lr: 1e-06
sub_1:Test (Best Model) - Loss: 1.5711 - Accuracy: 0.2571 - F1: 0.2272
sub_1:Test (Best Model) - Loss: 1.5686 - Accuracy: 0.2952 - F1: 0.2644
sub_1:Test (Best Model) - Loss: 1.5906 - Accuracy: 0.2667 - F1: 0.2520
sub_1:Test (Best Model) - Loss: 1.5692 - Accuracy: 0.2714 - F1: 0.2590
sub_1:Test (Best Model) - Loss: 1.5733 - Accuracy: 0.2714 - F1: 0.2513
sub_1:Test (Best Model) - Loss: 1.5602 - Accuracy: 0.3190 - F1: 0.3258
sub_1:Test (Best Model) - Loss: 1.5619 - Accuracy: 0.2571 - F1: 0.2618
sub_1:Test (Best Model) - Loss: 1.4896 - Accuracy: 0.3571 - F1: 0.3551
sub_1:Test (Best Model) - Loss: 1.5378 - Accuracy: 0.3286 - F1: 0.3442
sub_1:Test (Best Model) - Loss: 1.5059 - Accuracy: 0.3000 - F1: 0.3140
sub_1:Test (Best Model) - Loss: 1.5422 - Accuracy: 0.3048 - F1: 0.2980
sub_1:Test (Best Model) - Loss: 1.5536 - Accuracy: 0.2857 - F1: 0.2563
sub_1:Test (Best Model) - Loss: 1.5466 - Accuracy: 0.3143 - F1: 0.2995
sub_1:Test (Best Model) - Loss: 1.5420 - Accuracy: 0.2714 - F1: 0.2469
sub_1:Test (Best Model) - Loss: 1.5483 - Accuracy: 0.2810 - F1: 0.2840
sub_2:Test (Best Model) - Loss: 1.5574 - Accuracy: 0.2857 - F1: 0.2605
sub_2:Test (Best Model) - Loss: 1.5536 - Accuracy: 0.2238 - F1: 0.1719
sub_2:Test (Best Model) - Loss: 1.5787 - Accuracy: 0.2143 - F1: 0.1843
sub_2:Test (Best Model) - Loss: 1.5644 - Accuracy: 0.2667 - F1: 0.2528
sub_2:Test (Best Model) - Loss: 1.5615 - Accuracy: 0.2714 - F1: 0.2505
sub_2:Test (Best Model) - Loss: 1.5792 - Accuracy: 0.2095 - F1: 0.1719
sub_2:Test (Best Model) - Loss: 1.5847 - Accuracy: 0.2190 - F1: 0.1973
sub_2:Test (Best Model) - Loss: 1.5620 - Accuracy: 0.2524 - F1: 0.2384
sub_2:Test (Best Model) - Loss: 1.5554 - Accuracy: 0.2476 - F1: 0.2198
sub_2:Test (Best Model) - Loss: 1.5714 - Accuracy: 0.1952 - F1: 0.1794
sub_2:Test (Best Model) - Loss: 1.5715 - Accuracy: 0.1905 - F1: 0.1826
sub_2:Test (Best Model) - Loss: 1.5641 - Accuracy: 0.2476 - F1: 0.2395
sub_2:Test (Best Model) - Loss: 1.5618 - Accuracy: 0.2524 - F1: 0.2240
sub_2:Test (Best Model) - Loss: 1.5832 - Accuracy: 0.1857 - F1: 0.1745
sub_2:Test (Best Model) - Loss: 1.5680 - Accuracy: 0.2190 - F1: 0.2133
sub_3:Test (Best Model) - Loss: 1.5951 - Accuracy: 0.2571 - F1: 0.2121
sub_3:Test (Best Model) - Loss: 1.5919 - Accuracy: 0.2524 - F1: 0.2004
sub_3:Test (Best Model) - Loss: 1.5812 - Accuracy: 0.2952 - F1: 0.2448
