lr: 1e-06
sub_1:Test (Best Model) - Loss: 1.5980 - Accuracy: 0.1762 - F1: 0.0982
sub_2:Test (Best Model) - Loss: 1.6127 - Accuracy: 0.1762 - F1: 0.1028
sub_1:Test (Best Model) - Loss: 1.6696 - Accuracy: 0.2048 - F1: 0.0762
sub_3:Test (Best Model) - Loss: 1.6082 - Accuracy: 0.3238 - F1: 0.2286
sub_2:Test (Best Model) - Loss: 1.6180 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6432 - Accuracy: 0.2048 - F1: 0.0762
sub_1:Test (Best Model) - Loss: 1.6716 - Accuracy: 0.2048 - F1: 0.0779
sub_3:Test (Best Model) - Loss: 1.6467 - Accuracy: 0.1905 - F1: 0.0725
sub_1:Test (Best Model) - Loss: 1.7443 - Accuracy: 0.2095 - F1: 0.0850
sub_3:Test (Best Model) - Loss: 1.6503 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.5915 - Accuracy: 0.2286 - F1: 0.1184
sub_3:Test (Best Model) - Loss: 1.6044 - Accuracy: 0.2143 - F1: 0.1589
sub_2:Test (Best Model) - Loss: 1.6112 - Accuracy: 0.1905 - F1: 0.0781
sub_1:Test (Best Model) - Loss: 1.6539 - Accuracy: 0.1524 - F1: 0.1560
sub_3:Test (Best Model) - Loss: 1.6006 - Accuracy: 0.2238 - F1: 0.2294
sub_2:Test (Best Model) - Loss: 1.5996 - Accuracy: 0.2143 - F1: 0.1337
sub_1:Test (Best Model) - Loss: 1.6088 - Accuracy: 0.1857 - F1: 0.1682
sub_2:Test (Best Model) - Loss: 1.6141 - Accuracy: 0.1905 - F1: 0.1596
sub_3:Test (Best Model) - Loss: 1.5901 - Accuracy: 0.3000 - F1: 0.2045
sub_1:Test (Best Model) - Loss: 1.7070 - Accuracy: 0.2619 - F1: 0.1744
sub_2:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.4286 - F1: 0.3386
sub_3:Test (Best Model) - Loss: 1.6038 - Accuracy: 0.2524 - F1: 0.2276
sub_1:Test (Best Model) - Loss: 1.6696 - Accuracy: 0.2333 - F1: 0.1806
sub_3:Test (Best Model) - Loss: 1.6175 - Accuracy: 0.1667 - F1: 0.1233
sub_1:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.2667 - F1: 0.2135
sub_3:Test (Best Model) - Loss: 1.5908 - Accuracy: 0.2381 - F1: 0.1433
sub_2:Test (Best Model) - Loss: 1.5484 - Accuracy: 0.3190 - F1: 0.2740
sub_1:Test (Best Model) - Loss: 1.6380 - Accuracy: 0.2095 - F1: 0.1261
sub_2:Test (Best Model) - Loss: 1.5780 - Accuracy: 0.4000 - F1: 0.3187
sub_3:Test (Best Model) - Loss: 1.5775 - Accuracy: 0.2619 - F1: 0.1493
sub_1:Test (Best Model) - Loss: 1.5843 - Accuracy: 0.2381 - F1: 0.1473
sub_3:Test (Best Model) - Loss: 1.5901 - Accuracy: 0.2238 - F1: 0.1507
sub_2:Test (Best Model) - Loss: 1.6272 - Accuracy: 0.2381 - F1: 0.1359
sub_1:Test (Best Model) - Loss: 1.6155 - Accuracy: 0.2381 - F1: 0.1705
sub_3:Test (Best Model) - Loss: 1.5657 - Accuracy: 0.1952 - F1: 0.1128
