lr: 1e-06
sub_1:Test (Best Model) - Loss: 1.6144 - Accuracy: 0.1571 - F1: 0.0657
sub_2:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.2000 - F1: 0.1277
sub_1:Test (Best Model) - Loss: 1.7130 - 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: 1.6283 - Accuracy: 0.2190 - F1: 0.1171
sub_1:Test (Best Model) - Loss: 1.7183 - Accuracy: 0.1810 - F1: 0.0787
sub_2:Test (Best Model) - Loss: 1.6147 - Accuracy: 0.2571 - F1: 0.1481
sub_3:Test (Best Model) - Loss: 1.6347 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6976 - Accuracy: 0.1905 - F1: 0.0910
sub_2:Test (Best Model) - Loss: 1.6284 - Accuracy: 0.2095 - F1: 0.0954
sub_3:Test (Best Model) - Loss: 1.6309 - Accuracy: 0.2095 - F1: 0.0850
sub_1:Test (Best Model) - Loss: 1.7134 - Accuracy: 0.1905 - F1: 0.0696
sub_2:Test (Best Model) - Loss: 1.6036 - Accuracy: 0.2286 - F1: 0.1216
sub_3:Test (Best Model) - Loss: 1.6176 - Accuracy: 0.2000 - F1: 0.0675
sub_1:Test (Best Model) - Loss: 1.5998 - Accuracy: 0.2095 - F1: 0.2061
sub_3:Test (Best Model) - Loss: 1.5988 - Accuracy: 0.2048 - F1: 0.1053
sub_2:Test (Best Model) - Loss: 1.6145 - Accuracy: 0.1714 - F1: 0.1533
sub_1:Test (Best Model) - Loss: 1.6833 - Accuracy: 0.2238 - F1: 0.1600
sub_1:Test (Best Model) - Loss: 1.6705 - Accuracy: 0.1810 - F1: 0.1211
sub_3:Test (Best Model) - Loss: 1.6061 - Accuracy: 0.2762 - F1: 0.2583
sub_2:Test (Best Model) - Loss: 1.6221 - Accuracy: 0.1714 - F1: 0.0990
sub_1:Test (Best Model) - Loss: 1.6084 - Accuracy: 0.2190 - F1: 0.1802
sub_3:Test (Best Model) - Loss: 1.6032 - Accuracy: 0.2095 - F1: 0.1595
sub_2:Test (Best Model) - Loss: 1.6019 - Accuracy: 0.2143 - F1: 0.1476
sub_1:Test (Best Model) - Loss: 1.5998 - Accuracy: 0.2143 - F1: 0.1280
sub_3:Test (Best Model) - Loss: 1.6191 - Accuracy: 0.1667 - F1: 0.0974
sub_1:Test (Best Model) - Loss: 1.5837 - Accuracy: 0.2048 - F1: 0.1224
sub_3:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.1571 - F1: 0.1396
sub_1:Test (Best Model) - Loss: 1.6018 - Accuracy: 0.2381 - F1: 0.1709
sub_2:Test (Best Model) - Loss: 1.6131 - Accuracy: 0.2905 - F1: 0.2367
sub_2:Test (Best Model) - Loss: 1.6276 - Accuracy: 0.2190 - F1: 0.1273
sub_3:Test (Best Model) - Loss: 1.5870 - Accuracy: 0.2667 - F1: 0.1510
sub_2:Test (Best Model) - Loss: 1.6529 - Accuracy: 0.1810 - F1: 0.1089
sub_1:Test (Best Model) - Loss: 1.5894 - Accuracy: 0.1952 - F1: 0.0661
sub_3:Test (Best Model) - Loss: 1.5791 - Accuracy: 0.1905 - F1: 0.0981
sub_2:Test (Best Model) - Loss: 1.6783 - Accuracy: 0.2048 - F1: 0.1107
