lr: 0.001
sub_8:Test (Best Model) - Loss: 0.6221 - Accuracy: 0.9405 - F1: 0.9405
sub_7:Test (Best Model) - Loss: 2.0778 - Accuracy: 0.8095 - F1: 0.8024
sub_14:Test (Best Model) - Loss: 1.1266 - Accuracy: 0.5952 - F1: 0.5654
sub_11:Test (Best Model) - Loss: 0.5456 - Accuracy: 0.9524 - F1: 0.9524
sub_2:Test (Best Model) - Loss: 0.2272 - Accuracy: 0.9643 - F1: 0.9642
sub_3:Test (Best Model) - Loss: 1.4614 - Accuracy: 0.5833 - F1: 0.4958
sub_9:Test (Best Model) - Loss: 0.3565 - Accuracy: 0.9643 - F1: 0.9643
sub_5:Test (Best Model) - Loss: 1.6372 - Accuracy: 0.8452 - F1: 0.8434
sub_6:Test (Best Model) - Loss: 1.0319 - Accuracy: 0.8810 - F1: 0.8792
sub_10:Test (Best Model) - Loss: 0.8808 - Accuracy: 0.8929 - F1: 0.8925
sub_13:Test (Best Model) - Loss: 0.3216 - Accuracy: 0.9167 - F1: 0.9164
sub_4:Test (Best Model) - Loss: 0.5885 - Accuracy: 0.7976 - F1: 0.7910
sub_12:Test (Best Model) - Loss: 0.0662 - Accuracy: 0.9881 - F1: 0.9881
sub_8:Test (Best Model) - Loss: 0.7921 - Accuracy: 0.9286 - F1: 0.9285
sub_14:Test (Best Model) - Loss: 1.2387 - Accuracy: 0.7976 - F1: 0.7969
sub_11:Test (Best Model) - Loss: 1.9822 - Accuracy: 0.8095 - F1: 0.8024
sub_9:Test (Best Model) - Loss: 1.0699 - Accuracy: 0.8452 - F1: 0.8425
sub_7:Test (Best Model) - Loss: 0.8606 - Accuracy: 0.7976 - F1: 0.7910
sub_3:Test (Best Model) - Loss: 0.5795 - Accuracy: 0.6667 - F1: 0.6250
sub_2:Test (Best Model) - Loss: 0.3101 - Accuracy: 0.9762 - F1: 0.9762
sub_6:Test (Best Model) - Loss: 0.7526 - Accuracy: 0.8929 - F1: 0.8916
sub_1:Test (Best Model) - Loss: 0.6552 - Accuracy: 0.9167 - F1: 0.9166
sub_13:Test (Best Model) - Loss: 0.3093 - Accuracy: 0.9524 - F1: 0.9523
sub_5:Test (Best Model) - Loss: 0.7733 - Accuracy: 0.7976 - F1: 0.7974
sub_12:Test (Best Model) - Loss: 1.0839 - Accuracy: 0.8095 - F1: 0.8041
sub_8:Test (Best Model) - Loss: 0.1738 - Accuracy: 0.9881 - F1: 0.9881
sub_14:Test (Best Model) - Loss: 1.1710 - Accuracy: 0.8690 - F1: 0.8690
sub_11:Test (Best Model) - Loss: 0.8446 - Accuracy: 0.8929 - F1: 0.8916
sub_9:Test (Best Model) - Loss: 0.5223 - Accuracy: 0.9643 - F1: 0.9643
sub_2:Test (Best Model) - Loss: 0.1341 - Accuracy: 0.9762 - F1: 0.9762
sub_3:Test (Best Model) - Loss: 1.7382 - Accuracy: 0.8452 - F1: 0.8425
sub_6:Test (Best Model) - Loss: 2.1822 - Accuracy: 0.7976 - F1: 0.7890
sub_10:Test (Best Model) - Loss: 0.7717 - Accuracy: 0.8929 - F1: 0.8925
sub_4:Test (Best Model) - Loss: 1.1207 - Accuracy: 0.9167 - F1: 0.9161
sub_1:Test (Best Model) - Loss: 0.7096 - Accuracy: 0.8929 - F1: 0.8916
