lr: 0.001
sub_9:Test (Best Model) - Loss: 0.1544 - Accuracy: 0.9524 - F1: 0.9524
sub_2:Test (Best Model) - Loss: 0.1245 - Accuracy: 0.9762 - F1: 0.9762
sub_8:Test (Best Model) - Loss: 0.1706 - Accuracy: 0.9524 - F1: 0.9523
sub_1:Test (Best Model) - Loss: 0.2822 - Accuracy: 0.9048 - F1: 0.9043
sub_13:Test (Best Model) - Loss: 0.1746 - Accuracy: 0.9524 - F1: 0.9524
sub_10:Test (Best Model) - Loss: 0.4120 - Accuracy: 0.8810 - F1: 0.8809
sub_12:Test (Best Model) - Loss: 0.2856 - Accuracy: 0.9048 - F1: 0.9043
sub_14:Test (Best Model) - Loss: 0.3467 - Accuracy: 0.9048 - F1: 0.9043
sub_6:Test (Best Model) - Loss: 0.8158 - Accuracy: 0.7857 - F1: 0.7856
sub_9:Test (Best Model) - Loss: 0.1347 - Accuracy: 0.9881 - F1: 0.9881
sub_7:Test (Best Model) - Loss: 0.7498 - Accuracy: 0.7500 - F1: 0.7418
sub_11:Test (Best Model) - Loss: 0.5198 - Accuracy: 0.8571 - F1: 0.8551
sub_8:Test (Best Model) - Loss: 0.2090 - Accuracy: 0.9405 - F1: 0.9404
sub_5:Test (Best Model) - Loss: 0.4449 - Accuracy: 0.8690 - F1: 0.8686
sub_1:Test (Best Model) - Loss: 0.1942 - Accuracy: 0.9524 - F1: 0.9523
sub_12:Test (Best Model) - Loss: 0.3579 - Accuracy: 0.8810 - F1: 0.8807
sub_2:Test (Best Model) - Loss: 0.3294 - Accuracy: 0.9048 - F1: 0.9039
sub_9:Test (Best Model) - Loss: 0.1012 - Accuracy: 0.9881 - F1: 0.9881
sub_4:Test (Best Model) - Loss: 0.2443 - Accuracy: 0.9286 - F1: 0.9284
sub_10:Test (Best Model) - Loss: 0.4194 - Accuracy: 0.8690 - F1: 0.8675
sub_14:Test (Best Model) - Loss: 0.3779 - Accuracy: 0.8810 - F1: 0.8807
sub_6:Test (Best Model) - Loss: 0.4100 - Accuracy: 0.8333 - F1: 0.8318
sub_7:Test (Best Model) - Loss: 0.5256 - Accuracy: 0.7976 - F1: 0.7927
sub_8:Test (Best Model) - Loss: 0.2524 - Accuracy: 0.9286 - F1: 0.9284
sub_5:Test (Best Model) - Loss: 0.5464 - Accuracy: 0.7857 - F1: 0.7796
sub_3:Test (Best Model) - Loss: 0.5904 - Accuracy: 0.8214 - F1: 0.8170
sub_11:Test (Best Model) - Loss: 0.5340 - Accuracy: 0.8333 - F1: 0.8299
sub_13:Test (Best Model) - Loss: 0.3160 - Accuracy: 0.9167 - F1: 0.9164
sub_2:Test (Best Model) - Loss: 0.1483 - Accuracy: 0.9643 - F1: 0.9643
sub_12:Test (Best Model) - Loss: 0.2214 - Accuracy: 0.9286 - F1: 0.9285
sub_9:Test (Best Model) - Loss: 0.1763 - Accuracy: 0.9524 - F1: 0.9523
sub_10:Test (Best Model) - Loss: 0.4436 - Accuracy: 0.8571 - F1: 0.8568
sub_8:Test (Best Model) - Loss: 0.1958 - Accuracy: 0.9405 - F1: 0.9404
sub_14:Test (Best Model) - Loss: 0.4060 - Accuracy: 0.8690 - F1: 0.8686
sub_1:Test (Best Model) - Loss: 0.2488 - Accuracy: 0.9286 - F1: 0.9282
