lr: 0.001
sub_1:Test (Best Model) - Loss: 0.8155 - Accuracy: 0.2190 - F1: 0.1224
sub_1:Test (Best Model) - Loss: 0.8050 - Accuracy: 0.2190 - F1: 0.1084
sub_1:Test (Best Model) - Loss: 0.8058 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 0.8089 - Accuracy: 0.2000 - F1: 0.0677
sub_1:Test (Best Model) - Loss: 0.8085 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 0.7575 - Accuracy: 0.2476 - F1: 0.2067
sub_1:Test (Best Model) - Loss: 0.8058 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 0.8110 - Accuracy: 0.1810 - F1: 0.0633
sub_1:Test (Best Model) - Loss: 0.8064 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 0.8079 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 0.8060 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 0.8052 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 0.8053 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 0.8063 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 0.8080 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 0.6370 - Accuracy: 0.4476 - F1: 0.3801
sub_2:Test (Best Model) - Loss: 0.6790 - Accuracy: 0.4095 - F1: 0.3827
sub_2:Test (Best Model) - Loss: 0.6971 - Accuracy: 0.3810 - F1: 0.3162
sub_2:Test (Best Model) - Loss: 0.7036 - Accuracy: 0.3714 - F1: 0.3210
sub_2:Test (Best Model) - Loss: 0.5946 - Accuracy: 0.4190 - F1: 0.3897
sub_2:Test (Best Model) - Loss: 0.6108 - Accuracy: 0.4857 - F1: 0.3691
sub_2:Test (Best Model) - Loss: 0.6379 - Accuracy: 0.4190 - F1: 0.3633
sub_2:Test (Best Model) - Loss: 0.7935 - Accuracy: 0.2667 - F1: 0.1432
sub_2:Test (Best Model) - Loss: 0.6533 - Accuracy: 0.3905 - F1: 0.3391
sub_2:Test (Best Model) - Loss: 0.8062 - Accuracy: 0.2000 - F1: 0.0672
sub_2:Test (Best Model) - Loss: 0.7033 - Accuracy: 0.4190 - F1: 0.3653
sub_2:Test (Best Model) - Loss: 0.7358 - Accuracy: 0.3619 - F1: 0.2772
sub_2:Test (Best Model) - Loss: 0.7189 - Accuracy: 0.3238 - F1: 0.2328
sub_2:Test (Best Model) - Loss: 0.6464 - Accuracy: 0.4571 - F1: 0.3713
sub_2:Test (Best Model) - Loss: 0.6447 - Accuracy: 0.4476 - F1: 0.3784
sub_3:Test (Best Model) - Loss: 0.8055 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 0.8054 - Accuracy: 0.2190 - F1: 0.1103
sub_3:Test (Best Model) - Loss: 0.8060 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 0.8062 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 0.8099 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 0.8064 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 0.8054 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 0.8065 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 0.8053 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 0.8088 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 0.8063 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 0.7990 - Accuracy: 0.2762 - F1: 0.1574
sub_3:Test (Best Model) - Loss: 0.8055 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 0.8053 - Accuracy: 0.2476 - F1: 0.1363
sub_3:Test (Best Model) - Loss: 0.8014 - Accuracy: 0.2000 - F1: 0.1494
sub_4:Test (Best Model) - Loss: 0.8055 - Accuracy: 0.1810 - F1: 0.0685
sub_4:Test (Best Model) - Loss: 0.8040 - Accuracy: 0.2952 - F1: 0.1671
sub_4:Test (Best Model) - Loss: 0.8060 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 0.8056 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 0.8075 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 0.8068 - Accuracy: 0.2000 - F1: 0.0821
sub_4:Test (Best Model) - Loss: 0.8053 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 0.7936 - Accuracy: 0.2190 - F1: 0.1439
sub_4:Test (Best Model) - Loss: 0.8048 - Accuracy: 0.2095 - F1: 0.1199
sub_4:Test (Best Model) - Loss: 0.8099 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2667 - F1: 0.1475
sub_4:Test (Best Model) - Loss: 0.7912 - Accuracy: 0.2667 - F1: 0.1931
sub_4:Test (Best Model) - Loss: 0.8035 - Accuracy: 0.1905 - F1: 0.0871
sub_4:Test (Best Model) - Loss: 0.8039 - Accuracy: 0.1905 - F1: 0.1121
sub_4:Test (Best Model) - Loss: 0.8031 - Accuracy: 0.2571 - F1: 0.1727
sub_5:Test (Best Model) - Loss: 0.8085 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 0.8053 - Accuracy: 0.1333 - F1: 0.0629
sub_5:Test (Best Model) - Loss: 0.8063 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 0.8062 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 0.8080 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 0.7985 - Accuracy: 0.2762 - F1: 0.2054
sub_5:Test (Best Model) - Loss: 0.8059 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 0.8066 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 0.8059 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2571 - F1: 0.1446
