Optimization started at 2023-02-25 01:31:31.312572--------------------------------
Loading column definition...
Checking column definition...
Loading data...
Dropping columns / rows...
Checking for NA values...
Setting data types...
Dropping columns / rows...
Encoding data...
	Updated column definition:
		id: REAL_VALUED (ID)
		time: DATE (TIME)
		gl: REAL_VALUED (TARGET)
		time_year: REAL_VALUED (KNOWN_INPUT)
		time_month: REAL_VALUED (KNOWN_INPUT)
		time_day: REAL_VALUED (KNOWN_INPUT)
		time_hour: REAL_VALUED (KNOWN_INPUT)
		time_minute: REAL_VALUED (KNOWN_INPUT)
Interpolating data...
	Dropped segments: 63
	Extracted segments: 205
	Interpolated values: 241
	Percent of values interpolated: 0.22%
Splitting data...
	Train: 37857 (38.80%)
	Val: 31296 (32.08%)
	Test: 39658 (40.65%)
Scaling data...
	No scaling applied
Data formatting complete.
--------------------------------
Current value: 0.0295226089656353, Current params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 2, 'dim_feedforward': 352, 'dropout': 0.06972729779440827, 'lr': 0.00010954881450734098, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.5305704447969886}
Best value: 0.0295226089656353, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 2, 'dim_feedforward': 352, 'dropout': 0.06972729779440827, 'lr': 0.00010954881450734098, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.5305704447969886}
Current value: 0.02783111296594143, Current params: {'in_len': 120, 'max_samples_per_ts': 150, 'd_model': 32, 'n_heads': 2, 'num_encoder_layers': 2, 'num_decoder_layers': 4, 'dim_feedforward': 224, 'dropout': 0.1678029720652269, 'lr': 0.00068000357611497, 'batch_size': 48, 'lr_epochs': 14, 'max_grad_norm': 0.23315642998012615}
Best value: 0.02783111296594143, Best params: {'in_len': 120, 'max_samples_per_ts': 150, 'd_model': 32, 'n_heads': 2, 'num_encoder_layers': 2, 'num_decoder_layers': 4, 'dim_feedforward': 224, 'dropout': 0.1678029720652269, 'lr': 0.00068000357611497, 'batch_size': 48, 'lr_epochs': 14, 'max_grad_norm': 0.23315642998012615}
Current value: 0.022680586203932762, Current params: {'in_len': 144, 'max_samples_per_ts': 200, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 1, 'num_decoder_layers': 1, 'dim_feedforward': 96, 'dropout': 0.14312847621909403, 'lr': 0.00040478175741239246, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.3006983282197255}
Best value: 0.022680586203932762, Best params: {'in_len': 144, 'max_samples_per_ts': 200, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 1, 'num_decoder_layers': 1, 'dim_feedforward': 96, 'dropout': 0.14312847621909403, 'lr': 0.00040478175741239246, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.3006983282197255}
Current value: 0.025798089802265167, Current params: {'in_len': 108, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 2, 'num_decoder_layers': 2, 'dim_feedforward': 384, 'dropout': 0.1310283884964878, 'lr': 0.0007974347412763076, 'batch_size': 48, 'lr_epochs': 14, 'max_grad_norm': 0.47906273543369793}
Best value: 0.022680586203932762, Best params: {'in_len': 144, 'max_samples_per_ts': 200, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 1, 'num_decoder_layers': 1, 'dim_feedforward': 96, 'dropout': 0.14312847621909403, 'lr': 0.00040478175741239246, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.3006983282197255}
Current value: 0.02379801869392395, Current params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 2, 'dim_feedforward': 352, 'dropout': 0.12301892869355009, 'lr': 0.0004869361165317092, 'batch_size': 32, 'lr_epochs': 6, 'max_grad_norm': 0.8885827807293228}
Best value: 0.022680586203932762, Best params: {'in_len': 144, 'max_samples_per_ts': 200, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 1, 'num_decoder_layers': 1, 'dim_feedforward': 96, 'dropout': 0.14312847621909403, 'lr': 0.00040478175741239246, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.3006983282197255}
Current value: 0.0010956906480714679, Current params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 32, 'n_heads': 2, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 224, 'dropout': 0.03192155065954488, 'lr': 0.00032270042451839015, 'batch_size': 48, 'lr_epochs': 10, 'max_grad_norm': 0.9136130823076385}
Best value: 0.022680586203932762, Best params: {'in_len': 144, 'max_samples_per_ts': 200, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 1, 'num_decoder_layers': 1, 'dim_feedforward': 96, 'dropout': 0.14312847621909403, 'lr': 0.00040478175741239246, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.3006983282197255}
Current value: 0.023663874715566635, Current params: {'in_len': 108, 'max_samples_per_ts': 100, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 2, 'dim_feedforward': 480, 'dropout': 0.13716616389779276, 'lr': 0.0006774604728603538, 'batch_size': 64, 'lr_epochs': 10, 'max_grad_norm': 0.8390080257195698}
Best value: 0.022680586203932762, Best params: {'in_len': 144, 'max_samples_per_ts': 200, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 1, 'num_decoder_layers': 1, 'dim_feedforward': 96, 'dropout': 0.14312847621909403, 'lr': 0.00040478175741239246, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.3006983282197255}
Current value: 0.0016511050052940845, Current params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 128, 'n_heads': 2, 'num_encoder_layers': 4, 'num_decoder_layers': 4, 'dim_feedforward': 160, 'dropout': 0.1374756347131699, 'lr': 0.00014483275392503025, 'batch_size': 64, 'lr_epochs': 16, 'max_grad_norm': 0.3442584386562129}
Best value: 0.022680586203932762, Best params: {'in_len': 144, 'max_samples_per_ts': 200, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 1, 'num_decoder_layers': 1, 'dim_feedforward': 96, 'dropout': 0.14312847621909403, 'lr': 0.00040478175741239246, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.3006983282197255}
Current value: 0.024967094883322716, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 320, 'dropout': 0.055654501420466664, 'lr': 0.0002043964783335913, 'batch_size': 32, 'lr_epochs': 4, 'max_grad_norm': 0.5277172025871066}
Best value: 0.022680586203932762, Best params: {'in_len': 144, 'max_samples_per_ts': 200, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 1, 'num_decoder_layers': 1, 'dim_feedforward': 96, 'dropout': 0.14312847621909403, 'lr': 0.00040478175741239246, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.3006983282197255}
Current value: 0.0011375687317922711, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 3, 'dim_feedforward': 320, 'dropout': 0.1987729791622702, 'lr': 0.0001882356926774668, 'batch_size': 48, 'lr_epochs': 20, 'max_grad_norm': 0.41204515107112116}
Best value: 0.022680586203932762, Best params: {'in_len': 144, 'max_samples_per_ts': 200, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 1, 'num_decoder_layers': 1, 'dim_feedforward': 96, 'dropout': 0.14312847621909403, 'lr': 0.00040478175741239246, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.3006983282197255}
Current value: 0.001533458475023508, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 1, 'num_decoder_layers': 1, 'dim_feedforward': 32, 'dropout': 0.09043748537584306, 'lr': 0.0009796870867503592, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.14457032737664033}
Best value: 0.022680586203932762, Best params: {'in_len': 144, 'max_samples_per_ts': 200, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 1, 'num_decoder_layers': 1, 'dim_feedforward': 96, 'dropout': 0.14312847621909403, 'lr': 0.00040478175741239246, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.3006983282197255}
Current value: 0.0034514355938881636, Current params: {'in_len': 96, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 1, 'dim_feedforward': 512, 'dropout': 0.16330923296664243, 'lr': 0.0004947197037520926, 'batch_size': 64, 'lr_epochs': 8, 'max_grad_norm': 0.715626776800525}
Best value: 0.022680586203932762, Best params: {'in_len': 144, 'max_samples_per_ts': 200, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 1, 'num_decoder_layers': 1, 'dim_feedforward': 96, 'dropout': 0.14312847621909403, 'lr': 0.00040478175741239246, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.3006983282197255}
