lr: 0.0001
sub_4:Test (Best Model) - Loss: 1.6110 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6109 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6113 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6015 - 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: 1.6112 - 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: 1.6095 - 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: 1.6048 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6084 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2000 - F1: 0.0667
sub_6: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_3:Test (Best Model) - Loss: 1.6111 - 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: 1.6103 - Accuracy: 0.2048 - F1: 0.0763
sub_7:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.2000 - F1: 0.0667
sub_5: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_4:Test (Best Model) - Loss: 1.6104 - 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: 1.6090 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2048 - F1: 0.0762
sub_1:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0747
sub_5:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2095 - F1: 0.1092
sub_6:Test (Best Model) - Loss: 1.6089 - Accuracy: 0.2238 - F1: 0.1542
sub_3:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.5778 - Accuracy: 0.3857 - F1: 0.2674
sub_5:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.1952 - F1: 0.0669
sub_7:Test (Best Model) - Loss: 1.6025 - Accuracy: 0.2286 - F1: 0.1224
sub_2:Test (Best Model) - Loss: 1.6082 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2000 - F1: 0.0672
sub_3:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.1952 - F1: 0.1021
sub_1:Test (Best Model) - Loss: 1.6087 - Accuracy: 0.2190 - F1: 0.1348
sub_4:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6085 - 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: 1.6078 - Accuracy: 0.2095 - F1: 0.0863
sub_5:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.1952 - F1: 0.1103
sub_6:Test (Best Model) - Loss: 1.4836 - Accuracy: 0.2667 - F1: 0.2277
sub_4:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2048 - F1: 0.0911
sub_7:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2095 - F1: 0.0854
sub_3:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.2714 - Accuracy: 0.4048 - F1: 0.2951
sub_7:Test (Best Model) - Loss: 1.6076 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.3973 - Accuracy: 0.3952 - F1: 0.3220
sub_3:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6046 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6077 - Accuracy: 0.2429 - F1: 0.1588
sub_1:Test (Best Model) - Loss: 1.4679 - Accuracy: 0.2857 - F1: 0.1884
sub_6:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6081 - Accuracy: 0.2429 - F1: 0.1327
sub_7:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0669
sub_4:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2048 - F1: 0.0946
sub_3:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6027 - Accuracy: 0.2762 - F1: 0.1808
sub_4:Test (Best Model) - Loss: 1.6090 - Accuracy: 0.2000 - F1: 0.0672
sub_5:Test (Best Model) - Loss: 1.6090 - 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: 1.3473 - Accuracy: 0.3810 - F1: 0.2676
sub_3:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.1952 - F1: 0.1372
sub_1:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.5998 - Accuracy: 0.2238 - F1: 0.1860
sub_7:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2143 - F1: 0.1288
sub_6:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.2095 - F1: 0.0972
sub_6:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6078 - Accuracy: 0.2476 - F1: 0.1683
sub_5:Test (Best Model) - Loss: 1.6054 - Accuracy: 0.2667 - F1: 0.1937
sub_2:Test (Best Model) - Loss: 1.6858 - Accuracy: 0.2571 - F1: 0.1656
sub_6:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.1905 - F1: 0.0831
sub_1:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2048 - F1: 0.0769
sub_3:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.1857 - F1: 0.0819
sub_7:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.1762 - F1: 0.0779
sub_3:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.1952 - F1: 0.0733
sub_1:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2048 - F1: 0.1040
sub_5:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2095 - F1: 0.0850
sub_2:Test (Best Model) - Loss: 1.5947 - Accuracy: 0.2619 - F1: 0.2099
sub_7:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.1952 - F1: 0.0672
sub_2:Test (Best Model) - Loss: 1.6090 - Accuracy: 0.2000 - F1: 0.0749
sub_5:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2048 - F1: 0.0763
sub_7:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0669
sub_1:Test (Best Model) - Loss: 1.6537 - Accuracy: 0.1952 - F1: 0.0985
sub_5:Test (Best Model) - Loss: 1.6090 - Accuracy: 0.1952 - F1: 0.0897
sub_2:Test (Best Model) - Loss: 1.5961 - Accuracy: 0.2714 - F1: 0.1563
