Optimization started at 2023-02-25 01:31:35.234421--------------------------------
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: 14
	Extracted segments: 18
	Interpolated values: 643
	Percent of values interpolated: 4.75%
Splitting data...
	Train: 7950 (66.26%)
	Val: 2160 (18.00%)
	Test: 3212 (26.77%)
Scaling data...
	No scaling applied
Data formatting complete.
--------------------------------
Current value: 0.0525856651365757, Current params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.05845769867300987, Current params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 32, 'dropout': 0.09891974294121364, 'lr': 0.00046207382141893696, 'batch_size': 48, 'lr_epochs': 12, 'max_grad_norm': 0.2318691699794686}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.060184597969055176, Current params: {'in_len': 180, 'max_samples_per_ts': 100, 'd_model': 32, 'n_heads': 2, 'num_encoder_layers': 2, 'num_decoder_layers': 3, 'dim_feedforward': 32, 'dropout': 0.04710383974730199, 'lr': 0.0006424503751129345, 'batch_size': 32, 'lr_epochs': 4, 'max_grad_norm': 0.3731177060319636}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.06559624522924423, Current params: {'in_len': 120, 'max_samples_per_ts': 200, 'd_model': 128, 'n_heads': 2, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 160, 'dropout': 0.007784959672498749, 'lr': 0.0009679165583895666, 'batch_size': 64, 'lr_epochs': 16, 'max_grad_norm': 0.22289068876266221}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.055081818252801895, Current params: {'in_len': 156, 'max_samples_per_ts': 150, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 3, 'num_decoder_layers': 4, 'dim_feedforward': 128, 'dropout': 0.0621326010956843, 'lr': 0.0006201128643927709, 'batch_size': 48, 'lr_epochs': 2, 'max_grad_norm': 0.8392764706450961}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.06143699586391449, Current params: {'in_len': 180, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 256, 'dropout': 0.09343783870867867, 'lr': 0.000930008850520026, 'batch_size': 64, 'lr_epochs': 10, 'max_grad_norm': 0.19564887961459598}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.01839527301490307, Current params: {'in_len': 108, 'max_samples_per_ts': 150, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 480, 'dropout': 0.07815454790963326, 'lr': 0.0007070099421289264, 'batch_size': 48, 'lr_epochs': 18, 'max_grad_norm': 0.9557759139660817}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.013283534906804562, Current params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 128, 'n_heads': 2, 'num_encoder_layers': 1, 'num_decoder_layers': 1, 'dim_feedforward': 512, 'dropout': 0.13259359345733132, 'lr': 0.0007718347073728812, 'batch_size': 64, 'lr_epochs': 6, 'max_grad_norm': 0.9646240009994588}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.0215224027633667, Current params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 32, 'n_heads': 2, 'num_encoder_layers': 1, 'num_decoder_layers': 4, 'dim_feedforward': 32, 'dropout': 0.18073731013155644, 'lr': 0.0005738435946130933, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.24192714614477362}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.06308010965585709, Current params: {'in_len': 180, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 1, 'dim_feedforward': 480, 'dropout': 0.046505400465375636, 'lr': 0.00092046034400958, 'batch_size': 48, 'lr_epochs': 18, 'max_grad_norm': 0.171854800238481}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.053492844104766846, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 352, 'dropout': 0.14973428671615116, 'lr': 0.00023240699313199276, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.6452812534231841}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.053846683353185654, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 384, 'dropout': 0.15130195155008752, 'lr': 0.0001307732685512472, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.5904244685095886}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.020871328189969063, 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': 352, 'dropout': 0.14207138224477742, 'lr': 0.0003305004840990447, 'batch_size': 32, 'lr_epochs': 12, 'max_grad_norm': 0.5993951333342178}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.0207217987626791, Current params: {'in_len': 96, 'max_samples_per_ts': 100, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 3, 'num_decoder_layers': 2, 'dim_feedforward': 384, 'dropout': 0.19956828684447603, 'lr': 0.00010170220892562442, 'batch_size': 32, 'lr_epochs': 20, 'max_grad_norm': 0.4583866278839101}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.0604340024292469, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 288, 'dropout': 0.12075995320106084, 'lr': 0.00030196616429627144, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.7048327882855462}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.023669201880693436, Current params: {'in_len': 156, 'max_samples_per_ts': 100, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 2, 'dim_feedforward': 416, 'dropout': 0.16733381974741546, 'lr': 0.00045890251357679114, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.4651581285572589}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.010384984314441681, Current params: {'in_len': 192, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 3, 'num_decoder_layers': 1, 'dim_feedforward': 288, 'dropout': 0.11915869471948938, 'lr': 0.0008390613030421747, 'batch_size': 48, 'lr_epochs': 10, 'max_grad_norm': 0.7262706301358044}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.06101495027542114, Current params: {'in_len': 132, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 224, 'dropout': 0.1668515176177528, 'lr': 0.00026618701773825924, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.3720653393048141}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.01650540716946125, Current params: {'in_len': 108, 'max_samples_per_ts': 100, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.11369715876026878, 'lr': 0.0004616780907815539, 'batch_size': 32, 'lr_epochs': 6, 'max_grad_norm': 0.6603556006470946}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.017345719039440155, Current params: {'in_len': 156, 'max_samples_per_ts': 200, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 2, 'dim_feedforward': 352, 'dropout': 0.15763689816546234, 'lr': 0.00023633794098837645, 'batch_size': 48, 'lr_epochs': 16, 'max_grad_norm': 0.8161879890848696}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.07456471771001816, Current params: {'in_len': 168, 'max_samples_per_ts': 50, 'd_model': 64, 'n_heads': 2, 'num_encoder_layers': 3, 'num_decoder_layers': 1, 'dim_feedforward': 352, 'dropout': 0.19555053060142077, 'lr': 0.00040318423623294364, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.47759194336071464}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.05432223901152611, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 416, 'dropout': 0.14664481033562268, 'lr': 0.00016034631736382436, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.5410522667647875}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.06003241240978241, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 320, 'dropout': 0.13801963710739784, 'lr': 0.00018329127526424833, 'batch_size': 32, 'lr_epochs': 12, 'max_grad_norm': 0.602717450274456}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.017974939197301865, Current params: {'in_len': 108, 'max_samples_per_ts': 100, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 416, 'dropout': 0.1561009137392253, 'lr': 0.00014050236551277847, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.34721352490694657}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.06671441346406937, Current params: {'in_len': 132, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 448, 'dropout': 0.17198969153414556, 'lr': 0.00036145396479779105, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.5365948982512714}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.01996501348912716, Current params: {'in_len': 108, 'max_samples_per_ts': 100, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 512, 'dropout': 0.12415207590379249, 'lr': 0.00022248595927171048, 'batch_size': 48, 'lr_epochs': 14, 'max_grad_norm': 0.7779774546252869}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.01794476807117462, Current