lr: 0.001
sub_14:Test (Best Model) - Loss: 0.4197 - Accuracy: 0.8452 - F1: 0.8414
sub_2:Test (Best Model) - Loss: 0.3793 - Accuracy: 0.8571 - F1: 0.8542
sub_8:Test (Best Model) - Loss: 0.1977 - Accuracy: 0.9405 - F1: 0.9403
sub_12:Test (Best Model) - Loss: 0.2351 - Accuracy: 0.9167 - F1: 0.9161
sub_6:Test (Best Model) - Loss: 0.3662 - Accuracy: 0.8929 - F1: 0.8916
sub_4:Test (Best Model) - Loss: 0.1460 - Accuracy: 0.9643 - F1: 0.9642
sub_13:Test (Best Model) - Loss: 0.4648 - Accuracy: 0.8452 - F1: 0.8414
sub_1:Test (Best Model) - Loss: 0.8173 - Accuracy: 0.7500 - F1: 0.7333
sub_9:Test (Best Model) - Loss: 0.0689 - Accuracy: 0.9881 - F1: 0.9881
sub_11:Test (Best Model) - Loss: 0.1351 - Accuracy: 0.9643 - F1: 0.9643
sub_10:Test (Best Model) - Loss: 0.2598 - Accuracy: 0.9167 - F1: 0.9161
sub_8:Test (Best Model) - Loss: 0.1551 - Accuracy: 0.9643 - F1: 0.9643
sub_14:Test (Best Model) - Loss: 0.3747 - Accuracy: 0.8810 - F1: 0.8803
sub_3:Test (Best Model) - Loss: 1.4175 - Accuracy: 0.5595 - F1: 0.4535
sub_12:Test (Best Model) - Loss: 0.4744 - Accuracy: 0.8333 - F1: 0.8286
sub_13:Test (Best Model) - Loss: 0.2094 - Accuracy: 0.9286 - F1: 0.9284
sub_2:Test (Best Model) - Loss: 0.3518 - Accuracy: 0.8929 - F1: 0.8916
sub_5:Test (Best Model) - Loss: 0.6951 - Accuracy: 0.7976 - F1: 0.7910
sub_6:Test (Best Model) - Loss: 0.5950 - Accuracy: 0.8214 - F1: 0.8155
sub_7:Test (Best Model) - Loss: 0.1998 - Accuracy: 0.9524 - F1: 0.9524
sub_11:Test (Best Model) - Loss: 0.1920 - Accuracy: 0.9524 - F1: 0.9523
sub_4:Test (Best Model) - Loss: 0.1744 - Accuracy: 0.9286 - F1: 0.9282
sub_1:Test (Best Model) - Loss: 0.9183 - Accuracy: 0.7143 - F1: 0.6889
sub_14:Test (Best Model) - Loss: 0.3321 - Accuracy: 0.8690 - F1: 0.8675
sub_10:Test (Best Model) - Loss: 0.3846 - Accuracy: 0.8929 - F1: 0.8916
sub_12:Test (Best Model) - Loss: 0.1726 - Accuracy: 0.9524 - F1: 0.9523
sub_9:Test (Best Model) - Loss: 0.0333 - Accuracy: 1.0000 - F1: 1.0000
sub_13:Test (Best Model) - Loss: 0.4794 - Accuracy: 0.8452 - F1: 0.8414
sub_8:Test (Best Model) - Loss: 0.1150 - Accuracy: 0.9762 - F1: 0.9762
sub_5:Test (Best Model) - Loss: 0.6455 - Accuracy: 0.7619 - F1: 0.7529
sub_2:Test (Best Model) - Loss: 0.6452 - Accuracy: 0.7976 - F1: 0.7890
sub_3:Test (Best Model) - Loss: 1.3006 - Accuracy: 0.5952 - F1: 0.5159
sub_11:Test (Best Model) - Loss: 0.2897 - Accuracy: 0.9048 - F1: 0.9039
sub_6:Test (Best Model) - Loss: 0.3970 - Accuracy: 0.8810 - F1: 0.8809
sub_7:Test (Best Model) - Loss: 0.3507 - Accuracy: 0.8810 - F1: 0.8809