sub_1:Test (Best Model) - Loss: 1.7565 - Accuracy: 0.1905 - F1: 0.1122
sub_1:Test (Best Model) - Loss: 1.6497 - Accuracy: 0.2048 - F1: 0.0911
sub_3:Test (Best Model) - Loss: 1.5688 - Accuracy: 0.2238 - F1: 0.1388
sub_2:Test (Best Model) - Loss: 1.5966 - Accuracy: 0.2619 - F1: 0.1577
sub_3:Test (Best Model) - Loss: 1.5711 - Accuracy: 0.1905 - F1: 0.1290
sub_2:Test (Best Model) - Loss: 1.7694 - Accuracy: 0.2238 - F1: 0.1680
sub_3:Test (Best Model) - Loss: 1.8356 - Accuracy: 0.2190 - F1: 0.1099
sub_2:Test (Best Model) - Loss: 1.6410 - Accuracy: 0.2095 - F1: 0.0863
sub_3:Test (Best Model) - Loss: 1.6828 - Accuracy: 0.2048 - F1: 0.0762
sub_6:Test (Best Model) - Loss: 1.6274 - Accuracy: 0.1905 - F1: 0.1232
sub_5:Test (Best Model) - Loss: 1.6335 - Accuracy: 0.1333 - F1: 0.0843
sub_6:Test (Best Model) - Loss: 1.6531 - Accuracy: 0.1952 - F1: 0.0745
sub_4:Test (Best Model) - Loss: 1.6176 - Accuracy: 0.2476 - F1: 0.1791
sub_5:Test (Best Model) - Loss: 1.8594 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6160 - Accuracy: 0.1286 - F1: 0.0731
sub_4:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6840 - Accuracy: 0.2000 - F1: 0.0675
sub_4:Test (Best Model) - Loss: 1.6127 - Accuracy: 0.2143 - F1: 0.1333
sub_5:Test (Best Model) - Loss: 1.6793 - Accuracy: 0.2095 - F1: 0.0985
sub_6:Test (Best Model) - Loss: 1.6071 - Accuracy: 0.2095 - F1: 0.1314
sub_4:Test (Best Model) - Loss: 1.5970 - Accuracy: 0.2048 - F1: 0.0986
sub_6:Test (Best Model) - Loss: 1.6156 - Accuracy: 0.1810 - F1: 0.1503
sub_5:Test (Best Model) - Loss: 1.6949 - Accuracy: 0.1905 - F1: 0.0721
sub_4:Test (Best Model) - Loss: 1.6060 - Accuracy: 0.1857 - F1: 0.0710
sub_5:Test (Best Model) - Loss: 1.7344 - Accuracy: 0.1952 - F1: 0.0992
sub_4:Test (Best Model) - Loss: 1.6113 - Accuracy: 0.2143 - F1: 0.1742
sub_6:Test (Best Model) - Loss: 1.5915 - Accuracy: 0.2571 - F1: 0.1853
sub_4:Test (Best Model) - Loss: 1.6486 - Accuracy: 0.1762 - F1: 0.1345
sub_5:Test (Best Model) - Loss: 1.7323 - Accuracy: 0.2714 - F1: 0.2501
sub_4:Test (Best Model) - Loss: 1.6246 - Accuracy: 0.2000 - F1: 0.1272
sub_6:Test (Best Model) - Loss: 1.5984 - Accuracy: 0.1857 - F1: 0.1352
sub_5:Test (Best Model) - Loss: 1.9888 - Accuracy: 0.2333 - F1: 0.1549
sub_6:Test (Best Model) - Loss: 1.6229 - Accuracy: 0.2095 - F1: 0.1422
sub_5:Test (Best Model) - Loss: 1.8660 - Accuracy: 0.2095 - F1: 0.1115
sub_6:Test (Best Model) - Loss: 1.6568 - Accuracy: 0.2000 - F1: 0.0672
sub_5:Test (Best Model) - Loss: 1.7471 - Accuracy: 0.2286 - F1: 0.1742
