lr: 1e-05
sub_11:Test (Best Model) - Loss: 0.1362 - Accuracy: 0.9286 - F1: 0.9284
sub_14:Test (Best Model) - Loss: 0.3537 - Accuracy: 0.8095 - F1: 0.8068
sub_9:Test (Best Model) - Loss: 0.0560 - Accuracy: 1.0000 - F1: 1.0000
sub_13:Test (Best Model) - Loss: 0.3745 - Accuracy: 0.8095 - F1: 0.8041
sub_5:Test (Best Model) - Loss: 0.3067 - Accuracy: 0.8810 - F1: 0.8809
sub_2:Test (Best Model) - Loss: 0.0928 - Accuracy: 0.9762 - F1: 0.9762
sub_8:Test (Best Model) - Loss: 0.0197 - Accuracy: 1.0000 - F1: 1.0000
sub_12:Test (Best Model) - Loss: 0.3397 - Accuracy: 0.8333 - F1: 0.8286
sub_3:Test (Best Model) - Loss: 0.3151 - Accuracy: 0.8333 - F1: 0.8299
sub_4:Test (Best Model) - Loss: 0.1318 - Accuracy: 0.9524 - F1: 0.9524
sub_7:Test (Best Model) - Loss: 0.4463 - Accuracy: 0.7857 - F1: 0.7776
sub_10:Test (Best Model) - Loss: 0.1832 - Accuracy: 0.9286 - F1: 0.9284
sub_1:Test (Best Model) - Loss: 0.1066 - Accuracy: 0.9524 - F1: 0.9523
sub_11:Test (Best Model) - Loss: 0.3220 - Accuracy: 0.8929 - F1: 0.8921
sub_9:Test (Best Model) - Loss: 0.0597 - Accuracy: 0.9762 - F1: 0.9762
sub_5:Test (Best Model) - Loss: 0.4680 - Accuracy: 0.7857 - F1: 0.7776
sub_13:Test (Best Model) - Loss: 0.2559 - Accuracy: 0.8452 - F1: 0.8434
sub_3:Test (Best Model) - Loss: 0.3640 - Accuracy: 0.8452 - F1: 0.8414
sub_8:Test (Best Model) - Loss: 0.1595 - Accuracy: 0.9405 - F1: 0.9404
sub_12:Test (Best Model) - Loss: 0.1855 - Accuracy: 0.9167 - F1: 0.9161
sub_14:Test (Best Model) - Loss: 0.1437 - Accuracy: 0.9405 - F1: 0.9404
sub_4:Test (Best Model) - Loss: 0.2459 - Accuracy: 0.9405 - F1: 0.9403
sub_6:Test (Best Model) - Loss: 0.0446 - Accuracy: 0.9762 - F1: 0.9762
sub_11:Test (Best Model) - Loss: 0.2070 - Accuracy: 0.9167 - F1: 0.9161
sub_1:Test (Best Model) - Loss: 0.3004 - Accuracy: 0.8571 - F1: 0.8542
sub_9:Test (Best Model) - Loss: 0.0483 - Accuracy: 0.9881 - F1: 0.9881
sub_2:Test (Best Model) - Loss: 0.0770 - Accuracy: 0.9881 - F1: 0.9881
sub_8:Test (Best Model) - Loss: 0.0516 - Accuracy: 0.9762 - F1: 0.9762
sub_7:Test (Best Model) - Loss: 0.2042 - Accuracy: 0.9167 - F1: 0.9166
sub_3:Test (Best Model) - Loss: 0.2103 - Accuracy: 0.9167 - F1: 0.9166
sub_13:Test (Best Model) - Loss: 0.1928 - Accuracy: 0.9167 - F1: 0.9164
sub_12:Test (Best Model) - Loss: 0.1150 - Accuracy: 0.9643 - F1: 0.9642
sub_14:Test (Best Model) - Loss: 0.2158 - Accuracy: 0.9167 - F1: 0.9167
sub_11:Test (Best Model) - Loss: 0.2642 - Accuracy: 0.8690 - F1: 0.8668
sub_5:Test (Best Model) - Loss: 0.4335 - Accuracy: 0.8810 - F1: 0.8799
