lr: 1e-05
sub_8:Test (Best Model) - Loss: 0.0814 - Accuracy: 0.9762 - F1: 0.9762
sub_9:Test (Best Model) - Loss: 0.2449 - Accuracy: 0.8452 - F1: 0.8434
sub_3:Test (Best Model) - Loss: 0.2354 - Accuracy: 0.9048 - F1: 0.9045
sub_12:Test (Best Model) - Loss: 0.3931 - Accuracy: 0.7619 - F1: 0.7476
sub_11:Test (Best Model) - Loss: 0.1930 - Accuracy: 0.9286 - F1: 0.9282
sub_13:Test (Best Model) - Loss: 0.3184 - Accuracy: 0.8690 - F1: 0.8675
sub_5:Test (Best Model) - Loss: 0.4392 - Accuracy: 0.7976 - F1: 0.7976
sub_2:Test (Best Model) - Loss: 0.0875 - Accuracy: 0.9762 - F1: 0.9762
sub_7:Test (Best Model) - Loss: 0.5603 - Accuracy: 0.7024 - F1: 0.6783
sub_10:Test (Best Model) - Loss: 0.1839 - Accuracy: 0.9048 - F1: 0.9047
sub_14:Test (Best Model) - Loss: 0.4522 - Accuracy: 0.7857 - F1: 0.7838
sub_8:Test (Best Model) - Loss: 0.1334 - Accuracy: 0.9524 - F1: 0.9524
sub_4:Test (Best Model) - Loss: 0.1566 - Accuracy: 0.9524 - F1: 0.9523
sub_1:Test (Best Model) - Loss: 0.1184 - Accuracy: 0.9643 - F1: 0.9643
sub_6:Test (Best Model) - Loss: 0.1294 - Accuracy: 0.9524 - F1: 0.9524
sub_3:Test (Best Model) - Loss: 0.2880 - Accuracy: 0.8929 - F1: 0.8916
sub_11:Test (Best Model) - Loss: 0.3014 - Accuracy: 0.8810 - F1: 0.8799
sub_12:Test (Best Model) - Loss: 0.1449 - Accuracy: 0.9762 - F1: 0.9762
sub_9:Test (Best Model) - Loss: 0.1470 - Accuracy: 0.9286 - F1: 0.9282
sub_13:Test (Best Model) - Loss: 0.3298 - Accuracy: 0.8452 - F1: 0.8425
sub_2:Test (Best Model) - Loss: 0.1072 - Accuracy: 0.9643 - F1: 0.9642
sub_7:Test (Best Model) - Loss: 0.2534 - Accuracy: 0.9286 - F1: 0.9284
sub_5:Test (Best Model) - Loss: 0.3914 - Accuracy: 0.8214 - F1: 0.8214
sub_11:Test (Best Model) - Loss: 0.1909 - Accuracy: 0.9286 - F1: 0.9282
sub_8:Test (Best Model) - Loss: 0.0635 - Accuracy: 0.9762 - F1: 0.9762
sub_4:Test (Best Model) - Loss: 0.3163 - Accuracy: 0.8690 - F1: 0.8689
sub_14:Test (Best Model) - Loss: 0.2650 - Accuracy: 0.9048 - F1: 0.9043
sub_3:Test (Best Model) - Loss: 0.2067 - Accuracy: 0.8929 - F1: 0.8925
sub_9:Test (Best Model) - Loss: 0.0655 - Accuracy: 0.9881 - F1: 0.9881
sub_12:Test (Best Model) - Loss: 0.1449 - Accuracy: 0.9286 - F1: 0.9282
sub_1:Test (Best Model) - Loss: 0.4235 - Accuracy: 0.7976 - F1: 0.7890
sub_2:Test (Best Model) - Loss: 0.2940 - Accuracy: 0.8690 - F1: 0.8668
sub_10:Test (Best Model) - Loss: 0.2150 - Accuracy: 0.9048 - F1: 0.9045
sub_11:Test (Best Model) - Loss: 0.3136 - Accuracy: 0.8810 - F1: 0.8792
sub_8:Test (Best Model) - Loss: 0.0533 - Accuracy: 0.9762 - F1: 0.9762
