lr: 0.0001
sub_1:Test (Best Model) - Loss: 0.8110 - Accuracy: 0.2095 - F1: 0.1184
sub_1:Test (Best Model) - Loss: 0.8040 - Accuracy: 0.1905 - F1: 0.1452
sub_1:Test (Best Model) - Loss: 0.8052 - Accuracy: 0.2095 - F1: 0.1082
sub_1:Test (Best Model) - Loss: 0.8041 - Accuracy: 0.2095 - F1: 0.1205
sub_1:Test (Best Model) - Loss: 0.8196 - Accuracy: 0.2190 - F1: 0.1149
sub_1:Test (Best Model) - Loss: 0.8470 - Accuracy: 0.2286 - F1: 0.1723
sub_1:Test (Best Model) - Loss: 0.8050 - Accuracy: 0.2000 - F1: 0.0939
sub_1:Test (Best Model) - Loss: 0.8214 - Accuracy: 0.2190 - F1: 0.1677
sub_1:Test (Best Model) - Loss: 0.8083 - Accuracy: 0.1048 - F1: 0.0473
sub_1:Test (Best Model) - Loss: 0.8050 - Accuracy: 0.2000 - F1: 0.1180
sub_1:Test (Best Model) - Loss: 0.8022 - Accuracy: 0.2190 - F1: 0.1273
sub_1:Test (Best Model) - Loss: 0.8045 - Accuracy: 0.2286 - F1: 0.1270
sub_1:Test (Best Model) - Loss: 0.8043 - Accuracy: 0.2190 - F1: 0.1016
sub_1:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2286 - F1: 0.1388
sub_1:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 0.6712 - Accuracy: 0.3905 - F1: 0.3688
sub_2:Test (Best Model) - Loss: 0.6811 - Accuracy: 0.4286 - F1: 0.3877
sub_2:Test (Best Model) - Loss: 0.5927 - Accuracy: 0.4952 - F1: 0.4525
sub_2:Test (Best Model) - Loss: 0.6633 - Accuracy: 0.4476 - F1: 0.4278
sub_2:Test (Best Model) - Loss: 0.5890 - Accuracy: 0.4571 - F1: 0.4570
sub_2:Test (Best Model) - Loss: 0.6060 - Accuracy: 0.4762 - F1: 0.4154
sub_2:Test (Best Model) - Loss: 0.6115 - Accuracy: 0.4762 - F1: 0.4009
sub_2:Test (Best Model) - Loss: 0.5610 - Accuracy: 0.4952 - F1: 0.4928
sub_2:Test (Best Model) - Loss: 0.7067 - Accuracy: 0.4000 - F1: 0.2641
sub_2:Test (Best Model) - Loss: 0.6180 - Accuracy: 0.4571 - F1: 0.4323
sub_2:Test (Best Model) - Loss: 0.7389 - Accuracy: 0.3714 - F1: 0.2429
sub_2:Test (Best Model) - Loss: 0.7133 - Accuracy: 0.4190 - F1: 0.3805
sub_2:Test (Best Model) - Loss: 0.5919 - Accuracy: 0.4857 - F1: 0.4668
sub_2:Test (Best Model) - Loss: 0.7902 - Accuracy: 0.3905 - F1: 0.2961
sub_2:Test (Best Model) - Loss: 0.6238 - Accuracy: 0.4762 - F1: 0.4764
sub_3:Test (Best Model) - Loss: 0.7852 - Accuracy: 0.2857 - F1: 0.2024
sub_3:Test (Best Model) - Loss: 0.8049 - Accuracy: 0.2095 - F1: 0.1676
sub_3:Test (Best Model) - Loss: 0.8048 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 0.8038 - Accuracy: 0.2571 - F1: 0.1615
sub_3:Test (Best Model) - Loss: 0.7975 - Accuracy: 0.2381 - F1: 0.1646
sub_3:Test (Best Model) - Loss: 0.8049 - Accuracy: 0.1429 - F1: 0.0953
sub_3:Test (Best Model) - Loss: 0.8006 - Accuracy: 0.2667 - F1: 0.2305
sub_3:Test (Best Model) - Loss: 0.8126 - Accuracy: 0.2095 - F1: 0.1287
sub_3:Test (Best Model) - Loss: 0.8503 - Accuracy: 0.2476 - F1: 0.2345
sub_3:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 0.8260 - Accuracy: 0.2857 - F1: 0.2698
sub_3:Test (Best Model) - Loss: 0.8600 - Accuracy: 0.2762 - F1: 0.2418
sub_3:Test (Best Model) - Loss: 0.7970 - Accuracy: 0.2571 - F1: 0.1751