params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 384, 'dropout': 0.18388294625885787, 'lr': 0.0005156321636876574, 'batch_size': 32, 'lr_epochs': 18, 'max_grad_norm': 0.6492576478171018}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.00729712937027216, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 3, 'num_decoder_layers': 2, 'dim_feedforward': 192, 'dropout': 0.105820360457853, 'lr': 0.0008212430330826924, 'batch_size': 32, 'lr_epochs': 12, 'max_grad_norm': 0.3293194801156889}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.022769447416067123, Current params: {'in_len': 120, 'max_samples_per_ts': 100, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 3, 'dim_feedforward': 320, 'dropout': 0.1515471321466748, 'lr': 0.00037553380131382746, 'batch_size': 48, 'lr_epochs': 20, 'max_grad_norm': 0.43398146966738005}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.0231527891010046, Current params: {'in_len': 108, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 3, 'num_decoder_layers': 4, 'dim_feedforward': 384, 'dropout': 0.08190266050285513, 'lr': 0.0007237424619639487, 'batch_size': 48, 'lr_epochs': 10, 'max_grad_norm': 0.5652857424945452}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.057084519416093826, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.0983266217164978, 'lr': 0.0002109373374367377, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.2993398093315842}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.05733244866132736, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 416, 'dropout': 0.1447115922549875, 'lr': 0.00013995023483941735, 'batch_size': 32, 'lr_epochs': 12, 'max_grad_norm': 0.530391408891703}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.053531549870967865, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 480, 'dropout': 0.1297694408693445, 'lr': 0.00010340138334013181, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.4145993296944296}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.007376824971288443, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 3, 'dim_feedforward': 480, 'dropout': 0.1309525484690066, 'lr': 0.00010505180412000406, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.4004469737340874}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.017122894525527954, Current params: {'in_len': 120, 'max_samples_per_ts': 100, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 512, 'dropout': 0.10440077877483935, 'lr': 0.0003041132480522019, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.5067891953560766}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.006307751405984163, Current params: {'in_len': 168, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 3, 'num_decoder_layers': 3, 'dim_feedforward': 320, 'dropout': 0.003964475047000676, 'lr': 0.0002668052252660056, 'batch_size': 32, 'lr_epochs': 12, 'max_grad_norm': 0.12556206651041169}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.024762161076068878, Current params: {'in_len': 96, 'max_samples_per_ts': 150, 'd_model': 128, 'n_heads': 2, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 448, 'dropout': 0.1293985406950662, 'lr': 0.0006570226187038706, 'batch_size': 64, 'lr_epochs': 14, 'max_grad_norm': 0.2838465960952061}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.008846775628626347, Current params: {'in_len': 192, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 3, 'dim_feedforward': 384, 'dropout': 0.03159518842614835, 'lr': 0.00018728341252776146, 'batch_size': 32, 'lr_epochs': 2, 'max_grad_norm': 0.41217991286657746}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.016987523064017296, Current params: {'in_len': 108, 'max_samples_per_ts': 100, 'd_model': 128, 'n_heads': 2, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 480, 'dropout': 0.08368005481494595, 'lr': 0.0005588869023377645, 'batch_size': 48, 'lr_epochs': 10, 'max_grad_norm': 0.6000384487319811}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.025010067969560623, Current params: {'in_len': 132, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 3, 'num_decoder_layers': 2, 'dim_feedforward': 128, 'dropout': 0.16032774367209146, 'lr': 0.0009072468209733003, 'batch_size': 32, 'lr_epochs': 6, 'max_grad_norm': 0.723625374802043}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.017915714532136917, Current params: {'in_len': 168, 'max_samples_per_ts': 200, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 256, 'dropout': 0.18012088393743322, 'lr': 0.00025951816515970756, 'batch_size': 32, 'lr_epochs': 18, 'max_grad_norm': 0.6637380233888726}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.005963427480310202, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 416, 'dropout': 0.14537495621079322, 'lr': 0.0009929708985019936, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.579527872100854}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.05530892312526703, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 480, 'dropout': 0.13777317328075134, 'lr': 0.00016308100175303688, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.4948914991166802}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.007486344315111637, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 352, 'dropout': 0.15106376542106392, 'lr': 0.00010534606076449015, 'batch_size': 32, 'lr_epochs': 12, 'max_grad_norm': 0.9040682665105371}
Best value: 0.0525856651365757, Best params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12707062966155555, 'lr': 0.0008757674794166835, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.45452462135986815}
Current value: 0.051956433802843094, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 416, 'dropout': 0.13298788460836478, 'lr': 0.00016968246458069517, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.6242066011314422}
Best value: 0.051956433802843094, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 416, 'dropout': 0.13298788460836478, 'lr': 0.00016968246458069517, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.6242066011314422}
Current value: 0.006406721193343401, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 3, 'dim_feedforward': 448, 'dropout': 0.1132666962683252, 'lr': 0.00020821095051526306, 'batch_size': 32, 'lr_epochs': 12, 'max_grad_norm': 0.6312156791954358}
Best value: 0.051956433802843094, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 416, 'dropout': 0.13298788460836478, 'lr': 0.00016968246458069517, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.6242066011314422}
Current value: 0.006090369541198015, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 2, 'dim_feedforward': 512, 'dropout': 0.1365542503557478, 'lr': 0.00030381306857366655, 'batch_size': 64, 'lr_epochs': 8, 'max_grad_norm': 0.7577121254083945}
Best value: 0.051956433802843094, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 416, 'dropout': 0.13298788460836478, 'lr': 0.00016968246458069517, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.6242066011314422}
Current value: 0.029167456552386284, Current params: {'in_len': 96, 'max_samples_per_ts': 100, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 3, 'num_decoder_layers': 1, 'dim_feedforward': 64, 'dropout': 0.12868953227741795, 'lr': 0.00013435879620458363, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.686073553245264}
Best value: 0.051956433802843094, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 416, 'dropout': 0.13298788460836478, 'lr': 0.00016968246458069517, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.6242066011314422}
Current value: 0.008117392659187317, Current params: {'in_len': 144, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 4, 'num_decoder_layers': 3, 'dim_feedforward': 384, 'dropout': 0.06507798101835033, 'lr': 0.00041605728915742517, 'batch_size': 32, 'lr_epochs': 18, 'max_grad_norm': 0.4509863592781419}
Best value: 0.051956433802843094, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 416, 'dropout': 0.13298788460836478, 'lr': 0.00016968246458069517, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.6242066011314422}
Current value: 0.006282048299908638, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 3, 'num_decoder_layers': 4, 'dim_feedforward': 320, 'dropout': 0.11267650164058822, 'lr': 0.0006117524384204223, 'batch_size': 48, 'lr_epochs': 10, 'max_grad_norm': 0.3868981041970705}
