lr: 0.0001
sub_1:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6962 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6961 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6909 - Accuracy: 0.5357 - F1: 0.4822
sub_1:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.4643 - F1: 0.3171
sub_1:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6826 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6905 - Accuracy: 0.5000 - F1: 0.3534
sub_1:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_1:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6652 - Accuracy: 0.5833 - F1: 0.4958
sub_2:Test (Best Model) - Loss: 0.6697 - Accuracy: 0.5000 - F1: 0.3333
sub_2:Test (Best Model) - Loss: 0.6685 - Accuracy: 0.6071 - F1: 0.5690
sub_2:Test (Best Model) - Loss: 0.6600 - Accuracy: 0.6905 - F1: 0.6788
sub_2:Test (Best Model) - Loss: 0.6455 - Accuracy: 0.8810 - F1: 0.8803
sub_2:Test (Best Model) - Loss: 0.6558 - Accuracy: 0.6429 - F1: 0.5982
sub_2:Test (Best Model) - Loss: 0.6251 - Accuracy: 0.8571 - F1: 0.8564
sub_2:Test (Best Model) - Loss: 0.6641 - Accuracy: 0.6310 - F1: 0.5810
sub_2:Test (Best Model) - Loss: 0.6145 - Accuracy: 0.7976 - F1: 0.7927
sub_2:Test (Best Model) - Loss: 0.6502 - Accuracy: 0.7500 - F1: 0.7393
sub_2:Test (Best Model) - Loss: 0.6553 - Accuracy: 0.7500 - F1: 0.7491
sub_2:Test (Best Model) - Loss: 0.6513 - Accuracy: 0.7738 - F1: 0.7712
sub_2:Test (Best Model) - Loss: 0.6602 - Accuracy: 0.8095 - F1: 0.8094
sub_2:Test (Best Model) - Loss: 0.6402 - Accuracy: 0.8214 - F1: 0.8214
sub_2:Test (Best Model) - Loss: 0.6420 - Accuracy: 0.7262 - F1: 0.7230
sub_3:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6973 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6948 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6928 - Accuracy: 0.5119 - F1: 0.3778
sub_3:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6962 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5595 - F1: 0.5088
sub_3:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_3:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6587 - Accuracy: 0.6786 - F1: 0.6415
sub_4:Test (Best Model) - Loss: 0.6177 - Accuracy: 0.7738 - F1: 0.7735
sub_4:Test (Best Model) - Loss: 0.6694 - Accuracy: 0.5595 - F1: 0.4535
sub_4:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5000 - F1: 0.3333
sub_4:Test (Best Model) - Loss: 0.6892 - Accuracy: 0.6786 - F1: 0.6680
sub_4:Test (Best Model) - Loss: 0.6282 - Accuracy: 0.7738 - F1: 0.7616
sub_4:Test (Best Model) - Loss: 0.6536 - Accuracy: 0.8571 - F1: 0.8564
sub_4:Test (Best Model) - Loss: 0.6445 - Accuracy: 0.8571 - F1: 0.8571
sub_4:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5119 - F1: 0.3593
sub_4:Test (Best Model) - Loss: 0.6954 - Accuracy: 0.5119 - F1: 0.4911
sub_4:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.6190 - F1: 0.5910
sub_4:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.5357 - F1: 0.5276
sub_4:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.5000 - F1: 0.4269
sub_4:Test (Best Model) - Loss: 0.6749 - Accuracy: 0.6429 - F1: 0.6377
sub_5:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.5119 - F1: 0.5062
sub_5:Test (Best Model) - Loss: 0.6953 - Accuracy: 0.4762 - F1: 0.4510
sub_5:Test (Best Model) - Loss: 0.6966 - Accuracy: 0.4881 - F1: 0.3806
sub_5:Test (Best Model) - Loss: 0.6951 - Accuracy: 0.4881 - F1: 0.3280
sub_5:Test (Best Model) - Loss: 0.6985 - Accuracy: 0.4167 - F1: 0.4166
sub_5:Test (Best Model) - Loss: 0.6932 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6922 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6905 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6873 - Accuracy: 0.6548 - F1: 0.6543
sub_5:Test (Best Model) - Loss: 0.6937 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.5119 - F1: 0.4459
sub_5:Test (Best Model) - Loss: 0.6898 - Accuracy: 0.5714 - F1: 0.4750
sub_5:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5000 - F1: 0.3713
sub_5:Test (Best Model) - Loss: 0.6930 - Accuracy: 0.5119 - F1: 0.5118
sub_6:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.5833 - F1: 0.5073
sub_6:Test (Best Model) - Loss: 0.6847 - Accuracy: 0.5000 - F1: 0.3333
sub_6:Test (Best Model) - Loss: 0.6845 - Accuracy: 0.5119 - F1: 0.4094
sub_6:Test (Best Model) - Loss: 0.6708 - Accuracy: 0.6548 - F1: 0.6523