sub_3:Test (Best Model) - Loss: 0.8641 - Accuracy: 0.2571 - F1: 0.2230
sub_3:Test (Best Model) - Loss: 0.8023 - Accuracy: 0.2190 - F1: 0.1905
sub_4:Test (Best Model) - Loss: 0.7997 - Accuracy: 0.2381 - F1: 0.1360
sub_4:Test (Best Model) - Loss: 0.7722 - Accuracy: 0.3429 - F1: 0.2370
sub_4:Test (Best Model) - Loss: 0.7678 - Accuracy: 0.3238 - F1: 0.2401
sub_4:Test (Best Model) - Loss: 0.7968 - Accuracy: 0.2000 - F1: 0.1792
sub_4:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1905 - F1: 0.0640
sub_4:Test (Best Model) - Loss: 0.8274 - Accuracy: 0.2857 - F1: 0.2810
sub_4:Test (Best Model) - Loss: 0.8003 - Accuracy: 0.3238 - F1: 0.2657
sub_4:Test (Best Model) - Loss: 0.7891 - Accuracy: 0.3619 - F1: 0.3249
sub_4:Test (Best Model) - Loss: 0.7963 - Accuracy: 0.2476 - F1: 0.1612
sub_4:Test (Best Model) - Loss: 0.7869 - Accuracy: 0.3238 - F1: 0.2528
sub_4:Test (Best Model) - Loss: 0.8054 - Accuracy: 0.3143 - F1: 0.2917
sub_4:Test (Best Model) - Loss: 0.8152 - Accuracy: 0.2381 - F1: 0.1440
sub_4:Test (Best Model) - Loss: 0.8258 - Accuracy: 0.3048 - F1: 0.2621
sub_4:Test (Best Model) - Loss: 0.7999 - Accuracy: 0.3143 - F1: 0.2861
sub_4:Test (Best Model) - Loss: 0.7939 - Accuracy: 0.2667 - F1: 0.1654
sub_5:Test (Best Model) - Loss: 0.7945 - Accuracy: 0.2667 - F1: 0.1675
sub_5:Test (Best Model) - Loss: 0.8284 - Accuracy: 0.2095 - F1: 0.1160
sub_5:Test (Best Model) - Loss: 0.8349 - Accuracy: 0.2190 - F1: 0.1746
sub_5:Test (Best Model) - Loss: 0.8054 - Accuracy: 0.1905 - F1: 0.0955
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 0.7988 - Accuracy: 0.2571 - F1: 0.1633
sub_5:Test (Best Model) - Loss: 0.8064 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 0.8055 - Accuracy: 0.1905 - F1: 0.1045
sub_5:Test (Best Model) - Loss: 0.8185 - Accuracy: 0.1905 - F1: 0.1824
sub_5:Test (Best Model) - Loss: 0.8048 - Accuracy: 0.2000 - F1: 0.0815
sub_5:Test (Best Model) - Loss: 0.7663 - Accuracy: 0.2857 - F1: 0.2059
sub_5:Test (Best Model) - Loss: 0.8023 - Accuracy: 0.2667 - F1: 0.2191
sub_5:Test (Best Model) - Loss: 0.7935 - Accuracy: 0.2667 - F1: 0.1843
sub_5:Test (Best Model) - Loss: 0.8481 - Accuracy: 0.2857 - F1: 0.2475
sub_5:Test (Best Model) - Loss: 0.8132 - Accuracy: 0.2000 - F1: 0.0821
sub_6:Test (Best Model) - Loss: 0.7770 - Accuracy: 0.3143 - F1: 0.2936
sub_6:Test (Best Model) - Loss: 0.7738 - Accuracy: 0.2952 - F1: 0.2079
sub_6:Test (Best Model) - Loss: 0.8945 - Accuracy: 0.2857 - F1: 0.2799
sub_6:Test (Best Model) - Loss: 0.8006 - Accuracy: 0.1810 - F1: 0.1205
sub_6:Test (Best Model) - Loss: 0.8011 - Accuracy: 0.2762 - F1: 0.2306
sub_6:Test (Best Model) - Loss: 0.7849 - Accuracy: 0.2952 - F1: 0.2429
sub_6:Test (Best Model) - Loss: 0.7909 - Accuracy: 0.2762 - F1: 0.1918
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0672
sub_6:Test (Best Model) - Loss: 0.8043 - Accuracy: 0.2476 - F1: 0.2379
sub_6:Test (Best Model) - Loss: 0.8249 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2190 - F1: 0.1348