sub_4:Test (Best Model) - Loss: 1.6310 - Accuracy: 0.2714 - F1: 0.2192
sub_6:Test (Best Model) - Loss: 2.8445 - Accuracy: 0.1524 - F1: 0.0669
sub_4:Test (Best Model) - Loss: 1.6752 - Accuracy: 0.2190 - F1: 0.1477
sub_4:Test (Best Model) - Loss: 1.6109 - Accuracy: 0.2048 - F1: 0.1142
sub_6:Test (Best Model) - Loss: 3.9887 - Accuracy: 0.2048 - F1: 0.1151
sub_5:Test (Best Model) - Loss: 1.9804 - Accuracy: 0.2190 - F1: 0.1135
sub_4:Test (Best Model) - Loss: 1.6088 - Accuracy: 0.2000 - F1: 0.0909
sub_6:Test (Best Model) - Loss: 1.9808 - Accuracy: 0.2524 - F1: 0.1857
sub_5:Test (Best Model) - Loss: 1.6176 - Accuracy: 0.2000 - F1: 0.1042
sub_6:Test (Best Model) - Loss: 1.6676 - Accuracy: 0.2000 - F1: 0.0952
sub_5:Test (Best Model) - Loss: 1.6241 - Accuracy: 0.2286 - F1: 0.1425
sub_4:Test (Best Model) - Loss: 1.6117 - Accuracy: 0.2190 - F1: 0.1921
sub_5:Test (Best Model) - Loss: 1.6012 - Accuracy: 0.2429 - F1: 0.1781
sub_4:Test (Best Model) - Loss: 1.6046 - Accuracy: 0.2238 - F1: 0.1456
sub_6:Test (Best Model) - Loss: 3.0991 - Accuracy: 0.1952 - F1: 0.0664
sub_5:Test (Best Model) - Loss: 1.6434 - Accuracy: 0.2000 - F1: 0.1172
sub_4:Test (Best Model) - Loss: 1.6188 - Accuracy: 0.2190 - F1: 0.1317
sub_5:Test (Best Model) - Loss: 1.6072 - Accuracy: 0.2619 - F1: 0.2053
sub_7:Test (Best Model) - Loss: 1.6195 - Accuracy: 0.2048 - F1: 0.1016
sub_7:Test (Best Model) - Loss: 1.6584 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2190 - F1: 0.1239
sub_9:Test (Best Model) - Loss: 1.6054 - Accuracy: 0.2238 - F1: 0.1266
sub_8:Test (Best Model) - Loss: 1.6179 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6692 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.5926 - Accuracy: 0.2000 - F1: 0.1457
sub_7:Test (Best Model) - Loss: 1.6272 - Accuracy: 0.2095 - F1: 0.1056
sub_9:Test (Best Model) - Loss: 1.5722 - Accuracy: 0.2095 - F1: 0.0902
sub_8:Test (Best Model) - Loss: 1.6035 - Accuracy: 0.2048 - F1: 0.0771
sub_9:Test (Best Model) - Loss: 1.6480 - Accuracy: 0.1476 - F1: 0.0708
sub_8:Test (Best Model) - Loss: 1.6240 - Accuracy: 0.1905 - F1: 0.0722
sub_7:Test (Best Model) - Loss: 1.6193 - Accuracy: 0.2429 - F1: 0.1863
sub_9:Test (Best Model) - Loss: 1.6446 - Accuracy: 0.1905 - F1: 0.0814
sub_8:Test (Best Model) - Loss: 1.6186 - Accuracy: 0.1667 - F1: 0.0672
sub_7:Test (Best Model) - Loss: 1.6112 - Accuracy: 0.1905 - F1: 0.1265
sub_9:Test (Best Model) - Loss: 1.6131 - Accuracy: 0.1905 - F1: 0.1840
sub_8:Test (Best Model) - Loss: 1.6133 - Accuracy: 0.2333 - F1: 0.2202