sub_3:Test (Best Model) - Loss: 1.5819 - Accuracy: 0.2762 - F1: 0.2221
sub_3:Test (Best Model) - Loss: 1.5991 - Accuracy: 0.2476 - F1: 0.1994
sub_3:Test (Best Model) - Loss: 1.5727 - Accuracy: 0.3190 - F1: 0.3047
sub_3:Test (Best Model) - Loss: 1.5819 - Accuracy: 0.2762 - F1: 0.2575
sub_3:Test (Best Model) - Loss: 1.5823 - Accuracy: 0.2810 - F1: 0.2548
sub_3:Test (Best Model) - Loss: 1.5902 - Accuracy: 0.2286 - F1: 0.2162
sub_3:Test (Best Model) - Loss: 1.5628 - Accuracy: 0.2762 - F1: 0.2560
sub_3:Test (Best Model) - Loss: 1.5769 - Accuracy: 0.2810 - F1: 0.2875
sub_3:Test (Best Model) - Loss: 1.5829 - Accuracy: 0.2381 - F1: 0.2309
sub_3:Test (Best Model) - Loss: 1.5563 - Accuracy: 0.3095 - F1: 0.3142
sub_3:Test (Best Model) - Loss: 1.5620 - Accuracy: 0.2905 - F1: 0.3002
sub_3:Test (Best Model) - Loss: 1.5822 - Accuracy: 0.2762 - F1: 0.2796
sub_4:Test (Best Model) - Loss: 1.5959 - Accuracy: 0.1952 - F1: 0.1871
sub_4:Test (Best Model) - Loss: 1.5972 - Accuracy: 0.2048 - F1: 0.2004
sub_4:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2048 - F1: 0.1905
sub_4:Test (Best Model) - Loss: 1.5905 - Accuracy: 0.2095 - F1: 0.1891
sub_4:Test (Best Model) - Loss: 1.5976 - Accuracy: 0.2429 - F1: 0.2121
sub_4:Test (Best Model) - Loss: 1.5839 - Accuracy: 0.2762 - F1: 0.2700
sub_4:Test (Best Model) - Loss: 1.5969 - Accuracy: 0.2333 - F1: 0.2236
sub_4:Test (Best Model) - Loss: 1.5813 - Accuracy: 0.2524 - F1: 0.2462
sub_4:Test (Best Model) - Loss: 1.5719 - Accuracy: 0.2333 - F1: 0.2325
sub_4:Test (Best Model) - Loss: 1.5978 - Accuracy: 0.2619 - F1: 0.2664
sub_4:Test (Best Model) - Loss: 1.5940 - Accuracy: 0.2143 - F1: 0.2003
sub_4:Test (Best Model) - Loss: 1.6052 - Accuracy: 0.2238 - F1: 0.1864
sub_4:Test (Best Model) - Loss: 1.5955 - Accuracy: 0.2190 - F1: 0.1946
sub_4:Test (Best Model) - Loss: 1.5908 - Accuracy: 0.2286 - F1: 0.2087
sub_4:Test (Best Model) - Loss: 1.5906 - Accuracy: 0.2333 - F1: 0.2161
sub_5:Test (Best Model) - Loss: 1.5923 - Accuracy: 0.2381 - F1: 0.2352
sub_5:Test (Best Model) - Loss: 1.5867 - Accuracy: 0.2143 - F1: 0.1795
sub_5:Test (Best Model) - Loss: 1.5932 - Accuracy: 0.2381 - F1: 0.2146
sub_5:Test (Best Model) - Loss: 1.5767 - Accuracy: 0.2667 - F1: 0.2499
sub_5:Test (Best Model) - Loss: 1.5913 - Accuracy: 0.2095 - F1: 0.2102
sub_5:Test (Best Model) - Loss: 1.5809 - Accuracy: 0.2714 - F1: 0.2553
sub_5:Test (Best Model) - Loss: 1.5783 - Accuracy: 0.2619 - F1: 0.2305
