lr: 0.0001
sub_4:Test (Best Model) - Loss: 1.6107 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6112 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6089 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6112 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6112 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6073 - Accuracy: 0.2000 - F1: 0.0669
sub_3:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0669
sub_4:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6111 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6065 - Accuracy: 0.2000 - F1: 0.0669
sub_5:Test (Best Model) - Loss: 1.6063 - Accuracy: 0.2286 - F1: 0.1329
sub_3:Test (Best Model) - Loss: 1.6109 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6110 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.3588 - Accuracy: 0.3810 - F1: 0.2825
sub_1:Test (Best Model) - Loss: 1.6031 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6085 - Accuracy: 0.2048 - F1: 0.0764
sub_4:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6063 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6088 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6109 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2048 - F1: 0.1002
sub_4:Test (Best Model) - Loss: 1.6087 - Accuracy: 0.1952 - F1: 0.1130
sub_6:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2381 - F1: 0.1332
sub_2:Test (Best Model) - Loss: 1.6080 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6083 - Accuracy: 0.2000 - F1: 0.0981
sub_5:Test (Best Model) - Loss: 1.6082 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.2000 - F1: 0.0675
sub_6:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0748
sub_2:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2000 - F1: 0.0669
sub_6:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6073 - Accuracy: 0.2095 - F1: 0.0941
sub_7:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.5889 - Accuracy: 0.3714 - F1: 0.2754
sub_4:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.5562 - Accuracy: 0.3238 - F1: 0.2446
sub_7:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.1952 - F1: 0.0739
sub_2:Test (Best Model) - Loss: 1.5976 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6089 - Accuracy: 0.2000 - F1: 0.1111
sub_5:Test (Best Model) - Loss: 1.6085 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.3648 - Accuracy: 0.3857 - F1: 0.3047
sub_7:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2048 - F1: 0.0763
sub_3:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6085 - Accuracy: 0.2048 - F1: 0.0924
sub_5:Test (Best Model) - Loss: 1.6034 - Accuracy: 0.2286 - F1: 0.1527
sub_7:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2143 - F1: 0.0989
sub_4:Test (Best Model) - Loss: 1.6035 - Accuracy: 0.2810 - F1: 0.2130
sub_6:Test (Best Model) - Loss: 1.6142 - Accuracy: 0.1857 - F1: 0.1455
sub_2:Test (Best Model) - Loss: 1.5210 - Accuracy: 0.2857 - F1: 0.1998
sub_5:Test (Best Model) - Loss: 1.6089 - Accuracy: 0.2000 - F1: 0.0669
sub_4:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.1952 - F1: 0.1260
sub_1:Test (Best Model) - Loss: 1.6076 - Accuracy: 0.2000 - F1: 0.0750
sub_7:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6032 - Accuracy: 0.2000 - F1: 0.0748
sub_4:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6135 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6015 - Accuracy: 0.2238 - F1: 0.1527
sub_5:Test (Best Model) - Loss: 1.6083 - Accuracy: 0.2238 - F1: 0.1307
sub_4:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.1952 - F1: 0.0669
sub_6:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.1524 - F1: 0.0647
sub_7:Test (Best Model) - Loss: 1.6068 - Accuracy: 0.2143 - F1: 0.1369
sub_3:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2000 - F1: 0.0672
sub_4:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.1905 - F1: 0.0952
sub_6:Test (Best Model) - Loss: 1.6156 - Accuracy: 0.1952 - F1: 0.1110
sub_7:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.2714 - Accuracy: 0.3810 - F1: 0.3243
