lr: 1e-06
sub_1:Test (Best Model) - Loss: 1.5972 - Accuracy: 0.2762 - F1: 0.2694
sub_1:Test (Best Model) - Loss: 1.5978 - Accuracy: 0.2810 - F1: 0.2807
sub_1:Test (Best Model) - Loss: 1.6000 - Accuracy: 0.2810 - F1: 0.2683
sub_1:Test (Best Model) - Loss: 1.5925 - Accuracy: 0.2857 - F1: 0.2822
sub_1:Test (Best Model) - Loss: 1.6018 - Accuracy: 0.2857 - F1: 0.2875
sub_1:Test (Best Model) - Loss: 1.5835 - Accuracy: 0.2810 - F1: 0.2754
sub_1:Test (Best Model) - Loss: 1.6015 - Accuracy: 0.2476 - F1: 0.2373
sub_1:Test (Best Model) - Loss: 1.5847 - Accuracy: 0.2952 - F1: 0.2798
sub_1:Test (Best Model) - Loss: 1.5853 - Accuracy: 0.2667 - F1: 0.2606
sub_1:Test (Best Model) - Loss: 1.6009 - Accuracy: 0.2238 - F1: 0.2211
sub_1:Test (Best Model) - Loss: 1.6009 - Accuracy: 0.2333 - F1: 0.2293
sub_1:Test (Best Model) - Loss: 1.5916 - Accuracy: 0.3048 - F1: 0.3022
sub_1:Test (Best Model) - Loss: 1.6002 - Accuracy: 0.2333 - F1: 0.2058
sub_1:Test (Best Model) - Loss: 1.5978 - Accuracy: 0.2429 - F1: 0.2044
sub_1:Test (Best Model) - Loss: 1.5785 - Accuracy: 0.2571 - F1: 0.2632
sub_2:Test (Best Model) - Loss: 1.5913 - Accuracy: 0.2333 - F1: 0.2150
sub_2:Test (Best Model) - Loss: 1.5955 - Accuracy: 0.1762 - F1: 0.1545
sub_2:Test (Best Model) - Loss: 1.6023 - Accuracy: 0.2143 - F1: 0.2002
sub_2:Test (Best Model) - Loss: 1.5968 - Accuracy: 0.1905 - F1: 0.1754
sub_2:Test (Best Model) - Loss: 1.6001 - Accuracy: 0.2095 - F1: 0.1693
sub_2:Test (Best Model) - Loss: 1.5994 - Accuracy: 0.2286 - F1: 0.2195
sub_2:Test (Best Model) - Loss: 1.6046 - Accuracy: 0.1857 - F1: 0.1789
sub_2:Test (Best Model) - Loss: 1.5965 - Accuracy: 0.2048 - F1: 0.1913
sub_2:Test (Best Model) - Loss: 1.6023 - Accuracy: 0.2190 - F1: 0.2118
sub_2:Test (Best Model) - Loss: 1.5955 - Accuracy: 0.2476 - F1: 0.2388
sub_2:Test (Best Model) - Loss: 1.5924 - Accuracy: 0.2143 - F1: 0.2032
sub_2:Test (Best Model) - Loss: 1.5994 - Accuracy: 0.2190 - F1: 0.2217
sub_2:Test (Best Model) - Loss: 1.5981 - Accuracy: 0.2333 - F1: 0.2211
sub_2:Test (Best Model) - Loss: 1.6039 - Accuracy: 0.2143 - F1: 0.1932
sub_2:Test (Best Model) - Loss: 1.6047 - Accuracy: 0.1810 - F1: 0.1759
sub_3:Test (Best Model) - Loss: 1.6030 - Accuracy: 0.2619 - F1: 0.2276
sub_3:Test (Best Model) - Loss: 1.6074 - Accuracy: 0.2429 - F1: 0.2074
sub_3:Test (Best Model) - Loss: 1.6041 - Accuracy: 0.2667 - F1: 0.2620
sub_3:Test (Best Model) - Loss: 1.6040 - Accuracy: 0.2286 - F1: 0.1924
sub_3:Test (Best Model) - Loss: 1.6083 - Accuracy: 0.2286 - F1: 0.2272
sub_3:Test (Best Model) - Loss: 1.6010 - Accuracy: 0.2429 - F1: 0.2263
