lr: 1e-06
sub_2:Test (Best Model) - Loss: 1.6232 - Accuracy: 0.1667 - F1: 0.1677
sub_3:Test (Best Model) - Loss: 1.6026 - Accuracy: 0.2524 - F1: 0.2371
sub_5:Test (Best Model) - Loss: 1.6253 - Accuracy: 0.2048 - F1: 0.1567
sub_7:Test (Best Model) - Loss: 1.6126 - Accuracy: 0.1667 - F1: 0.1571
sub_6:Test (Best Model) - Loss: 1.6024 - Accuracy: 0.2714 - F1: 0.2252
sub_12:Test (Best Model) - Loss: 1.6010 - Accuracy: 0.2190 - F1: 0.2040
sub_9:Test (Best Model) - Loss: 1.5730 - Accuracy: 0.2762 - F1: 0.2775
sub_13:Test (Best Model) - Loss: 1.6325 - Accuracy: 0.1810 - F1: 0.0697
sub_11:Test (Best Model) - Loss: 1.6018 - Accuracy: 0.2333 - F1: 0.2366
sub_1:Test (Best Model) - Loss: 1.6015 - Accuracy: 0.1810 - F1: 0.1576
sub_4:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2286 - F1: 0.2050
sub_10:Test (Best Model) - Loss: 1.6054 - Accuracy: 0.2429 - F1: 0.2183
sub_14:Test (Best Model) - Loss: 1.6159 - Accuracy: 0.1810 - F1: 0.1594
sub_3:Test (Best Model) - Loss: 1.6174 - Accuracy: 0.1857 - F1: 0.1445
sub_12:Test (Best Model) - Loss: 1.6248 - Accuracy: 0.1619 - F1: 0.1626
sub_5:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2143 - F1: 0.2002
sub_8:Test (Best Model) - Loss: 1.5851 - Accuracy: 0.2810 - F1: 0.2810
sub_9:Test (Best Model) - Loss: 1.6070 - Accuracy: 0.2286 - F1: 0.1427
sub_13:Test (Best Model) - Loss: 1.6003 - Accuracy: 0.2476 - F1: 0.2385
sub_7:Test (Best Model) - Loss: 1.6200 - Accuracy: 0.1429 - F1: 0.1255
sub_4:Test (Best Model) - Loss: 1.6111 - Accuracy: 0.2333 - F1: 0.2204
sub_11:Test (Best Model) - Loss: 1.6088 - Accuracy: 0.1810 - F1: 0.1404
sub_2:Test (Best Model) - Loss: 1.5965 - Accuracy: 0.2762 - F1: 0.2742
sub_1:Test (Best Model) - Loss: 1.6200 - Accuracy: 0.1810 - F1: 0.1816
sub_14:Test (Best Model) - Loss: 1.6168 - Accuracy: 0.1857 - F1: 0.1708
sub_3:Test (Best Model) - Loss: 1.6158 - Accuracy: 0.1952 - F1: 0.1677
sub_10:Test (Best Model) - Loss: 1.6072 - Accuracy: 0.1667 - F1: 0.1516
sub_12:Test (Best Model) - Loss: 1.6131 - Accuracy: 0.1810 - F1: 0.1772
sub_6:Test (Best Model) - Loss: 1.6089 - Accuracy: 0.1714 - F1: 0.1752
sub_13:Test (Best Model) - Loss: 1.6022 - Accuracy: 0.1857 - F1: 0.1323
sub_4:Test (Best Model) - Loss: 1.6231 - Accuracy: 0.1524 - F1: 0.1447
sub_7:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.2000 - F1: 0.1941
sub_11:Test (Best Model) - Loss: 1.6122 - Accuracy: 0.1857 - F1: 0.1684
sub_1:Test (Best Model) - Loss: 1.5932 - Accuracy: 0.2476 - F1: 0.2349
sub_8:Test (Best Model) - Loss: 1.5978 - Accuracy: 0.2190 - F1: 0.2077