sub_5:Test (Best Model) - Loss: 0.4797 - Accuracy: 0.8571 - F1: 0.8564
sub_13:Test (Best Model) - Loss: 0.2064 - Accuracy: 0.9048 - F1: 0.9043
sub_6:Test (Best Model) - Loss: 0.2215 - Accuracy: 0.9048 - F1: 0.9047
sub_4:Test (Best Model) - Loss: 0.3561 - Accuracy: 0.8810 - F1: 0.8810
sub_9:Test (Best Model) - Loss: 0.1090 - Accuracy: 0.9762 - F1: 0.9762
sub_14:Test (Best Model) - Loss: 0.3497 - Accuracy: 0.8690 - F1: 0.8689
sub_7:Test (Best Model) - Loss: 0.4336 - Accuracy: 0.8333 - F1: 0.8330
sub_10:Test (Best Model) - Loss: 0.4095 - Accuracy: 0.8452 - F1: 0.8434
sub_11:Test (Best Model) - Loss: 0.2181 - Accuracy: 0.9524 - F1: 0.9523
sub_3:Test (Best Model) - Loss: 0.3838 - Accuracy: 0.8690 - F1: 0.8675
sub_12:Test (Best Model) - Loss: 0.1731 - Accuracy: 0.9167 - F1: 0.9161
sub_5:Test (Best Model) - Loss: 0.4802 - Accuracy: 0.8095 - F1: 0.8078
sub_8:Test (Best Model) - Loss: 0.0742 - Accuracy: 0.9643 - F1: 0.9643
sub_13:Test (Best Model) - Loss: 0.2767 - Accuracy: 0.9167 - F1: 0.9167
sub_1:Test (Best Model) - Loss: 0.1084 - Accuracy: 0.9762 - F1: 0.9762
sub_9:Test (Best Model) - Loss: 0.0198 - Accuracy: 1.0000 - F1: 1.0000
sub_6:Test (Best Model) - Loss: 0.2080 - Accuracy: 0.8810 - F1: 0.8809
sub_11:Test (Best Model) - Loss: 0.3754 - Accuracy: 0.8810 - F1: 0.8792
sub_14:Test (Best Model) - Loss: 0.3696 - Accuracy: 0.8333 - F1: 0.8325
sub_7:Test (Best Model) - Loss: 0.3656 - Accuracy: 0.8690 - F1: 0.8675
sub_4:Test (Best Model) - Loss: 0.2387 - Accuracy: 0.9167 - F1: 0.9161
sub_2:Test (Best Model) - Loss: 0.0636 - Accuracy: 0.9881 - F1: 0.9881
sub_12:Test (Best Model) - Loss: 0.1841 - Accuracy: 0.9167 - F1: 0.9161
sub_10:Test (Best Model) - Loss: 0.1972 - Accuracy: 0.9048 - F1: 0.9047
sub_13:Test (Best Model) - Loss: 0.5740 - Accuracy: 0.7143 - F1: 0.6932
sub_8:Test (Best Model) - Loss: 0.0252 - Accuracy: 0.9881 - F1: 0.9881
sub_3:Test (Best Model) - Loss: 0.5139 - Accuracy: 0.8452 - F1: 0.8414
sub_6:Test (Best Model) - Loss: 0.1385 - Accuracy: 0.9881 - F1: 0.9881
sub_5:Test (Best Model) - Loss: 0.4543 - Accuracy: 0.8452 - F1: 0.8442
sub_9:Test (Best Model) - Loss: 0.4375 - Accuracy: 0.8214 - F1: 0.8208
sub_11:Test (Best Model) - Loss: 0.1745 - Accuracy: 0.9405 - F1: 0.9403
sub_14:Test (Best Model) - Loss: 0.2601 - Accuracy: 0.8810 - F1: 0.8792
sub_1:Test (Best Model) - Loss: 0.1226 - Accuracy: 0.9643 - F1: 0.9642
sub_5:Test (Best Model) - Loss: 0.2349 - Accuracy: 0.8810 - F1: 0.8803
sub_4:Test (Best Model) - Loss: 0.2989 - Accuracy: 0.8929 - F1: 0.8921