sub_9:Test (Best Model) - Loss: 0.0342 - Accuracy: 0.9881 - F1: 0.9881
sub_4:Test (Best Model) - Loss: 0.1943 - Accuracy: 0.9286 - F1: 0.9285
sub_2:Test (Best Model) - Loss: 0.1785 - Accuracy: 0.9405 - F1: 0.9403
sub_10:Test (Best Model) - Loss: 0.1907 - Accuracy: 0.9167 - F1: 0.9164
sub_8:Test (Best Model) - Loss: 0.0159 - Accuracy: 1.0000 - F1: 1.0000
sub_1:Test (Best Model) - Loss: 0.1484 - Accuracy: 0.9643 - F1: 0.9642
sub_6:Test (Best Model) - Loss: 0.1629 - Accuracy: 0.9286 - F1: 0.9285
sub_12:Test (Best Model) - Loss: 0.2104 - Accuracy: 0.8810 - F1: 0.8792
sub_14:Test (Best Model) - Loss: 0.2026 - Accuracy: 0.9167 - F1: 0.9167
sub_7:Test (Best Model) - Loss: 0.3241 - Accuracy: 0.8452 - F1: 0.8447
sub_11:Test (Best Model) - Loss: 0.1485 - Accuracy: 0.9286 - F1: 0.9282
sub_13:Test (Best Model) - Loss: 0.3012 - Accuracy: 0.8452 - F1: 0.8414
sub_3:Test (Best Model) - Loss: 0.4338 - Accuracy: 0.8214 - F1: 0.8155
sub_2:Test (Best Model) - Loss: 0.0772 - Accuracy: 0.9643 - F1: 0.9643
sub_4:Test (Best Model) - Loss: 0.1874 - Accuracy: 0.9524 - F1: 0.9523
sub_5:Test (Best Model) - Loss: 0.5240 - Accuracy: 0.8452 - F1: 0.8425
sub_10:Test (Best Model) - Loss: 0.3704 - Accuracy: 0.8452 - F1: 0.8434
sub_9:Test (Best Model) - Loss: 0.0075 - Accuracy: 1.0000 - F1: 1.0000
sub_12:Test (Best Model) - Loss: 0.1895 - Accuracy: 0.9048 - F1: 0.9039
sub_11:Test (Best Model) - Loss: 0.3931 - Accuracy: 0.8929 - F1: 0.8916
sub_13:Test (Best Model) - Loss: 0.5334 - Accuracy: 0.7738 - F1: 0.7641
sub_6:Test (Best Model) - Loss: 0.2445 - Accuracy: 0.8690 - F1: 0.8686
sub_1:Test (Best Model) - Loss: 0.0674 - Accuracy: 0.9881 - F1: 0.9881
sub_8:Test (Best Model) - Loss: 0.0463 - Accuracy: 0.9881 - F1: 0.9881
sub_7:Test (Best Model) - Loss: 0.2718 - Accuracy: 0.9167 - F1: 0.9161
sub_2:Test (Best Model) - Loss: 0.0545 - Accuracy: 0.9881 - F1: 0.9881
sub_3:Test (Best Model) - Loss: 0.4422 - Accuracy: 0.8333 - F1: 0.8286
sub_5:Test (Best Model) - Loss: 0.5158 - Accuracy: 0.8214 - F1: 0.8183
sub_13:Test (Best Model) - Loss: 0.1062 - Accuracy: 0.9643 - F1: 0.9642
sub_4:Test (Best Model) - Loss: 0.2299 - Accuracy: 0.9167 - F1: 0.9161
sub_14:Test (Best Model) - Loss: 0.1967 - Accuracy: 0.8929 - F1: 0.8916
sub_11:Test (Best Model) - Loss: 0.1216 - Accuracy: 0.9524 - F1: 0.9523
sub_10:Test (Best Model) - Loss: 0.1129 - Accuracy: 0.9524 - F1: 0.9524
sub_1:Test (Best Model) - Loss: 0.1523 - Accuracy: 0.9524 - F1: 0.9524
sub_8:Test (Best Model) - Loss: 0.0104 - Accuracy: 1.0000 - F1: 1.0000
