lr: 1e-06
sub_6:Test (Best Model) - Loss: 1.7344 - Accuracy: 0.2048 - F1: 0.1488
sub_5:Test (Best Model) - Loss: 1.6987 - Accuracy: 0.2000 - F1: 0.1583
sub_1:Test (Best Model) - Loss: 1.6429 - Accuracy: 0.2381 - F1: 0.2133
sub_4:Test (Best Model) - Loss: 1.7755 - Accuracy: 0.2000 - F1: 0.1720
sub_14:Test (Best Model) - Loss: 1.5913 - Accuracy: 0.2667 - F1: 0.2728
sub_6:Test (Best Model) - Loss: 1.7558 - Accuracy: 0.1571 - F1: 0.1414
sub_2:Test (Best Model) - Loss: 1.6295 - Accuracy: 0.3095 - F1: 0.2506
sub_12:Test (Best Model) - Loss: 1.6366 - Accuracy: 0.2571 - F1: 0.2434
sub_7:Test (Best Model) - Loss: 1.6385 - Accuracy: 0.2857 - F1: 0.2499
sub_4:Test (Best Model) - Loss: 1.8675 - Accuracy: 0.1667 - F1: 0.1501
sub_5:Test (Best Model) - Loss: 1.7716 - Accuracy: 0.2048 - F1: 0.1636
sub_1:Test (Best Model) - Loss: 1.7286 - Accuracy: 0.2333 - F1: 0.1774
sub_6:Test (Best Model) - Loss: 1.8687 - Accuracy: 0.1619 - F1: 0.1051
sub_3:Test (Best Model) - Loss: 1.6666 - Accuracy: 0.2048 - F1: 0.1963
sub_2:Test (Best Model) - Loss: 1.9173 - Accuracy: 0.1333 - F1: 0.0711
sub_8:Test (Best Model) - Loss: 1.4862 - Accuracy: 0.3381 - F1: 0.2802
sub_6:Test (Best Model) - Loss: 1.7284 - Accuracy: 0.2048 - F1: 0.1696
sub_14:Test (Best Model) - Loss: 1.6783 - Accuracy: 0.2286 - F1: 0.2104
sub_10:Test (Best Model) - Loss: 1.5397 - Accuracy: 0.3524 - F1: 0.3260
sub_13:Test (Best Model) - Loss: 1.5876 - Accuracy: 0.2381 - F1: 0.2105
sub_2:Test (Best Model) - Loss: 1.7539 - Accuracy: 0.1857 - F1: 0.1583
sub_5:Test (Best Model) - Loss: 1.9136 - Accuracy: 0.1905 - F1: 0.1409
sub_1:Test (Best Model) - Loss: 1.9376 - Accuracy: 0.2190 - F1: 0.1337
sub_3:Test (Best Model) - Loss: 1.7313 - Accuracy: 0.1857 - F1: 0.1083
sub_11:Test (Best Model) - Loss: 1.5690 - Accuracy: 0.3524 - F1: 0.3095
sub_4:Test (Best Model) - Loss: 1.8288 - Accuracy: 0.1714 - F1: 0.1375
sub_10:Test (Best Model) - Loss: 1.7498 - Accuracy: 0.2143 - F1: 0.1601
sub_9:Test (Best Model) - Loss: 1.6546 - Accuracy: 0.2952 - F1: 0.2397
sub_8:Test (Best Model) - Loss: 1.6724 - Accuracy: 0.2619 - F1: 0.2296
sub_13:Test (Best Model) - Loss: 1.8924 - Accuracy: 0.1952 - F1: 0.1151
sub_12:Test (Best Model) - Loss: 1.5912 - Accuracy: 0.2571 - F1: 0.2316
sub_14:Test (Best Model) - Loss: 1.7662 - Accuracy: 0.2238 - F1: 0.1980
sub_5:Test (Best Model) - Loss: 1.7473 - Accuracy: 0.2286 - F1: 0.2187
sub_6:Test (Best Model) - Loss: 1.7221 - Accuracy: 0.2333 - F1: 0.2002
sub_4:Test (Best Model) - Loss: 1.7206 - Accuracy: 0.2286 - F1: 0.1751