sub_13:Test (Best Model) - Loss: 0.1236 - Accuracy: 0.9524 - F1: 0.9524
sub_10:Test (Best Model) - Loss: 0.2689 - Accuracy: 0.8571 - F1: 0.8551
sub_12:Test (Best Model) - Loss: 0.2484 - Accuracy: 0.8810 - F1: 0.8809
sub_2:Test (Best Model) - Loss: 0.1012 - Accuracy: 0.9524 - F1: 0.9524
sub_7:Test (Best Model) - Loss: 0.9179 - Accuracy: 0.6548 - F1: 0.6080
sub_8:Test (Best Model) - Loss: 0.0303 - Accuracy: 0.9762 - F1: 0.9762
sub_3:Test (Best Model) - Loss: 0.1953 - Accuracy: 0.9167 - F1: 0.9164
sub_11:Test (Best Model) - Loss: 0.1799 - Accuracy: 0.9286 - F1: 0.9282
sub_9:Test (Best Model) - Loss: 0.2731 - Accuracy: 0.8929 - F1: 0.8916
sub_6:Test (Best Model) - Loss: 0.1199 - Accuracy: 0.9643 - F1: 0.9642
sub_14:Test (Best Model) - Loss: 0.1562 - Accuracy: 0.9405 - F1: 0.9403
sub_4:Test (Best Model) - Loss: 0.5624 - Accuracy: 0.7857 - F1: 0.7838
sub_1:Test (Best Model) - Loss: 0.1577 - Accuracy: 0.9524 - F1: 0.9524
sub_13:Test (Best Model) - Loss: 0.2184 - Accuracy: 0.9286 - F1: 0.9282
sub_2:Test (Best Model) - Loss: 0.3066 - Accuracy: 0.8810 - F1: 0.8792
sub_11:Test (Best Model) - Loss: 0.1334 - Accuracy: 0.9167 - F1: 0.9161
sub_12:Test (Best Model) - Loss: 0.1419 - Accuracy: 0.9405 - F1: 0.9404
sub_5:Test (Best Model) - Loss: 0.2263 - Accuracy: 0.9048 - F1: 0.9039
sub_9:Test (Best Model) - Loss: 0.1633 - Accuracy: 0.8929 - F1: 0.8925
sub_8:Test (Best Model) - Loss: 0.0298 - Accuracy: 0.9881 - F1: 0.9881
sub_3:Test (Best Model) - Loss: 0.1523 - Accuracy: 0.9286 - F1: 0.9282
sub_10:Test (Best Model) - Loss: 0.1500 - Accuracy: 0.9643 - F1: 0.9643
sub_7:Test (Best Model) - Loss: 0.1290 - Accuracy: 0.9405 - F1: 0.9405
sub_11:Test (Best Model) - Loss: 0.2050 - Accuracy: 0.9167 - F1: 0.9161
sub_13:Test (Best Model) - Loss: 0.1360 - Accuracy: 0.9524 - F1: 0.9524
sub_1:Test (Best Model) - Loss: 0.2542 - Accuracy: 0.9048 - F1: 0.9039
sub_9:Test (Best Model) - Loss: 0.1583 - Accuracy: 0.9643 - F1: 0.9642
sub_12:Test (Best Model) - Loss: 0.2258 - Accuracy: 0.8929 - F1: 0.8925
sub_8:Test (Best Model) - Loss: 0.0713 - Accuracy: 0.9762 - F1: 0.9762
sub_6:Test (Best Model) - Loss: 0.3680 - Accuracy: 0.8810 - F1: 0.8792
sub_5:Test (Best Model) - Loss: 0.1843 - Accuracy: 0.9524 - F1: 0.9524
sub_14:Test (Best Model) - Loss: 0.0698 - Accuracy: 0.9643 - F1: 0.9642
sub_2:Test (Best Model) - Loss: 0.2045 - Accuracy: 0.9405 - F1: 0.9403
sub_4:Test (Best Model) - Loss: 0.3773 - Accuracy: 0.8929 - F1: 0.8927
sub_11:Test (Best Model) - Loss: 0.0846 - Accuracy: 0.9881 - F1: 0.9881
sub_3:Test (Best Model) - Loss: 0.3833 - Accuracy: 0.8452 - F1: 0.8434