sub_7:Test (Best Model) - Loss: 1.3163 - Accuracy: 0.8571 - F1: 0.8551
sub_13:Test (Best Model) - Loss: 0.5027 - Accuracy: 0.9524 - F1: 0.9524
sub_5:Test (Best Model) - Loss: 1.3455 - Accuracy: 0.8095 - F1: 0.8091
sub_8:Test (Best Model) - Loss: 0.6756 - Accuracy: 0.9286 - F1: 0.9285
sub_14:Test (Best Model) - Loss: 1.4316 - Accuracy: 0.8333 - F1: 0.8333
sub_11:Test (Best Model) - Loss: 0.7465 - Accuracy: 0.9167 - F1: 0.9161
sub_9:Test (Best Model) - Loss: 0.7243 - Accuracy: 0.9286 - F1: 0.9284
sub_2:Test (Best Model) - Loss: 0.4470 - Accuracy: 0.9405 - F1: 0.9404
sub_3:Test (Best Model) - Loss: 0.6211 - Accuracy: 0.7976 - F1: 0.7927
sub_1:Test (Best Model) - Loss: 0.5719 - Accuracy: 0.9167 - F1: 0.9166
sub_10:Test (Best Model) - Loss: 0.9342 - Accuracy: 0.9167 - F1: 0.9166
sub_12:Test (Best Model) - Loss: 0.4688 - Accuracy: 0.8929 - F1: 0.8927
sub_7:Test (Best Model) - Loss: 0.4836 - Accuracy: 0.8333 - F1: 0.8299
sub_13:Test (Best Model) - Loss: 0.7605 - Accuracy: 0.9286 - F1: 0.9286
sub_5:Test (Best Model) - Loss: 0.9990 - Accuracy: 0.8095 - F1: 0.8085
sub_8:Test (Best Model) - Loss: 0.3068 - Accuracy: 0.9762 - F1: 0.9762
sub_14:Test (Best Model) - Loss: 1.2449 - Accuracy: 0.8690 - F1: 0.8690
sub_6:Test (Best Model) - Loss: 0.2976 - Accuracy: 0.9405 - F1: 0.9403
sub_4:Test (Best Model) - Loss: 0.3791 - Accuracy: 0.9524 - F1: 0.9523
sub_9:Test (Best Model) - Loss: 1.1809 - Accuracy: 0.8452 - F1: 0.8414
sub_11:Test (Best Model) - Loss: 0.7989 - Accuracy: 0.9167 - F1: 0.9167
sub_2:Test (Best Model) - Loss: 1.4746 - Accuracy: 0.7976 - F1: 0.7927
sub_3:Test (Best Model) - Loss: 1.0315 - Accuracy: 0.8571 - F1: 0.8542
sub_10:Test (Best Model) - Loss: 1.0806 - Accuracy: 0.8095 - F1: 0.8056
sub_12:Test (Best Model) - Loss: 0.7972 - Accuracy: 0.9048 - F1: 0.9047
sub_13:Test (Best Model) - Loss: 1.7625 - Accuracy: 0.8810 - F1: 0.8792
sub_7:Test (Best Model) - Loss: 2.3961 - Accuracy: 0.8095 - F1: 0.8024
sub_8:Test (Best Model) - Loss: 0.3356 - Accuracy: 0.9524 - F1: 0.9523
sub_1:Test (Best Model) - Loss: 0.8535 - Accuracy: 0.8095 - F1: 0.8056
sub_6:Test (Best Model) - Loss: 0.3594 - Accuracy: 0.9286 - F1: 0.9284
sub_9:Test (Best Model) - Loss: 3.9187 - Accuracy: 0.7381 - F1: 0.7381
sub_11:Test (Best Model) - Loss: 0.3261 - Accuracy: 0.9643 - F1: 0.9642
sub_2:Test (Best Model) - Loss: 0.1783 - Accuracy: 0.9762 - F1: 0.9762
sub_5:Test (Best Model) - Loss: 1.0167 - Accuracy: 0.8929 - F1: 0.8928
sub_3:Test (Best Model) - Loss: 0.4851 - Accuracy: 0.8452 - F1: 0.8434