sub_3:Test (Best Model) - Loss: 1.6031 - Accuracy: 0.2143 - F1: 0.2024
sub_3:Test (Best Model) - Loss: 1.5987 - Accuracy: 0.2381 - F1: 0.2272
sub_3:Test (Best Model) - Loss: 1.6065 - Accuracy: 0.2190 - F1: 0.2046
sub_3:Test (Best Model) - Loss: 1.5963 - Accuracy: 0.2381 - F1: 0.2341
sub_3:Test (Best Model) - Loss: 1.6007 - Accuracy: 0.2667 - F1: 0.2567
sub_3:Test (Best Model) - Loss: 1.5987 - Accuracy: 0.2381 - F1: 0.2237
sub_3:Test (Best Model) - Loss: 1.6115 - Accuracy: 0.2524 - F1: 0.2506
sub_3:Test (Best Model) - Loss: 1.6049 - Accuracy: 0.2143 - F1: 0.2071
sub_3:Test (Best Model) - Loss: 1.6037 - Accuracy: 0.2190 - F1: 0.2097
sub_4:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.1952 - F1: 0.1914
sub_4:Test (Best Model) - Loss: 1.6110 - Accuracy: 0.1762 - F1: 0.1722
sub_4:Test (Best Model) - Loss: 1.6161 - Accuracy: 0.1810 - F1: 0.1631
sub_4:Test (Best Model) - Loss: 1.6071 - Accuracy: 0.2048 - F1: 0.1939
sub_4:Test (Best Model) - Loss: 1.6017 - Accuracy: 0.2190 - F1: 0.2088
sub_4:Test (Best Model) - Loss: 1.6021 - Accuracy: 0.2333 - F1: 0.2055
sub_4:Test (Best Model) - Loss: 1.6080 - Accuracy: 0.2190 - F1: 0.1987
sub_4:Test (Best Model) - Loss: 1.6075 - Accuracy: 0.2333 - F1: 0.2147
sub_4:Test (Best Model) - Loss: 1.6067 - Accuracy: 0.2190 - F1: 0.2127
sub_4:Test (Best Model) - Loss: 1.6057 - Accuracy: 0.2286 - F1: 0.2190
sub_4:Test (Best Model) - Loss: 1.6110 - Accuracy: 0.2095 - F1: 0.2088
sub_4:Test (Best Model) - Loss: 1.6069 - Accuracy: 0.2286 - F1: 0.2207
sub_4:Test (Best Model) - Loss: 1.6089 - Accuracy: 0.2190 - F1: 0.1963
sub_4:Test (Best Model) - Loss: 1.6083 - Accuracy: 0.2000 - F1: 0.1790
sub_4:Test (Best Model) - Loss: 1.6060 - Accuracy: 0.2238 - F1: 0.2072
sub_5:Test (Best Model) - Loss: 1.6085 - Accuracy: 0.2381 - F1: 0.2293
sub_5:Test (Best Model) - Loss: 1.6053 - Accuracy: 0.2048 - F1: 0.1843
sub_5:Test (Best Model) - Loss: 1.5964 - Accuracy: 0.2143 - F1: 0.1916
sub_5:Test (Best Model) - Loss: 1.5988 - Accuracy: 0.2429 - F1: 0.2459
sub_5:Test (Best Model) - Loss: 1.6041 - Accuracy: 0.2333 - F1: 0.2162
sub_5:Test (Best Model) - Loss: 1.6000 - Accuracy: 0.2524 - F1: 0.2360
sub_5:Test (Best Model) - Loss: 1.6089 - Accuracy: 0.1905 - F1: 0.1647
sub_5:Test (Best Model) - Loss: 1.5967 - Accuracy: 0.2571 - F1: 0.2361
sub_5:Test (Best Model) - Loss: 1.6004 - Accuracy: 0.2571 - F1: 0.2300
sub_5:Test (Best Model) - Loss: 1.6040 - Accuracy: 0.2381 - F1: 0.2319
sub_5:Test (Best Model) - Loss: 1.5999 - Accuracy: 0.2571 - F1: 0.2574