sub_6:Test (Best Model) - Loss: 0.5324 - Accuracy: 0.8214 - F1: 0.8194
sub_7:Test (Best Model) - Loss: 0.5003 - Accuracy: 0.8333 - F1: 0.8332
sub_5:Test (Best Model) - Loss: 0.5660 - Accuracy: 0.8214 - F1: 0.8170
sub_4:Test (Best Model) - Loss: 0.5686 - Accuracy: 0.8214 - F1: 0.8208
sub_3:Test (Best Model) - Loss: 0.7100 - Accuracy: 0.7738 - F1: 0.7641
sub_11:Test (Best Model) - Loss: 0.2880 - Accuracy: 0.9167 - F1: 0.9166
sub_12:Test (Best Model) - Loss: 0.3175 - Accuracy: 0.9048 - F1: 0.9043
sub_2:Test (Best Model) - Loss: 0.1198 - Accuracy: 0.9762 - F1: 0.9762
sub_8:Test (Best Model) - Loss: 0.1976 - Accuracy: 0.9405 - F1: 0.9404
sub_9:Test (Best Model) - Loss: 0.4024 - Accuracy: 0.8690 - F1: 0.8668
sub_10:Test (Best Model) - Loss: 0.6020 - Accuracy: 0.8095 - F1: 0.8068
sub_13:Test (Best Model) - Loss: 0.4183 - Accuracy: 0.8690 - F1: 0.8668
sub_6:Test (Best Model) - Loss: 0.5149 - Accuracy: 0.8333 - F1: 0.8309
sub_14:Test (Best Model) - Loss: 0.3719 - Accuracy: 0.8810 - F1: 0.8792
sub_7:Test (Best Model) - Loss: 0.6004 - Accuracy: 0.7619 - F1: 0.7618
sub_4:Test (Best Model) - Loss: 0.4052 - Accuracy: 0.8690 - F1: 0.8668
sub_1:Test (Best Model) - Loss: 0.3122 - Accuracy: 0.9167 - F1: 0.9161
sub_5:Test (Best Model) - Loss: 0.4844 - Accuracy: 0.8452 - F1: 0.8447
sub_12:Test (Best Model) - Loss: 0.3915 - Accuracy: 0.8571 - F1: 0.8551
sub_11:Test (Best Model) - Loss: 0.5581 - Accuracy: 0.8095 - F1: 0.8041
sub_3:Test (Best Model) - Loss: 0.7755 - Accuracy: 0.7500 - F1: 0.7418
sub_9:Test (Best Model) - Loss: 0.1893 - Accuracy: 0.9524 - F1: 0.9523
sub_2:Test (Best Model) - Loss: 0.1574 - Accuracy: 0.9524 - F1: 0.9524
sub_8:Test (Best Model) - Loss: 0.0858 - Accuracy: 0.9881 - F1: 0.9881
sub_1:Test (Best Model) - Loss: 0.3536 - Accuracy: 0.8810 - F1: 0.8792
sub_10:Test (Best Model) - Loss: 0.8611 - Accuracy: 0.7381 - F1: 0.7255
sub_14:Test (Best Model) - Loss: 0.4542 - Accuracy: 0.8333 - F1: 0.8333
sub_7:Test (Best Model) - Loss: 0.5496 - Accuracy: 0.8333 - F1: 0.8318
sub_6:Test (Best Model) - Loss: 0.6517 - Accuracy: 0.8095 - F1: 0.8056
sub_13:Test (Best Model) - Loss: 0.2570 - Accuracy: 0.9167 - F1: 0.9167
sub_11:Test (Best Model) - Loss: 0.5668 - Accuracy: 0.8333 - F1: 0.8286
sub_9:Test (Best Model) - Loss: 0.1372 - Accuracy: 0.9762 - F1: 0.9762
sub_3:Test (Best Model) - Loss: 0.6808 - Accuracy: 0.7976 - F1: 0.7927
sub_4:Test (Best Model) - Loss: 0.3968 - Accuracy: 0.8929 - F1: 0.8921
sub_2:Test (Best Model) - Loss: 0.2121 - Accuracy: 0.9405 - F1: 0.9405
