lr: 1e-06
sub_1:Test (Best Model) - Loss: 1.5858 - Accuracy: 0.2524 - F1: 0.2317
sub_1:Test (Best Model) - Loss: 1.5689 - Accuracy: 0.3048 - F1: 0.2750
sub_1:Test (Best Model) - Loss: 1.5794 - Accuracy: 0.2952 - F1: 0.2808
sub_1:Test (Best Model) - Loss: 1.5924 - Accuracy: 0.2571 - F1: 0.2585
sub_1:Test (Best Model) - Loss: 1.5960 - Accuracy: 0.2952 - F1: 0.2754
sub_1:Test (Best Model) - Loss: 1.5832 - Accuracy: 0.2524 - F1: 0.2559
sub_1:Test (Best Model) - Loss: 1.5842 - Accuracy: 0.2667 - F1: 0.2678
sub_1:Test (Best Model) - Loss: 1.5637 - Accuracy: 0.2952 - F1: 0.2853
sub_1:Test (Best Model) - Loss: 1.5572 - Accuracy: 0.3143 - F1: 0.3193
sub_1:Test (Best Model) - Loss: 1.5938 - Accuracy: 0.2524 - F1: 0.2452
sub_1:Test (Best Model) - Loss: 1.5721 - Accuracy: 0.2476 - F1: 0.2470
sub_1:Test (Best Model) - Loss: 1.5462 - Accuracy: 0.2952 - F1: 0.2763
sub_1:Test (Best Model) - Loss: 1.5741 - Accuracy: 0.3095 - F1: 0.2824
sub_1:Test (Best Model) - Loss: 1.5664 - Accuracy: 0.2810 - F1: 0.2750
sub_1:Test (Best Model) - Loss: 1.5649 - Accuracy: 0.2667 - F1: 0.2682
sub_2:Test (Best Model) - Loss: 1.5669 - Accuracy: 0.2429 - F1: 0.2169
sub_2:Test (Best Model) - Loss: 1.5919 - Accuracy: 0.2571 - F1: 0.2524
sub_2:Test (Best Model) - Loss: 1.5877 - Accuracy: 0.2095 - F1: 0.1812
sub_2:Test (Best Model) - Loss: 1.5883 - Accuracy: 0.2238 - F1: 0.2131
sub_2:Test (Best Model) - Loss: 1.5959 - Accuracy: 0.2286 - F1: 0.2100
sub_2:Test (Best Model) - Loss: 1.5950 - Accuracy: 0.2381 - F1: 0.2179
sub_2:Test (Best Model) - Loss: 1.5901 - Accuracy: 0.2190 - F1: 0.2113
sub_2:Test (Best Model) - Loss: 1.5770 - Accuracy: 0.2571 - F1: 0.2556
sub_2:Test (Best Model) - Loss: 1.5777 - Accuracy: 0.2429 - F1: 0.2317
sub_2:Test (Best Model) - Loss: 1.5791 - Accuracy: 0.2095 - F1: 0.1882
sub_2:Test (Best Model) - Loss: 1.5887 - Accuracy: 0.2143 - F1: 0.2046
sub_2:Test (Best Model) - Loss: 1.5913 - Accuracy: 0.2238 - F1: 0.2248
sub_2:Test (Best Model) - Loss: 1.5811 - Accuracy: 0.2286 - F1: 0.2159
sub_2:Test (Best Model) - Loss: 1.5875 - Accuracy: 0.2476 - F1: 0.2356
sub_2:Test (Best Model) - Loss: 1.5969 - Accuracy: 0.2476 - F1: 0.2393
sub_3:Test (Best Model) - Loss: 1.5988 - Accuracy: 0.2524 - F1: 0.2147
sub_3:Test (Best Model) - Loss: 1.5982 - Accuracy: 0.2810 - F1: 0.2321
sub_3:Test (Best Model) - Loss: 1.6026 - Accuracy: 0.2429 - F1: 0.2296
sub_3:Test (Best Model) - Loss: 1.5969 - Accuracy: 0.2762 - F1: 0.2346
sub_3:Test (Best Model) - Loss: 1.6109 - Accuracy: 0.2048 - F1: 0.2034
