lr: 1e-06
sub_4:Test (Best Model) - Loss: 0.6801 - Accuracy: 0.5833 - F1: 0.5761
sub_12:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.5357 - F1: 0.5325
sub_6:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5476 - F1: 0.4997
sub_10:Test (Best Model) - Loss: 0.7289 - Accuracy: 0.3452 - F1: 0.2922
sub_7:Test (Best Model) - Loss: 0.7063 - Accuracy: 0.4524 - F1: 0.4260
sub_8:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.5000 - F1: 0.4759
sub_14:Test (Best Model) - Loss: 0.7069 - Accuracy: 0.4881 - F1: 0.4466
sub_1:Test (Best Model) - Loss: 0.6557 - Accuracy: 0.6667 - F1: 0.6619
sub_4:Test (Best Model) - Loss: 0.6953 - Accuracy: 0.4762 - F1: 0.4565
sub_6:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.6429 - F1: 0.6427
sub_10:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.5714 - F1: 0.5457
sub_5:Test (Best Model) - Loss: 0.7138 - Accuracy: 0.4048 - F1: 0.3962
sub_2:Test (Best Model) - Loss: 0.6729 - Accuracy: 0.6190 - F1: 0.6188
sub_12:Test (Best Model) - Loss: 0.7033 - Accuracy: 0.4881 - F1: 0.4466
sub_8:Test (Best Model) - Loss: 0.6718 - Accuracy: 0.7024 - F1: 0.7013
sub_7:Test (Best Model) - Loss: 0.7012 - Accuracy: 0.4524 - F1: 0.4474
sub_11:Test (Best Model) - Loss: 0.7112 - Accuracy: 0.4286 - F1: 0.4273
sub_3:Test (Best Model) - Loss: 0.6857 - Accuracy: 0.5952 - F1: 0.5800
sub_9:Test (Best Model) - Loss: 0.6444 - Accuracy: 0.7500 - F1: 0.7418
sub_10:Test (Best Model) - Loss: 0.6757 - Accuracy: 0.5476 - F1: 0.5382
sub_13:Test (Best Model) - Loss: 0.7181 - Accuracy: 0.4643 - F1: 0.3517
sub_2:Test (Best Model) - Loss: 0.7043 - Accuracy: 0.4405 - F1: 0.4398
sub_5:Test (Best Model) - Loss: 0.7157 - Accuracy: 0.3810 - F1: 0.3354
sub_6:Test (Best Model) - Loss: 0.6986 - Accuracy: 0.4881 - F1: 0.4792
sub_12:Test (Best Model) - Loss: 0.6492 - Accuracy: 0.7381 - F1: 0.7357
sub_1:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.5595 - F1: 0.5450
sub_14:Test (Best Model) - Loss: 0.6900 - Accuracy: 0.4881 - F1: 0.4880
sub_8:Test (Best Model) - Loss: 0.6593 - Accuracy: 0.6429 - F1: 0.6410
sub_4:Test (Best Model) - Loss: 0.6628 - Accuracy: 0.7024 - F1: 0.6951
sub_3:Test (Best Model) - Loss: 0.6633 - Accuracy: 0.7500 - F1: 0.7456
sub_9:Test (Best Model) - Loss: 0.7002 - Accuracy: 0.4167 - F1: 0.3975
sub_10:Test (Best Model) - Loss: 0.6862 - Accuracy: 0.5833 - F1: 0.5696
sub_6:Test (Best Model) - Loss: 0.6978 - Accuracy: 0.4762 - F1: 0.4107
sub_5:Test (Best Model) - Loss: 0.6648 - Accuracy: 0.6667 - F1: 0.6421
sub_13:Test (Best Model) - Loss: 0.7093 - Accuracy: 0.4524 - F1: 0.3451
sub_11:Test (Best Model) - Loss: 0.6758 - Accuracy: 0.6190 - F1: 0.6188
sub_7:Test (Best Model) - Loss: 0.6795 - Accuracy: 0.5595 - F1: 0.5167
sub_8:Test (Best Model) - Loss: 0.6810 - Accuracy: 0.5833 - F1: 0.5828
sub_2:Test (Best Model) - Loss: 0.6459 - Accuracy: 0.7262 - F1: 0.7145
sub_3:Test (Best Model) - Loss: 0.6953 - Accuracy: 0.5000 - F1: 0.4151
sub_4:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.5952 - F1: 0.5915
sub_12:Test (Best Model) - Loss: 0.7073 - Accuracy: 0.4048 - F1: 0.4034