sub_12:Test (Best Model) - Loss: 0.3099 - Accuracy: 0.8929 - F1: 0.8916
sub_8:Test (Best Model) - Loss: 0.2908 - Accuracy: 0.8810 - F1: 0.8792
sub_5:Test (Best Model) - Loss: 0.4628 - Accuracy: 0.8690 - F1: 0.8681
sub_10:Test (Best Model) - Loss: 0.3988 - Accuracy: 0.8571 - F1: 0.8571
sub_7:Test (Best Model) - Loss: 0.2156 - Accuracy: 0.9405 - F1: 0.9404
sub_14:Test (Best Model) - Loss: 0.1643 - Accuracy: 0.9524 - F1: 0.9523
sub_13:Test (Best Model) - Loss: 0.2509 - Accuracy: 0.9286 - F1: 0.9286
sub_1:Test (Best Model) - Loss: 0.1591 - Accuracy: 0.9643 - F1: 0.9642
sub_6:Test (Best Model) - Loss: 0.9674 - Accuracy: 0.7024 - F1: 0.6951
sub_12:Test (Best Model) - Loss: 0.5702 - Accuracy: 0.7738 - F1: 0.7735
sub_8:Test (Best Model) - Loss: 0.1497 - Accuracy: 0.9643 - F1: 0.9642
sub_3:Test (Best Model) - Loss: 0.8936 - Accuracy: 0.7262 - F1: 0.7114
sub_5:Test (Best Model) - Loss: 0.5539 - Accuracy: 0.7976 - F1: 0.7927
sub_4:Test (Best Model) - Loss: 0.6353 - Accuracy: 0.8095 - F1: 0.8085
sub_10:Test (Best Model) - Loss: 0.3497 - Accuracy: 0.8810 - F1: 0.8809
sub_11:Test (Best Model) - Loss: 0.6967 - Accuracy: 0.8095 - F1: 0.8041
sub_2:Test (Best Model) - Loss: 0.3597 - Accuracy: 0.8929 - F1: 0.8925
sub_7:Test (Best Model) - Loss: 0.2010 - Accuracy: 0.9405 - F1: 0.9405
sub_9:Test (Best Model) - Loss: 0.1189 - Accuracy: 0.9762 - F1: 0.9762
sub_1:Test (Best Model) - Loss: 0.2779 - Accuracy: 0.9167 - F1: 0.9161
sub_14:Test (Best Model) - Loss: 0.0992 - Accuracy: 0.9881 - F1: 0.9881
sub_13:Test (Best Model) - Loss: 0.4338 - Accuracy: 0.8214 - F1: 0.8202
sub_6:Test (Best Model) - Loss: 0.7350 - Accuracy: 0.7619 - F1: 0.7585
sub_8:Test (Best Model) - Loss: 0.1132 - Accuracy: 0.9881 - F1: 0.9881
sub_12:Test (Best Model) - Loss: 0.5595 - Accuracy: 0.7976 - F1: 0.7976
sub_1:Test (Best Model) - Loss: 0.2311 - Accuracy: 0.9167 - F1: 0.9161
sub_9:Test (Best Model) - Loss: 0.2434 - Accuracy: 0.9286 - F1: 0.9282
sub_11:Test (Best Model) - Loss: 0.3079 - Accuracy: 0.8810 - F1: 0.8807
sub_10:Test (Best Model) - Loss: 0.4072 - Accuracy: 0.8810 - F1: 0.8803
sub_4:Test (Best Model) - Loss: 0.5838 - Accuracy: 0.7857 - F1: 0.7846
sub_13:Test (Best Model) - Loss: 0.4424 - Accuracy: 0.8214 - F1: 0.8170
sub_5:Test (Best Model) - Loss: 0.6728 - Accuracy: 0.8095 - F1: 0.8056
sub_3:Test (Best Model) - Loss: 0.7119 - Accuracy: 0.7857 - F1: 0.7856
sub_2:Test (Best Model) - Loss: 0.2626 - Accuracy: 0.9167 - F1: 0.9167
sub_14:Test (Best Model) - Loss: 0.2418 - Accuracy: 0.9286 - F1: 0.9282
sub_12:Test (Best Model) - Loss: 0.5056 - Accuracy: 0.8095 - F1: 0.8094