sub_4:Test (Best Model) - Loss: 0.6898 - Accuracy: 0.9048 - F1: 0.9039
sub_14:Test (Best Model) - Loss: 0.3091 - Accuracy: 0.9405 - F1: 0.9403
sub_13:Test (Best Model) - Loss: 0.4369 - Accuracy: 0.9643 - F1: 0.9643
sub_8:Test (Best Model) - Loss: 0.2852 - Accuracy: 0.9643 - F1: 0.9642
sub_1:Test (Best Model) - Loss: 0.5978 - Accuracy: 0.9286 - F1: 0.9282
sub_7:Test (Best Model) - Loss: 0.4647 - Accuracy: 0.8452 - F1: 0.8447
sub_10:Test (Best Model) - Loss: 2.4455 - Accuracy: 0.7976 - F1: 0.7927
sub_11:Test (Best Model) - Loss: 0.4520 - Accuracy: 0.9524 - F1: 0.9523
sub_2:Test (Best Model) - Loss: 0.2114 - Accuracy: 0.9762 - F1: 0.9762
sub_12:Test (Best Model) - Loss: 1.5625 - Accuracy: 0.8333 - F1: 0.8286
sub_9:Test (Best Model) - Loss: 2.3106 - Accuracy: 0.7619 - F1: 0.7618
sub_5:Test (Best Model) - Loss: 0.4279 - Accuracy: 0.8214 - F1: 0.8170
sub_8:Test (Best Model) - Loss: 0.3504 - Accuracy: 0.9643 - F1: 0.9642
sub_6:Test (Best Model) - Loss: 1.6273 - Accuracy: 0.8452 - F1: 0.8414
sub_1:Test (Best Model) - Loss: 0.8693 - Accuracy: 0.8690 - F1: 0.8675
sub_10:Test (Best Model) - Loss: 0.3311 - Accuracy: 0.9643 - F1: 0.9642
sub_3:Test (Best Model) - Loss: 0.5261 - Accuracy: 0.9524 - F1: 0.9524
sub_11:Test (Best Model) - Loss: 1.1592 - Accuracy: 0.8929 - F1: 0.8916
sub_13:Test (Best Model) - Loss: 0.3349 - Accuracy: 0.9762 - F1: 0.9762
sub_12:Test (Best Model) - Loss: 0.6495 - Accuracy: 0.8810 - F1: 0.8809
sub_9:Test (Best Model) - Loss: 1.7700 - Accuracy: 0.8571 - F1: 0.8542
sub_4:Test (Best Model) - Loss: 1.0574 - Accuracy: 0.9048 - F1: 0.9043
sub_5:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.6429 - F1: 0.5982
sub_14:Test (Best Model) - Loss: 0.2474 - Accuracy: 0.9762 - F1: 0.9762
sub_8:Test (Best Model) - Loss: 0.0002 - Accuracy: 1.0000 - F1: 1.0000
sub_2:Test (Best Model) - Loss: 0.8210 - Accuracy: 0.9405 - F1: 0.9403
sub_10:Test (Best Model) - Loss: 0.3152 - Accuracy: 0.9524 - F1: 0.9524
sub_11:Test (Best Model) - Loss: 0.3256 - Accuracy: 0.9405 - F1: 0.9403
sub_7:Test (Best Model) - Loss: 0.0941 - Accuracy: 0.9881 - F1: 0.9881
sub_13:Test (Best Model) - Loss: 1.0007 - Accuracy: 0.9167 - F1: 0.9164
sub_4:Test (Best Model) - Loss: 1.2571 - Accuracy: 0.8452 - F1: 0.8425
sub_9:Test (Best Model) - Loss: 2.2729 - Accuracy: 0.8095 - F1: 0.8094
sub_6:Test (Best Model) - Loss: 1.5992 - Accuracy: 0.8571 - F1: 0.8542
sub_12:Test (Best Model) - Loss: 0.2892 - Accuracy: 0.9286 - F1: 0.9286
sub_1:Test (Best Model) - Loss: 0.6226 - Accuracy: 0.9048 - F1: 0.9039
sub_3:Test (Best Model) - Loss: 0.6440 - Accuracy: 0.8571 - F1: 0.8551
