lr: 1e-06
sub_7:Test (Best Model) - Loss: 0.7149 - Accuracy: 0.3810 - F1: 0.3681
sub_4:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.6190 - F1: 0.6171
sub_10:Test (Best Model) - Loss: 0.6965 - Accuracy: 0.5119 - F1: 0.5085
sub_8:Test (Best Model) - Loss: 0.7009 - Accuracy: 0.4762 - F1: 0.4750
sub_12:Test (Best Model) - Loss: 0.7251 - Accuracy: 0.3333 - F1: 0.3237
sub_2:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.5000 - F1: 0.4896
sub_14:Test (Best Model) - Loss: 0.6880 - Accuracy: 0.5119 - F1: 0.5113
sub_3:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.5595 - F1: 0.5564
sub_1:Test (Best Model) - Loss: 0.7005 - Accuracy: 0.5238 - F1: 0.5227
sub_13:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5833 - F1: 0.5804
sub_9:Test (Best Model) - Loss: 0.7177 - Accuracy: 0.3214 - F1: 0.2924
sub_6:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.5119 - F1: 0.5062
sub_5:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5595 - F1: 0.5590
sub_8:Test (Best Model) - Loss: 0.6746 - Accuracy: 0.6786 - F1: 0.6785
sub_11:Test (Best Model) - Loss: 0.7056 - Accuracy: 0.4524 - F1: 0.4318
sub_12:Test (Best Model) - Loss: 0.6986 - Accuracy: 0.5714 - F1: 0.5625
sub_3:Test (Best Model) - Loss: 0.6737 - Accuracy: 0.6786 - F1: 0.6785
sub_7:Test (Best Model) - Loss: 0.6778 - Accuracy: 0.6190 - F1: 0.6156
sub_14:Test (Best Model) - Loss: 0.6806 - Accuracy: 0.6548 - F1: 0.6487
sub_4:Test (Best Model) - Loss: 0.6995 - Accuracy: 0.5357 - F1: 0.5356
sub_10:Test (Best Model) - Loss: 0.6987 - Accuracy: 0.4405 - F1: 0.4366
sub_9:Test (Best Model) - Loss: 0.7028 - Accuracy: 0.4405 - F1: 0.4340
sub_5:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.5833 - F1: 0.5828
sub_8:Test (Best Model) - Loss: 0.7168 - Accuracy: 0.4048 - F1: 0.4048
sub_6:Test (Best Model) - Loss: 0.6672 - Accuracy: 0.6786 - F1: 0.6707
sub_7:Test (Best Model) - Loss: 0.7132 - Accuracy: 0.4524 - F1: 0.4318
sub_13:Test (Best Model) - Loss: 0.6701 - Accuracy: 0.7143 - F1: 0.7143
sub_11:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.5119 - F1: 0.5118
sub_2:Test (Best Model) - Loss: 0.6751 - Accuracy: 0.5714 - F1: 0.5705
sub_10:Test (Best Model) - Loss: 0.7139 - Accuracy: 0.3929 - F1: 0.3907
sub_3:Test (Best Model) - Loss: 0.7277 - Accuracy: 0.3690 - F1: 0.3483
sub_12:Test (Best Model) - Loss: 0.7105 - Accuracy: 0.3452 - F1: 0.3429
sub_8:Test (Best Model) - Loss: 0.7027 - Accuracy: 0.4405 - F1: 0.4267
sub_4:Test (Best Model) - Loss: 0.7144 - Accuracy: 0.3929 - F1: 0.3921
sub_5:Test (Best Model) - Loss: 0.7101 - Accuracy: 0.4286 - F1: 0.3680
sub_1:Test (Best Model) - Loss: 0.7090 - Accuracy: 0.4643 - F1: 0.4642
sub_9:Test (Best Model) - Loss: 0.6998 - Accuracy: 0.4524 - F1: 0.4195
sub_7:Test (Best Model) - Loss: 0.7143 - Accuracy: 0.3929 - F1: 0.3886
sub_10:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.5119 - F1: 0.5062
sub_13:Test (Best Model) - Loss: 0.6844 - Accuracy: 0.5595 - F1: 0.5407
sub_8:Test (Best Model) - Loss: 0.7077 - Accuracy: 0.4643 - F1: 0.4581
sub_14:Test (Best Model) - Loss: 0.7075 - Accuracy: 0.4405 - F1: 0.4398