sub_12:Test (Best Model) - Loss: 0.2329 - Accuracy: 0.9405 - F1: 0.9403
sub_4:Test (Best Model) - Loss: 0.2591 - Accuracy: 0.9167 - F1: 0.9161
sub_8:Test (Best Model) - Loss: 0.1344 - Accuracy: 0.9762 - F1: 0.9762
sub_13:Test (Best Model) - Loss: 0.4030 - Accuracy: 0.8571 - F1: 0.8551
sub_9:Test (Best Model) - Loss: 0.0961 - Accuracy: 0.9881 - F1: 0.9881
sub_2:Test (Best Model) - Loss: 0.6051 - Accuracy: 0.7976 - F1: 0.7890
sub_14:Test (Best Model) - Loss: 0.2193 - Accuracy: 0.9405 - F1: 0.9403
sub_11:Test (Best Model) - Loss: 0.2825 - Accuracy: 0.9167 - F1: 0.9161
sub_1:Test (Best Model) - Loss: 0.8571 - Accuracy: 0.7024 - F1: 0.6735
sub_10:Test (Best Model) - Loss: 0.4471 - Accuracy: 0.8690 - F1: 0.8668
sub_3:Test (Best Model) - Loss: 0.4485 - Accuracy: 0.7976 - F1: 0.7890
sub_5:Test (Best Model) - Loss: 0.6277 - Accuracy: 0.7857 - F1: 0.7812
sub_12:Test (Best Model) - Loss: 0.3459 - Accuracy: 0.8690 - F1: 0.8668
sub_6:Test (Best Model) - Loss: 0.1071 - Accuracy: 0.9643 - F1: 0.9643
sub_7:Test (Best Model) - Loss: 0.1862 - Accuracy: 0.9524 - F1: 0.9523
sub_8:Test (Best Model) - Loss: 0.1090 - Accuracy: 0.9762 - F1: 0.9762
sub_13:Test (Best Model) - Loss: 0.4522 - Accuracy: 0.8333 - F1: 0.8286
sub_2:Test (Best Model) - Loss: 0.1994 - Accuracy: 0.9286 - F1: 0.9282
sub_14:Test (Best Model) - Loss: 0.2411 - Accuracy: 0.9286 - F1: 0.9282
sub_4:Test (Best Model) - Loss: 0.2775 - Accuracy: 0.9048 - F1: 0.9039
sub_11:Test (Best Model) - Loss: 0.3413 - Accuracy: 0.8929 - F1: 0.8916
sub_12:Test (Best Model) - Loss: 0.2008 - Accuracy: 0.9405 - F1: 0.9405
sub_9:Test (Best Model) - Loss: 0.2321 - Accuracy: 0.9405 - F1: 0.9403
sub_10:Test (Best Model) - Loss: 0.1843 - Accuracy: 0.9405 - F1: 0.9404
sub_1:Test (Best Model) - Loss: 0.6189 - Accuracy: 0.7857 - F1: 0.7754
sub_6:Test (Best Model) - Loss: 0.3714 - Accuracy: 0.8929 - F1: 0.8916
sub_7:Test (Best Model) - Loss: 0.1588 - Accuracy: 0.9643 - F1: 0.9643
sub_2:Test (Best Model) - Loss: 0.2786 - Accuracy: 0.9167 - F1: 0.9161
sub_3:Test (Best Model) - Loss: 0.8231 - Accuracy: 0.7500 - F1: 0.7333
sub_11:Test (Best Model) - Loss: 0.1546 - Accuracy: 0.9643 - F1: 0.9642
sub_8:Test (Best Model) - Loss: 0.0860 - Accuracy: 0.9881 - F1: 0.9881
sub_4:Test (Best Model) - Loss: 0.2617 - Accuracy: 0.9048 - F1: 0.9039
sub_5:Test (Best Model) - Loss: 0.7187 - Accuracy: 0.7619 - F1: 0.7476
sub_9:Test (Best Model) - Loss: 0.4101 - Accuracy: 0.8452 - F1: 0.8414
sub_13:Test (Best Model) - Loss: 0.1890 - Accuracy: 0.9524 - F1: 0.9523
