lr: 1e-06
sub_1:Test (Best Model) - Loss: 1.5627 - Accuracy: 0.2762 - F1: 0.2374
sub_1:Test (Best Model) - Loss: 1.5761 - Accuracy: 0.2952 - F1: 0.2728
sub_1:Test (Best Model) - Loss: 1.5642 - Accuracy: 0.3000 - F1: 0.2763
sub_1:Test (Best Model) - Loss: 1.5862 - Accuracy: 0.2714 - F1: 0.2568
sub_1:Test (Best Model) - Loss: 1.5856 - Accuracy: 0.2762 - F1: 0.2677
sub_1:Test (Best Model) - Loss: 1.5660 - Accuracy: 0.3000 - F1: 0.3037
sub_1:Test (Best Model) - Loss: 1.5775 - Accuracy: 0.2857 - F1: 0.2694
sub_1:Test (Best Model) - Loss: 1.5521 - Accuracy: 0.3190 - F1: 0.3119
sub_1:Test (Best Model) - Loss: 1.5481 - Accuracy: 0.2905 - F1: 0.3039
sub_1:Test (Best Model) - Loss: 1.5854 - Accuracy: 0.2238 - F1: 0.2364
sub_1:Test (Best Model) - Loss: 1.5437 - Accuracy: 0.3000 - F1: 0.3023
sub_1:Test (Best Model) - Loss: 1.5559 - Accuracy: 0.2952 - F1: 0.2754
sub_1:Test (Best Model) - Loss: 1.5779 - Accuracy: 0.2714 - F1: 0.2519
sub_1:Test (Best Model) - Loss: 1.5726 - Accuracy: 0.3000 - F1: 0.2900
sub_1:Test (Best Model) - Loss: 1.5527 - Accuracy: 0.2762 - F1: 0.2791
sub_2:Test (Best Model) - Loss: 1.5583 - Accuracy: 0.2571 - F1: 0.2199
sub_2:Test (Best Model) - Loss: 1.5638 - Accuracy: 0.2714 - F1: 0.2373
sub_2:Test (Best Model) - Loss: 1.5857 - Accuracy: 0.2381 - F1: 0.2203
sub_2:Test (Best Model) - Loss: 1.5666 - Accuracy: 0.2286 - F1: 0.2004
sub_2:Test (Best Model) - Loss: 1.5866 - Accuracy: 0.2238 - F1: 0.1875
sub_2:Test (Best Model) - Loss: 1.5799 - Accuracy: 0.2238 - F1: 0.1928
sub_2:Test (Best Model) - Loss: 1.5780 - Accuracy: 0.2333 - F1: 0.2226
sub_2:Test (Best Model) - Loss: 1.5865 - Accuracy: 0.2429 - F1: 0.2190
sub_2:Test (Best Model) - Loss: 1.5585 - Accuracy: 0.2810 - F1: 0.2610
sub_2:Test (Best Model) - Loss: 1.5796 - Accuracy: 0.2476 - F1: 0.2298
sub_2:Test (Best Model) - Loss: 1.5701 - Accuracy: 0.2524 - F1: 0.2492
sub_2:Test (Best Model) - Loss: 1.5767 - Accuracy: 0.2333 - F1: 0.2296
sub_2:Test (Best Model) - Loss: 1.5767 - Accuracy: 0.2143 - F1: 0.1904
sub_2:Test (Best Model) - Loss: 1.5851 - Accuracy: 0.2095 - F1: 0.1933
sub_2:Test (Best Model) - Loss: 1.5825 - Accuracy: 0.2333 - F1: 0.2299
sub_3:Test (Best Model) - Loss: 1.5815 - Accuracy: 0.2524 - F1: 0.1937
sub_3:Test (Best Model) - Loss: 1.6049 - Accuracy: 0.2381 - F1: 0.1944
sub_3:Test (Best Model) - Loss: 1.5933 - Accuracy: 0.3190 - F1: 0.3051
sub_3:Test (Best Model) - Loss: 1.6017 - Accuracy: 0.2286 - F1: 0.1761
sub_3:Test (Best Model) - Loss: 1.5974 - Accuracy: 0.2857 - F1: 0.2184