sub_6:Test (Best Model) - Loss: 0.6950 - Accuracy: 0.4643 - F1: 0.4581
sub_5:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5714 - F1: 0.5714
sub_10:Test (Best Model) - Loss: 0.7117 - Accuracy: 0.3929 - F1: 0.3823
sub_7:Test (Best Model) - Loss: 0.7002 - Accuracy: 0.4405 - F1: 0.4267
sub_1:Test (Best Model) - Loss: 0.6818 - Accuracy: 0.5952 - F1: 0.5894
sub_2:Test (Best Model) - Loss: 0.7217 - Accuracy: 0.3333 - F1: 0.3318
sub_3:Test (Best Model) - Loss: 0.6540 - Accuracy: 0.7738 - F1: 0.7730
sub_11:Test (Best Model) - Loss: 0.6843 - Accuracy: 0.5595 - F1: 0.5580
sub_12:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.5714 - F1: 0.5553
sub_14:Test (Best Model) - Loss: 0.6553 - Accuracy: 0.7619 - F1: 0.7569
sub_13:Test (Best Model) - Loss: 0.6724 - Accuracy: 0.6190 - F1: 0.6082
sub_4:Test (Best Model) - Loss: 0.7047 - Accuracy: 0.4286 - F1: 0.3571
sub_5:Test (Best Model) - Loss: 0.6969 - Accuracy: 0.4762 - F1: 0.4687
sub_6:Test (Best Model) - Loss: 0.6778 - Accuracy: 0.6190 - F1: 0.5910
sub_9:Test (Best Model) - Loss: 0.7165 - Accuracy: 0.3333 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.7064 - Accuracy: 0.4643 - F1: 0.4624
sub_1:Test (Best Model) - Loss: 0.6767 - Accuracy: 0.6548 - F1: 0.6212
sub_2:Test (Best Model) - Loss: 0.7041 - Accuracy: 0.5119 - F1: 0.5113
sub_3:Test (Best Model) - Loss: 0.7088 - Accuracy: 0.4286 - F1: 0.3450
sub_12:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.5000 - F1: 0.4928
sub_10:Test (Best Model) - Loss: 0.6983 - Accuracy: 0.4762 - F1: 0.4735
sub_4:Test (Best Model) - Loss: 0.7061 - Accuracy: 0.4881 - F1: 0.4874
sub_11:Test (Best Model) - Loss: 0.6885 - Accuracy: 0.5476 - F1: 0.5466
sub_6:Test (Best Model) - Loss: 0.7065 - Accuracy: 0.4167 - F1: 0.4159
sub_5:Test (Best Model) - Loss: 0.7251 - Accuracy: 0.3095 - F1: 0.3060
sub_2:Test (Best Model) - Loss: 0.7212 - Accuracy: 0.3333 - F1: 0.3012
sub_8:Test (Best Model) - Loss: 0.7139 - Accuracy: 0.4643 - F1: 0.3918
sub_1:Test (Best Model) - Loss: 0.6979 - Accuracy: 0.5000 - F1: 0.4989
sub_14:Test (Best Model) - Loss: 0.7016 - Accuracy: 0.4405 - F1: 0.4366
sub_12:Test (Best Model) - Loss: 0.6926 - Accuracy: 0.5357 - F1: 0.5243
sub_13:Test (Best Model) - Loss: 0.6964 - Accuracy: 0.5000 - F1: 0.4812
sub_3:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5119 - F1: 0.4557
sub_7:Test (Best Model) - Loss: 0.7024 - Accuracy: 0.4405 - F1: 0.4220
sub_10:Test (Best Model) - Loss: 0.6958 - Accuracy: 0.3929 - F1: 0.3928
sub_6:Test (Best Model) - Loss: 0.6975 - Accuracy: 0.4881 - F1: 0.4880
sub_14:Test (Best Model) - Loss: 0.6843 - Accuracy: 0.5833 - F1: 0.5428
sub_8:Test (Best Model) - Loss: 0.7020 - Accuracy: 0.4524 - F1: 0.4474
sub_1:Test (Best Model) - Loss: 0.7059 - Accuracy: 0.4762 - F1: 0.4714
sub_12:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5000 - F1: 0.4997
sub_5:Test (Best Model) - Loss: 0.6790 - Accuracy: 0.6310 - F1: 0.6267
sub_7:Test (Best Model) - Loss: 0.7033 - Accuracy: 0.3810 - F1: 0.3721
sub_10:Test (Best Model) - Loss: 0.7027 - Accuracy: 0.4881 - F1: 0.4712