sub_5:Test (Best Model) - Loss: 1.5756 - Accuracy: 0.2714 - F1: 0.2511
sub_5:Test (Best Model) - Loss: 1.5732 - Accuracy: 0.2571 - F1: 0.2295
sub_5:Test (Best Model) - Loss: 1.5815 - Accuracy: 0.2571 - F1: 0.2261
sub_5:Test (Best Model) - Loss: 1.5795 - Accuracy: 0.2667 - F1: 0.2417
sub_5:Test (Best Model) - Loss: 1.5793 - Accuracy: 0.2619 - F1: 0.2518
sub_5:Test (Best Model) - Loss: 1.5797 - Accuracy: 0.2381 - F1: 0.2249
sub_5:Test (Best Model) - Loss: 1.5847 - Accuracy: 0.2381 - F1: 0.2240
sub_5:Test (Best Model) - Loss: 1.5907 - Accuracy: 0.2381 - F1: 0.2321
sub_6:Test (Best Model) - Loss: 1.6071 - Accuracy: 0.2190 - F1: 0.2185
sub_6:Test (Best Model) - Loss: 1.6077 - Accuracy: 0.2381 - F1: 0.2318
sub_6:Test (Best Model) - Loss: 1.6225 - Accuracy: 0.2000 - F1: 0.1947
sub_6:Test (Best Model) - Loss: 1.6120 - Accuracy: 0.2143 - F1: 0.2017
sub_6:Test (Best Model) - Loss: 1.6022 - Accuracy: 0.2238 - F1: 0.2219
sub_6:Test (Best Model) - Loss: 1.6312 - Accuracy: 0.2000 - F1: 0.1979
sub_6:Test (Best Model) - Loss: 1.6086 - Accuracy: 0.2238 - F1: 0.2210
sub_6:Test (Best Model) - Loss: 1.6124 - Accuracy: 0.2238 - F1: 0.2172
sub_6:Test (Best Model) - Loss: 1.6087 - Accuracy: 0.1952 - F1: 0.1919
sub_6:Test (Best Model) - Loss: 1.5946 - Accuracy: 0.2667 - F1: 0.2653
sub_6:Test (Best Model) - Loss: 1.6239 - Accuracy: 0.2333 - F1: 0.2312
sub_6:Test (Best Model) - Loss: 1.6185 - Accuracy: 0.1952 - F1: 0.1900
sub_6:Test (Best Model) - Loss: 1.6107 - Accuracy: 0.2810 - F1: 0.2758
sub_6:Test (Best Model) - Loss: 1.6264 - Accuracy: 0.1952 - F1: 0.1938
sub_6:Test (Best Model) - Loss: 1.6192 - Accuracy: 0.1952 - F1: 0.1846
sub_7:Test (Best Model) - Loss: 1.6354 - Accuracy: 0.2190 - F1: 0.2141
sub_7:Test (Best Model) - Loss: 1.6139 - Accuracy: 0.1857 - F1: 0.1739
sub_7:Test (Best Model) - Loss: 1.6228 - Accuracy: 0.2333 - F1: 0.2279
sub_7:Test (Best Model) - Loss: 1.6138 - Accuracy: 0.2286 - F1: 0.2146
sub_7:Test (Best Model) - Loss: 1.6159 - Accuracy: 0.1905 - F1: 0.1852
sub_7:Test (Best Model) - Loss: 1.6135 - Accuracy: 0.2429 - F1: 0.2234
sub_7:Test (Best Model) - Loss: 1.5980 - Accuracy: 0.2190 - F1: 0.2023
sub_7:Test (Best Model) - Loss: 1.6116 - Accuracy: 0.1810 - F1: 0.1776
sub_7:Test (Best Model) - Loss: 1.6282 - Accuracy: 0.1619 - F1: 0.1541
sub_7:Test (Best Model) - Loss: 1.6193 - Accuracy: 0.1810 - F1: 0.1736
sub_7:Test (Best Model) - Loss: 1.6070 - Accuracy: 0.2238 - F1: 0.1984