sub_5:Test (Best Model) - Loss: 1.6148 - Accuracy: 0.1857 - F1: 0.1663
sub_3:Test (Best Model) - Loss: 1.6153 - Accuracy: 0.1524 - F1: 0.1212
sub_14:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2095 - F1: 0.1997
sub_12:Test (Best Model) - Loss: 1.5935 - Accuracy: 0.2905 - F1: 0.2730
sub_10:Test (Best Model) - Loss: 1.6203 - Accuracy: 0.1952 - F1: 0.1531
sub_9:Test (Best Model) - Loss: 1.6138 - Accuracy: 0.2524 - F1: 0.1511
sub_7:Test (Best Model) - Loss: 1.6130 - Accuracy: 0.2048 - F1: 0.1819
sub_11:Test (Best Model) - Loss: 1.5940 - Accuracy: 0.2619 - F1: 0.2343
sub_2:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.1952 - F1: 0.1825
sub_1:Test (Best Model) - Loss: 1.6169 - Accuracy: 0.1857 - F1: 0.1606
sub_8:Test (Best Model) - Loss: 1.5975 - Accuracy: 0.2381 - F1: 0.2170
sub_6:Test (Best Model) - Loss: 1.6159 - Accuracy: 0.2048 - F1: 0.1611
sub_4:Test (Best Model) - Loss: 1.6153 - Accuracy: 0.1857 - F1: 0.1869
sub_13:Test (Best Model) - Loss: 1.6239 - Accuracy: 0.2095 - F1: 0.1829
sub_5:Test (Best Model) - Loss: 1.6193 - Accuracy: 0.1762 - F1: 0.1445
sub_9:Test (Best Model) - Loss: 1.6187 - Accuracy: 0.1381 - F1: 0.1198
sub_3:Test (Best Model) - Loss: 1.6450 - Accuracy: 0.1048 - F1: 0.0911
sub_14:Test (Best Model) - Loss: 1.5952 - Accuracy: 0.2286 - F1: 0.2186
sub_10:Test (Best Model) - Loss: 1.6114 - Accuracy: 0.2048 - F1: 0.1793
sub_12:Test (Best Model) - Loss: 1.6054 - Accuracy: 0.1810 - F1: 0.1831
sub_7:Test (Best Model) - Loss: 1.6069 - Accuracy: 0.2571 - F1: 0.2057
sub_11:Test (Best Model) - Loss: 1.6480 - Accuracy: 0.1429 - F1: 0.1281
sub_1:Test (Best Model) - Loss: 1.5910 - Accuracy: 0.2429 - F1: 0.2396
sub_2:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2333 - F1: 0.2119
sub_8:Test (Best Model) - Loss: 1.6131 - Accuracy: 0.2381 - F1: 0.2364
sub_13:Test (Best Model) - Loss: 1.6228 - Accuracy: 0.1619 - F1: 0.1121
sub_4:Test (Best Model) - Loss: 1.6280 - Accuracy: 0.1667 - F1: 0.1491
sub_6:Test (Best Model) - Loss: 1.6144 - Accuracy: 0.1714 - F1: 0.1563
sub_9:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2476 - F1: 0.1840
sub_10:Test (Best Model) - Loss: 1.6246 - Accuracy: 0.2143 - F1: 0.1870
sub_7:Test (Best Model) - Loss: 1.6069 - Accuracy: 0.2190 - F1: 0.2175
sub_5:Test (Best Model) - Loss: 1.6064 - Accuracy: 0.2190 - F1: 0.2163
sub_12:Test (Best Model) - Loss: 1.6014 - Accuracy: 0.2095 - F1: 0.1951
sub_8:Test (Best Model) - Loss: 1.6260 - Accuracy: 0.1762 - F1: 0.1541
sub_11:Test (Best Model) - Loss: 1.6011 - Accuracy: 0.2238 - F1: 0.2070