sub_11:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5357 - F1: 0.5341
sub_12:Test (Best Model) - Loss: 0.7041 - Accuracy: 0.4762 - F1: 0.4735
sub_3:Test (Best Model) - Loss: 0.7101 - Accuracy: 0.3690 - F1: 0.3483
sub_1:Test (Best Model) - Loss: 0.7095 - Accuracy: 0.4286 - F1: 0.4204
sub_6:Test (Best Model) - Loss: 0.6963 - Accuracy: 0.4762 - F1: 0.4750
sub_10:Test (Best Model) - Loss: 0.6946 - Accuracy: 0.5000 - F1: 0.4928
sub_5:Test (Best Model) - Loss: 0.7041 - Accuracy: 0.4643 - F1: 0.4605
sub_2:Test (Best Model) - Loss: 0.6854 - Accuracy: 0.5357 - F1: 0.5243
sub_7:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.4643 - F1: 0.4466
sub_8:Test (Best Model) - Loss: 0.7113 - Accuracy: 0.4048 - F1: 0.3878
sub_4:Test (Best Model) - Loss: 0.7026 - Accuracy: 0.4643 - F1: 0.4624
sub_3:Test (Best Model) - Loss: 0.6793 - Accuracy: 0.5357 - F1: 0.5351
sub_1:Test (Best Model) - Loss: 0.6898 - Accuracy: 0.4881 - F1: 0.4662
sub_6:Test (Best Model) - Loss: 0.6815 - Accuracy: 0.5595 - F1: 0.5590
sub_12:Test (Best Model) - Loss: 0.7143 - Accuracy: 0.3929 - F1: 0.3858
sub_9:Test (Best Model) - Loss: 0.6542 - Accuracy: 0.7024 - F1: 0.6989
sub_5:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.4881 - F1: 0.4792
sub_2:Test (Best Model) - Loss: 0.6778 - Accuracy: 0.6310 - F1: 0.6305
sub_11:Test (Best Model) - Loss: 0.6845 - Accuracy: 0.5714 - F1: 0.5692
sub_3:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5000 - F1: 0.4896
sub_4:Test (Best Model) - Loss: 0.7175 - Accuracy: 0.3929 - F1: 0.3823
sub_10:Test (Best Model) - Loss: 0.6815 - Accuracy: 0.5476 - F1: 0.5466
sub_14:Test (Best Model) - Loss: 0.6981 - Accuracy: 0.4643 - F1: 0.4624
sub_6:Test (Best Model) - Loss: 0.7077 - Accuracy: 0.4881 - F1: 0.4863
sub_7:Test (Best Model) - Loss: 0.7023 - Accuracy: 0.4286 - F1: 0.4286
sub_13:Test (Best Model) - Loss: 0.6994 - Accuracy: 0.4524 - F1: 0.4474
sub_2:Test (Best Model) - Loss: 0.7019 - Accuracy: 0.4643 - F1: 0.4605
sub_4:Test (Best Model) - Loss: 0.7025 - Accuracy: 0.5238 - F1: 0.4643
sub_8:Test (Best Model) - Loss: 0.6770 - Accuracy: 0.5714 - F1: 0.5399
sub_11:Test (Best Model) - Loss: 0.7235 - Accuracy: 0.3810 - F1: 0.3806
sub_14:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5119 - F1: 0.5102
sub_9:Test (Best Model) - Loss: 0.6994 - Accuracy: 0.4762 - F1: 0.4762
sub_10:Test (Best Model) - Loss: 0.7105 - Accuracy: 0.4048 - F1: 0.3761
sub_5:Test (Best Model) - Loss: 0.6722 - Accuracy: 0.6071 - F1: 0.5942
sub_6:Test (Best Model) - Loss: 0.7041 - Accuracy: 0.4048 - F1: 0.3878
sub_3:Test (Best Model) - Loss: 0.7031 - Accuracy: 0.4762 - F1: 0.4687
sub_12:Test (Best Model) - Loss: 0.6994 - Accuracy: 0.4881 - F1: 0.4755
sub_13:Test (Best Model) - Loss: 0.7155 - Accuracy: 0.3810 - F1: 0.3512
sub_1:Test (Best Model) - Loss: 0.7040 - Accuracy: 0.4167 - F1: 0.3918
sub_11:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.5476 - F1: 0.5453
sub_8:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5476 - F1: 0.5453
sub_9:Test (Best Model) - Loss: 0.6756 - Accuracy: 0.6429 - F1: 0.6420