Best value: 0.051956433802843094, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 416, 'dropout': 0.13298788460836478, 'lr': 0.00016968246458069517, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.6242066011314422}
Current value: 0.020744943991303444, 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': 0.0947018541434814, 'lr': 0.00024630498569980317, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.6296655500840959}
Best value: 0.051956433802843094, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 416, 'dropout': 0.13298788460836478, 'lr': 0.00016968246458069517, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.6242066011314422}
Current value: 0.007321624550968409, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 416, 'dropout': 0.15067416883287488, 'lr': 0.00016347947788833257, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.48862671342826586}
Best value: 0.051956433802843094, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 416, 'dropout': 0.13298788460836478, 'lr': 0.00016968246458069517, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.6242066011314422}
Current value: 0.006814830005168915, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 416, 'dropout': 0.16923113681319202, 'lr': 0.00017978594762962311, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.5461603929891463}
Best value: 0.051956433802843094, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 416, 'dropout': 0.13298788460836478, 'lr': 0.00016968246458069517, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.6242066011314422}
Current value: 0.006191352382302284, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 384, 'dropout': 0.11888453749685123, 'lr': 0.00013035545501164972, 'batch_size': 32, 'lr_epochs': 12, 'max_grad_norm': 0.5218308913433781}
Best value: 0.051956433802843094, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 416, 'dropout': 0.13298788460836478, 'lr': 0.00016968246458069517, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.6242066011314422}
Current value: 0.05643037334084511, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 352, 'dropout': 0.15822353672033138, 'lr': 0.0005078874894505776, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.572250637657172}
Best value: 0.051956433802843094, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 416, 'dropout': 0.13298788460836478, 'lr': 0.00016968246458069517, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.6242066011314422}
Current value: 0.00744165712967515, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 448, 'dropout': 0.13791803949129752, 'lr': 0.0001962132179162945, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.688848047295386}
Best value: 0.051956433802843094, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 416, 'dropout': 0.13298788460836478, 'lr': 0.00016968246458069517, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.6242066011314422}
Current value: 0.016472304239869118, Current params: {'in_len': 96, 'max_samples_per_ts': 150, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 288, 'dropout': 0.12464379235080955, 'lr': 0.0001571935374289461, 'batch_size': 32, 'lr_epochs': 8, 'max_grad_norm': 0.6153400695154222}
Best value: 0.051956433802843094, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 416, 'dropout': 0.13298788460836478, 'lr': 0.00016968246458069517, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.6242066011314422}
Current value: 0.006695530377328396, Current params: {'in_len': 144, 'max_samples_per_ts': 50, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 448, 'dropout': 0.14559446995969563, 'lr': 0.0001059215085005956, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.42100500351913966}
Best value: 0.051956433802843094, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 416, 'dropout': 0.13298788460836478, 'lr': 0.00016968246458069517, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.6242066011314422}
Current value: 0.0180243868380785, Current params: {'in_len': 108, 'max_samples_per_ts': 100, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 3, 'num_decoder_layers': 1, 'dim_feedforward': 416, 'dropout': 0.17752569575861463, 'lr': 0.00028173933480459397, 'batch_size': 32, 'lr_epochs': 18, 'max_grad_norm': 0.7531713727406357}
Best value: 0.051956433802843094, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 416, 'dropout': 0.13298788460836478, 'lr': 0.00016968246458069517, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.6242066011314422}
Current value: 0.0075821783393621445, Current params: {'in_len': 156, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 384, 'dropout': 0.16343136776321907, 'lr': 0.00022905683121337558, 'batch_size': 32, 'lr_epochs': 12, 'max_grad_norm': 0.46195422815620835}
Best value: 0.051956433802843094, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 416, 'dropout': 0.13298788460836478, 'lr': 0.00016968246458069517, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.6242066011314422}
Current value: 0.009023374877870083, Current params: {'in_len': 180, 'max_samples_per_ts': 50, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 352, 'dropout': 0.10824721448232627, 'lr': 0.0003320040973804764, 'batch_size': 48, 'lr_epochs': 14, 'max_grad_norm': 0.3709795808587372}
Best value: 0.051956433802843094, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 416, 'dropout': 0.13298788460836478, 'lr': 0.00016968246458069517, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.6242066011314422}
Current value: 0.019549408927559853, Current params: {'in_len': 156, 'max_samples_per_ts': 150, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 2, 'num_decoder_layers': 4, 'dim_feedforward': 128, 'dropout': 0.03292273857272422, 'lr': 0.0007570675283288717, 'batch_size': 64, 'lr_epochs': 2, 'max_grad_norm': 0.8693291086000642}
Best value: 0.051956433802843094, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 416, 'dropout': 0.13298788460836478, 'lr': 0.00016968246458069517, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.6242066011314422}
Current value: 0.02094532735645771, Current params: {'in_len': 156, 'max_samples_per_ts': 150, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 4, 'dim_feedforward': 224, 'dropout': 0.06692140513567645, 'lr': 0.0008710566657523969, 'batch_size': 48, 'lr_epochs': 4, 'max_grad_norm': 0.809602963079764}
Best value: 0.051956433802843094, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 416, 'dropout': 0.13298788460836478, 'lr': 0.00016968246458069517, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.6242066011314422}
Current value: 0.023226266726851463, Current params: {'in_len': 180, 'max_samples_per_ts': 150, 'd_model': 64, 'n_heads': 4, 'num_encoder_layers': 1, 'num_decoder_layers': 3, 'dim_feedforward': 32, 'dropout': 0.1889748999800101, 'lr': 0.000681950121771931, 'batch_size': 32, 'lr_epochs': 4, 'max_grad_norm': 0.9304477647431574}
Best value: 0.051956433802843094, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 416, 'dropout': 0.13298788460836478, 'lr': 0.00016968246458069517, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.6242066011314422}
Current value: 0.010561970993876457, Current params: {'in_len': 144, 'max_samples_per_ts': 200, 'd_model': 128, 'n_heads': 4, 'num_encoder_layers': 3, 'num_decoder_layers': 2, 'dim_feedforward': 96, 'dropout': 0.020699226743025934, 'lr': 0.0006332998898572639, 'batch_size': 64, 'lr_epochs': 14, 'max_grad_norm': 0.8324392971616795}
Best value: 0.051956433802843094, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 416, 'dropout': 0.13298788460836478, 'lr': 0.00016968246458069517, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.6242066011314422}
Current value: 0.024150876328349113, Current params: {'in_len': 96, 'max_samples_per_ts': 150, 'd_model': 32, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 3, 'dim_feedforward': 192, 'dropout': 0.06107927906856186, 'lr': 0.0007798531081612506, 'batch_size': 48, 'lr_epochs': 14, 'max_grad_norm': 0.33999260856636637}
Best value: 0.051956433802843094, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 2, 'dim_feedforward': 416, 'dropout': 0.13298788460836478, 'lr': 0.00016968246458069517, 'batch_size': 32, 'lr_epochs': 14, 'max_grad_norm': 0.6242066011314422}
Current value: 0.049381669610738754, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 416, 'dropout': 0.08746873074119388, 'lr': 0.0009365417441693891, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.5602980233515981}