sub_5:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.1952 - F1: 0.0983
sub_2:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0675
sub_11:Test (Best Model) - Loss: 1.6111 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6106 - 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: 1.6112 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6109 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6096 - 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: 1.6089 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6077 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6107 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6108 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6111 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6107 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2000 - F1: 0.0753
sub_10:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6107 - Accuracy: 0.2000 - F1: 0.0747
sub_12:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2000 - F1: 0.0669
sub_13:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.1126
sub_12:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6084 - Accuracy: 0.2143 - F1: 0.1274
sub_10:Test (Best Model) - Loss: 1.6038 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.1476 - F1: 0.0835
sub_9:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.1952 - F1: 0.1115
sub_13:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6071 - Accuracy: 0.2190 - F1: 0.1183
sub_11:Test (Best Model) - Loss: 1.5984 - Accuracy: 0.2381 - F1: 0.1405
sub_9:Test (Best Model) - Loss: 1.6078 - Accuracy: 0.2143 - F1: 0.1279
sub_8:Test (Best Model) - Loss: 1.5939 - Accuracy: 0.2952 - F1: 0.2379
sub_12:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.7144 - Accuracy: 0.2619 - F1: 0.1770
sub_11:Test (Best Model) - Loss: 1.6089 - 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: 1.6048 - Accuracy: 0.2000 - F1: 0.0747
sub_13:Test (Best Model) - Loss: 1.5230 - Accuracy: 0.2571 - F1: 0.1623
sub_11:Test (Best Model) - Loss: 1.6071 - Accuracy: 0.2048 - F1: 0.0762
sub_14:Test (Best Model) - Loss: 1.6138 - Accuracy: 0.1714 - F1: 0.0632
sub_10:Test (Best Model) - Loss: 1.6065 - Accuracy: 0.2095 - F1: 0.1082
sub_13:Test (Best Model) - Loss: 1.6085 - Accuracy: 0.1952 - F1: 0.0957
sub_11:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.2048 - F1: 0.0833
sub_8:Test (Best Model) - Loss: 1.6090 - Accuracy: 0.2524 - F1: 0.1461
sub_9:Test (Best Model) - Loss: 1.6026 - Accuracy: 0.2810 - F1: 0.1630
sub_12:Test (Best Model) - Loss: 1.5094 - Accuracy: 0.3048 - F1: 0.2118
sub_14:Test (Best Model) - Loss: 1.6085 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.1905 - F1: 0.0724
sub_10:Test (Best Model) - Loss: 1.6060 - Accuracy: 0.2810 - F1: 0.1803
sub_11:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6088 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6069 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2048 - F1: 0.0834
sub_11:Test (Best Model) - Loss: 1.6085 - Accuracy: 0.1905 - F1: 0.0954
sub_12:Test (Best Model) - Loss: 1.5715 - Accuracy: 0.2571 - F1: 0.1608
sub_13:Test (Best Model) - Loss: 1.5967 - Accuracy: 0.2238 - F1: 0.1481
sub_9:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2286 - F1: 0.1238
sub_11:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.2048 - F1: 0.1141
sub_13: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_9:Test (Best Model) - Loss: 1.6107 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.5953 - Accuracy: 0.2429 - F1: 0.1604
sub_11:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6053 - Accuracy: 0.2190 - F1: 0.1644
sub_13:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.1810 - F1: 0.0686
sub_8:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0669
sub_10:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.1952 - F1: 0.0653
sub_12:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6107 - Accuracy: 0.2000 - F1: 0.0762
sub_8:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6070 - Accuracy: 0.2381 - F1: 0.1378
sub_13:Test (Best Model) - Loss: 1.6076 - Accuracy: 0.2571 - F1: 0.1770
sub_12:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.1952 - F1: 0.0659
sub_10:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2190 - F1: 0.1584
sub_12:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6070 - Accuracy: 0.2286 - F1: 0.1225
sub_8:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2000 - F1: 0.0669
sub_12:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.1857 - F1: 0.0653
sub_14:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.1952 - F1: 0.0848
sub_12:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2048 - F1: 0.0764
sub_10:Test (Best Model) - Loss: 1.6089 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2048 - F1: 0.0835

=== Summary Results ===

acc: 21.10 ± 1.22
F1: 9.12 ± 1.41
acc-in: 22.42 ± 1.40
F1-in: 10.03 ± 1.84
runing time: 924.10 seconds
