lr: 0.0001
sub_2:Test (Best Model) - Loss: 0.0637 - Accuracy: 0.9881 - F1: 0.9881
sub_13:Test (Best Model) - Loss: 0.1789 - Accuracy: 0.9524 - F1: 0.9523
sub_14:Test (Best Model) - Loss: 0.2811 - Accuracy: 0.9286 - F1: 0.9285
sub_1:Test (Best Model) - Loss: 0.3441 - Accuracy: 0.9524 - F1: 0.9523
sub_9:Test (Best Model) - Loss: 0.0113 - Accuracy: 1.0000 - F1: 1.0000
sub_11:Test (Best Model) - Loss: 0.2818 - Accuracy: 0.9524 - F1: 0.9523
sub_8:Test (Best Model) - Loss: 0.0184 - Accuracy: 0.9881 - F1: 0.9881
sub_6:Test (Best Model) - Loss: 0.4689 - Accuracy: 0.9286 - F1: 0.9282
sub_5:Test (Best Model) - Loss: 0.9939 - Accuracy: 0.8333 - F1: 0.8333
sub_10:Test (Best Model) - Loss: 0.6451 - Accuracy: 0.9286 - F1: 0.9285
sub_12:Test (Best Model) - Loss: 0.0918 - Accuracy: 0.9881 - F1: 0.9881
sub_7:Test (Best Model) - Loss: 1.8312 - Accuracy: 0.7262 - F1: 0.7040
sub_4:Test (Best Model) - Loss: 0.7196 - Accuracy: 0.9167 - F1: 0.9161
sub_3:Test (Best Model) - Loss: 1.1179 - Accuracy: 0.8571 - F1: 0.8542
sub_2:Test (Best Model) - Loss: 0.1282 - Accuracy: 0.9881 - F1: 0.9881
sub_13:Test (Best Model) - Loss: 0.3323 - Accuracy: 0.9405 - F1: 0.9403
sub_11:Test (Best Model) - Loss: 0.6580 - Accuracy: 0.9167 - F1: 0.9161
sub_1:Test (Best Model) - Loss: 1.3815 - Accuracy: 0.7857 - F1: 0.7754
sub_9:Test (Best Model) - Loss: 0.0097 - Accuracy: 1.0000 - F1: 1.0000
sub_8:Test (Best Model) - Loss: 0.2886 - Accuracy: 0.9524 - F1: 0.9524
sub_12:Test (Best Model) - Loss: 0.0322 - Accuracy: 0.9881 - F1: 0.9881
sub_10:Test (Best Model) - Loss: 0.6300 - Accuracy: 0.9167 - F1: 0.9166
sub_6:Test (Best Model) - Loss: 0.3561 - Accuracy: 0.9405 - F1: 0.9405
sub_14:Test (Best Model) - Loss: 0.5792 - Accuracy: 0.9167 - F1: 0.9161
sub_7:Test (Best Model) - Loss: 0.1691 - Accuracy: 0.9524 - F1: 0.9524
sub_2:Test (Best Model) - Loss: 0.0754 - Accuracy: 0.9762 - F1: 0.9762
sub_5:Test (Best Model) - Loss: 0.9914 - Accuracy: 0.8571 - F1: 0.8571
sub_4:Test (Best Model) - Loss: 0.4199 - Accuracy: 0.9405 - F1: 0.9404
sub_11:Test (Best Model) - Loss: 1.0602 - Accuracy: 0.8690 - F1: 0.8668
sub_3:Test (Best Model) - Loss: 1.7890 - Accuracy: 0.7857 - F1: 0.7754
sub_9:Test (Best Model) - Loss: 0.0015 - Accuracy: 1.0000 - F1: 1.0000
sub_8:Test (Best Model) - Loss: 0.0212 - Accuracy: 0.9881 - F1: 0.9881
sub_13:Test (Best Model) - Loss: 0.2041 - Accuracy: 0.9524 - F1: 0.9524
sub_12:Test (Best Model) - Loss: 0.1010 - Accuracy: 0.9881 - F1: 0.9881
sub_1:Test (Best Model) - Loss: 0.6043 - Accuracy: 0.8810 - F1: 0.8792
