lr: 1e-05
sub_6:Test (Best Model) - Loss: 1.6132 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6131 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6131 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6133 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6132 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6132 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6131 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6130 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6129 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6129 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6117 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6116 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6116 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6130 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6130 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6130 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6128 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6127 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6126 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6127 - Accuracy: 0.2000 - F1: 0.0667
sub_7: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_6:Test (Best Model) - Loss: 1.6108 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6114 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2048 - F1: 0.0763
sub_1:Test (Best Model) - Loss: 1.6111 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6089 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6127 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6127 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6128 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.1429 - F1: 0.0823
sub_1:Test (Best Model) - Loss: 1.6129 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2048 - F1: 0.1018
sub_6:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6108 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2000 - F1: 0.0669
sub_3:Test (Best Model) - Loss: 1.6108 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.2048 - F1: 0.0762
sub_1:Test (Best Model) - Loss: 1.6107 - Accuracy: 0.2000 - F1: 0.0675
sub_4:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2048 - F1: 0.0763
sub_6:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6127 - Accuracy: 0.1571 - F1: 0.0555
sub_2:Test (Best Model) - Loss: 1.6122 - Accuracy: 0.1952 - F1: 0.0935
sub_4:Test (Best Model) - Loss: 1.6119 - Accuracy: 0.1952 - F1: 0.0994
sub_3:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.1476 - F1: 0.0795
sub_7:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.1762 - F1: 0.0818
sub_6:Test (Best Model) - Loss: 1.6111 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6109 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2381 - F1: 0.1420
sub_4:Test (Best Model) - Loss: 1.6113 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6113 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2190 - F1: 0.1184
sub_4:Test (Best Model) - Loss: 1.6109 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.1952 - F1: 0.0656
sub_6:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.0669
sub_3:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.2000 - F1: 0.0694
sub_5:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6124 - Accuracy: 0.1952 - F1: 0.0854
sub_7:Test (Best Model) - Loss: 1.6125 - Accuracy: 0.2095 - F1: 0.0849
sub_5:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6123 - Accuracy: 0.1857 - F1: 0.0701
sub_3:Test (Best Model) - Loss: 1.6111 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6113 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6124 - Accuracy: 0.1905 - F1: 0.0718
sub_1:Test (Best Model) - Loss: 1.6112 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6107 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6109 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6108 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6109 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0669
sub_1:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.1952 - F1: 0.0653
sub_5:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6134 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6133 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6129 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6128 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6128 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6132 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6133 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6109 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6129 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6129 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6124 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6112 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6117 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6115 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6126 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6126 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6128 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6129 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6129 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6127 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6125 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2000 - F1: 0.0667
sub_10: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_14:Test (Best Model) - Loss: 1.6114 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6117 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6076 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6127 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6123 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6125 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6126 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2048 - F1: 0.0835
sub_13:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.1952 - F1: 0.1123
sub_9:Test (Best Model) - Loss: 1.6086 - Accuracy: 0.2524 - F1: 0.1470
sub_10:Test (Best Model) - Loss: 1.6110 - Accuracy: 0.2048 - F1: 0.0765
sub_14:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.2048 - F1: 0.0764
sub_12:Test (Best Model) - Loss: 1.6109 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2143 - F1: 0.1233
sub_10:Test (Best Model) - Loss: 1.6098 - 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: 1.6098 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6087 - Accuracy: 0.3190 - F1: 0.1816
sub_9:Test (Best Model) - Loss: 1.6122 - Accuracy: 0.2048 - F1: 0.0769
sub_12:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2048 - F1: 0.1157
sub_14:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.1952 - F1: 0.1060
sub_13:Test (Best Model) - Loss: 1.6120 - Accuracy: 0.2048 - F1: 0.0834
sub_11:Test (Best Model) - Loss: 1.6121 - Accuracy: 0.2000 - F1: 0.0761
sub_9:Test (Best Model) - Loss: 1.6110 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6109 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2286 - F1: 0.1279
sub_14:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.1952 - F1: 0.0733
sub_11:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6109 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2048 - F1: 0.0764
sub_11:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2286 - F1: 0.1108
sub_10:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2048 - F1: 0.0765
sub_9:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.1810 - F1: 0.0618
sub_13:Test (Best Model) - Loss: 1.6100 - 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: 1.6098 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6123 - Accuracy: 0.2000 - F1: 0.0669
sub_11:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6122 - Accuracy: 0.2095 - F1: 0.1020
sub_8:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6120 - Accuracy: 0.2333 - F1: 0.1202
sub_14:Test (Best Model) - Loss: 1.6111 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6120 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6112 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6107 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.3048 - F1: 0.1836
sub_14:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6085 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.1714 - F1: 0.0662
sub_8:Test (Best Model) - Loss: 1.6108 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6067 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2000 - F1: 0.0667

=== Summary Results ===

acc: 20.11 ± 0.48
F1: 7.20 ± 0.42
acc-in: 20.57 ± 0.45
F1-in: 7.34 ± 0.47
runing time: 868.36 seconds