sub_9:Test (Best Model) - Loss: 0.2721 - Accuracy: 0.8810 - F1: 0.8809
sub_6:Test (Best Model) - Loss: 0.1330 - Accuracy: 0.9524 - F1: 0.9524
sub_12:Test (Best Model) - Loss: 0.2040 - Accuracy: 0.9048 - F1: 0.9043
sub_4:Test (Best Model) - Loss: 0.3053 - Accuracy: 0.8810 - F1: 0.8799
sub_7:Test (Best Model) - Loss: 0.6092 - Accuracy: 0.6905 - F1: 0.6577
sub_2:Test (Best Model) - Loss: 0.4217 - Accuracy: 0.8690 - F1: 0.8668
sub_3:Test (Best Model) - Loss: 0.2002 - Accuracy: 0.9167 - F1: 0.9164
sub_5:Test (Best Model) - Loss: 0.1043 - Accuracy: 0.9524 - F1: 0.9524
sub_9:Test (Best Model) - Loss: 0.2053 - Accuracy: 0.9048 - F1: 0.9039
sub_11:Test (Best Model) - Loss: 0.1868 - Accuracy: 0.9405 - F1: 0.9403
sub_13:Test (Best Model) - Loss: 0.2669 - Accuracy: 0.8929 - F1: 0.8916
sub_7:Test (Best Model) - Loss: 0.1917 - Accuracy: 0.9405 - F1: 0.9405
sub_8:Test (Best Model) - Loss: 0.0113 - Accuracy: 1.0000 - F1: 1.0000
sub_12:Test (Best Model) - Loss: 0.1189 - Accuracy: 0.9643 - F1: 0.9642
sub_14:Test (Best Model) - Loss: 0.0606 - Accuracy: 0.9762 - F1: 0.9762
sub_1:Test (Best Model) - Loss: 0.1798 - Accuracy: 0.9405 - F1: 0.9403
sub_10:Test (Best Model) - Loss: 0.2189 - Accuracy: 0.8929 - F1: 0.8916
sub_9:Test (Best Model) - Loss: 0.1315 - Accuracy: 0.9405 - F1: 0.9403
sub_11:Test (Best Model) - Loss: 0.1096 - Accuracy: 0.9524 - F1: 0.9523
sub_2:Test (Best Model) - Loss: 0.3438 - Accuracy: 0.8929 - F1: 0.8916
sub_6:Test (Best Model) - Loss: 0.0979 - Accuracy: 0.9405 - F1: 0.9404
sub_5:Test (Best Model) - Loss: 0.1195 - Accuracy: 0.9762 - F1: 0.9762
sub_9:Test (Best Model) - Loss: 0.1088 - Accuracy: 0.9524 - F1: 0.9523
sub_8:Test (Best Model) - Loss: 0.0110 - Accuracy: 1.0000 - F1: 1.0000
sub_12:Test (Best Model) - Loss: 0.1790 - Accuracy: 0.9524 - F1: 0.9523
sub_11:Test (Best Model) - Loss: 0.1872 - Accuracy: 0.9167 - F1: 0.9161
sub_3:Test (Best Model) - Loss: 0.1787 - Accuracy: 0.9524 - F1: 0.9524
sub_4:Test (Best Model) - Loss: 0.1109 - Accuracy: 0.9643 - F1: 0.9642
sub_13:Test (Best Model) - Loss: 0.1492 - Accuracy: 0.9643 - F1: 0.9643
sub_14:Test (Best Model) - Loss: 0.0577 - Accuracy: 0.9762 - F1: 0.9762
sub_5:Test (Best Model) - Loss: 0.2195 - Accuracy: 0.9286 - F1: 0.9285
sub_2:Test (Best Model) - Loss: 0.3011 - Accuracy: 0.8810 - F1: 0.8792
sub_7:Test (Best Model) - Loss: 0.2706 - Accuracy: 0.9048 - F1: 0.9039
sub_10:Test (Best Model) - Loss: 0.1048 - Accuracy: 0.9643 - F1: 0.9643
sub_8:Test (Best Model) - Loss: 0.0511 - Accuracy: 0.9643 - F1: 0.9642
sub_1:Test (Best Model) - Loss: 0.2958 - Accuracy: 0.9167 - F1: 0.9161