sub_10:Test (Best Model) - Loss: 1.7480 - Accuracy: 0.2571 - F1: 0.2373
sub_7:Test (Best Model) - Loss: 1.6926 - Accuracy: 0.2238 - F1: 0.1656
sub_3:Test (Best Model) - Loss: 1.7799 - Accuracy: 0.1905 - F1: 0.0899
sub_11:Test (Best Model) - Loss: 1.6868 - Accuracy: 0.1667 - F1: 0.1423
sub_9:Test (Best Model) - Loss: 1.7768 - Accuracy: 0.2190 - F1: 0.1276
sub_12:Test (Best Model) - Loss: 1.8636 - Accuracy: 0.1524 - F1: 0.1111
sub_6:Test (Best Model) - Loss: 1.8768 - Accuracy: 0.2286 - F1: 0.1737
sub_13:Test (Best Model) - Loss: 1.8182 - Accuracy: 0.2190 - F1: 0.1626
sub_8:Test (Best Model) - Loss: 1.7917 - Accuracy: 0.2095 - F1: 0.1466
sub_2:Test (Best Model) - Loss: 1.6301 - Accuracy: 0.2762 - F1: 0.1986
sub_11:Test (Best Model) - Loss: 1.6552 - Accuracy: 0.2619 - F1: 0.2145
sub_10:Test (Best Model) - Loss: 1.7045 - Accuracy: 0.2762 - F1: 0.1998
sub_14:Test (Best Model) - Loss: 1.5338 - Accuracy: 0.3190 - F1: 0.2618
sub_3:Test (Best Model) - Loss: 1.9226 - Accuracy: 0.2619 - F1: 0.1497
sub_7:Test (Best Model) - Loss: 1.7681 - Accuracy: 0.2000 - F1: 0.1509
sub_6:Test (Best Model) - Loss: 1.9832 - Accuracy: 0.2143 - F1: 0.1380
sub_4:Test (Best Model) - Loss: 1.7075 - Accuracy: 0.1429 - F1: 0.1216
sub_1:Test (Best Model) - Loss: 1.6776 - Accuracy: 0.2762 - F1: 0.2061
sub_5:Test (Best Model) - Loss: 1.6255 - Accuracy: 0.2905 - F1: 0.2300
sub_2:Test (Best Model) - Loss: 1.5064 - Accuracy: 0.3667 - F1: 0.3198
sub_13:Test (Best Model) - Loss: 1.7196 - Accuracy: 0.2476 - F1: 0.1853
sub_3:Test (Best Model) - Loss: 1.8162 - Accuracy: 0.1762 - F1: 0.1185
sub_12:Test (Best Model) - Loss: 1.4904 - Accuracy: 0.3571 - F1: 0.3114
sub_14:Test (Best Model) - Loss: 1.6230 - Accuracy: 0.2714 - F1: 0.2573
sub_7:Test (Best Model) - Loss: 1.7421 - Accuracy: 0.2429 - F1: 0.1814
sub_9:Test (Best Model) - Loss: 1.5548 - Accuracy: 0.2238 - F1: 0.1612
sub_6:Test (Best Model) - Loss: 1.6062 - Accuracy: 0.3000 - F1: 0.2295
sub_4:Test (Best Model) - Loss: 1.7953 - Accuracy: 0.2571 - F1: 0.2037
sub_8:Test (Best Model) - Loss: 1.5677 - Accuracy: 0.2905 - F1: 0.2102
sub_3:Test (Best Model) - Loss: 1.8189 - Accuracy: 0.1952 - F1: 0.1509
sub_5:Test (Best Model) - Loss: 1.7388 - Accuracy: 0.1762 - F1: 0.0866
sub_7:Test (Best Model) - Loss: 1.6981 - Accuracy: 0.2190 - F1: 0.1897
sub_10:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2714 - F1: 0.1892
sub_6:Test (Best Model) - Loss: 1.7065 - Accuracy: 0.2095 - F1: 0.1397
sub_12:Test (Best Model) - Loss: 1.6709 - Accuracy: 0.2286 - F1: 0.1618