Current value: 0.001104929600842297, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 3, 'dim_feedforward': 64, 'dropout': 0.10254593531293058, 'lr': 0.0006716139351006562, 'batch_size': 64, 'lr_epochs': 6, 'max_grad_norm': 0.7120115892154804}
Best value: 0.022680586203932762, Best params: {'in_len': 144, 'max_samples_per_ts': 200, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 1, 'num_decoder_layers': 1, 'dim_feedforward': 96, 'dropout': 0.14312847621909403, 'lr': 0.00040478175741239246, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.3006983282197255}
Current value: 0.0015937857097014785, Current params: {'in_len': 96, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 3, 'num_decoder_layers': 1, 'dim_feedforward': 512, 'dropout': 0.16187644965888418, 'lr': 0.00040108794872732517, 'batch_size': 64, 'lr_epochs': 12, 'max_grad_norm': 0.6890127011258733}
Best value: 0.022680586203932762, Best params: {'in_len': 144, 'max_samples_per_ts': 200, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 1, 'num_decoder_layers': 1, 'dim_feedforward': 96, 'dropout': 0.14312847621909403, 'lr': 0.00040478175741239246, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.3006983282197255}
Current value: 0.0011246746871620417, Current params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 128, 'dropout': 0.19916594717080788, 'lr': 0.0006457270891720732, 'batch_size': 48, 'lr_epochs': 8, 'max_grad_norm': 0.9940850634135191}
Best value: 0.022680586203932762, Best params: {'in_len': 144, 'max_samples_per_ts': 200, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 1, 'num_decoder_layers': 1, 'dim_feedforward': 96, 'dropout': 0.14312847621909403, 'lr': 0.00040478175741239246, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.3006983282197255}
Current value: 0.0011369046987965703, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 2, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.0016697700219177325, 'lr': 0.0008261588914940571, 'batch_size': 32, 'lr_epochs': 12, 'max_grad_norm': 0.283747720123512}
Best value: 0.022680586203932762, Best params: {'in_len': 144, 'max_samples_per_ts': 200, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 1, 'num_decoder_layers': 1, 'dim_feedforward': 96, 'dropout': 0.14312847621909403, 'lr': 0.00040478175741239246, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.3006983282197255}
Current value: 0.0011756893945857882, Current params: {'in_len': 120, 'max_samples_per_ts': 200, 'd_model': 128, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 2, 'dim_feedforward': 96, 'dropout': 0.10942560447361942, 'lr': 0.00033967809496131317, 'batch_size': 64, 'lr_epochs': 18, 'max_grad_norm': 0.1078695547553905}
Best value: 0.022680586203932762, Best params: {'in_len': 144, 'max_samples_per_ts': 200, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 1, 'num_decoder_layers': 1, 'dim_feedforward': 96, 'dropout': 0.14312847621909403, 'lr': 0.00040478175741239246, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.3006983282197255}
Current value: 0.0008882214315235615, Current params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 1, 'dim_feedforward': 192, 'dropout': 0.1454514947170623, 'lr': 0.0005664550331589918, 'batch_size': 48, 'lr_epochs': 8, 'max_grad_norm': 0.6347424800084637}
Best value: 0.022680586203932762, Best params: {'in_len': 144, 'max_samples_per_ts': 200, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 1, 'num_decoder_layers': 1, 'dim_feedforward': 96, 'dropout': 0.14312847621909403, 'lr': 0.00040478175741239246, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.3006983282197255}
Current value: 0.00204251566901803, Current params: {'in_len': 120, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 2, 'num_decoder_layers': 2, 'dim_feedforward': 448, 'dropout': 0.17792131683644888, 'lr': 0.0007640258366943469, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.8163825617618139}
Best value: 0.022680586203932762, Best params: {'in_len': 144, 'max_samples_per_ts': 200, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 1, 'num_decoder_layers': 1, 'dim_feedforward': 96, 'dropout': 0.14312847621909403, 'lr': 0.00040478175741239246, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.3006983282197255}
Current value: 0.0014022828545421362, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 256, 'dropout': 0.0872987722085108, 'lr': 0.0009421078411956222, 'batch_size': 64, 'lr_epochs': 6, 'max_grad_norm': 0.40519103081715846}
Best value: 0.022680586203932762, Best params: {'in_len': 144, 'max_samples_per_ts': 200, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 1, 'num_decoder_layers': 1, 'dim_feedforward': 96, 'dropout': 0.14312847621909403, 'lr': 0.00040478175741239246, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.3006983282197255}
Current value: 0.02805781178176403, Current params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 2, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.11489431511099388, 'lr': 0.0005372489824649577, 'batch_size': 48, 'lr_epochs': 14, 'max_grad_norm': 0.6164746971942663}
Best value: 0.022680586203932762, Best params: {'in_len': 144, 'max_samples_per_ts': 200, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 1, 'num_decoder_layers': 1, 'dim_feedforward': 96, 'dropout': 0.14312847621909403, 'lr': 0.00040478175741239246, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.3006983282197255}
Current value: 0.0012512608664110303, Current params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 2, 'dim_feedforward': 416, 'dropout': 0.12338935829889455, 'lr': 0.0004378642400129414, 'batch_size': 32, 'lr_epochs': 6, 'max_grad_norm': 0.8172316456876011}
Best value: 0.022680586203932762, Best params: {'in_len': 144, 'max_samples_per_ts': 200, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 1, 'num_decoder_layers': 1, 'dim_feedforward': 96, 'dropout': 0.14312847621909403, 'lr': 0.00040478175741239246, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.3006983282197255}
Current value: 0.001632761675864458, Current params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 2, 'dim_feedforward': 288, 'dropout': 0.14798249838778593, 'lr': 0.00029644359502070596, 'batch_size': 32, 'lr_epochs': 4, 'max_grad_norm': 0.8404355363711259}
Best value: 0.022680586203932762, Best params: {'in_len': 144, 'max_samples_per_ts': 200, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 1, 'num_decoder_layers': 1, 'dim_feedforward': 96, 'dropout': 0.14312847621909403, 'lr': 0.00040478175741239246, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.3006983282197255}
Current value: 0.0009261173545382917, Current params: {'in_len': 96, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 2, 'dim_feedforward': 384, 'dropout': 0.146495497670143, 'lr': 0.0005986888031891444, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.9782110555654051}
Best value: 0.022680586203932762, Best params: {'in_len': 144, 'max_samples_per_ts': 200, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 1, 'num_decoder_layers': 1, 'dim_feedforward': 96, 'dropout': 0.14312847621909403, 'lr': 0.00040478175741239246, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.3006983282197255}
