lr: 1e-06
sub_4:Test (Best Model) - Loss: 1.6197 - Accuracy: 0.1667 - F1: 0.1538
sub_3:Test (Best Model) - Loss: 1.6067 - Accuracy: 0.2000 - F1: 0.1924
sub_9:Test (Best Model) - Loss: 1.6141 - Accuracy: 0.2571 - F1: 0.2249
sub_7:Test (Best Model) - Loss: 1.6146 - Accuracy: 0.2095 - F1: 0.1874
sub_10:Test (Best Model) - Loss: 1.6051 - Accuracy: 0.2238 - F1: 0.2231
sub_11:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.1874
sub_2:Test (Best Model) - Loss: 1.6027 - Accuracy: 0.2286 - F1: 0.2144
sub_12:Test (Best Model) - Loss: 1.6216 - Accuracy: 0.2095 - F1: 0.1984
sub_13:Test (Best Model) - Loss: 1.6128 - Accuracy: 0.2048 - F1: 0.1967
sub_14:Test (Best Model) - Loss: 1.6018 - Accuracy: 0.2429 - F1: 0.2367
sub_1:Test (Best Model) - Loss: 1.5988 - Accuracy: 0.2238 - F1: 0.2214
sub_6:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2286 - F1: 0.2295
sub_5:Test (Best Model) - Loss: 1.6153 - Accuracy: 0.2238 - F1: 0.2135
sub_8:Test (Best Model) - Loss: 1.6044 - Accuracy: 0.2095 - F1: 0.2067
sub_3:Test (Best Model) - Loss: 1.6179 - Accuracy: 0.1810 - F1: 0.1735
sub_9:Test (Best Model) - Loss: 1.5964 - Accuracy: 0.2667 - F1: 0.2733
sub_10:Test (Best Model) - Loss: 1.6123 - Accuracy: 0.2238 - F1: 0.2196
sub_4:Test (Best Model) - Loss: 1.6124 - Accuracy: 0.1905 - F1: 0.1805
sub_7:Test (Best Model) - Loss: 1.5938 - Accuracy: 0.2619 - F1: 0.2423
sub_13:Test (Best Model) - Loss: 1.6159 - Accuracy: 0.1952 - F1: 0.1898
sub_11:Test (Best Model) - Loss: 1.6056 - Accuracy: 0.2238 - F1: 0.2259
sub_14:Test (Best Model) - Loss: 1.6242 - Accuracy: 0.2095 - F1: 0.2073
sub_1:Test (Best Model) - Loss: 1.6127 - Accuracy: 0.2048 - F1: 0.1983
sub_5:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2000 - F1: 0.1935
sub_12:Test (Best Model) - Loss: 1.6135 - Accuracy: 0.1524 - F1: 0.1505
sub_8:Test (Best Model) - Loss: 1.6129 - Accuracy: 0.2190 - F1: 0.2166
sub_2:Test (Best Model) - Loss: 1.6155 - Accuracy: 0.1952 - F1: 0.1891
sub_4:Test (Best Model) - Loss: 1.6132 - Accuracy: 0.1857 - F1: 0.1790
sub_3:Test (Best Model) - Loss: 1.6234 - Accuracy: 0.1952 - F1: 0.1706
sub_9:Test (Best Model) - Loss: 1.6225 - Accuracy: 0.1714 - F1: 0.1276
sub_10:Test (Best Model) - Loss: 1.6133 - Accuracy: 0.2000 - F1: 0.1821
sub_13:Test (Best Model) - Loss: 1.6123 - Accuracy: 0.1524 - F1: 0.1465
sub_7:Test (Best Model) - Loss: 1.6075 - Accuracy: 0.2143 - F1: 0.1961
sub_14:Test (Best Model) - Loss: 1.6089 - Accuracy: 0.2381 - F1: 0.2291
sub_6:Test (Best Model) - Loss: 1.6112 - Accuracy: 0.1952 - F1: 0.1867