sub_1:Test (Best Model) - Loss: 1.5922 - Accuracy: 0.2381 - F1: 0.1408
sub_3:Test (Best Model) - Loss: 1.9343 - Accuracy: 0.2000 - F1: 0.0765
sub_2:Test (Best Model) - Loss: 1.6222 - Accuracy: 0.2286 - F1: 0.1418
sub_3:Test (Best Model) - Loss: 1.6796 - Accuracy: 0.1952 - F1: 0.1033
sub_1:Test (Best Model) - Loss: 1.7519 - Accuracy: 0.2095 - F1: 0.1272
sub_2:Test (Best Model) - Loss: 1.6122 - Accuracy: 0.1952 - F1: 0.1144
sub_1:Test (Best Model) - Loss: 1.6799 - Accuracy: 0.1667 - F1: 0.0741
sub_2:Test (Best Model) - Loss: 1.6117 - Accuracy: 0.2857 - F1: 0.2133
sub_2:Test (Best Model) - Loss: 1.7211 - Accuracy: 0.1952 - F1: 0.1315
sub_2:Test (Best Model) - Loss: 1.6465 - Accuracy: 0.1952 - F1: 0.0832
sub_6:Test (Best Model) - Loss: 1.6124 - Accuracy: 0.2333 - F1: 0.1677
sub_5:Test (Best Model) - Loss: 1.6549 - Accuracy: 0.1476 - F1: 0.0962
sub_6:Test (Best Model) - Loss: 1.6655 - Accuracy: 0.2238 - F1: 0.1150
sub_4:Test (Best Model) - Loss: 1.5990 - Accuracy: 0.2667 - F1: 0.2047
sub_6:Test (Best Model) - Loss: 1.6351 - Accuracy: 0.1667 - F1: 0.0927
sub_5:Test (Best Model) - Loss: 1.8335 - Accuracy: 0.2048 - F1: 0.0771
sub_4:Test (Best Model) - Loss: 1.6086 - Accuracy: 0.2095 - F1: 0.0854
sub_6:Test (Best Model) - Loss: 1.6939 - Accuracy: 0.2000 - F1: 0.0672
sub_4:Test (Best Model) - Loss: 1.6168 - Accuracy: 0.2095 - F1: 0.1569
sub_5:Test (Best Model) - Loss: 1.6839 - Accuracy: 0.2048 - F1: 0.0874
sub_6:Test (Best Model) - Loss: 1.6230 - Accuracy: 0.1667 - F1: 0.1456
sub_5:Test (Best Model) - Loss: 1.8096 - Accuracy: 0.2000 - F1: 0.0752
sub_4:Test (Best Model) - Loss: 1.5967 - Accuracy: 0.1571 - F1: 0.0777
sub_6:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2286 - F1: 0.1997
sub_5:Test (Best Model) - Loss: 1.7182 - Accuracy: 0.2048 - F1: 0.1001
sub_4:Test (Best Model) - Loss: 1.6062 - Accuracy: 0.2381 - F1: 0.1562
sub_6:Test (Best Model) - Loss: 1.5835 - Accuracy: 0.2571 - F1: 0.1656
sub_5:Test (Best Model) - Loss: 1.6529 - Accuracy: 0.3048 - F1: 0.3068
sub_6:Test (Best Model) - Loss: 1.5885 - Accuracy: 0.2000 - F1: 0.1716
sub_4:Test (Best Model) - Loss: 1.5958 - Accuracy: 0.2857 - F1: 0.2592
sub_5:Test (Best Model) - Loss: 2.0721 - Accuracy: 0.2810 - F1: 0.1847
sub_5:Test (Best Model) - Loss: 1.8241 - Accuracy: 0.1857 - F1: 0.1323
sub_6:Test (Best Model) - Loss: 1.6335 - Accuracy: 0.2238 - F1: 0.1619
sub_4:Test (Best Model) - Loss: 1.6646 - Accuracy: 0.3143 - F1: 0.2377
sub_5:Test (Best Model) - Loss: 1.7290 - Accuracy: 0.2619 - F1: 0.2071
sub_6:Test (Best Model) - Loss: 1.6561 - Accuracy: 0.2333 - F1: 0.1293