Best value: 0.049381669610738754, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 416, 'dropout': 0.08746873074119388, 'lr': 0.0009365417441693891, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.5602980233515981}
Current value: 0.05269525945186615, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 416, 'dropout': 0.07311997436982483, 'lr': 0.0009635383806776537, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.5520124817805293}
Best value: 0.049381669610738754, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 416, 'dropout': 0.08746873074119388, 'lr': 0.0009365417441693891, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.5602980233515981}
Current value: 0.05237231031060219, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.07770168386963773, 'lr': 0.0009446332083717599, 'batch_size': 32, 'lr_epochs': 18, 'max_grad_norm': 0.5854640135854703}
Best value: 0.049381669610738754, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 416, 'dropout': 0.08746873074119388, 'lr': 0.0009365417441693891, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.5602980233515981}
Current value: 0.06040274351835251, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 512, 'dropout': 0.05458206614914787, 'lr': 0.000948522351737501, 'batch_size': 32, 'lr_epochs': 20, 'max_grad_norm': 0.5590116830915721}
Best value: 0.049381669610738754, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 416, 'dropout': 0.08746873074119388, 'lr': 0.0009365417441693891, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.5602980233515981}
Current value: 0.05740438029170036, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.07385460766526293, 'lr': 0.0008858324958915285, 'batch_size': 32, 'lr_epochs': 18, 'max_grad_norm': 0.5205481021787206}
Best value: 0.049381669610738754, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 416, 'dropout': 0.08746873074119388, 'lr': 0.0009365417441693891, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.5602980233515981}
Current value: 0.05055929720401764, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 480, 'dropout': 0.09009233924555896, 'lr': 0.0009710169195642898, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.591359263182822}
Best value: 0.049381669610738754, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 416, 'dropout': 0.08746873074119388, 'lr': 0.0009365417441693891, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.5602980233515981}
Current value: 0.005889092106372118, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 480, 'dropout': 0.08945438800348621, 'lr': 0.000997665287067742, 'batch_size': 32, 'lr_epochs': 18, 'max_grad_norm': 0.6479411133095034}
Best value: 0.049381669610738754, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 416, 'dropout': 0.08746873074119388, 'lr': 0.0009365417441693891, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.5602980233515981}
Current value: 0.054448239505290985, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 480, 'dropout': 0.0739425399992385, 'lr': 0.0009433427424681414, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.5950025282892493}
Best value: 0.049381669610738754, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 416, 'dropout': 0.08746873074119388, 'lr': 0.0009365417441693891, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.5602980233515981}
Current value: 0.07490619271993637, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 512, 'dropout': 0.08853862787712331, 'lr': 0.0009653992755658182, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.4375715497283377}
Best value: 0.049381669610738754, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 416, 'dropout': 0.08746873074119388, 'lr': 0.0009365417441693891, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.5602980233515981}
Current value: 0.04539022222161293, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.10161152207464333, 'lr': 0.000840888489686657, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.6740479322943925}
Best value: 0.04539022222161293, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.10161152207464333, 'lr': 0.000840888489686657, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.6740479322943925}
Current value: 0.05291871726512909, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 416, 'dropout': 0.0744085450521759, 'lr': 0.0008427312194989222, 'batch_size': 32, 'lr_epochs': 18, 'max_grad_norm': 0.6764432196953293}
Best value: 0.04539022222161293, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.10161152207464333, 'lr': 0.000840888489686657, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.6740479322943925}
Current value: 0.05740685760974884, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 416, 'dropout': 0.07778494712507572, 'lr': 0.0008421444194617505, 'batch_size': 32, 'lr_epochs': 20, 'max_grad_norm': 0.7036182299775681}
Best value: 0.04539022222161293, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.10161152207464333, 'lr': 0.000840888489686657, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.6740479322943925}
Current value: 0.006013435311615467, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.09913088562392905, 'lr': 0.000917454565566603, 'batch_size': 32, 'lr_epochs': 18, 'max_grad_norm': 0.6696694015034726}
Best value: 0.04539022222161293, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.10161152207464333, 'lr': 0.000840888489686657, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.6740479322943925}
Current value: 0.006092534866183996, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 416, 'dropout': 0.08815482877870799, 'lr': 0.0008138227753137024, 'batch_size': 32, 'lr_epochs': 20, 'max_grad_norm': 0.6135159414299302}
Best value: 0.04539022222161293, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.10161152207464333, 'lr': 0.000840888489686657, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.6740479322943925}
Current value: 0.006139605306088924, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.0724519548901346, 'lr': 0.0008603726937418166, 'batch_size': 32, 'lr_epochs': 18, 'max_grad_norm': 0.7294212115843456}
Best value: 0.04539022222161293, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.10161152207464333, 'lr': 0.000840888489686657, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.6740479322943925}
Current value: 0.0055387308821082115, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 384, 'dropout': 0.0817748851766271, 'lr': 0.0008975004005606189, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.6415686568566237}
Best value: 0.04539022222161293, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.10161152207464333, 'lr': 0.000840888489686657, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.6740479322943925}
Current value: 0.007698981557041407, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.05111203756443267, 'lr': 0.0009724663997460065, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.576630295814219}
Best value: 0.04539022222161293, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.10161152207464333, 'lr': 0.000840888489686657, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.6740479322943925}
Current value: 0.051384519785642624, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 416, 'dropout': 0.09235671533747594, 'lr': 0.0009274857855890895, 'batch_size': 32, 'lr_epochs': 18, 'max_grad_norm': 0.671920214282118}
Best value: 0.04539022222161293, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.10161152207464333, 'lr': 0.000840888489686657, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.6740479322943925}
Current value: 0.06530150026082993, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 416, 'dropout': 0.1028337630894696, 'lr': 0.0009382957067902636, 'batch_size': 32, 'lr_epochs': 18, 'max_grad_norm': 0.673535025625673}
Best value: 0.04539022222161293, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.10161152207464333, 'lr': 0.000840888489686657, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.6740479322943925}
Current value: 0.053473398089408875, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 480, 'dropout': 0.09219076378402015, 'lr': 0.0009212117448037193, 'batch_size': 32, 'lr_epochs': 18, 'max_grad_norm': 0.6203449739869806}
Best value: 0.04539022222161293, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.10161152207464333, 'lr': 0.000840888489686657, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.6740479322943925}