sub_7:Test (Best Model) - Loss: 1.6117 - Accuracy: 0.1810 - F1: 0.1252
sub_8:Test (Best Model) - Loss: 1.5938 - Accuracy: 0.3000 - F1: 0.2208
sub_7:Test (Best Model) - Loss: 1.6485 - Accuracy: 0.1905 - F1: 0.1102
sub_9:Test (Best Model) - Loss: 1.5906 - Accuracy: 0.2000 - F1: 0.1244
sub_8:Test (Best Model) - Loss: 1.6114 - Accuracy: 0.1667 - F1: 0.0954
sub_7:Test (Best Model) - Loss: 1.6342 - Accuracy: 0.2238 - F1: 0.1828
sub_9:Test (Best Model) - Loss: 1.6247 - Accuracy: 0.1905 - F1: 0.1631
sub_9:Test (Best Model) - Loss: 1.6038 - Accuracy: 0.1238 - F1: 0.0988
sub_7:Test (Best Model) - Loss: 1.6512 - Accuracy: 0.1952 - F1: 0.0734
sub_8:Test (Best Model) - Loss: 1.5988 - Accuracy: 0.2190 - F1: 0.1433
sub_7:Test (Best Model) - Loss: 1.6286 - Accuracy: 0.2048 - F1: 0.1088
sub_7:Test (Best Model) - Loss: 1.6121 - Accuracy: 0.2000 - F1: 0.0763
sub_9:Test (Best Model) - Loss: 1.5854 - Accuracy: 0.2667 - F1: 0.1732
sub_8:Test (Best Model) - Loss: 1.5870 - Accuracy: 0.2476 - F1: 0.1569
sub_9:Test (Best Model) - Loss: 1.8924 - Accuracy: 0.1952 - F1: 0.0741
sub_7:Test (Best Model) - Loss: 1.6535 - Accuracy: 0.2476 - F1: 0.1806
sub_8:Test (Best Model) - Loss: 1.6622 - Accuracy: 0.2000 - F1: 0.0915
sub_9:Test (Best Model) - Loss: 1.8765 - Accuracy: 0.1619 - F1: 0.0984
sub_7:Test (Best Model) - Loss: 1.7261 - Accuracy: 0.2190 - F1: 0.1371
sub_8:Test (Best Model) - Loss: 1.6195 - Accuracy: 0.2714 - F1: 0.2121
sub_7:Test (Best Model) - Loss: 1.6031 - Accuracy: 0.2048 - F1: 0.0912
sub_9:Test (Best Model) - Loss: 1.8066 - Accuracy: 0.1381 - F1: 0.0489
sub_8:Test (Best Model) - Loss: 1.6427 - Accuracy: 0.2095 - F1: 0.0849
sub_9:Test (Best Model) - Loss: 1.6983 - Accuracy: 0.1381 - F1: 0.1103
sub_8:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.1952 - F1: 0.1349
sub_9:Test (Best Model) - Loss: 1.7691 - Accuracy: 0.2000 - F1: 0.0672
sub_8:Test (Best Model) - Loss: 1.6279 - Accuracy: 0.2048 - F1: 0.0767
sub_12:Test (Best Model) - Loss: 1.6017 - Accuracy: 0.2143 - F1: 0.1338
sub_11:Test (Best Model) - Loss: 1.6124 - Accuracy: 0.1857 - F1: 0.1281
sub_10:Test (Best Model) - Loss: 1.6156 - Accuracy: 0.2000 - F1: 0.1277
sub_12:Test (Best Model) - Loss: 1.6260 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6222 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.8355 - Accuracy: 0.1952 - F1: 0.0653
sub_12:Test (Best Model) - Loss: 1.6142 - Accuracy: 0.1714 - F1: 0.0894
sub_11:Test (Best Model) - Loss: 1.6109 - Accuracy: 0.2143 - F1: 0.1227