sub_4:Test (Best Model) - Loss: 0.6756 - Accuracy: 0.6190 - F1: 0.6188
sub_10:Test (Best Model) - Loss: 0.6835 - Accuracy: 0.5357 - F1: 0.5356
sub_3:Test (Best Model) - Loss: 0.6990 - Accuracy: 0.5476 - F1: 0.5453
sub_6:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.5238 - F1: 0.5214
sub_5:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5238 - F1: 0.5170
sub_7:Test (Best Model) - Loss: 0.6822 - Accuracy: 0.5357 - F1: 0.5276
sub_1:Test (Best Model) - Loss: 0.6963 - Accuracy: 0.4881 - F1: 0.4863
sub_12:Test (Best Model) - Loss: 0.7051 - Accuracy: 0.4286 - F1: 0.4233
sub_2:Test (Best Model) - Loss: 0.6859 - Accuracy: 0.5476 - F1: 0.5204
sub_8:Test (Best Model) - Loss: 0.7227 - Accuracy: 0.3095 - F1: 0.2951
sub_11:Test (Best Model) - Loss: 0.7225 - Accuracy: 0.2976 - F1: 0.2951
sub_13:Test (Best Model) - Loss: 0.6955 - Accuracy: 0.5000 - F1: 0.4928
sub_14:Test (Best Model) - Loss: 0.7032 - Accuracy: 0.5000 - F1: 0.5000
sub_6:Test (Best Model) - Loss: 0.6890 - Accuracy: 0.5595 - F1: 0.5407
sub_3:Test (Best Model) - Loss: 0.7028 - Accuracy: 0.3690 - F1: 0.3682
sub_7:Test (Best Model) - Loss: 0.6789 - Accuracy: 0.5714 - F1: 0.5705
sub_12:Test (Best Model) - Loss: 0.6908 - Accuracy: 0.5238 - F1: 0.5214
sub_5:Test (Best Model) - Loss: 0.6980 - Accuracy: 0.4881 - F1: 0.4845
sub_8:Test (Best Model) - Loss: 0.6841 - Accuracy: 0.5833 - F1: 0.5731
sub_11:Test (Best Model) - Loss: 0.7016 - Accuracy: 0.4643 - F1: 0.4581
sub_13:Test (Best Model) - Loss: 0.7016 - Accuracy: 0.4405 - F1: 0.4340
sub_1:Test (Best Model) - Loss: 0.7099 - Accuracy: 0.3690 - F1: 0.3690
sub_14:Test (Best Model) - Loss: 0.6723 - Accuracy: 0.6548 - F1: 0.6543
sub_4:Test (Best Model) - Loss: 0.7059 - Accuracy: 0.4405 - F1: 0.4340
sub_9:Test (Best Model) - Loss: 0.6871 - Accuracy: 0.5714 - F1: 0.5653
sub_6:Test (Best Model) - Loss: 0.7147 - Accuracy: 0.3929 - F1: 0.3601
sub_7:Test (Best Model) - Loss: 0.7178 - Accuracy: 0.3810 - F1: 0.3806
sub_12:Test (Best Model) - Loss: 0.6590 - Accuracy: 0.7500 - F1: 0.7497
sub_3:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.5238 - F1: 0.5227
sub_2:Test (Best Model) - Loss: 0.6871 - Accuracy: 0.5357 - F1: 0.5159
sub_1:Test (Best Model) - Loss: 0.6832 - Accuracy: 0.5476 - F1: 0.5435
sub_11:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.6071 - F1: 0.6057
sub_14:Test (Best Model) - Loss: 0.6657 - Accuracy: 0.7262 - F1: 0.7230
sub_10:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5119 - F1: 0.5034
sub_5:Test (Best Model) - Loss: 0.6967 - Accuracy: 0.3929 - F1: 0.3921
sub_13:Test (Best Model) - Loss: 0.6949 - Accuracy: 0.4881 - F1: 0.4845
sub_7:Test (Best Model) - Loss: 0.6783 - Accuracy: 0.5833 - F1: 0.5828
sub_12:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5119 - F1: 0.5102
sub_3:Test (Best Model) - Loss: 0.7015 - Accuracy: 0.4286 - F1: 0.4256
sub_4:Test (Best Model) - Loss: 0.7024 - Accuracy: 0.4167 - F1: 0.4159
sub_10:Test (Best Model) - Loss: 0.6837 - Accuracy: 0.5238 - F1: 0.5170
sub_8:Test (Best Model) - Loss: 0.7165 - Accuracy: 0.4286 - F1: 0.3942
sub_9:Test (Best Model) - Loss: 0.6861 - Accuracy: 0.5357 - F1: 0.5356