sub_12:Test (Best Model) - Loss: 1.6291 - Accuracy: 0.1333 - F1: 0.1289
sub_8:Test (Best Model) - Loss: 1.6078 - Accuracy: 0.2429 - F1: 0.2478
sub_2:Test (Best Model) - Loss: 1.6217 - Accuracy: 0.1857 - F1: 0.1789
sub_4:Test (Best Model) - Loss: 1.6147 - Accuracy: 0.2286 - F1: 0.2236
sub_5:Test (Best Model) - Loss: 1.6174 - Accuracy: 0.2048 - F1: 0.2021
sub_3:Test (Best Model) - Loss: 1.6122 - Accuracy: 0.2000 - F1: 0.1923
sub_13:Test (Best Model) - Loss: 1.6057 - Accuracy: 0.2095 - F1: 0.1928
sub_11:Test (Best Model) - Loss: 1.6186 - Accuracy: 0.1762 - F1: 0.1759
sub_6:Test (Best Model) - Loss: 1.6130 - Accuracy: 0.2143 - F1: 0.2029
sub_12:Test (Best Model) - Loss: 1.6199 - Accuracy: 0.1571 - F1: 0.1615
sub_14:Test (Best Model) - Loss: 1.6219 - Accuracy: 0.1286 - F1: 0.1299
sub_1:Test (Best Model) - Loss: 1.6164 - Accuracy: 0.1810 - F1: 0.1771
sub_7:Test (Best Model) - Loss: 1.6209 - Accuracy: 0.1667 - F1: 0.1609
sub_10:Test (Best Model) - Loss: 1.6060 - Accuracy: 0.2095 - F1: 0.2069
sub_8:Test (Best Model) - Loss: 1.6270 - Accuracy: 0.1810 - F1: 0.1777
sub_9:Test (Best Model) - Loss: 1.6234 - Accuracy: 0.1810 - F1: 0.1520
sub_4:Test (Best Model) - Loss: 1.6030 - Accuracy: 0.2381 - F1: 0.2170
sub_5:Test (Best Model) - Loss: 1.6139 - Accuracy: 0.2143 - F1: 0.2106
sub_3:Test (Best Model) - Loss: 1.5996 - Accuracy: 0.2381 - F1: 0.2053
sub_13:Test (Best Model) - Loss: 1.6069 - Accuracy: 0.2095 - F1: 0.1985
sub_11:Test (Best Model) - Loss: 1.6209 - Accuracy: 0.1619 - F1: 0.1559
sub_14:Test (Best Model) - Loss: 1.6139 - Accuracy: 0.2190 - F1: 0.2135
sub_6:Test (Best Model) - Loss: 1.6138 - Accuracy: 0.1810 - F1: 0.1711
sub_12:Test (Best Model) - Loss: 1.6160 - Accuracy: 0.1952 - F1: 0.1871
sub_1:Test (Best Model) - Loss: 1.6319 - Accuracy: 0.1667 - F1: 0.1707
sub_7:Test (Best Model) - Loss: 1.6210 - Accuracy: 0.1619 - F1: 0.1441
sub_2:Test (Best Model) - Loss: 1.6219 - Accuracy: 0.1619 - F1: 0.1584
sub_8:Test (Best Model) - Loss: 1.5958 - Accuracy: 0.2524 - F1: 0.2482
sub_10:Test (Best Model) - Loss: 1.6134 - Accuracy: 0.2000 - F1: 0.1998
sub_9:Test (Best Model) - Loss: 1.6142 - Accuracy: 0.1619 - F1: 0.1529
sub_5:Test (Best Model) - Loss: 1.5991 - Accuracy: 0.2238 - F1: 0.2215
sub_11:Test (Best Model) - Loss: 1.5997 - Accuracy: 0.2762 - F1: 0.2711
sub_3:Test (Best Model) - Loss: 1.6144 - Accuracy: 0.1714 - F1: 0.1677
sub_6:Test (Best Model) - Loss: 1.5999 - Accuracy: 0.2476 - F1: 0.2298
sub_13:Test (Best Model) - Loss: 1.6107 - Accuracy: 0.2238 - F1: 0.2180
