%)
	No scaling applied
		Model Seed: 17 Seed: 2 ID mean of (MSE, MAE): [212.11511    9.043722]
		Model Seed: 17 Seed: 2 OOD mean of (MSE, MAE) stats: [178.09016    8.834377]
		Model Seed: 17 Seed: 2 ID median of (MSE, MAE): [54.40263    6.3131394]
		Model Seed: 17 Seed: 2 OOD median of (MSE, MAE) stats: [57.41255    6.4086003]
		Model Seed: 17 Seed: 2 ID likelihoods: -9.597502584589698
		Model Seed: 17 Seed: 2 OOD likelihoods: -9.510082529085453
		Model Seed: 17 Seed: 2 ID calibration errors: [0.40543156 0.26476678 0.17030007 0.10925195 0.06712617 0.04776706
 0.03142846 0.02298064 0.01746996 0.01288794 0.01059768 0.00790803]
		Model Seed: 17 Seed: 2 OOD calibration errors: [0.38531559 0.23830716 0.14191856 0.09139689 0.05593118 0.04191057
 0.03057206 0.02099966 0.01892405 0.01569858 0.01519399 0.01201692]
	Model Seed: 17 ID mean of (MSE, MAE): [211.09412    9.103146]
	Model Seed: 17 OOD mean of (MSE, MAE): [170.0675     8.594035]
	Model Seed: 17 ID median of (MSE, MAE): [56.08207    6.4176683]
	Model Seed: 17 OOD median of (MSE, MAE): [54.76619   6.292484]
	Model Seed: 17 ID likelihoods: -9.59508423811816
	Model Seed: 17 OOD likelihoods: -9.48647838778124
	Model Seed: 17 ID calibration errors: [0.40971287 0.26173165 0.16203244 0.1033584  0.06659097 0.04637886
 0.02900725 0.02073973 0.01587956 0.01221752 0.01002904 0.00869859]
	Model Seed: 17 OOD calibration errors: [0.35995729 0.22134792 0.13117154 0.08217009 0.05436444 0.03632115
 0.02502965 0.01725622 0.01576133 0.01375679 0.01209838 0.01261148]
	Train: 62090 (61.20%)
	Val: 12502 (12.32%)
	Test: 16648 (16.41%)
	Test OOD: 10208 (10.06%)
	No scaling applied
		Model Seed: 18 Seed: 1 ID mean of (MSE, MAE): [210.07312   9.16257]
		Model Seed: 18 Seed: 1 OOD mean of (MSE, MAE) stats: [162.04483    8.353693]
		Model Seed: 18 Seed: 1 ID median of (MSE, MAE): [57.761513   6.5221977]
		Model Seed: 18 Seed: 1 OOD median of (MSE, MAE) stats: [52.119823   6.1763673]
		Model Seed: 18 Seed: 1 ID likelihoods: -9.592665891646622
		Model Seed: 18 Seed: 1 OOD likelihoods: -9.462874246477025
		Model Seed: 18 Seed: 1 ID calibration errors: [0.41399417 0.25869652 0.15376482 0.09746485 0.06605577 0.04499067
 0.02658605 0.01849882 0.01428915 0.01154711 0.0094604  0.00948914]
		Model Seed: 18 Seed: 1 OOD calibration errors: [0.33459899 0.20438867 0.12042451 0.07294328 0.0527977  0.03073174
 0.01948723 0.01351278 0.0125986  0.01181499 0.00900278 0.01320604]
	Train: 64804 (63.70%)
	Val: 12349 (12.14%)
	Test: 16419 (16.14%)
	Test OOD: 8164 (8.02%)
	No scaling applied
		Model Seed: 18 Seed: 2 ID mean of (MSE, MAE): [212.11511    9.043722]
		Model Seed: 18 Seed: 2 OOD mean of (MSE, MAE) stats: [178.09016    8.834377]
		Model Seed: 18 Seed: 2 ID median of (MSE, MAE): [54.40263    6.3131394]