Current value: 0.0203961543738842, Current params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0009892561938613653, Current params: {'in_len': 120, 'max_samples_per_ts': 150, 'd_model': 32, 'n_heads': 2, 'num_encoder_layers': 2, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.07597627608702379, 'lr': 0.00037189392437826185, 'batch_size': 48, 'lr_epochs': 8, 'max_grad_norm': 0.8027868834682086}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0017107094172388315, Current params: {'in_len': 96, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 3, 'num_decoder_layers': 4, 'dim_feedforward': 512, 'dropout': 0.18112861590885015, 'lr': 0.00046000708109445875, 'batch_size': 32, 'lr_epochs': 12, 'max_grad_norm': 0.740304428298367}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.001171117415651679, Current params: {'in_len': 120, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 2, 'num_decoder_layers': 3, 'dim_feedforward': 416, 'dropout': 0.15664442848058885, 'lr': 0.00025324760814704765, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.6074205800750676}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0010961061343550682, Current params: {'in_len': 108, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 32, 'dropout': 0.13082952855764854, 'lr': 0.0007312839170119981, 'batch_size': 64, 'lr_epochs': 4, 'max_grad_norm': 0.19023377774934133}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0009221337968483567, Current params: {'in_len': 132, 'max_samples_per_ts': 200, 'd_model': 32, 'n_heads': 2, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 128, 'dropout': 0.0637804100070719, 'lr': 0.0005998245534842696, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.5272370343357498}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0008621888118796051, Current params: {'in_len': 144, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 2, 'dim_feedforward': 480, 'dropout': 0.10253102028095155, 'lr': 0.000863144139587325, 'batch_size': 48, 'lr_epochs': 8, 'max_grad_norm': 0.8976818251338725}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0011561211431398988, Current params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 2, 'dim_feedforward': 352, 'dropout': 0.11952237620004653, 'lr': 0.0005128328467566982, 'batch_size': 32, 'lr_epochs': 6, 'max_grad_norm': 0.9048778679748952}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0012032126542180777, Current params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 2, 'dim_feedforward': 384, 'dropout': 0.1376671165392285, 'lr': 0.00042157213036183493, 'batch_size': 32, 'lr_epochs': 6, 'max_grad_norm': 0.7635562587236588}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0018469104543328285, Current params: {'in_len': 120, 'max_samples_per_ts': 200, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 352, 'dropout': 0.1238199936304072, 'lr': 0.0004865484875481144, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.9271062482270271}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0009415799286216497, Current params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 1, 'dim_feedforward': 256, 'dropout': 0.17556415682615367, 'lr': 0.0006251761019306456, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.8735116330520377}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0013013706775382161, Current params: {'in_len': 108, 'max_samples_per_ts': 150, 'd_model': 128, 'n_heads': 2, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 416, 'dropout': 0.08784501372791453, 'lr': 0.0007225588662518145, 'batch_size': 48, 'lr_epochs': 14, 'max_grad_norm': 0.954823747420727}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0009777238592505455, Current params: {'in_len': 120, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 2, 'num_decoder_layers': 4, 'dim_feedforward': 192, 'dropout': 0.13139239716818876, 'lr': 0.0005432290277672602, 'batch_size': 32, 'lr_epochs': 4, 'max_grad_norm': 0.4463637078020019}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0018748590955510736, Current params: {'in_len': 96, 'max_samples_per_ts': 200, 'd_model': 32, 'n_heads': 2, 'num_encoder_layers': 4, 'num_decoder_layers': 3, 'dim_feedforward': 320, 'dropout': 0.11022730458455073, 'lr': 0.00037318891417666134, 'batch_size': 48, 'lr_epochs': 12, 'max_grad_norm': 0.6643105376953953}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0008466328727081418, Current params: {'in_len': 108, 'max_samples_per_ts': 100, 'd_model': 128, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 2, 'dim_feedforward': 288, 'dropout': 0.15390658715948072, 'lr': 0.00030931997294261765, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.3508332180540352}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0009519360028207302, Current params: {'in_len': 96, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 2, 'num_decoder_layers': 1, 'dim_feedforward': 480, 'dropout': 0.13832224714819907, 'lr': 0.0002477198804136133, 'batch_size': 32, 'lr_epochs': 4, 'max_grad_norm': 0.7721347671919331}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.001321019371971488, Current params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 224, 'dropout': 0.0930738944040082, 'lr': 0.0004761683029670952, 'batch_size': 48, 'lr_epochs': 16, 'max_grad_norm': 0.554814776096435}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.020573580637574196, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 320, 'dropout': 0.03627133587277919, 'lr': 0.00010286744434992158, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.2308534708161789}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0008165082545019686, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 352, 'dropout': 0.04014077552613998, 'lr': 0.0005703313637153167, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.24355482956943042}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.022780578583478928, Current params: {'in_len': 132, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 288, 'dropout': 0.04957219075316559, 'lr': 0.00010885565089192352, 'batch_size': 32, 'lr_epochs': 6, 'max_grad_norm': 0.19595668145558046}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0008405126864090562, Current params: {'in_len': 132, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 192, 'dropout': 0.019303371380033237, 'lr': 0.00010131327356256659, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.28147829745137365}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0008109210757538676, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 3, 'dim_feedforward': 320, 'dropout': 0.048247714176736504, 'lr': 0.00014755983979081817, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.17621591710932308}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0014748600078746676, Current params: {'in_len': 132, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 256, 'dropout': 0.023650142436958843, 'lr': 0.00016499361226439294, 'batch_size': 32, 'lr_epochs': 6, 'max_grad_norm': 0.32234403675325196}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.026423243805766106, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 64, 'dropout': 0.008584313939048203, 'lr': 0.00024407141289385122, 'batch_size': 64, 'lr_epochs': 4, 'max_grad_norm': 0.21107803520154783}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0026204860769212246, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 160, 'dropout': 0.07455636573877275, 'lr': 0.00019356387193878512, 'batch_size': 48, 'lr_epochs': 8, 'max_grad_norm': 0.1028233031055068}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0012346056755632162, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 224, 'dropout': 0.05764591399160265, 'lr': 0.0001255584364047179, 'batch_size': 32, 'lr_epochs': 6, 'max_grad_norm': 0.14827995232042404}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.02368287555873394, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 384, 'dropout': 0.02790684342701416, 'lr': 0.0006784251852076006, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.2317196164137873}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.021426117047667503, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 384, 'dropout': 0.03994055707852873, 'lr': 0.0007329993629308057, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.25971748528797894}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0009483129833824933, Current params: {'in_len': 144, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 288, 'dropout': 0.04374891502026211, 'lr': 0.0008040542679152503, 'batch_size': 32, 'lr_epochs': 4, 'max_grad_norm': 0.28055835848563443}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.000803877308499068, Current params: {'in_len': 120, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.03427494803110539, 'lr': 0.0007468545971749653, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.37872399463480577}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.025934038683772087, Current params: {'in_len': 132, 'max_samples_per_ts': 50, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 320, 'dropout': 0.049606256908534145, 'lr': 0.0006479424975828587, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.311754665546885}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0008495412766933441, Current params: {'in_len': 120, 'max_samples_per_ts': 100, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 480, 'dropout': 0.015660970445802884, 'lr': 