lr: 1e-06
sub_2:Test (Best Model) - Loss: 1.6085 - Accuracy: 0.1952 - F1: 0.1024
sub_1:Test (Best Model) - Loss: 1.6125 - Accuracy: 0.1714 - F1: 0.0811
sub_3:Test (Best Model) - Loss: 1.6007 - Accuracy: 0.3000 - F1: 0.2286
sub_2:Test (Best Model) - Loss: 1.6164 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6154 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 1.6135 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.5995 - Accuracy: 0.3286 - F1: 0.1995
sub_3:Test (Best Model) - Loss: 1.6055 - Accuracy: 0.2048 - F1: 0.0762
sub_2:Test (Best Model) - Loss: 1.6148 - Accuracy: 0.1905 - F1: 0.0723
sub_1:Test (Best Model) - Loss: 1.5995 - Accuracy: 0.2095 - F1: 0.0871
sub_3:Test (Best Model) - Loss: 1.6197 - Accuracy: 0.2000 - F1: 0.0667
sub_2:Test (Best Model) - Loss: 1.6120 - Accuracy: 0.2333 - F1: 0.1338
sub_1:Test (Best Model) - Loss: 1.6083 - Accuracy: 0.2333 - F1: 0.1172
sub_3:Test (Best Model) - Loss: 1.6075 - Accuracy: 0.2000 - F1: 0.0934
sub_2:Test (Best Model) - Loss: 1.6128 - Accuracy: 0.1667 - F1: 0.1444
sub_1:Test (Best Model) - Loss: 1.6114 - Accuracy: 0.2000 - F1: 0.0792
sub_3:Test (Best Model) - Loss: 1.6069 - Accuracy: 0.2048 - F1: 0.1615
sub_1:Test (Best Model) - Loss: 1.6108 - Accuracy: 0.2190 - F1: 0.1881
sub_3:Test (Best Model) - Loss: 1.6061 - Accuracy: 0.2762 - F1: 0.2001
sub_2:Test (Best Model) - Loss: 1.6035 - Accuracy: 0.2429 - F1: 0.1365
sub_1:Test (Best Model) - Loss: 1.5993 - Accuracy: 0.2857 - F1: 0.1742
sub_2:Test (Best Model) - Loss: 1.6114 - Accuracy: 0.2095 - F1: 0.0854
sub_3:Test (Best Model) - Loss: 1.6079 - Accuracy: 0.1762 - F1: 0.1051
sub_1:Test (Best Model) - Loss: 1.6066 - Accuracy: 0.2095 - F1: 0.1018
sub_3:Test (Best Model) - Loss: 1.6069 - Accuracy: 0.1667 - F1: 0.1477
sub_1:Test (Best Model) - Loss: 1.6014 - Accuracy: 0.3476 - F1: 0.2697
sub_2:Test (Best Model) - Loss: 1.5998 - Accuracy: 0.3286 - F1: 0.2452
sub_3:Test (Best Model) - Loss: 1.6043 - Accuracy: 0.2095 - F1: 0.1049
sub_2:Test (Best Model) - Loss: 1.6061 - Accuracy: 0.2048 - F1: 0.0986
sub_3:Test (Best Model) - Loss: 1.6057 - Accuracy: 0.1762 - F1: 0.0951
sub_2:Test (Best Model) - Loss: 1.6013 - Accuracy: 0.2000 - F1: 0.1136
sub_1:Test (Best Model) - Loss: 1.5920 - Accuracy: 0.3048 - F1: 0.2272
sub_2:Test (Best Model) - Loss: 1.6028 - Accuracy: 0.2095 - F1: 0.0981
sub_1:Test (Best Model) - Loss: 1.5969 - Accuracy: 0.2000 - F1: 0.0818
sub_3:Test (Best Model) - Loss: 1.6026 - Accuracy: 0.2286 - F1: 0.1455
sub_2:Test (Best Model) - Loss: 1.5978 - Accuracy: 0.2095 - F1: 0.1302
sub_3:Test (Best Model) - Loss: 1.6036 - Accuracy: 0.1810 - F1: 0.1301
sub_2:Test (Best Model) - Loss: 1.6129 - Accuracy: 0.2333 - F1: 0.1811
sub_3:Test (Best Model) - Loss: 1.6178 - Accuracy: 0.2000 - F1: 0.0974
sub_1:Test (Best Model) - Loss: 1.5906 - Accuracy: 0.2619 - F1: 0.1924
sub_2:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.2000 - F1: 0.0675
sub_3:Test (Best Model) - Loss: 1.6135 - Accuracy: 0.2048 - F1: 0.0762
sub_1:Test (Best Model) - Loss: 1.5978 - Accuracy: 0.2333 - F1: 0.1306