sub_3:Test (Best Model) - Loss: 1.5687 - Accuracy: 0.2952 - F1: 0.2713
sub_3:Test (Best Model) - Loss: 1.5841 - Accuracy: 0.2667 - F1: 0.2579
sub_3:Test (Best Model) - Loss: 1.5879 - Accuracy: 0.2714 - F1: 0.2529
sub_3:Test (Best Model) - Loss: 1.5918 - Accuracy: 0.2714 - F1: 0.2457
sub_3:Test (Best Model) - Loss: 1.5696 - Accuracy: 0.2762 - F1: 0.2612
sub_3:Test (Best Model) - Loss: 1.5767 - Accuracy: 0.3000 - F1: 0.3073
sub_3:Test (Best Model) - Loss: 1.5657 - Accuracy: 0.3095 - F1: 0.3101
sub_3:Test (Best Model) - Loss: 1.5970 - Accuracy: 0.2714 - F1: 0.2767
sub_3:Test (Best Model) - Loss: 1.5761 - Accuracy: 0.2857 - F1: 0.2843
sub_3:Test (Best Model) - Loss: 1.5678 - Accuracy: 0.2857 - F1: 0.2951
sub_4:Test (Best Model) - Loss: 1.6058 - Accuracy: 0.2095 - F1: 0.2023
sub_4:Test (Best Model) - Loss: 1.6074 - Accuracy: 0.1810 - F1: 0.1678
sub_4:Test (Best Model) - Loss: 1.6109 - Accuracy: 0.2286 - F1: 0.2183
sub_4:Test (Best Model) - Loss: 1.6067 - Accuracy: 0.1857 - F1: 0.1723
sub_4:Test (Best Model) - Loss: 1.6049 - Accuracy: 0.1762 - F1: 0.1464
sub_4:Test (Best Model) - Loss: 1.5946 - Accuracy: 0.2571 - F1: 0.2495
sub_4:Test (Best Model) - Loss: 1.5965 - Accuracy: 0.2810 - F1: 0.2699
sub_4:Test (Best Model) - Loss: 1.5934 - Accuracy: 0.2238 - F1: 0.2149
sub_4:Test (Best Model) - Loss: 1.5968 - Accuracy: 0.2524 - F1: 0.2524
sub_4:Test (Best Model) - Loss: 1.5926 - Accuracy: 0.2714 - F1: 0.2684
sub_4:Test (Best Model) - Loss: 1.6025 - Accuracy: 0.2238 - F1: 0.2150
sub_4:Test (Best Model) - Loss: 1.5976 - Accuracy: 0.2571 - F1: 0.2433
sub_4:Test (Best Model) - Loss: 1.5989 - Accuracy: 0.1952 - F1: 0.1483
sub_4:Test (Best Model) - Loss: 1.5991 - Accuracy: 0.2524 - F1: 0.2349
sub_4:Test (Best Model) - Loss: 1.6012 - Accuracy: 0.1952 - F1: 0.1864
sub_5:Test (Best Model) - Loss: 1.5984 - Accuracy: 0.2238 - F1: 0.2244
sub_5:Test (Best Model) - Loss: 1.5944 - Accuracy: 0.2095 - F1: 0.1851
sub_5:Test (Best Model) - Loss: 1.5671 - Accuracy: 0.2762 - F1: 0.2591
sub_5:Test (Best Model) - Loss: 1.5826 - Accuracy: 0.2286 - F1: 0.2286
sub_5:Test (Best Model) - Loss: 1.5904 - Accuracy: 0.2095 - F1: 0.1858
sub_5:Test (Best Model) - Loss: 1.5781 - Accuracy: 0.2857 - F1: 0.2682
sub_5:Test (Best Model) - Loss: 1.5935 - Accuracy: 0.2667 - F1: 0.2299
sub_5:Test (Best Model) - Loss: 1.5930 - Accuracy: 0.2476 - F1: 0.2047
sub_5:Test (Best Model) - Loss: 1.5681 - Accuracy: 0.2810 - F1: 0.2554
sub_5:Test (Best Model) - Loss: 1.5945 - Accuracy: 0.2429 - F1: 0.2121
sub_5:Test (Best Model) - Loss: 1.5705 - Accuracy: 0.2952 - F1: 0.2910