0.0009060161824591053, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.2494707698154925}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0008452667389065027, Current params: {'in_len': 132, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 2, 'dim_feedforward': 416, 'dropout': 0.06491366042114671, 'lr': 0.0007116772058062159, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.1610556976638247}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0008574894163757563, Current params: {'in_len': 120, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 512, 'dropout': 0.03528267594223844, 'lr': 0.0007819118537472325, 'batch_size': 64, 'lr_epochs': 4, 'max_grad_norm': 0.46861581528604235}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0008220264571718872, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 3, 'dim_feedforward': 320, 'dropout': 0.08081164267581681, 'lr': 0.0002188255696541679, 'batch_size': 32, 'lr_epochs': 12, 'max_grad_norm': 0.1252361875770364}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0010816025314852595, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 3, 'num_decoder_layers': 2, 'dim_feedforward': 256, 'dropout': 0.16545066753906698, 'lr': 0.000865630042456555, 'batch_size': 48, 'lr_epochs': 20, 'max_grad_norm': 0.20121559746827009}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0008227644138969481, 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': 448, 'dropout': 0.12670540561306626, 'lr': 0.00028025187342001125, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.3596128620353519}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.02299351431429386, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 384, 'dropout': 0.022876633430983076, 'lr': 0.000685016790456527, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.21736711655946322}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0011687439400702715, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 384, 'dropout': 0.0007687949025290998, 'lr': 0.0007016522548925807, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.21982103268964073}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0008431547903455794, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 352, 'dropout': 0.01646697336075731, 'lr': 0.0006427379821139749, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.2618195298249415}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.02452922612428665, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 288, 'dropout': 0.028602025243860102, 'lr': 0.0006007523371130933, 'batch_size': 32, 'lr_epochs': 6, 'max_grad_norm': 0.3044243130871756}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0007560427184216678, Current params: {'in_len': 120, 'max_samples_per_ts': 100, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 416, 'dropout': 0.009677294955395557, 'lr': 0.0005112432629922047, 'batch_size': 32, 'lr_epochs': 4, 'max_grad_norm': 0.18217525715567362}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.023459922522306442, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 3, 'num_decoder_layers': 2, 'dim_feedforward': 512, 'dropout': 0.1426597852766987, 'lr': 0.00033734012189718624, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.8408661820117698}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0009807310998439789, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 3, 'num_decoder_layers': 2, 'dim_feedforward': 512, 'dropout': 0.05652560936316921, 'lr': 0.0003893206118177956, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.8666293822858118}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.000952942471485585, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 3, 'num_decoder_layers': 2, 'dim_feedforward': 480, 'dropout': 0.14352793913870726, 'lr': 0.00035498215508882194, 'batch_size': 32, 'lr_epochs': 6, 'max_grad_norm': 0.38258215268867046}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0010206104489043355, Current params: {'in_len': 132, 'max_samples_per_ts': 50, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 384, 'dropout': 0.15700017589321938, 'lr': 0.00043479405466316853, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.15331502753912274}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0008905415888875723, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 3, 'num_decoder_layers': 1, 'dim_feedforward': 512, 'dropout': 0.041267597048325735, 'lr': 0.00016876684474358237, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.41912715030087877}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.000782597460784018, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 2, 'dim_feedforward': 448, 'dropout': 0.11631067613848865, 'lr': 0.0003392175837461749, 'batch_size': 32, 'lr_epochs': 12, 'max_grad_norm': 0.8012656197096966}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.002641258994117379, Current params: {'in_len': 108, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 480, 'dropout': 0.1330527661992181, 'lr': 0.00045824603196215253, 'batch_size': 64, 'lr_epochs': 10, 'max_grad_norm': 0.2648183988475981}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0019086356041952968, Current params: {'in_len': 120, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 2, 'dim_feedforward': 480, 'dropout': 0.1709532998211432, 'lr': 0.00012086980919324217, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8452961039538124}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0012199310585856438, Current params: {'in_len': 132, 'max_samples_per_ts': 50, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 3, 'num_decoder_layers': 2, 'dim_feedforward': 352, 'dropout': 0.1534937187136169, 'lr': 0.0004184389992671625, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.7172210606254174}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0007671968196518719, Current params: {'in_len': 144, 'max_samples_per_ts': 100, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 4, 'num_decoder_layers': 3, 'dim_feedforward': 416, 'dropout': 0.14216855701024966, 'lr': 0.0007592333755340745, 'batch_size': 32, 'lr_epochs': 4, 'max_grad_norm': 0.9451896456423877}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0007625151774846017, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 2, 'dim_feedforward': 448, 'dropout': 0.10968957340767564, 'lr': 0.0005696008470611601, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.12819651510570662}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0009523836197331548, Current params: {'in_len': 120, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 288, 'dropout': 0.1507646602002612, 'lr': 0.0005187239134418044, 'batch_size': 48, 'lr_epochs': 12, 'max_grad_norm': 0.777767016333407}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.025471173226833344, Current params: {'in_len': 132, 'max_samples_per_ts': 200, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 3, 'num_decoder_layers': 1, 'dim_feedforward': 320, 'dropout': 0.023201582119011185, 'lr': 0.00021846159458611156, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.8504101530415661}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.001112240250222385, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 512, 'dropout': 0.13534074704801285, 'lr': 0.0008288915247312777, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.5504560665762179}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0007621615077368915, Current params: {'in_len': 120, 'max_samples_per_ts': 100, 'd_model': 128, 'n_heads': 2, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 224, 'dropout': 0.12759407920488378, 'lr': 0.0006613634792937026, 'batch_size': 32, 'lr_epochs': 6, 'max_grad_norm': 0.3226355491931372}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0009130464750342071, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 384, 'dropout': 0.0316124713194831, 'lr': 0.0006882371060584079, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.23484267977005865}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.021807953715324402, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 384, 'dropout': 0.04779329544833655, 'lr': 0.0006774983019003792, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.2154831936178777}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.001148316659964621, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 