sub_4:Test (Best Model) - Loss: 1.6055 - Accuracy: 0.2333 - F1: 0.1763
sub_6:Test (Best Model) - Loss: 4.2855 - Accuracy: 0.1905 - F1: 0.0912
sub_4:Test (Best Model) - Loss: 1.6340 - Accuracy: 0.2619 - F1: 0.1962
sub_5:Test (Best Model) - Loss: 1.8943 - Accuracy: 0.3190 - F1: 0.2054
sub_6:Test (Best Model) - Loss: 5.1508 - Accuracy: 0.2000 - F1: 0.1396
sub_4:Test (Best Model) - Loss: 1.7158 - Accuracy: 0.2524 - F1: 0.1765
sub_6:Test (Best Model) - Loss: 5.2581 - Accuracy: 0.2143 - F1: 0.1533
sub_5:Test (Best Model) - Loss: 1.6022 - Accuracy: 0.1857 - F1: 0.0629
sub_4:Test (Best Model) - Loss: 1.6153 - Accuracy: 0.1667 - F1: 0.1030
sub_4:Test (Best Model) - Loss: 1.6181 - Accuracy: 0.1905 - F1: 0.1304
sub_6:Test (Best Model) - Loss: 1.6404 - Accuracy: 0.2381 - F1: 0.1591
sub_6:Test (Best Model) - Loss: 4.0464 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6156 - Accuracy: 0.1905 - F1: 0.1415
sub_5:Test (Best Model) - Loss: 1.5926 - Accuracy: 0.2476 - F1: 0.1966
sub_4:Test (Best Model) - Loss: 1.6066 - Accuracy: 0.2143 - F1: 0.1567
sub_4:Test (Best Model) - Loss: 1.6210 - Accuracy: 0.2190 - F1: 0.1243
sub_5:Test (Best Model) - Loss: 1.5991 - Accuracy: 0.2095 - F1: 0.0966
sub_5:Test (Best Model) - Loss: 1.6112 - Accuracy: 0.2048 - F1: 0.1266
sub_5:Test (Best Model) - Loss: 1.6208 - Accuracy: 0.2286 - F1: 0.1334
sub_7:Test (Best Model) - Loss: 1.6208 - Accuracy: 0.1952 - F1: 0.0745
sub_7:Test (Best Model) - Loss: 1.6717 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.5702 - Accuracy: 0.3524 - F1: 0.2904
sub_9:Test (Best Model) - Loss: 1.5665 - Accuracy: 0.3429 - F1: 0.2126
sub_7:Test (Best Model) - Loss: 1.6138 - Accuracy: 0.2048 - F1: 0.1297
sub_9:Test (Best Model) - Loss: 1.6706 - Accuracy: 0.2286 - F1: 0.1202
sub_8:Test (Best Model) - Loss: 1.6057 - Accuracy: 0.2048 - F1: 0.0762
sub_7:Test (Best Model) - Loss: 1.6460 - Accuracy: 0.1667 - F1: 0.0903
sub_9:Test (Best Model) - Loss: 1.5483 - Accuracy: 0.2143 - F1: 0.0975
sub_7:Test (Best Model) - Loss: 1.6136 - Accuracy: 0.2429 - F1: 0.2128
sub_8:Test (Best Model) - Loss: 1.5679 - Accuracy: 0.3476 - F1: 0.2101
sub_9:Test (Best Model) - Loss: 1.6575 - Accuracy: 0.2000 - F1: 0.1067
sub_8:Test (Best Model) - Loss: 1.6169 - Accuracy: 0.2048 - F1: 0.0763
sub_9:Test (Best Model) - Loss: 1.6058 - Accuracy: 0.2381 - F1: 0.1468
sub_7:Test (Best Model) - Loss: 1.6333 - Accuracy: 0.2048 - F1: 0.1428
sub_7:Test (Best Model) - Loss: 1.6303 - Accuracy: 0.2048 - F1: 0.1311
sub_9:Test (Best Model) - Loss: 1.5563 - Accuracy: 0.3286 - F1: 0.2273