sub_11:Test (Best Model) - Loss: 0.0947 - Accuracy: 0.9762 - F1: 0.9762
sub_13:Test (Best Model) - Loss: 0.1687 - Accuracy: 0.9405 - F1: 0.9403
sub_9:Test (Best Model) - Loss: 0.1598 - Accuracy: 0.9167 - F1: 0.9164
sub_12:Test (Best Model) - Loss: 0.3524 - Accuracy: 0.8690 - F1: 0.8668
sub_2:Test (Best Model) - Loss: 0.4018 - Accuracy: 0.8571 - F1: 0.8542
sub_14:Test (Best Model) - Loss: 0.2359 - Accuracy: 0.8810 - F1: 0.8792
sub_1:Test (Best Model) - Loss: 0.1721 - Accuracy: 0.9405 - F1: 0.9403
sub_7:Test (Best Model) - Loss: 0.1891 - Accuracy: 0.9286 - F1: 0.9282
sub_6:Test (Best Model) - Loss: 0.1703 - Accuracy: 0.9286 - F1: 0.9282
sub_4:Test (Best Model) - Loss: 0.1077 - Accuracy: 0.9405 - F1: 0.9405
sub_8:Test (Best Model) - Loss: 0.0032 - Accuracy: 1.0000 - F1: 1.0000
sub_10:Test (Best Model) - Loss: 0.0609 - Accuracy: 0.9643 - F1: 0.9643
sub_11:Test (Best Model) - Loss: 0.0711 - Accuracy: 0.9881 - F1: 0.9881
sub_5:Test (Best Model) - Loss: 0.0846 - Accuracy: 0.9643 - F1: 0.9642
sub_9:Test (Best Model) - Loss: 0.4442 - Accuracy: 0.8690 - F1: 0.8668
sub_13:Test (Best Model) - Loss: 0.1437 - Accuracy: 0.9524 - F1: 0.9523
sub_3:Test (Best Model) - Loss: 0.3236 - Accuracy: 0.8690 - F1: 0.8668
sub_12:Test (Best Model) - Loss: 0.1615 - Accuracy: 0.9286 - F1: 0.9282
sub_4:Test (Best Model) - Loss: 0.1509 - Accuracy: 0.9405 - F1: 0.9403
sub_8:Test (Best Model) - Loss: 0.1400 - Accuracy: 0.9286 - F1: 0.9282
sub_13:Test (Best Model) - Loss: 0.1946 - Accuracy: 0.9286 - F1: 0.9282
sub_2:Test (Best Model) - Loss: 0.2912 - Accuracy: 0.9167 - F1: 0.9161
sub_10:Test (Best Model) - Loss: 0.0840 - Accuracy: 0.9524 - F1: 0.9524
sub_1:Test (Best Model) - Loss: 0.2141 - Accuracy: 0.9167 - F1: 0.9161
sub_9:Test (Best Model) - Loss: 0.4240 - Accuracy: 0.8333 - F1: 0.8286
sub_7:Test (Best Model) - Loss: 0.1331 - Accuracy: 0.9524 - F1: 0.9523
sub_6:Test (Best Model) - Loss: 0.3861 - Accuracy: 0.7976 - F1: 0.7974
sub_14:Test (Best Model) - Loss: 0.0832 - Accuracy: 0.9643 - F1: 0.9642
sub_11:Test (Best Model) - Loss: 0.0625 - Accuracy: 0.9762 - F1: 0.9762
sub_12:Test (Best Model) - Loss: 0.2270 - Accuracy: 0.9167 - F1: 0.9166
sub_3:Test (Best Model) - Loss: 0.1238 - Accuracy: 0.9524 - F1: 0.9524
sub_5:Test (Best Model) - Loss: 0.4253 - Accuracy: 0.8452 - F1: 0.8414
sub_2:Test (Best Model) - Loss: 0.1324 - Accuracy: 0.9524 - F1: 0.9523
sub_9:Test (Best Model) - Loss: 0.3272 - Accuracy: 0.8810 - F1: 0.8792
sub_8:Test (Best Model) - Loss: 0.1114 - Accuracy: 0.9762 - F1: 0.9762