		Model Seed: 18 Seed: 2 OOD median of (MSE, MAE) stats: [57.41255    6.4086003]
		Model Seed: 18 Seed: 2 ID likelihoods: -9.597502584589698
		Model Seed: 18 Seed: 2 OOD likelihoods: -9.510082529085453
		Model Seed: 18 Seed: 2 ID calibration errors: [0.40543156 0.26476678 0.17030007 0.10925195 0.06712617 0.04776706
 0.03142846 0.02298064 0.01746996 0.01288794 0.01059768 0.00790803]
		Model Seed: 18 Seed: 2 OOD calibration errors: [0.38531559 0.23830716 0.14191856 0.09139689 0.05593118 0.04191057
 0.03057206 0.02099966 0.01892405 0.01569858 0.01519399 0.01201692]
	Model Seed: 18 ID mean of (MSE, MAE): [211.09412    9.103146]
	Model Seed: 18 OOD mean of (MSE, MAE): [170.0675     8.594035]
	Model Seed: 18 ID median of (MSE, MAE): [56.08207    6.4176683]
	Model Seed: 18 OOD median of (MSE, MAE): [54.76619   6.292484]
	Model Seed: 18 ID likelihoods: -9.59508423811816
	Model Seed: 18 OOD likelihoods: -9.48647838778124
	Model Seed: 18 ID calibration errors: [0.40971287 0.26173165 0.16203244 0.1033584  0.06659097 0.04637886
 0.02900725 0.02073973 0.01587956 0.01221752 0.01002904 0.00869859]
	Model Seed: 18 OOD calibration errors: [0.35995729 0.22134792 0.13117154 0.08217009 0.05436444 0.03632115
 0.02502965 0.01725622 0.01576133 0.01375679 0.01209838 0.01261148]
	Train: 62090 (61.20%)
	Val: 12502 (12.32%)
	Test: 16648 (16.41%)
	Test OOD: 10208 (10.06%)
	No scaling applied
		Model Seed: 19 Seed: 1 ID mean of (MSE, MAE): [210.07312   9.16257]
		Model Seed: 19 Seed: 1 OOD mean of (MSE, MAE) stats: [162.04483    8.353693]
		Model Seed: 19 Seed: 1 ID median of (MSE, MAE): [57.761513   6.5221977]
		Model Seed: 19 Seed: 1 OOD median of (MSE, MAE) stats: [52.119823   6.1763673]
		Model Seed: 19 Seed: 1 ID likelihoods: -9.592665891646622
		Model Seed: 19 Seed: 1 OOD likelihoods: -9.462874246477025
		Model Seed: 19 Seed: 1 ID calibration errors: [0.41399417 0.25869652 0.15376482 0.09746485 0.06605577 0.04499067
 0.02658605 0.01849882 0.01428915 0.01154711 0.0094604  0.00948914]
		Model Seed: 19 Seed: 1 OOD calibration errors: [0.33459899 0.20438867 0.12042451 0.07294328 0.0527977  0.03073174
 0.01948723 0.01351278 0.0125986  0.01181499 0.00900278 0.01320604]
	Train: 64804 (63.70%)
	Val: 12349 (12.14%)
	Test: 16419 (16.14%)
	Test OOD: 8164 (8.02%)
	No scaling applied
		Model Seed: 19 Seed: 2 ID mean of (MSE, MAE): [212.11511    9.043722]
		Model Seed: 19 Seed: 2 OOD mean of (MSE, MAE) stats: [178.09016    8.834377]
		Model Seed: 19 Seed: 2 ID median of (MSE, MAE): [54.40263    6.3131394]
		Model Seed: 19 Seed: 2 OOD median of (MSE, MAE) stats: [57.41255    6.4086003]
		Model Seed: 19 Seed: 2 ID likelihoods: -9.597502584589698
		Model Seed: 19 Seed: 2 OOD likelihoods: -9.510082529085453
		Model Seed: 19 Seed: 2 ID calibration errors: [0.40543156 0.26476678 0.17030007 0.10925195 0.06712617 0.04776706