sub_11:Test (Best Model) - Loss: 1.5557 - Accuracy: 0.3286 - F1: 0.2711
sub_10:Test (Best Model) - Loss: 1.6478 - Accuracy: 0.2095 - F1: 0.1840
sub_3:Test (Best Model) - Loss: 1.9383 - Accuracy: 0.1524 - F1: 0.1119
sub_14:Test (Best Model) - Loss: 1.6666 - Accuracy: 0.2714 - F1: 0.1940
sub_6:Test (Best Model) - Loss: 1.7904 - Accuracy: 0.1952 - F1: 0.1766
sub_7:Test (Best Model) - Loss: 1.8786 - Accuracy: 0.1619 - F1: 0.0989
sub_4:Test (Best Model) - Loss: 1.9621 - Accuracy: 0.2048 - F1: 0.1371
sub_2:Test (Best Model) - Loss: 1.6702 - Accuracy: 0.3143 - F1: 0.2610
sub_12:Test (Best Model) - Loss: 1.7178 - Accuracy: 0.1952 - F1: 0.1768
sub_10:Test (Best Model) - Loss: 1.7083 - Accuracy: 0.2619 - F1: 0.2141
sub_6:Test (Best Model) - Loss: 1.8515 - Accuracy: 0.2286 - F1: 0.1792
sub_4:Test (Best Model) - Loss: 1.6606 - Accuracy: 0.2286 - F1: 0.1907
sub_2:Test (Best Model) - Loss: 1.8098 - Accuracy: 0.1810 - F1: 0.1366
sub_5:Test (Best Model) - Loss: 1.8243 - Accuracy: 0.2238 - F1: 0.1272
sub_12:Test (Best Model) - Loss: 1.7901 - Accuracy: 0.1952 - F1: 0.1716
sub_1:Test (Best Model) - Loss: 1.6554 - Accuracy: 0.2524 - F1: 0.1708
sub_7:Test (Best Model) - Loss: 1.8385 - Accuracy: 0.1905 - F1: 0.1507
sub_8:Test (Best Model) - Loss: 1.4076 - Accuracy: 0.4619 - F1: 0.4496
sub_10:Test (Best Model) - Loss: 1.5923 - Accuracy: 0.2143 - F1: 0.1929
sub_6:Test (Best Model) - Loss: 1.7674 - Accuracy: 0.1667 - F1: 0.1502
sub_14:Test (Best Model) - Loss: 1.6602 - Accuracy: 0.2476 - F1: 0.2150
sub_9:Test (Best Model) - Loss: 1.7456 - Accuracy: 0.3857 - F1: 0.2278
sub_5:Test (Best Model) - Loss: 1.7890 - Accuracy: 0.1476 - F1: 0.1085
sub_8:Test (Best Model) - Loss: 1.7838 - Accuracy: 0.2476 - F1: 0.1864
sub_13:Test (Best Model) - Loss: 1.5582 - Accuracy: 0.3524 - F1: 0.3042
sub_7:Test (Best Model) - Loss: 1.7451 - Accuracy: 0.1905 - F1: 0.1443
sub_1:Test (Best Model) - Loss: 1.6030 - Accuracy: 0.2952 - F1: 0.2895
sub_4:Test (Best Model) - Loss: 1.6403 - Accuracy: 0.2476 - F1: 0.1896
sub_2:Test (Best Model) - Loss: 1.4802 - Accuracy: 0.3714 - F1: 0.3737
sub_6:Test (Best Model) - Loss: 1.6970 - Accuracy: 0.2238 - F1: 0.1775
sub_5:Test (Best Model) - Loss: 1.7346 - Accuracy: 0.1857 - F1: 0.1540
sub_7:Test (Best Model) - Loss: 1.8047 - Accuracy: 0.1905 - F1: 0.1376
sub_13:Test (Best Model) - Loss: 1.8598 - Accuracy: 0.1619 - F1: 0.1104
sub_2:Test (Best Model) - Loss: 1.8277 - Accuracy: 0.1476 - F1: 0.1139
sub_1:Test (Best Model) - Loss: 1.8447 - Accuracy: 0.2095 - F1: 0.1024
sub_12:Test (Best Model) - Loss: 1.4315 - Accuracy: 0.4571 - F1: 0.4299