sub_1:Test (Best Model) - Loss: 1.6219 - Accuracy: 0.1619 - F1: 0.1520
sub_3:Test (Best Model) - Loss: 1.5876 - Accuracy: 0.2714 - F1: 0.2502
sub_4:Test (Best Model) - Loss: 1.6071 - Accuracy: 0.1905 - F1: 0.1839
sub_7:Test (Best Model) - Loss: 1.6297 - Accuracy: 0.1571 - F1: 0.1494
sub_10:Test (Best Model) - Loss: 1.6073 - Accuracy: 0.2476 - F1: 0.2416
sub_2:Test (Best Model) - Loss: 1.6119 - Accuracy: 0.1905 - F1: 0.1615
sub_11:Test (Best Model) - Loss: 1.6063 - Accuracy: 0.1714 - F1: 0.1579
sub_1:Test (Best Model) - Loss: 1.6015 - Accuracy: 0.2048 - F1: 0.2024
sub_6:Test (Best Model) - Loss: 1.6128 - Accuracy: 0.2095 - F1: 0.1942
sub_3:Test (Best Model) - Loss: 1.6162 - Accuracy: 0.1619 - F1: 0.1541
sub_14:Test (Best Model) - Loss: 1.6064 - Accuracy: 0.2000 - F1: 0.1920
sub_13:Test (Best Model) - Loss: 1.6067 - Accuracy: 0.2333 - F1: 0.2191
sub_9:Test (Best Model) - Loss: 1.5976 - Accuracy: 0.2476 - F1: 0.2376
sub_8:Test (Best Model) - Loss: 1.5978 - Accuracy: 0.2143 - F1: 0.2142
sub_5:Test (Best Model) - Loss: 1.6166 - Accuracy: 0.2190 - F1: 0.1971
sub_7:Test (Best Model) - Loss: 1.6166 - Accuracy: 0.1810 - F1: 0.1778
sub_4:Test (Best Model) - Loss: 1.6121 - Accuracy: 0.1762 - F1: 0.1724
sub_12:Test (Best Model) - Loss: 1.6113 - Accuracy: 0.2048 - F1: 0.1959
sub_11:Test (Best Model) - Loss: 1.5964 - Accuracy: 0.2381 - F1: 0.2323
sub_3:Test (Best Model) - Loss: 1.6179 - Accuracy: 0.1524 - F1: 0.1414
sub_14:Test (Best Model) - Loss: 1.6149 - Accuracy: 0.2238 - F1: 0.1954
sub_10:Test (Best Model) - Loss: 1.6076 - Accuracy: 0.1619 - F1: 0.1441
sub_6:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2238 - F1: 0.1647
sub_2:Test (Best Model) - Loss: 1.6342 - Accuracy: 0.1476 - F1: 0.0974
sub_9:Test (Best Model) - Loss: 1.6039 - Accuracy: 0.2095 - F1: 0.2097
sub_8:Test (Best Model) - Loss: 1.6027 - Accuracy: 0.2524 - F1: 0.2499
sub_5:Test (Best Model) - Loss: 1.6017 - Accuracy: 0.2095 - F1: 0.1974
sub_13:Test (Best Model) - Loss: 1.6049 - Accuracy: 0.2667 - F1: 0.2362
sub_4:Test (Best Model) - Loss: 1.6051 - Accuracy: 0.2048 - F1: 0.1727
sub_12:Test (Best Model) - Loss: 1.5958 - Accuracy: 0.2238 - F1: 0.2168
sub_11:Test (Best Model) - Loss: 1.6426 - Accuracy: 0.1905 - F1: 0.1321
sub_7:Test (Best Model) - Loss: 1.6299 - Accuracy: 0.1381 - F1: 0.1313
sub_10:Test (Best Model) - Loss: 1.6057 - Accuracy: 0.2238 - F1: 0.2153
sub_14:Test (Best Model) - Loss: 1.6071 - Accuracy: 0.1952 - F1: 0.1861
sub_1:Test (Best Model) - Loss: 1.6011 - Accuracy: 0.2286 - F1: 0.1858
sub_9:Test (Best Model) - Loss: 1.5914 - Accuracy: 0.3238 - F1: 0.2941