Current value: 0.006176728289574385, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 416, 'dropout': 0.08507193012837891, 'lr': 0.000973927024532718, 'batch_size': 32, 'lr_epochs': 20, 'max_grad_norm': 0.548816488480866}
Best value: 0.04539022222161293, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.10161152207464333, 'lr': 0.000840888489686657, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.6740479322943925}
Current value: 0.013897601515054703, Current params: {'in_len': 108, 'max_samples_per_ts': 100, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.09760448677127534, 'lr': 0.0008821879728008966, 'batch_size': 32, 'lr_epochs': 18, 'max_grad_norm': 0.7010147531176102}
Best value: 0.04539022222161293, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.10161152207464333, 'lr': 0.000840888489686657, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.6740479322943925}
Current value: 0.005658756010234356, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 2, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 480, 'dropout': 0.057566039030208245, 'lr': 0.000805269890545729, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.5856993063989354}
Best value: 0.04539022222161293, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.10161152207464333, 'lr': 0.000840888489686657, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.6740479322943925}
Current value: 0.0070223938673734665, Current params: {'in_len': 192, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 416, 'dropout': 0.07916723869834748, 'lr': 0.0008570557596027808, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.503768334371577}
Best value: 0.04539022222161293, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.10161152207464333, 'lr': 0.000840888489686657, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.6740479322943925}
Current value: 0.006473281420767307, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 384, 'dropout': 0.07068626277405977, 'lr': 0.0009006475815163993, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.7252249224500888}
Best value: 0.04539022222161293, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.10161152207464333, 'lr': 0.000840888489686657, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.6740479322943925}
Current value: 0.005733065772801638, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 480, 'dropout': 0.0901890627681394, 'lr': 0.0009258536023871903, 'batch_size': 32, 'lr_epochs': 18, 'max_grad_norm': 0.62783722640165}
Best value: 0.04539022222161293, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.10161152207464333, 'lr': 0.000840888489686657, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.6740479322943925}
Current value: 0.05767305567860603, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.09397291004556226, 'lr': 0.0008401586365912097, 'batch_size': 32, 'lr_epochs': 18, 'max_grad_norm': 0.6097606900341316}
Best value: 0.04539022222161293, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.10161152207464333, 'lr': 0.000840888489686657, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.6740479322943925}
Current value: 0.05277661979198456, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 480, 'dropout': 0.10865030854852722, 'lr': 0.000925753231262351, 'batch_size': 32, 'lr_epochs': 18, 'max_grad_norm': 0.6545369861809964}
Best value: 0.04539022222161293, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.10161152207464333, 'lr': 0.000840888489686657, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.6740479322943925}
Current value: 0.005798600148409605, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 512, 'dropout': 0.10765240735543798, 'lr': 0.0009600360941701135, 'batch_size': 32, 'lr_epochs': 20, 'max_grad_norm': 0.6711911792584302}
Best value: 0.04539022222161293, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.10161152207464333, 'lr': 0.000840888489686657, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.6740479322943925}
Current value: 0.005810882896184921, Current params: {'in_len': 132, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.11545852542079306, 'lr': 0.0009831619865999953, 'batch_size': 32, 'lr_epochs': 18, 'max_grad_norm': 0.7559020241046701}
Best value: 0.04539022222161293, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.10161152207464333, 'lr': 0.000840888489686657, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.6740479322943925}
Current value: 0.005733794998377562, Current params: {'in_len': 108, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 480, 'dropout': 0.07783684160016574, 'lr': 0.0009468545346593435, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.6545423718634936}
Best value: 0.04539022222161293, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.10161152207464333, 'lr': 0.000840888489686657, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.6740479322943925}
Current value: 0.0063958982937037945, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 416, 'dropout': 0.10344183947938704, 'lr': 0.0008849173102695774, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.5581967632761954}
Best value: 0.04539022222161293, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.10161152207464333, 'lr': 0.000840888489686657, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.6740479322943925}
Current value: 0.006116156466305256, Current params: {'in_len': 120, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 384, 'dropout': 0.08531689624678133, 'lr': 0.0009103928584267434, 'batch_size': 32, 'lr_epochs': 20, 'max_grad_norm': 0.5320090487488951}
Best value: 0.04539022222161293, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.10161152207464333, 'lr': 0.000840888489686657, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.6740479322943925}
Current value: 0.052153393626213074, Current params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.12365190036572044, 'lr': 0.0007879860577963434, 'batch_size': 32, 'lr_epochs': 10, 'max_grad_norm': 0.5922199403827956}
Best value: 0.04539022222161293, Best params: {'in_len': 96, 'max_samples_per_ts': 50, 'd_model': 96, 'n_heads': 4, 'num_encoder_layers': 4, 'num_decoder_layers': 1, 'dim_feedforward': 448, 'dropout': 0.10161152207464333, 'lr': 0.000840888489686657, 'batch_size': 32, 'lr_epochs': 16, 'max_grad_norm': 0.6740479322943925}
--------------------------------
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)
		time_second: REAL_VALUED (KNOWN_INPUT)
Interpolating data...
	Dropped segments: 17
	Extracted segments: 15
	Interpolated values: 561
	Percent of values interpolated: 4.37%
Splitting data...
	Train: 9056 (64.79%)
	Val: 1774 (12.69%)
	Test: 1848 (13.22%)
	Test OOD: 1300 (9.30%)
Scaling data...
	No scaling applied
Data formatting complete.
--------------------------------
	Train: 9056 (64.79%)
	Val: 1774 (12.69%)
	Test: 1848 (13.22%)
	Test OOD: 1300 (9.30%)
	No scaling applied
		Model Seed: 10 Seed: 1 ID mean of (MSE, MAE): [557.87885   17.989094]
		Model Seed: 10 Seed: 1 OOD mean of (MSE, MAE) stats: [481.1013    15.677579]
		Model Seed: 10 Seed: 1 ID median of (MSE, MAE): [295.6076    15.511268]
		Model Seed: 10 Seed: 1 OOD median of (MSE, MAE) stats: [213.74767    13.1071005]
		Model Seed: 10 Seed: 1 ID likelihoods: -10.081009605081153
		Model Seed: 10 Seed: 1 OOD likelihoods: -10.006977223975534
		Model Seed: 10 Seed: 1 ID calibration errors: [0.5309274  0.40039278 0.30183694 0.22640746 0.21858064 0.21400813
 0.39436421 0.24195745 0.31334061 0.28860643 0.21885985 0.20888415]
		Model Seed: 10 Seed: 1 OOD calibration errors: [0.50114702 0.35703966 0.25633237 0.1725872  0.12826669 0.12215801
 0.25461145 0.11869009 0.17330796 0.14150694 0.11450162 0.11358221]
	Train: 9056 (64.79%)
	Val: 1774 (12.69%)
	Test: 1848 (13.22%)
	Test OOD: 1300 (9.30%)
	No scaling applied
		Model Seed: 10 Seed: 2 ID mean of (MSE, MAE): [390.98834   13.961954]
		Model Seed: 10 Seed: 2 OOD mean of (MSE, MAE) stats: [428.60852   14.264388]
		Model Seed: 10 Seed: 2 ID median of (MSE, MAE): [161.6217    10.885485]
		Model Seed: 10 Seed: 2 OOD median of (MSE, MAE) stats: [180.31459   11.453397]
		Model Seed: 10 Seed: 2 ID likelihoods: -9.903277444437574
		Model Seed: 10 Seed: 2 OOD likelihoods: -9.949210550156154
		Model Seed: 10 Seed: 2 ID calibration errors: [0.66044039 0.31116098 0.16750942 0.09189893 0.07069084 0.03413807
 0.0444877  0.03985519 0.09256199 0.13360246 0.17000099 0.09402995]
		Model Seed: 10 Seed: 2 OOD calibration errors: [0.66337318 0.34437743 0.19252374 0.10832493 0.10320891 0.04507784
