lr: 1e-06
sub_2:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0669
sub_8:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.1714 - F1: 0.1013
sub_1:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2095 - F1: 0.1194
sub_9:Test (Best Model) - Loss: 1.6108 - Accuracy: 0.1429 - F1: 0.0792
sub_6:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.1905 - F1: 0.0645
sub_3:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2000 - F1: 0.0675
sub_4:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2000 - F1: 0.0932
sub_10:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.1952 - F1: 0.0904
sub_5:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.1857 - F1: 0.1011
sub_7:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.1905 - F1: 0.1096
sub_6:Test (Best Model) - Loss: 1.6109 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6108 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6107 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6107 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6108 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6110 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6108 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6108 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6084 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6089 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6112 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6114 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6122 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6117 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6111 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6112 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6112 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6113 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6116 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6110 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6111 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6112 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6107 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6111 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6097 - 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: 1.6098 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6097 - 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: 1.6095 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6091 - 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: 1.6106 - Accuracy: 0.1952 - F1: 0.0653
sub_3:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.1952 - F1: 0.0653
sub_5:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6116 - Accuracy: 0.2286 - F1: 0.1223
sub_8:Test (Best Model) - Loss: 1.6112 - Accuracy: 0.3095 - F1: 0.2023
sub_4:Test (Best Model) - Loss: 1.6117 - Accuracy: 0.1619 - F1: 0.0906
sub_2:Test (Best Model) - Loss: 1.6115 - Accuracy: 0.2048 - F1: 0.0762
sub_9:Test (Best Model) - Loss: 1.6121 - Accuracy: 0.1857 - F1: 0.0893
sub_3:Test (Best Model) - Loss: 1.6118 - Accuracy: 0.1524 - F1: 0.0876
sub_1:Test (Best Model) - Loss: 1.6118 - Accuracy: 0.2000 - F1: 0.0915
sub_10:Test (Best Model) - Loss: 1.6115 - Accuracy: 0.2143 - F1: 0.1285
sub_5:Test (Best Model) - Loss: 1.6116 - Accuracy: 0.2619 - F1: 0.1717
sub_7:Test (Best Model) - Loss: 1.6111 - Accuracy: 0.2095 - F1: 0.1049
sub_6:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.3143 - F1: 0.1977
sub_3:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.1762 - F1: 0.0731
sub_2:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.1952 - F1: 0.0856
sub_9:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2238 - F1: 0.1072
sub_5:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.1857 - F1: 0.0704
sub_10:Test (Best Model) - Loss: 1.6107 - Accuracy: 0.1952 - F1: 0.1014
sub_7:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.1905 - F1: 0.0877
sub_4:Test (Best Model) - Loss: 1.6116 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6114 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6131 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.1381 - F1: 0.0798
sub_5:Test (Best Model) - Loss: 1.6117 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2381 - F1: 0.1210
sub_7:Test (Best Model) - Loss: 1.6115 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6107 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6108 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6108 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2476 - F1: 0.1411
sub_8:Test (Best Model) - Loss: 1.6115 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6111 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6123 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6109 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6110 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6108 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.2095 - F1: 0.0854
sub_3:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2000 - F1: 0.0669
sub_2:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6117 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6108 - Accuracy: 0.1952 - F1: 0.0653
sub_6:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2000 - F1: 0.0669
sub_1:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6113 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2000 - F1: 0.0669
sub_1:Test (Best Model) - Loss: 1.6108 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2048 - F1: 0.0763
sub_14:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.1619 - F1: 0.0882
sub_11:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2095 - F1: 0.1075
sub_14:Test (Best Model) - Loss: 1.6110 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6111 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6108 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6110 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6109 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6114 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6114 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6108 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6114 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6113 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.1952 - F1: 0.0653
sub_12:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6110 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6107 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6117 - Accuracy: 0.2571 - F1: 0.1647
sub_13:Test (Best Model) - Loss: 1.6113 - Accuracy: 0.2095 - F1: 0.0854
sub_14:Test (Best Model) - Loss: 1.6113 - Accuracy: 0.2571 - F1: 0.1663
sub_11:Test (Best Model) - Loss: 1.6116 - Accuracy: 0.1714 - F1: 0.0869
sub_12:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6109 - Accuracy: 0.1810 - F1: 0.0998
sub_13:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2238 - F1: 0.1149
sub_14:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.1762 - F1: 0.1012
sub_11:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.1857 - F1: 0.0767
sub_12:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6116 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6120 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6118 - 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: 1.6107 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6108 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6110 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6108 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6138 - Accuracy: 0.1476 - F1: 0.0577
sub_14:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6108 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2000 - F1: 0.0667

=== Summary Results ===

acc: 20.05 ± 0.30
F1: 7.41 ± 0.34
acc-in: 20.12 ± 0.43
F1-in: 7.50 ± 0.38
runing time: 1702.64 seconds