sub_5:Test (Best Model) - Loss: 1.6034 - Accuracy: 0.2429 - F1: 0.2375
sub_5:Test (Best Model) - Loss: 1.6031 - Accuracy: 0.2190 - F1: 0.2041
sub_5:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2333 - F1: 0.2188
sub_5:Test (Best Model) - Loss: 1.6143 - Accuracy: 0.2048 - F1: 0.1994
sub_6:Test (Best Model) - Loss: 1.6061 - Accuracy: 0.1857 - F1: 0.1751
sub_6:Test (Best Model) - Loss: 1.6069 - Accuracy: 0.2143 - F1: 0.2012
sub_6:Test (Best Model) - Loss: 1.6086 - Accuracy: 0.1952 - F1: 0.1957
sub_6:Test (Best Model) - Loss: 1.6085 - Accuracy: 0.2048 - F1: 0.1855
sub_6:Test (Best Model) - Loss: 1.6009 - Accuracy: 0.2381 - F1: 0.2343
sub_6:Test (Best Model) - Loss: 1.6163 - Accuracy: 0.1619 - F1: 0.1453
sub_6:Test (Best Model) - Loss: 1.6138 - Accuracy: 0.2048 - F1: 0.2114
sub_6:Test (Best Model) - Loss: 1.6113 - Accuracy: 0.1905 - F1: 0.1733
sub_6:Test (Best Model) - Loss: 1.6084 - Accuracy: 0.2333 - F1: 0.2288
sub_6:Test (Best Model) - Loss: 1.6066 - Accuracy: 0.2048 - F1: 0.1995
sub_6:Test (Best Model) - Loss: 1.6147 - Accuracy: 0.2238 - F1: 0.2257
sub_6:Test (Best Model) - Loss: 1.6174 - Accuracy: 0.1619 - F1: 0.1574
sub_6:Test (Best Model) - Loss: 1.6143 - Accuracy: 0.1952 - F1: 0.1958
sub_6:Test (Best Model) - Loss: 1.6200 - Accuracy: 0.1381 - F1: 0.1300
sub_6:Test (Best Model) - Loss: 1.6149 - Accuracy: 0.1952 - F1: 0.1771
sub_7:Test (Best Model) - Loss: 1.6181 - Accuracy: 0.1762 - F1: 0.1518
sub_7:Test (Best Model) - Loss: 1.6107 - Accuracy: 0.1857 - F1: 0.1777
sub_7:Test (Best Model) - Loss: 1.6133 - Accuracy: 0.2429 - F1: 0.2327
sub_7:Test (Best Model) - Loss: 1.6144 - Accuracy: 0.2286 - F1: 0.2134
sub_7:Test (Best Model) - Loss: 1.6143 - Accuracy: 0.1857 - F1: 0.1748
sub_7:Test (Best Model) - Loss: 1.6135 - Accuracy: 0.1905 - F1: 0.1826
sub_7:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2000 - F1: 0.2005
sub_7:Test (Best Model) - Loss: 1.6148 - Accuracy: 0.2095 - F1: 0.2020
sub_7:Test (Best Model) - Loss: 1.6153 - Accuracy: 0.2143 - F1: 0.2131
sub_7:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2381 - F1: 0.2256
sub_7:Test (Best Model) - Loss: 1.6009 - Accuracy: 0.2476 - F1: 0.2432
sub_7:Test (Best Model) - Loss: 1.6067 - Accuracy: 0.2333 - F1: 0.2244
sub_7:Test (Best Model) - Loss: 1.6080 - Accuracy: 0.2333 - F1: 0.2289
sub_7:Test (Best Model) - Loss: 1.6068 - Accuracy: 0.2000 - F1: 0.2000
sub_7:Test (Best Model) - Loss: 1.6053 - Accuracy: 0.2381 - F1: 0.2243
sub_8:Test (Best Model) - Loss: 1.5888 - Accuracy: 0.2524 - F1: 0.2473
sub_8:Test (Best Model) - Loss: 1.5896 - Accuracy: 0.3000 - F1: 0.2984