sub_3:Test (Best Model) - Loss: 1.5890 - Accuracy: 0.2714 - F1: 0.2578
sub_3:Test (Best Model) - Loss: 1.5986 - Accuracy: 0.2381 - F1: 0.2197
sub_3:Test (Best Model) - Loss: 1.5873 - Accuracy: 0.2810 - F1: 0.2547
sub_3:Test (Best Model) - Loss: 1.6028 - Accuracy: 0.2619 - F1: 0.2553
sub_3:Test (Best Model) - Loss: 1.5951 - Accuracy: 0.2381 - F1: 0.2366
sub_3:Test (Best Model) - Loss: 1.5989 - Accuracy: 0.2714 - F1: 0.2694
sub_3:Test (Best Model) - Loss: 1.5713 - Accuracy: 0.2714 - F1: 0.2755
sub_3:Test (Best Model) - Loss: 1.5984 - Accuracy: 0.2476 - F1: 0.2459
sub_3:Test (Best Model) - Loss: 1.5992 - Accuracy: 0.2238 - F1: 0.2186
sub_3:Test (Best Model) - Loss: 1.5937 - Accuracy: 0.2381 - F1: 0.2440
sub_4:Test (Best Model) - Loss: 1.6018 - Accuracy: 0.1905 - F1: 0.1747
sub_4:Test (Best Model) - Loss: 1.6089 - Accuracy: 0.1810 - F1: 0.1666
sub_4:Test (Best Model) - Loss: 1.6177 - Accuracy: 0.1810 - F1: 0.1629
sub_4:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.1952 - F1: 0.1904
sub_4:Test (Best Model) - Loss: 1.6114 - Accuracy: 0.2048 - F1: 0.1979
sub_4:Test (Best Model) - Loss: 1.5899 - Accuracy: 0.2667 - F1: 0.2554
sub_4:Test (Best Model) - Loss: 1.5983 - Accuracy: 0.2571 - F1: 0.2449
sub_4:Test (Best Model) - Loss: 1.5962 - Accuracy: 0.2286 - F1: 0.2152
sub_4:Test (Best Model) - Loss: 1.6002 - Accuracy: 0.2238 - F1: 0.2212
sub_4:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.1905 - F1: 0.1935
sub_4:Test (Best Model) - Loss: 1.6148 - Accuracy: 0.1952 - F1: 0.1758
sub_4:Test (Best Model) - Loss: 1.5974 - Accuracy: 0.2524 - F1: 0.2469
sub_4:Test (Best Model) - Loss: 1.5999 - Accuracy: 0.2048 - F1: 0.1845
sub_4:Test (Best Model) - Loss: 1.6022 - Accuracy: 0.2286 - F1: 0.2215
sub_4:Test (Best Model) - Loss: 1.6036 - Accuracy: 0.2524 - F1: 0.2394
sub_5:Test (Best Model) - Loss: 1.6064 - Accuracy: 0.2143 - F1: 0.2111
sub_5:Test (Best Model) - Loss: 1.5993 - Accuracy: 0.2381 - F1: 0.2357
sub_5:Test (Best Model) - Loss: 1.5783 - Accuracy: 0.2714 - F1: 0.2531
sub_5:Test (Best Model) - Loss: 1.5922 - Accuracy: 0.2286 - F1: 0.2306
sub_5:Test (Best Model) - Loss: 1.5916 - Accuracy: 0.2000 - F1: 0.1971
sub_5:Test (Best Model) - Loss: 1.5979 - Accuracy: 0.2286 - F1: 0.2123
sub_5:Test (Best Model) - Loss: 1.5988 - Accuracy: 0.2238 - F1: 0.2037
sub_5:Test (Best Model) - Loss: 1.5915 - Accuracy: 0.2429 - F1: 0.2220
sub_5:Test (Best Model) - Loss: 1.5933 - Accuracy: 0.2667 - F1: 0.2249
sub_5:Test (Best Model) - Loss: 1.6028 - Accuracy: 0.2429 - F1: 0.2140
sub_5:Test (Best Model) - Loss: 1.5978 - Accuracy: 0.2095 - F1: 0.2030