sub_7:Test (Best Model) - Loss: 1.6076 - Accuracy: 0.2095 - F1: 0.2113
sub_7:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2095 - F1: 0.2069
sub_7:Test (Best Model) - Loss: 1.6087 - Accuracy: 0.2286 - F1: 0.2206
sub_7:Test (Best Model) - Loss: 1.5901 - Accuracy: 0.2476 - F1: 0.2188
sub_8:Test (Best Model) - Loss: 1.5366 - Accuracy: 0.2857 - F1: 0.2936
sub_8:Test (Best Model) - Loss: 1.5550 - Accuracy: 0.2810 - F1: 0.2897
sub_8:Test (Best Model) - Loss: 1.5500 - Accuracy: 0.2857 - F1: 0.2991
sub_8:Test (Best Model) - Loss: 1.5511 - Accuracy: 0.2857 - F1: 0.2976
sub_8:Test (Best Model) - Loss: 1.5369 - Accuracy: 0.3095 - F1: 0.3080
sub_8:Test (Best Model) - Loss: 1.5351 - Accuracy: 0.2810 - F1: 0.2972
sub_8:Test (Best Model) - Loss: 1.5459 - Accuracy: 0.2952 - F1: 0.3078
sub_8:Test (Best Model) - Loss: 1.5500 - Accuracy: 0.2667 - F1: 0.2752
sub_8:Test (Best Model) - Loss: 1.5385 - Accuracy: 0.2619 - F1: 0.2679
sub_8:Test (Best Model) - Loss: 1.5199 - Accuracy: 0.3238 - F1: 0.3402
sub_8:Test (Best Model) - Loss: 1.5800 - Accuracy: 0.2048 - F1: 0.2049
sub_8:Test (Best Model) - Loss: 1.5613 - Accuracy: 0.2143 - F1: 0.2222
sub_8:Test (Best Model) - Loss: 1.5608 - Accuracy: 0.2190 - F1: 0.2060
sub_8:Test (Best Model) - Loss: 1.5704 - Accuracy: 0.2190 - F1: 0.2133
sub_8:Test (Best Model) - Loss: 1.5824 - Accuracy: 0.2143 - F1: 0.2061
sub_9:Test (Best Model) - Loss: 1.5778 - Accuracy: 0.2667 - F1: 0.2651
sub_9:Test (Best Model) - Loss: 1.5910 - Accuracy: 0.2619 - F1: 0.2488
sub_9:Test (Best Model) - Loss: 1.5698 - Accuracy: 0.2952 - F1: 0.2782
sub_9:Test (Best Model) - Loss: 1.5913 - Accuracy: 0.2048 - F1: 0.1939
sub_9:Test (Best Model) - Loss: 1.5902 - Accuracy: 0.2381 - F1: 0.2291
sub_9:Test (Best Model) - Loss: 1.6002 - Accuracy: 0.2190 - F1: 0.2080
sub_9:Test (Best Model) - Loss: 1.6005 - Accuracy: 0.2000 - F1: 0.2018
sub_9:Test (Best Model) - Loss: 1.5967 - Accuracy: 0.2476 - F1: 0.2439
sub_9:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2095 - F1: 0.2051
sub_9:Test (Best Model) - Loss: 1.6022 - Accuracy: 0.2286 - F1: 0.2234
sub_9:Test (Best Model) - Loss: 1.6300 - Accuracy: 0.1905 - F1: 0.1847
sub_9:Test (Best Model) - Loss: 1.5903 - Accuracy: 0.2524 - F1: 0.2488
sub_9:Test (Best Model) - Loss: 1.5920 - Accuracy: 0.2429 - F1: 0.2407
sub_9:Test (Best Model) - Loss: 1.5996 - Accuracy: 0.2238 - F1: 0.2255