 0.03142846 0.02298064 0.01746996 0.01288794 0.01059768 0.00790803]
		Model Seed: 19 Seed: 2 OOD calibration errors: [0.38531559 0.23830716 0.14191856 0.09139689 0.05593118 0.04191057
 0.03057206 0.02099966 0.01892405 0.01569858 0.01519399 0.01201692]
	Model Seed: 19 ID mean of (MSE, MAE): [211.09412    9.103146]
	Model Seed: 19 OOD mean of (MSE, MAE): [170.0675     8.594035]
	Model Seed: 19 ID median of (MSE, MAE): [56.08207    6.4176683]
	Model Seed: 19 OOD median of (MSE, MAE): [54.76619   6.292484]
	Model Seed: 19 ID likelihoods: -9.59508423811816
	Model Seed: 19 OOD likelihoods: -9.48647838778124
	Model Seed: 19 ID calibration errors: [0.40971287 0.26173165 0.16203244 0.1033584  0.06659097 0.04637886
 0.02900725 0.02073973 0.01587956 0.01221752 0.01002904 0.00869859]
	Model Seed: 19 OOD calibration errors: [0.35995729 0.22134792 0.13117154 0.08217009 0.05436444 0.03632115
 0.02502965 0.01725622 0.01576133 0.01375679 0.01209838 0.01261148]
ID mean of (MSE, MAE): [211.0941162109375, 9.10314655303955] +- [0.0, 9.5367431640625e-07] +- [1.020995 0.059424] 
OOD mean of (MSE, MAE): [170.0675048828125, 8.594034194946289] +- [0.0, 9.5367431640625e-07] +- [8.022665 0.240342] 
ID median of (MSE, MAE): [56.082069396972656, 6.417668342590332] +- [0.0, 0.0] +- [1.6794415  0.10452915] 
OOD median of (MSE, MAE): [54.76618194580078, 6.292483806610107] +- [7.62939453125e-06, 0.0] +- [2.6463635 0.1161165] 
ID likelihoods: -9.59508423811816 +- 0.0 +- 0.0024183464715390457 
OOD likelihoods: -9.486478387781238 +- 1.7763568394002505e-15 +- 0.023604141304214288 
ID calibration errors: [0.40971286569569154, 0.2617316491235253, 0.16203244388417976, 0.10335839511464398, 0.06659096924075657, 0.04637886329237006, 0.029007254626055155, 0.02073973015322919, 0.01587955812016137, 0.012217522687658704, 0.010029037224928926, 0.00869858713630393] +- [5.551115123125783e-17, 0.0, 2.7755575615628914e-17, 2.7755575615628914e-17, 0.0, 0.0, 0.0, 0.0, 0.0, 1.734723475976807e-18, 0.0, 1.734723475976807e-18] +- [0.0042813  0.00303513 0.00826763 0.00589355 0.0005352  0.00138819
 0.0024212  0.00224091 0.00159041 0.00067042 0.00056864 0.00079056] 
OOD calibration errors: [0.3599572899448308, 0.22134791628368666, 0.13117153562928577, 0.08217008631448552, 0.05436444071262776, 0.036321153681205476, 0.025029645808208954, 0.017256220078467784, 0.01576132502905275, 0.013756785810705344, 0.01209838386699906, 0.01261148079633381] +- [5.551115123125783e-17, 0.0, 2.7755575615628914e-17, 0.0, 0.0, 0.0, 3.469446951953614e-18, 3.469446951953614e-18, 0.0, 0.0, 0.0, 3.469446951953614e-18] +- [0.0253583  0.01695925 0.01074702 0.0092268  0.00156674 0.00558941
 0.00554242 0.00374344 0.00316273 0.00194179 0.0030956  0.00059456] 