sub_13:Test (Best Model) - Loss: 0.1592 - Accuracy: 0.9167 - F1: 0.9161
sub_4:Test (Best Model) - Loss: 0.1885 - Accuracy: 0.9286 - F1: 0.9284
sub_10:Test (Best Model) - Loss: 0.0783 - Accuracy: 0.9643 - F1: 0.9643
sub_14:Test (Best Model) - Loss: 0.0443 - Accuracy: 0.9762 - F1: 0.9762
sub_6:Test (Best Model) - Loss: 0.3058 - Accuracy: 0.8571 - F1: 0.8542
sub_11:Test (Best Model) - Loss: 0.0497 - Accuracy: 0.9881 - F1: 0.9881
sub_1:Test (Best Model) - Loss: 0.3306 - Accuracy: 0.9405 - F1: 0.9403
sub_12:Test (Best Model) - Loss: 0.1457 - Accuracy: 0.9286 - F1: 0.9286
sub_3:Test (Best Model) - Loss: 0.2526 - Accuracy: 0.8929 - F1: 0.8916
sub_2:Test (Best Model) - Loss: 0.0937 - Accuracy: 0.9524 - F1: 0.9524
sub_7:Test (Best Model) - Loss: 0.0816 - Accuracy: 0.9643 - F1: 0.9642
sub_8:Test (Best Model) - Loss: 0.2399 - Accuracy: 0.8929 - F1: 0.8916
sub_13:Test (Best Model) - Loss: 0.0689 - Accuracy: 1.0000 - F1: 1.0000
sub_9:Test (Best Model) - Loss: 0.5354 - Accuracy: 0.8452 - F1: 0.8414
sub_4:Test (Best Model) - Loss: 0.4285 - Accuracy: 0.8214 - F1: 0.8155
sub_11:Test (Best Model) - Loss: 0.0304 - Accuracy: 0.9881 - F1: 0.9881
sub_5:Test (Best Model) - Loss: 0.2597 - Accuracy: 0.8810 - F1: 0.8803
sub_14:Test (Best Model) - Loss: 0.8972 - Accuracy: 0.6548 - F1: 0.6080
sub_1:Test (Best Model) - Loss: 0.1241 - Accuracy: 0.9524 - F1: 0.9523
sub_2:Test (Best Model) - Loss: 0.0552 - Accuracy: 0.9881 - F1: 0.9881
sub_9:Test (Best Model) - Loss: 0.3450 - Accuracy: 0.8929 - F1: 0.8916
sub_3:Test (Best Model) - Loss: 1.1291 - Accuracy: 0.7024 - F1: 0.6735
sub_6:Test (Best Model) - Loss: 0.1835 - Accuracy: 0.9286 - F1: 0.9282
sub_10:Test (Best Model) - Loss: 0.0590 - Accuracy: 0.9762 - F1: 0.9762
sub_12:Test (Best Model) - Loss: 0.2273 - Accuracy: 0.9167 - F1: 0.9166
sub_8:Test (Best Model) - Loss: 0.1626 - Accuracy: 0.9167 - F1: 0.9161
sub_7:Test (Best Model) - Loss: 0.2302 - Accuracy: 0.9167 - F1: 0.9167
sub_1:Test (Best Model) - Loss: 0.2900 - Accuracy: 0.8929 - F1: 0.8921
sub_14:Test (Best Model) - Loss: 0.6445 - Accuracy: 0.7262 - F1: 0.7040
sub_4:Test (Best Model) - Loss: 0.3521 - Accuracy: 0.8810 - F1: 0.8792
sub_13:Test (Best Model) - Loss: 0.0584 - Accuracy: 0.9762 - F1: 0.9762
sub_10:Test (Best Model) - Loss: 1.2905 - Accuracy: 0.5833 - F1: 0.4958
sub_3:Test (Best Model) - Loss: 0.6134 - Accuracy: 0.7619 - F1: 0.7504
sub_5:Test (Best Model) - Loss: 0.2301 - Accuracy: 0.9167 - F1: 0.9164
sub_2:Test (Best Model) - Loss: 0.0943 - Accuracy: 0.9762 - F1: 0.9762