 0.06974895 0.05450836 0.11125489 0.17653549 0.2201509  0.13194641]
	Model Seed: 10 ID mean of (MSE, MAE): [474.4336    15.975524]
	Model Seed: 10 OOD mean of (MSE, MAE): [454.85492    14.9709835]
	Model Seed: 10 ID median of (MSE, MAE): [228.61465   13.198376]
	Model Seed: 10 OOD median of (MSE, MAE): [197.03113   12.280249]
	Model Seed: 10 ID likelihoods: -9.992143524759364
	Model Seed: 10 OOD likelihoods: -9.978093887065844
	Model Seed: 10 ID calibration errors: [0.59568389 0.35577688 0.23467318 0.15915319 0.14463574 0.1240731
 0.21942596 0.14090632 0.2029513  0.21110444 0.19443042 0.15145705]
	Model Seed: 10 OOD calibration errors: [0.5822601  0.35070855 0.22442806 0.14045606 0.1157378  0.08361793
 0.1621802  0.08659923 0.14228142 0.15902121 0.16732626 0.12276431]
	Train: 9056 (64.79%)
	Val: 1774 (12.69%)
	Test: 1848 (13.22%)
	Test OOD: 1300 (9.30%)
	No scaling applied
		Model Seed: 11 Seed: 1 ID mean of (MSE, MAE): [557.87885   17.989094]
		Model Seed: 11 Seed: 1 OOD mean of (MSE, MAE) stats: [481.1013    15.677579]
		Model Seed: 11 Seed: 1 ID median of (MSE, MAE): [295.6076    15.511268]
		Model Seed: 11 Seed: 1 OOD median of (MSE, MAE) stats: [213.74767    13.1071005]
		Model Seed: 11 Seed: 1 ID likelihoods: -10.081009605081153
		Model Seed: 11 Seed: 1 OOD likelihoods: -10.006977223975534
		Model Seed: 11 Seed: 1 ID calibration errors: [0.5309274  0.40039278 0.30183694 0.22640746 0.21858064 0.21400813
 0.39436421 0.24195745 0.31334061 0.28860643 0.21885985 0.20888415]
		Model Seed: 11 Seed: 1 OOD calibration errors: [0.50114702 0.35703966 0.25633237 0.1725872  0.12826669 0.12215801
 0.25461145 0.11869009 0.17330796 0.14150694 0.11450162 0.11358221]
	Train: 9056 (64.79%)
	Val: 1774 (12.69%)
	Test: 1848 (13.22%)
	Test OOD: 1300 (9.30%)
	No scaling applied
		Model Seed: 11 Seed: 2 ID mean of (MSE, MAE): [390.98834   13.961954]
		Model Seed: 11 Seed: 2 OOD mean of (MSE, MAE) stats: [428.60852   14.264388]
		Model Seed: 11 Seed: 2 ID median of (MSE, MAE): [161.6217    10.885485]
		Model Seed: 11 Seed: 2 OOD median of (MSE, MAE) stats: [180.31459   11.453397]
		Model Seed: 11 Seed: 2 ID likelihoods: -9.903277444437574
		Model Seed: 11 Seed: 2 OOD likelihoods: -9.949210550156154
		Model Seed: 11 Seed: 2 ID calibration errors: [0.66044039 0.31116098 0.16750942 0.09189893 0.07069084 0.03413807
 0.0444877  0.03985519 0.09256199 0.13360246 0.17000099 0.09402995]
		Model Seed: 11 Seed: 2 OOD calibration errors: [0.66337318 0.34437743 0.19252374 0.10832493 0.10320891 0.04507784
 0.06974895 0.05450836 0.11125489 0.17653549 0.2201509  0.13194641]
	Model Seed: 11 ID mean of (MSE, MAE): [474.4336    15.975524]
	Model Seed: 11 OOD mean of (MSE, MAE): [454.85492    14.9709835]
	Model Seed: 11 ID median of (MSE, MAE): [228.61465   13.198376]
	Model Seed: 11 OOD median of (MSE, MAE): [197.03113   12.280249]
	Model Seed: 11 ID likelihoods: -9.992143524759364
	Model Seed: 11 OOD likelihoods: -9.978093887065844
	Model Seed: 11 ID calibration errors: [0.59568389 0.35577688 0.23467318 0.15915319 0.14463574 0.1240731
 0.21942596 0.14090632 0.2029513  0.21110444 0.19443042 0.15145705]
	Model Seed: 11 OOD calibration errors: [0.5822601  0.35070855 0.22442806 0.14045606 0.1157378  0.08361793
 0.1621802  0.08659923 0.14228142 0.15902121 0.16732626 0.12276431]
	Train: 9056 (64.79%)
	Val: 1774 (12.69%)
	Test: 1848 (13.22%)
	Test OOD: 1300 (9.30%)
	No scaling applied
		Model Seed: 12 Seed: 1 ID mean of (MSE, MAE): [557.87885   17.989094]
		Model Seed: 12 Seed: 1 OOD mean of (MSE, MAE) stats: [481.1013    15.677579]
		Model Seed: 12 Seed: 1 ID median of (MSE, MAE): [295.6076    15.511268]
		Model Seed: 12 Seed: 1 OOD median of (MSE, MAE) stats: [213.74767    13.1071005]
		Model Seed: 12 Seed: 1 ID likelihoods: -10.081009605081153
		Model Seed: 12 Seed: 1 OOD likelihoods: -10.006977223975534
		Model Seed: 12 Seed: 1 ID calibration errors: [0.5309274  0.40039278 0.30183694 0.22640746 0.21858064 0.21400813
 0.39436421 0.24195745 0.31334061 0.28860643 0.21885985 0.20888415]
		Model Seed: 12 Seed: 1 OOD calibration errors: [0.50114702 0.35703966 0.25633237 0.1725872  0.12826669 0.12215801
 0.25461145 0.11869009 0.17330796 0.14150694 0.11450162 0.11358221]
	Train: 9056 (64.79%)
	Val: 1774 (12.69%)
	Test: 1848 (13.22%)
	Test OOD: 1300 (9.30%)
	No scaling applied
		Model Seed: 12 Seed: 2 ID mean of (MSE, MAE): [390.98834   13.961954]
		Model Seed: 12 Seed: 2 OOD mean of (MSE, MAE) stats: [428.60852   14.264388]
		Model Seed: 12 Seed: 2 ID median of (MSE, MAE): [161.6217    10.885485]
		Model Seed: 12 Seed: 2 OOD median of (MSE, MAE) stats: [180.31459   11.453397]
		Model Seed: 12 Seed: 2 ID likelihoods: -9.903277444437574
		Model Seed: 12 Seed: 2 OOD likelihoods: -9.949210550156154
		Model Seed: 12 Seed: 2 ID calibration errors: [0.66044039 0.31116098 0.16750942 0.09189893 0.07069084 0.03413807
 0.0444877  0.03985519 0.09256199 0.13360246 0.17000099 0.09402995]
		Model Seed: 12 Seed: 2 OOD calibration errors: [0.66337318 0.34437743 0.19252374 0.10832493 0.10320891 0.04507784
 0.06974895 0.05450836 0.11125489 0.17653549 0.2201509  0.13194641]
	Model Seed: 12 ID mean of (MSE, MAE): [474.4336    15.975524]
	Model Seed: 12 OOD mean of (MSE, MAE): [454.85492    14.9709835]
	Model Seed: 12 ID median of (MSE, MAE): [228.61465   13.198376]
	Model Seed: 12 OOD median of (MSE, MAE): [197.03113   12.280249]
	Model Seed: 12 ID likelihoods: -9.992143524759364
	Model Seed: 12 OOD likelihoods: -9.978093887065844
	Model Seed: 12 ID calibration errors: [0.59568389 0.35577688 0.23467318 0.15915319 0.14463574 0.1240731
 0.21942596 0.14090632 0.2029513  0.21110444 0.19443042 0.15145705]
	Model Seed: 12 OOD calibration errors: [0.5822601  0.35070855 0.22442806 0.14045606 0.1157378  0.08361793
 0.1621802  0.08659923 0.14228142 0.15902121 0.16732626 0.12276431]
	Train: 9056 (64.79%)
	Val: 1774 (12.69%)
	Test: 1848 (13.22%)
	Test OOD: 1300 (9.30%)
	No scaling applied
		Model Seed: 13 Seed: 1 ID mean of (MSE, MAE): [557.87885   17.989094]
		Model Seed: 13 Seed: 1 OOD mean of (MSE, MAE) stats: [481.1013    15.677579]
		Model Seed: 13 Seed: 1 ID median of (MSE, MAE): [295.6076    15.511268]
		Model Seed: 13 Seed: 1 OOD median of (MSE, MAE) stats: [213.74767    13.1071005]
		Model Seed: 13 Seed: 1 ID likelihoods: -10.081009605081153
		Model Seed: 13 Seed: 1 OOD likelihoods: -10.006977223975534
		Model Seed: 13 Seed: 1 ID calibration errors: [0.5309274  0.40039278 0.30183694 0.22640746 0.21858064 0.21400813
 0.39436421 0.24195745 0.31334061 0.28860643 0.21885985 0.20888415]
		Model Seed: 13 Seed: 1 OOD calibration errors: [0.50114702 0.35703966 0.25633237 0.1725872  0.12826669 0.12215801
 0.25461145 0.11869009 0.17330796 0.14150694 0.11450162 0.11358221]
	Train: 9056 (64.79%)
	Val: 1774 (12.69%)
	Test: 1848 (13.22%)
	Test OOD: 1300 (9.30%)
	No scaling applied
		Model Seed: 13 Seed: 2 ID mean of (MSE, MAE): [390.98834   13.961954]
		Model Seed: 13 Seed: 2 OOD mean of (MSE, MAE) stats: [428.60852   14.264388]
		Model Seed: 13 Seed: 2 ID median of (MSE, MAE): [161.6217    10.885485]
		Model Seed: 13 Seed: 2 OOD median of (MSE, MAE) stats: [180.31459   11.453397]
		Model Seed: 13 Seed: 2 ID likelihoods: -9.903277444437574
		Model Seed: 13 Seed: 2 OOD likelihoods: -9.949210550156154
		Model Seed: 13 Seed: 2 ID calibration errors: [0.66044039 0.31116098 0.16750942 0.09189893 0.07069084 0.03413807
 0.0444877  0.03985519 0.09256199 0.13360246 0.17000099 0.09402995]
		Model Seed: 13 Seed: 2 OOD calibration errors: [0.66337318 0.34437743 0.19252374 0.10832493 0.10320891 0.04507784
 0.06974895 0.05450836 0.11125489 0.17653549 0.2201509  0.13194641]
	Model Seed: 13 ID mean of (MSE, MAE): [474.4336    15.975524]
	Model Seed: 13 OOD mean of (MSE, MAE): [454.85492    14.9709835]
	Model Seed: 13 ID median of (MSE, MAE): [228.61465   13.198376]
	Model Seed: 13 OOD median of (MSE, MAE): [197.03113   12.280249]
	Model Seed: 13 ID likelihoods: -9.992143524759364
	Model Seed: 13 OOD likelihoods: -9.978093887065844
	Model Seed: 13 ID calibration errors: [0.59568389 0.35577688 0.23467318 0.15915319 0.14463574 0.1240731
 0.21942596 0.14090632 0.2029513  0.21110444 0.19443042 0.15145705]
	Model Seed: 13 OOD calibration errors: [0.5822601  0.35070855 0.22442806 0.14045606 0.1157378  0.08361793
 0.1621802  0.08659923 0.14228142 0.15902121 0.16732626 0.12276431]
	Train: 9056 (64.79%)
	Val: 1774 (12.69%)
	Test: 1848 (13.22%)
	Test OOD: 1300 (9.30%)