sub_1:Test (Best Model) - Loss: 1.6196 - Accuracy: 0.1952 - F1: 0.1184
sub_1:Test (Best Model) - Loss: 1.6108 - Accuracy: 0.1952 - F1: 0.0879
sub_5:Test (Best Model) - Loss: 1.6132 - Accuracy: 0.2000 - F1: 0.1067
sub_6:Test (Best Model) - Loss: 1.6108 - Accuracy: 0.1619 - F1: 0.1022
sub_5:Test (Best Model) - Loss: 1.6405 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.1905 - F1: 0.0678
sub_4:Test (Best Model) - Loss: 1.6036 - Accuracy: 0.2571 - F1: 0.1880
sub_6:Test (Best Model) - Loss: 1.6089 - Accuracy: 0.1810 - F1: 0.1083
sub_4:Test (Best Model) - Loss: 1.6108 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.5992 - Accuracy: 0.2048 - F1: 0.0832
sub_6:Test (Best Model) - Loss: 1.6179 - Accuracy: 0.2000 - F1: 0.0672
sub_4:Test (Best Model) - Loss: 1.6055 - Accuracy: 0.2667 - F1: 0.1553
sub_5:Test (Best Model) - Loss: 1.6191 - Accuracy: 0.2000 - F1: 0.0749
sub_4:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2048 - F1: 0.0944
sub_6:Test (Best Model) - Loss: 1.6012 - Accuracy: 0.2381 - F1: 0.1549
sub_5:Test (Best Model) - Loss: 1.6285 - Accuracy: 0.2000 - F1: 0.0847
sub_6:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.1952 - F1: 0.1340
sub_5:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2048 - F1: 0.1595
sub_5:Test (Best Model) - Loss: 1.6046 - Accuracy: 0.2429 - F1: 0.1566
sub_4:Test (Best Model) - Loss: 1.5992 - Accuracy: 0.3095 - F1: 0.2339
sub_4:Test (Best Model) - Loss: 1.6081 - Accuracy: 0.2095 - F1: 0.1482
sub_5:Test (Best Model) - Loss: 1.6067 - Accuracy: 0.2190 - F1: 0.1469
sub_6:Test (Best Model) - Loss: 1.6050 - Accuracy: 0.2476 - F1: 0.1450
sub_6:Test (Best Model) - Loss: 1.6067 - Accuracy: 0.2095 - F1: 0.1274
sub_5:Test (Best Model) - Loss: 1.6021 - Accuracy: 0.2190 - F1: 0.1215
sub_4:Test (Best Model) - Loss: 1.6028 - Accuracy: 0.2333 - F1: 0.1433
sub_6:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2143 - F1: 0.1106
sub_4:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.1619 - F1: 0.1055
sub_6:Test (Best Model) - Loss: 1.6189 - Accuracy: 0.1810 - F1: 0.0700
sub_4:Test (Best Model) - Loss: 1.6054 - Accuracy: 0.2333 - F1: 0.1640
sub_5:Test (Best Model) - Loss: 1.5937 - Accuracy: 0.2952 - F1: 0.1823
sub_6:Test (Best Model) - Loss: 1.6034 - Accuracy: 0.2190 - F1: 0.1254
sub_4:Test (Best Model) - Loss: 1.5995 - Accuracy: 0.3238 - F1: 0.2399
sub_4:Test (Best Model) - Loss: 1.6029 - Accuracy: 0.2190 - F1: 0.1005
sub_6:Test (Best Model) - Loss: 1.6116 - Accuracy: 0.2143 - F1: 0.1168
sub_5:Test (Best Model) - Loss: 1.6036 - Accuracy: 0.2000 - F1: 0.0669
sub_4:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2048 - F1: 0.0851
sub_5:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.1952 - F1: 0.1059
sub_6:Test (Best Model) - Loss: 1.6013 - Accuracy: 0.2095 - F1: 0.1335
sub_5:Test (Best Model) - Loss: 1.6045 - Accuracy: 0.2429 - F1: 0.1572
sub_4:Test (Best Model) - Loss: 1.6031 - Accuracy: 0.2286 - F1: 0.1494
sub_5:Test (Best Model) - Loss: 1.6165 - Accuracy: 0.1762 - F1: 0.1080