sub_5:Test (Best Model) - Loss: 1.5846 - Accuracy: 0.2333 - F1: 0.2143
sub_5:Test (Best Model) - Loss: 1.5822 - Accuracy: 0.2476 - F1: 0.2285
sub_5:Test (Best Model) - Loss: 1.5902 - Accuracy: 0.2429 - F1: 0.2313
sub_5:Test (Best Model) - Loss: 1.5831 - Accuracy: 0.2381 - F1: 0.2329
sub_6:Test (Best Model) - Loss: 1.5959 - Accuracy: 0.2714 - F1: 0.2687
sub_6:Test (Best Model) - Loss: 1.6088 - Accuracy: 0.1762 - F1: 0.1653
sub_6:Test (Best Model) - Loss: 1.6224 - Accuracy: 0.1619 - F1: 0.1528
sub_6:Test (Best Model) - Loss: 1.6128 - Accuracy: 0.1952 - F1: 0.1922
sub_6:Test (Best Model) - Loss: 1.6027 - Accuracy: 0.2333 - F1: 0.2244
sub_6:Test (Best Model) - Loss: 1.6188 - Accuracy: 0.2048 - F1: 0.2023
sub_6:Test (Best Model) - Loss: 1.6156 - Accuracy: 0.2524 - F1: 0.2493
sub_6:Test (Best Model) - Loss: 1.6205 - Accuracy: 0.2048 - F1: 0.1838
sub_6:Test (Best Model) - Loss: 1.6136 - Accuracy: 0.2238 - F1: 0.2203
sub_6:Test (Best Model) - Loss: 1.6017 - Accuracy: 0.2571 - F1: 0.2570
sub_6:Test (Best Model) - Loss: 1.6143 - Accuracy: 0.2429 - F1: 0.2457
sub_6:Test (Best Model) - Loss: 1.6137 - Accuracy: 0.2143 - F1: 0.2132
sub_6:Test (Best Model) - Loss: 1.6109 - Accuracy: 0.1857 - F1: 0.1734
sub_6:Test (Best Model) - Loss: 1.6246 - Accuracy: 0.1952 - F1: 0.1920
sub_6:Test (Best Model) - Loss: 1.6109 - Accuracy: 0.2571 - F1: 0.2486
sub_7:Test (Best Model) - Loss: 1.6234 - Accuracy: 0.2095 - F1: 0.1982
sub_7:Test (Best Model) - Loss: 1.6259 - Accuracy: 0.2048 - F1: 0.1985
sub_7:Test (Best Model) - Loss: 1.6293 - Accuracy: 0.2429 - F1: 0.2371
sub_7:Test (Best Model) - Loss: 1.6262 - Accuracy: 0.2095 - F1: 0.2051
sub_7:Test (Best Model) - Loss: 1.6136 - Accuracy: 0.1952 - F1: 0.1806
sub_7:Test (Best Model) - Loss: 1.6168 - Accuracy: 0.2286 - F1: 0.2097
sub_7:Test (Best Model) - Loss: 1.6069 - Accuracy: 0.2286 - F1: 0.2177
sub_7:Test (Best Model) - Loss: 1.6040 - Accuracy: 0.2333 - F1: 0.2119
sub_7:Test (Best Model) - Loss: 1.6140 - Accuracy: 0.1762 - F1: 0.1705
sub_7:Test (Best Model) - Loss: 1.6190 - Accuracy: 0.1381 - F1: 0.1284
sub_7:Test (Best Model) - Loss: 1.5995 - Accuracy: 0.2048 - F1: 0.1851
sub_7:Test (Best Model) - Loss: 1.6018 - Accuracy: 0.2381 - F1: 0.2310
sub_7:Test (Best Model) - Loss: 1.6142 - Accuracy: 0.2048 - F1: 0.1980
sub_7:Test (Best Model) - Loss: 1.6058 - Accuracy: 0.2143 - F1: 0.2009
sub_7:Test (Best Model) - Loss: 1.6045 - Accuracy: 0.2286 - F1: 0.2081
sub_8:Test (Best Model) - Loss: 1.5359 - Accuracy: 0.3286 - F1: 0.3351