sub_2:Test (Best Model) - Loss: 1.5964 - Accuracy: 0.2048 - F1: 0.1701
sub_6:Test (Best Model) - Loss: 1.6183 - Accuracy: 0.1905 - F1: 0.1781
sub_8:Test (Best Model) - Loss: 1.5908 - Accuracy: 0.2905 - F1: 0.2908
sub_5:Test (Best Model) - Loss: 1.6025 - Accuracy: 0.2238 - F1: 0.2323
sub_3:Test (Best Model) - Loss: 1.6393 - Accuracy: 0.1524 - F1: 0.1461
sub_12:Test (Best Model) - Loss: 1.6179 - Accuracy: 0.1619 - F1: 0.1635
sub_4:Test (Best Model) - Loss: 1.6368 - Accuracy: 0.1619 - F1: 0.1519
sub_11:Test (Best Model) - Loss: 1.6427 - Accuracy: 0.0905 - F1: 0.0771
sub_7:Test (Best Model) - Loss: 1.6041 - Accuracy: 0.2048 - F1: 0.1680
sub_1:Test (Best Model) - Loss: 1.6203 - Accuracy: 0.1524 - F1: 0.1348
sub_13:Test (Best Model) - Loss: 1.6177 - Accuracy: 0.1524 - F1: 0.1476
sub_14:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2048 - F1: 0.1970
sub_9:Test (Best Model) - Loss: 1.6258 - Accuracy: 0.1619 - F1: 0.1389
sub_6:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2524 - F1: 0.2255
sub_3:Test (Best Model) - Loss: 1.6073 - Accuracy: 0.2238 - F1: 0.2043
sub_12:Test (Best Model) - Loss: 1.6058 - Accuracy: 0.2143 - F1: 0.2014
sub_4:Test (Best Model) - Loss: 1.5872 - Accuracy: 0.2667 - F1: 0.2432
sub_11:Test (Best Model) - Loss: 1.6056 - Accuracy: 0.2381 - F1: 0.2293
sub_5:Test (Best Model) - Loss: 1.6182 - Accuracy: 0.1905 - F1: 0.1870
sub_1:Test (Best Model) - Loss: 1.6169 - Accuracy: 0.2143 - F1: 0.1817
sub_7:Test (Best Model) - Loss: 1.6163 - Accuracy: 0.1714 - F1: 0.1554
sub_14:Test (Best Model) - Loss: 1.6242 - Accuracy: 0.1810 - F1: 0.1729
sub_8:Test (Best Model) - Loss: 1.6340 - Accuracy: 0.1190 - F1: 0.1045
sub_2:Test (Best Model) - Loss: 1.5964 - Accuracy: 0.1524 - F1: 0.1214
sub_10:Test (Best Model) - Loss: 1.6186 - Accuracy: 0.1905 - F1: 0.1823
sub_3:Test (Best Model) - Loss: 1.6065 - Accuracy: 0.2524 - F1: 0.2130
sub_12:Test (Best Model) - Loss: 1.6282 - Accuracy: 0.1762 - F1: 0.1534
sub_9:Test (Best Model) - Loss: 1.5986 - Accuracy: 0.2619 - F1: 0.2360
sub_1:Test (Best Model) - Loss: 1.6017 - Accuracy: 0.2048 - F1: 0.1914
sub_4:Test (Best Model) - Loss: 1.6119 - Accuracy: 0.1619 - F1: 0.1572
sub_13:Test (Best Model) - Loss: 1.6138 - Accuracy: 0.1952 - F1: 0.1794
sub_5:Test (Best Model) - Loss: 1.5994 - Accuracy: 0.3000 - F1: 0.2815
sub_7:Test (Best Model) - Loss: 1.6148 - Accuracy: 0.2238 - F1: 0.2130
sub_2:Test (Best Model) - Loss: 1.6232 - Accuracy: 0.1333 - F1: 0.1056
sub_8:Test (Best Model) - Loss: 1.5821 - Accuracy: 0.2952 - F1: 0.2818