sub_5:Test (Best Model) - Loss: 1.5989 - Accuracy: 0.2571 - F1: 0.2535
sub_5:Test (Best Model) - Loss: 1.5883 - Accuracy: 0.2286 - F1: 0.2206
sub_5:Test (Best Model) - Loss: 1.6000 - Accuracy: 0.2190 - F1: 0.2083
sub_5:Test (Best Model) - Loss: 1.6051 - Accuracy: 0.2000 - F1: 0.1880
sub_6:Test (Best Model) - Loss: 1.6080 - Accuracy: 0.1952 - F1: 0.1854
sub_6:Test (Best Model) - Loss: 1.6088 - Accuracy: 0.2333 - F1: 0.2228
sub_6:Test (Best Model) - Loss: 1.5975 - Accuracy: 0.2571 - F1: 0.2549
sub_6:Test (Best Model) - Loss: 1.6187 - Accuracy: 0.1952 - F1: 0.1872
sub_6:Test (Best Model) - Loss: 1.6078 - Accuracy: 0.2143 - F1: 0.1992
sub_6:Test (Best Model) - Loss: 1.6377 - Accuracy: 0.1667 - F1: 0.1641
sub_6:Test (Best Model) - Loss: 1.6127 - Accuracy: 0.2143 - F1: 0.2044
sub_6:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.2524 - F1: 0.2490
sub_6:Test (Best Model) - Loss: 1.6038 - Accuracy: 0.2190 - F1: 0.2222
sub_6:Test (Best Model) - Loss: 1.6006 - Accuracy: 0.2571 - F1: 0.2577
sub_6:Test (Best Model) - Loss: 1.6141 - Accuracy: 0.2429 - F1: 0.2311
sub_6:Test (Best Model) - Loss: 1.6106 - Accuracy: 0.2286 - F1: 0.2180
sub_6:Test (Best Model) - Loss: 1.6070 - Accuracy: 0.2238 - F1: 0.2212
sub_6:Test (Best Model) - Loss: 1.6203 - Accuracy: 0.1429 - F1: 0.1370
sub_6:Test (Best Model) - Loss: 1.6187 - Accuracy: 0.2000 - F1: 0.1919
sub_7:Test (Best Model) - Loss: 1.6236 - Accuracy: 0.2238 - F1: 0.2036
sub_7:Test (Best Model) - Loss: 1.6234 - Accuracy: 0.1762 - F1: 0.1669
sub_7:Test (Best Model) - Loss: 1.6149 - Accuracy: 0.2571 - F1: 0.2495
sub_7:Test (Best Model) - Loss: 1.6199 - Accuracy: 0.1905 - F1: 0.1814
sub_7:Test (Best Model) - Loss: 1.6122 - Accuracy: 0.2095 - F1: 0.2030
sub_7:Test (Best Model) - Loss: 1.6246 - Accuracy: 0.2190 - F1: 0.2164
sub_7:Test (Best Model) - Loss: 1.6137 - Accuracy: 0.1810 - F1: 0.1769
sub_7:Test (Best Model) - Loss: 1.6118 - Accuracy: 0.2333 - F1: 0.2245
sub_7:Test (Best Model) - Loss: 1.6127 - Accuracy: 0.2190 - F1: 0.2203
sub_7:Test (Best Model) - Loss: 1.6155 - Accuracy: 0.1571 - F1: 0.1433
sub_7:Test (Best Model) - Loss: 1.6015 - Accuracy: 0.2095 - F1: 0.1726
sub_7:Test (Best Model) - Loss: 1.5949 - Accuracy: 0.2524 - F1: 0.2470
sub_7:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.1857 - F1: 0.1847
sub_7:Test (Best Model) - Loss: 1.6047 - Accuracy: 0.2476 - F1: 0.2361
sub_7:Test (Best Model) - Loss: 1.5980 - Accuracy: 0.2286 - F1: 0.2054
sub_8:Test (Best Model) - Loss: 1.5732 - Accuracy: 0.3048 - F1: 0.3090