sub_1:Test (Best Model) - Loss: 0.7352 - Accuracy: 0.7381 - F1: 0.7188
sub_10:Test (Best Model) - Loss: 0.4082 - Accuracy: 0.8690 - F1: 0.8675
sub_12:Test (Best Model) - Loss: 0.2699 - Accuracy: 0.9048 - F1: 0.9043
sub_2:Test (Best Model) - Loss: 0.1864 - Accuracy: 0.9524 - F1: 0.9523
sub_7:Test (Best Model) - Loss: 0.2669 - Accuracy: 0.9286 - F1: 0.9284
sub_6:Test (Best Model) - Loss: 0.1535 - Accuracy: 0.9643 - F1: 0.9643
sub_3:Test (Best Model) - Loss: 0.7955 - Accuracy: 0.6071 - F1: 0.5354
sub_11:Test (Best Model) - Loss: 0.2558 - Accuracy: 0.9167 - F1: 0.9161
sub_8:Test (Best Model) - Loss: 0.1021 - Accuracy: 0.9881 - F1: 0.9881
sub_4:Test (Best Model) - Loss: 0.2482 - Accuracy: 0.9286 - F1: 0.9285
sub_5:Test (Best Model) - Loss: 0.6324 - Accuracy: 0.7619 - F1: 0.7504
sub_13:Test (Best Model) - Loss: 0.1453 - Accuracy: 0.9524 - F1: 0.9523
sub_10:Test (Best Model) - Loss: 0.1235 - Accuracy: 0.9762 - F1: 0.9762
sub_12:Test (Best Model) - Loss: 0.4377 - Accuracy: 0.8452 - F1: 0.8414
sub_14:Test (Best Model) - Loss: 0.1407 - Accuracy: 0.9643 - F1: 0.9642
sub_9:Test (Best Model) - Loss: 0.4238 - Accuracy: 0.8571 - F1: 0.8542
sub_1:Test (Best Model) - Loss: 0.1551 - Accuracy: 0.9643 - F1: 0.9642
sub_3:Test (Best Model) - Loss: 0.1763 - Accuracy: 0.9524 - F1: 0.9523
sub_2:Test (Best Model) - Loss: 0.2407 - Accuracy: 0.9286 - F1: 0.9282
sub_8:Test (Best Model) - Loss: 0.1704 - Accuracy: 0.9643 - F1: 0.9642
sub_6:Test (Best Model) - Loss: 0.2949 - Accuracy: 0.9167 - F1: 0.9161
sub_13:Test (Best Model) - Loss: 0.2387 - Accuracy: 0.9167 - F1: 0.9167
sub_11:Test (Best Model) - Loss: 0.0455 - Accuracy: 1.0000 - F1: 1.0000
sub_12:Test (Best Model) - Loss: 0.3991 - Accuracy: 0.8571 - F1: 0.8542
sub_7:Test (Best Model) - Loss: 0.0746 - Accuracy: 0.9881 - F1: 0.9881
sub_4:Test (Best Model) - Loss: 0.1665 - Accuracy: 0.9524 - F1: 0.9524
sub_10:Test (Best Model) - Loss: 0.1353 - Accuracy: 0.9643 - F1: 0.9643
sub_14:Test (Best Model) - Loss: 0.1250 - Accuracy: 0.9762 - F1: 0.9762
sub_8:Test (Best Model) - Loss: 0.0901 - Accuracy: 0.9881 - F1: 0.9881
sub_1:Test (Best Model) - Loss: 0.1306 - Accuracy: 0.9643 - F1: 0.9643
sub_5:Test (Best Model) - Loss: 0.2377 - Accuracy: 0.9167 - F1: 0.9164
sub_11:Test (Best Model) - Loss: 0.1311 - Accuracy: 0.9762 - F1: 0.9762
sub_3:Test (Best Model) - Loss: 0.2340 - Accuracy: 0.9286 - F1: 0.9285
sub_13:Test (Best Model) - Loss: 0.1336 - Accuracy: 0.9524 - F1: 0.9524
sub_12:Test (Best Model) - Loss: 0.5009 - Accuracy: 0.8452 - F1: 0.8414
sub_6:Test (Best Model) - Loss: 0.4102 - Accuracy: 0.8810 - F1: 0.8799