sub_8:Test (Best Model) - Loss: 1.5928 - Accuracy: 0.2238 - F1: 0.1346
sub_7:Test (Best Model) - Loss: 1.6315 - Accuracy: 0.2000 - F1: 0.1144
sub_7:Test (Best Model) - Loss: 1.6244 - Accuracy: 0.2524 - F1: 0.2253
sub_9:Test (Best Model) - Loss: 1.6076 - Accuracy: 0.2571 - F1: 0.1546
sub_8:Test (Best Model) - Loss: 1.5795 - Accuracy: 0.3762 - F1: 0.3240
sub_7:Test (Best Model) - Loss: 1.6525 - Accuracy: 0.2048 - F1: 0.1016
sub_7:Test (Best Model) - Loss: 1.6240 - Accuracy: 0.1524 - F1: 0.0779
sub_9:Test (Best Model) - Loss: 1.5620 - Accuracy: 0.3000 - F1: 0.2311
sub_8:Test (Best Model) - Loss: 1.5505 - Accuracy: 0.3762 - F1: 0.2312
sub_7:Test (Best Model) - Loss: 1.6229 - Accuracy: 0.1905 - F1: 0.1089
sub_9:Test (Best Model) - Loss: 1.5530 - Accuracy: 0.3143 - F1: 0.2370
sub_7:Test (Best Model) - Loss: 1.6847 - Accuracy: 0.2000 - F1: 0.1242
sub_8:Test (Best Model) - Loss: 1.5501 - Accuracy: 0.3762 - F1: 0.3126
sub_9:Test (Best Model) - Loss: 1.5720 - Accuracy: 0.2000 - F1: 0.1384
sub_7:Test (Best Model) - Loss: 1.6751 - Accuracy: 0.1571 - F1: 0.0865
sub_8:Test (Best Model) - Loss: 1.5775 - Accuracy: 0.3429 - F1: 0.2587
sub_9:Test (Best Model) - Loss: 1.7513 - Accuracy: 0.2143 - F1: 0.1173
sub_7:Test (Best Model) - Loss: 1.6165 - Accuracy: 0.2000 - F1: 0.0966
sub_9:Test (Best Model) - Loss: 1.7306 - Accuracy: 0.2095 - F1: 0.1259
sub_8:Test (Best Model) - Loss: 1.5541 - Accuracy: 0.3286 - F1: 0.2309
sub_9:Test (Best Model) - Loss: 1.8494 - Accuracy: 0.1571 - F1: 0.0625
sub_8:Test (Best Model) - Loss: 1.5519 - Accuracy: 0.3333 - F1: 0.2251
sub_9:Test (Best Model) - Loss: 1.6642 - Accuracy: 0.2286 - F1: 0.1323
sub_9:Test (Best Model) - Loss: 1.7125 - Accuracy: 0.1619 - F1: 0.0956
sub_8:Test (Best Model) - Loss: 1.5579 - Accuracy: 0.3762 - F1: 0.3315
sub_8:Test (Best Model) - Loss: 1.6709 - Accuracy: 0.2143 - F1: 0.1007
sub_8:Test (Best Model) - Loss: 1.5675 - Accuracy: 0.2095 - F1: 0.1247
sub_8:Test (Best Model) - Loss: 1.6192 - Accuracy: 0.2095 - F1: 0.0935
sub_11:Test (Best Model) - Loss: 1.6010 - Accuracy: 0.2619 - F1: 0.2237
sub_12:Test (Best Model) - Loss: 1.5929 - Accuracy: 0.2524 - F1: 0.1980
sub_11:Test (Best Model) - Loss: 1.6243 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.5970 - Accuracy: 0.2190 - F1: 0.1582
sub_12:Test (Best Model) - Loss: 1.6353 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.8506 - Accuracy: 0.2143 - F1: 0.0929
sub_12:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2286 - F1: 0.1511
