lr: 1e-05
sub_3:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6072 - Accuracy: 0.2000 - F1: 0.0727
sub_6:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2000 - F1: 0.0683
sub_9:Test (Best Model) - Loss: 1.6088 - Accuracy: 0.1762 - F1: 0.0772
sub_7:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2000 - F1: 0.0762
sub_5:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.1952 - F1: 0.0804
sub_1:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2143 - F1: 0.1318
sub_3:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6090 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6080 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6089 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6090 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6074 - Accuracy: 0.2048 - F1: 0.0762
sub_10:Test (Best Model) - Loss: 1.6070 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6080 - Accuracy: 0.3381 - F1: 0.1953
sub_8:Test (Best Model) - Loss: 1.6062 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6058 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6112 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6075 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2000 - F1: 0.0680
sub_10:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6108 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6108 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6107 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6089 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.1857 - F1: 0.1057
sub_8:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6107 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6088 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6097 - 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: 1.6090 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6078 - Accuracy: 0.2238 - F1: 0.1067
sub_4:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.2000 - F1: 0.0669
sub_3:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2000 - F1: 0.0667
sub_6: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_7:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.1905 - F1: 0.0718
sub_8:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2524 - F1: 0.1610
sub_4:Test (Best Model) - Loss: 1.6110 - Accuracy: 0.1762 - F1: 0.0965
sub_2:Test (Best Model) - Loss: 1.6109 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6114 - Accuracy: 0.1667 - F1: 0.0922
sub_6:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.2286 - F1: 0.1183
sub_8:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.3238 - F1: 0.2236
sub_7:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2000 - F1: 0.0669
sub_10:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2476 - F1: 0.1537
sub_3:Test (Best Model) - Loss: 1.6111 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6107 - Accuracy: 0.2143 - F1: 0.1046
sub_6:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2048 - F1: 0.0762
sub_1:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0672
sub_4:Test (Best Model) - Loss: 1.6073 - Accuracy: 0.3333 - F1: 0.2204
sub_9:Test (Best Model) - Loss: 1.6090 - Accuracy: 0.2429 - F1: 0.1435
sub_7:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.1952 - F1: 0.0739
sub_3:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2048 - F1: 0.1082
sub_2:Test (Best Model) - Loss: 1.6116 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6115 - 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: 1.6090 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6109 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6130 - Accuracy: 0.1381 - F1: 0.0563
sub_3:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6031 - Accuracy: 0.3476 - F1: 0.2044
sub_8:Test (Best Model) - Loss: 1.6046 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6089 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6107 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6111 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0669
sub_4:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2095 - F1: 0.0854
sub_7:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2095 - F1: 0.0848
sub_10:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2095 - F1: 0.0854
sub_8:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6075 - Accuracy: 0.2095 - F1: 0.0919
sub_5:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.1952 - F1: 0.0653
sub_10:Test (Best Model) - Loss: 1.6110 - Accuracy: 0.2000 - F1: 0.0669
sub_8:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6101 - 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: 1.6071 - Accuracy: 0.2048 - F1: 0.0881
sub_12:Test (Best Model) - Loss: 1.6066 - Accuracy: 0.2000 - F1: 0.0680
sub_14:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6086 - Accuracy: 0.2667 - F1: 0.1514
sub_14:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6072 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6015 - Accuracy: 0.2524 - F1: 0.1496
sub_13:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6108 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6072 - Accuracy: 0.2476 - F1: 0.1556
sub_11:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6096 - 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: 1.6106 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6089 - Accuracy: 0.2143 - F1: 0.0938
sub_12:Test (Best Model) - Loss: 1.6062 - Accuracy: 0.3190 - F1: 0.1874
sub_11:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6102 - 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: 1.6082 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2238 - F1: 0.1095
sub_12:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2667 - F1: 0.1643
sub_13:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2905 - F1: 0.1929
sub_14:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6098 - 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: 1.6085 - Accuracy: 0.3048 - F1: 0.1940
sub_12:Test (Best Model) - Loss: 1.6108 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6117 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6110 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6082 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6084 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6064 - Accuracy: 0.2524 - F1: 0.1588
sub_14:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6109 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6107 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6100 - 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: 1.6141 - Accuracy: 0.1000 - F1: 0.0472
sub_11:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.5915 - Accuracy: 0.2762 - F1: 0.1719
sub_11:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2000 - F1: 0.0667

=== Summary Results ===

acc: 20.60 ± 0.56
F1: 7.77 ± 0.63
acc-in: 21.09 ± 0.77
F1-in: 8.45 ± 0.82
runing time: 1949.83 seconds