352, 'dropout': 0.05117909307347532, 'lr': 0.000744056333057086, 'batch_size': 32, 'lr_epochs': 4, 'max_grad_norm': 0.20464760203944832}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.001115068793296814, Current params: {'in_len': 144, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 416, 'dropout': 0.0981881544335331, 'lr': 0.000142959116494503, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.16504919903607923}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.026250962167978287, Current params: {'in_len': 132, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.18507561798948954, 'lr': 0.0005943959787445515, 'batch_size': 32, 'lr_epochs': 4, 'max_grad_norm': 0.8237754259257574}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0007435139268636703, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 384, 'dropout': 0.060764807473097544, 'lr': 0.000464784178415032, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.1938925051706103}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0007475127349607646, 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': 96, 'dropout': 0.06848634096683454, 'lr': 0.0006234928855301954, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.8787942188613678}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0008436042116954923, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 2, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 256, 'dropout': 0.03692445227453677, 'lr': 0.0006920389289997295, 'batch_size': 64, 'lr_epochs': 10, 'max_grad_norm': 0.29422040863136256}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0011230733944103122, 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': 512, 'dropout': 0.04500486592496389, 'lr': 0.00027944269388265703, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.5803990092905649}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0008975783712230623, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 3, 'num_decoder_layers': 1, 'dim_feedforward': 480, 'dropout': 0.15931386296723138, 'lr': 0.0007257515067209338, 'batch_size': 32, 'lr_epochs': 4, 'max_grad_norm': 0.2241886023173977}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0007380766328424215, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 384, 'dropout': 0.03085178188318155, 'lr': 0.0006599619853322137, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.2474915508208582}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0014446142595261335, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 352, 'dropout': 0.009768471751896315, 'lr': 0.0006251555175783248, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.12977500665309027}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0007876637973822653, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 416, 'dropout': 0.027061567134247726, 'lr': 0.0007868533629272919, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.2668616117667255}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0010502327932044864, Current params: {'in_len': 132, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 320, 'dropout': 0.02290616079224199, 'lr': 0.0006772023062017504, 'batch_size': 32, 'lr_epochs': 4, 'max_grad_norm': 0.22075574762651715}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0010009859688580036, Current params: {'in_len': 144, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 384, 'dropout': 0.050965991629377, 'lr': 0.0007126541705339423, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.5099097448823373}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0008717469172552228, Current params: {'in_len': 132, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 288, 'dropout': 0.03992856481293572, 'lr': 0.0001002935874006226, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.6759795666196564}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.001061391900293529, Current params: {'in_len': 120, 'max_samples_per_ts': 100, 'd_model': 128, 'n_heads': 2, 'num_encoder_layers': 1, 'num_decoder_layers': 2, 'dim_feedforward': 448, 'dropout': 0.14686483730429564, 'lr': 0.0005468629063429956, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.3278404523686458}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0019489387050271034, Current params: {'in_len': 108, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 352, 'dropout': 0.014805082869424994, 'lr': 0.00039893858824647496, 'batch_size': 32, 'lr_epochs': 18, 'max_grad_norm': 0.1776761426863276}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
Current value: 0.0008672800613567233, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 384, 'dropout': 0.04582729766497359, 'lr': 0.0007699070985883835, 'batch_size': 32, 'lr_epochs': 6, 'max_grad_norm': 0.9996021841036411}
Best value: 0.0203961543738842, Best params: {'in_len': 108, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.12434517563324206, 'lr': 0.00048663109178350133, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.8299004621292704}
--------------------------------
Loading column definition...
Checking column definition...
Loading data...
Dropping columns / rows...
Checking for NA values...
Setting data types...
Dropping columns / rows...
Encoding data...
	Updated column definition:
		id: REAL_VALUED (ID)
		time: DATE (TIME)
		gl: REAL_VALUED (TARGET)
		gender: REAL_VALUED (STATIC_INPUT)
		age: REAL_VALUED (STATIC_INPUT)
		BMI: REAL_VALUED (STATIC_INPUT)
		glycaemia: REAL_VALUED (STATIC_INPUT)
		HbA1c: REAL_VALUED (STATIC_INPUT)
		follow.up: REAL_VALUED (STATIC_INPUT)
		T2DM: REAL_VALUED (STATIC_INPUT)
		time_year: REAL_VALUED (KNOWN_INPUT)
		time_month: REAL_VALUED (KNOWN_INPUT)
		time_day: REAL_VALUED (KNOWN_INPUT)
		time_hour: REAL_VALUED (KNOWN_INPUT)
		time_minute: REAL_VALUED (KNOWN_INPUT)
Interpolating data...
	Dropped segments: 63
	Extracted segments: 205
	Interpolated values: 241
	Percent of values interpolated: 0.22%
Splitting data...
	Train: 72275 (45.89%)
	Val: 35713 (22.68%)
	Test: 38253 (24.29%)
	Test OOD: 11242 (7.14%)
Scaling data...
	No scaling applied
Data formatting complete.
--------------------------------
	Train: 72152 (45.77%)
	Val: 35929 (22.79%)
	Test: 38024 (24.12%)
	Test OOD: 11522 (7.31%)
	No scaling applied
		Model Seed: 10 Seed: 1 ID mean of (MSE, MAE): [124.06556     7.3023243]
		Model Seed: 10 Seed: 1 OOD mean of (MSE, MAE) stats: [110.00546     6.9061046]
		Model Seed: 10 Seed: 1 ID median of (MSE, MAE): [38.187637   5.2668905]
		Model Seed: 10 Seed: 1 OOD median of (MSE, MAE) stats: [34.078003  4.963751]
		Model Seed: 10 Seed: 1 ID likelihoods: -9.329343137305727
		Model Seed: 10 Seed: 1 OOD likelihoods: -9.269203719082345
		Model Seed: 10 Seed: 1 ID calibration errors: [0.55831763 0.40700867 0.25629439 0.16237603 0.09394193 0.05456416
 0.02789045 0.01226799 0.0085919  0.01288337 0.02148384 0.03181932]
		Model Seed: 10 Seed: 1 OOD calibration errors: [0.5484718  0.39749024 0.24705132 0.15426458 0.08708284 0.04916465
 0.02420584 0.01104744 0.01328292 0.02398021 0.03857197 0.05632067]
	Train: 72134 (45.80%)
	Val: 35684 (22.66%)
	Test: 38037 (24.15%)
	Test OOD: 11628 (7.38%)
	No scaling applied
		Model Seed: 10 Seed: 2 ID mean of (MSE, MAE): [146.6077     8.217678]
		Model Seed: 10 Seed: 2 OOD mean of (MSE, MAE) stats: [123.48274    7.622092]
		Model Seed: 10 Seed: 2 ID median of (MSE, MAE): [45.646313   6.0323753]
		Model Seed: 10 Seed: 2 OOD median of (MSE, MAE) stats: [37.2145     5.5186863]
		Model Seed: 10 Seed: 2 ID likelihoods: -9.412818729394669
		Model Seed: 10 Seed: 2 OOD likelihoods: -9.326988897346299
		Model Seed: 10 Seed: 2 ID calibration errors: [0.64581129 0.58086303 0.47430303 0.3919712  0.31133336 0.2563338
 0.17594595 0.16447474 0.1040889  0.10910449 0.10369159 0.08017493]
		Model Seed: 10 Seed: 2 OOD calibration errors: [0.67524779 0.62385987 0.51038183 0.42919643 0.32805886 0.27338994
 0.18137771 0.1666542  0.09854602 0.1030613  0.09558928 0.06857822]
	Model Seed: 10 ID mean of (MSE, MAE): [135.33662    7.760001]
	Model Seed: 10 OOD mean of (MSE, MAE): [116.7441     7.264098]
	Model Seed: 10 ID median of (MSE, MAE): [41.916977  5.649633]
	Model Seed: 10 OOD median of (MSE, MAE): [35.64625    5.2412186]
	Model Seed: 10 ID likelihoods: -9.371080933350198