sub_10:Test (Best Model) - Loss: 1.8629 - Accuracy: 0.2571 - F1: 0.1521
sub_12:Test (Best Model) - Loss: 1.6194 - Accuracy: 0.2000 - F1: 0.1105
sub_11:Test (Best Model) - Loss: 1.5707 - Accuracy: 0.3048 - F1: 0.1788
sub_12:Test (Best Model) - Loss: 1.6112 - Accuracy: 0.2000 - F1: 0.0937
sub_11:Test (Best Model) - Loss: 1.6174 - Accuracy: 0.1857 - F1: 0.0703
sub_10:Test (Best Model) - Loss: 1.8315 - Accuracy: 0.2095 - F1: 0.1082
sub_12:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2286 - F1: 0.2152
sub_11:Test (Best Model) - Loss: 1.6116 - Accuracy: 0.1952 - F1: 0.1078
sub_10:Test (Best Model) - Loss: 1.7510 - Accuracy: 0.1905 - F1: 0.0672
sub_12:Test (Best Model) - Loss: 1.6119 - Accuracy: 0.2048 - F1: 0.1529
sub_12:Test (Best Model) - Loss: 1.6282 - Accuracy: 0.1857 - F1: 0.1243
sub_10:Test (Best Model) - Loss: 1.5919 - Accuracy: 0.2810 - F1: 0.2311
sub_12:Test (Best Model) - Loss: 1.6033 - Accuracy: 0.2143 - F1: 0.1605
sub_11:Test (Best Model) - Loss: 1.5772 - Accuracy: 0.2095 - F1: 0.0861
sub_10:Test (Best Model) - Loss: 1.6054 - Accuracy: 0.2524 - F1: 0.1698
sub_12:Test (Best Model) - Loss: 1.6459 - Accuracy: 0.2000 - F1: 0.0750
sub_10:Test (Best Model) - Loss: 1.6040 - Accuracy: 0.2095 - F1: 0.1400
sub_11:Test (Best Model) - Loss: 1.5572 - Accuracy: 0.3857 - F1: 0.2264
sub_10:Test (Best Model) - Loss: 1.6144 - Accuracy: 0.2810 - F1: 0.2290
sub_12:Test (Best Model) - Loss: 1.9146 - Accuracy: 0.2286 - F1: 0.1111
sub_11:Test (Best Model) - Loss: 1.5542 - Accuracy: 0.4048 - F1: 0.3408
sub_12:Test (Best Model) - Loss: 1.8093 - Accuracy: 0.1905 - F1: 0.1236
sub_10:Test (Best Model) - Loss: 1.6074 - Accuracy: 0.2476 - F1: 0.1686
sub_12:Test (Best Model) - Loss: 1.8385 - Accuracy: 0.1905 - F1: 0.0721
sub_10:Test (Best Model) - Loss: 1.6746 - Accuracy: 0.1619 - F1: 0.0749
sub_11:Test (Best Model) - Loss: 1.5980 - Accuracy: 0.3238 - F1: 0.1932
sub_10:Test (Best Model) - Loss: 1.6361 - Accuracy: 0.1952 - F1: 0.1271
sub_11:Test (Best Model) - Loss: 1.5815 - Accuracy: 0.2905 - F1: 0.1853
sub_12:Test (Best Model) - Loss: 1.6370 - Accuracy: 0.2810 - F1: 0.2271
sub_10:Test (Best Model) - Loss: 1.7223 - Accuracy: 0.1524 - F1: 0.0772
sub_12:Test (Best Model) - Loss: 1.7064 - Accuracy: 0.1952 - F1: 0.0656
sub_10:Test (Best Model) - Loss: 1.5952 - Accuracy: 0.2333 - F1: 0.1432
sub_11:Test (Best Model) - Loss: 1.5720 - Accuracy: 0.2762 - F1: 0.1593
sub_10:Test (Best Model) - Loss: 1.6256 - Accuracy: 0.1905 - F1: 0.0643
sub_11:Test (Best Model) - Loss: 1.6175 - Accuracy: 0.2190 - F1: 0.1463
