lr: 0.0001
sub_8:Test (Best Model) - Loss: 1.6080 - Accuracy: 0.2000 - F1: 0.0672
sub_1:Test (Best Model) - Loss: 1.6021 - Accuracy: 0.2476 - F1: 0.1417
sub_6:Test (Best Model) - Loss: 1.6076 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.1952 - F1: 0.0656
sub_9:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6086 - Accuracy: 0.2048 - F1: 0.0922
sub_5:Test (Best Model) - Loss: 1.5540 - Accuracy: 0.2667 - F1: 0.2044
sub_2:Test (Best Model) - Loss: 1.3404 - Accuracy: 0.3619 - F1: 0.2400
sub_6:Test (Best Model) - Loss: 1.6082 - Accuracy: 0.2238 - F1: 0.1067
sub_4:Test (Best Model) - Loss: 1.6088 - Accuracy: 0.2000 - F1: 0.0763
sub_10:Test (Best Model) - Loss: 1.6038 - Accuracy: 0.2429 - F1: 0.1434
sub_3:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0750
sub_9:Test (Best Model) - Loss: 1.6089 - Accuracy: 0.1952 - F1: 0.0913
sub_7:Test (Best Model) - Loss: 1.6065 - Accuracy: 0.2381 - F1: 0.1775
sub_6:Test (Best Model) - Loss: 1.6089 - Accuracy: 0.2286 - F1: 0.1229
sub_8:Test (Best Model) - Loss: 1.6048 - Accuracy: 0.3286 - F1: 0.2070
sub_1:Test (Best Model) - Loss: 1.5840 - Accuracy: 0.3238 - F1: 0.2225
sub_5:Test (Best Model) - Loss: 1.5532 - Accuracy: 0.2905 - F1: 0.2017
sub_2:Test (Best Model) - Loss: 1.4290 - Accuracy: 0.3429 - F1: 0.2032
sub_3:Test (Best Model) - Loss: 1.6089 - Accuracy: 0.2095 - F1: 0.1449
sub_6:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.1857 - F1: 0.1271
sub_10:Test (Best Model) - Loss: 1.4174 - Accuracy: 0.3571 - F1: 0.3083
sub_9:Test (Best Model) - Loss: 1.5871 - Accuracy: 0.2571 - F1: 0.1670
sub_7:Test (Best Model) - Loss: 1.5689 - Accuracy: 0.2905 - F1: 0.1841
sub_5:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6986 - Accuracy: 0.2048 - F1: 0.1065
sub_3:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0669
sub_6:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.1952 - F1: 0.0811
sub_7:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.2095 - F1: 0.1039
sub_5:Test (Best Model) - Loss: 1.6077 - Accuracy: 0.1714 - F1: 0.0695
sub_3:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.2336 - Accuracy: 0.4476 - F1: 0.3685
sub_9:Test (Best Model) - Loss: 1.6082 - Accuracy: 0.1952 - F1: 0.0774
sub_8:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6085 - Accuracy: 0.1952 - F1: 0.0756
sub_4:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2048 - F1: 0.1215
sub_10:Test (Best Model) - Loss: 1.4768 - Accuracy: 0.3429 - F1: 0.2872
sub_3:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2000 - F1: 0.0669
sub_9:Test (Best Model) - Loss: 1.6079 - Accuracy: 0.1857 - F1: 0.0741
sub_1:Test (Best Model) - Loss: 1.5195 - Accuracy: 0.2667 - F1: 0.2123
sub_7:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.1952 - F1: 0.0744
sub_8:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0748
sub_6:Test (Best Model) - Loss: 1.6053 - Accuracy: 0.2000 - F1: 0.0853
sub_9:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2095 - F1: 0.0850
sub_7:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2238 - F1: 0.1123
sub_8:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2524 - F1: 0.1394
sub_3:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6088 - Accuracy: 0.2000 - F1: 0.0683
sub_9:Test (Best Model) - Loss: 1.6066 - Accuracy: 0.2524 - F1: 0.1578
sub_7:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2429 - F1: 0.1388
sub_1:Test (Best Model) - Loss: 1.6111 - Accuracy: 0.1905 - F1: 0.1252
sub_2:Test (Best Model) - Loss: 1.6230 - Accuracy: 0.2524 - F1: 0.1717
sub_3:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.1714 - F1: 0.1043
sub_4:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0672
sub_5:Test (Best Model) - Loss: 1.5664 - Accuracy: 0.2810 - F1: 0.1980
sub_10:Test (Best Model) - Loss: 1.4227 - Accuracy: 0.3429 - F1: 0.2700
sub_7:Test (Best Model) - Loss: 1.6010 - Accuracy: 0.2143 - F1: 0.0933
sub_1:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.1762 - F1: 0.0790
sub_4:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.5325 - Accuracy: 0.2810 - F1: 0.2251
sub_5:Test (Best Model) - Loss: 1.6088 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2048 - F1: 0.1135
