lr: 1e-05
sub_1:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.1905 - F1: 0.1027
sub_1:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.1857 - F1: 0.1144
sub_1:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2190 - F1: 0.1025
sub_1:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.1320
sub_1:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2190 - F1: 0.1021
sub_1:Test (Best Model) - Loss: 1.6090 - Accuracy: 0.2286 - F1: 0.1347
sub_1:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2238 - F1: 0.1109
sub_1:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.0771
sub_1:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.1429 - F1: 0.0953
sub_1:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2190 - F1: 0.1251
sub_1:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2333 - F1: 0.1264
sub_1:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0677
sub_1:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2143 - F1: 0.1122
sub_2:Test (Best Model) - Loss: 1.6047 - Accuracy: 0.2952 - F1: 0.1667
sub_2:Test (Best Model) - Loss: 1.6067 - Accuracy: 0.2714 - F1: 0.1587
sub_2:Test (Best Model) - Loss: 1.6041 - Accuracy: 0.3667 - F1: 0.2509
sub_2:Test (Best Model) - Loss: 1.6046 - Accuracy: 0.3095 - F1: 0.2219
sub_2:Test (Best Model) - Loss: 1.6048 - Accuracy: 0.3381 - F1: 0.3012
sub_2:Test (Best Model) - Loss: 1.6070 - Accuracy: 0.2381 - F1: 0.1514
sub_2:Test (Best Model) - Loss: 1.6057 - Accuracy: 0.2810 - F1: 0.2035
sub_2:Test (Best Model) - Loss: 1.6029 - Accuracy: 0.3619 - F1: 0.2644
sub_2:Test (Best Model) - Loss: 1.6051 - Accuracy: 0.3286 - F1: 0.2402
sub_2:Test (Best Model) - Loss: 1.6063 - Accuracy: 0.3190 - F1: 0.1831
sub_2:Test (Best Model) - Loss: 1.6067 - Accuracy: 0.2714 - F1: 0.2020
sub_2:Test (Best Model) - Loss: 1.6063 - Accuracy: 0.3048 - F1: 0.2356
sub_2:Test (Best Model) - Loss: 1.6054 - Accuracy: 0.2714 - F1: 0.1618
sub_2:Test (Best Model) - Loss: 1.6059 - Accuracy: 0.2667 - F1: 0.1767
sub_2:Test (Best Model) - Loss: 1.6001 - Accuracy: 0.3429 - F1: 0.2642
sub_3:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.2429 - F1: 0.1420
sub_3:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.1952 - F1: 0.0732
sub_3:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2048 - F1: 0.0764
sub_3:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.1905 - F1: 0.0746
sub_3:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2571 - F1: 0.1369
sub_3:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.2381 - F1: 0.1369
sub_3:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.1905 - F1: 0.0784
sub_3:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2143 - F1: 0.1121
sub_3:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.1714 - F1: 0.0823
sub_3:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2048 - F1: 0.1160
sub_3:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.1952 - F1: 0.1020
sub_3:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.1667 - F1: 0.1093
sub_3:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.1905 - F1: 0.0801
sub_3:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2095 - F1: 0.1608
sub_3:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0973
sub_4:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.1952 - F1: 0.0805
sub_4:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 1.6090 - Accuracy: 0.2381 - F1: 0.1307
sub_4:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2333 - F1: 0.1203
sub_4:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.2286 - F1: 0.1309
sub_4:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2238 - F1: 0.1213
sub_4:Test (Best Model) - Loss: 1.6087 - Accuracy: 0.2286 - F1: 0.1214
sub_4:Test (Best Model) - Loss: 1.6068 - Accuracy: 0.3333 - F1: 0.2299
sub_4:Test (Best Model) - Loss: 1.6088 - Accuracy: 0.2095 - F1: 0.0934
sub_4:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2286 - F1: 0.1651
sub_4:Test (Best Model) - Loss: 1.6090 - Accuracy: 0.2095 - F1: 0.0850
sub_4:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2095 - F1: 0.1064
sub_4:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2190 - F1: 0.1074
sub_4:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.1905 - F1: 0.1436
sub_4:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2143 - F1: 0.1155
sub_5:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2238 - F1: 0.1225
sub_5:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.1857 - F1: 0.0711
sub_5:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.1952 - F1: 0.0741
sub_5:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2286 - F1: 0.1178
sub_5:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.1857 - F1: 0.0642
sub_5:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2619 - F1: 0.1528
sub_5:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.1952 - F1: 0.0656
sub_5:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.2143 - F1: 0.1029
sub_5:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2000 - F1: 0.1277
sub_5:Test (Best Model) - Loss: 1.6081 - Accuracy: 0.2952 - F1: 0.1822