sub_8:Test (Best Model) - Loss: 1.5705 - Accuracy: 0.3190 - F1: 0.3233
sub_8:Test (Best Model) - Loss: 1.5746 - Accuracy: 0.2524 - F1: 0.2428
sub_8:Test (Best Model) - Loss: 1.5768 - Accuracy: 0.2762 - F1: 0.2781
sub_8:Test (Best Model) - Loss: 1.5525 - Accuracy: 0.3190 - F1: 0.3142
sub_8:Test (Best Model) - Loss: 1.5613 - Accuracy: 0.2952 - F1: 0.3056
sub_8:Test (Best Model) - Loss: 1.5609 - Accuracy: 0.2667 - F1: 0.2838
sub_8:Test (Best Model) - Loss: 1.5650 - Accuracy: 0.3238 - F1: 0.3303
sub_8:Test (Best Model) - Loss: 1.5626 - Accuracy: 0.2857 - F1: 0.2937
sub_8:Test (Best Model) - Loss: 1.5872 - Accuracy: 0.2571 - F1: 0.2619
sub_8:Test (Best Model) - Loss: 1.5987 - Accuracy: 0.1810 - F1: 0.1678
sub_8:Test (Best Model) - Loss: 1.5731 - Accuracy: 0.2190 - F1: 0.2206
sub_8:Test (Best Model) - Loss: 1.5718 - Accuracy: 0.2238 - F1: 0.2132
sub_8:Test (Best Model) - Loss: 1.5888 - Accuracy: 0.1810 - F1: 0.1669
sub_8:Test (Best Model) - Loss: 1.6050 - Accuracy: 0.1857 - F1: 0.1797
sub_9:Test (Best Model) - Loss: 1.5992 - Accuracy: 0.2714 - F1: 0.2659
sub_9:Test (Best Model) - Loss: 1.5972 - Accuracy: 0.2286 - F1: 0.2285
sub_9:Test (Best Model) - Loss: 1.5910 - Accuracy: 0.2524 - F1: 0.2484
sub_9:Test (Best Model) - Loss: 1.5984 - Accuracy: 0.2619 - F1: 0.2628
sub_9:Test (Best Model) - Loss: 1.6015 - Accuracy: 0.2381 - F1: 0.2365
sub_9:Test (Best Model) - Loss: 1.6086 - Accuracy: 0.1810 - F1: 0.1714
sub_9:Test (Best Model) - Loss: 1.6114 - Accuracy: 0.2000 - F1: 0.2017
sub_9:Test (Best Model) - Loss: 1.6025 - Accuracy: 0.2476 - F1: 0.2469
sub_9:Test (Best Model) - Loss: 1.6203 - Accuracy: 0.1810 - F1: 0.1810
sub_9:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2238 - F1: 0.2275
sub_9:Test (Best Model) - Loss: 1.6276 - Accuracy: 0.1810 - F1: 0.1689
sub_9:Test (Best Model) - Loss: 1.5991 - Accuracy: 0.2571 - F1: 0.2497
sub_9:Test (Best Model) - Loss: 1.6074 - Accuracy: 0.1952 - F1: 0.1982
sub_9:Test (Best Model) - Loss: 1.6061 - Accuracy: 0.2238 - F1: 0.2260
sub_9:Test (Best Model) - Loss: 1.6063 - Accuracy: 0.2190 - F1: 0.2125
sub_10:Test (Best Model) - Loss: 1.6158 - Accuracy: 0.2571 - F1: 0.2531
sub_10:Test (Best Model) - Loss: 1.6064 - Accuracy: 0.2714 - F1: 0.2695
sub_10:Test (Best Model) - Loss: 1.6128 - Accuracy: 0.2429 - F1: 0.2432
sub_10:Test (Best Model) - Loss: 1.6156 - Accuracy: 0.2143 - F1: 0.2110
sub_10:Test (Best Model) - Loss: 1.6169 - Accuracy: 0.2571 - F1: 0.2458
sub_10:Test (Best Model) - Loss: 1.6082 - Accuracy: 0.2143 - F1: 0.2151
sub_10:Test (Best Model) - Loss: 1.6055 - Accuracy: 0.2476 - F1: 0.2460