sub_6:Test (Best Model) - Loss: 1.6222 - Accuracy: 0.2095 - F1: 0.1003
sub_4:Test (Best Model) - Loss: 1.6079 - Accuracy: 0.2143 - F1: 0.1307
sub_4:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2095 - F1: 0.0932
sub_6:Test (Best Model) - Loss: 1.6168 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2000 - F1: 0.0824
sub_7:Test (Best Model) - Loss: 1.6126 - Accuracy: 0.1476 - F1: 0.0863
sub_9:Test (Best Model) - Loss: 1.6108 - Accuracy: 0.1952 - F1: 0.1535
sub_7:Test (Best Model) - Loss: 1.6252 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6288 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.6051 - Accuracy: 0.1762 - F1: 0.0946
sub_9:Test (Best Model) - Loss: 1.5877 - Accuracy: 0.2714 - F1: 0.1584
sub_7:Test (Best Model) - Loss: 1.6032 - Accuracy: 0.2857 - F1: 0.1882
sub_8:Test (Best Model) - Loss: 1.6198 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6119 - Accuracy: 0.2048 - F1: 0.0832
sub_9:Test (Best Model) - Loss: 1.6157 - Accuracy: 0.1952 - F1: 0.0731
sub_7:Test (Best Model) - Loss: 1.6175 - Accuracy: 0.1905 - F1: 0.1219
sub_8:Test (Best Model) - Loss: 1.5901 - Accuracy: 0.2857 - F1: 0.1742
sub_8:Test (Best Model) - Loss: 1.6125 - Accuracy: 0.2048 - F1: 0.0764
sub_9:Test (Best Model) - Loss: 1.5885 - Accuracy: 0.2714 - F1: 0.1806
sub_7:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.2238 - F1: 0.1435
sub_8:Test (Best Model) - Loss: 1.6139 - Accuracy: 0.1905 - F1: 0.0693
sub_7:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2381 - F1: 0.1616
sub_9:Test (Best Model) - Loss: 1.6043 - Accuracy: 0.2714 - F1: 0.2720
sub_7:Test (Best Model) - Loss: 1.6139 - Accuracy: 0.1476 - F1: 0.0829
sub_8:Test (Best Model) - Loss: 1.5915 - Accuracy: 0.2905 - F1: 0.2138
sub_9:Test (Best Model) - Loss: 1.5856 - Accuracy: 0.2381 - F1: 0.1264
sub_7:Test (Best Model) - Loss: 1.6067 - Accuracy: 0.2429 - F1: 0.1818
sub_9:Test (Best Model) - Loss: 1.6077 - Accuracy: 0.1810 - F1: 0.1403
sub_7:Test (Best Model) - Loss: 1.6135 - Accuracy: 0.2000 - F1: 0.0667
sub_8:Test (Best Model) - Loss: 1.5775 - Accuracy: 0.3333 - F1: 0.2173
sub_9:Test (Best Model) - Loss: 1.5879 - Accuracy: 0.2000 - F1: 0.0998
sub_8:Test (Best Model) - Loss: 1.6062 - Accuracy: 0.1762 - F1: 0.1131
sub_7:Test (Best Model) - Loss: 1.6075 - Accuracy: 0.2143 - F1: 0.0931
sub_9:Test (Best Model) - Loss: 1.5949 - Accuracy: 0.2810 - F1: 0.1862
sub_8:Test (Best Model) - Loss: 1.5903 - Accuracy: 0.2429 - F1: 0.1349
sub_7:Test (Best Model) - Loss: 1.6018 - Accuracy: 0.2333 - F1: 0.1291
sub_9:Test (Best Model) - Loss: 1.6180 - Accuracy: 0.2000 - F1: 0.0669
sub_9:Test (Best Model) - Loss: 1.6167 - Accuracy: 0.1857 - F1: 0.1160
sub_7:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2048 - F1: 0.0845
sub_8:Test (Best Model) - Loss: 1.5663 - Accuracy: 0.2524 - F1: 0.1491
sub_7:Test (Best Model) - Loss: 1.6132 - Accuracy: 0.2333 - F1: 0.1648
sub_9:Test (Best Model) - Loss: 1.6166 - Accuracy: 0.1429 - F1: 0.0644
sub_8:Test (Best Model) - Loss: 1.5969 - Accuracy: 0.2000 - F1: 0.0669