sub_9:Test (Best Model) - Loss: 0.3451 - Accuracy: 0.8810 - F1: 0.8799
sub_2:Test (Best Model) - Loss: 0.2311 - Accuracy: 0.9286 - F1: 0.9282
sub_4:Test (Best Model) - Loss: 0.1943 - Accuracy: 0.9405 - F1: 0.9405
sub_8:Test (Best Model) - Loss: 0.1215 - Accuracy: 0.9881 - F1: 0.9881
sub_14:Test (Best Model) - Loss: 0.1310 - Accuracy: 0.9643 - F1: 0.9642
sub_7:Test (Best Model) - Loss: 0.3746 - Accuracy: 0.8571 - F1: 0.8542
sub_10:Test (Best Model) - Loss: 0.1041 - Accuracy: 0.9762 - F1: 0.9762
sub_12:Test (Best Model) - Loss: 0.2954 - Accuracy: 0.9167 - F1: 0.9166
sub_11:Test (Best Model) - Loss: 0.0879 - Accuracy: 1.0000 - F1: 1.0000
sub_13:Test (Best Model) - Loss: 0.1827 - Accuracy: 0.9643 - F1: 0.9642
sub_6:Test (Best Model) - Loss: 0.2719 - Accuracy: 0.9048 - F1: 0.9045
sub_2:Test (Best Model) - Loss: 0.2626 - Accuracy: 0.9286 - F1: 0.9282
sub_9:Test (Best Model) - Loss: 0.3308 - Accuracy: 0.8571 - F1: 0.8551
sub_5:Test (Best Model) - Loss: 0.1520 - Accuracy: 0.9524 - F1: 0.9523
sub_1:Test (Best Model) - Loss: 0.2284 - Accuracy: 0.9405 - F1: 0.9403
sub_3:Test (Best Model) - Loss: 0.3351 - Accuracy: 0.8929 - F1: 0.8916
sub_10:Test (Best Model) - Loss: 0.1490 - Accuracy: 0.9643 - F1: 0.9643
sub_4:Test (Best Model) - Loss: 0.1414 - Accuracy: 0.9643 - F1: 0.9643
sub_8:Test (Best Model) - Loss: 0.1451 - Accuracy: 0.9643 - F1: 0.9642
sub_12:Test (Best Model) - Loss: 0.2730 - Accuracy: 0.9167 - F1: 0.9166
sub_7:Test (Best Model) - Loss: 0.1944 - Accuracy: 0.9405 - F1: 0.9404
sub_13:Test (Best Model) - Loss: 0.1422 - Accuracy: 0.9643 - F1: 0.9642
sub_14:Test (Best Model) - Loss: 0.1443 - Accuracy: 0.9643 - F1: 0.9642
sub_11:Test (Best Model) - Loss: 0.0747 - Accuracy: 0.9881 - F1: 0.9881
sub_6:Test (Best Model) - Loss: 0.1091 - Accuracy: 0.9762 - F1: 0.9762
sub_4:Test (Best Model) - Loss: 0.3826 - Accuracy: 0.8690 - F1: 0.8681
sub_2:Test (Best Model) - Loss: 0.1059 - Accuracy: 0.9643 - F1: 0.9642
sub_3:Test (Best Model) - Loss: 0.1440 - Accuracy: 0.9643 - F1: 0.9642
sub_1:Test (Best Model) - Loss: 0.1595 - Accuracy: 0.9524 - F1: 0.9523
sub_12:Test (Best Model) - Loss: 0.2019 - Accuracy: 0.9524 - F1: 0.9524
sub_9:Test (Best Model) - Loss: 0.3888 - Accuracy: 0.8810 - F1: 0.8799
sub_13:Test (Best Model) - Loss: 0.1829 - Accuracy: 0.9524 - F1: 0.9523
sub_10:Test (Best Model) - Loss: 0.1839 - Accuracy: 0.9524 - F1: 0.9524
sub_14:Test (Best Model) - Loss: 0.1109 - Accuracy: 0.9881 - F1: 0.9881
sub_5:Test (Best Model) - Loss: 0.2607 - Accuracy: 0.9286 - F1: 0.9286