sub_12:Test (Best Model) - Loss: 1.6156 - Accuracy: 0.2190 - F1: 0.1138
sub_10:Test (Best Model) - Loss: 1.7186 - Accuracy: 0.2238 - F1: 0.1310
sub_11:Test (Best Model) - Loss: 1.6224 - Accuracy: 0.1810 - F1: 0.0798
sub_12:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.2000 - F1: 0.0761
sub_11:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2048 - F1: 0.0986
sub_10:Test (Best Model) - Loss: 1.9463 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6130 - Accuracy: 0.2381 - F1: 0.2120
sub_11:Test (Best Model) - Loss: 1.6083 - Accuracy: 0.2476 - F1: 0.2189
sub_10:Test (Best Model) - Loss: 1.6418 - Accuracy: 0.2048 - F1: 0.0911
sub_12:Test (Best Model) - Loss: 1.6058 - Accuracy: 0.2048 - F1: 0.1437
sub_10:Test (Best Model) - Loss: 1.6061 - Accuracy: 0.2048 - F1: 0.1748
sub_11:Test (Best Model) - Loss: 1.5900 - Accuracy: 0.2762 - F1: 0.1585
sub_12:Test (Best Model) - Loss: 1.6266 - Accuracy: 0.1762 - F1: 0.1248
sub_11:Test (Best Model) - Loss: 1.6042 - Accuracy: 0.2000 - F1: 0.1525
sub_10:Test (Best Model) - Loss: 1.6135 - Accuracy: 0.2190 - F1: 0.1555
sub_12:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.1905 - F1: 0.1419
sub_11:Test (Best Model) - Loss: 1.6253 - Accuracy: 0.2524 - F1: 0.1885
sub_10:Test (Best Model) - Loss: 1.6117 - Accuracy: 0.1762 - F1: 0.1148
sub_12:Test (Best Model) - Loss: 1.6279 - Accuracy: 0.1905 - F1: 0.0784
sub_11:Test (Best Model) - Loss: 1.6296 - Accuracy: 0.2095 - F1: 0.0862
sub_12:Test (Best Model) - Loss: 1.8482 - Accuracy: 0.2429 - F1: 0.1284
sub_10:Test (Best Model) - Loss: 1.6212 - Accuracy: 0.3095 - F1: 0.2384
sub_12:Test (Best Model) - Loss: 1.6832 - Accuracy: 0.1762 - F1: 0.1252
sub_10:Test (Best Model) - Loss: 1.6139 - Accuracy: 0.1810 - F1: 0.0882
sub_11:Test (Best Model) - Loss: 1.6084 - Accuracy: 0.2000 - F1: 0.0672
sub_12:Test (Best Model) - Loss: 1.8081 - Accuracy: 0.2000 - F1: 0.0669
sub_10:Test (Best Model) - Loss: 1.6604 - Accuracy: 0.2238 - F1: 0.1284
sub_12:Test (Best Model) - Loss: 1.5817 - Accuracy: 0.2095 - F1: 0.1707
sub_10:Test (Best Model) - Loss: 1.6410 - Accuracy: 0.1857 - F1: 0.1434
sub_11:Test (Best Model) - Loss: 1.6048 - Accuracy: 0.2381 - F1: 0.2048
sub_12:Test (Best Model) - Loss: 1.6703 - Accuracy: 0.2000 - F1: 0.0667
sub_11:Test (Best Model) - Loss: 1.6004 - Accuracy: 0.2333 - F1: 0.1361
sub_10:Test (Best Model) - Loss: 1.6814 - Accuracy: 0.1762 - F1: 0.1088
sub_10:Test (Best Model) - Loss: 1.6370 - Accuracy: 0.1952 - F1: 0.0664