sub_6:Test (Best Model) - Loss: 0.8526 - Accuracy: 0.3238 - F1: 0.3229
sub_6:Test (Best Model) - Loss: 0.8048 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 0.7926 - Accuracy: 0.2381 - F1: 0.1728
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 0.8077 - Accuracy: 0.2095 - F1: 0.0907
sub_7:Test (Best Model) - Loss: 0.7723 - Accuracy: 0.2952 - F1: 0.2526
sub_7:Test (Best Model) - Loss: 0.8249 - Accuracy: 0.2190 - F1: 0.1907
sub_7:Test (Best Model) - Loss: 0.8048 - Accuracy: 0.2381 - F1: 0.2160
sub_7:Test (Best Model) - Loss: 0.8042 - Accuracy: 0.2476 - F1: 0.1885
sub_7:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.1191
sub_7:Test (Best Model) - Loss: 0.8196 - Accuracy: 0.1714 - F1: 0.1260
sub_7:Test (Best Model) - Loss: 0.8594 - Accuracy: 0.2857 - F1: 0.2411
sub_7:Test (Best Model) - Loss: 0.8039 - Accuracy: 0.3048 - F1: 0.2770
sub_7:Test (Best Model) - Loss: 0.8010 - Accuracy: 0.2762 - F1: 0.2276
sub_7:Test (Best Model) - Loss: 0.8039 - Accuracy: 0.2762 - F1: 0.2067
sub_7:Test (Best Model) - Loss: 0.8220 - Accuracy: 0.2762 - F1: 0.1981
sub_7:Test (Best Model) - Loss: 0.7862 - Accuracy: 0.2952 - F1: 0.2441
sub_7:Test (Best Model) - Loss: 0.8126 - Accuracy: 0.2476 - F1: 0.1648
sub_7:Test (Best Model) - Loss: 0.7821 - Accuracy: 0.2667 - F1: 0.1865
sub_8:Test (Best Model) - Loss: 0.8222 - Accuracy: 0.3429 - F1: 0.2498
sub_8:Test (Best Model) - Loss: 0.7763 - Accuracy: 0.3238 - F1: 0.2702
sub_8:Test (Best Model) - Loss: 0.6994 - Accuracy: 0.3810 - F1: 0.3021
sub_8:Test (Best Model) - Loss: 0.6897 - Accuracy: 0.3333 - F1: 0.2928
sub_8:Test (Best Model) - Loss: 0.7523 - Accuracy: 0.3714 - F1: 0.3092
sub_8:Test (Best Model) - Loss: 0.7149 - Accuracy: 0.3333 - F1: 0.2408
sub_8:Test (Best Model) - Loss: 0.7586 - Accuracy: 0.3238 - F1: 0.2294
sub_8:Test (Best Model) - Loss: 0.7510 - Accuracy: 0.3048 - F1: 0.2528
sub_8:Test (Best Model) - Loss: 0.7618 - Accuracy: 0.3619 - F1: 0.3635
sub_8:Test (Best Model) - Loss: 0.7472 - Accuracy: 0.2952 - F1: 0.2486
sub_8:Test (Best Model) - Loss: 0.6796 - Accuracy: 0.4095 - F1: 0.3312
sub_8:Test (Best Model) - Loss: 0.6354 - Accuracy: 0.4000 - F1: 0.3322
sub_8:Test (Best Model) - Loss: 0.7087 - Accuracy: 0.3905 - F1: 0.3700
sub_8:Test (Best Model) - Loss: 0.8018 - Accuracy: 0.2857 - F1: 0.2435
sub_8:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.3810 - F1: 0.2863
sub_9:Test (Best Model) - Loss: 0.8012 - Accuracy: 0.2381 - F1: 0.1573
sub_9:Test (Best Model) - Loss: 0.8045 - Accuracy: 0.2571 - F1: 0.1441
sub_9:Test (Best Model) - Loss: 0.8173 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 0.7965 - Accuracy: 0.2190 - F1: 0.1533
sub_9:Test (Best Model) - Loss: 0.8052 - Accuracy: 0.1810 - F1: 0.0868
sub_9:Test (Best Model) - Loss: 0.8058 - Accuracy: 0.1905 - F1: 0.1384
sub_9:Test (Best Model) - Loss: 0.9463 - Accuracy: 0.2381 - F1: 0.2294
sub_9:Test (Best Model) - Loss: 0.8036 - Accuracy: 0.2571 - F1: 0.1990
sub_9:Test (Best Model) - Loss: 0.8186 - Accuracy: 0.2190 - F1: 0.1009