sub_11:Test (Best Model) - Loss: 0.1477 - Accuracy: 0.9643 - F1: 0.9642
sub_4:Test (Best Model) - Loss: 0.4246 - Accuracy: 0.8571 - F1: 0.8542
sub_7:Test (Best Model) - Loss: 0.1321 - Accuracy: 0.9524 - F1: 0.9524
sub_8:Test (Best Model) - Loss: 0.1015 - Accuracy: 0.9762 - F1: 0.9762
sub_2:Test (Best Model) - Loss: 0.1094 - Accuracy: 0.9643 - F1: 0.9642
sub_3:Test (Best Model) - Loss: 0.1908 - Accuracy: 0.9524 - F1: 0.9524
sub_12:Test (Best Model) - Loss: 0.2767 - Accuracy: 0.9167 - F1: 0.9166
sub_6:Test (Best Model) - Loss: 0.3831 - Accuracy: 0.8690 - F1: 0.8668
sub_9:Test (Best Model) - Loss: 0.3267 - Accuracy: 0.8929 - F1: 0.8916
sub_10:Test (Best Model) - Loss: 0.2418 - Accuracy: 0.9167 - F1: 0.9166
sub_14:Test (Best Model) - Loss: 1.2879 - Accuracy: 0.5357 - F1: 0.4081
sub_1:Test (Best Model) - Loss: 0.2251 - Accuracy: 0.9405 - F1: 0.9403
sub_12:Test (Best Model) - Loss: 0.2577 - Accuracy: 0.9167 - F1: 0.9166
sub_8:Test (Best Model) - Loss: 0.1842 - Accuracy: 0.9524 - F1: 0.9523
sub_4:Test (Best Model) - Loss: 0.2976 - Accuracy: 0.9048 - F1: 0.9039
sub_3:Test (Best Model) - Loss: 0.5700 - Accuracy: 0.7857 - F1: 0.7754
sub_13:Test (Best Model) - Loss: 0.1638 - Accuracy: 0.9524 - F1: 0.9523
sub_6:Test (Best Model) - Loss: 0.6631 - Accuracy: 0.7619 - F1: 0.7551
sub_9:Test (Best Model) - Loss: 0.5755 - Accuracy: 0.8095 - F1: 0.8024
sub_5:Test (Best Model) - Loss: 0.1596 - Accuracy: 0.9524 - F1: 0.9524
sub_7:Test (Best Model) - Loss: 0.1101 - Accuracy: 0.9762 - F1: 0.9762
sub_10:Test (Best Model) - Loss: 0.1939 - Accuracy: 0.9405 - F1: 0.9405
sub_2:Test (Best Model) - Loss: 0.1297 - Accuracy: 0.9405 - F1: 0.9403
sub_14:Test (Best Model) - Loss: 1.0416 - Accuracy: 0.5476 - F1: 0.4312
sub_11:Test (Best Model) - Loss: 0.0672 - Accuracy: 0.9881 - F1: 0.9881
sub_1:Test (Best Model) - Loss: 0.0803 - Accuracy: 1.0000 - F1: 1.0000
sub_8:Test (Best Model) - Loss: 0.1281 - Accuracy: 0.9643 - F1: 0.9642
sub_9:Test (Best Model) - Loss: 0.1898 - Accuracy: 0.9405 - F1: 0.9403
sub_2:Test (Best Model) - Loss: 0.0931 - Accuracy: 0.9881 - F1: 0.9881
sub_13:Test (Best Model) - Loss: 0.0727 - Accuracy: 1.0000 - F1: 1.0000
sub_14:Test (Best Model) - Loss: 1.0549 - Accuracy: 0.5595 - F1: 0.4535
sub_5:Test (Best Model) - Loss: 0.1628 - Accuracy: 0.9524 - F1: 0.9523
sub_8:Test (Best Model) - Loss: 0.1425 - Accuracy: 0.9643 - F1: 0.9642
sub_10:Test (Best Model) - Loss: 0.2141 - Accuracy: 0.9167 - F1: 0.9161
sub_4:Test (Best Model) - Loss: 0.1668 - Accuracy: 0.9524 - F1: 0.9523