sub_6:Test (Best Model) - Loss: 0.3791 - Accuracy: 0.9286 - F1: 0.9284
sub_7:Test (Best Model) - Loss: 0.8148 - Accuracy: 0.8929 - F1: 0.8921
sub_2:Test (Best Model) - Loss: 0.1427 - Accuracy: 0.9881 - F1: 0.9881
sub_10:Test (Best Model) - Loss: 0.9278 - Accuracy: 0.9048 - F1: 0.9045
sub_5:Test (Best Model) - Loss: 0.6849 - Accuracy: 0.9048 - F1: 0.9043
sub_14:Test (Best Model) - Loss: 0.9454 - Accuracy: 0.8929 - F1: 0.8925
sub_11:Test (Best Model) - Loss: 0.6811 - Accuracy: 0.9048 - F1: 0.9039
sub_4:Test (Best Model) - Loss: 0.4988 - Accuracy: 0.9405 - F1: 0.9403
sub_8:Test (Best Model) - Loss: 0.1310 - Accuracy: 0.9762 - F1: 0.9762
sub_12:Test (Best Model) - Loss: 0.0811 - Accuracy: 0.9881 - F1: 0.9881
sub_1:Test (Best Model) - Loss: 0.2788 - Accuracy: 0.9762 - F1: 0.9762
sub_6:Test (Best Model) - Loss: 0.1397 - Accuracy: 0.9643 - F1: 0.9643
sub_9:Test (Best Model) - Loss: 0.0000 - Accuracy: 1.0000 - F1: 1.0000
sub_3:Test (Best Model) - Loss: 1.1971 - Accuracy: 0.8571 - F1: 0.8542
sub_13:Test (Best Model) - Loss: 0.2828 - Accuracy: 0.9405 - F1: 0.9403
sub_11:Test (Best Model) - Loss: 0.6204 - Accuracy: 0.9167 - F1: 0.9161
sub_2:Test (Best Model) - Loss: 0.1781 - Accuracy: 0.9524 - F1: 0.9523
sub_14:Test (Best Model) - Loss: 0.2781 - Accuracy: 0.9286 - F1: 0.9286
sub_7:Test (Best Model) - Loss: 0.4131 - Accuracy: 0.9167 - F1: 0.9164
sub_12:Test (Best Model) - Loss: 0.4551 - Accuracy: 0.9167 - F1: 0.9161
sub_8:Test (Best Model) - Loss: 0.2343 - Accuracy: 0.9643 - F1: 0.9642
sub_5:Test (Best Model) - Loss: 1.2991 - Accuracy: 0.8095 - F1: 0.8078
sub_6:Test (Best Model) - Loss: 0.2297 - Accuracy: 0.9405 - F1: 0.9404
sub_4:Test (Best Model) - Loss: 0.6712 - Accuracy: 0.8929 - F1: 0.8925
sub_13:Test (Best Model) - Loss: 0.6019 - Accuracy: 0.9048 - F1: 0.9043
sub_9:Test (Best Model) - Loss: 0.0007 - Accuracy: 1.0000 - F1: 1.0000
sub_10:Test (Best Model) - Loss: 0.5856 - Accuracy: 0.9405 - F1: 0.9405
sub_11:Test (Best Model) - Loss: 0.5871 - Accuracy: 0.9405 - F1: 0.9403
sub_2:Test (Best Model) - Loss: 0.2042 - Accuracy: 0.9643 - F1: 0.9642
sub_1:Test (Best Model) - Loss: 0.5742 - Accuracy: 0.9048 - F1: 0.9043
sub_3:Test (Best Model) - Loss: 1.1647 - Accuracy: 0.8333 - F1: 0.8286
sub_12:Test (Best Model) - Loss: 0.6725 - Accuracy: 0.9048 - F1: 0.9047
sub_7:Test (Best Model) - Loss: 1.8588 - Accuracy: 0.7381 - F1: 0.7188
sub_14:Test (Best Model) - Loss: 0.1215 - Accuracy: 0.9762 - F1: 0.9762
sub_5:Test (Best Model) - Loss: 1.1280 - Accuracy: 0.8690 - F1: 0.8668