sub_11:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5595 - F1: 0.5595
sub_4:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5119 - F1: 0.4911
sub_9:Test (Best Model) - Loss: 0.6536 - Accuracy: 0.5952 - F1: 0.5361
sub_13:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.4881 - F1: 0.4188
sub_14:Test (Best Model) - Loss: 0.7275 - Accuracy: 0.2500 - F1: 0.2253
sub_3:Test (Best Model) - Loss: 0.6997 - Accuracy: 0.4762 - F1: 0.4612
sub_2:Test (Best Model) - Loss: 0.6710 - Accuracy: 0.7143 - F1: 0.7117
sub_5:Test (Best Model) - Loss: 0.7122 - Accuracy: 0.4524 - F1: 0.4511
sub_10:Test (Best Model) - Loss: 0.6832 - Accuracy: 0.5476 - F1: 0.5143
sub_1:Test (Best Model) - Loss: 0.6669 - Accuracy: 0.6786 - F1: 0.6774
sub_4:Test (Best Model) - Loss: 0.6862 - Accuracy: 0.5595 - F1: 0.5487
sub_7:Test (Best Model) - Loss: 0.7106 - Accuracy: 0.4762 - F1: 0.3996
sub_3:Test (Best Model) - Loss: 0.6898 - Accuracy: 0.5000 - F1: 0.5000
sub_12:Test (Best Model) - Loss: 0.7068 - Accuracy: 0.4643 - F1: 0.4026
sub_13:Test (Best Model) - Loss: 0.6959 - Accuracy: 0.5000 - F1: 0.4954
sub_9:Test (Best Model) - Loss: 0.7003 - Accuracy: 0.5119 - F1: 0.5085
sub_10:Test (Best Model) - Loss: 0.7301 - Accuracy: 0.2738 - F1: 0.2687
sub_6:Test (Best Model) - Loss: 0.6782 - Accuracy: 0.5714 - F1: 0.5692
sub_8:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.5476 - F1: 0.5453
sub_1:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.5357 - F1: 0.5107
sub_14:Test (Best Model) - Loss: 0.7017 - Accuracy: 0.4405 - F1: 0.4166
sub_11:Test (Best Model) - Loss: 0.6698 - Accuracy: 0.7024 - F1: 0.6989
sub_12:Test (Best Model) - Loss: 0.7281 - Accuracy: 0.2738 - F1: 0.2687
sub_3:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.4762 - F1: 0.4735
sub_7:Test (Best Model) - Loss: 0.6898 - Accuracy: 0.5595 - F1: 0.5167
sub_10:Test (Best Model) - Loss: 0.6738 - Accuracy: 0.6786 - F1: 0.6782
sub_13:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.4881 - F1: 0.4880
sub_5:Test (Best Model) - Loss: 0.6693 - Accuracy: 0.6190 - F1: 0.6182
sub_4:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.5119 - F1: 0.4999
sub_8:Test (Best Model) - Loss: 0.6774 - Accuracy: 0.6310 - F1: 0.6309
sub_6:Test (Best Model) - Loss: 0.7222 - Accuracy: 0.2500 - F1: 0.2499
sub_1:Test (Best Model) - Loss: 0.6809 - Accuracy: 0.5357 - F1: 0.5107
sub_12:Test (Best Model) - Loss: 0.6797 - Accuracy: 0.6786 - F1: 0.6748
sub_4:Test (Best Model) - Loss: 0.7151 - Accuracy: 0.3452 - F1: 0.3429
sub_14:Test (Best Model) - Loss: 0.6834 - Accuracy: 0.5357 - F1: 0.4729
sub_2:Test (Best Model) - Loss: 0.6624 - Accuracy: 0.7024 - F1: 0.7013
sub_9:Test (Best Model) - Loss: 0.6978 - Accuracy: 0.4881 - F1: 0.4540
sub_5:Test (Best Model) - Loss: 0.7137 - Accuracy: 0.3214 - F1: 0.3206
sub_8:Test (Best Model) - Loss: 0.6751 - Accuracy: 0.6310 - F1: 0.6296
sub_13:Test (Best Model) - Loss: 0.7230 - Accuracy: 0.2857 - F1: 0.2653
sub_6:Test (Best Model) - Loss: 0.7221 - Accuracy: 0.3095 - F1: 0.2835
sub_7:Test (Best Model) - Loss: 0.7162 - Accuracy: 0.4048 - F1: 0.4017
sub_10:Test (Best Model) - Loss: 0.7001 - Accuracy: 0.5119 - F1: 0.4723