sub_4:Test (Best Model) - Loss: 1.6742 - Accuracy: 0.2333 - F1: 0.1653
sub_10:Test (Best Model) - Loss: 1.5370 - Accuracy: 0.3524 - F1: 0.3588
sub_11:Test (Best Model) - Loss: 1.5535 - Accuracy: 0.3095 - F1: 0.2247
sub_5:Test (Best Model) - Loss: 1.6695 - Accuracy: 0.2476 - F1: 0.2035
sub_7:Test (Best Model) - Loss: 1.7427 - Accuracy: 0.2000 - F1: 0.1757
sub_9:Test (Best Model) - Loss: 1.7047 - Accuracy: 0.2095 - F1: 0.1524
sub_8:Test (Best Model) - Loss: 1.3910 - Accuracy: 0.3952 - F1: 0.3708
sub_12:Test (Best Model) - Loss: 1.8359 - Accuracy: 0.1381 - F1: 0.1389
sub_14:Test (Best Model) - Loss: 1.4549 - Accuracy: 0.4143 - F1: 0.3337
sub_3:Test (Best Model) - Loss: 1.5127 - Accuracy: 0.3333 - F1: 0.3127
sub_4:Test (Best Model) - Loss: 1.7454 - Accuracy: 0.1905 - F1: 0.1492
sub_6:Test (Best Model) - Loss: 1.6936 - Accuracy: 0.1810 - F1: 0.1838
sub_8:Test (Best Model) - Loss: 1.4635 - Accuracy: 0.4524 - F1: 0.4363
sub_12:Test (Best Model) - Loss: 1.6129 - Accuracy: 0.2333 - F1: 0.2146
sub_5:Test (Best Model) - Loss: 1.7561 - Accuracy: 0.1810 - F1: 0.1425
sub_7:Test (Best Model) - Loss: 1.9197 - Accuracy: 0.2000 - F1: 0.1084
sub_10:Test (Best Model) - Loss: 1.5613 - Accuracy: 0.3143 - F1: 0.3071
sub_6:Test (Best Model) - Loss: 1.6791 - Accuracy: 0.1952 - F1: 0.1623
sub_3:Test (Best Model) - Loss: 1.6813 - Accuracy: 0.1667 - F1: 0.1322
sub_14:Test (Best Model) - Loss: 1.5778 - Accuracy: 0.2762 - F1: 0.2710
sub_13:Test (Best Model) - Loss: 1.6925 - Accuracy: 0.2333 - F1: 0.1990
sub_2:Test (Best Model) - Loss: 1.5730 - Accuracy: 0.2286 - F1: 0.2116
sub_10:Test (Best Model) - Loss: 1.6366 - Accuracy: 0.2190 - F1: 0.1722
sub_8:Test (Best Model) - Loss: 1.6448 - Accuracy: 0.2476 - F1: 0.2490
sub_7:Test (Best Model) - Loss: 1.6717 - Accuracy: 0.2333 - F1: 0.2006
sub_2:Test (Best Model) - Loss: 1.7942 - Accuracy: 0.2143 - F1: 0.1547
sub_4:Test (Best Model) - Loss: 1.5703 - Accuracy: 0.2952 - F1: 0.3065
sub_3:Test (Best Model) - Loss: 1.6367 - Accuracy: 0.2381 - F1: 0.1847
sub_8:Test (Best Model) - Loss: 1.6201 - Accuracy: 0.3238 - F1: 0.2846
sub_12:Test (Best Model) - Loss: 1.6835 - Accuracy: 0.3286 - F1: 0.2739
sub_13:Test (Best Model) - Loss: 1.6238 - Accuracy: 0.2524 - F1: 0.2099
sub_7:Test (Best Model) - Loss: 1.8870 - Accuracy: 0.2143 - F1: 0.1623
sub_4:Test (Best Model) - Loss: 1.6950 - Accuracy: 0.2048 - F1: 0.1659
sub_11:Test (Best Model) - Loss: 1.5777 - Accuracy: 0.3667 - F1: 0.3087
sub_1:Test (Best Model) - Loss: 1.5577 - Accuracy: 0.2333 - F1: 0.1940