sub_10:Test (Best Model) - Loss: 1.6022 - Accuracy: 0.2286 - F1: 0.2261
sub_10:Test (Best Model) - Loss: 1.6022 - Accuracy: 0.2429 - F1: 0.2385
sub_10:Test (Best Model) - Loss: 1.6056 - Accuracy: 0.2286 - F1: 0.2197
sub_10:Test (Best Model) - Loss: 1.6302 - Accuracy: 0.1714 - F1: 0.1713
sub_10:Test (Best Model) - Loss: 1.6159 - Accuracy: 0.1857 - F1: 0.1878
sub_10:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2190 - F1: 0.2172
sub_10:Test (Best Model) - Loss: 1.6080 - Accuracy: 0.1905 - F1: 0.1766
sub_10:Test (Best Model) - Loss: 1.6233 - Accuracy: 0.2381 - F1: 0.2384
sub_11:Test (Best Model) - Loss: 1.6109 - Accuracy: 0.2095 - F1: 0.2026
sub_11:Test (Best Model) - Loss: 1.6139 - Accuracy: 0.2238 - F1: 0.2130
sub_11:Test (Best Model) - Loss: 1.6150 - Accuracy: 0.1714 - F1: 0.1608
sub_11:Test (Best Model) - Loss: 1.6166 - Accuracy: 0.1571 - F1: 0.1527
sub_11:Test (Best Model) - Loss: 1.6120 - Accuracy: 0.2048 - F1: 0.1959
sub_11:Test (Best Model) - Loss: 1.6049 - Accuracy: 0.2238 - F1: 0.2184
sub_11:Test (Best Model) - Loss: 1.6080 - Accuracy: 0.2048 - F1: 0.1996
sub_11:Test (Best Model) - Loss: 1.5892 - Accuracy: 0.3048 - F1: 0.2982
sub_11:Test (Best Model) - Loss: 1.6028 - Accuracy: 0.2190 - F1: 0.2111
sub_11:Test (Best Model) - Loss: 1.6057 - Accuracy: 0.1905 - F1: 0.1774
sub_11:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2000 - F1: 0.1959
sub_11:Test (Best Model) - Loss: 1.5997 - Accuracy: 0.2381 - F1: 0.2296
sub_11:Test (Best Model) - Loss: 1.6173 - Accuracy: 0.2333 - F1: 0.2151
sub_11:Test (Best Model) - Loss: 1.6168 - Accuracy: 0.1905 - F1: 0.1727
sub_11:Test (Best Model) - Loss: 1.6204 - Accuracy: 0.2476 - F1: 0.2510
sub_12:Test (Best Model) - Loss: 1.5976 - Accuracy: 0.2286 - F1: 0.2280
sub_12:Test (Best Model) - Loss: 1.5984 - Accuracy: 0.2381 - F1: 0.2338
sub_12:Test (Best Model) - Loss: 1.6052 - Accuracy: 0.2143 - F1: 0.2126
sub_12:Test (Best Model) - Loss: 1.5975 - Accuracy: 0.2714 - F1: 0.2721
sub_12:Test (Best Model) - Loss: 1.6060 - Accuracy: 0.2190 - F1: 0.2187
sub_12:Test (Best Model) - Loss: 1.5832 - Accuracy: 0.2810 - F1: 0.2564
sub_12:Test (Best Model) - Loss: 1.5981 - Accuracy: 0.2143 - F1: 0.2039
sub_12:Test (Best Model) - Loss: 1.5970 - Accuracy: 0.2476 - F1: 0.2284
sub_12:Test (Best Model) - Loss: 1.6019 - Accuracy: 0.2429 - F1: 0.2393
sub_12:Test (Best Model) - Loss: 1.5949 - Accuracy: 0.2667 - F1: 0.2690
sub_12:Test (Best Model) - Loss: 1.6138 - Accuracy: 0.2143 - F1: 0.2148