sub_12:Test (Best Model) - Loss: 1.6202 - Accuracy: 0.1905 - F1: 0.1882
sub_4:Test (Best Model) - Loss: 1.6067 - Accuracy: 0.2048 - F1: 0.2036
sub_14:Test (Best Model) - Loss: 1.6073 - Accuracy: 0.1667 - F1: 0.1633
sub_7:Test (Best Model) - Loss: 1.6142 - Accuracy: 0.2095 - F1: 0.1913
sub_2:Test (Best Model) - Loss: 1.5920 - Accuracy: 0.2571 - F1: 0.2540
sub_8:Test (Best Model) - Loss: 1.6131 - Accuracy: 0.1952 - F1: 0.1928
sub_10:Test (Best Model) - Loss: 1.6240 - Accuracy: 0.1524 - F1: 0.1550
sub_9:Test (Best Model) - Loss: 1.6064 - Accuracy: 0.2333 - F1: 0.2308
sub_1:Test (Best Model) - Loss: 1.6042 - Accuracy: 0.2095 - F1: 0.2064
sub_5:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2190 - F1: 0.2117
sub_11:Test (Best Model) - Loss: 1.6108 - Accuracy: 0.2333 - F1: 0.2269
sub_3:Test (Best Model) - Loss: 1.6116 - Accuracy: 0.2238 - F1: 0.2145
sub_6:Test (Best Model) - Loss: 1.6110 - Accuracy: 0.2048 - F1: 0.1949
sub_13:Test (Best Model) - Loss: 1.6285 - Accuracy: 0.1714 - F1: 0.1651
sub_12:Test (Best Model) - Loss: 1.6160 - Accuracy: 0.2095 - F1: 0.2031
sub_7:Test (Best Model) - Loss: 1.6006 - Accuracy: 0.2476 - F1: 0.2405
sub_4:Test (Best Model) - Loss: 1.6080 - Accuracy: 0.2048 - F1: 0.2041
sub_2:Test (Best Model) - Loss: 1.6068 - Accuracy: 0.2238 - F1: 0.1992
sub_14:Test (Best Model) - Loss: 1.6126 - Accuracy: 0.2286 - F1: 0.2134
sub_10:Test (Best Model) - Loss: 1.6167 - Accuracy: 0.1810 - F1: 0.1839
sub_9:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.1810 - F1: 0.1811
sub_1:Test (Best Model) - Loss: 1.6065 - Accuracy: 0.2190 - F1: 0.2075
sub_5:Test (Best Model) - Loss: 1.6176 - Accuracy: 0.1952 - F1: 0.1930
sub_8:Test (Best Model) - Loss: 1.6076 - Accuracy: 0.2238 - F1: 0.2214
sub_11:Test (Best Model) - Loss: 1.6154 - Accuracy: 0.2190 - F1: 0.2186
sub_6:Test (Best Model) - Loss: 1.6190 - Accuracy: 0.1952 - F1: 0.1895
sub_13:Test (Best Model) - Loss: 1.6111 - Accuracy: 0.1905 - F1: 0.1790
sub_4:Test (Best Model) - Loss: 1.6250 - Accuracy: 0.2238 - F1: 0.2205
sub_14:Test (Best Model) - Loss: 1.6056 - Accuracy: 0.2571 - F1: 0.2566
sub_2:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2286 - F1: 0.2210
sub_3:Test (Best Model) - Loss: 1.6076 - Accuracy: 0.1952 - F1: 0.1913
sub_10:Test (Best Model) - Loss: 1.6144 - Accuracy: 0.2238 - F1: 0.2111
sub_12:Test (Best Model) - Loss: 1.6155 - Accuracy: 0.1810 - F1: 0.1697
sub_1:Test (Best Model) - Loss: 1.6070 - Accuracy: 0.2286 - F1: 0.2288
sub_9:Test (Best Model) - Loss: 1.6202 - Accuracy: 0.1286 - F1: 0.1113
sub_7:Test (Best Model) - Loss: 1.6220 - Accuracy: 0.1667 - F1: 0.1592