sub_10:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.5185 - Accuracy: 0.2952 - F1: 0.2068
sub_9:Test (Best Model) - Loss: 1.6081 - Accuracy: 0.2857 - F1: 0.1852
sub_7:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2048 - F1: 0.0762
sub_8:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.1714 - F1: 0.1002
sub_3:Test (Best Model) - Loss: 1.6069 - Accuracy: 0.2238 - F1: 0.1328
sub_6:Test (Best Model) - Loss: 1.6087 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0750
sub_5:Test (Best Model) - Loss: 1.6071 - Accuracy: 0.1857 - F1: 0.0783
sub_9:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6086 - Accuracy: 0.1810 - F1: 0.1025
sub_1:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.1762 - F1: 0.1139
sub_4:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.1952 - F1: 0.1418
sub_6:Test (Best Model) - Loss: 1.5890 - Accuracy: 0.2905 - F1: 0.2000
sub_5:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.2037 - Accuracy: 0.4381 - F1: 0.3780
sub_7:Test (Best Model) - Loss: 1.6053 - Accuracy: 0.2095 - F1: 0.0944
sub_8:Test (Best Model) - Loss: 1.6084 - Accuracy: 0.2048 - F1: 0.0835
sub_1:Test (Best Model) - Loss: 1.6073 - Accuracy: 0.2286 - F1: 0.1847
sub_4:Test (Best Model) - Loss: 1.6048 - Accuracy: 0.2143 - F1: 0.1610
sub_10:Test (Best Model) - Loss: 1.5605 - Accuracy: 0.2571 - F1: 0.1740
sub_3:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.1952 - F1: 0.0659
sub_9:Test (Best Model) - Loss: 2.0125 - Accuracy: 0.2095 - F1: 0.0866
sub_7:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0672
sub_8:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.1952 - F1: 0.1086
sub_4:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0669
sub_7:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.2623 - Accuracy: 0.4238 - F1: 0.3547
sub_5:Test (Best Model) - Loss: 1.5629 - Accuracy: 0.3048 - F1: 0.1969
sub_3:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.1667 - F1: 0.0929
sub_9:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.1952 - F1: 0.0653
sub_6:Test (Best Model) - Loss: 1.5739 - Accuracy: 0.2667 - F1: 0.2150
sub_4:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.3908 - Accuracy: 0.3429 - F1: 0.2741
sub_10:Test (Best Model) - Loss: 1.3167 - Accuracy: 0.3381 - F1: 0.2844
sub_6:Test (Best Model) - Loss: 1.6085 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6392 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2048 - F1: 0.0833
sub_8:Test (Best Model) - Loss: 2.3453 - Accuracy: 0.2095 - F1: 0.0870
sub_2:Test (Best Model) - Loss: 1.2156 - Accuracy: 0.3952 - F1: 0.3425
sub_5:Test (Best Model) - Loss: 1.5188 - Accuracy: 0.3048 - F1: 0.2265
sub_6:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6076 - Accuracy: 0.2143 - F1: 0.0938
sub_7:Test (Best Model) - Loss: 1.5350 - Accuracy: 0.3238 - F1: 0.2625
sub_8:Test (Best Model) - Loss: 1.6090 - Accuracy: 0.2095 - F1: 0.0852
sub_10:Test (Best Model) - Loss: 1.3263 - Accuracy: 0.3524 - F1: 0.2822
sub_7:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.1952 - F1: 0.0984
sub_1:Test (Best Model) - Loss: 1.6593 - Accuracy: 0.1857 - F1: 0.0723
sub_8:Test (Best Model) - Loss: 1.6064 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.5587 - Accuracy: 0.2714 - F1: 0.1899
sub_2:Test (Best Model) - Loss: 1.2116 - Accuracy: 0.4429 - F1: 0.4202
sub_8:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2048 - F1: 0.0764
sub_5:Test (Best Model) - Loss: 1.6088 - Accuracy: 0.2143 - F1: 0.0931
sub_2:Test (Best Model) - Loss: 1.6083 - Accuracy: 0.2048 - F1: 0.0762
sub_8:Test (Best Model) - Loss: 1.6069 - Accuracy: 0.2000 - F1: 0.0834
sub_5:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.1952 - F1: 0.0653
sub_10:Test (Best Model) - Loss: 1.3882 - Accuracy: 0.3952 - F1: 0.3540
sub_2:Test (Best Model) - Loss: 1.6858 - Accuracy: 0.2619 - F1: 0.1756
sub_1:Test (Best Model) - Loss: 2.0978 - Accuracy: 0.2667 - F1: 0.1801
sub_10:Test (Best Model) - Loss: 1.5172 - Accuracy: 0.3190 - F1: 0.2493
sub_2:Test (Best Model) - Loss: 1.5519 - Accuracy: 0.3095 - F1: 0.2357
sub_1:Test (Best Model) - Loss: 1.5763 - Accuracy: 0.2524 - F1: 0.1864
sub_10:Test (Best Model) - Loss: 1.6545 - Accuracy: 0.2810 - F1: 0.2115