sub_5:Test (Best Model) - Loss: 0.8106 - Accuracy: 0.2000 - F1: 0.0819
sub_5:Test (Best Model) - Loss: 0.8143 - Accuracy: 0.2381 - F1: 0.1804
sub_5:Test (Best Model) - Loss: 0.8070 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 0.8072 - Accuracy: 0.1905 - F1: 0.1419
sub_5:Test (Best Model) - Loss: 0.8095 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 0.8034 - Accuracy: 0.2381 - F1: 0.1375
sub_6:Test (Best Model) - Loss: 0.8053 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 0.8066 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 0.8061 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 0.8090 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 0.8057 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 0.8055 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 0.8065 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 0.8067 - Accuracy: 0.2190 - F1: 0.1148
sub_6:Test (Best Model) - Loss: 0.8084 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 0.8055 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 0.8055 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 0.8059 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 0.8038 - Accuracy: 0.2667 - F1: 0.1726
sub_6:Test (Best Model) - Loss: 0.8087 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 0.8049 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 0.8049 - Accuracy: 0.2095 - F1: 0.1132
sub_7:Test (Best Model) - Loss: 0.8063 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 0.8064 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 0.8102 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 0.8048 - Accuracy: 0.3048 - F1: 0.1819
sub_7:Test (Best Model) - Loss: 0.8071 - Accuracy: 0.2095 - F1: 0.1087
sub_7:Test (Best Model) - Loss: 0.8064 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 0.8028 - Accuracy: 0.2381 - F1: 0.1254
sub_7:Test (Best Model) - Loss: 0.8089 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 0.8043 - Accuracy: 0.2095 - F1: 0.1260
sub_7:Test (Best Model) - Loss: 0.8074 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 0.8063 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 0.8053 - Accuracy: 0.2571 - F1: 0.1432
sub_7:Test (Best Model) - Loss: 0.8097 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 0.8051 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 0.7201 - Accuracy: 0.3048 - F1: 0.2493
sub_8:Test (Best Model) - Loss: 0.6740 - Accuracy: 0.3714 - F1: 0.3363
sub_8:Test (Best Model) - Loss: 0.8057 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 0.7269 - Accuracy: 0.3619 - F1: 0.2789
sub_8:Test (Best Model) - Loss: 0.7306 - Accuracy: 0.3333 - F1: 0.2719
sub_8:Test (Best Model) - Loss: 0.8273 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 0.8084 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 0.8070 - Accuracy: 0.2476 - F1: 0.1310
sub_8:Test (Best Model) - Loss: 0.7303 - Accuracy: 0.3238 - F1: 0.2656
sub_8:Test (Best Model) - Loss: 0.6801 - Accuracy: 0.4286 - F1: 0.3211
sub_8:Test (Best Model) - Loss: 0.7724 - Accuracy: 0.2857 - F1: 0.1918
sub_8:Test (Best Model) - Loss: 0.6611 - Accuracy: 0.3524 - F1: 0.2381
sub_8:Test (Best Model) - Loss: 0.6942 - Accuracy: 0.3714 - F1: 0.3294
sub_8:Test (Best Model) - Loss: 0.6311 - Accuracy: 0.3810 - F1: 0.3037
sub_9:Test (Best Model) - Loss: 0.8057 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 0.8051 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 0.8061 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 0.8069 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 0.8106 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 0.8059 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 0.8049 - Accuracy: 0.2381 - F1: 0.1365
sub_9:Test (Best Model) - Loss: 0.8068 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 0.8062 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 0.8048 - Accuracy: 0.1905 - F1: 0.1078
sub_9:Test (Best Model) - Loss: 0.8056 - Accuracy: 0.2095 - F1: 0.0984
sub_9:Test (Best Model) - Loss: 0.8059 - Accuracy: 0.2286 - F1: 0.1144
sub_9:Test (Best Model) - Loss: 0.8069 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 0.8056 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 0.8096 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 0.8045 - Accuracy: 0.2095 - F1: 0.0848
sub_10:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.3143 - F1: 0.1806
sub_10:Test (Best Model) - Loss: 0.8129 - Accuracy: 0.2095 - F1: 0.1162
sub_10:Test (Best Model) - Loss: 0.8054 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 0.8080 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 0.8066 - Accuracy: 0.2381 - F1: 0.1541