sub_8:Test (Best Model) - Loss: 1.6216 - Accuracy: 0.1857 - F1: 0.1815
sub_11:Test (Best Model) - Loss: 1.6153 - Accuracy: 0.2286 - F1: 0.2278
sub_6:Test (Best Model) - Loss: 1.6240 - Accuracy: 0.1571 - F1: 0.1434
sub_13:Test (Best Model) - Loss: 1.6173 - Accuracy: 0.2048 - F1: 0.2010
sub_4:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2095 - F1: 0.2057
sub_14:Test (Best Model) - Loss: 1.6057 - Accuracy: 0.2286 - F1: 0.2298
sub_10:Test (Best Model) - Loss: 1.6064 - Accuracy: 0.2619 - F1: 0.2535
sub_12:Test (Best Model) - Loss: 1.6114 - Accuracy: 0.2190 - F1: 0.2188
sub_2:Test (Best Model) - Loss: 1.6192 - Accuracy: 0.2143 - F1: 0.2128
sub_5:Test (Best Model) - Loss: 1.5987 - Accuracy: 0.2714 - F1: 0.2629
sub_3:Test (Best Model) - Loss: 1.6108 - Accuracy: 0.2000 - F1: 0.1874
sub_9:Test (Best Model) - Loss: 1.5987 - Accuracy: 0.2476 - F1: 0.2342
sub_7:Test (Best Model) - Loss: 1.6132 - Accuracy: 0.1476 - F1: 0.1468
sub_11:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2048 - F1: 0.1957
sub_6:Test (Best Model) - Loss: 1.6043 - Accuracy: 0.2286 - F1: 0.2088
sub_13:Test (Best Model) - Loss: 1.6171 - Accuracy: 0.2143 - F1: 0.2049
sub_4:Test (Best Model) - Loss: 1.6116 - Accuracy: 0.2429 - F1: 0.2395
sub_14:Test (Best Model) - Loss: 1.6030 - Accuracy: 0.2286 - F1: 0.2261
sub_1:Test (Best Model) - Loss: 1.6172 - Accuracy: 0.1762 - F1: 0.1660
sub_3:Test (Best Model) - Loss: 1.6291 - Accuracy: 0.1810 - F1: 0.1727
sub_12:Test (Best Model) - Loss: 1.6168 - Accuracy: 0.2095 - F1: 0.2111
sub_10:Test (Best Model) - Loss: 1.6283 - Accuracy: 0.1667 - F1: 0.1607
sub_7:Test (Best Model) - Loss: 1.6023 - Accuracy: 0.1619 - F1: 0.1552
sub_9:Test (Best Model) - Loss: 1.6044 - Accuracy: 0.2238 - F1: 0.2276
sub_8:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.1952 - F1: 0.1954
sub_11:Test (Best Model) - Loss: 1.6156 - Accuracy: 0.1667 - F1: 0.1611
sub_5:Test (Best Model) - Loss: 1.6029 - Accuracy: 0.2095 - F1: 0.2033
sub_6:Test (Best Model) - Loss: 1.6079 - Accuracy: 0.2238 - F1: 0.2155
sub_13:Test (Best Model) - Loss: 1.6181 - Accuracy: 0.2000 - F1: 0.1833
sub_4:Test (Best Model) - Loss: 1.6121 - Accuracy: 0.2238 - F1: 0.2167
sub_14:Test (Best Model) - Loss: 1.6136 - Accuracy: 0.2143 - F1: 0.2085
sub_1:Test (Best Model) - Loss: 1.6180 - Accuracy: 0.1857 - F1: 0.1805
sub_10:Test (Best Model) - Loss: 1.6188 - Accuracy: 0.1667 - F1: 0.1603
sub_3:Test (Best Model) - Loss: 1.6284 - Accuracy: 0.1381 - F1: 0.1206
sub_2:Test (Best Model) - Loss: 1.5783 - Accuracy: 0.3095 - F1: 0.2883