sub_9:Test (Best Model) - Loss: 1.5960 - Accuracy: 0.2810 - F1: 0.2703
sub_10:Test (Best Model) - Loss: 1.6281 - Accuracy: 0.2238 - F1: 0.2164
sub_10:Test (Best Model) - Loss: 1.6137 - Accuracy: 0.2476 - F1: 0.2487
sub_10:Test (Best Model) - Loss: 1.6286 - Accuracy: 0.2571 - F1: 0.2585
sub_10:Test (Best Model) - Loss: 1.6133 - Accuracy: 0.2238 - F1: 0.2268
sub_10:Test (Best Model) - Loss: 1.6113 - Accuracy: 0.2714 - F1: 0.2723
sub_10:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2190 - F1: 0.2174
sub_10:Test (Best Model) - Loss: 1.6085 - Accuracy: 0.2476 - F1: 0.2313
sub_10:Test (Best Model) - Loss: 1.6074 - Accuracy: 0.1905 - F1: 0.1896
sub_10:Test (Best Model) - Loss: 1.5913 - Accuracy: 0.2571 - F1: 0.2499
sub_10:Test (Best Model) - Loss: 1.6042 - Accuracy: 0.2571 - F1: 0.2585
sub_10:Test (Best Model) - Loss: 1.6300 - Accuracy: 0.1667 - F1: 0.1640
sub_10:Test (Best Model) - Loss: 1.6051 - Accuracy: 0.2381 - F1: 0.2368
sub_10:Test (Best Model) - Loss: 1.5984 - Accuracy: 0.2571 - F1: 0.2592
sub_10:Test (Best Model) - Loss: 1.6213 - Accuracy: 0.2524 - F1: 0.2510
sub_10:Test (Best Model) - Loss: 1.6228 - Accuracy: 0.2000 - F1: 0.1988
sub_11:Test (Best Model) - Loss: 1.6054 - Accuracy: 0.1952 - F1: 0.1876
sub_11:Test (Best Model) - Loss: 1.6365 - Accuracy: 0.1762 - F1: 0.1673
sub_11:Test (Best Model) - Loss: 1.6213 - Accuracy: 0.2095 - F1: 0.1847
sub_11:Test (Best Model) - Loss: 1.6114 - Accuracy: 0.1857 - F1: 0.1716
sub_11:Test (Best Model) - Loss: 1.5915 - Accuracy: 0.2238 - F1: 0.2014
sub_11:Test (Best Model) - Loss: 1.5940 - Accuracy: 0.2238 - F1: 0.2160
sub_11:Test (Best Model) - Loss: 1.5960 - Accuracy: 0.2238 - F1: 0.2156
sub_11:Test (Best Model) - Loss: 1.6033 - Accuracy: 0.2095 - F1: 0.1924
sub_11:Test (Best Model) - Loss: 1.5828 - Accuracy: 0.2333 - F1: 0.2291
sub_11:Test (Best Model) - Loss: 1.6090 - Accuracy: 0.2619 - F1: 0.2516
sub_11:Test (Best Model) - Loss: 1.6127 - Accuracy: 0.2190 - F1: 0.2094
sub_11:Test (Best Model) - Loss: 1.6000 - Accuracy: 0.2190 - F1: 0.2065
sub_11:Test (Best Model) - Loss: 1.6203 - Accuracy: 0.2476 - F1: 0.2439
sub_11:Test (Best Model) - Loss: 1.6177 - Accuracy: 0.1952 - F1: 0.1852
sub_11:Test (Best Model) - Loss: 1.6120 - Accuracy: 0.2429 - F1: 0.2485
sub_12:Test (Best Model) - Loss: 1.5762 - Accuracy: 0.2667 - F1: 0.2589
sub_12:Test (Best Model) - Loss: 1.5837 - Accuracy: 0.2476 - F1: 0.2515