sub_2:Test (Best Model) - Loss: 1.5329 - Accuracy: 0.3048 - F1: 0.2338
sub_2:Test (Best Model) - Loss: 1.5727 - Accuracy: 0.2571 - F1: 0.1658
sub_10:Test (Best Model) - Loss: 1.6982 - Accuracy: 0.2667 - F1: 0.1838
sub_1:Test (Best Model) - Loss: 1.5974 - Accuracy: 0.3000 - F1: 0.2769
sub_2:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.5651 - Accuracy: 0.2381 - F1: 0.1386
sub_10:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.5382 - Accuracy: 0.3286 - F1: 0.2379
sub_11:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.2000 - F1: 0.0683
sub_13:Test (Best Model) - Loss: 1.6088 - Accuracy: 0.1952 - F1: 0.0741
sub_12:Test (Best Model) - Loss: 1.6133 - Accuracy: 0.1952 - F1: 0.1083
sub_11:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6112 - Accuracy: 0.1857 - F1: 0.0886
sub_14:Test (Best Model) - Loss: 1.4984 - Accuracy: 0.3333 - F1: 0.2430
sub_11:Test (Best Model) - Loss: 1.6080 - Accuracy: 0.1905 - F1: 0.1338
sub_13:Test (Best Model) - Loss: 1.5966 - Accuracy: 0.2238 - F1: 0.1091
sub_11:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2095 - F1: 0.0848
sub_12:Test (Best Model) - Loss: 1.5282 - Accuracy: 0.2952 - F1: 0.2002
sub_14:Test (Best Model) - Loss: 1.7229 - Accuracy: 0.2762 - F1: 0.2170
sub_13:Test (Best Model) - Loss: 1.6083 - Accuracy: 0.2000 - F1: 0.1110
sub_11:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6089 - Accuracy: 0.2048 - F1: 0.0915
sub_14:Test (Best Model) - Loss: 1.5335 - Accuracy: 0.3190 - F1: 0.2531
sub_13:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2000 - F1: 0.0755
sub_11:Test (Best Model) - Loss: 1.6087 - Accuracy: 0.2048 - F1: 0.0763
sub_12:Test (Best Model) - Loss: 1.6121 - Accuracy: 0.2571 - F1: 0.2344
sub_11:Test (Best Model) - Loss: 1.6087 - Accuracy: 0.2000 - F1: 0.0752
sub_12:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.2000 - F1: 0.0694
sub_13:Test (Best Model) - Loss: 1.6088 - Accuracy: 0.2429 - F1: 0.1387
sub_11:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6435 - Accuracy: 0.2952 - F1: 0.1969
sub_13:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.1952 - F1: 0.0653
sub_12:Test (Best Model) - Loss: 1.6011 - Accuracy: 0.2286 - F1: 0.1505
sub_11:Test (Best Model) - Loss: 1.6089 - Accuracy: 0.2095 - F1: 0.0859
sub_14:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.5999 - Accuracy: 0.2333 - F1: 0.1441
sub_12:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2143 - F1: 0.0985
sub_13:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.1952 - F1: 0.1110
sub_14:Test (Best Model) - Loss: 1.5980 - Accuracy: 0.2714 - F1: 0.1798
sub_12:Test (Best Model) - Loss: 1.6087 - Accuracy: 0.2238 - F1: 0.1289
sub_13:Test (Best Model) - Loss: 1.6090 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.1952 - F1: 0.0800
sub_11:Test (Best Model) - Loss: 1.5418 - Accuracy: 0.3238 - F1: 0.2583
sub_12:Test (Best Model) - Loss: 1.6162 - Accuracy: 0.1857 - F1: 0.0713
sub_14:Test (Best Model) - Loss: 1.3852 - Accuracy: 0.3429 - F1: 0.2849
sub_13:Test (Best Model) - Loss: 1.5681 - Accuracy: 0.2619 - F1: 0.1784
sub_11:Test (Best Model) - Loss: 1.6069 - Accuracy: 0.2143 - F1: 0.1609
sub_12:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6081 - Accuracy: 0.2000 - F1: 0.0680
sub_11:Test (Best Model) - Loss: 1.5886 - Accuracy: 0.2333 - F1: 0.1485
sub_13:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2095 - F1: 0.1085
sub_12:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2048 - F1: 0.1037
sub_14:Test (Best Model) - Loss: 1.6090 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2000 - F1: 0.0669
sub_14:Test (Best Model) - Loss: 1.6487 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6116 - Accuracy: 0.2000 - F1: 0.0706
sub_14:Test (Best Model) - Loss: 1.6117 - Accuracy: 0.1810 - F1: 0.0739
sub_12:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2048 - F1: 0.0762
sub_14:Test (Best Model) - Loss: 1.6125 - Accuracy: 0.1857 - F1: 0.0919
sub_14:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2286 - F1: 0.1244

=== Summary Results ===

acc: 23.13 ± 3.52
F1: 12.58 ± 4.52
acc-in: 25.82 ± 4.43
F1-in: 15.10 ± 5.36
runing time: 2895.94 seconds