sub_9:Test (Best Model) - Loss: 1.6060 - Accuracy: 0.1810 - F1: 0.1709
sub_12:Test (Best Model) - Loss: 1.6196 - Accuracy: 0.1381 - F1: 0.1401
sub_7:Test (Best Model) - Loss: 1.6026 - Accuracy: 0.2143 - F1: 0.2006
sub_8:Test (Best Model) - Loss: 1.6113 - Accuracy: 0.2238 - F1: 0.2101
sub_5:Test (Best Model) - Loss: 1.5885 - Accuracy: 0.2524 - F1: 0.2454
sub_6:Test (Best Model) - Loss: 1.6072 - Accuracy: 0.2524 - F1: 0.2130
sub_13:Test (Best Model) - Loss: 1.6228 - Accuracy: 0.1857 - F1: 0.1742
sub_4:Test (Best Model) - Loss: 1.6150 - Accuracy: 0.1714 - F1: 0.1749
sub_1:Test (Best Model) - Loss: 1.6046 - Accuracy: 0.2714 - F1: 0.2638
sub_14:Test (Best Model) - Loss: 1.6160 - Accuracy: 0.1905 - F1: 0.1851
sub_3:Test (Best Model) - Loss: 1.6088 - Accuracy: 0.1952 - F1: 0.1955
sub_10:Test (Best Model) - Loss: 1.6268 - Accuracy: 0.1524 - F1: 0.1278
sub_9:Test (Best Model) - Loss: 1.6047 - Accuracy: 0.2286 - F1: 0.2221
sub_11:Test (Best Model) - Loss: 1.6120 - Accuracy: 0.2000 - F1: 0.1941
sub_12:Test (Best Model) - Loss: 1.6219 - Accuracy: 0.1857 - F1: 0.1765
sub_7:Test (Best Model) - Loss: 1.6035 - Accuracy: 0.2571 - F1: 0.2541
sub_8:Test (Best Model) - Loss: 1.6061 - Accuracy: 0.2714 - F1: 0.2691
sub_5:Test (Best Model) - Loss: 1.6196 - Accuracy: 0.1810 - F1: 0.1805
sub_6:Test (Best Model) - Loss: 1.6152 - Accuracy: 0.1429 - F1: 0.1443
sub_2:Test (Best Model) - Loss: 1.6050 - Accuracy: 0.2095 - F1: 0.2086
sub_4:Test (Best Model) - Loss: 1.6027 - Accuracy: 0.2619 - F1: 0.2581
sub_13:Test (Best Model) - Loss: 1.6234 - Accuracy: 0.1952 - F1: 0.1914
sub_14:Test (Best Model) - Loss: 1.6186 - Accuracy: 0.1810 - F1: 0.1771
sub_1:Test (Best Model) - Loss: 1.6231 - Accuracy: 0.1857 - F1: 0.1757
sub_3:Test (Best Model) - Loss: 1.6174 - Accuracy: 0.2143 - F1: 0.2088
sub_9:Test (Best Model) - Loss: 1.6132 - Accuracy: 0.2333 - F1: 0.2323
sub_11:Test (Best Model) - Loss: 1.6081 - Accuracy: 0.1857 - F1: 0.1781
sub_7:Test (Best Model) - Loss: 1.6017 - Accuracy: 0.2095 - F1: 0.2074
sub_12:Test (Best Model) - Loss: 1.6227 - Accuracy: 0.2000 - F1: 0.1921
sub_8:Test (Best Model) - Loss: 1.6183 - Accuracy: 0.1810 - F1: 0.1825
sub_6:Test (Best Model) - Loss: 1.6181 - Accuracy: 0.2095 - F1: 0.2053
sub_5:Test (Best Model) - Loss: 1.6052 - Accuracy: 0.2429 - F1: 0.2317
sub_2:Test (Best Model) - Loss: 1.6133 - Accuracy: 0.1905 - F1: 0.1885
sub_13:Test (Best Model) - Loss: 1.6326 - Accuracy: 0.1762 - F1: 0.1707
sub_14:Test (Best Model) - Loss: 1.6030 - Accuracy: 0.2095 - F1: 0.2072