sub_8:Test (Best Model) - Loss: 0.4638 - Accuracy: 0.9643 - F1: 0.9642
sub_2:Test (Best Model) - Loss: 0.4625 - Accuracy: 0.9643 - F1: 0.9642
sub_10:Test (Best Model) - Loss: 0.2683 - Accuracy: 0.9643 - F1: 0.9643
sub_11:Test (Best Model) - Loss: 0.5620 - Accuracy: 0.9643 - F1: 0.9642
sub_14:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.9405 - F1: 0.9403
sub_13:Test (Best Model) - Loss: 0.5061 - Accuracy: 0.9524 - F1: 0.9524
sub_4:Test (Best Model) - Loss: 0.8439 - Accuracy: 0.8452 - F1: 0.8450
sub_12:Test (Best Model) - Loss: 0.3313 - Accuracy: 0.9405 - F1: 0.9403
sub_9:Test (Best Model) - Loss: 2.4684 - Accuracy: 0.8333 - F1: 0.8299
sub_6:Test (Best Model) - Loss: 0.9738 - Accuracy: 0.8929 - F1: 0.8916
sub_1:Test (Best Model) - Loss: 0.6533 - Accuracy: 0.9167 - F1: 0.9161
sub_5:Test (Best Model) - Loss: 0.1735 - Accuracy: 0.9762 - F1: 0.9762
sub_8:Test (Best Model) - Loss: 0.5889 - Accuracy: 0.9643 - F1: 0.9642
sub_3:Test (Best Model) - Loss: 0.2675 - Accuracy: 0.9643 - F1: 0.9643
sub_7:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.8810 - F1: 0.8799
sub_2:Test (Best Model) - Loss: 0.4513 - Accuracy: 0.9405 - F1: 0.9403
sub_11:Test (Best Model) - Loss: 0.3185 - Accuracy: 0.9762 - F1: 0.9762
sub_10:Test (Best Model) - Loss: 0.1151 - Accuracy: 0.9643 - F1: 0.9642
sub_12:Test (Best Model) - Loss: 2.4233 - Accuracy: 0.7857 - F1: 0.7857
sub_9:Test (Best Model) - Loss: 1.0661 - Accuracy: 0.8571 - F1: 0.8542
sub_6:Test (Best Model) - Loss: 0.3270 - Accuracy: 0.9405 - F1: 0.9403
sub_1:Test (Best Model) - Loss: 0.5162 - Accuracy: 0.8690 - F1: 0.8668
sub_5:Test (Best Model) - Loss: 0.3289 - Accuracy: 0.9286 - F1: 0.9284
sub_8:Test (Best Model) - Loss: 0.1961 - Accuracy: 0.9881 - F1: 0.9881
sub_3:Test (Best Model) - Loss: 0.2664 - Accuracy: 0.9524 - F1: 0.9523
sub_13:Test (Best Model) - Loss: 1.4234 - Accuracy: 0.8690 - F1: 0.8668
sub_4:Test (Best Model) - Loss: 0.4650 - Accuracy: 0.8452 - F1: 0.8442
sub_2:Test (Best Model) - Loss: 0.7172 - Accuracy: 0.9167 - F1: 0.9167
sub_14:Test (Best Model) - Loss: 0.3409 - Accuracy: 0.9762 - F1: 0.9762
sub_7:Test (Best Model) - Loss: 0.6528 - Accuracy: 0.6429 - F1: 0.6257
sub_11:Test (Best Model) - Loss: 0.2766 - Accuracy: 0.9762 - F1: 0.9762
sub_10:Test (Best Model) - Loss: 0.6732 - Accuracy: 0.9048 - F1: 0.9045
sub_12:Test (Best Model) - Loss: 1.6380 - Accuracy: 0.7619 - F1: 0.7529
sub_5:Test (Best Model) - Loss: 0.3594 - Accuracy: 0.9048 - F1: 0.9045
sub_1:Test (Best Model) - Loss: 0.4651 - Accuracy: 0.8571 - F1: 0.8542