sub_7:Test (Best Model) - Loss: 0.2065 - Accuracy: 0.9286 - F1: 0.9284
sub_9:Test (Best Model) - Loss: 0.2899 - Accuracy: 0.9048 - F1: 0.9039
sub_6:Test (Best Model) - Loss: 1.0137 - Accuracy: 0.6905 - F1: 0.6840
sub_8:Test (Best Model) - Loss: 0.1177 - Accuracy: 0.9643 - F1: 0.9642
sub_11:Test (Best Model) - Loss: 0.4537 - Accuracy: 0.8452 - F1: 0.8425
sub_1:Test (Best Model) - Loss: 0.3847 - Accuracy: 0.8929 - F1: 0.8916
sub_5:Test (Best Model) - Loss: 0.3880 - Accuracy: 0.8690 - F1: 0.8681
sub_2:Test (Best Model) - Loss: 0.2294 - Accuracy: 0.9286 - F1: 0.9284
sub_10:Test (Best Model) - Loss: 0.2911 - Accuracy: 0.9167 - F1: 0.9166
sub_4:Test (Best Model) - Loss: 0.3239 - Accuracy: 0.8810 - F1: 0.8803
sub_13:Test (Best Model) - Loss: 0.5896 - Accuracy: 0.8214 - F1: 0.8212
sub_12:Test (Best Model) - Loss: 0.7466 - Accuracy: 0.7024 - F1: 0.6972
sub_9:Test (Best Model) - Loss: 0.4595 - Accuracy: 0.8452 - F1: 0.8414
sub_14:Test (Best Model) - Loss: 0.3750 - Accuracy: 0.8810 - F1: 0.8792
sub_8:Test (Best Model) - Loss: 0.1118 - Accuracy: 0.9881 - F1: 0.9881
sub_7:Test (Best Model) - Loss: 0.3459 - Accuracy: 0.9048 - F1: 0.9047
sub_1:Test (Best Model) - Loss: 0.1659 - Accuracy: 0.9643 - F1: 0.9642
sub_6:Test (Best Model) - Loss: 1.0283 - Accuracy: 0.6905 - F1: 0.6816
sub_11:Test (Best Model) - Loss: 0.3992 - Accuracy: 0.8690 - F1: 0.8686
sub_3:Test (Best Model) - Loss: 0.7649 - Accuracy: 0.7143 - F1: 0.7141
sub_5:Test (Best Model) - Loss: 0.3735 - Accuracy: 0.8810 - F1: 0.8810
sub_13:Test (Best Model) - Loss: 0.5469 - Accuracy: 0.8095 - F1: 0.8056
sub_4:Test (Best Model) - Loss: 0.4061 - Accuracy: 0.8690 - F1: 0.8675
sub_9:Test (Best Model) - Loss: 0.6374 - Accuracy: 0.8214 - F1: 0.8183
sub_10:Test (Best Model) - Loss: 0.2559 - Accuracy: 0.9167 - F1: 0.9164
sub_2:Test (Best Model) - Loss: 0.2842 - Accuracy: 0.9286 - F1: 0.9282
sub_6:Test (Best Model) - Loss: 0.7116 - Accuracy: 0.7262 - F1: 0.7172
sub_12:Test (Best Model) - Loss: 0.6706 - Accuracy: 0.8214 - F1: 0.8170
sub_14:Test (Best Model) - Loss: 0.1625 - Accuracy: 0.9524 - F1: 0.9523
sub_7:Test (Best Model) - Loss: 0.2224 - Accuracy: 0.9405 - F1: 0.9405
sub_8:Test (Best Model) - Loss: 0.0740 - Accuracy: 0.9881 - F1: 0.9881
sub_5:Test (Best Model) - Loss: 0.3835 - Accuracy: 0.8690 - F1: 0.8686
sub_11:Test (Best Model) - Loss: 0.3879 - Accuracy: 0.8810 - F1: 0.8792
sub_1:Test (Best Model) - Loss: 0.5488 - Accuracy: 0.7857 - F1: 0.7838
sub_9:Test (Best Model) - Loss: 0.5355 - Accuracy: 0.7976 - F1: 0.7890