sub_6:Test (Best Model) - Loss: 0.7809 - Accuracy: 0.8929 - F1: 0.8916
sub_8:Test (Best Model) - Loss: 0.1320 - Accuracy: 0.9881 - F1: 0.9881
sub_10:Test (Best Model) - Loss: 0.7184 - Accuracy: 0.8452 - F1: 0.8434
sub_11:Test (Best Model) - Loss: 0.5736 - Accuracy: 0.9405 - F1: 0.9403
sub_13:Test (Best Model) - Loss: 0.0524 - Accuracy: 0.9881 - F1: 0.9881
sub_9:Test (Best Model) - Loss: 1.1461 - Accuracy: 0.8095 - F1: 0.8094
sub_1:Test (Best Model) - Loss: 0.3877 - Accuracy: 0.9405 - F1: 0.9403
sub_12:Test (Best Model) - Loss: 0.5175 - Accuracy: 0.9286 - F1: 0.9282
sub_4:Test (Best Model) - Loss: 0.7457 - Accuracy: 0.8929 - F1: 0.8925
sub_2:Test (Best Model) - Loss: 0.1591 - Accuracy: 0.9762 - F1: 0.9762
sub_6:Test (Best Model) - Loss: 1.1385 - Accuracy: 0.8452 - F1: 0.8414
sub_3:Test (Best Model) - Loss: 2.9473 - Accuracy: 0.7143 - F1: 0.6889
sub_8:Test (Best Model) - Loss: 0.0145 - Accuracy: 0.9881 - F1: 0.9881
sub_5:Test (Best Model) - Loss: 0.0514 - Accuracy: 0.9881 - F1: 0.9881
sub_14:Test (Best Model) - Loss: 0.1513 - Accuracy: 0.9881 - F1: 0.9881
sub_13:Test (Best Model) - Loss: 0.0106 - Accuracy: 0.9881 - F1: 0.9881
sub_7:Test (Best Model) - Loss: 0.0053 - Accuracy: 1.0000 - F1: 1.0000
sub_10:Test (Best Model) - Loss: 0.3921 - Accuracy: 0.9405 - F1: 0.9404
sub_11:Test (Best Model) - Loss: 0.5670 - Accuracy: 0.9405 - F1: 0.9403
sub_9:Test (Best Model) - Loss: 0.8549 - Accuracy: 0.8690 - F1: 0.8689
sub_12:Test (Best Model) - Loss: 0.8886 - Accuracy: 0.8810 - F1: 0.8803
sub_8:Test (Best Model) - Loss: 0.2496 - Accuracy: 0.9762 - F1: 0.9762
sub_4:Test (Best Model) - Loss: 1.4255 - Accuracy: 0.8333 - F1: 0.8332
sub_1:Test (Best Model) - Loss: 0.3270 - Accuracy: 0.9524 - F1: 0.9523
sub_13:Test (Best Model) - Loss: 0.0935 - Accuracy: 0.9762 - F1: 0.9762
sub_5:Test (Best Model) - Loss: 0.0104 - Accuracy: 1.0000 - F1: 1.0000
sub_3:Test (Best Model) - Loss: 0.3136 - Accuracy: 0.9405 - F1: 0.9404
sub_6:Test (Best Model) - Loss: 1.0409 - Accuracy: 0.8690 - F1: 0.8668
sub_2:Test (Best Model) - Loss: 0.2666 - Accuracy: 0.9643 - F1: 0.9642
sub_11:Test (Best Model) - Loss: 0.7327 - Accuracy: 0.9286 - F1: 0.9282
sub_10:Test (Best Model) - Loss: 0.2853 - Accuracy: 0.9643 - F1: 0.9643
sub_8:Test (Best Model) - Loss: 0.0004 - Accuracy: 1.0000 - F1: 1.0000
sub_9:Test (Best Model) - Loss: 0.4542 - Accuracy: 0.8690 - F1: 0.8690
sub_14:Test (Best Model) - Loss: 0.0000 - Accuracy: 1.0000 - F1: 1.0000
sub_7:Test (Best Model) - Loss: 0.4942 - Accuracy: 0.9286 - F1: 0.9284
sub_5:Test (Best Model) - Loss: 0.1449 - Accuracy: 0.9643 - F1: 0.9643