sub_2:Test (Best Model) - Loss: 1.4783 - Accuracy: 0.3048 - F1: 0.2220
sub_3:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.5444 - Accuracy: 0.2810 - F1: 0.2110
sub_7:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0677
sub_5:Test (Best Model) - Loss: 1.5800 - Accuracy: 0.3143 - F1: 0.2580
sub_2:Test (Best Model) - Loss: 1.3600 - Accuracy: 0.3714 - F1: 0.2649
sub_3:Test (Best Model) - Loss: 1.6140 - Accuracy: 0.1905 - F1: 0.0944
sub_7:Test (Best Model) - Loss: 1.6107 - Accuracy: 0.2095 - F1: 0.0849
sub_5:Test (Best Model) - Loss: 1.6079 - Accuracy: 0.2238 - F1: 0.1171
sub_2:Test (Best Model) - Loss: 1.6085 - Accuracy: 0.2000 - F1: 0.0691
sub_1:Test (Best Model) - Loss: 1.4119 - Accuracy: 0.3667 - F1: 0.3067
sub_5:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2000 - F1: 0.0672
sub_1:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.4872 - Accuracy: 0.3286 - F1: 0.2392
sub_3:Test (Best Model) - Loss: 1.5926 - Accuracy: 0.2571 - F1: 0.1766
sub_2:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2048 - F1: 0.0834
sub_5:Test (Best Model) - Loss: 1.6144 - Accuracy: 0.3095 - F1: 0.2746
sub_1:Test (Best Model) - Loss: 2.3939 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.4770 - Accuracy: 0.3095 - F1: 0.2408
sub_5:Test (Best Model) - Loss: 1.5618 - Accuracy: 0.3048 - F1: 0.2164
sub_1:Test (Best Model) - Loss: 2.0007 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6708 - Accuracy: 0.2000 - F1: 0.0677
sub_12:Test (Best Model) - Loss: 1.6113 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6090 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6466 - Accuracy: 0.2048 - F1: 0.0781
sub_14:Test (Best Model) - Loss: 1.6073 - Accuracy: 0.2095 - F1: 0.0919
sub_10:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6155 - Accuracy: 0.2571 - F1: 0.1607
sub_14:Test (Best Model) - Loss: 1.6072 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6071 - Accuracy: 0.2381 - F1: 0.1417
sub_8:Test (Best Model) - Loss: 1.4868 - Accuracy: 0.2952 - F1: 0.2012
sub_10:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6904 - Accuracy: 0.1952 - F1: 0.0653
sub_13:Test (Best Model) - Loss: 1.6052 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6077 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6087 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.5946 - Accuracy: 0.2048 - F1: 0.0836
sub_9:Test (Best Model) - Loss: 1.6107 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6324 - Accuracy: 0.2286 - F1: 0.1191
sub_13:Test (Best Model) - Loss: 1.6067 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6030 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6085 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6056 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6111 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6002 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6029 - Accuracy: 0.3619 - F1: 0.2679
sub_9:Test (Best Model) - Loss: 1.8779 - Accuracy: 0.2429 - F1: 0.1347
sub_10:Test (Best Model) - Loss: 1.6086 - Accuracy: 0.2095 - F1: 0.0942
sub_13:Test (Best Model) - Loss: 1.6073 - Accuracy: 0.2000 - F1: 0.0675
sub_12:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.1857 - F1: 0.0647
sub_9:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6078 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6689 - Accuracy: 0.2095 - F1: 0.0867
sub_11:Test (Best Model) - Loss: 1.6086 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6074 - Accuracy: 0.2095 - F1: 0.0854
sub_14:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2048 - F1: 0.0835
sub_10:Test (Best Model) - Loss: 1.6071 - Accuracy: 0.2095 - F1: 0.1188
sub_11:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.1905 - F1: 0.0787
sub_13:Test (Best Model) - Loss: 1.5285 - Accuracy: 0.3143 - F1: 0.2064
sub_11:Test (Best Model) - Loss: 1.6078 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6078 - Accuracy: 0.2381 - F1: 0.1375
sub_8:Test (Best Model) - Loss: 1.1885 - Accuracy: 0.4429 - F1: 0.3541