sub_10:Test (Best Model) - Loss: 0.8119 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 0.8069 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 0.8078 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 0.8131 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 0.8066 - Accuracy: 0.2190 - F1: 0.1025
sub_10:Test (Best Model) - Loss: 0.8038 - Accuracy: 0.2095 - F1: 0.1116
sub_10:Test (Best Model) - Loss: 0.8055 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 0.8063 - Accuracy: 0.2381 - F1: 0.1349
sub_10:Test (Best Model) - Loss: 0.8039 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 0.8026 - Accuracy: 0.2190 - F1: 0.1002
sub_11:Test (Best Model) - Loss: 0.8056 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 0.8110 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 0.8045 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 0.7551 - Accuracy: 0.4286 - F1: 0.3506
sub_11:Test (Best Model) - Loss: 0.8070 - Accuracy: 0.2667 - F1: 0.1620
sub_11:Test (Best Model) - Loss: 0.8057 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 0.8077 - Accuracy: 0.2190 - F1: 0.1092
sub_11:Test (Best Model) - Loss: 0.7879 - Accuracy: 0.2952 - F1: 0.2475
sub_11:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2286 - F1: 0.1300
sub_11:Test (Best Model) - Loss: 0.8052 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 0.8074 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 0.8068 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 0.8054 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 0.8098 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 0.8101 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 0.8072 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 0.8052 - Accuracy: 0.2000 - F1: 0.0930
sub_12:Test (Best Model) - Loss: 0.8060 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 0.8075 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 0.8052 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 0.8055 - Accuracy: 0.2667 - F1: 0.1496
sub_12:Test (Best Model) - Loss: 0.8054 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 0.8068 - Accuracy: 0.2762 - F1: 0.1572
sub_12:Test (Best Model) - Loss: 0.8081 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 0.8030 - Accuracy: 0.2476 - F1: 0.1491
sub_12:Test (Best Model) - Loss: 0.8050 - Accuracy: 0.2667 - F1: 0.1752
sub_12:Test (Best Model) - Loss: 0.8049 - Accuracy: 0.2571 - F1: 0.1590
sub_12:Test (Best Model) - Loss: 0.8060 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 0.8012 - Accuracy: 0.2857 - F1: 0.1645
sub_13:Test (Best Model) - Loss: 0.8130 - Accuracy: 0.1905 - F1: 0.1625
sub_13:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.1090
sub_13:Test (Best Model) - Loss: 0.8042 - Accuracy: 0.2000 - F1: 0.1086
sub_13:Test (Best Model) - Loss: 0.8058 - Accuracy: 0.2476 - F1: 0.1396
sub_13:Test (Best Model) - Loss: 0.8083 - Accuracy: 0.2000 - F1: 0.1190
sub_13:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.3238 - F1: 0.1931
sub_13:Test (Best Model) - Loss: 0.8056 - Accuracy: 0.2286 - F1: 0.1303
sub_13:Test (Best Model) - Loss: 0.8057 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 0.8059 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 0.8058 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 0.8054 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 0.7866 - Accuracy: 0.3143 - F1: 0.2122
sub_13:Test (Best Model) - Loss: 0.8062 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 0.8035 - Accuracy: 0.2571 - F1: 0.1445
sub_13:Test (Best Model) - Loss: 0.8065 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 0.8010 - Accuracy: 0.2667 - F1: 0.1907
sub_14:Test (Best Model) - Loss: 0.7984 - Accuracy: 0.3238 - F1: 0.1824
sub_14:Test (Best Model) - Loss: 0.8045 - Accuracy: 0.2190 - F1: 0.1392
sub_14:Test (Best Model) - Loss: 0.8083 - Accuracy: 0.2190 - F1: 0.1311
sub_14:Test (Best Model) - Loss: 0.8090 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 0.8054 - Accuracy: 0.2190 - F1: 0.1025
sub_14:Test (Best Model) - Loss: 0.8034 - Accuracy: 0.2667 - F1: 0.1557
sub_14:Test (Best Model) - Loss: 0.7629 - Accuracy: 0.3048 - F1: 0.2034
sub_14:Test (Best Model) - Loss: 0.8062 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 0.8088 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 0.8053 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 0.8072 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 0.8051 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 0.8056 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0830

=== Summary Results ===

acc:   23.45 ± 4.86
F1:    12.06 ± 6.21
acc-in:27.97 ± 5.83
F1-in: 14.78 ± 7.58