sub_8:Test (Best Model) - Loss: 0.1505 - Accuracy: 0.9524 - F1: 0.9523
sub_14:Test (Best Model) - Loss: 0.4335 - Accuracy: 0.8571 - F1: 0.8542
sub_12:Test (Best Model) - Loss: 0.2692 - Accuracy: 0.8929 - F1: 0.8927
sub_3:Test (Best Model) - Loss: 0.4560 - Accuracy: 0.7857 - F1: 0.7754
sub_13:Test (Best Model) - Loss: 0.0699 - Accuracy: 0.9762 - F1: 0.9762
sub_1:Test (Best Model) - Loss: 0.1071 - Accuracy: 0.9762 - F1: 0.9762
sub_6:Test (Best Model) - Loss: 0.2601 - Accuracy: 0.8810 - F1: 0.8792
sub_7:Test (Best Model) - Loss: 0.2364 - Accuracy: 0.9048 - F1: 0.9043
sub_4:Test (Best Model) - Loss: 0.2515 - Accuracy: 0.9167 - F1: 0.9161
sub_2:Test (Best Model) - Loss: 0.0910 - Accuracy: 0.9643 - F1: 0.9643
sub_5:Test (Best Model) - Loss: 0.1126 - Accuracy: 0.9643 - F1: 0.9643
sub_14:Test (Best Model) - Loss: 0.7875 - Accuracy: 0.6786 - F1: 0.6415
sub_12:Test (Best Model) - Loss: 0.3243 - Accuracy: 0.8690 - F1: 0.8686
sub_1:Test (Best Model) - Loss: 0.2700 - Accuracy: 0.9048 - F1: 0.9047
sub_3:Test (Best Model) - Loss: 0.6667 - Accuracy: 0.7381 - F1: 0.7224
sub_7:Test (Best Model) - Loss: 0.8743 - Accuracy: 0.6071 - F1: 0.5354
sub_10:Test (Best Model) - Loss: 0.7112 - Accuracy: 0.6548 - F1: 0.6080
sub_4:Test (Best Model) - Loss: 0.3673 - Accuracy: 0.8690 - F1: 0.8668
sub_1:Test (Best Model) - Loss: 0.2237 - Accuracy: 0.9048 - F1: 0.9039
sub_3:Test (Best Model) - Loss: 0.6211 - Accuracy: 0.7619 - F1: 0.7504
sub_14:Test (Best Model) - Loss: 0.8361 - Accuracy: 0.7500 - F1: 0.7333
sub_7:Test (Best Model) - Loss: 0.2570 - Accuracy: 0.8810 - F1: 0.8807
sub_10:Test (Best Model) - Loss: 0.1770 - Accuracy: 0.9286 - F1: 0.9284
sub_5:Test (Best Model) - Loss: 0.1676 - Accuracy: 0.9286 - F1: 0.9286
sub_6:Test (Best Model) - Loss: 0.2425 - Accuracy: 0.8690 - F1: 0.8675
sub_4:Test (Best Model) - Loss: 0.5108 - Accuracy: 0.8571 - F1: 0.8542
sub_5:Test (Best Model) - Loss: 0.2881 - Accuracy: 0.8690 - F1: 0.8690
sub_10:Test (Best Model) - Loss: 0.5580 - Accuracy: 0.7143 - F1: 0.6889
sub_7:Test (Best Model) - Loss: 0.3008 - Accuracy: 0.9167 - F1: 0.9161
sub_6:Test (Best Model) - Loss: 0.2057 - Accuracy: 0.9524 - F1: 0.9524
sub_10:Test (Best Model) - Loss: 0.3780 - Accuracy: 0.8452 - F1: 0.8414
sub_6:Test (Best Model) - Loss: 0.3762 - Accuracy: 0.8214 - F1: 0.8202
sub_6:Test (Best Model) - Loss: 0.4279 - Accuracy: 0.8095 - F1: 0.8024
sub_6:Test (Best Model) - Loss: 0.1938 - Accuracy: 0.9167 - F1: 0.9164

=== Summary Results ===

acc: 90.56 ± 3.45
F1: 90.25 ± 3.74
acc-in: 96.52 ± 2.01
F1-in: 96.45 ± 2.10