	Model Seed: 10 OOD likelihoods: -9.298096308214323
	Model Seed: 10 ID calibration errors: [0.60206446 0.49393585 0.36529871 0.27717361 0.20263764 0.15544898
 0.1019182  0.08837137 0.0563404  0.06099393 0.06258772 0.05599712]
	Model Seed: 10 OOD calibration errors: [0.6118598  0.51067506 0.37871657 0.2917305  0.20757085 0.1612773
 0.10279178 0.08885082 0.05591447 0.06352076 0.06708063 0.06244945]
	Train: 72152 (45.77%)
	Val: 35929 (22.79%)
	Test: 38024 (24.12%)
	Test OOD: 11522 (7.31%)
	No scaling applied
		Model Seed: 11 Seed: 1 ID mean of (MSE, MAE): [124.06556     7.3023243]
		Model Seed: 11 Seed: 1 OOD mean of (MSE, MAE) stats: [110.00546     6.9061046]
		Model Seed: 11 Seed: 1 ID median of (MSE, MAE): [38.187637   5.2668905]
		Model Seed: 11 Seed: 1 OOD median of (MSE, MAE) stats: [34.078003  4.963751]
		Model Seed: 11 Seed: 1 ID likelihoods: -9.329343137305727
		Model Seed: 11 Seed: 1 OOD likelihoods: -9.269203719082345
		Model Seed: 11 Seed: 1 ID calibration errors: [0.55831763 0.40700867 0.25629439 0.16237603 0.09394193 0.05456416
 0.02789045 0.01226799 0.0085919  0.01288337 0.02148384 0.03181932]
		Model Seed: 11 Seed: 1 OOD calibration errors: [0.5484718  0.39749024 0.24705132 0.15426458 0.08708284 0.04916465
 0.02420584 0.01104744 0.01328292 0.02398021 0.03857197 0.05632067]
	Train: 72134 (45.80%)
	Val: 35684 (22.66%)
	Test: 38037 (24.15%)
	Test OOD: 11628 (7.38%)
	No scaling applied
		Model Seed: 11 Seed: 2 ID mean of (MSE, MAE): [146.6077     8.217678]
		Model Seed: 11 Seed: 2 OOD mean of (MSE, MAE) stats: [123.48274    7.622092]
		Model Seed: 11 Seed: 2 ID median of (MSE, MAE): [45.646313   6.0323753]
		Model Seed: 11 Seed: 2 OOD median of (MSE, MAE) stats: [37.2145     5.5186863]
		Model Seed: 11 Seed: 2 ID likelihoods: -9.412818729394669
		Model Seed: 11 Seed: 2 OOD likelihoods: -9.326988897346299
		Model Seed: 11 Seed: 2 ID calibration errors: [0.64581129 0.58086303 0.47430303 0.3919712  0.31133336 0.2563338
 0.17594595 0.16447474 0.1040889  0.10910449 0.10369159 0.08017493]
		Model Seed: 11 Seed: 2 OOD calibration errors: [0.67524779 0.62385987 0.51038183 0.42919643 0.32805886 0.27338994
 0.18137771 0.1666542  0.09854602 0.1030613  0.09558928 0.06857822]
	Model Seed: 11 ID mean of (MSE, MAE): [135.33662    7.760001]
	Model Seed: 11 OOD mean of (MSE, MAE): [116.7441     7.264098]
	Model Seed: 11 ID median of (MSE, MAE): [41.916977  5.649633]
	Model Seed: 11 OOD median of (MSE, MAE): [35.64625    5.2412186]
	Model Seed: 11 ID likelihoods: -9.371080933350198
	Model Seed: 11 OOD likelihoods: -9.298096308214323
	Model Seed: 11 ID calibration errors: [0.60206446 0.49393585 0.36529871 0.27717361 0.20263764 0.15544898
 0.1019182  0.08837137 0.0563404  0.06099393 0.06258772 0.05599712]
	Model Seed: 11 OOD calibration errors: [0.6118598  0.51067506 0.37871657 0.2917305  0.20757085 0.1612773
 0.10279178 0.08885082 0.05591447 0.06352076 0.06708063 0.06244945]
	Train: 72152 (45.77%)
	Val: 35929 (22.79%)
	Test: 38024 (24.12%)
	Test OOD: 11522 (7.31%)
	No scaling applied
		Model Seed: 12 Seed: 1 ID mean of (MSE, MAE): [124.06556     7.3023243]
		Model Seed: 12 Seed: 1 OOD mean of (MSE, MAE) stats: [110.00546     6.9061046]
		Model Seed: 12 Seed: 1 ID median of (MSE, MAE): [38.187637   5.2668905]
		Model Seed: 12 Seed: 1 OOD median of (MSE, MAE) stats: [34.078003  4.963751]
		Model Seed: 12 Seed: 1 ID likelihoods: -9.329343137305727
		Model Seed: 12 Seed: 1 OOD likelihoods: -9.269203719082345
		Model Seed: 12 Seed: 1 ID calibration errors: [0.55831763 0.40700867 0.25629439 0.16237603 0.09394193 0.05456416
 0.02789045 0.01226799 0.0085919  0.01288337 0.02148384 0.03181932]
		Model Seed: 12 Seed: 1 OOD calibration errors: [0.5484718  0.39749024 0.24705132 0.15426458 0.08708284 0.04916465
 0.02420584 0.01104744 0.01328292 0.02398021 0.03857197 0.05632067]
	Train: 72134 (45.80%)
	Val: 35684 (22.66%)
	Test: 38037 (24.15%)
	Test OOD: 11628 (7.38%)
	No scaling applied
		Model Seed: 12 Seed: 2 ID mean of (MSE, MAE): [146.6077     8.217678]
		Model Seed: 12 Seed: 2 OOD mean of (MSE, MAE) stats: [123.48274    7.622092]
		Model Seed: 12 Seed: 2 ID median of (MSE, MAE): [45.646313   6.0323753]
		Model Seed: 12 Seed: 2 OOD median of (MSE, MAE) stats: [37.2145     5.5186863]
		Model Seed: 12 Seed: 2 ID likelihoods: -9.412818729394669
		Model Seed: 12 Seed: 2 OOD likelihoods: -9.326988897346299
		Model Seed: 12 Seed: 2 ID calibration errors: [0.64581129 0.58086303 0.47430303 0.3919712  0.31133336 0.2563338
 0.17594595 0.16447474 0.1040889  0.10910449 0.10369159 0.08017493]
		Model Seed: 12 Seed: 2 OOD calibration errors: [0.67524779 0.62385987 0.51038183 0.42919643 0.32805886 0.27338994
 0.18137771 0.1666542  0.09854602 0.1030613  0.09558928 0.06857822]
	Model Seed: 12 ID mean of (MSE, MAE): [135.33662    7.760001]
	Model Seed: 12 OOD mean of (MSE, MAE): [116.7441     7.264098]
	Model Seed: 12 ID median of (MSE, MAE): [41.916977  5.649633]
	Model Seed: 12 OOD median of (MSE, MAE): [35.64625    5.2412186]
	Model Seed: 12 ID likelihoods: -9.371080933350198
	Model Seed: 12 OOD likelihoods: -9.298096308214323
	Model Seed: 12 ID calibration errors: [0.60206446 0.49393585 0.36529871 0.27717361 0.20263764 0.15544898
 0.1019182  0.08837137 0.0563404  0.06099393 0.06258772 0.05599712]
	Model Seed: 12 OOD calibration errors: [0.6118598  0.51067506 0.37871657 0.2917305  0.20757085 0.1612773
 0.10279178 0.08885082 0.05591447 0.06352076 0.06708063 0.06244945]
	Train: 72152 (45.77%)
	Val: 35929 (22.79%)
	Test: 38024 (24.12%)
	Test OOD: 11522 (7.31%)
	No scaling applied
		Model Seed: 13 Seed: 1 ID mean of (MSE, MAE): [124.06556     7.3023243]
		Model Seed: 13 Seed: 1 OOD mean of (MSE, MAE) stats: [110.00546     6.9061046]
		Model Seed: 13 Seed: 1 ID median of (MSE, MAE): [38.187637   5.2668905]
		Model Seed: 13 Seed: 1 OOD median of (MSE, MAE) stats: [34.078003  4.963751]
		Model Seed: 13 Seed: 1 ID likelihoods: -9.329343137305727
		Model Seed: 13 Seed: 1 OOD likelihoods: -9.269203719082345
		Model Seed: 13 Seed: 1 ID calibration errors: [0.55831763 0.40700867 0.25629439 0.16237603 0.09394193 0.05456416
 0.02789045 0.01226799 0.0085919  0.01288337 0.02148384 0.03181932]
		Model Seed: 13 Seed: 1 OOD calibration errors: [0.5484718  0.39749024 0.24705132 0.15426458 0.08708284 0.04916465
 0.02420584 0.01104744 0.01328292 0.02398021 0.03857197 0.05632067]
	Train: 72134 (45.80%)
	Val: 35684 (22.66%)
	Test: 38037 (24.15%)
	Test OOD: 11628 (7.38%)
	No scaling applied
		Model Seed: 13 Seed: 2 ID mean of (MSE, MAE): [146.6077     8.217678]
		Model Seed: 13 Seed: 2 OOD mean of (MSE, MAE) stats: [123.48274    7.622092]
		Model Seed: 13 Seed: 2 ID median of (MSE, MAE): [45.646313   6.0323753]
		Model Seed: 13 Seed: 2 OOD median of (MSE, MAE) stats: [37.2145     5.5186863]
		Model Seed: 13 Seed: 2 ID likelihoods: -9.412818729394669
		Model Seed: 13 Seed: 2 OOD likelihoods: -9.326988897346299
		Model Seed: 13 Seed: 2 ID calibration errors: [0.64581129 0.58086303 0.47430303 0.3919712  0.31133336 0.2563338
 0.17594595 0.16447474 0.1040889  0.10910449 0.10369159 0.08017493]
		Model Seed: 13 Seed: 2 OOD calibration errors: [0.67524779 0.62385987 0.51038183 0.42919643 0.32805886 0.27338994
 0.18137771 0.1666542  0.09854602 0.1030613  0.09558928 0.06857822]
	Model Seed: 13 ID mean of (MSE, MAE): [135.33662    7.760001]
	Model Seed: 13 OOD mean of (MSE, MAE): [116.7441     7.264098]
	Model Seed: 13 ID median of (MSE, MAE): [41.916977  5.649633]
	Model Seed: 13 OOD median of (MSE, MAE): [35.64625    5.2412186]
	Model Seed: 13 ID likelihoods: -9.371080933350198
	Model Seed: 13 OOD likelihoods: -9.298096308214323
	Model Seed: 13 ID calibration errors: [0.60206446 0.49393585 0.36529871 0.27717361 0.20263764 0.15544898
 0.1019182  0.08837137 0.0563404  0.06099393 0.06258772 0.05599712]
	Model Seed: 13 OOD calibration errors: [0.6118598  0.51067506 0.37871657 0.2917305  0.20757085 0.1612773
 0.10279178 0.08885082 0.05591447 0.06352076 0.06708063 0.06244945]
	Train: 72152 (45.77%)
	Val: 35929 (22.79%)
	Test: 38024 (24.12%)
	Test OOD: 11522 (7.31%)
	No scaling applied
		Model Seed: 14 Seed: 1 ID mean of (MSE, MAE): [124.06556     7.3023243]
		Model Seed: 14 Seed: 1 OOD mean of (MSE, MAE) stats: [110.00546     6.9061046]
		Model Seed: 14 Seed: 1 ID median of (MSE, MAE): [38.187637   5.2668905]