sub_13:Test (Best Model) - Loss: 0.1392 - Accuracy: 0.9524 - F1: 0.9523
sub_9:Test (Best Model) - Loss: 0.2037 - Accuracy: 0.8571 - F1: 0.8542
sub_10:Test (Best Model) - Loss: 0.0799 - Accuracy: 0.9643 - F1: 0.9643
sub_1:Test (Best Model) - Loss: 0.2789 - Accuracy: 0.9167 - F1: 0.9161
sub_6:Test (Best Model) - Loss: 0.3910 - Accuracy: 0.7976 - F1: 0.7976
sub_8:Test (Best Model) - Loss: 0.0114 - Accuracy: 1.0000 - F1: 1.0000
sub_2:Test (Best Model) - Loss: 0.2180 - Accuracy: 0.9286 - F1: 0.9282
sub_5:Test (Best Model) - Loss: 0.1860 - Accuracy: 0.9524 - F1: 0.9523
sub_7:Test (Best Model) - Loss: 0.2294 - Accuracy: 0.9286 - F1: 0.9284
sub_12:Test (Best Model) - Loss: 0.3224 - Accuracy: 0.8571 - F1: 0.8551
sub_11:Test (Best Model) - Loss: 0.1059 - Accuracy: 0.9881 - F1: 0.9881
sub_13:Test (Best Model) - Loss: 0.2839 - Accuracy: 0.8690 - F1: 0.8675
sub_14:Test (Best Model) - Loss: 0.3208 - Accuracy: 0.8452 - F1: 0.8414
sub_3:Test (Best Model) - Loss: 0.2194 - Accuracy: 0.8810 - F1: 0.8792
sub_8:Test (Best Model) - Loss: 0.2010 - Accuracy: 0.9643 - F1: 0.9642
sub_9:Test (Best Model) - Loss: 0.5320 - Accuracy: 0.8333 - F1: 0.8299
sub_4:Test (Best Model) - Loss: 0.2451 - Accuracy: 0.9167 - F1: 0.9166
sub_1:Test (Best Model) - Loss: 0.2470 - Accuracy: 0.9167 - F1: 0.9161
sub_10:Test (Best Model) - Loss: 0.1023 - Accuracy: 0.9524 - F1: 0.9524
sub_11:Test (Best Model) - Loss: 0.2422 - Accuracy: 0.8929 - F1: 0.8921
sub_2:Test (Best Model) - Loss: 0.2420 - Accuracy: 0.8929 - F1: 0.8916
sub_6:Test (Best Model) - Loss: 0.3736 - Accuracy: 0.8095 - F1: 0.8024
sub_12:Test (Best Model) - Loss: 0.2176 - Accuracy: 0.9048 - F1: 0.9043
sub_5:Test (Best Model) - Loss: 0.4020 - Accuracy: 0.8452 - F1: 0.8414
sub_7:Test (Best Model) - Loss: 0.2264 - Accuracy: 0.8929 - F1: 0.8925
sub_3:Test (Best Model) - Loss: 0.2334 - Accuracy: 0.8810 - F1: 0.8799
sub_13:Test (Best Model) - Loss: 0.2228 - Accuracy: 0.9286 - F1: 0.9282
sub_9:Test (Best Model) - Loss: 0.5676 - Accuracy: 0.7738 - F1: 0.7641
sub_4:Test (Best Model) - Loss: 0.2449 - Accuracy: 0.8810 - F1: 0.8807
sub_14:Test (Best Model) - Loss: 0.1211 - Accuracy: 0.9643 - F1: 0.9642
sub_1:Test (Best Model) - Loss: 0.2331 - Accuracy: 0.9167 - F1: 0.9161
sub_8:Test (Best Model) - Loss: 0.1712 - Accuracy: 0.9524 - F1: 0.9523
sub_11:Test (Best Model) - Loss: 0.1408 - Accuracy: 0.9643 - F1: 0.9643
sub_12:Test (Best Model) - Loss: 0.3231 - Accuracy: 0.8810 - F1: 0.8799
sub_10:Test (Best Model) - Loss: 0.1423 - Accuracy: 0.9524 - F1: 0.9524