sub_8:Test (Best Model) - Loss: 1.5770 - Accuracy: 0.2429 - F1: 0.2485
sub_8:Test (Best Model) - Loss: 1.5961 - Accuracy: 0.2524 - F1: 0.2581
sub_8:Test (Best Model) - Loss: 1.5936 - Accuracy: 0.2952 - F1: 0.2800
sub_8:Test (Best Model) - Loss: 1.5852 - Accuracy: 0.2333 - F1: 0.2253
sub_8:Test (Best Model) - Loss: 1.5951 - Accuracy: 0.2190 - F1: 0.2191
sub_8:Test (Best Model) - Loss: 1.5902 - Accuracy: 0.2857 - F1: 0.2808
sub_8:Test (Best Model) - Loss: 1.5764 - Accuracy: 0.2619 - F1: 0.2695
sub_8:Test (Best Model) - Loss: 1.5872 - Accuracy: 0.2952 - F1: 0.2900
sub_8:Test (Best Model) - Loss: 1.5949 - Accuracy: 0.2286 - F1: 0.2290
sub_8:Test (Best Model) - Loss: 1.5973 - Accuracy: 0.2238 - F1: 0.2192
sub_8:Test (Best Model) - Loss: 1.5982 - Accuracy: 0.2333 - F1: 0.2169
sub_8:Test (Best Model) - Loss: 1.6052 - Accuracy: 0.2095 - F1: 0.2012
sub_8:Test (Best Model) - Loss: 1.6010 - Accuracy: 0.2143 - F1: 0.1826
sub_9:Test (Best Model) - Loss: 1.6031 - Accuracy: 0.2095 - F1: 0.2034
sub_9:Test (Best Model) - Loss: 1.6058 - Accuracy: 0.2429 - F1: 0.2460
sub_9:Test (Best Model) - Loss: 1.5965 - Accuracy: 0.2810 - F1: 0.2795
sub_9:Test (Best Model) - Loss: 1.6006 - Accuracy: 0.2429 - F1: 0.2363
sub_9:Test (Best Model) - Loss: 1.6029 - Accuracy: 0.2333 - F1: 0.2269
sub_9:Test (Best Model) - Loss: 1.6145 - Accuracy: 0.1810 - F1: 0.1764
sub_9:Test (Best Model) - Loss: 1.6083 - Accuracy: 0.2381 - F1: 0.2415
sub_9:Test (Best Model) - Loss: 1.6080 - Accuracy: 0.2238 - F1: 0.2088
sub_9:Test (Best Model) - Loss: 1.6188 - Accuracy: 0.1762 - F1: 0.1740
sub_9:Test (Best Model) - Loss: 1.6130 - Accuracy: 0.2000 - F1: 0.1939
sub_9:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.1667 - F1: 0.1633
sub_9:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2000 - F1: 0.1855
sub_9:Test (Best Model) - Loss: 1.6058 - Accuracy: 0.2000 - F1: 0.1877
sub_9:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2429 - F1: 0.2172
sub_9:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.1952 - F1: 0.1915
sub_10:Test (Best Model) - Loss: 1.6124 - Accuracy: 0.1810 - F1: 0.1769
sub_10:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2476 - F1: 0.2437
sub_10:Test (Best Model) - Loss: 1.6136 - Accuracy: 0.1714 - F1: 0.1555
sub_10:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2095 - F1: 0.2087
sub_10:Test (Best Model) - Loss: 1.6147 - Accuracy: 0.1714 - F1: 0.1696
sub_10:Test (Best Model) - Loss: 1.6135 - Accuracy: 0.1905 - F1: 0.1848
sub_10:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2190 - F1: 0.2128