sub_11:Test (Best Model) - Loss: 1.6118 - Accuracy: 0.2000 - F1: 0.1279
sub_11:Test (Best Model) - Loss: 1.6119 - Accuracy: 0.2000 - F1: 0.1019
sub_10:Test (Best Model) - Loss: 1.6255 - Accuracy: 0.1905 - F1: 0.0741
sub_13:Test (Best Model) - Loss: 1.6187 - Accuracy: 0.2000 - F1: 0.1411
sub_14:Test (Best Model) - Loss: 1.6152 - Accuracy: 0.2048 - F1: 0.1017
sub_13:Test (Best Model) - Loss: 1.6182 - Accuracy: 0.2095 - F1: 0.0852
sub_14:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.1952 - F1: 0.0653
sub_14:Test (Best Model) - Loss: 1.6319 - Accuracy: 0.1952 - F1: 0.1325
sub_13:Test (Best Model) - Loss: 1.5984 - Accuracy: 0.2048 - F1: 0.0771
sub_14:Test (Best Model) - Loss: 1.6046 - Accuracy: 0.2190 - F1: 0.1239
sub_13:Test (Best Model) - Loss: 1.6262 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6173 - Accuracy: 0.1810 - F1: 0.1056
sub_13:Test (Best Model) - Loss: 1.6143 - Accuracy: 0.1952 - F1: 0.1153
sub_14:Test (Best Model) - Loss: 1.6182 - Accuracy: 0.2190 - F1: 0.1794
sub_13:Test (Best Model) - Loss: 1.6052 - Accuracy: 0.2619 - F1: 0.2447
sub_14:Test (Best Model) - Loss: 1.6216 - Accuracy: 0.2381 - F1: 0.1687
sub_13:Test (Best Model) - Loss: 1.6054 - Accuracy: 0.3190 - F1: 0.1855
sub_14:Test (Best Model) - Loss: 1.6210 - Accuracy: 0.2524 - F1: 0.1818
sub_14:Test (Best Model) - Loss: 1.6133 - Accuracy: 0.2476 - F1: 0.1823
sub_13:Test (Best Model) - Loss: 1.5969 - Accuracy: 0.3333 - F1: 0.2933
sub_14:Test (Best Model) - Loss: 1.6270 - Accuracy: 0.2095 - F1: 0.1121
sub_13:Test (Best Model) - Loss: 1.6075 - Accuracy: 0.2381 - F1: 0.1814
sub_14:Test (Best Model) - Loss: 1.6086 - Accuracy: 0.1762 - F1: 0.0731
sub_13:Test (Best Model) - Loss: 1.6257 - Accuracy: 0.1952 - F1: 0.1151
sub_14:Test (Best Model) - Loss: 1.6110 - Accuracy: 0.1952 - F1: 0.1246
sub_14:Test (Best Model) - Loss: 1.6033 - Accuracy: 0.2000 - F1: 0.1755
sub_14:Test (Best Model) - Loss: 1.6200 - Accuracy: 0.2143 - F1: 0.1354
sub_13:Test (Best Model) - Loss: 1.5951 - Accuracy: 0.3286 - F1: 0.2190
sub_14:Test (Best Model) - Loss: 1.6130 - Accuracy: 0.2143 - F1: 0.0953
sub_13:Test (Best Model) - Loss: 1.5831 - Accuracy: 0.3905 - F1: 0.3297
sub_13:Test (Best Model) - Loss: 1.6007 - Accuracy: 0.3048 - F1: 0.2178
sub_13:Test (Best Model) - Loss: 1.6402 - Accuracy: 0.2000 - F1: 0.1198
sub_13:Test (Best Model) - Loss: 1.6366 - Accuracy: 0.1762 - F1: 0.0624

=== Summary Results ===

acc: 21.03 ± 1.40
F1: 12.51 ± 1.35
acc-in: 22.62 ± 1.67
F1-in: 13.73 ± 1.65
runing time: 1741.49 seconds