sub_9:Test (Best Model) - Loss: 1.6081 - Accuracy: 0.2381 - F1: 0.2180
sub_11:Test (Best Model) - Loss: 1.6300 - Accuracy: 0.1667 - F1: 0.1632
sub_7:Test (Best Model) - Loss: 1.6149 - Accuracy: 0.1905 - F1: 0.1839
sub_4:Test (Best Model) - Loss: 1.6240 - Accuracy: 0.1762 - F1: 0.1777
sub_3:Test (Best Model) - Loss: 1.6149 - Accuracy: 0.1905 - F1: 0.1884
sub_12:Test (Best Model) - Loss: 1.6149 - Accuracy: 0.2333 - F1: 0.2224
sub_8:Test (Best Model) - Loss: 1.6191 - Accuracy: 0.1762 - F1: 0.1709
sub_10:Test (Best Model) - Loss: 1.6164 - Accuracy: 0.1667 - F1: 0.1647
sub_5:Test (Best Model) - Loss: 1.6195 - Accuracy: 0.2048 - F1: 0.1954
sub_2:Test (Best Model) - Loss: 1.6201 - Accuracy: 0.1905 - F1: 0.1849
sub_6:Test (Best Model) - Loss: 1.6361 - Accuracy: 0.1333 - F1: 0.1219
sub_1:Test (Best Model) - Loss: 1.6221 - Accuracy: 0.1667 - F1: 0.1635
sub_13:Test (Best Model) - Loss: 1.6166 - Accuracy: 0.1810 - F1: 0.1461
sub_11:Test (Best Model) - Loss: 1.6075 - Accuracy: 0.2333 - F1: 0.2203
sub_14:Test (Best Model) - Loss: 1.6124 - Accuracy: 0.2143 - F1: 0.2080
sub_4:Test (Best Model) - Loss: 1.6168 - Accuracy: 0.2143 - F1: 0.2007
sub_3:Test (Best Model) - Loss: 1.6214 - Accuracy: 0.1476 - F1: 0.1426
sub_12:Test (Best Model) - Loss: 1.5998 - Accuracy: 0.2095 - F1: 0.1943
sub_8:Test (Best Model) - Loss: 1.6219 - Accuracy: 0.1476 - F1: 0.1432
sub_10:Test (Best Model) - Loss: 1.6185 - Accuracy: 0.2286 - F1: 0.1939
sub_2:Test (Best Model) - Loss: 1.6121 - Accuracy: 0.1905 - F1: 0.1829
sub_5:Test (Best Model) - Loss: 1.6107 - Accuracy: 0.1952 - F1: 0.1903
sub_6:Test (Best Model) - Loss: 1.6253 - Accuracy: 0.1667 - F1: 0.1649
sub_9:Test (Best Model) - Loss: 1.6078 - Accuracy: 0.2143 - F1: 0.1848
sub_1:Test (Best Model) - Loss: 1.5985 - Accuracy: 0.2619 - F1: 0.2627
sub_11:Test (Best Model) - Loss: 1.6227 - Accuracy: 0.1810 - F1: 0.1839
sub_7:Test (Best Model) - Loss: 1.6121 - Accuracy: 0.2571 - F1: 0.2425
sub_10:Test (Best Model) - Loss: 1.6132 - Accuracy: 0.2143 - F1: 0.2068
sub_8:Test (Best Model) - Loss: 1.6286 - Accuracy: 0.1619 - F1: 0.1352
sub_5:Test (Best Model) - Loss: 1.6153 - Accuracy: 0.1762 - F1: 0.1718
sub_1:Test (Best Model) - Loss: 1.6066 - Accuracy: 0.2238 - F1: 0.1939
sub_2:Test (Best Model) - Loss: 1.6050 - Accuracy: 0.2000 - F1: 0.1928
sub_1:Test (Best Model) - Loss: 1.6240 - Accuracy: 0.1619 - F1: 0.1485
sub_2:Test (Best Model) - Loss: 1.6205 - Accuracy: 0.2238 - F1: 0.2056

=== Summary Results ===

acc: 20.33 ± 0.79
F1: 19.55 ± 0.87
acc-in: 21.15 ± 1.25
F1-in: 20.58 ± 1.10