sub_9:Test (Best Model) - Loss: 1.4875 - Accuracy: 0.3714 - F1: 0.2969
sub_13:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.1905 - F1: 0.0658
sub_11:Test (Best Model) - Loss: 1.5862 - Accuracy: 0.3095 - F1: 0.2357
sub_10:Test (Best Model) - Loss: 1.6078 - Accuracy: 0.2095 - F1: 0.0857
sub_14:Test (Best Model) - Loss: 1.5789 - Accuracy: 0.2952 - F1: 0.1964
sub_12:Test (Best Model) - Loss: 1.2054 - Accuracy: 0.4095 - F1: 0.3195
sub_13:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2048 - F1: 0.0764
sub_8:Test (Best Model) - Loss: 1.4745 - Accuracy: 0.3143 - F1: 0.1910
sub_10:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.2000 - F1: 0.0879
sub_14:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2048 - F1: 0.0973
sub_9:Test (Best Model) - Loss: 1.5100 - Accuracy: 0.3476 - F1: 0.2320
sub_11:Test (Best Model) - Loss: 1.5461 - Accuracy: 0.3238 - F1: 0.2284
sub_10:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2952 - F1: 0.1681
sub_14:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.5286 - Accuracy: 0.2667 - F1: 0.1718
sub_10:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.5940 - Accuracy: 0.3476 - F1: 0.2602
sub_12:Test (Best Model) - Loss: 1.5749 - Accuracy: 0.3048 - F1: 0.2001
sub_11:Test (Best Model) - Loss: 1.3318 - Accuracy: 0.4190 - F1: 0.3092
sub_8:Test (Best Model) - Loss: 1.2179 - Accuracy: 0.4476 - F1: 0.3914
sub_10:Test (Best Model) - Loss: 1.6089 - Accuracy: 0.2000 - F1: 0.0672
sub_14:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.1810 - F1: 0.0691
sub_10:Test (Best Model) - Loss: 1.6070 - Accuracy: 0.2667 - F1: 0.1505
sub_13:Test (Best Model) - Loss: 1.4635 - Accuracy: 0.3524 - F1: 0.2514
sub_9:Test (Best Model) - Loss: 1.2388 - Accuracy: 0.4000 - F1: 0.2775
sub_8:Test (Best Model) - Loss: 1.5124 - Accuracy: 0.3000 - F1: 0.2224
sub_10:Test (Best Model) - Loss: 1.6060 - Accuracy: 0.2524 - F1: 0.1373
sub_14:Test (Best Model) - Loss: 1.6036 - Accuracy: 0.2429 - F1: 0.1411
sub_12:Test (Best Model) - Loss: 1.5192 - Accuracy: 0.3000 - F1: 0.2240
sub_11:Test (Best Model) - Loss: 1.5859 - Accuracy: 0.3667 - F1: 0.2792
sub_13:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.1810 - F1: 0.0756
sub_9:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.2000 - F1: 0.0754
sub_8:Test (Best Model) - Loss: 1.5223 - Accuracy: 0.2905 - F1: 0.1783
sub_13:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.1857 - F1: 0.1208
sub_12:Test (Best Model) - Loss: 1.5780 - Accuracy: 0.2476 - F1: 0.1439
sub_9:Test (Best Model) - Loss: 1.5347 - Accuracy: 0.2667 - F1: 0.1678
sub_13:Test (Best Model) - Loss: 1.6085 - Accuracy: 0.1952 - F1: 0.0656
sub_8:Test (Best Model) - Loss: 1.5129 - Accuracy: 0.3095 - F1: 0.2004
sub_11:Test (Best Model) - Loss: 1.5380 - Accuracy: 0.2905 - F1: 0.1761
sub_12:Test (Best Model) - Loss: 1.6075 - Accuracy: 0.2190 - F1: 0.1603
sub_9:Test (Best Model) - Loss: 1.4710 - Accuracy: 0.3333 - F1: 0.2279
sub_12:Test (Best Model) - Loss: 1.6081 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.4954 - Accuracy: 0.3238 - F1: 0.2149
sub_13:Test (Best Model) - Loss: 1.5359 - Accuracy: 0.3286 - F1: 0.2551
sub_12:Test (Best Model) - Loss: 1.6000 - Accuracy: 0.2381 - F1: 0.1251
sub_9:Test (Best Model) - Loss: 1.4883 - Accuracy: 0.3048 - F1: 0.1979
sub_8:Test (Best Model) - Loss: 1.2076 - Accuracy: 0.4286 - F1: 0.3864
sub_12:Test (Best Model) - Loss: 1.5356 - Accuracy: 0.3238 - F1: 0.2134
sub_11:Test (Best Model) - Loss: 1.5185 - Accuracy: 0.3143 - F1: 0.2321
sub_11:Test (Best Model) - Loss: 1.6130 - Accuracy: 0.1857 - F1: 0.1076
sub_8:Test (Best Model) - Loss: 1.4534 - Accuracy: 0.3429 - F1: 0.2356
sub_9:Test (Best Model) - Loss: 1.5751 - Accuracy: 0.2524 - F1: 0.1593
sub_12:Test (Best Model) - Loss: 1.4407 - Accuracy: 0.3238 - F1: 0.2293
sub_8:Test (Best Model) - Loss: 1.5320 - Accuracy: 0.3000 - F1: 0.2378
sub_8:Test (Best Model) - Loss: 1.4895 - Accuracy: 0.3667 - F1: 0.2884

=== Summary Results ===

acc: 23.72 ± 3.08
F1: 12.36 ± 3.70
acc-in: 26.84 ± 4.50
F1-in: 15.18 ± 5.10
runing time: 942.59 seconds