sub_8:Test (Best Model) - Loss: 1.5585 - Accuracy: 0.2714 - F1: 0.2732
sub_8:Test (Best Model) - Loss: 1.5337 - Accuracy: 0.2619 - F1: 0.2702
sub_8:Test (Best Model) - Loss: 1.5546 - Accuracy: 0.3238 - F1: 0.3282
sub_8:Test (Best Model) - Loss: 1.5423 - Accuracy: 0.3048 - F1: 0.3134
sub_8:Test (Best Model) - Loss: 1.5629 - Accuracy: 0.2381 - F1: 0.2504
sub_8:Test (Best Model) - Loss: 1.5563 - Accuracy: 0.2762 - F1: 0.2822
sub_8:Test (Best Model) - Loss: 1.5270 - Accuracy: 0.3000 - F1: 0.3084
sub_8:Test (Best Model) - Loss: 1.5619 - Accuracy: 0.2524 - F1: 0.2606
sub_8:Test (Best Model) - Loss: 1.5534 - Accuracy: 0.2619 - F1: 0.2749
sub_8:Test (Best Model) - Loss: 1.5706 - Accuracy: 0.2286 - F1: 0.2296
sub_8:Test (Best Model) - Loss: 1.5692 - Accuracy: 0.2238 - F1: 0.2341
sub_8:Test (Best Model) - Loss: 1.5776 - Accuracy: 0.1905 - F1: 0.1639
sub_8:Test (Best Model) - Loss: 1.5754 - Accuracy: 0.2095 - F1: 0.1953
sub_8:Test (Best Model) - Loss: 1.5882 - Accuracy: 0.2000 - F1: 0.1819
sub_9:Test (Best Model) - Loss: 1.5951 - Accuracy: 0.2429 - F1: 0.2438
sub_9:Test (Best Model) - Loss: 1.5995 - Accuracy: 0.2286 - F1: 0.2224
sub_9:Test (Best Model) - Loss: 1.5755 - Accuracy: 0.2905 - F1: 0.2819
sub_9:Test (Best Model) - Loss: 1.5828 - Accuracy: 0.2619 - F1: 0.2528
sub_9:Test (Best Model) - Loss: 1.5871 - Accuracy: 0.2762 - F1: 0.2804
sub_9:Test (Best Model) - Loss: 1.6026 - Accuracy: 0.1905 - F1: 0.1862
sub_9:Test (Best Model) - Loss: 1.6079 - Accuracy: 0.2000 - F1: 0.2061
sub_9:Test (Best Model) - Loss: 1.6070 - Accuracy: 0.2286 - F1: 0.2236
sub_9:Test (Best Model) - Loss: 1.6199 - Accuracy: 0.2381 - F1: 0.2377
sub_9:Test (Best Model) - Loss: 1.6038 - Accuracy: 0.2048 - F1: 0.1991
sub_9:Test (Best Model) - Loss: 1.6083 - Accuracy: 0.1905 - F1: 0.1810
sub_9:Test (Best Model) - Loss: 1.5855 - Accuracy: 0.2238 - F1: 0.2245
sub_9:Test (Best Model) - Loss: 1.6028 - Accuracy: 0.2476 - F1: 0.2377
sub_9:Test (Best Model) - Loss: 1.6011 - Accuracy: 0.2381 - F1: 0.2311
sub_9:Test (Best Model) - Loss: 1.5940 - Accuracy: 0.2524 - F1: 0.2418
sub_10:Test (Best Model) - Loss: 1.6211 - Accuracy: 0.2476 - F1: 0.2320
sub_10:Test (Best Model) - Loss: 1.6050 - Accuracy: 0.2429 - F1: 0.2355
sub_10:Test (Best Model) - Loss: 1.6117 - Accuracy: 0.2762 - F1: 0.2748
sub_10:Test (Best Model) - Loss: 1.6110 - Accuracy: 0.2143 - F1: 0.2095
sub_10:Test (Best Model) - Loss: 1.6224 - Accuracy: 0.2143 - F1: 0.2086
sub_10:Test (Best Model) - Loss: 1.6112 - Accuracy: 0.2143 - F1: 0.2073
sub_10:Test (Best Model) - Loss: 1.6045 - Accuracy: 0.2381 - F1: 0.2355