sub_7:Test (Best Model) - Loss: 1.6130 - Accuracy: 0.1905 - F1: 0.0650
sub_9:Test (Best Model) - Loss: 1.6176 - Accuracy: 0.2000 - F1: 0.1449
sub_9:Test (Best Model) - Loss: 1.6138 - Accuracy: 0.2048 - F1: 0.0762
sub_8:Test (Best Model) - Loss: 1.5879 - Accuracy: 0.2381 - F1: 0.1321
sub_8:Test (Best Model) - Loss: 1.6001 - Accuracy: 0.2000 - F1: 0.0677
sub_8:Test (Best Model) - Loss: 1.6168 - Accuracy: 0.2381 - F1: 0.1588
sub_8:Test (Best Model) - Loss: 1.6123 - Accuracy: 0.2095 - F1: 0.0848
sub_10:Test (Best Model) - Loss: 1.6166 - Accuracy: 0.1762 - F1: 0.1037
sub_11:Test (Best Model) - Loss: 1.6112 - Accuracy: 0.2000 - F1: 0.1412
sub_10:Test (Best Model) - Loss: 1.6227 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.5985 - Accuracy: 0.2286 - F1: 0.1335
sub_11:Test (Best Model) - Loss: 1.6184 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 1.6170 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.5902 - Accuracy: 0.2333 - F1: 0.1211
sub_10:Test (Best Model) - Loss: 1.6135 - Accuracy: 0.2000 - F1: 0.0751
sub_10:Test (Best Model) - Loss: 1.6165 - Accuracy: 0.2048 - F1: 0.0786
sub_12:Test (Best Model) - Loss: 1.6044 - Accuracy: 0.3095 - F1: 0.1766
sub_11:Test (Best Model) - Loss: 1.5986 - Accuracy: 0.2571 - F1: 0.1489
sub_12:Test (Best Model) - Loss: 1.6121 - Accuracy: 0.1952 - F1: 0.0735
sub_11:Test (Best Model) - Loss: 1.6185 - Accuracy: 0.1905 - F1: 0.0640
sub_12:Test (Best Model) - Loss: 1.6065 - Accuracy: 0.2000 - F1: 0.0689
sub_10:Test (Best Model) - Loss: 1.6050 - Accuracy: 0.2667 - F1: 0.2386
sub_11:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.0952
sub_11:Test (Best Model) - Loss: 1.6055 - Accuracy: 0.2381 - F1: 0.2274
sub_10:Test (Best Model) - Loss: 1.5935 - Accuracy: 0.3095 - F1: 0.2224
sub_12:Test (Best Model) - Loss: 1.6033 - Accuracy: 0.2857 - F1: 0.2915
sub_10:Test (Best Model) - Loss: 1.6032 - Accuracy: 0.2190 - F1: 0.1870
sub_11:Test (Best Model) - Loss: 1.5883 - Accuracy: 0.3143 - F1: 0.1804
sub_10:Test (Best Model) - Loss: 1.5937 - Accuracy: 0.2524 - F1: 0.1684
sub_11:Test (Best Model) - Loss: 1.6037 - Accuracy: 0.2476 - F1: 0.1717
sub_12:Test (Best Model) - Loss: 1.5820 - Accuracy: 0.2286 - F1: 0.1206
sub_11:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2905 - F1: 0.1903
sub_12:Test (Best Model) - Loss: 1.6113 - Accuracy: 0.1619 - F1: 0.1019
sub_10:Test (Best Model) - Loss: 1.5887 - Accuracy: 0.3000 - F1: 0.1767
sub_12:Test (Best Model) - Loss: 1.5975 - Accuracy: 0.2476 - F1: 0.1482
sub_11:Test (Best Model) - Loss: 1.6075 - Accuracy: 0.2095 - F1: 0.1340
sub_10:Test (Best Model) - Loss: 1.5993 - Accuracy: 0.3000 - F1: 0.2341
sub_11:Test (Best Model) - Loss: 1.6074 - Accuracy: 0.1952 - F1: 0.0656
sub_12:Test (Best Model) - Loss: 1.5945 - Accuracy: 0.1857 - F1: 0.1104
sub_10:Test (Best Model) - Loss: 1.5974 - Accuracy: 0.2619 - F1: 0.1872
sub_12:Test (Best Model) - Loss: 1.6165 - Accuracy: 0.2048 - F1: 0.0815
sub_11:Test (Best Model) - Loss: 1.6037 - Accuracy: 0.1952 - F1: 0.1743