sub_14:Test (Best Model) - Loss: 1.5784 - Accuracy: 0.2667 - F1: 0.2586
sub_11:Test (Best Model) - Loss: 1.5984 - Accuracy: 0.2238 - F1: 0.2177
sub_12:Test (Best Model) - Loss: 1.5941 - Accuracy: 0.2714 - F1: 0.2750
sub_6:Test (Best Model) - Loss: 1.6154 - Accuracy: 0.2048 - F1: 0.2021
sub_9:Test (Best Model) - Loss: 1.6230 - Accuracy: 0.1286 - F1: 0.1272
sub_7:Test (Best Model) - Loss: 1.6289 - Accuracy: 0.2095 - F1: 0.1750
sub_2:Test (Best Model) - Loss: 1.6074 - Accuracy: 0.1857 - F1: 0.1747
sub_10:Test (Best Model) - Loss: 1.6139 - Accuracy: 0.1762 - F1: 0.1697
sub_8:Test (Best Model) - Loss: 1.6118 - Accuracy: 0.2095 - F1: 0.1724
sub_11:Test (Best Model) - Loss: 1.6225 - Accuracy: 0.1571 - F1: 0.1332
sub_14:Test (Best Model) - Loss: 1.6167 - Accuracy: 0.1810 - F1: 0.1791
sub_13:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2333 - F1: 0.2088
sub_5:Test (Best Model) - Loss: 1.6007 - Accuracy: 0.2476 - F1: 0.2328
sub_6:Test (Best Model) - Loss: 1.6077 - Accuracy: 0.2143 - F1: 0.2045
sub_9:Test (Best Model) - Loss: 1.5890 - Accuracy: 0.2238 - F1: 0.2159
sub_7:Test (Best Model) - Loss: 1.6254 - Accuracy: 0.1333 - F1: 0.0982
sub_4:Test (Best Model) - Loss: 1.6181 - Accuracy: 0.1667 - F1: 0.1610
sub_11:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2238 - F1: 0.2229
sub_2:Test (Best Model) - Loss: 1.6108 - Accuracy: 0.2048 - F1: 0.2002
sub_14:Test (Best Model) - Loss: 1.6158 - Accuracy: 0.2000 - F1: 0.1862
sub_5:Test (Best Model) - Loss: 1.6210 - Accuracy: 0.1857 - F1: 0.1637
sub_1:Test (Best Model) - Loss: 1.6053 - Accuracy: 0.2571 - F1: 0.2328
sub_13:Test (Best Model) - Loss: 1.6279 - Accuracy: 0.1143 - F1: 0.0923
sub_6:Test (Best Model) - Loss: 1.6175 - Accuracy: 0.1714 - F1: 0.1422
sub_3:Test (Best Model) - Loss: 1.6087 - Accuracy: 0.2190 - F1: 0.2126
sub_10:Test (Best Model) - Loss: 1.6030 - Accuracy: 0.2429 - F1: 0.2418
sub_4:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.1524 - F1: 0.1351
sub_7:Test (Best Model) - Loss: 1.6208 - Accuracy: 0.2048 - F1: 0.1779
sub_12:Test (Best Model) - Loss: 1.6129 - Accuracy: 0.2667 - F1: 0.2259
sub_11:Test (Best Model) - Loss: 1.5963 - Accuracy: 0.2571 - F1: 0.2443
sub_9:Test (Best Model) - Loss: 1.6199 - Accuracy: 0.2190 - F1: 0.1940
sub_14:Test (Best Model) - Loss: 1.6047 - Accuracy: 0.2571 - F1: 0.2067
sub_5:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2238 - F1: 0.2223
sub_2:Test (Best Model) - Loss: 1.6202 - Accuracy: 0.1952 - F1: 0.1917
sub_8:Test (Best Model) - Loss: 1.5995 - Accuracy: 0.2333 - F1: 0.2165