sub_10:Test (Best Model) - Loss: 1.6087 - Accuracy: 0.2190 - F1: 0.2062
sub_10:Test (Best Model) - Loss: 1.6071 - Accuracy: 0.2048 - F1: 0.1976
sub_10:Test (Best Model) - Loss: 1.5936 - Accuracy: 0.2286 - F1: 0.2224
sub_10:Test (Best Model) - Loss: 1.6267 - Accuracy: 0.1905 - F1: 0.1910
sub_10:Test (Best Model) - Loss: 1.6064 - Accuracy: 0.2429 - F1: 0.2320
sub_10:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2476 - F1: 0.2429
sub_10:Test (Best Model) - Loss: 1.6127 - Accuracy: 0.1810 - F1: 0.1749
sub_10:Test (Best Model) - Loss: 1.6145 - Accuracy: 0.1952 - F1: 0.1909
sub_11:Test (Best Model) - Loss: 1.6116 - Accuracy: 0.2238 - F1: 0.2103
sub_11:Test (Best Model) - Loss: 1.6186 - Accuracy: 0.1714 - F1: 0.1661
sub_11:Test (Best Model) - Loss: 1.6217 - Accuracy: 0.1905 - F1: 0.1785
sub_11:Test (Best Model) - Loss: 1.6249 - Accuracy: 0.1762 - F1: 0.1573
sub_11:Test (Best Model) - Loss: 1.6086 - Accuracy: 0.2143 - F1: 0.1941
sub_11:Test (Best Model) - Loss: 1.5951 - Accuracy: 0.2571 - F1: 0.2486
sub_11:Test (Best Model) - Loss: 1.6005 - Accuracy: 0.1952 - F1: 0.1786
sub_11:Test (Best Model) - Loss: 1.5948 - Accuracy: 0.2429 - F1: 0.2194
sub_11:Test (Best Model) - Loss: 1.5985 - Accuracy: 0.2476 - F1: 0.2131
sub_11:Test (Best Model) - Loss: 1.5965 - Accuracy: 0.2714 - F1: 0.2629
sub_11:Test (Best Model) - Loss: 1.6112 - Accuracy: 0.2286 - F1: 0.2256
sub_11:Test (Best Model) - Loss: 1.6077 - Accuracy: 0.2000 - F1: 0.1717
sub_11:Test (Best Model) - Loss: 1.6306 - Accuracy: 0.2286 - F1: 0.1902
sub_11:Test (Best Model) - Loss: 1.6204 - Accuracy: 0.1952 - F1: 0.1820
sub_11:Test (Best Model) - Loss: 1.6140 - Accuracy: 0.2238 - F1: 0.2188
sub_12:Test (Best Model) - Loss: 1.5809 - Accuracy: 0.3000 - F1: 0.2980
sub_12:Test (Best Model) - Loss: 1.5968 - Accuracy: 0.2238 - F1: 0.2269
sub_12:Test (Best Model) - Loss: 1.5933 - Accuracy: 0.2476 - F1: 0.2477
sub_12:Test (Best Model) - Loss: 1.5792 - Accuracy: 0.2905 - F1: 0.2914
sub_12:Test (Best Model) - Loss: 1.6013 - Accuracy: 0.2476 - F1: 0.2429
sub_12:Test (Best Model) - Loss: 1.5985 - Accuracy: 0.2333 - F1: 0.2344
sub_12:Test (Best Model) - Loss: 1.5837 - Accuracy: 0.2524 - F1: 0.2493
sub_12:Test (Best Model) - Loss: 1.6031 - Accuracy: 0.2286 - F1: 0.2216
sub_12:Test (Best Model) - Loss: 1.5891 - Accuracy: 0.2952 - F1: 0.2876
sub_12:Test (Best Model) - Loss: 1.5947 - Accuracy: 0.2048 - F1: 0.2035
sub_12:Test (Best Model) - Loss: 1.5992 - Accuracy: 0.2143 - F1: 0.2220