sub_14:Test (Best Model) - Loss: 1.6250 - Accuracy: 0.2429 - F1: 0.2209
sub_10:Test (Best Model) - Loss: 1.7066 - Accuracy: 0.2095 - F1: 0.1647
sub_4:Test (Best Model) - Loss: 1.8674 - Accuracy: 0.2095 - F1: 0.1716
sub_9:Test (Best Model) - Loss: 1.6902 - Accuracy: 0.2571 - F1: 0.1840
sub_14:Test (Best Model) - Loss: 1.7694 - Accuracy: 0.1857 - F1: 0.1298
sub_13:Test (Best Model) - Loss: 1.6433 - Accuracy: 0.2524 - F1: 0.2388
sub_7:Test (Best Model) - Loss: 1.8001 - Accuracy: 0.1714 - F1: 0.1492
sub_2:Test (Best Model) - Loss: 1.5792 - Accuracy: 0.2810 - F1: 0.2741
sub_14:Test (Best Model) - Loss: 1.6726 - Accuracy: 0.2238 - F1: 0.1952
sub_12:Test (Best Model) - Loss: 1.4939 - Accuracy: 0.3048 - F1: 0.2818
sub_8:Test (Best Model) - Loss: 1.5551 - Accuracy: 0.2619 - F1: 0.2778
sub_13:Test (Best Model) - Loss: 1.7035 - Accuracy: 0.2524 - F1: 0.2402
sub_4:Test (Best Model) - Loss: 1.5668 - Accuracy: 0.3143 - F1: 0.2958
sub_5:Test (Best Model) - Loss: 1.6164 - Accuracy: 0.2190 - F1: 0.2061
sub_1:Test (Best Model) - Loss: 1.7343 - Accuracy: 0.1810 - F1: 0.1663
sub_9:Test (Best Model) - Loss: 1.7235 - Accuracy: 0.2286 - F1: 0.1786
sub_10:Test (Best Model) - Loss: 1.7363 - Accuracy: 0.2429 - F1: 0.1840
sub_11:Test (Best Model) - Loss: 1.6713 - Accuracy: 0.2524 - F1: 0.2010
sub_5:Test (Best Model) - Loss: 1.8091 - Accuracy: 0.2143 - F1: 0.1410
sub_7:Test (Best Model) - Loss: 1.6904 - Accuracy: 0.2143 - F1: 0.1896
sub_3:Test (Best Model) - Loss: 1.6510 - Accuracy: 0.2571 - F1: 0.2107
sub_14:Test (Best Model) - Loss: 1.7001 - Accuracy: 0.1952 - F1: 0.1698
sub_13:Test (Best Model) - Loss: 1.6216 - Accuracy: 0.2905 - F1: 0.2652
sub_1:Test (Best Model) - Loss: 1.5604 - Accuracy: 0.2571 - F1: 0.2166
sub_5:Test (Best Model) - Loss: 1.6299 - Accuracy: 0.2000 - F1: 0.1827
sub_8:Test (Best Model) - Loss: 1.4781 - Accuracy: 0.3429 - F1: 0.3243
sub_2:Test (Best Model) - Loss: 1.5949 - Accuracy: 0.2476 - F1: 0.2450
sub_13:Test (Best Model) - Loss: 1.7616 - Accuracy: 0.2905 - F1: 0.2287
sub_12:Test (Best Model) - Loss: 1.5742 - Accuracy: 0.2905 - F1: 0.2571
sub_1:Test (Best Model) - Loss: 1.9774 - Accuracy: 0.2048 - F1: 0.0866
sub_11:Test (Best Model) - Loss: 1.4659 - Accuracy: 0.3667 - F1: 0.2884
sub_3:Test (Best Model) - Loss: 1.6908 - Accuracy: 0.2476 - F1: 0.2150
sub_10:Test (Best Model) - Loss: 1.6522 - Accuracy: 0.2476 - F1: 0.1900
sub_9:Test (Best Model) - Loss: 1.6191 - Accuracy: 0.2381 - F1: 0.2414
sub_13:Test (Best Model) - Loss: 1.6843 - Accuracy: 0.2333 - F1: 0.1843