sub_5:Test (Best Model) - Loss: 1.6082 - Accuracy: 0.2619 - F1: 0.1891
sub_5:Test (Best Model) - Loss: 1.6084 - Accuracy: 0.2429 - F1: 0.1680
sub_5:Test (Best Model) - Loss: 1.6079 - Accuracy: 0.2905 - F1: 0.2268
sub_5:Test (Best Model) - Loss: 1.6080 - Accuracy: 0.1952 - F1: 0.1396
sub_6:Test (Best Model) - Loss: 1.6082 - Accuracy: 0.2810 - F1: 0.2052
sub_6:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.2095 - F1: 0.1164
sub_6:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2095 - F1: 0.0914
sub_6:Test (Best Model) - Loss: 1.6072 - Accuracy: 0.2667 - F1: 0.1531
sub_6:Test (Best Model) - Loss: 1.6089 - Accuracy: 0.2667 - F1: 0.1894
sub_6:Test (Best Model) - Loss: 1.6073 - Accuracy: 0.2476 - F1: 0.1930
sub_6:Test (Best Model) - Loss: 1.6090 - Accuracy: 0.2000 - F1: 0.0669
sub_6:Test (Best Model) - Loss: 1.6088 - Accuracy: 0.2000 - F1: 0.0672
sub_6:Test (Best Model) - Loss: 1.6056 - Accuracy: 0.2667 - F1: 0.1726
sub_6:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2524 - F1: 0.1461
sub_6:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.1905 - F1: 0.0787
sub_6:Test (Best Model) - Loss: 1.6062 - Accuracy: 0.2286 - F1: 0.1984
sub_6:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 1.6071 - Accuracy: 0.2857 - F1: 0.1803
sub_6:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 1.6128 - Accuracy: 0.1524 - F1: 0.0662
sub_7:Test (Best Model) - Loss: 1.6131 - Accuracy: 0.1143 - F1: 0.0519
sub_7:Test (Best Model) - Loss: 1.6139 - Accuracy: 0.2048 - F1: 0.0929
sub_7:Test (Best Model) - Loss: 1.6125 - Accuracy: 0.1429 - F1: 0.0684
sub_7:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.1476 - F1: 0.0559
sub_7:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.1905 - F1: 0.0902
sub_7:Test (Best Model) - Loss: 1.6108 - Accuracy: 0.1857 - F1: 0.0935
sub_7:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.1905 - F1: 0.0672
sub_7:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.1952 - F1: 0.1174
sub_7:Test (Best Model) - Loss: 1.6123 - Accuracy: 0.1952 - F1: 0.1291
sub_7:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.1857 - F1: 0.1032
sub_7:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.1857 - F1: 0.1316
sub_7:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.1905 - F1: 0.1051
sub_7:Test (Best Model) - Loss: 1.6088 - Accuracy: 0.2286 - F1: 0.1295
sub_7:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2048 - F1: 0.0946
sub_8:Test (Best Model) - Loss: 1.6089 - Accuracy: 0.2000 - F1: 0.1319
sub_8:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2190 - F1: 0.1269
sub_8:Test (Best Model) - Loss: 1.6078 - Accuracy: 0.2095 - F1: 0.0850
sub_8:Test (Best Model) - Loss: 1.6090 - Accuracy: 0.2000 - F1: 0.0748
sub_8:Test (Best Model) - Loss: 1.6086 - Accuracy: 0.2095 - F1: 0.0849
sub_8:Test (Best Model) - Loss: 1.6086 - Accuracy: 0.2333 - F1: 0.1751
sub_8:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.2238 - F1: 0.1441
sub_8:Test (Best Model) - Loss: 1.6082 - Accuracy: 0.2714 - F1: 0.2018
sub_8:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.2143 - F1: 0.1172
sub_8:Test (Best Model) - Loss: 1.6085 - Accuracy: 0.2238 - F1: 0.1278
sub_8:Test (Best Model) - Loss: 1.6086 - Accuracy: 0.2190 - F1: 0.1221
sub_8:Test (Best Model) - Loss: 1.6083 - Accuracy: 0.2143 - F1: 0.1276
sub_8:Test (Best Model) - Loss: 1.6078 - Accuracy: 0.2524 - F1: 0.1546
sub_8:Test (Best Model) - Loss: 1.6076 - Accuracy: 0.2667 - F1: 0.1676
sub_8:Test (Best Model) - Loss: 1.6074 - Accuracy: 0.2524 - F1: 0.1619
sub_9:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2048 - F1: 0.0763
sub_9:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0768
sub_9:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2524 - F1: 0.1460
sub_9:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.1810 - F1: 0.1313
sub_9:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2095 - F1: 0.0860
sub_9:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2048 - F1: 0.0762
sub_9:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2095 - F1: 0.1446
sub_9:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.1762 - F1: 0.1300
sub_9:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2619 - F1: 0.1505
sub_9:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.1476 - F1: 0.0835
sub_9:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.1148
sub_9:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2048 - F1: 0.0842
sub_9:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2286 - F1: 0.1147
sub_10:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2238 - F1: 0.1249
sub_10:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.1714 - F1: 0.0995
sub_10:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_10:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.1619 - F1: 0.0901
sub_10:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2333 - F1: 0.1565
sub_10:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2571 - F1: 0.1798
sub_10:Test (Best Model) - Loss: 1.6087 - Accuracy: 0.2476 - F1: 0.1369
sub_10:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0669
sub_10:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2000 - F1: 0.0669