sub_12:Test (Best Model) - Loss: 1.6115 - Accuracy: 0.2238 - F1: 0.2322
sub_12:Test (Best Model) - Loss: 1.6141 - Accuracy: 0.2048 - F1: 0.2068
sub_12:Test (Best Model) - Loss: 1.6144 - Accuracy: 0.2381 - F1: 0.2435
sub_12:Test (Best Model) - Loss: 1.6088 - Accuracy: 0.2619 - F1: 0.2656
sub_13:Test (Best Model) - Loss: 1.6019 - Accuracy: 0.2190 - F1: 0.2059
sub_13:Test (Best Model) - Loss: 1.5989 - Accuracy: 0.2762 - F1: 0.2590
sub_13:Test (Best Model) - Loss: 1.6008 - Accuracy: 0.2429 - F1: 0.2373
sub_13:Test (Best Model) - Loss: 1.5975 - Accuracy: 0.2762 - F1: 0.2595
sub_13:Test (Best Model) - Loss: 1.6000 - Accuracy: 0.2381 - F1: 0.2166
sub_13:Test (Best Model) - Loss: 1.6086 - Accuracy: 0.2286 - F1: 0.2198
sub_13:Test (Best Model) - Loss: 1.5902 - Accuracy: 0.1905 - F1: 0.1865
sub_13:Test (Best Model) - Loss: 1.6039 - Accuracy: 0.2381 - F1: 0.2296
sub_13:Test (Best Model) - Loss: 1.6001 - Accuracy: 0.2333 - F1: 0.2286
sub_13:Test (Best Model) - Loss: 1.6019 - Accuracy: 0.2286 - F1: 0.2285
sub_13:Test (Best Model) - Loss: 1.5922 - Accuracy: 0.2571 - F1: 0.2538
sub_13:Test (Best Model) - Loss: 1.5964 - Accuracy: 0.2333 - F1: 0.2067
sub_13:Test (Best Model) - Loss: 1.6044 - Accuracy: 0.2381 - F1: 0.2308
sub_13:Test (Best Model) - Loss: 1.6054 - Accuracy: 0.2190 - F1: 0.2215
sub_13:Test (Best Model) - Loss: 1.6031 - Accuracy: 0.2524 - F1: 0.2503
sub_14:Test (Best Model) - Loss: 1.6031 - Accuracy: 0.2238 - F1: 0.2086
sub_14:Test (Best Model) - Loss: 1.5900 - Accuracy: 0.2333 - F1: 0.2100
sub_14:Test (Best Model) - Loss: 1.6042 - Accuracy: 0.2190 - F1: 0.1938
sub_14:Test (Best Model) - Loss: 1.5986 - Accuracy: 0.2524 - F1: 0.2443
sub_14:Test (Best Model) - Loss: 1.6014 - Accuracy: 0.2476 - F1: 0.2243
sub_14:Test (Best Model) - Loss: 1.5681 - Accuracy: 0.2571 - F1: 0.2211
sub_14:Test (Best Model) - Loss: 1.5679 - Accuracy: 0.2667 - F1: 0.2321
sub_14:Test (Best Model) - Loss: 1.5865 - Accuracy: 0.2429 - F1: 0.1968
sub_14:Test (Best Model) - Loss: 1.5804 - Accuracy: 0.2714 - F1: 0.2507
sub_14:Test (Best Model) - Loss: 1.5912 - Accuracy: 0.2048 - F1: 0.1890
sub_14:Test (Best Model) - Loss: 1.5950 - Accuracy: 0.2238 - F1: 0.2094
sub_14:Test (Best Model) - Loss: 1.5966 - Accuracy: 0.2381 - F1: 0.2129
sub_14:Test (Best Model) - Loss: 1.5986 - Accuracy: 0.2190 - F1: 0.1708
sub_14:Test (Best Model) - Loss: 1.5906 - Accuracy: 0.2238 - F1: 0.1780
sub_14:Test (Best Model) - Loss: 1.5995 - Accuracy: 0.2476 - F1: 0.2170

=== Summary Results ===

acc: 24.00 ± 2.10
F1: 22.85 ± 2.23
acc-in: 26.81 ± 2.05
F1-in: 25.56 ± 2.25