sub_6:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.7143 - F1: 0.7083
sub_6:Test (Best Model) - Loss: 0.6791 - Accuracy: 0.6310 - F1: 0.6188
sub_6:Test (Best Model) - Loss: 0.6751 - Accuracy: 0.6310 - F1: 0.6188
sub_6:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.5238 - F1: 0.4013
sub_6:Test (Best Model) - Loss: 0.6726 - Accuracy: 0.5833 - F1: 0.5496
sub_6:Test (Best Model) - Loss: 0.6807 - Accuracy: 0.5952 - F1: 0.5894
sub_6:Test (Best Model) - Loss: 0.6764 - Accuracy: 0.6667 - F1: 0.6313
sub_6:Test (Best Model) - Loss: 0.6814 - Accuracy: 0.5952 - F1: 0.5800
sub_6:Test (Best Model) - Loss: 0.6787 - Accuracy: 0.7143 - F1: 0.7128
sub_6:Test (Best Model) - Loss: 0.6829 - Accuracy: 0.6071 - F1: 0.5904
sub_6:Test (Best Model) - Loss: 0.6792 - Accuracy: 0.5833 - F1: 0.5556
sub_7:Test (Best Model) - Loss: 0.6969 - Accuracy: 0.3690 - F1: 0.3668
sub_7:Test (Best Model) - Loss: 0.6954 - Accuracy: 0.4048 - F1: 0.4044
sub_7:Test (Best Model) - Loss: 0.6979 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6977 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.4881 - F1: 0.3947
sub_7:Test (Best Model) - Loss: 0.6969 - Accuracy: 0.3095 - F1: 0.2898
sub_7:Test (Best Model) - Loss: 0.6939 - Accuracy: 0.5119 - F1: 0.4911
sub_7:Test (Best Model) - Loss: 0.6851 - Accuracy: 0.5595 - F1: 0.4901
sub_7:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.6071 - F1: 0.5619
sub_7:Test (Best Model) - Loss: 0.6947 - Accuracy: 0.4405 - F1: 0.3760
sub_7:Test (Best Model) - Loss: 0.6924 - Accuracy: 0.4762 - F1: 0.3736
sub_7:Test (Best Model) - Loss: 0.6941 - Accuracy: 0.4048 - F1: 0.3924
sub_7:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5476 - F1: 0.4997
sub_7:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5000 - F1: 0.3333
sub_7:Test (Best Model) - Loss: 0.6951 - Accuracy: 0.5119 - F1: 0.3593
sub_8:Test (Best Model) - Loss: 0.6831 - Accuracy: 0.6071 - F1: 0.5810
sub_8:Test (Best Model) - Loss: 0.6866 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5119 - F1: 0.3593
sub_8:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6883 - Accuracy: 0.5714 - F1: 0.4750
sub_8:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.6190 - F1: 0.6136
sub_8:Test (Best Model) - Loss: 0.6888 - Accuracy: 0.5000 - F1: 0.3333
sub_8:Test (Best Model) - Loss: 0.6822 - Accuracy: 0.5833 - F1: 0.5731
sub_8:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.4881 - F1: 0.3280
sub_8:Test (Best Model) - Loss: 0.6811 - Accuracy: 0.6429 - F1: 0.6410
sub_8:Test (Best Model) - Loss: 0.6683 - Accuracy: 0.6786 - F1: 0.6525
sub_8:Test (Best Model) - Loss: 0.6627 - Accuracy: 0.7738 - F1: 0.7712
sub_8:Test (Best Model) - Loss: 0.6596 - Accuracy: 0.6429 - F1: 0.5906
sub_8:Test (Best Model) - Loss: 0.6424 - Accuracy: 0.6786 - F1: 0.6415
sub_8:Test (Best Model) - Loss: 0.6389 - Accuracy: 0.7381 - F1: 0.7224
sub_9:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6956 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6959 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6900 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6881 - Accuracy: 0.5833 - F1: 0.4958
sub_9:Test (Best Model) - Loss: 0.6969 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6960 - Accuracy: 0.5119 - F1: 0.3593
sub_9:Test (Best Model) - Loss: 0.6998 - Accuracy: 0.4048 - F1: 0.4044
sub_9:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5714 - F1: 0.5457
sub_9:Test (Best Model) - Loss: 0.6975 - Accuracy: 0.4524 - F1: 0.4496
sub_9:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5000 - F1: 0.3333
sub_9:Test (Best Model) - Loss: 0.6938 - Accuracy: 0.5119 - F1: 0.3593
sub_9:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5238 - F1: 0.4167
sub_9:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5357 - F1: 0.4081
sub_9:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5119 - F1: 0.4094
sub_10:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.4643 - F1: 0.3517
sub_10:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6923 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6875 - Accuracy: 0.6071 - F1: 0.6057
sub_10:Test (Best Model) - Loss: 0.6864 - Accuracy: 0.5714 - F1: 0.4987
sub_10:Test (Best Model) - Loss: 0.6974 - Accuracy: 0.4286 - F1: 0.3450
sub_10:Test (Best Model) - Loss: 0.6948 - Accuracy: 0.4524 - F1: 0.3451
sub_10:Test (Best Model) - Loss: 0.6913 - Accuracy: 0.5000 - F1: 0.3333