sub_11:Test (Best Model) - Loss: 1.5963 - Accuracy: 0.2143 - F1: 0.1209
sub_11:Test (Best Model) - Loss: 1.5980 - Accuracy: 0.2619 - F1: 0.1770
sub_11:Test (Best Model) - Loss: 1.6119 - Accuracy: 0.2381 - F1: 0.1424
sub_14:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.1714 - F1: 0.0690
sub_14:Test (Best Model) - Loss: 1.6039 - Accuracy: 0.2048 - F1: 0.0762
sub_13:Test (Best Model) - Loss: 1.5741 - Accuracy: 0.2810 - F1: 0.1732
sub_13:Test (Best Model) - Loss: 1.6224 - Accuracy: 0.1952 - F1: 0.0659
sub_14:Test (Best Model) - Loss: 1.6225 - Accuracy: 0.2810 - F1: 0.1861
sub_14:Test (Best Model) - Loss: 1.6050 - Accuracy: 0.1810 - F1: 0.1036
sub_13:Test (Best Model) - Loss: 1.5953 - Accuracy: 0.2000 - F1: 0.0669
sub_14:Test (Best Model) - Loss: 1.6157 - Accuracy: 0.2048 - F1: 0.0843
sub_13:Test (Best Model) - Loss: 1.6130 - Accuracy: 0.2190 - F1: 0.1032
sub_14:Test (Best Model) - Loss: 1.6138 - Accuracy: 0.2095 - F1: 0.1592
sub_13:Test (Best Model) - Loss: 1.6188 - Accuracy: 0.2000 - F1: 0.1595
sub_14:Test (Best Model) - Loss: 1.6183 - Accuracy: 0.2667 - F1: 0.1943
sub_13:Test (Best Model) - Loss: 1.6189 - Accuracy: 0.1810 - F1: 0.1633
sub_14:Test (Best Model) - Loss: 1.6031 - Accuracy: 0.2762 - F1: 0.2020
sub_14:Test (Best Model) - Loss: 1.5939 - Accuracy: 0.3095 - F1: 0.2600
sub_13:Test (Best Model) - Loss: 1.6050 - Accuracy: 0.2952 - F1: 0.1765
sub_13:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2048 - F1: 0.1611
sub_14:Test (Best Model) - Loss: 1.5766 - Accuracy: 0.3667 - F1: 0.2901
sub_13:Test (Best Model) - Loss: 1.6107 - Accuracy: 0.2048 - F1: 0.1445
sub_13:Test (Best Model) - Loss: 1.6564 - Accuracy: 0.2048 - F1: 0.1012
sub_14:Test (Best Model) - Loss: 1.6003 - Accuracy: 0.1762 - F1: 0.0828
sub_14:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.1762 - F1: 0.0898
sub_13:Test (Best Model) - Loss: 1.5720 - Accuracy: 0.3143 - F1: 0.1959
sub_13:Test (Best Model) - Loss: 1.5978 - Accuracy: 0.2714 - F1: 0.2185
sub_14:Test (Best Model) - Loss: 1.5914 - Accuracy: 0.2048 - F1: 0.0779
sub_14:Test (Best Model) - Loss: 1.6140 - Accuracy: 0.2381 - F1: 0.1519
sub_13:Test (Best Model) - Loss: 1.6069 - Accuracy: 0.2571 - F1: 0.1624
sub_13:Test (Best Model) - Loss: 1.6448 - Accuracy: 0.1952 - F1: 0.1345
sub_14:Test (Best Model) - Loss: 1.6036 - Accuracy: 0.2190 - F1: 0.1235
sub_13:Test (Best Model) - Loss: 1.6445 - Accuracy: 0.2000 - F1: 0.0835

=== Summary Results ===

acc: 23.18 ± 2.43
F1: 14.62 ± 1.93
acc-in: 25.07 ± 3.12
F1-in: 16.63 ± 2.66
runing time: 2013.53 seconds