sub_12:Test (Best Model) - Loss: 1.6731 - Accuracy: 0.1619 - F1: 0.1369
sub_11:Test (Best Model) - Loss: 1.7123 - Accuracy: 0.1571 - F1: 0.1205
sub_14:Test (Best Model) - Loss: 1.6702 - Accuracy: 0.2952 - F1: 0.2514
sub_13:Test (Best Model) - Loss: 1.7056 - Accuracy: 0.2048 - F1: 0.1246
sub_9:Test (Best Model) - Loss: 1.9003 - Accuracy: 0.1571 - F1: 0.1076
sub_8:Test (Best Model) - Loss: 1.6017 - Accuracy: 0.2429 - F1: 0.2309
sub_2:Test (Best Model) - Loss: 1.6729 - Accuracy: 0.2524 - F1: 0.2449
sub_13:Test (Best Model) - Loss: 1.7434 - Accuracy: 0.2238 - F1: 0.1711
sub_9:Test (Best Model) - Loss: 1.7481 - Accuracy: 0.1286 - F1: 0.1237
sub_10:Test (Best Model) - Loss: 1.6321 - Accuracy: 0.2524 - F1: 0.1660
sub_11:Test (Best Model) - Loss: 1.7128 - Accuracy: 0.2667 - F1: 0.2365
sub_1:Test (Best Model) - Loss: 1.5585 - Accuracy: 0.2952 - F1: 0.2862
sub_9:Test (Best Model) - Loss: 1.7885 - Accuracy: 0.2048 - F1: 0.1051
sub_12:Test (Best Model) - Loss: 1.5953 - Accuracy: 0.3048 - F1: 0.2544
sub_14:Test (Best Model) - Loss: 1.7096 - Accuracy: 0.2333 - F1: 0.2095
sub_3:Test (Best Model) - Loss: 1.6944 - Accuracy: 0.2381 - F1: 0.1839
sub_5:Test (Best Model) - Loss: 1.5573 - Accuracy: 0.3381 - F1: 0.3171
sub_11:Test (Best Model) - Loss: 1.7467 - Accuracy: 0.1810 - F1: 0.1625
sub_2:Test (Best Model) - Loss: 1.6538 - Accuracy: 0.2952 - F1: 0.1976
sub_9:Test (Best Model) - Loss: 1.8277 - Accuracy: 0.1429 - F1: 0.1272
sub_8:Test (Best Model) - Loss: 1.6378 - Accuracy: 0.2190 - F1: 0.2282
sub_8:Test (Best Model) - Loss: 1.5916 - Accuracy: 0.2714 - F1: 0.2393
sub_11:Test (Best Model) - Loss: 1.6868 - Accuracy: 0.2190 - F1: 0.2052
sub_9:Test (Best Model) - Loss: 1.7116 - Accuracy: 0.2095 - F1: 0.1704
sub_1:Test (Best Model) - Loss: 1.6752 - Accuracy: 0.1857 - F1: 0.1569
sub_3:Test (Best Model) - Loss: 1.6851 - Accuracy: 0.2667 - F1: 0.2362
sub_11:Test (Best Model) - Loss: 1.5974 - Accuracy: 0.2571 - F1: 0.2282
sub_11:Test (Best Model) - Loss: 1.6693 - Accuracy: 0.2524 - F1: 0.2422
sub_3:Test (Best Model) - Loss: 1.7519 - Accuracy: 0.2667 - F1: 0.1817
sub_1:Test (Best Model) - Loss: 1.7514 - Accuracy: 0.1714 - F1: 0.1338
sub_9:Test (Best Model) - Loss: 1.5740 - Accuracy: 0.2952 - F1: 0.2679
sub_1:Test (Best Model) - Loss: 1.7789 - Accuracy: 0.2333 - F1: 0.1525
sub_11:Test (Best Model) - Loss: 1.4350 - Accuracy: 0.3810 - F1: 0.3283
sub_9:Test (Best Model) - Loss: 1.6483 - Accuracy: 0.2286 - F1: 0.2365

=== Summary Results ===

acc: 24.22 ± 2.67
F1: 19.99 ± 3.17
acc-in: 28.88 ± 3.02
F1-in: 25.28 ± 3.45