sub_1:Test (Best Model) - Loss: 0.7316 - Accuracy: 0.2619 - F1: 0.2341
sub_12:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.5476 - F1: 0.5258
sub_11:Test (Best Model) - Loss: 0.7074 - Accuracy: 0.4286 - F1: 0.4233
sub_4:Test (Best Model) - Loss: 0.6704 - Accuracy: 0.6190 - F1: 0.6171
sub_14:Test (Best Model) - Loss: 0.6595 - Accuracy: 0.7500 - F1: 0.7500
sub_8:Test (Best Model) - Loss: 0.7542 - Accuracy: 0.1429 - F1: 0.1409
sub_3:Test (Best Model) - Loss: 0.7278 - Accuracy: 0.2738 - F1: 0.2560
sub_5:Test (Best Model) - Loss: 0.6756 - Accuracy: 0.6310 - F1: 0.6152
sub_13:Test (Best Model) - Loss: 0.6665 - Accuracy: 0.6786 - F1: 0.6785
sub_2:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.5476 - F1: 0.4590
sub_6:Test (Best Model) - Loss: 0.7057 - Accuracy: 0.3929 - F1: 0.3729
sub_10:Test (Best Model) - Loss: 0.6891 - Accuracy: 0.5357 - F1: 0.4625
sub_9:Test (Best Model) - Loss: 0.6815 - Accuracy: 0.6905 - F1: 0.6816
sub_1:Test (Best Model) - Loss: 0.6859 - Accuracy: 0.5595 - F1: 0.5590
sub_12:Test (Best Model) - Loss: 0.7356 - Accuracy: 0.2262 - F1: 0.1931
sub_6:Test (Best Model) - Loss: 0.6822 - Accuracy: 0.6429 - F1: 0.6420
sub_5:Test (Best Model) - Loss: 0.7082 - Accuracy: 0.3810 - F1: 0.3681
sub_7:Test (Best Model) - Loss: 0.6820 - Accuracy: 0.5833 - F1: 0.5785
sub_2:Test (Best Model) - Loss: 0.7291 - Accuracy: 0.2381 - F1: 0.2014
sub_13:Test (Best Model) - Loss: 0.7242 - Accuracy: 0.2976 - F1: 0.2745
sub_14:Test (Best Model) - Loss: 0.7310 - Accuracy: 0.2619 - F1: 0.2615
sub_4:Test (Best Model) - Loss: 0.7059 - Accuracy: 0.4286 - F1: 0.4122
sub_1:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5000 - F1: 0.4759
sub_11:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.5833 - F1: 0.5609
sub_12:Test (Best Model) - Loss: 0.7599 - Accuracy: 0.2262 - F1: 0.2261
sub_8:Test (Best Model) - Loss: 0.6718 - Accuracy: 0.6310 - F1: 0.6152
sub_2:Test (Best Model) - Loss: 0.6732 - Accuracy: 0.6429 - F1: 0.6327
sub_6:Test (Best Model) - Loss: 0.6837 - Accuracy: 0.5714 - F1: 0.5457
sub_9:Test (Best Model) - Loss: 0.6551 - Accuracy: 0.7262 - F1: 0.7172
sub_14:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.6071 - F1: 0.6071
sub_3:Test (Best Model) - Loss: 0.6753 - Accuracy: 0.6310 - F1: 0.6219
sub_4:Test (Best Model) - Loss: 0.6708 - Accuracy: 0.6786 - F1: 0.6730
sub_7:Test (Best Model) - Loss: 0.7010 - Accuracy: 0.4286 - F1: 0.4011
sub_13:Test (Best Model) - Loss: 0.6352 - Accuracy: 0.8333 - F1: 0.8332
sub_6:Test (Best Model) - Loss: 0.7109 - Accuracy: 0.4762 - F1: 0.3736
sub_11:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5238 - F1: 0.5214
sub_10:Test (Best Model) - Loss: 0.7040 - Accuracy: 0.4524 - F1: 0.3451
sub_5:Test (Best Model) - Loss: 0.6772 - Accuracy: 0.6071 - F1: 0.6026
sub_1:Test (Best Model) - Loss: 0.6676 - Accuracy: 0.7262 - F1: 0.7145
sub_8:Test (Best Model) - Loss: 0.6743 - Accuracy: 0.5833 - F1: 0.5270
sub_12:Test (Best Model) - Loss: 0.6634 - Accuracy: 0.7262 - F1: 0.7079
sub_13:Test (Best Model) - Loss: 0.6495 - Accuracy: 0.8333 - F1: 0.8332