sub_8:Test (Best Model) - Loss: 1.3040 - Accuracy: 0.9167 - F1: 0.9161
sub_3:Test (Best Model) - Loss: 0.6153 - Accuracy: 0.7262 - F1: 0.7040
sub_2:Test (Best Model) - Loss: 0.4582 - Accuracy: 0.9405 - F1: 0.9405
sub_13:Test (Best Model) - Loss: 0.6189 - Accuracy: 0.9048 - F1: 0.9039
sub_4:Test (Best Model) - Loss: 1.0001 - Accuracy: 0.8571 - F1: 0.8542
sub_9:Test (Best Model) - Loss: 1.2983 - Accuracy: 0.8810 - F1: 0.8792
sub_6:Test (Best Model) - Loss: 1.4282 - Accuracy: 0.8571 - F1: 0.8542
sub_11:Test (Best Model) - Loss: 0.0939 - Accuracy: 0.9881 - F1: 0.9881
sub_10:Test (Best Model) - Loss: 1.1107 - Accuracy: 0.8333 - F1: 0.8299
sub_14:Test (Best Model) - Loss: 0.9986 - Accuracy: 0.8571 - F1: 0.8542
sub_12:Test (Best Model) - Loss: 1.2396 - Accuracy: 0.9048 - F1: 0.9045
sub_1:Test (Best Model) - Loss: 0.1364 - Accuracy: 0.9762 - F1: 0.9762
sub_5:Test (Best Model) - Loss: 1.3785 - Accuracy: 0.6905 - F1: 0.6577
sub_8:Test (Best Model) - Loss: 0.0000 - Accuracy: 1.0000 - F1: 1.0000
sub_2:Test (Best Model) - Loss: 0.4926 - Accuracy: 0.9167 - F1: 0.9167
sub_7:Test (Best Model) - Loss: 0.2130 - Accuracy: 0.9762 - F1: 0.9762
sub_13:Test (Best Model) - Loss: 0.1093 - Accuracy: 0.9762 - F1: 0.9762
sub_4:Test (Best Model) - Loss: 1.2080 - Accuracy: 0.8214 - F1: 0.8212
sub_9:Test (Best Model) - Loss: 1.4160 - Accuracy: 0.7976 - F1: 0.7910
sub_6:Test (Best Model) - Loss: 0.9827 - Accuracy: 0.9286 - F1: 0.9286
sub_12:Test (Best Model) - Loss: 0.5124 - Accuracy: 0.9286 - F1: 0.9286
sub_3:Test (Best Model) - Loss: 2.6874 - Accuracy: 0.7976 - F1: 0.7927
sub_10:Test (Best Model) - Loss: 1.1392 - Accuracy: 0.8929 - F1: 0.8925
sub_8:Test (Best Model) - Loss: 0.8852 - Accuracy: 0.9643 - F1: 0.9642
sub_11:Test (Best Model) - Loss: 0.8728 - Accuracy: 0.9286 - F1: 0.9286
sub_4:Test (Best Model) - Loss: 1.0724 - Accuracy: 0.7381 - F1: 0.7188
sub_14:Test (Best Model) - Loss: 2.2903 - Accuracy: 0.7738 - F1: 0.7616
sub_1:Test (Best Model) - Loss: 0.9894 - Accuracy: 0.8452 - F1: 0.8414
sub_13:Test (Best Model) - Loss: 0.6343 - Accuracy: 0.6786 - F1: 0.6571
sub_9:Test (Best Model) - Loss: 1.8056 - Accuracy: 0.6310 - F1: 0.5810
sub_6:Test (Best Model) - Loss: 1.8164 - Accuracy: 0.7381 - F1: 0.7379
sub_12:Test (Best Model) - Loss: 1.2533 - Accuracy: 0.8810 - F1: 0.8803
sub_5:Test (Best Model) - Loss: 1.1241 - Accuracy: 0.8571 - F1: 0.8571
sub_3:Test (Best Model) - Loss: 1.2068 - Accuracy: 0.7619 - F1: 0.7569
sub_2:Test (Best Model) - Loss: 0.6084 - Accuracy: 0.9524 - F1: 0.9524