		Model Seed: 14 Seed: 1 OOD median of (MSE, MAE) stats: [34.078003  4.963751]
		Model Seed: 14 Seed: 1 ID likelihoods: -9.329343137305727
		Model Seed: 14 Seed: 1 OOD likelihoods: -9.269203719082345
		Model Seed: 14 Seed: 1 ID calibration errors: [0.55831763 0.40700867 0.25629439 0.16237603 0.09394193 0.05456416
 0.02789045 0.01226799 0.0085919  0.01288337 0.02148384 0.03181932]
		Model Seed: 14 Seed: 1 OOD calibration errors: [0.5484718  0.39749024 0.24705132 0.15426458 0.08708284 0.04916465
 0.02420584 0.01104744 0.01328292 0.02398021 0.03857197 0.05632067]
	Train: 72134 (45.80%)
	Val: 35684 (22.66%)
	Test: 38037 (24.15%)
	Test OOD: 11628 (7.38%)
	No scaling applied
		Model Seed: 14 Seed: 2 ID mean of (MSE, MAE): [146.6077     8.217678]
		Model Seed: 14 Seed: 2 OOD mean of (MSE, MAE) stats: [123.48274    7.622092]
		Model Seed: 14 Seed: 2 ID median of (MSE, MAE): [45.646313   6.0323753]
		Model Seed: 14 Seed: 2 OOD median of (MSE, MAE) stats: [37.2145     5.5186863]
		Model Seed: 14 Seed: 2 ID likelihoods: -9.412818729394669
		Model Seed: 14 Seed: 2 OOD likelihoods: -9.326988897346299
		Model Seed: 14 Seed: 2 ID calibration errors: [0.64581129 0.58086303 0.47430303 0.3919712  0.31133336 0.2563338
 0.17594595 0.16447474 0.1040889  0.10910449 0.10369159 0.08017493]
		Model Seed: 14 Seed: 2 OOD calibration errors: [0.67524779 0.62385987 0.51038183 0.42919643 0.32805886 0.27338994
 0.18137771 0.1666542  0.09854602 0.1030613  0.09558928 0.06857822]
	Model Seed: 14 ID mean of (MSE, MAE): [135.33662    7.760001]
	Model Seed: 14 OOD mean of (MSE, MAE): [116.7441     7.264098]
	Model Seed: 14 ID median of (MSE, MAE): [41.916977  5.649633]
	Model Seed: 14 OOD median of (MSE, MAE): [35.64625    5.2412186]
	Model Seed: 14 ID likelihoods: -9.371080933350198
	Model Seed: 14 OOD likelihoods: -9.298096308214323
	Model Seed: 14 ID calibration errors: [0.60206446 0.49393585 0.36529871 0.27717361 0.20263764 0.15544898
 0.1019182  0.08837137 0.0563404  0.06099393 0.06258772 0.05599712]
	Model Seed: 14 OOD calibration errors: [0.6118598  0.51067506 0.37871657 0.2917305  0.20757085 0.1612773
 0.10279178 0.08885082 0.05591447 0.06352076 0.06708063 0.06244945]
	Train: 72152 (45.77%)
	Val: 35929 (22.79%)
	Test: 38024 (24.12%)
	Test OOD: 11522 (7.31%)
	No scaling applied
		Model Seed: 15 Seed: 1 ID mean of (MSE, MAE): [124.06556     7.3023243]
		Model Seed: 15 Seed: 1 OOD mean of (MSE, MAE) stats: [110.00546     6.9061046]
		Model Seed: 15 Seed: 1 ID median of (MSE, MAE): [38.187637   5.2668905]
		Model Seed: 15 Seed: 1 OOD median of (MSE, MAE) stats: [34.078003  4.963751]
		Model Seed: 15 Seed: 1 ID likelihoods: -9.329343137305727
		Model Seed: 15 Seed: 1 OOD likelihoods: -9.269203719082345
		Model Seed: 15 Seed: 1 ID calibration errors: [0.55831763 0.40700867 0.25629439 0.16237603 0.09394193 0.05456416
 0.02789045 0.01226799 0.0085919  0.01288337 0.02148384 0.03181932]
		Model Seed: 15 Seed: 1 OOD calibration errors: [0.5484718  0.39749024 0.24705132 0.15426458 0.08708284 0.04916465
 0.02420584 0.01104744 0.01328292 0.02398021 0.03857197 0.05632067]
	Train: 72134 (45.80%)
	Val: 35684 (22.66%)
	Test: 38037 (24.15%)
	Test OOD: 11628 (7.38%)
	No scaling applied
		Model Seed: 15 Seed: 2 ID mean of (MSE, MAE): [146.6077     8.217678]
		Model Seed: 15 Seed: 2 OOD mean of (MSE, MAE) stats: [123.48274    7.622092]
		Model Seed: 15 Seed: 2 ID median of (MSE, MAE): [45.646313   6.0323753]
		Model Seed: 15 Seed: 2 OOD median of (MSE, MAE) stats: [37.2145     5.5186863]
		Model Seed: 15 Seed: 2 ID likelihoods: -9.412818729394669
		Model Seed: 15 Seed: 2 OOD likelihoods: -9.326988897346299
		Model Seed: 15 Seed: 2 ID calibration errors: [0.64581129 0.58086303 0.47430303 0.3919712  0.31133336 0.2563338
 0.17594595 0.16447474 0.1040889  0.10910449 0.10369159 0.08017493]
		Model Seed: 15 Seed: 2 OOD calibration errors: [0.67524779 0.62385987 0.51038183 0.42919643 0.32805886 0.27338994
 0.18137771 0.1666542  0.09854602 0.1030613  0.09558928 0.06857822]
	Model Seed: 15 ID mean of (MSE, MAE): [135.33662    7.760001]
	Model Seed: 15 OOD mean of (MSE, MAE): [116.7441     7.264098]
	Model Seed: 15 ID median of (MSE, MAE): [41.916977  5.649633]
	Model Seed: 15 OOD median of (MSE, MAE): [35.64625    5.2412186]
	Model Seed: 15 ID likelihoods: -9.371080933350198
	Model Seed: 15 OOD likelihoods: -9.298096308214323
	Model Seed: 15 ID calibration errors: [0.60206446 0.49393585 0.36529871 0.27717361 0.20263764 0.15544898
 0.1019182  0.08837137 0.0563404  0.06099393 0.06258772 0.05599712]
	Model Seed: 15 OOD calibration errors: [0.6118598  0.51067506 0.37871657 0.2917305  0.20757085 0.1612773
 0.10279178 0.08885082 0.05591447 0.06352076 0.06708063 0.06244945]
	Train: 72152 (45.77%)
	Val: 35929 (22.79%)
	Test: 38024 (24.12%)
	Test OOD: 11522 (7.31%)
	No scaling applied
		Model Seed: 16 Seed: 1 ID mean of (MSE, MAE): [124.06556     7.3023243]
		Model Seed: 16 Seed: 1 OOD mean of (MSE, MAE) stats: [110.00546     6.9061046]
		Model Seed: 16 Seed: 1 ID median of (MSE, MAE): [38.187637   5.2668905]
		Model Seed: 16 Seed: 1 OOD median of (MSE, MAE) stats: [34.078003  4.963751]
		Model Seed: 16 Seed: 1 ID likelihoods: -9.329343137305727
		Model Seed: 16 Seed: 1 OOD likelihoods: -9.269203719082345
		Model Seed: 16 Seed: 1 ID calibration errors: [0.55831763 0.40700867 0.25629439 0.16237603 0.09394193 0.05456416
 0.02789045 0.01226799 0.0085919  0.01288337 0.02148384 0.03181932]
		Model Seed: 16 Seed: 1 OOD calibration errors: [0.5484718  0.39749024 0.24705132 0.15426458 0.08708284 0.04916465
 0.02420584 0.01104744 0.01328292 0.02398021 0.03857197 0.05632067]
	Train: 72134 (45.80%)
	Val: 35684 (22.66%)
	Test: 38037 (24.15%)
	Test OOD: 11628 (7.38%)
	No scaling applied
		Model Seed: 16 Seed: 2 ID mean of (MSE, MAE): [146.6077     8.217678]
		Model Seed: 16 Seed: 2 OOD mean of (MSE, MAE) stats: [123.48274    7.622092]
		Model Seed: 16 Seed: 2 ID median of (MSE, MAE): [45.646313   6.0323753]
		Model Seed: 16 Seed: 2 OOD median of (MSE, MAE) stats: [37.2145     5.5186863]
		Model Seed: 16 Seed: 2 ID likelihoods: -9.412818729394669
		Model Seed: 16 Seed: 2 OOD likelihoods: -9.326988897346299
		Model Seed: 16 Seed: 2 ID calibration errors: [0.64581129 0.58086303 0.47430303 0.3919712  0.31133336 0.2563338
 0.17594595 0.16447474 0.1040889  0.10910449 0.10369159 0.08017493]
		Model Seed: 16 Seed: 2 OOD calibration errors: [0.67524779 0.62385987 0.51038183 0.42919643 0.32805886 0.27338994
 0.18137771 0.1666542  0.09854602 0.1030613  0.09558928 0.06857822]
	Model Seed: 16 ID mean of (MSE, MAE): [135.33662    7.760001]
	Model Seed: 16 OOD mean of (MSE, MAE): [116.7441     7.264098]
	Model Seed: 16 ID median of (MSE, MAE): [41.916977  5.649633]
	Model Seed: 16 OOD median of (MSE, MAE): [35.64625    5.2412186]
	Model Seed: 16 ID likelihoods: -9.371080933350198
	Model Seed: 16 OOD likelihoods: -9.298096308214323
	Model Seed: 16 ID calibration errors: [0.60206446 0.49393585 0.36529871 0.27717361 0.20263764 0.15544898
 0.1019182  0.08837137 0.0563404  0.06099393 0.06258772 0.05599712]
	Model Seed: 16 OOD calibration errors: [0.6118598  0.51067506 0.37871657 0.2917305  0.20757085 0.1612773
 0.10279178 0.08885082 0.05591447 0.06352076 0.06708063 0.06244945]
	Train: 72152 (45.77%)
	Val: 35929 (22.79%)
	Test: 38024 (24.12%)
	Test OOD: 11522 (7.31%)
	No scaling applied
		Model Seed: 17 Seed: 1 ID mean of (MSE, MAE): [124.06556     7.3023243]
		Model Seed: 17 Seed: 1 OOD mean of (MSE, MAE) stats: [110.00546     6.9061046]
		Model Seed: 17 Seed: 1 ID median of (MSE, MAE): [38.187637   5.2668905]
		Model Seed: 17 Seed: 1 OOD median of (MSE, MAE) stats: [34.078003  4.963751]
		Model Seed: 17 Seed: 1 ID likelihoods: -9.329343137305727
		Model Seed: 17 Seed: 1 OOD likelihoods: -9.269203719082345
		Model Seed: 17 Seed: 1 ID calibration errors: [0.55831763 0.40700867 0.25629439 0.16237603 0.09394193 0.05456416
 0.02789045 0.01226799 0.0085919  0.01288337 0.02148384 0.03181932]
		Model Seed: 17 Seed: 1 OOD calibration errors: [0.5484718  0.39749024 0.24705132 0.15426458 0.08708284 0.04916465
 0.02420584 0.01104744 0.01328292 0.02398021 0.03857197 0.05632067]
	Train: 72134 (45.80%)
	Val: 35684 (22.66%)
	Test: 38037 (24.15%)
	Test OOD: 11628 (7.38%)
	No scaling applied
		Model Seed: 17 Seed: 2 ID mean of (MSE, MAE): [146.6077     8.217678]