sub_12:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2143 - F1: 0.2227
sub_12:Test (Best Model) - Loss: 1.6195 - Accuracy: 0.2048 - F1: 0.2027
sub_12:Test (Best Model) - Loss: 1.6119 - Accuracy: 0.1714 - F1: 0.1717
sub_12:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2095 - F1: 0.2061
sub_13:Test (Best Model) - Loss: 1.6020 - Accuracy: 0.2429 - F1: 0.2317
sub_13:Test (Best Model) - Loss: 1.6002 - Accuracy: 0.2714 - F1: 0.2411
sub_13:Test (Best Model) - Loss: 1.6018 - Accuracy: 0.2143 - F1: 0.2050
sub_13:Test (Best Model) - Loss: 1.5984 - Accuracy: 0.2810 - F1: 0.2665
sub_13:Test (Best Model) - Loss: 1.6030 - Accuracy: 0.2381 - F1: 0.2395
sub_13:Test (Best Model) - Loss: 1.6058 - Accuracy: 0.2381 - F1: 0.2222
sub_13:Test (Best Model) - Loss: 1.5985 - Accuracy: 0.2048 - F1: 0.1833
sub_13:Test (Best Model) - Loss: 1.6159 - Accuracy: 0.2095 - F1: 0.1861
sub_13:Test (Best Model) - Loss: 1.6001 - Accuracy: 0.2667 - F1: 0.2567
sub_13:Test (Best Model) - Loss: 1.6032 - Accuracy: 0.1762 - F1: 0.1715
sub_13:Test (Best Model) - Loss: 1.6062 - Accuracy: 0.1905 - F1: 0.1866
sub_13:Test (Best Model) - Loss: 1.6080 - Accuracy: 0.1905 - F1: 0.1772
sub_13:Test (Best Model) - Loss: 1.6122 - Accuracy: 0.1810 - F1: 0.1676
sub_13:Test (Best Model) - Loss: 1.6048 - Accuracy: 0.2524 - F1: 0.2410
sub_13:Test (Best Model) - Loss: 1.6143 - Accuracy: 0.2048 - F1: 0.1925
sub_14:Test (Best Model) - Loss: 1.6170 - Accuracy: 0.1810 - F1: 0.1618
sub_14:Test (Best Model) - Loss: 1.5983 - Accuracy: 0.2190 - F1: 0.2045
sub_14:Test (Best Model) - Loss: 1.5999 - Accuracy: 0.2286 - F1: 0.1991
sub_14:Test (Best Model) - Loss: 1.6048 - Accuracy: 0.2095 - F1: 0.1987
sub_14:Test (Best Model) - Loss: 1.6153 - Accuracy: 0.2143 - F1: 0.1805
sub_14:Test (Best Model) - Loss: 1.5890 - Accuracy: 0.2571 - F1: 0.2306
sub_14:Test (Best Model) - Loss: 1.5878 - Accuracy: 0.2381 - F1: 0.2139
sub_14:Test (Best Model) - Loss: 1.5841 - Accuracy: 0.2571 - F1: 0.2464
sub_14:Test (Best Model) - Loss: 1.5888 - Accuracy: 0.2762 - F1: 0.2613
sub_14:Test (Best Model) - Loss: 1.6031 - Accuracy: 0.1952 - F1: 0.1879
sub_14:Test (Best Model) - Loss: 1.5975 - Accuracy: 0.2381 - F1: 0.2306
sub_14:Test (Best Model) - Loss: 1.5937 - Accuracy: 0.2286 - F1: 0.2039
sub_14:Test (Best Model) - Loss: 1.6069 - Accuracy: 0.1952 - F1: 0.1600
sub_14:Test (Best Model) - Loss: 1.5956 - Accuracy: 0.2238 - F1: 0.2011
sub_14:Test (Best Model) - Loss: 1.6115 - Accuracy: 0.2143 - F1: 0.2060

=== Summary Results ===

acc: 23.19 ± 1.85
F1: 22.28 ± 1.97
acc-in: 26.84 ± 2.13
F1-in: 25.82 ± 2.14