sub_10:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.7024 - F1: 0.6825
sub_10:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5238 - F1: 0.5170
sub_10:Test (Best Model) - Loss: 0.6918 - Accuracy: 0.5357 - F1: 0.4729
sub_10:Test (Best Model) - Loss: 0.6950 - Accuracy: 0.5238 - F1: 0.4643
sub_10:Test (Best Model) - Loss: 0.6961 - Accuracy: 0.5238 - F1: 0.4887
sub_10:Test (Best Model) - Loss: 0.6944 - Accuracy: 0.4643 - F1: 0.4466
sub_11:Test (Best Model) - Loss: 0.6911 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6991 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6936 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6927 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6792 - Accuracy: 0.8571 - F1: 0.8568
sub_11:Test (Best Model) - Loss: 0.6957 - Accuracy: 0.4881 - F1: 0.3947
sub_11:Test (Best Model) - Loss: 0.7000 - Accuracy: 0.4881 - F1: 0.3649
sub_11:Test (Best Model) - Loss: 0.7040 - Accuracy: 0.4643 - F1: 0.4286
sub_11:Test (Best Model) - Loss: 0.7011 - Accuracy: 0.4048 - F1: 0.3993
sub_11:Test (Best Model) - Loss: 0.7016 - Accuracy: 0.4405 - F1: 0.3648
sub_11:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6899 - Accuracy: 0.5119 - F1: 0.3593
sub_11:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.5000 - F1: 0.3333
sub_11:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.4881 - F1: 0.3649
sub_11:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5714 - F1: 0.5592
sub_12:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6970 - Accuracy: 0.4881 - F1: 0.3280
sub_12:Test (Best Model) - Loss: 0.7022 - Accuracy: 0.4405 - F1: 0.3523
sub_12:Test (Best Model) - Loss: 0.6966 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6950 - Accuracy: 0.5119 - F1: 0.3593
sub_12:Test (Best Model) - Loss: 0.7046 - Accuracy: 0.4286 - F1: 0.3450
sub_12:Test (Best Model) - Loss: 0.6977 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6976 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.7011 - Accuracy: 0.4524 - F1: 0.4410
sub_12:Test (Best Model) - Loss: 0.6996 - Accuracy: 0.4643 - F1: 0.4414
sub_12:Test (Best Model) - Loss: 0.6914 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6929 - Accuracy: 0.5000 - F1: 0.3333
sub_12:Test (Best Model) - Loss: 0.6940 - Accuracy: 0.4762 - F1: 0.3226
sub_12:Test (Best Model) - Loss: 0.6984 - Accuracy: 0.4881 - F1: 0.4291
sub_12:Test (Best Model) - Loss: 0.6985 - Accuracy: 0.3929 - F1: 0.2821
sub_13:Test (Best Model) - Loss: 0.6890 - Accuracy: 0.5238 - F1: 0.4013
sub_13:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6881 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6898 - Accuracy: 0.5000 - F1: 0.3333
sub_13:Test (Best Model) - Loss: 0.6865 - Accuracy: 0.6429 - F1: 0.6214
sub_13:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.6190 - F1: 0.5787
sub_13:Test (Best Model) - Loss: 0.6838 - Accuracy: 0.5238 - F1: 0.3842
sub_13:Test (Best Model) - Loss: 0.6858 - Accuracy: 0.4881 - F1: 0.3280
sub_13:Test (Best Model) - Loss: 0.6801 - Accuracy: 0.7262 - F1: 0.7243
sub_13:Test (Best Model) - Loss: 0.6844 - Accuracy: 0.6429 - F1: 0.6166
sub_13:Test (Best Model) - Loss: 0.6564 - Accuracy: 0.6905 - F1: 0.6876
sub_13:Test (Best Model) - Loss: 0.6841 - Accuracy: 0.6310 - F1: 0.6296
sub_13:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.5238 - F1: 0.4013
sub_13:Test (Best Model) - Loss: 0.6684 - Accuracy: 0.7381 - F1: 0.7375
sub_13:Test (Best Model) - Loss: 0.6616 - Accuracy: 0.6786 - F1: 0.6782
sub_14:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5238 - F1: 0.4013
sub_14:Test (Best Model) - Loss: 0.6860 - Accuracy: 0.5833 - F1: 0.5556
sub_14:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.6071 - F1: 0.6003
sub_14:Test (Best Model) - Loss: 0.6894 - Accuracy: 0.7262 - F1: 0.7230
sub_14:Test (Best Model) - Loss: 0.6866 - Accuracy: 0.7262 - F1: 0.7243
sub_14:Test (Best Model) - Loss: 0.6900 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6906 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.5833 - F1: 0.5696
sub_14:Test (Best Model) - Loss: 0.6920 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6925 - Accuracy: 0.5000 - F1: 0.3333
sub_14:Test (Best Model) - Loss: 0.6889 - Accuracy: 0.5119 - F1: 0.3593

=== Summary Results ===

acc: 55.11 ± 6.84
F1: 45.85 ± 10.01
acc-in: 62.41 ± 8.52
F1-in: 55.06 ± 12.63