sub_10:Test (Best Model) - Loss: 2.5171 - Accuracy: 0.7500 - F1: 0.7393
sub_9:Test (Best Model) - Loss: 1.1688 - Accuracy: 0.7738 - F1: 0.7616
sub_1:Test (Best Model) - Loss: 1.6185 - Accuracy: 0.9048 - F1: 0.9039
sub_6:Test (Best Model) - Loss: 0.6009 - Accuracy: 0.8929 - F1: 0.8925
sub_11:Test (Best Model) - Loss: 0.4934 - Accuracy: 0.9524 - F1: 0.9524
sub_7:Test (Best Model) - Loss: 0.7097 - Accuracy: 0.8929 - F1: 0.8927
sub_5:Test (Best Model) - Loss: 0.8377 - Accuracy: 0.8690 - F1: 0.8686
sub_14:Test (Best Model) - Loss: 4.7614 - Accuracy: 0.6429 - F1: 0.5906
sub_4:Test (Best Model) - Loss: 0.6171 - Accuracy: 0.8452 - F1: 0.8450
sub_13:Test (Best Model) - Loss: 0.6011 - Accuracy: 0.9405 - F1: 0.9404
sub_12:Test (Best Model) - Loss: 1.0483 - Accuracy: 0.8929 - F1: 0.8921
sub_10:Test (Best Model) - Loss: 1.6246 - Accuracy: 0.7143 - F1: 0.6889
sub_3:Test (Best Model) - Loss: 2.0240 - Accuracy: 0.8214 - F1: 0.8183
sub_6:Test (Best Model) - Loss: 0.3954 - Accuracy: 0.9405 - F1: 0.9403
sub_1:Test (Best Model) - Loss: 0.9169 - Accuracy: 0.6786 - F1: 0.6763
sub_2:Test (Best Model) - Loss: 0.7373 - Accuracy: 0.6429 - F1: 0.6327
sub_7:Test (Best Model) - Loss: 0.5663 - Accuracy: 0.8810 - F1: 0.8799
sub_14:Test (Best Model) - Loss: 0.5845 - Accuracy: 0.8929 - F1: 0.8925
sub_5:Test (Best Model) - Loss: 0.7346 - Accuracy: 0.7143 - F1: 0.6932
sub_13:Test (Best Model) - Loss: 0.2971 - Accuracy: 0.9762 - F1: 0.9762
sub_4:Test (Best Model) - Loss: 0.6412 - Accuracy: 0.8929 - F1: 0.8921
sub_12:Test (Best Model) - Loss: 1.0445 - Accuracy: 0.9048 - F1: 0.9043
sub_6:Test (Best Model) - Loss: 0.7607 - Accuracy: 0.8690 - F1: 0.8681
sub_3:Test (Best Model) - Loss: 0.6344 - Accuracy: 0.7619 - F1: 0.7476
sub_1:Test (Best Model) - Loss: 0.5654 - Accuracy: 0.8929 - F1: 0.8916
sub_14:Test (Best Model) - Loss: 2.8189 - Accuracy: 0.7024 - F1: 0.6735
sub_7:Test (Best Model) - Loss: 0.6680 - Accuracy: 0.8452 - F1: 0.8434
sub_4:Test (Best Model) - Loss: 0.5086 - Accuracy: 0.8214 - F1: 0.8155
sub_10:Test (Best Model) - Loss: 0.7404 - Accuracy: 0.9048 - F1: 0.9043
sub_5:Test (Best Model) - Loss: 1.7279 - Accuracy: 0.7738 - F1: 0.7664
sub_14:Test (Best Model) - Loss: 3.0828 - Accuracy: 0.7738 - F1: 0.7664
sub_7:Test (Best Model) - Loss: 0.6208 - Accuracy: 0.8690 - F1: 0.8668
sub_4:Test (Best Model) - Loss: 1.1232 - Accuracy: 0.8333 - F1: 0.8286
sub_7:Test (Best Model) - Loss: 0.5831 - Accuracy: 0.9286 - F1: 0.9285

=== Summary Results ===

acc: 87.61 ± 4.37
F1: 87.23 ± 4.67
acc-in: 98.20 ± 1.08
F1-in: 98.19 ± 1.09