sub_13:Test (Best Model) - Loss: 0.5489 - Accuracy: 0.8333 - F1: 0.8299
sub_2:Test (Best Model) - Loss: 0.2700 - Accuracy: 0.9048 - F1: 0.9047
sub_5:Test (Best Model) - Loss: 0.3509 - Accuracy: 0.8929 - F1: 0.8921
sub_10:Test (Best Model) - Loss: 1.2312 - Accuracy: 0.6310 - F1: 0.5810
sub_7:Test (Best Model) - Loss: 0.6677 - Accuracy: 0.7857 - F1: 0.7857
sub_6:Test (Best Model) - Loss: 0.1882 - Accuracy: 0.9524 - F1: 0.9524
sub_3:Test (Best Model) - Loss: 0.7216 - Accuracy: 0.7619 - F1: 0.7618
sub_9:Test (Best Model) - Loss: 0.6230 - Accuracy: 0.7619 - F1: 0.7476
sub_4:Test (Best Model) - Loss: 0.3173 - Accuracy: 0.8810 - F1: 0.8792
sub_1:Test (Best Model) - Loss: 0.6111 - Accuracy: 0.7976 - F1: 0.7969
sub_14:Test (Best Model) - Loss: 0.1644 - Accuracy: 0.9405 - F1: 0.9405
sub_12:Test (Best Model) - Loss: 0.4439 - Accuracy: 0.8452 - F1: 0.8434
sub_8:Test (Best Model) - Loss: 0.1092 - Accuracy: 0.9762 - F1: 0.9762
sub_11:Test (Best Model) - Loss: 0.2696 - Accuracy: 0.9167 - F1: 0.9161
sub_5:Test (Best Model) - Loss: 0.5033 - Accuracy: 0.8214 - F1: 0.8155
sub_2:Test (Best Model) - Loss: 0.2244 - Accuracy: 0.9405 - F1: 0.9405
sub_13:Test (Best Model) - Loss: 0.2922 - Accuracy: 0.9167 - F1: 0.9166
sub_9:Test (Best Model) - Loss: 0.4675 - Accuracy: 0.8095 - F1: 0.8024
sub_14:Test (Best Model) - Loss: 0.1675 - Accuracy: 0.9643 - F1: 0.9642
sub_10:Test (Best Model) - Loss: 0.7528 - Accuracy: 0.7262 - F1: 0.7114
sub_7:Test (Best Model) - Loss: 0.5710 - Accuracy: 0.7857 - F1: 0.7846
sub_1:Test (Best Model) - Loss: 0.3574 - Accuracy: 0.8929 - F1: 0.8928
sub_11:Test (Best Model) - Loss: 0.1475 - Accuracy: 0.9643 - F1: 0.9643
sub_8:Test (Best Model) - Loss: 0.1794 - Accuracy: 0.9405 - F1: 0.9403
sub_12:Test (Best Model) - Loss: 0.4865 - Accuracy: 0.8333 - F1: 0.8325
sub_5:Test (Best Model) - Loss: 0.4662 - Accuracy: 0.8333 - F1: 0.8286
sub_6:Test (Best Model) - Loss: 0.2200 - Accuracy: 0.9286 - F1: 0.9284
sub_3:Test (Best Model) - Loss: 0.8464 - Accuracy: 0.7262 - F1: 0.7262
sub_10:Test (Best Model) - Loss: 0.5006 - Accuracy: 0.7976 - F1: 0.7927
sub_4:Test (Best Model) - Loss: 0.7146 - Accuracy: 0.7976 - F1: 0.7941
sub_2:Test (Best Model) - Loss: 0.4376 - Accuracy: 0.8571 - F1: 0.8564
sub_13:Test (Best Model) - Loss: 0.2434 - Accuracy: 0.9405 - F1: 0.9403
sub_7:Test (Best Model) - Loss: 0.7034 - Accuracy: 0.7976 - F1: 0.7976
sub_14:Test (Best Model) - Loss: 0.1545 - Accuracy: 0.9643 - F1: 0.9642
sub_1:Test (Best Model) - Loss: 0.7315 - Accuracy: 0.7619 - F1: 0.7597