sub_14:Test (Best Model) - Loss: 0.7086 - Accuracy: 0.4524 - F1: 0.4474
sub_5:Test (Best Model) - Loss: 0.6851 - Accuracy: 0.5476 - F1: 0.5435
sub_13:Test (Best Model) - Loss: 0.6833 - Accuracy: 0.5476 - F1: 0.5453
sub_6:Test (Best Model) - Loss: 0.6960 - Accuracy: 0.5119 - F1: 0.5118
sub_3:Test (Best Model) - Loss: 0.6995 - Accuracy: 0.5238 - F1: 0.5102
sub_1:Test (Best Model) - Loss: 0.7059 - Accuracy: 0.4643 - F1: 0.4642
sub_7:Test (Best Model) - Loss: 0.7057 - Accuracy: 0.4167 - F1: 0.4065
sub_2:Test (Best Model) - Loss: 0.7040 - Accuracy: 0.4524 - F1: 0.4511
sub_8:Test (Best Model) - Loss: 0.6948 - Accuracy: 0.4643 - F1: 0.4354
sub_11:Test (Best Model) - Loss: 0.6998 - Accuracy: 0.5357 - F1: 0.5276
sub_13:Test (Best Model) - Loss: 0.7052 - Accuracy: 0.3690 - F1: 0.3682
sub_14:Test (Best Model) - Loss: 0.6785 - Accuracy: 0.6190 - F1: 0.6190
sub_12:Test (Best Model) - Loss: 0.6814 - Accuracy: 0.5238 - F1: 0.5238
sub_4:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.5357 - F1: 0.5351
sub_5:Test (Best Model) - Loss: 0.7037 - Accuracy: 0.4286 - F1: 0.4256
sub_6:Test (Best Model) - Loss: 0.7012 - Accuracy: 0.4405 - F1: 0.4404
sub_3:Test (Best Model) - Loss: 0.7018 - Accuracy: 0.4762 - F1: 0.4653
sub_9:Test (Best Model) - Loss: 0.7038 - Accuracy: 0.4286 - F1: 0.4273
sub_1:Test (Best Model) - Loss: 0.6884 - Accuracy: 0.5357 - F1: 0.5351
sub_7:Test (Best Model) - Loss: 0.7074 - Accuracy: 0.4405 - F1: 0.4307
sub_11:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5119 - F1: 0.5113
sub_13:Test (Best Model) - Loss: 0.7289 - Accuracy: 0.3452 - F1: 0.3444
sub_12:Test (Best Model) - Loss: 0.6958 - Accuracy: 0.5000 - F1: 0.4928
sub_4:Test (Best Model) - Loss: 0.6904 - Accuracy: 0.5476 - F1: 0.5435
sub_3:Test (Best Model) - Loss: 0.6978 - Accuracy: 0.4881 - F1: 0.4712
sub_6:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.5714 - F1: 0.5675
sub_9:Test (Best Model) - Loss: 0.6765 - Accuracy: 0.6667 - F1: 0.6571
sub_14:Test (Best Model) - Loss: 0.7047 - Accuracy: 0.4405 - F1: 0.4404
sub_8:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.5595 - F1: 0.5580
sub_5:Test (Best Model) - Loss: 0.7017 - Accuracy: 0.4405 - F1: 0.4366
sub_7:Test (Best Model) - Loss: 0.7080 - Accuracy: 0.4643 - F1: 0.4549
sub_11:Test (Best Model) - Loss: 0.6797 - Accuracy: 0.6190 - F1: 0.6171
sub_2:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.5357 - F1: 0.5107
sub_12:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5119 - F1: 0.5113
sub_6:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5238 - F1: 0.5059
sub_3:Test (Best Model) - Loss: 0.7016 - Accuracy: 0.4762 - F1: 0.4735
sub_10:Test (Best Model) - Loss: 0.7244 - Accuracy: 0.3690 - F1: 0.2837
sub_14:Test (Best Model) - Loss: 0.6961 - Accuracy: 0.5000 - F1: 0.4632
sub_9:Test (Best Model) - Loss: 0.6765 - Accuracy: 0.5952 - F1: 0.5950
sub_8:Test (Best Model) - Loss: 0.6700 - Accuracy: 0.6310 - F1: 0.6267
sub_13:Test (Best Model) - Loss: 0.6740 - Accuracy: 0.6071 - F1: 0.5860
sub_7:Test (Best Model) - Loss: 0.6836 - Accuracy: 0.5357 - F1: 0.5341