sub_9:Test (Best Model) - Loss: 0.7937 - Accuracy: 0.2667 - F1: 0.2257
sub_9:Test (Best Model) - Loss: 0.8042 - Accuracy: 0.2286 - F1: 0.1256
sub_9:Test (Best Model) - Loss: 0.8194 - Accuracy: 0.2667 - F1: 0.1981
sub_9:Test (Best Model) - Loss: 0.8850 - Accuracy: 0.2667 - F1: 0.2438
sub_9:Test (Best Model) - Loss: 0.8012 - Accuracy: 0.2667 - F1: 0.1995
sub_9:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 0.7844 - Accuracy: 0.2762 - F1: 0.1873
sub_10:Test (Best Model) - Loss: 0.7542 - Accuracy: 0.3333 - F1: 0.2778
sub_10:Test (Best Model) - Loss: 0.7418 - Accuracy: 0.3333 - F1: 0.3077
sub_10:Test (Best Model) - Loss: 0.7870 - Accuracy: 0.2571 - F1: 0.2431
sub_10:Test (Best Model) - Loss: 0.7928 - Accuracy: 0.2286 - F1: 0.1759
sub_10:Test (Best Model) - Loss: 0.8040 - Accuracy: 0.2286 - F1: 0.1642
sub_10:Test (Best Model) - Loss: 0.8055 - Accuracy: 0.1810 - F1: 0.0661
sub_10:Test (Best Model) - Loss: 0.7724 - Accuracy: 0.2762 - F1: 0.2267
sub_10:Test (Best Model) - Loss: 0.9094 - Accuracy: 0.2286 - F1: 0.2133
sub_10:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2190 - F1: 0.1280
sub_10:Test (Best Model) - Loss: 0.7749 - Accuracy: 0.2476 - F1: 0.2072
sub_10:Test (Best Model) - Loss: 0.7933 - Accuracy: 0.2952 - F1: 0.2418
sub_10:Test (Best Model) - Loss: 0.8042 - Accuracy: 0.1619 - F1: 0.0945
sub_10:Test (Best Model) - Loss: 0.8048 - Accuracy: 0.2190 - F1: 0.1063
sub_10:Test (Best Model) - Loss: 0.9266 - Accuracy: 0.2286 - F1: 0.2191
sub_11:Test (Best Model) - Loss: 0.7918 - Accuracy: 0.2571 - F1: 0.2204
sub_11:Test (Best Model) - Loss: 0.7627 - Accuracy: 0.2667 - F1: 0.2064
sub_11:Test (Best Model) - Loss: 0.6915 - Accuracy: 0.3810 - F1: 0.2919
sub_11:Test (Best Model) - Loss: 0.8024 - Accuracy: 0.2190 - F1: 0.1849
sub_11:Test (Best Model) - Loss: 0.7203 - Accuracy: 0.3619 - F1: 0.3393
sub_11:Test (Best Model) - Loss: 0.7055 - Accuracy: 0.3143 - F1: 0.2822
sub_11:Test (Best Model) - Loss: 0.7474 - Accuracy: 0.3238 - F1: 0.2321
sub_11:Test (Best Model) - Loss: 0.7606 - Accuracy: 0.3143 - F1: 0.2942
sub_11:Test (Best Model) - Loss: 0.7040 - Accuracy: 0.3429 - F1: 0.2934
sub_11:Test (Best Model) - Loss: 0.8036 - Accuracy: 0.2095 - F1: 0.1882
sub_11:Test (Best Model) - Loss: 0.7502 - Accuracy: 0.3619 - F1: 0.2791
sub_11:Test (Best Model) - Loss: 0.7871 - Accuracy: 0.2667 - F1: 0.1709
sub_11:Test (Best Model) - Loss: 0.7785 - Accuracy: 0.3143 - F1: 0.2374
sub_11:Test (Best Model) - Loss: 0.7818 - Accuracy: 0.2571 - F1: 0.2443
sub_11:Test (Best Model) - Loss: 0.8478 - Accuracy: 0.2476 - F1: 0.2406
sub_12:Test (Best Model) - Loss: 0.8051 - Accuracy: 0.2095 - F1: 0.1050
sub_12:Test (Best Model) - Loss: 0.8136 - Accuracy: 0.2190 - F1: 0.1265
sub_12:Test (Best Model) - Loss: 0.8049 - Accuracy: 0.1810 - F1: 0.0613
sub_12:Test (Best Model) - Loss: 0.8054 - Accuracy: 0.2190 - F1: 0.1221
sub_12:Test (Best Model) - Loss: 0.8157 - Accuracy: 0.1905 - F1: 0.0645