sub_2:Test (Best Model) - Loss: 0.1745 - Accuracy: 0.9286 - F1: 0.9282
sub_6:Test (Best Model) - Loss: 0.3466 - Accuracy: 0.8214 - F1: 0.8170
sub_7:Test (Best Model) - Loss: 0.1861 - Accuracy: 0.9048 - F1: 0.9043
sub_3:Test (Best Model) - Loss: 1.1093 - Accuracy: 0.6429 - F1: 0.5906
sub_5:Test (Best Model) - Loss: 0.2663 - Accuracy: 0.9048 - F1: 0.9047
sub_13:Test (Best Model) - Loss: 0.1457 - Accuracy: 0.9048 - F1: 0.9039
sub_9:Test (Best Model) - Loss: 0.3662 - Accuracy: 0.8690 - F1: 0.8668
sub_8:Test (Best Model) - Loss: 0.2213 - Accuracy: 0.9286 - F1: 0.9282
sub_14:Test (Best Model) - Loss: 0.0964 - Accuracy: 0.9643 - F1: 0.9642
sub_4:Test (Best Model) - Loss: 0.4495 - Accuracy: 0.8810 - F1: 0.8803
sub_12:Test (Best Model) - Loss: 0.2562 - Accuracy: 0.9167 - F1: 0.9167
sub_11:Test (Best Model) - Loss: 0.0433 - Accuracy: 0.9881 - F1: 0.9881
sub_2:Test (Best Model) - Loss: 0.1860 - Accuracy: 0.9167 - F1: 0.9164
sub_1:Test (Best Model) - Loss: 0.3868 - Accuracy: 0.8810 - F1: 0.8792
sub_10:Test (Best Model) - Loss: 0.2028 - Accuracy: 0.9286 - F1: 0.9284
sub_6:Test (Best Model) - Loss: 0.2484 - Accuracy: 0.8810 - F1: 0.8792
sub_9:Test (Best Model) - Loss: 0.6076 - Accuracy: 0.7857 - F1: 0.7754
sub_12:Test (Best Model) - Loss: 0.3240 - Accuracy: 0.8690 - F1: 0.8686
sub_3:Test (Best Model) - Loss: 0.7458 - Accuracy: 0.7381 - F1: 0.7188
sub_5:Test (Best Model) - Loss: 0.3402 - Accuracy: 0.8571 - F1: 0.8571
sub_13:Test (Best Model) - Loss: 0.0591 - Accuracy: 1.0000 - F1: 1.0000
sub_8:Test (Best Model) - Loss: 0.1314 - Accuracy: 0.9762 - F1: 0.9762
sub_4:Test (Best Model) - Loss: 0.5973 - Accuracy: 0.7857 - F1: 0.7754
sub_2:Test (Best Model) - Loss: 0.1767 - Accuracy: 0.9167 - F1: 0.9164
sub_9:Test (Best Model) - Loss: 0.4031 - Accuracy: 0.8333 - F1: 0.8286
sub_10:Test (Best Model) - Loss: 1.2177 - Accuracy: 0.5952 - F1: 0.5159
sub_7:Test (Best Model) - Loss: 0.1038 - Accuracy: 0.9643 - F1: 0.9643
sub_1:Test (Best Model) - Loss: 0.0805 - Accuracy: 0.9643 - F1: 0.9642
sub_6:Test (Best Model) - Loss: 0.2085 - Accuracy: 0.9167 - F1: 0.9166
sub_8:Test (Best Model) - Loss: 0.1442 - Accuracy: 0.9405 - F1: 0.9405
sub_12:Test (Best Model) - Loss: 0.4411 - Accuracy: 0.8333 - F1: 0.8309
sub_14:Test (Best Model) - Loss: 0.9370 - Accuracy: 0.6071 - F1: 0.5354
sub_13:Test (Best Model) - Loss: 0.1083 - Accuracy: 0.9762 - F1: 0.9762
sub_4:Test (Best Model) - Loss: 0.3528 - Accuracy: 0.8690 - F1: 0.8675
sub_5:Test (Best Model) - Loss: 0.2927 - Accuracy: 0.8929 - F1: 0.8925