sub_10:Test (Best Model) - Loss: 1.6088 - Accuracy: 0.2095 - F1: 0.1495
sub_3:Test (Best Model) - Loss: 1.6253 - Accuracy: 0.1762 - F1: 0.1416
sub_4:Test (Best Model) - Loss: 1.6121 - Accuracy: 0.1857 - F1: 0.1582
sub_1:Test (Best Model) - Loss: 1.5975 - Accuracy: 0.2619 - F1: 0.2445
sub_5:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2048 - F1: 0.2117
sub_9:Test (Best Model) - Loss: 1.6145 - Accuracy: 0.1810 - F1: 0.1608
sub_12:Test (Best Model) - Loss: 1.6196 - Accuracy: 0.2190 - F1: 0.1628
sub_14:Test (Best Model) - Loss: 1.6169 - Accuracy: 0.1857 - F1: 0.1724
sub_8:Test (Best Model) - Loss: 1.6027 - Accuracy: 0.2190 - F1: 0.2121
sub_4:Test (Best Model) - Loss: 1.6062 - Accuracy: 0.1905 - F1: 0.1878
sub_6:Test (Best Model) - Loss: 1.6164 - Accuracy: 0.1762 - F1: 0.1690
sub_13:Test (Best Model) - Loss: 1.6186 - Accuracy: 0.1429 - F1: 0.1340
sub_1:Test (Best Model) - Loss: 1.6037 - Accuracy: 0.1810 - F1: 0.1680
sub_5:Test (Best Model) - Loss: 1.6141 - Accuracy: 0.1905 - F1: 0.1722
sub_3:Test (Best Model) - Loss: 1.6226 - Accuracy: 0.1667 - F1: 0.1509
sub_9:Test (Best Model) - Loss: 1.6027 - Accuracy: 0.2381 - F1: 0.2288
sub_10:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2571 - F1: 0.2142
sub_14:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2000 - F1: 0.1946
sub_6:Test (Best Model) - Loss: 1.6140 - Accuracy: 0.2000 - F1: 0.1945
sub_8:Test (Best Model) - Loss: 1.6144 - Accuracy: 0.2429 - F1: 0.2260
sub_2:Test (Best Model) - Loss: 1.5951 - Accuracy: 0.2952 - F1: 0.2561
sub_13:Test (Best Model) - Loss: 1.6009 - Accuracy: 0.2286 - F1: 0.2022
sub_3:Test (Best Model) - Loss: 1.6159 - Accuracy: 0.1810 - F1: 0.1688
sub_12:Test (Best Model) - Loss: 1.6165 - Accuracy: 0.1857 - F1: 0.1365
sub_8:Test (Best Model) - Loss: 1.6067 - Accuracy: 0.2667 - F1: 0.2190
sub_13:Test (Best Model) - Loss: 1.5906 - Accuracy: 0.2619 - F1: 0.2137
sub_6:Test (Best Model) - Loss: 1.6031 - Accuracy: 0.2238 - F1: 0.2015
sub_1:Test (Best Model) - Loss: 1.6033 - Accuracy: 0.2190 - F1: 0.2053
sub_13:Test (Best Model) - Loss: 1.6191 - Accuracy: 0.2238 - F1: 0.2009
sub_10:Test (Best Model) - Loss: 1.6149 - Accuracy: 0.2429 - F1: 0.1412
sub_6:Test (Best Model) - Loss: 1.6141 - Accuracy: 0.1619 - F1: 0.1468
sub_2:Test (Best Model) - Loss: 1.6059 - Accuracy: 0.2286 - F1: 0.2059
sub_10:Test (Best Model) - Loss: 1.6058 - Accuracy: 0.2190 - F1: 0.1880
sub_2:Test (Best Model) - Loss: 1.6196 - Accuracy: 0.2095 - F1: 0.1590

=== Summary Results ===

acc: 20.58 ± 1.23
F1: 18.62 ± 1.32
acc-in: 22.04 ± 1.21
F1-in: 21.23 ± 1.29