sub_10:Test (Best Model) - Loss: 1.6044 - Accuracy: 0.2238 - F1: 0.2185
sub_10:Test (Best Model) - Loss: 1.6026 - Accuracy: 0.2429 - F1: 0.2391
sub_10:Test (Best Model) - Loss: 1.6140 - Accuracy: 0.1619 - F1: 0.1596
sub_10:Test (Best Model) - Loss: 1.6162 - Accuracy: 0.1762 - F1: 0.1727
sub_10:Test (Best Model) - Loss: 1.6079 - Accuracy: 0.2143 - F1: 0.2160
sub_10:Test (Best Model) - Loss: 1.6118 - Accuracy: 0.2238 - F1: 0.2254
sub_10:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2286 - F1: 0.2207
sub_10:Test (Best Model) - Loss: 1.6143 - Accuracy: 0.1619 - F1: 0.1610
sub_11:Test (Best Model) - Loss: 1.6154 - Accuracy: 0.1714 - F1: 0.1420
sub_11:Test (Best Model) - Loss: 1.6168 - Accuracy: 0.1762 - F1: 0.1685
sub_11:Test (Best Model) - Loss: 1.6160 - Accuracy: 0.1571 - F1: 0.1391
sub_11:Test (Best Model) - Loss: 1.6193 - Accuracy: 0.1762 - F1: 0.1671
sub_11:Test (Best Model) - Loss: 1.6072 - Accuracy: 0.2095 - F1: 0.2064
sub_11:Test (Best Model) - Loss: 1.6077 - Accuracy: 0.2381 - F1: 0.2249
sub_11:Test (Best Model) - Loss: 1.6087 - Accuracy: 0.2095 - F1: 0.2069
sub_11:Test (Best Model) - Loss: 1.6035 - Accuracy: 0.2143 - F1: 0.2030
sub_11:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.2143 - F1: 0.2015
sub_11:Test (Best Model) - Loss: 1.6070 - Accuracy: 0.2048 - F1: 0.2052
sub_11:Test (Best Model) - Loss: 1.6174 - Accuracy: 0.1952 - F1: 0.1876
sub_11:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2286 - F1: 0.2179
sub_11:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2048 - F1: 0.1830
sub_11:Test (Best Model) - Loss: 1.6189 - Accuracy: 0.1810 - F1: 0.1685
sub_11:Test (Best Model) - Loss: 1.6213 - Accuracy: 0.1667 - F1: 0.1613
sub_12:Test (Best Model) - Loss: 1.6054 - Accuracy: 0.2143 - F1: 0.2194
sub_12:Test (Best Model) - Loss: 1.6087 - Accuracy: 0.1952 - F1: 0.1909
sub_12:Test (Best Model) - Loss: 1.6030 - Accuracy: 0.2571 - F1: 0.2496
sub_12:Test (Best Model) - Loss: 1.6001 - Accuracy: 0.2143 - F1: 0.2126
sub_12:Test (Best Model) - Loss: 1.6042 - Accuracy: 0.2571 - F1: 0.2581
sub_12:Test (Best Model) - Loss: 1.6024 - Accuracy: 0.2619 - F1: 0.2418
sub_12:Test (Best Model) - Loss: 1.6037 - Accuracy: 0.2143 - F1: 0.2141
sub_12:Test (Best Model) - Loss: 1.6083 - Accuracy: 0.2286 - F1: 0.2225
sub_12:Test (Best Model) - Loss: 1.6043 - Accuracy: 0.2667 - F1: 0.2506
sub_12:Test (Best Model) - Loss: 1.5991 - Accuracy: 0.2905 - F1: 0.2731
sub_12:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.1952 - F1: 0.1745