sub_2:Test (Best Model) - Loss: 0.3778 - Accuracy: 0.9167 - F1: 0.9161
sub_13:Test (Best Model) - Loss: 0.1027 - Accuracy: 0.9881 - F1: 0.9881
sub_4:Test (Best Model) - Loss: 0.7613 - Accuracy: 0.8929 - F1: 0.8927
sub_12:Test (Best Model) - Loss: 0.6392 - Accuracy: 0.9167 - F1: 0.9164
sub_11:Test (Best Model) - Loss: 0.6075 - Accuracy: 0.9286 - F1: 0.9282
sub_1:Test (Best Model) - Loss: 0.3041 - Accuracy: 0.9524 - F1: 0.9523
sub_10:Test (Best Model) - Loss: 0.1356 - Accuracy: 0.9643 - F1: 0.9643
sub_9:Test (Best Model) - Loss: 0.5506 - Accuracy: 0.8690 - F1: 0.8686
sub_6:Test (Best Model) - Loss: 1.2843 - Accuracy: 0.8810 - F1: 0.8792
sub_8:Test (Best Model) - Loss: 0.0000 - Accuracy: 1.0000 - F1: 1.0000
sub_14:Test (Best Model) - Loss: 0.2065 - Accuracy: 0.9762 - F1: 0.9762
sub_3:Test (Best Model) - Loss: 0.1712 - Accuracy: 0.9643 - F1: 0.9642
sub_7:Test (Best Model) - Loss: 0.2727 - Accuracy: 0.9524 - F1: 0.9524
sub_13:Test (Best Model) - Loss: 0.0183 - Accuracy: 0.9881 - F1: 0.9881
sub_4:Test (Best Model) - Loss: 0.7815 - Accuracy: 0.8810 - F1: 0.8810
sub_1:Test (Best Model) - Loss: 0.4438 - Accuracy: 0.9405 - F1: 0.9404
sub_5:Test (Best Model) - Loss: 0.1034 - Accuracy: 0.9762 - F1: 0.9762
sub_9:Test (Best Model) - Loss: 0.7654 - Accuracy: 0.8571 - F1: 0.8571
sub_10:Test (Best Model) - Loss: 0.3348 - Accuracy: 0.9405 - F1: 0.9405
sub_8:Test (Best Model) - Loss: 0.0003 - Accuracy: 1.0000 - F1: 1.0000
sub_6:Test (Best Model) - Loss: 0.3166 - Accuracy: 0.9048 - F1: 0.9039
sub_11:Test (Best Model) - Loss: 0.0964 - Accuracy: 0.9881 - F1: 0.9881
sub_2:Test (Best Model) - Loss: 0.1801 - Accuracy: 0.9762 - F1: 0.9762
sub_14:Test (Best Model) - Loss: 0.0945 - Accuracy: 0.9881 - F1: 0.9881
sub_12:Test (Best Model) - Loss: 0.6435 - Accuracy: 0.8929 - F1: 0.8916
sub_13:Test (Best Model) - Loss: 0.2506 - Accuracy: 0.9405 - F1: 0.9403
sub_4:Test (Best Model) - Loss: 0.7786 - Accuracy: 0.8929 - F1: 0.8928
sub_1:Test (Best Model) - Loss: 0.3333 - Accuracy: 0.9524 - F1: 0.9523
sub_9:Test (Best Model) - Loss: 1.0798 - Accuracy: 0.8452 - F1: 0.8434
sub_7:Test (Best Model) - Loss: 0.5517 - Accuracy: 0.9405 - F1: 0.9404
sub_11:Test (Best Model) - Loss: 0.1593 - Accuracy: 0.9762 - F1: 0.9762
sub_5:Test (Best Model) - Loss: 0.4138 - Accuracy: 0.9048 - F1: 0.9039
sub_3:Test (Best Model) - Loss: 0.6460 - Accuracy: 0.8810 - F1: 0.8792
sub_8:Test (Best Model) - Loss: 0.1858 - Accuracy: 0.9643 - F1: 0.9642
sub_14:Test (Best Model) - Loss: 0.1363 - Accuracy: 0.9762 - F1: 0.9762