	No scaling applied
		Model Seed: 14 Seed: 1 ID mean of (MSE, MAE): [557.87885   17.989094]
		Model Seed: 14 Seed: 1 OOD mean of (MSE, MAE) stats: [481.1013    15.677579]
		Model Seed: 14 Seed: 1 ID median of (MSE, MAE): [295.6076    15.511268]
		Model Seed: 14 Seed: 1 OOD median of (MSE, MAE) stats: [213.74767    13.1071005]
		Model Seed: 14 Seed: 1 ID likelihoods: -10.081009605081153
		Model Seed: 14 Seed: 1 OOD likelihoods: -10.006977223975534
		Model Seed: 14 Seed: 1 ID calibration errors: [0.5309274  0.40039278 0.30183694 0.22640746 0.21858064 0.21400813
 0.39436421 0.24195745 0.31334061 0.28860643 0.21885985 0.20888415]
		Model Seed: 14 Seed: 1 OOD calibration errors: [0.50114702 0.35703966 0.25633237 0.1725872  0.12826669 0.12215801
 0.25461145 0.11869009 0.17330796 0.14150694 0.11450162 0.11358221]
	Train: 9056 (64.79%)
	Val: 1774 (12.69%)
	Test: 1848 (13.22%)
	Test OOD: 1300 (9.30%)
	No scaling applied
		Model Seed: 14 Seed: 2 ID mean of (MSE, MAE): [390.98834   13.961954]
		Model Seed: 14 Seed: 2 OOD mean of (MSE, MAE) stats: [428.60852   14.264388]
		Model Seed: 14 Seed: 2 ID median of (MSE, MAE): [161.6217    10.885485]
		Model Seed: 14 Seed: 2 OOD median of (MSE, MAE) stats: [180.31459   11.453397]
		Model Seed: 14 Seed: 2 ID likelihoods: -9.903277444437574
		Model Seed: 14 Seed: 2 OOD likelihoods: -9.949210550156154
		Model Seed: 14 Seed: 2 ID calibration errors: [0.66044039 0.31116098 0.16750942 0.09189893 0.07069084 0.03413807
 0.0444877  0.03985519 0.09256199 0.13360246 0.17000099 0.09402995]
		Model Seed: 14 Seed: 2 OOD calibration errors: [0.66337318 0.34437743 0.19252374 0.10832493 0.10320891 0.04507784
 0.06974895 0.05450836 0.11125489 0.17653549 0.2201509  0.13194641]
	Model Seed: 14 ID mean of (MSE, MAE): [474.4336    15.975524]
	Model Seed: 14 OOD mean of (MSE, MAE): [454.85492    14.9709835]
	Model Seed: 14 ID median of (MSE, MAE): [228.61465   13.198376]
	Model Seed: 14 OOD median of (MSE, MAE): [197.03113   12.280249]
	Model Seed: 14 ID likelihoods: -9.992143524759364
	Model Seed: 14 OOD likelihoods: -9.978093887065844
	Model Seed: 14 ID calibration errors: [0.59568389 0.35577688 0.23467318 0.15915319 0.14463574 0.1240731
 0.21942596 0.14090632 0.2029513  0.21110444 0.19443042 0.15145705]
	Model Seed: 14 OOD calibration errors: [0.5822601  0.35070855 0.22442806 0.14045606 0.1157378  0.08361793
 0.1621802  0.08659923 0.14228142 0.15902121 0.16732626 0.12276431]
	Train: 9056 (64.79%)
	Val: 1774 (12.69%)
	Test: 1848 (13.22%)
	Test OOD: 1300 (9.30%)
	No scaling applied
		Model Seed: 15 Seed: 1 ID mean of (MSE, MAE): [557.87885   17.989094]
		Model Seed: 15 Seed: 1 OOD mean of (MSE, MAE) stats: [481.1013    15.677579]
		Model Seed: 15 Seed: 1 ID median of (MSE, MAE): [295.6076    15.511268]
		Model Seed: 15 Seed: 1 OOD median of (MSE, MAE) stats: [213.74767    13.1071005]
		Model Seed: 15 Seed: 1 ID likelihoods: -10.081009605081153
		Model Seed: 15 Seed: 1 OOD likelihoods: -10.006977223975534
		Model Seed: 15 Seed: 1 ID calibration errors: [0.5309274  0.40039278 0.30183694 0.22640746 0.21858064 0.21400813
 0.39436421 0.24195745 0.31334061 0.28860643 0.21885985 0.20888415]
		Model Seed: 15 Seed: 1 OOD calibration errors: [0.50114702 0.35703966 0.25633237 0.1725872  0.12826669 0.12215801
 0.25461145 0.11869009 0.17330796 0.14150694 0.11450162 0.11358221]
	Train: 9056 (64.79%)
	Val: 1774 (12.69%)
	Test: 1848 (13.22%)
	Test OOD: 1300 (9.30%)
	No scaling applied
		Model Seed: 15 Seed: 2 ID mean of (MSE, MAE): [390.98834   13.961954]
		Model Seed: 15 Seed: 2 OOD mean of (MSE, MAE) stats: [428.60852   14.264388]
		Model Seed: 15 Seed: 2 ID median of (MSE, MAE): [161.6217    10.885485]
		Model Seed: 15 Seed: 2 OOD median of (MSE, MAE) stats: [180.31459   11.453397]
		Model Seed: 15 Seed: 2 ID likelihoods: -9.903277444437574
		Model Seed: 15 Seed: 2 OOD likelihoods: -9.949210550156154
		Model Seed: 15 Seed: 2 ID calibration errors: [0.66044039 0.31116098 0.16750942 0.09189893 0.07069084 0.03413807
 0.0444877  0.03985519 0.09256199 0.13360246 0.17000099 0.09402995]
		Model Seed: 15 Seed: 2 OOD calibration errors: [0.66337318 0.34437743 0.19252374 0.10832493 0.10320891 0.04507784
 0.06974895 0.05450836 0.11125489 0.17653549 0.2201509  0.13194641]
	Model Seed: 15 ID mean of (MSE, MAE): [474.4336    15.975524]
	Model Seed: 15 OOD mean of (MSE, MAE): [454.85492    14.9709835]
	Model Seed: 15 ID median of (MSE, MAE): [228.61465   13.198376]
	Model Seed: 15 OOD median of (MSE, MAE): [197.03113   12.280249]
	Model Seed: 15 ID likelihoods: -9.992143524759364
	Model Seed: 15 OOD likelihoods: -9.978093887065844
	Model Seed: 15 ID calibration errors: [0.59568389 0.35577688 0.23467318 0.15915319 0.14463574 0.1240731
 0.21942596 0.14090632 0.2029513  0.21110444 0.19443042 0.15145705]
	Model Seed: 15 OOD calibration errors: [0.5822601  0.35070855 0.22442806 0.14045606 0.1157378  0.08361793
 0.1621802  0.08659923 0.14228142 0.15902121 0.16732626 0.12276431]
	Train: 9056 (64.79%)
	Val: 1774 (12.69%)
	Test: 1848 (13.22%)
	Test OOD: 1300 (9.30%)
	No scaling applied
		Model Seed: 16 Seed: 1 ID mean of (MSE, MAE): [557.87885   17.989094]
		Model Seed: 16 Seed: 1 OOD mean of (MSE, MAE) stats: [481.1013    15.677579]
		Model Seed: 16 Seed: 1 ID median of (MSE, MAE): [295.6076    15.511268]
		Model Seed: 16 Seed: 1 OOD median of (MSE, MAE) stats: [213.74767    13.1071005]
		Model Seed: 16 Seed: 1 ID likelihoods: -10.081009605081153
		Model Seed: 16 Seed: 1 OOD likelihoods: -10.006977223975534
		Model Seed: 16 Seed: 1 ID calibration errors: [0.5309274  0.40039278 0.30183694 0.22640746 0.21858064 0.21400813
 0.39436421 0.24195745 0.31334061 0.28860643 0.21885985 0.20888415]
		Model Seed: 16 Seed: 1 OOD calibration errors: [0.50114702 0.35703966 0.25633237 0.1725872  0.12826669 0.12215801
 0.25461145 0.11869009 0.17330796 0.14150694 0.11450162 0.11358221]
	Train: 9056 (64.79%)
	Val: 1774 (12.69%)
	Test: 1848 (13.22%)
	Test OOD: 1300 (9.30%)
	No scaling applied
		Model Seed: 16 Seed: 2 ID mean of (MSE, MAE): [390.98834   13.961954]
		Model Seed: 16 Seed: 2 OOD mean of (MSE, MAE) stats: [428.60852   14.264388]
		Model Seed: 16 Seed: 2 ID median of (MSE, MAE): [161.6217    10.885485]
		Model Seed: 16 Seed: 2 OOD median of (MSE, MAE) stats: [180.31459   11.453397]
		Model Seed: 16 Seed: 2 ID likelihoods: -9.903277444437574
		Model Seed: 16 Seed: 2 OOD likelihoods: -9.949210550156154
		Model Seed: 16 Seed: 2 ID calibration errors: [0.66044039 0.31116098 0.16750942 0.09189893 0.07069084 0.03413807
 0.0444877  0.03985519 0.09256199 0.13360246 0.17000099 0.09402995]
		Model Seed: 16 Seed: 2 OOD calibration errors: [0.66337318 0.34437743 0.19252374 0.10832493 0.10320891 0.04507784
 0.06974895 0.05450836 0.11125489 0.17653549 0.2201509  0.13194641]
	Model Seed: 16 ID mean of (MSE, MAE): [474.4336    15.975524]
	Model Seed: 16 OOD mean of (MSE, MAE): [454.85492    14.9709835]
	Model Seed: 16 ID median of (MSE, MAE): [228.61465   13.198376]
	Model Seed: 16 OOD median of (MSE, MAE): [197.03113   12.280249]
	Model Seed: 16 ID likelihoods: -9.992143524759364
	Model Seed: 16 OOD likelihoods: -9.978093887065844
	Model Seed: 16 ID calibration errors: [0.59568389 0.35577688 0.23467318 0.15915319 0.14463574 0.1240731
 0.21942596 0.14090632 0.2029513  0.21110444 0.19443042 0.15145705]
	Model Seed: 16 OOD calibration errors: [0.5822601  0.35070855 0.22442806 0.14045606 0.1157378  0.08361793
 0.1621802  0.08659923 0.14228142 0.15902121 0.16732626 0.12276431]
	Train: 9056 (64.79%)
	Val: 1774 (12.69%)
	Test: 1848 (13.22%)
	Test OOD: 1300 (9.30%)
	No scaling applied
		Model Seed: 17 Seed: 1 ID mean of (MSE, MAE): [557.87885   17.989094]
		Model Seed: 17 Seed: 1 OOD mean of (MSE, MAE) stats: [481.1013    15.677579]
		Model Seed: 17 Seed: 1 ID median of (MSE, MAE): [295.6076    15.511268]
		Model Seed: 17 Seed: 1 OOD median of (MSE, MAE) stats: [213.74767    13.1071005]
		Model Seed: 17 Seed: 1 ID likelihoods: -10.081009605081153
		Model Seed: 17 Seed: 1 OOD likelihoods: -10.006977223975534
		Model Seed: 17 Seed: 1 ID calibration errors: [0.5309274  0.40039278 0.30183694 0.22640746 0.21858064 0.21400813
 0.39436421 0.24195745 0.31334061 0.28860643 0.21885985 0.20888415]
		Model Seed: 17 Seed: 1 OOD calibration errors: [0.50114702 0.35703966 0.25633237 0.1725872  0.12826669 0.12215801
 0.25461145 0.11869009 0.17330796 0.14150694 0.11450162 0.11358221]
	Train: 9056 (64.79%)
	Val: 1774 (12.69%)
	Test: 1848 (13.22%)
	Test OOD: 1300 (9.30%)