sub_10:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2048 - F1: 0.0762
sub_10:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.2333 - F1: 0.1642
sub_10:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2095 - F1: 0.1222
sub_10:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2095 - F1: 0.0901
sub_10:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.2333 - F1: 0.1205
sub_10:Test (Best Model) - Loss: 1.6090 - Accuracy: 0.2619 - F1: 0.1454
sub_11:Test (Best Model) - Loss: 1.6084 - Accuracy: 0.2381 - F1: 0.1316
sub_11:Test (Best Model) - Loss: 1.6086 - Accuracy: 0.2571 - F1: 0.1650
sub_11:Test (Best Model) - Loss: 1.6081 - Accuracy: 0.3333 - F1: 0.1915
sub_11:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.2429 - F1: 0.1387
sub_11:Test (Best Model) - Loss: 1.6088 - Accuracy: 0.2381 - F1: 0.1344
sub_11:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2238 - F1: 0.1130
sub_11:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.2524 - F1: 0.1580
sub_11:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.1952 - F1: 0.1339
sub_11:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2048 - F1: 0.1255
sub_11:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.1714 - F1: 0.1247
sub_11:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2048 - F1: 0.1101
sub_11:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2048 - F1: 0.1155
sub_11:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.1952 - F1: 0.1077
sub_11:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.1810 - F1: 0.0838
sub_11:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2286 - F1: 0.1634
sub_12:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.1619 - F1: 0.0962
sub_12:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.1857 - F1: 0.0629
sub_12:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2286 - F1: 0.1351
sub_12:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2381 - F1: 0.1691
sub_12:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.1810 - F1: 0.0957
sub_12:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2333 - F1: 0.1571
sub_12:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2333 - F1: 0.1484
sub_12:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.1619 - F1: 0.0624
sub_12:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2000 - F1: 0.1502
sub_12:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.1571 - F1: 0.0548
sub_12:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.1952 - F1: 0.1177
sub_12:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.1762 - F1: 0.0986
sub_12:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.1857 - F1: 0.1037
sub_12:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.1226
sub_12:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.1905 - F1: 0.1479
sub_13:Test (Best Model) - Loss: 1.6084 - Accuracy: 0.2476 - F1: 0.1883
sub_13:Test (Best Model) - Loss: 1.6087 - Accuracy: 0.2000 - F1: 0.0669
sub_13:Test (Best Model) - Loss: 1.6081 - Accuracy: 0.2619 - F1: 0.1680
sub_13:Test (Best Model) - Loss: 1.6087 - Accuracy: 0.2286 - F1: 0.1318
sub_13:Test (Best Model) - Loss: 1.6083 - Accuracy: 0.2429 - F1: 0.1652
sub_13:Test (Best Model) - Loss: 1.6066 - Accuracy: 0.2190 - F1: 0.1646
sub_13:Test (Best Model) - Loss: 1.6087 - Accuracy: 0.2286 - F1: 0.1087
sub_13:Test (Best Model) - Loss: 1.6078 - Accuracy: 0.2952 - F1: 0.1689
sub_13:Test (Best Model) - Loss: 1.6085 - Accuracy: 0.2714 - F1: 0.1946
sub_13:Test (Best Model) - Loss: 1.6081 - Accuracy: 0.2476 - F1: 0.1481
sub_13:Test (Best Model) - Loss: 1.6051 - Accuracy: 0.2571 - F1: 0.2163
sub_13:Test (Best Model) - Loss: 1.6080 - Accuracy: 0.2714 - F1: 0.2131
sub_13:Test (Best Model) - Loss: 1.6071 - Accuracy: 0.2857 - F1: 0.1870
sub_13:Test (Best Model) - Loss: 1.6057 - Accuracy: 0.2619 - F1: 0.1993
sub_13:Test (Best Model) - Loss: 1.6069 - Accuracy: 0.2905 - F1: 0.2199
sub_14:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.1714 - F1: 0.0857
sub_14:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.1857 - F1: 0.1086
sub_14:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2000 - F1: 0.0667
sub_14:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2048 - F1: 0.1182
sub_14:Test (Best Model) - Loss: 1.6090 - Accuracy: 0.2095 - F1: 0.1006
sub_14:Test (Best Model) - Loss: 1.6089 - Accuracy: 0.2143 - F1: 0.1591
sub_14:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.2000 - F1: 0.0895
sub_14:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.1905 - F1: 0.1058
sub_14:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2095 - F1: 0.1380
sub_14:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.1810 - F1: 0.1031
sub_14:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.1952 - F1: 0.0778
sub_14:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2143 - F1: 0.1445
sub_14:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0816
sub_14:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2000 - F1: 0.0667

=== Summary Results ===

acc: 22.14 ± 2.91
F1: 12.57 ± 3.04
acc-in: 25.09 ± 3.13
F1-in: 15.21 ± 3.60