sub_2:Test (Best Model) - Loss: 0.0726 - Accuracy: 0.9762 - F1: 0.9762
sub_10:Test (Best Model) - Loss: 0.3061 - Accuracy: 0.9524 - F1: 0.9524
sub_13:Test (Best Model) - Loss: 0.1297 - Accuracy: 0.9643 - F1: 0.9642
sub_12:Test (Best Model) - Loss: 1.1078 - Accuracy: 0.8929 - F1: 0.8925
sub_6:Test (Best Model) - Loss: 0.0294 - Accuracy: 0.9881 - F1: 0.9881
sub_9:Test (Best Model) - Loss: 0.7742 - Accuracy: 0.8810 - F1: 0.8792
sub_3:Test (Best Model) - Loss: 0.0803 - Accuracy: 0.9643 - F1: 0.9643
sub_5:Test (Best Model) - Loss: 0.6935 - Accuracy: 0.8690 - F1: 0.8690
sub_1:Test (Best Model) - Loss: 0.0496 - Accuracy: 0.9762 - F1: 0.9762
sub_8:Test (Best Model) - Loss: 0.1677 - Accuracy: 0.9524 - F1: 0.9523
sub_2:Test (Best Model) - Loss: 0.3584 - Accuracy: 0.9286 - F1: 0.9285
sub_14:Test (Best Model) - Loss: 2.1233 - Accuracy: 0.7024 - F1: 0.6735
sub_7:Test (Best Model) - Loss: 0.1313 - Accuracy: 0.9762 - F1: 0.9762
sub_11:Test (Best Model) - Loss: 0.2219 - Accuracy: 0.9643 - F1: 0.9643
sub_13:Test (Best Model) - Loss: 0.0526 - Accuracy: 0.9643 - F1: 0.9642
sub_12:Test (Best Model) - Loss: 0.6808 - Accuracy: 0.9048 - F1: 0.9045
sub_10:Test (Best Model) - Loss: 1.5567 - Accuracy: 0.7500 - F1: 0.7365
sub_4:Test (Best Model) - Loss: 1.2654 - Accuracy: 0.8810 - F1: 0.8803
sub_3:Test (Best Model) - Loss: 0.1593 - Accuracy: 0.9524 - F1: 0.9524
sub_9:Test (Best Model) - Loss: 0.7319 - Accuracy: 0.9167 - F1: 0.9161
sub_8:Test (Best Model) - Loss: 0.0982 - Accuracy: 0.9881 - F1: 0.9881
sub_1:Test (Best Model) - Loss: 0.2500 - Accuracy: 0.9643 - F1: 0.9642
sub_5:Test (Best Model) - Loss: 0.9490 - Accuracy: 0.8929 - F1: 0.8928
sub_6:Test (Best Model) - Loss: 0.0599 - Accuracy: 0.9762 - F1: 0.9762
sub_2:Test (Best Model) - Loss: 0.3247 - Accuracy: 0.9405 - F1: 0.9404
sub_11:Test (Best Model) - Loss: 0.0927 - Accuracy: 0.9881 - F1: 0.9881
sub_10:Test (Best Model) - Loss: 0.6528 - Accuracy: 0.8333 - F1: 0.8330
sub_14:Test (Best Model) - Loss: 2.3350 - Accuracy: 0.7500 - F1: 0.7333
sub_12:Test (Best Model) - Loss: 1.0932 - Accuracy: 0.8690 - F1: 0.8686
sub_3:Test (Best Model) - Loss: 1.8998 - Accuracy: 0.7262 - F1: 0.7040
sub_13:Test (Best Model) - Loss: 0.0894 - Accuracy: 0.9643 - F1: 0.9642
sub_9:Test (Best Model) - Loss: 0.8470 - Accuracy: 0.8571 - F1: 0.8542
sub_8:Test (Best Model) - Loss: 0.0346 - Accuracy: 0.9881 - F1: 0.9881
sub_7:Test (Best Model) - Loss: 0.8885 - Accuracy: 0.8571 - F1: 0.8558
sub_2:Test (Best Model) - Loss: 0.2153 - Accuracy: 0.9405 - F1: 0.9403