	No scaling applied
		Model Seed: 17 Seed: 2 ID mean of (MSE, MAE): [390.98834   13.961954]
		Model Seed: 17 Seed: 2 OOD mean of (MSE, MAE) stats: [428.60852   14.264388]
		Model Seed: 17 Seed: 2 ID median of (MSE, MAE): [161.6217    10.885485]
		Model Seed: 17 Seed: 2 OOD median of (MSE, MAE) stats: [180.31459   11.453397]
		Model Seed: 17 Seed: 2 ID likelihoods: -9.903277444437574
		Model Seed: 17 Seed: 2 OOD likelihoods: -9.949210550156154
		Model Seed: 17 Seed: 2 ID calibration errors: [0.66044039 0.31116098 0.16750942 0.09189893 0.07069084 0.03413807
 0.0444877  0.03985519 0.09256199 0.13360246 0.17000099 0.09402995]
		Model Seed: 17 Seed: 2 OOD calibration errors: [0.66337318 0.34437743 0.19252374 0.10832493 0.10320891 0.04507784
 0.06974895 0.05450836 0.11125489 0.17653549 0.2201509  0.13194641]
	Model Seed: 17 ID mean of (MSE, MAE): [474.4336    15.975524]
	Model Seed: 17 OOD mean of (MSE, MAE): [454.85492    14.9709835]
	Model Seed: 17 ID median of (MSE, MAE): [228.61465   13.198376]
	Model Seed: 17 OOD median of (MSE, MAE): [197.03113   12.280249]
	Model Seed: 17 ID likelihoods: -9.992143524759364
	Model Seed: 17 OOD likelihoods: -9.978093887065844
	Model Seed: 17 ID calibration errors: [0.59568389 0.35577688 0.23467318 0.15915319 0.14463574 0.1240731
 0.21942596 0.14090632 0.2029513  0.21110444 0.19443042 0.15145705]
	Model Seed: 17 OOD calibration errors: [0.5822601  0.35070855 0.22442806 0.14045606 0.1157378  0.08361793
 0.1621802  0.08659923 0.14228142 0.15902121 0.16732626 0.12276431]
	Train: 9056 (64.79%)
	Val: 1774 (12.69%)
	Test: 1848 (13.22%)
	Test OOD: 1300 (9.30%)
	No scaling applied
		Model Seed: 18 Seed: 1 ID mean of (MSE, MAE): [557.87885   17.989094]
		Model Seed: 18 Seed: 1 OOD mean of (MSE, MAE) stats: [481.1013    15.677579]
		Model Seed: 18 Seed: 1 ID median of (MSE, MAE): [295.6076    15.511268]
		Model Seed: 18 Seed: 1 OOD median of (MSE, MAE) stats: [213.74767    13.1071005]
		Model Seed: 18 Seed: 1 ID likelihoods: -10.081009605081153
		Model Seed: 18 Seed: 1 OOD likelihoods: -10.006977223975534
		Model Seed: 18 Seed: 1 ID calibration errors: [0.5309274  0.40039278 0.30183694 0.22640746 0.21858064 0.21400813
 0.39436421 0.24195745 0.31334061 0.28860643 0.21885985 0.20888415]
		Model Seed: 18 Seed: 1 OOD calibration errors: [0.50114702 0.35703966 0.25633237 0.1725872  0.12826669 0.12215801
 0.25461145 0.11869009 0.17330796 0.14150694 0.11450162 0.11358221]
	Train: 9056 (64.79%)
	Val: 1774 (12.69%)
	Test: 1848 (13.22%)
	Test OOD: 1300 (9.30%)
	No scaling applied
		Model Seed: 18 Seed: 2 ID mean of (MSE, MAE): [390.98834   13.961954]
		Model Seed: 18 Seed: 2 OOD mean of (MSE, MAE) stats: [428.60852   14.264388]
		Model Seed: 18 Seed: 2 ID median of (MSE, MAE): [161.6217    10.885485]
		Model Seed: 18 Seed: 2 OOD median of (MSE, MAE) stats: [180.31459   11.453397]
		Model Seed: 18 Seed: 2 ID likelihoods: -9.903277444437574
		Model Seed: 18 Seed: 2 OOD likelihoods: -9.949210550156154
		Model Seed: 18 Seed: 2 ID calibration errors: [0.66044039 0.31116098 0.16750942 0.09189893 0.07069084 0.03413807
 0.0444877  0.03985519 0.09256199 0.13360246 0.17000099 0.09402995]
		Model Seed: 18 Seed: 2 OOD calibration errors: [0.66337318 0.34437743 0.19252374 0.10832493 0.10320891 0.04507784
 0.06974895 0.05450836 0.11125489 0.17653549 0.2201509  0.13194641]
	Model Seed: 18 ID mean of (MSE, MAE): [474.4336    15.975524]
	Model Seed: 18 OOD mean of (MSE, MAE): [454.85492    14.9709835]
	Model Seed: 18 ID median of (MSE, MAE): [228.61465   13.198376]
	Model Seed: 18 OOD median of (MSE, MAE): [197.03113   12.280249]
	Model Seed: 18 ID likelihoods: -9.992143524759364
	Model Seed: 18 OOD likelihoods: -9.978093887065844
	Model Seed: 18 ID calibration errors: [0.59568389 0.35577688 0.23467318 0.15915319 0.14463574 0.1240731
 0.21942596 0.14090632 0.2029513  0.21110444 0.19443042 0.15145705]
	Model Seed: 18 OOD calibration errors: [0.5822601  0.35070855 0.22442806 0.14045606 0.1157378  0.08361793
 0.1621802  0.08659923 0.14228142 0.15902121 0.16732626 0.12276431]
	Train: 9056 (64.79%)
	Val: 1774 (12.69%)
	Test: 1848 (13.22%)
	Test OOD: 1300 (9.30%)
	No scaling applied
		Model Seed: 19 Seed: 1 ID mean of (MSE, MAE): [557.87885   17.989094]
		Model Seed: 19 Seed: 1 OOD mean of (MSE, MAE) stats: [481.1013    15.677579]
		Model Seed: 19 Seed: 1 ID median of (MSE, MAE): [295.6076    15.511268]
		Model Seed: 19 Seed: 1 OOD median of (MSE, MAE) stats: [213.74767    13.1071005]
		Model Seed: 19 Seed: 1 ID likelihoods: -10.081009605081153
		Model Seed: 19 Seed: 1 OOD likelihoods: -10.006977223975534
		Model Seed: 19 Seed: 1 ID calibration errors: [0.5309274  0.40039278 0.30183694 0.22640746 0.21858064 0.21400813
 0.39436421 0.24195745 0.31334061 0.28860643 0.21885985 0.20888415]
		Model Seed: 19 Seed: 1 OOD calibration errors: [0.50114702 0.35703966 0.25633237 0.1725872  0.12826669 0.12215801
 0.25461145 0.11869009 0.17330796 0.14150694 0.11450162 0.11358221]
	Train: 9056 (64.79%)
	Val: 1774 (12.69%)
	Test: 1848 (13.22%)
	Test OOD: 1300 (9.30%)
	No scaling applied
		Model Seed: 19 Seed: 2 ID mean of (MSE, MAE): [390.98834   13.961954]
		Model Seed: 19 Seed: 2 OOD mean of (MSE, MAE) stats: [428.60852   14.264388]
		Model Seed: 19 Seed: 2 ID median of (MSE, MAE): [161.6217    10.885485]
		Model Seed: 19 Seed: 2 OOD median of (MSE, MAE) stats: [180.31459   11.453397]
		Model Seed: 19 Seed: 2 ID likelihoods: -9.903277444437574
		Model Seed: 19 Seed: 2 OOD likelihoods: -9.949210550156154
		Model Seed: 19 Seed: 2 ID calibration errors: [0.66044039 0.31116098 0.16750942 0.09189893 0.07069084 0.03413807
 0.0444877  0.03985519 0.09256199 0.13360246 0.17000099 0.09402995]
		Model Seed: 19 Seed: 2 OOD calibration errors: [0.66337318 0.34437743 0.19252374 0.10832493 0.10320891 0.04507784
 0.06974895 0.05450836 0.11125489 0.17653549 0.2201509  0.13194641]
	Model Seed: 19 ID mean of (MSE, MAE): [474.4336    15.975524]
	Model Seed: 19 OOD mean of (MSE, MAE): [454.85492    14.9709835]
	Model Seed: 19 ID median of (MSE, MAE): [228.61465   13.198376]
	Model Seed: 19 OOD median of (MSE, MAE): [197.03113   12.280249]
	Model Seed: 19 ID likelihoods: -9.992143524759364
	Model Seed: 19 OOD likelihoods: -9.978093887065844
	Model Seed: 19 ID calibration errors: [0.59568389 0.35577688 0.23467318 0.15915319 0.14463574 0.1240731
 0.21942596 0.14090632 0.2029513  0.21110444 0.19443042 0.15145705]
	Model Seed: 19 OOD calibration errors: [0.5822601  0.35070855 0.22442806 0.14045606 0.1157378  0.08361793
 0.1621802  0.08659923 0.14228142 0.15902121 0.16732626 0.12276431]
ID mean of (MSE, MAE): [474.43359375, 15.975522994995117] +- [0.0, 9.5367431640625e-07] +- [83.445255  2.01357 ] 
OOD mean of (MSE, MAE): [454.85491943359375, 14.970983505249023] +- [0.0, 0.0] +- [26.24639    0.7065955] 
ID median of (MSE, MAE): [228.61465454101562, 13.19837760925293] +- [0.0, 1.9073486328125e-06] +- [66.99295    2.3128915] 
OOD median of (MSE, MAE): [197.0311279296875, 12.28024959564209] +- [0.0, 9.5367431640625e-07] +- [16.71654     0.82685175] 
ID likelihoods: -9.992143524759365 +- 1.7763568394002505e-15 +- 0.08886608032178955 
OOD likelihoods: -9.978093887065842 +- 1.7763568394002505e-15 +- 0.028883336909690804 
ID calibration errors: [0.5956838920849039, 0.3557768795873834, 0.23467317992461806, 0.1591531938107518, 0.1446357369569529, 0.12407310057528262, 0.21942595715135876, 0.14090631819083513, 0.20295129934536799, 0.21110444356278507, 0.19443042055147777, 0.15145705217218802] +- [0.0, 0.0, 0.0, 0.0, 2.7755575615628914e-17, 0.0, 2.7755575615628914e-17, 2.7755575615628914e-17, 2.7755575615628914e-17, 0.0, 2.7755575615628914e-17, 2.7755575615628914e-17] +- [0.06475649 0.0446159  0.06716376 0.06725426 0.0739449  0.08993503
 0.17493825 0.10105113 0.11038931 0.07750199 0.02442943 0.0574271 ] 
OOD calibration errors: [0.5822600973873194, 0.35070854648329947, 0.2244280555610621, 0.14045606354486082, 0.11573779711009854, 0.08361792744675987, 0.16218019679875953, 0.08659922728681256, 0.14228142368700827, 0.15902121257333518, 0.16732626212776783, 0.12276431204424679] +- [1.1102230246251565e-16, 5.551115123125783e-17, 5.551115123125783e-17, 2.7755575615628914e-17, 0.0, 1.3877787807814457e-17, 2.7755575615628914e-17, 0.0, 2.7755575615628914e-17, 2.7755575615628914e-17, 2.7755575615628914e-17, 2.7755575615628914e-17] +- [0.08111308 0.00633111 0.03190432 0.03213113 0.01252889 0.03854009
 0.09243125 0.03209087 0.03102653 0.01751427 0.05282464 0.0091821 ] 