sub_12:Test (Best Model) - Loss: 1.6136 - Accuracy: 0.2048 - F1: 0.1963
sub_12:Test (Best Model) - Loss: 1.6159 - Accuracy: 0.2000 - F1: 0.1981
sub_12:Test (Best Model) - Loss: 1.6116 - Accuracy: 0.2333 - F1: 0.2234
sub_12:Test (Best Model) - Loss: 1.6177 - Accuracy: 0.2190 - F1: 0.2195
sub_13:Test (Best Model) - Loss: 1.6082 - Accuracy: 0.2286 - F1: 0.2240
sub_13:Test (Best Model) - Loss: 1.6062 - Accuracy: 0.2143 - F1: 0.2165
sub_13:Test (Best Model) - Loss: 1.6064 - Accuracy: 0.2571 - F1: 0.2500
sub_13:Test (Best Model) - Loss: 1.6024 - Accuracy: 0.2048 - F1: 0.1951
sub_13:Test (Best Model) - Loss: 1.6048 - Accuracy: 0.2048 - F1: 0.1851
sub_13:Test (Best Model) - Loss: 1.6147 - Accuracy: 0.2238 - F1: 0.2111
sub_13:Test (Best Model) - Loss: 1.6121 - Accuracy: 0.1762 - F1: 0.1803
sub_13:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.1810 - F1: 0.1717
sub_13:Test (Best Model) - Loss: 1.6047 - Accuracy: 0.2238 - F1: 0.2241
sub_13:Test (Best Model) - Loss: 1.6078 - Accuracy: 0.2190 - F1: 0.2252
sub_13:Test (Best Model) - Loss: 1.6123 - Accuracy: 0.1762 - F1: 0.1569
sub_13:Test (Best Model) - Loss: 1.6075 - Accuracy: 0.1952 - F1: 0.1836
sub_13:Test (Best Model) - Loss: 1.6126 - Accuracy: 0.2143 - F1: 0.2160
sub_13:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2095 - F1: 0.1987
sub_13:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2286 - F1: 0.2234
sub_14:Test (Best Model) - Loss: 1.6184 - Accuracy: 0.2238 - F1: 0.1921
sub_14:Test (Best Model) - Loss: 1.6140 - Accuracy: 0.2095 - F1: 0.1883
sub_14:Test (Best Model) - Loss: 1.6054 - Accuracy: 0.2381 - F1: 0.2253
sub_14:Test (Best Model) - Loss: 1.6090 - Accuracy: 0.2238 - F1: 0.2142
sub_14:Test (Best Model) - Loss: 1.6202 - Accuracy: 0.1905 - F1: 0.1788
sub_14:Test (Best Model) - Loss: 1.5960 - Accuracy: 0.2429 - F1: 0.2355
sub_14:Test (Best Model) - Loss: 1.5946 - Accuracy: 0.2095 - F1: 0.1948
sub_14:Test (Best Model) - Loss: 1.5987 - Accuracy: 0.2190 - F1: 0.2073
sub_14:Test (Best Model) - Loss: 1.6009 - Accuracy: 0.2286 - F1: 0.2314
sub_14:Test (Best Model) - Loss: 1.6125 - Accuracy: 0.2048 - F1: 0.2009
sub_14:Test (Best Model) - Loss: 1.6079 - Accuracy: 0.2095 - F1: 0.1901
sub_14:Test (Best Model) - Loss: 1.5989 - Accuracy: 0.2429 - F1: 0.2190
sub_14:Test (Best Model) - Loss: 1.6124 - Accuracy: 0.1952 - F1: 0.1672
sub_14:Test (Best Model) - Loss: 1.6122 - Accuracy: 0.1905 - F1: 0.1648
sub_14:Test (Best Model) - Loss: 1.6123 - Accuracy: 0.1714 - F1: 0.1556

=== Summary Results ===

acc: 22.07 ± 1.96
F1: 21.10 ± 1.99
acc-in: 25.44 ± 1.59
F1-in: 24.31 ± 1.67