sub_1:Test (Best Model) - Loss: 0.1349 - Accuracy: 0.9643 - F1: 0.9643
sub_4:Test (Best Model) - Loss: 1.8782 - Accuracy: 0.7738 - F1: 0.7616
sub_11:Test (Best Model) - Loss: 0.0364 - Accuracy: 0.9881 - F1: 0.9881
sub_13:Test (Best Model) - Loss: 0.0856 - Accuracy: 0.9762 - F1: 0.9762
sub_12:Test (Best Model) - Loss: 1.0669 - Accuracy: 0.9048 - F1: 0.9043
sub_9:Test (Best Model) - Loss: 0.2285 - Accuracy: 0.9405 - F1: 0.9403
sub_5:Test (Best Model) - Loss: 0.3111 - Accuracy: 0.9643 - F1: 0.9642
sub_6:Test (Best Model) - Loss: 0.0887 - Accuracy: 0.9762 - F1: 0.9762
sub_2:Test (Best Model) - Loss: 0.1465 - Accuracy: 0.9643 - F1: 0.9643
sub_10:Test (Best Model) - Loss: 0.3293 - Accuracy: 0.9286 - F1: 0.9284
sub_3:Test (Best Model) - Loss: 1.4743 - Accuracy: 0.7976 - F1: 0.7890
sub_14:Test (Best Model) - Loss: 1.4281 - Accuracy: 0.8095 - F1: 0.8024
sub_7:Test (Best Model) - Loss: 0.5391 - Accuracy: 0.8929 - F1: 0.8916
sub_12:Test (Best Model) - Loss: 1.1928 - Accuracy: 0.8810 - F1: 0.8803
sub_1:Test (Best Model) - Loss: 0.1747 - Accuracy: 0.9643 - F1: 0.9642
sub_10:Test (Best Model) - Loss: 0.6036 - Accuracy: 0.8690 - F1: 0.8681
sub_6:Test (Best Model) - Loss: 0.0618 - Accuracy: 0.9881 - F1: 0.9881
sub_14:Test (Best Model) - Loss: 1.4900 - Accuracy: 0.7619 - F1: 0.7476
sub_4:Test (Best Model) - Loss: 1.4671 - Accuracy: 0.8333 - F1: 0.8286
sub_5:Test (Best Model) - Loss: 0.6921 - Accuracy: 0.8929 - F1: 0.8925
sub_3:Test (Best Model) - Loss: 1.7072 - Accuracy: 0.7381 - F1: 0.7188
sub_1:Test (Best Model) - Loss: 0.4606 - Accuracy: 0.9405 - F1: 0.9403
sub_10:Test (Best Model) - Loss: 0.3941 - Accuracy: 0.8571 - F1: 0.8568
sub_6:Test (Best Model) - Loss: 0.0066 - Accuracy: 1.0000 - F1: 1.0000
sub_7:Test (Best Model) - Loss: 0.9648 - Accuracy: 0.8571 - F1: 0.8542
sub_14:Test (Best Model) - Loss: 1.1123 - Accuracy: 0.8810 - F1: 0.8792
sub_4:Test (Best Model) - Loss: 1.4389 - Accuracy: 0.8214 - F1: 0.8155
sub_5:Test (Best Model) - Loss: 0.4905 - Accuracy: 0.9167 - F1: 0.9161
sub_3:Test (Best Model) - Loss: 1.7273 - Accuracy: 0.7857 - F1: 0.7754
sub_7:Test (Best Model) - Loss: 0.2168 - Accuracy: 0.9405 - F1: 0.9403
sub_3:Test (Best Model) - Loss: 0.9739 - Accuracy: 0.8333 - F1: 0.8286
sub_4:Test (Best Model) - Loss: 1.6476 - Accuracy: 0.8214 - F1: 0.8155
sub_7:Test (Best Model) - Loss: 0.1152 - Accuracy: 0.9643 - F1: 0.9643
sub_4:Test (Best Model) - Loss: 1.2458 - Accuracy: 0.8810 - F1: 0.8792

=== Summary Results ===

acc: 92.04 ± 3.57
F1: 91.88 ± 3.74
acc-in: 98.13 ± 0.80
F1-in: 98.12 ± 0.81