sub_10:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5476 - F1: 0.4590
sub_9:Test (Best Model) - Loss: 0.7116 - Accuracy: 0.4524 - F1: 0.3839
sub_2:Test (Best Model) - Loss: 0.7125 - Accuracy: 0.4048 - F1: 0.3304
sub_4:Test (Best Model) - Loss: 0.7086 - Accuracy: 0.3571 - F1: 0.3557
sub_7:Test (Best Model) - Loss: 0.6700 - Accuracy: 0.7024 - F1: 0.6972
sub_11:Test (Best Model) - Loss: 0.7159 - Accuracy: 0.3214 - F1: 0.3096
sub_3:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.4375
sub_8:Test (Best Model) - Loss: 0.7085 - Accuracy: 0.3452 - F1: 0.3376
sub_5:Test (Best Model) - Loss: 0.6740 - Accuracy: 0.5952 - F1: 0.5950
sub_1:Test (Best Model) - Loss: 0.7083 - Accuracy: 0.4048 - F1: 0.4044
sub_4:Test (Best Model) - Loss: 0.7253 - Accuracy: 0.3690 - F1: 0.3536
sub_2:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.5000 - F1: 0.4896
sub_3:Test (Best Model) - Loss: 0.6961 - Accuracy: 0.4881 - F1: 0.4291
sub_11:Test (Best Model) - Loss: 0.6784 - Accuracy: 0.5357 - F1: 0.5159
sub_14:Test (Best Model) - Loss: 0.6990 - Accuracy: 0.4643 - F1: 0.4549
sub_9:Test (Best Model) - Loss: 0.7017 - Accuracy: 0.4643 - F1: 0.4354
sub_5:Test (Best Model) - Loss: 0.7018 - Accuracy: 0.5119 - F1: 0.4856
sub_13:Test (Best Model) - Loss: 0.7176 - Accuracy: 0.3214 - F1: 0.2848
sub_2:Test (Best Model) - Loss: 0.6724 - Accuracy: 0.6310 - F1: 0.6010
sub_3:Test (Best Model) - Loss: 0.7188 - Accuracy: 0.3095 - F1: 0.3095
sub_1:Test (Best Model) - Loss: 0.6745 - Accuracy: 0.6310 - F1: 0.6305
sub_14:Test (Best Model) - Loss: 0.6965 - Accuracy: 0.4643 - F1: 0.4642
sub_8:Test (Best Model) - Loss: 0.7098 - Accuracy: 0.4286 - F1: 0.3450
sub_2:Test (Best Model) - Loss: 0.6975 - Accuracy: 0.4643 - F1: 0.4026
sub_7:Test (Best Model) - Loss: 0.6974 - Accuracy: 0.5357 - F1: 0.5303
sub_9:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.5833 - F1: 0.5696
sub_11:Test (Best Model) - Loss: 0.6948 - Accuracy: 0.4881 - F1: 0.4863
sub_8:Test (Best Model) - Loss: 0.6588 - Accuracy: 0.7024 - F1: 0.6989
sub_7:Test (Best Model) - Loss: 0.7075 - Accuracy: 0.3929 - F1: 0.3823
sub_3:Test (Best Model) - Loss: 0.7027 - Accuracy: 0.4405 - F1: 0.4267
sub_13:Test (Best Model) - Loss: 0.7237 - Accuracy: 0.2857 - F1: 0.2841
sub_14:Test (Best Model) - Loss: 0.7221 - Accuracy: 0.4048 - F1: 0.3924
sub_9:Test (Best Model) - Loss: 0.7023 - Accuracy: 0.5476 - F1: 0.5143
sub_13:Test (Best Model) - Loss: 0.6329 - Accuracy: 0.8333 - F1: 0.8332
sub_11:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.5000 - F1: 0.4954
sub_9:Test (Best Model) - Loss: 0.7026 - Accuracy: 0.3929 - F1: 0.3823
sub_14:Test (Best Model) - Loss: 0.7007 - Accuracy: 0.4405 - F1: 0.4220
sub_9:Test (Best Model) - Loss: 0.7326 - Accuracy: 0.2619 - F1: 0.2513
sub_11:Test (Best Model) - Loss: 0.7068 - Accuracy: 0.4048 - F1: 0.3924
sub_9:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5119 - F1: 0.5062
sub_11:Test (Best Model) - Loss: 0.7295 - Accuracy: 0.3452 - F1: 0.3451

=== Summary Results ===

acc: 50.90 ± 1.84
F1: 49.00 ± 2.05
acc-in: 54.59 ± 3.71
F1-in: 54.02 ± 3.94