sub_12:Test (Best Model) - Loss: 0.8028 - Accuracy: 0.2381 - F1: 0.1460
sub_12:Test (Best Model) - Loss: 0.8146 - Accuracy: 0.1333 - F1: 0.0973
sub_12:Test (Best Model) - Loss: 0.8045 - Accuracy: 0.2667 - F1: 0.1504
sub_12:Test (Best Model) - Loss: 0.8080 - Accuracy: 0.2381 - F1: 0.1648
sub_12:Test (Best Model) - Loss: 0.8468 - Accuracy: 0.1143 - F1: 0.0726
sub_12:Test (Best Model) - Loss: 0.7927 - Accuracy: 0.2571 - F1: 0.1789
sub_12:Test (Best Model) - Loss: 0.7942 - Accuracy: 0.2762 - F1: 0.1901
sub_12:Test (Best Model) - Loss: 0.7853 - Accuracy: 0.2667 - F1: 0.2119
sub_12:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2381 - F1: 0.1465
sub_12:Test (Best Model) - Loss: 0.8031 - Accuracy: 0.1619 - F1: 0.0770
sub_13:Test (Best Model) - Loss: 0.7967 - Accuracy: 0.2762 - F1: 0.1678
sub_13:Test (Best Model) - Loss: 0.7985 - Accuracy: 0.2667 - F1: 0.1532
sub_13:Test (Best Model) - Loss: 0.8034 - Accuracy: 0.1905 - F1: 0.1120
sub_13:Test (Best Model) - Loss: 0.8043 - Accuracy: 0.2095 - F1: 0.0976
sub_13:Test (Best Model) - Loss: 0.8049 - Accuracy: 0.2571 - F1: 0.1492
sub_13:Test (Best Model) - Loss: 0.7984 - Accuracy: 0.3048 - F1: 0.1886
sub_13:Test (Best Model) - Loss: 0.7974 - Accuracy: 0.3048 - F1: 0.1809
sub_13:Test (Best Model) - Loss: 0.7720 - Accuracy: 0.3238 - F1: 0.1922
sub_13:Test (Best Model) - Loss: 0.7671 - Accuracy: 0.3333 - F1: 0.2112
sub_13:Test (Best Model) - Loss: 0.7770 - Accuracy: 0.2667 - F1: 0.2021
sub_13:Test (Best Model) - Loss: 0.7808 - Accuracy: 0.3048 - F1: 0.1751
sub_13:Test (Best Model) - Loss: 0.7704 - Accuracy: 0.3143 - F1: 0.1952
sub_13:Test (Best Model) - Loss: 0.7901 - Accuracy: 0.3048 - F1: 0.1736
sub_13:Test (Best Model) - Loss: 0.7957 - Accuracy: 0.3048 - F1: 0.2151
sub_13:Test (Best Model) - Loss: 0.7954 - Accuracy: 0.3143 - F1: 0.2075
sub_14:Test (Best Model) - Loss: 0.7887 - Accuracy: 0.2286 - F1: 0.1621
sub_14:Test (Best Model) - Loss: 0.8034 - Accuracy: 0.2095 - F1: 0.1105
sub_14:Test (Best Model) - Loss: 0.7736 - Accuracy: 0.3143 - F1: 0.1812
sub_14:Test (Best Model) - Loss: 0.7279 - Accuracy: 0.3905 - F1: 0.3198
sub_14:Test (Best Model) - Loss: 0.7722 - Accuracy: 0.3143 - F1: 0.2202
sub_14:Test (Best Model) - Loss: 0.7016 - Accuracy: 0.3810 - F1: 0.3411
sub_14:Test (Best Model) - Loss: 0.7089 - Accuracy: 0.3619 - F1: 0.2863
sub_14:Test (Best Model) - Loss: 0.7389 - Accuracy: 0.3524 - F1: 0.2717
sub_14:Test (Best Model) - Loss: 0.7899 - Accuracy: 0.2857 - F1: 0.1715
sub_14:Test (Best Model) - Loss: 0.7768 - Accuracy: 0.2857 - F1: 0.1877
sub_14:Test (Best Model) - Loss: 0.7994 - Accuracy: 0.3048 - F1: 0.2542
sub_14:Test (Best Model) - Loss: 0.7730 - Accuracy: 0.3048 - F1: 0.2038
sub_14:Test (Best Model) - Loss: 0.7562 - Accuracy: 0.3048 - F1: 0.2585
sub_14:Test (Best Model) - Loss: 0.7603 - Accuracy: 0.3333 - F1: 0.2388
sub_14:Test (Best Model) - Loss: 0.7305 - Accuracy: 0.3905 - F1: 0.2915

=== Summary Results ===

acc:   27.48 ± 6.11
F1:    20.33 ± 7.03
acc-in:35.59 ± 6.36
F1-in: 27.72 ± 7.78