sub_8:Test (Best Model) - Loss: 0.0929 - Accuracy: 0.9881 - F1: 0.9881
sub_12:Test (Best Model) - Loss: 0.5240 - Accuracy: 0.8095 - F1: 0.8091
sub_5:Test (Best Model) - Loss: 0.6874 - Accuracy: 0.7976 - F1: 0.7910
sub_10:Test (Best Model) - Loss: 0.8230 - Accuracy: 0.6786 - F1: 0.6571
sub_3:Test (Best Model) - Loss: 0.6699 - Accuracy: 0.7619 - F1: 0.7619
sub_13:Test (Best Model) - Loss: 0.1885 - Accuracy: 0.9524 - F1: 0.9524
sub_4:Test (Best Model) - Loss: 0.4752 - Accuracy: 0.8095 - F1: 0.8056
sub_2:Test (Best Model) - Loss: 0.1789 - Accuracy: 0.9524 - F1: 0.9524
sub_7:Test (Best Model) - Loss: 0.4283 - Accuracy: 0.8333 - F1: 0.8333
sub_11:Test (Best Model) - Loss: 0.1617 - Accuracy: 0.9524 - F1: 0.9524
sub_14:Test (Best Model) - Loss: 0.2186 - Accuracy: 0.9286 - F1: 0.9282
sub_1:Test (Best Model) - Loss: 0.7392 - Accuracy: 0.7738 - F1: 0.7738
sub_5:Test (Best Model) - Loss: 0.4176 - Accuracy: 0.8452 - F1: 0.8425
sub_6:Test (Best Model) - Loss: 0.1687 - Accuracy: 0.9405 - F1: 0.9405
sub_7:Test (Best Model) - Loss: 0.3849 - Accuracy: 0.8333 - F1: 0.8330
sub_12:Test (Best Model) - Loss: 0.5716 - Accuracy: 0.8333 - F1: 0.8299
sub_13:Test (Best Model) - Loss: 0.2594 - Accuracy: 0.9286 - F1: 0.9284
sub_2:Test (Best Model) - Loss: 0.2652 - Accuracy: 0.9167 - F1: 0.9167
sub_3:Test (Best Model) - Loss: 0.6728 - Accuracy: 0.8095 - F1: 0.8041
sub_11:Test (Best Model) - Loss: 0.3590 - Accuracy: 0.8810 - F1: 0.8799
sub_6:Test (Best Model) - Loss: 0.2556 - Accuracy: 0.9048 - F1: 0.9047
sub_10:Test (Best Model) - Loss: 0.7176 - Accuracy: 0.7857 - F1: 0.7796
sub_4:Test (Best Model) - Loss: 0.8631 - Accuracy: 0.7738 - F1: 0.7683
sub_14:Test (Best Model) - Loss: 0.2473 - Accuracy: 0.9167 - F1: 0.9161
sub_3:Test (Best Model) - Loss: 0.9064 - Accuracy: 0.7143 - F1: 0.6889
sub_13:Test (Best Model) - Loss: 0.3519 - Accuracy: 0.9048 - F1: 0.9047
sub_11:Test (Best Model) - Loss: 0.3335 - Accuracy: 0.8929 - F1: 0.8916
sub_4:Test (Best Model) - Loss: 0.6049 - Accuracy: 0.8095 - F1: 0.8085
sub_3:Test (Best Model) - Loss: 1.0304 - Accuracy: 0.6667 - F1: 0.6370
sub_6:Test (Best Model) - Loss: 0.1542 - Accuracy: 0.9643 - F1: 0.9642
sub_4:Test (Best Model) - Loss: 0.7335 - Accuracy: 0.7857 - F1: 0.7796
sub_3:Test (Best Model) - Loss: 0.6154 - Accuracy: 0.7381 - F1: 0.7188
sub_4:Test (Best Model) - Loss: 0.6340 - Accuracy: 0.7976 - F1: 0.7910
sub_3:Test (Best Model) - Loss: 0.6979 - Accuracy: 0.7976 - F1: 0.7890

=== Summary Results ===

acc: 86.50 ± 5.13
F1: 86.26 ± 5.34
acc-in: 94.67 ± 3.13
F1-in: 94.61 ± 3.16