sub_3:Test (Best Model) - Loss: 0.6848 - Accuracy: 0.7381 - F1: 0.7188
sub_10:Test (Best Model) - Loss: 0.7096 - Accuracy: 0.6786 - F1: 0.6415
sub_2:Test (Best Model) - Loss: 0.1536 - Accuracy: 0.9286 - F1: 0.9284
sub_7:Test (Best Model) - Loss: 0.3596 - Accuracy: 0.7976 - F1: 0.7976
sub_13:Test (Best Model) - Loss: 0.1124 - Accuracy: 0.9524 - F1: 0.9523
sub_12:Test (Best Model) - Loss: 0.6097 - Accuracy: 0.8214 - F1: 0.8183
sub_1:Test (Best Model) - Loss: 0.2330 - Accuracy: 0.9048 - F1: 0.9043
sub_14:Test (Best Model) - Loss: 0.7967 - Accuracy: 0.7143 - F1: 0.6889
sub_5:Test (Best Model) - Loss: 0.2505 - Accuracy: 0.9048 - F1: 0.9048
sub_3:Test (Best Model) - Loss: 0.6672 - Accuracy: 0.7262 - F1: 0.7079
sub_10:Test (Best Model) - Loss: 0.2402 - Accuracy: 0.9048 - F1: 0.9039
sub_2:Test (Best Model) - Loss: 0.1513 - Accuracy: 0.9405 - F1: 0.9405
sub_6:Test (Best Model) - Loss: 0.0646 - Accuracy: 0.9881 - F1: 0.9881
sub_4:Test (Best Model) - Loss: 0.2849 - Accuracy: 0.9286 - F1: 0.9282
sub_14:Test (Best Model) - Loss: 0.7385 - Accuracy: 0.6667 - F1: 0.6250
sub_7:Test (Best Model) - Loss: 0.3151 - Accuracy: 0.8690 - F1: 0.8675
sub_5:Test (Best Model) - Loss: 0.3607 - Accuracy: 0.8571 - F1: 0.8571
sub_3:Test (Best Model) - Loss: 0.6525 - Accuracy: 0.7262 - F1: 0.7040
sub_1:Test (Best Model) - Loss: 0.0854 - Accuracy: 0.9762 - F1: 0.9762
sub_10:Test (Best Model) - Loss: 0.6348 - Accuracy: 0.7024 - F1: 0.6735
sub_2:Test (Best Model) - Loss: 0.1483 - Accuracy: 0.9405 - F1: 0.9405
sub_4:Test (Best Model) - Loss: 0.4272 - Accuracy: 0.8810 - F1: 0.8792
sub_14:Test (Best Model) - Loss: 0.6970 - Accuracy: 0.6786 - F1: 0.6415
sub_7:Test (Best Model) - Loss: 0.8065 - Accuracy: 0.6548 - F1: 0.6080
sub_1:Test (Best Model) - Loss: 0.2439 - Accuracy: 0.8929 - F1: 0.8925
sub_6:Test (Best Model) - Loss: 0.3287 - Accuracy: 0.8571 - F1: 0.8542
sub_10:Test (Best Model) - Loss: 0.4374 - Accuracy: 0.7976 - F1: 0.7890
sub_1:Test (Best Model) - Loss: 0.3694 - Accuracy: 0.8333 - F1: 0.8286
sub_4:Test (Best Model) - Loss: 0.7209 - Accuracy: 0.7381 - F1: 0.7188
sub_7:Test (Best Model) - Loss: 0.3473 - Accuracy: 0.8333 - F1: 0.8286
sub_14:Test (Best Model) - Loss: 0.4952 - Accuracy: 0.8095 - F1: 0.8024
sub_6:Test (Best Model) - Loss: 0.1348 - Accuracy: 0.9286 - F1: 0.9282
sub_7:Test (Best Model) - Loss: 0.3477 - Accuracy: 0.8810 - F1: 0.8809
sub_6:Test (Best Model) - Loss: 0.2409 - Accuracy: 0.8690 - F1: 0.8681

=== Summary Results ===

acc: 88.78 ± 3.99
F1: 88.39 ± 4.35
acc-in: 95.32 ± 2.17
F1-in: 95.26 ± 2.23