		Model Seed: 17 Seed: 2 OOD mean of (MSE, MAE) stats: [123.48274    7.622092]
		Model Seed: 17 Seed: 2 ID median of (MSE, MAE): [45.646313   6.0323753]
		Model Seed: 17 Seed: 2 OOD median of (MSE, MAE) stats: [37.2145     5.5186863]
		Model Seed: 17 Seed: 2 ID likelihoods: -9.412818729394669
		Model Seed: 17 Seed: 2 OOD likelihoods: -9.326988897346299
		Model Seed: 17 Seed: 2 ID calibration errors: [0.64581129 0.58086303 0.47430303 0.3919712  0.31133336 0.2563338
 0.17594595 0.16447474 0.1040889  0.10910449 0.10369159 0.08017493]
		Model Seed: 17 Seed: 2 OOD calibration errors: [0.67524779 0.62385987 0.51038183 0.42919643 0.32805886 0.27338994
 0.18137771 0.1666542  0.09854602 0.1030613  0.09558928 0.06857822]
	Model Seed: 17 ID mean of (MSE, MAE): [135.33662    7.760001]
	Model Seed: 17 OOD mean of (MSE, MAE): [116.7441     7.264098]
	Model Seed: 17 ID median of (MSE, MAE): [41.916977  5.649633]
	Model Seed: 17 OOD median of (MSE, MAE): [35.64625    5.2412186]
	Model Seed: 17 ID likelihoods: -9.371080933350198
	Model Seed: 17 OOD likelihoods: -9.298096308214323
	Model Seed: 17 ID calibration errors: [0.60206446 0.49393585 0.36529871 0.27717361 0.20263764 0.15544898
 0.1019182  0.08837137 0.0563404  0.06099393 0.06258772 0.05599712]
	Model Seed: 17 OOD calibration errors: [0.6118598  0.51067506 0.37871657 0.2917305  0.20757085 0.1612773
 0.10279178 0.08885082 0.05591447 0.06352076 0.06708063 0.06244945]
	Train: 72152 (45.77%)
	Val: 35929 (22.79%)
	Test: 38024 (24.12%)
	Test OOD: 11522 (7.31%)
	No scaling applied
		Model Seed: 18 Seed: 1 ID mean of (MSE, MAE): [124.06556     7.3023243]
		Model Seed: 18 Seed: 1 OOD mean of (MSE, MAE) stats: [110.00546     6.9061046]
		Model Seed: 18 Seed: 1 ID median of (MSE, MAE): [38.187637   5.2668905]
		Model Seed: 18 Seed: 1 OOD median of (MSE, MAE) stats: [34.078003  4.963751]
		Model Seed: 18 Seed: 1 ID likelihoods: -9.329343137305727
		Model Seed: 18 Seed: 1 OOD likelihoods: -9.269203719082345
		Model Seed: 18 Seed: 1 ID calibration errors: [0.55831763 0.40700867 0.25629439 0.16237603 0.09394193 0.05456416
 0.02789045 0.01226799 0.0085919  0.01288337 0.02148384 0.03181932]
		Model Seed: 18 Seed: 1 OOD calibration errors: [0.5484718  0.39749024 0.24705132 0.15426458 0.08708284 0.04916465
 0.02420584 0.01104744 0.01328292 0.02398021 0.03857197 0.05632067]
	Train: 72134 (45.80%)
	Val: 35684 (22.66%)
	Test: 38037 (24.15%)
	Test OOD: 11628 (7.38%)
	No scaling applied
		Model Seed: 18 Seed: 2 ID mean of (MSE, MAE): [146.6077     8.217678]
		Model Seed: 18 Seed: 2 OOD mean of (MSE, MAE) stats: [123.48274    7.622092]
		Model Seed: 18 Seed: 2 ID median of (MSE, MAE): [45.646313   6.0323753]
		Model Seed: 18 Seed: 2 OOD median of (MSE, MAE) stats: [37.2145     5.5186863]
		Model Seed: 18 Seed: 2 ID likelihoods: -9.412818729394669
		Model Seed: 18 Seed: 2 OOD likelihoods: -9.326988897346299
		Model Seed: 18 Seed: 2 ID calibration errors: [0.64581129 0.58086303 0.47430303 0.3919712  0.31133336 0.2563338
 0.17594595 0.16447474 0.1040889  0.10910449 0.10369159 0.08017493]
		Model Seed: 18 Seed: 2 OOD calibration errors: [0.67524779 0.62385987 0.51038183 0.42919643 0.32805886 0.27338994
 0.18137771 0.1666542  0.09854602 0.1030613  0.09558928 0.06857822]
	Model Seed: 18 ID mean of (MSE, MAE): [135.33662    7.760001]
	Model Seed: 18 OOD mean of (MSE, MAE): [116.7441     7.264098]
	Model Seed: 18 ID median of (MSE, MAE): [41.916977  5.649633]
	Model Seed: 18 OOD median of (MSE, MAE): [35.64625    5.2412186]
	Model Seed: 18 ID likelihoods: -9.371080933350198
	Model Seed: 18 OOD likelihoods: -9.298096308214323
	Model Seed: 18 ID calibration errors: [0.60206446 0.49393585 0.36529871 0.27717361 0.20263764 0.15544898
 0.1019182  0.08837137 0.0563404  0.06099393 0.06258772 0.05599712]
	Model Seed: 18 OOD calibration errors: [0.6118598  0.51067506 0.37871657 0.2917305  0.20757085 0.1612773
 0.10279178 0.08885082 0.05591447 0.06352076 0.06708063 0.06244945]
	Train: 72152 (45.77%)
	Val: 35929 (22.79%)
	Test: 38024 (24.12%)
	Test OOD: 11522 (7.31%)
	No scaling applied
		Model Seed: 19 Seed: 1 ID mean of (MSE, MAE): [124.06556     7.3023243]
		Model Seed: 19 Seed: 1 OOD mean of (MSE, MAE) stats: [110.00546     6.9061046]
		Model Seed: 19 Seed: 1 ID median of (MSE, MAE): [38.187637   5.2668905]
		Model Seed: 19 Seed: 1 OOD median of (MSE, MAE) stats: [34.078003  4.963751]
		Model Seed: 19 Seed: 1 ID likelihoods: -9.329343137305727
		Model Seed: 19 Seed: 1 OOD likelihoods: -9.269203719082345
		Model Seed: 19 Seed: 1 ID calibration errors: [0.55831763 0.40700867 0.25629439 0.16237603 0.09394193 0.05456416
 0.02789045 0.01226799 0.0085919  0.01288337 0.02148384 0.03181932]
		Model Seed: 19 Seed: 1 OOD calibration errors: [0.5484718  0.39749024 0.24705132 0.15426458 0.08708284 0.04916465
 0.02420584 0.01104744 0.01328292 0.02398021 0.03857197 0.05632067]
	Train: 72134 (45.80%)
	Val: 35684 (22.66%)
	Test: 38037 (24.15%)
	Test OOD: 11628 (7.38%)
	No scaling applied
		Model Seed: 19 Seed: 2 ID mean of (MSE, MAE): [146.6077     8.217678]
		Model Seed: 19 Seed: 2 OOD mean of (MSE, MAE) stats: [123.48274    7.622092]
		Model Seed: 19 Seed: 2 ID median of (MSE, MAE): [45.646313   6.0323753]
		Model Seed: 19 Seed: 2 OOD median of (MSE, MAE) stats: [37.2145     5.5186863]
		Model Seed: 19 Seed: 2 ID likelihoods: -9.412818729394669
		Model Seed: 19 Seed: 2 OOD likelihoods: -9.326988897346299
		Model Seed: 19 Seed: 2 ID calibration errors: [0.64581129 0.58086303 0.47430303 0.3919712  0.31133336 0.2563338
 0.17594595 0.16447474 0.1040889  0.10910449 0.10369159 0.08017493]
		Model Seed: 19 Seed: 2 OOD calibration errors: [0.67524779 0.62385987 0.51038183 0.42919643 0.32805886 0.27338994
 0.18137771 0.1666542  0.09854602 0.1030613  0.09558928 0.06857822]
	Model Seed: 19 ID mean of (MSE, MAE): [135.33662    7.760001]
	Model Seed: 19 OOD mean of (MSE, MAE): [116.7441     7.264098]
	Model Seed: 19 ID median of (MSE, MAE): [41.916977  5.649633]
	Model Seed: 19 OOD median of (MSE, MAE): [35.64625    5.2412186]
	Model Seed: 19 ID likelihoods: -9.371080933350198
	Model Seed: 19 OOD likelihoods: -9.298096308214323
	Model Seed: 19 ID calibration errors: [0.60206446 0.49393585 0.36529871 0.27717361 0.20263764 0.15544898
 0.1019182  0.08837137 0.0563404  0.06099393 0.06258772 0.05599712]
	Model Seed: 19 OOD calibration errors: [0.6118598  0.51067506 0.37871657 0.2917305  0.20757085 0.1612773
 0.10279178 0.08885082 0.05591447 0.06352076 0.06708063 0.06244945]
ID mean of (MSE, MAE): [135.33663940429688, 7.760001182556152] +- [1.52587890625e-05, 0.0] +- [11.27107     0.45767685] 
OOD mean of (MSE, MAE): [116.74410247802734, 7.264098167419434] +- [0.0, 0.0] +- [6.73864   0.3579937] 
ID median of (MSE, MAE): [41.9169807434082, 5.649632453918457] +- [3.814697265625e-06, 4.76837158203125e-07] +- [3.729338  0.3827424] 
OOD median of (MSE, MAE): [35.64624786376953, 5.241218566894531] +- [3.814697265625e-06, 0.0] +- [1.5682485  0.27746765] 
ID likelihoods: -9.371080933350198 +- 0.0 +- 0.0417377960444707 
OOD likelihoods: -9.298096308214323 +- 0.0 +- 0.028892589131976898 
ID calibration errors: [0.6020644614783707, 0.4939358488479374, 0.3652987124288272, 0.27717361239444477, 0.20263764149845315, 0.15544898407144708, 0.10191819704937177, 0.0883713697307178, 0.056340396792175326, 0.06099393248007878, 0.06258771637513126, 0.05599712267823355] +- [1.1102230246251565e-16, 5.551115123125783e-17, 5.551115123125783e-17, 0.0, 2.7755575615628914e-17, 2.7755575615628914e-17, 0.0, 0.0, 6.938893903907228e-18, 0.0, 0.0, 0.0] +- [0.04374683 0.08692718 0.10900432 0.11479759 0.10869571 0.10088482
 0.07402775 0.07610337 0.0477485  0.04811056 0.04110387 0.0241778 ] 
OOD calibration errors: [0.6118597965139049, 0.5106750574185238, 0.378716573349895, 0.291730502523572, 0.20757084932392605, 0.16127729555391637, 0.10279177705851542, 0.08885082184682837, 0.05591446991493183, 0.06352075590006769, 0.0670806250806747, 0.062449447733113575] +- [1.1102230246251565e-16, 1.1102230246251565e-16, 5.551115123125783e-17, 5.551115123125783e-17, 2.7755575615628914e-17, 0.0, 1.3877787807814457e-17, 1.3877787807814457e-17, 1.3877787807814457e-17, 1.3877787807814457e-17, 0.0, 1.3877787807814457e-17] +- [0.063388   0.11318482 0.13166526 0.13746593 0.12048801 0.11211264
 0.07858593 0.07780338 0.04263155 0.03954054 0.02850865 0.00612878] 