sub_4:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.5119 - F1: 0.5113
sub_1:Test (Best Model) - Loss: 0.7068 - Accuracy: 0.4881 - F1: 0.4863
sub_2:Test (Best Model) - Loss: 0.6724 - Accuracy: 0.6429 - F1: 0.6396
sub_11:Test (Best Model) - Loss: 0.7226 - Accuracy: 0.2976 - F1: 0.2951
sub_12:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.4881 - F1: 0.4880
sub_5:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5238 - F1: 0.5170
sub_6:Test (Best Model) - Loss: 0.6676 - Accuracy: 0.6905 - F1: 0.6889
sub_9:Test (Best Model) - Loss: 0.6854 - Accuracy: 0.5595 - F1: 0.5518
sub_13:Test (Best Model) - Loss: 0.7138 - Accuracy: 0.3333 - F1: 0.3012
sub_8:Test (Best Model) - Loss: 0.7475 - Accuracy: 0.2738 - F1: 0.2729
sub_7:Test (Best Model) - Loss: 0.7301 - Accuracy: 0.2857 - F1: 0.2853
sub_2:Test (Best Model) - Loss: 0.6753 - Accuracy: 0.6071 - F1: 0.6066
sub_10:Test (Best Model) - Loss: 0.7022 - Accuracy: 0.4524 - F1: 0.4474
sub_11:Test (Best Model) - Loss: 0.7103 - Accuracy: 0.3929 - F1: 0.3928
sub_5:Test (Best Model) - Loss: 0.6850 - Accuracy: 0.5595 - F1: 0.5544
sub_14:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.4881 - F1: 0.4880
sub_6:Test (Best Model) - Loss: 0.7587 - Accuracy: 0.2024 - F1: 0.2014
sub_12:Test (Best Model) - Loss: 0.7106 - Accuracy: 0.4048 - F1: 0.4034
sub_13:Test (Best Model) - Loss: 0.6789 - Accuracy: 0.6190 - F1: 0.6182
sub_1:Test (Best Model) - Loss: 0.7104 - Accuracy: 0.4167 - F1: 0.4126
sub_2:Test (Best Model) - Loss: 0.7075 - Accuracy: 0.4048 - F1: 0.3962
sub_5:Test (Best Model) - Loss: 0.7172 - Accuracy: 0.3571 - F1: 0.3568
sub_10:Test (Best Model) - Loss: 0.6666 - Accuracy: 0.7143 - F1: 0.7035
sub_11:Test (Best Model) - Loss: 0.6966 - Accuracy: 0.4643 - F1: 0.4511
sub_4:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5238 - F1: 0.5170
sub_9:Test (Best Model) - Loss: 0.7144 - Accuracy: 0.3810 - F1: 0.3512
sub_14:Test (Best Model) - Loss: 0.6845 - Accuracy: 0.5476 - F1: 0.5382
sub_13:Test (Best Model) - Loss: 0.7006 - Accuracy: 0.4524 - F1: 0.4524
sub_2:Test (Best Model) - Loss: 0.6828 - Accuracy: 0.5952 - F1: 0.5952
sub_10:Test (Best Model) - Loss: 0.6844 - Accuracy: 0.5833 - F1: 0.5785
sub_4:Test (Best Model) - Loss: 0.6702 - Accuracy: 0.6667 - F1: 0.6636
sub_9:Test (Best Model) - Loss: 0.7034 - Accuracy: 0.4405 - F1: 0.4385
sub_1:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.5238 - F1: 0.5195
sub_14:Test (Best Model) - Loss: 0.6949 - Accuracy: 0.5119 - F1: 0.5102
sub_2:Test (Best Model) - Loss: 0.6742 - Accuracy: 0.5595 - F1: 0.5580
sub_1:Test (Best Model) - Loss: 0.7003 - Accuracy: 0.5000 - F1: 0.4974
sub_9:Test (Best Model) - Loss: 0.7067 - Accuracy: 0.4048 - F1: 0.4044
sub_4:Test (Best Model) - Loss: 0.7048 - Accuracy: 0.4286 - F1: 0.4256
sub_10:Test (Best Model) - Loss: 0.6971 - Accuracy: 0.4762 - F1: 0.4510
sub_1:Test (Best Model) - Loss: 0.7054 - Accuracy: 0.4286 - F1: 0.4256
sub_2:Test (Best Model) - Loss: 0.7096 - Accuracy: 0.4405 - F1: 0.4398

=== Summary Results ===

acc: 49.58 ± 2.01
F1: 48.84 ± 2.02
acc-in: 51.60 ± 3.21
F1-in: 50.91 ± 3.29