sub_12:Test (Best Model) - Loss: 1.6044 - Accuracy: 0.2190 - F1: 0.1561
sub_10:Test (Best Model) - Loss: 1.6087 - Accuracy: 0.2143 - F1: 0.1410
sub_11:Test (Best Model) - Loss: 1.6025 - Accuracy: 0.2143 - F1: 0.1362
sub_10:Test (Best Model) - Loss: 1.6079 - Accuracy: 0.2048 - F1: 0.0765
sub_12:Test (Best Model) - Loss: 1.6220 - Accuracy: 0.2000 - F1: 0.0820
sub_11:Test (Best Model) - Loss: 1.6090 - Accuracy: 0.2333 - F1: 0.1378
sub_12:Test (Best Model) - Loss: 1.6053 - Accuracy: 0.2000 - F1: 0.1491
sub_10:Test (Best Model) - Loss: 1.6126 - Accuracy: 0.2000 - F1: 0.0832
sub_12:Test (Best Model) - Loss: 1.6182 - Accuracy: 0.2048 - F1: 0.0762
sub_11:Test (Best Model) - Loss: 1.6071 - Accuracy: 0.1952 - F1: 0.0933
sub_14:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2286 - F1: 0.1318
sub_14:Test (Best Model) - Loss: 1.6117 - Accuracy: 0.2190 - F1: 0.1078
sub_13:Test (Best Model) - Loss: 1.5934 - Accuracy: 0.2857 - F1: 0.2419
sub_14:Test (Best Model) - Loss: 1.6219 - Accuracy: 0.2190 - F1: 0.1524
sub_13:Test (Best Model) - Loss: 1.6089 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6076 - Accuracy: 0.1714 - F1: 0.0763
sub_13:Test (Best Model) - Loss: 1.5929 - Accuracy: 0.3190 - F1: 0.1841
sub_14:Test (Best Model) - Loss: 1.6140 - Accuracy: 0.2143 - F1: 0.1438
sub_13:Test (Best Model) - Loss: 1.6088 - Accuracy: 0.2000 - F1: 0.0677
sub_14:Test (Best Model) - Loss: 1.6123 - Accuracy: 0.2095 - F1: 0.1742
sub_13:Test (Best Model) - Loss: 1.6132 - Accuracy: 0.1905 - F1: 0.0732
sub_14:Test (Best Model) - Loss: 1.6045 - Accuracy: 0.3048 - F1: 0.2203
sub_14:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.1857 - F1: 0.0822
sub_14:Test (Best Model) - Loss: 1.5985 - Accuracy: 0.3048 - F1: 0.2271
sub_13:Test (Best Model) - Loss: 1.5923 - Accuracy: 0.3143 - F1: 0.2170
sub_14:Test (Best Model) - Loss: 1.5986 - Accuracy: 0.3476 - F1: 0.2550
sub_13:Test (Best Model) - Loss: 1.5918 - Accuracy: 0.3333 - F1: 0.1956
sub_14:Test (Best Model) - Loss: 1.6041 - Accuracy: 0.2000 - F1: 0.0817
sub_13:Test (Best Model) - Loss: 1.6048 - Accuracy: 0.1810 - F1: 0.0995
sub_13:Test (Best Model) - Loss: 1.5974 - Accuracy: 0.2762 - F1: 0.2027
sub_14:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2810 - F1: 0.1904
sub_13:Test (Best Model) - Loss: 1.5920 - Accuracy: 0.3476 - F1: 0.2526
sub_14:Test (Best Model) - Loss: 1.6001 - Accuracy: 0.2286 - F1: 0.1209
sub_14:Test (Best Model) - Loss: 1.6134 - Accuracy: 0.2381 - F1: 0.1423
sub_14:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.1952 - F1: 0.0656
sub_13:Test (Best Model) - Loss: 1.5483 - Accuracy: 0.2714 - F1: 0.1763
sub_13:Test (Best Model) - Loss: 1.5955 - Accuracy: 0.2238 - F1: 0.1134
sub_13:Test (Best Model) - Loss: 1.5836 - Accuracy: 0.2810 - F1: 0.1845
sub_13:Test (Best Model) - Loss: 1.6008 - Accuracy: 0.2143 - F1: 0.1501
sub_13:Test (Best Model) - Loss: 1.6064 - Accuracy: 0.2143 - F1: 0.0938

=== Summary Results ===

acc: 22.44 ± 1.34
F1: 12.90 ± 1.30
acc-in: 24.65 ± 2.26
F1-in: 14.93 ± 1.99
runing time: 2084.02 seconds