sub_3:Test (Best Model) - Loss: 0.4542 - Accuracy: 0.8333 - F1: 0.8286
sub_2:Test (Best Model) - Loss: 0.0961 - Accuracy: 0.9881 - F1: 0.9881
sub_7:Test (Best Model) - Loss: 0.6439 - Accuracy: 0.7976 - F1: 0.7890
sub_9:Test (Best Model) - Loss: 0.2981 - Accuracy: 0.8929 - F1: 0.8916
sub_13:Test (Best Model) - Loss: 0.1733 - Accuracy: 0.9405 - F1: 0.9403
sub_11:Test (Best Model) - Loss: 0.1452 - Accuracy: 0.9524 - F1: 0.9524
sub_14:Test (Best Model) - Loss: 1.2817 - Accuracy: 0.5119 - F1: 0.3593
sub_1:Test (Best Model) - Loss: 0.0779 - Accuracy: 0.9881 - F1: 0.9881
sub_6:Test (Best Model) - Loss: 0.4688 - Accuracy: 0.8214 - F1: 0.8155
sub_4:Test (Best Model) - Loss: 0.4416 - Accuracy: 0.8452 - F1: 0.8414
sub_10:Test (Best Model) - Loss: 0.3888 - Accuracy: 0.8571 - F1: 0.8568
sub_11:Test (Best Model) - Loss: 0.1375 - Accuracy: 0.9762 - F1: 0.9762
sub_14:Test (Best Model) - Loss: 1.3686 - Accuracy: 0.5000 - F1: 0.3333
sub_5:Test (Best Model) - Loss: 0.7534 - Accuracy: 0.7619 - F1: 0.7504
sub_6:Test (Best Model) - Loss: 0.2951 - Accuracy: 0.8929 - F1: 0.8916
sub_4:Test (Best Model) - Loss: 0.3641 - Accuracy: 0.8690 - F1: 0.8668
sub_9:Test (Best Model) - Loss: 0.3111 - Accuracy: 0.8571 - F1: 0.8542
sub_7:Test (Best Model) - Loss: 0.3834 - Accuracy: 0.8452 - F1: 0.8425
sub_10:Test (Best Model) - Loss: 0.3680 - Accuracy: 0.8452 - F1: 0.8425
sub_1:Test (Best Model) - Loss: 0.1122 - Accuracy: 0.9881 - F1: 0.9881
sub_3:Test (Best Model) - Loss: 0.5583 - Accuracy: 0.7976 - F1: 0.7890
sub_6:Test (Best Model) - Loss: 0.3926 - Accuracy: 0.8690 - F1: 0.8668
sub_5:Test (Best Model) - Loss: 0.2890 - Accuracy: 0.9048 - F1: 0.9045
sub_9:Test (Best Model) - Loss: 0.3113 - Accuracy: 0.8929 - F1: 0.8916
sub_7:Test (Best Model) - Loss: 0.3225 - Accuracy: 0.9048 - F1: 0.9047
sub_1:Test (Best Model) - Loss: 0.0765 - Accuracy: 0.9762 - F1: 0.9762
sub_3:Test (Best Model) - Loss: 0.6350 - Accuracy: 0.7976 - F1: 0.7910
sub_7:Test (Best Model) - Loss: 0.2559 - Accuracy: 0.9167 - F1: 0.9164
sub_5:Test (Best Model) - Loss: 0.5599 - Accuracy: 0.8214 - F1: 0.8155
sub_3:Test (Best Model) - Loss: 0.5650 - Accuracy: 0.7976 - F1: 0.7890
sub_1:Test (Best Model) - Loss: 0.0835 - Accuracy: 0.9762 - F1: 0.9762
sub_5:Test (Best Model) - Loss: 0.3781 - Accuracy: 0.8690 - F1: 0.8686
sub_7:Test (Best Model) - Loss: 0.1942 - Accuracy: 0.9405 - F1: 0.9404
sub_5:Test (Best Model) - Loss: 0.4977 - Accuracy: 0.8452 - F1: 0.8414

=== Summary Results ===

acc: 89.69 ± 4.84
F1: 89.06 ± 5.86
acc-in: 97.89 ± 1.36
F1-in: 97.87 ± 1.39