sub_12:Test (Best Model) - Loss: 1.5830 - Accuracy: 0.2429 - F1: 0.2479
sub_12:Test (Best Model) - Loss: 1.5644 - Accuracy: 0.3333 - F1: 0.3362
sub_12:Test (Best Model) - Loss: 1.5694 - Accuracy: 0.2571 - F1: 0.2683
sub_12:Test (Best Model) - Loss: 1.5800 - Accuracy: 0.3048 - F1: 0.2885
sub_12:Test (Best Model) - Loss: 1.5969 - Accuracy: 0.2381 - F1: 0.2430
sub_12:Test (Best Model) - Loss: 1.5986 - Accuracy: 0.2810 - F1: 0.2695
sub_12:Test (Best Model) - Loss: 1.5956 - Accuracy: 0.2381 - F1: 0.2378
sub_12:Test (Best Model) - Loss: 1.5548 - Accuracy: 0.3143 - F1: 0.2884
sub_12:Test (Best Model) - Loss: 1.6229 - Accuracy: 0.2000 - F1: 0.2016
sub_12:Test (Best Model) - Loss: 1.6159 - Accuracy: 0.2143 - F1: 0.2193
sub_12:Test (Best Model) - Loss: 1.5987 - Accuracy: 0.2524 - F1: 0.2602
sub_12:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2286 - F1: 0.2264
sub_12:Test (Best Model) - Loss: 1.6057 - Accuracy: 0.2476 - F1: 0.2555
sub_13:Test (Best Model) - Loss: 1.6003 - Accuracy: 0.2238 - F1: 0.2152
sub_13:Test (Best Model) - Loss: 1.6009 - Accuracy: 0.2429 - F1: 0.2320
sub_13:Test (Best Model) - Loss: 1.5966 - Accuracy: 0.2524 - F1: 0.2369
sub_13:Test (Best Model) - Loss: 1.6016 - Accuracy: 0.2524 - F1: 0.2305
sub_13:Test (Best Model) - Loss: 1.5866 - Accuracy: 0.2667 - F1: 0.2455
sub_13:Test (Best Model) - Loss: 1.5873 - Accuracy: 0.2810 - F1: 0.2755
sub_13:Test (Best Model) - Loss: 1.6017 - Accuracy: 0.2238 - F1: 0.2253
sub_13:Test (Best Model) - Loss: 1.5863 - Accuracy: 0.2571 - F1: 0.2401
sub_13:Test (Best Model) - Loss: 1.5828 - Accuracy: 0.2857 - F1: 0.2614
sub_13:Test (Best Model) - Loss: 1.6052 - Accuracy: 0.2048 - F1: 0.1996
sub_13:Test (Best Model) - Loss: 1.5891 - Accuracy: 0.2524 - F1: 0.2414
sub_13:Test (Best Model) - Loss: 1.5989 - Accuracy: 0.2238 - F1: 0.2055
sub_13:Test (Best Model) - Loss: 1.6013 - Accuracy: 0.2476 - F1: 0.2244
sub_13:Test (Best Model) - Loss: 1.6021 - Accuracy: 0.2190 - F1: 0.2044
sub_13:Test (Best Model) - Loss: 1.5928 - Accuracy: 0.2571 - F1: 0.2505
sub_14:Test (Best Model) - Loss: 1.5801 - Accuracy: 0.2857 - F1: 0.2679
sub_14:Test (Best Model) - Loss: 1.5716 - Accuracy: 0.2857 - F1: 0.2858
sub_14:Test (Best Model) - Loss: 1.5835 - Accuracy: 0.2571 - F1: 0.2306
sub_14:Test (Best Model) - Loss: 1.5747 - Accuracy: 0.2952 - F1: 0.2981
sub_14:Test (Best Model) - Loss: 1.5880 - Accuracy: 0.2619 - F1: 0.2435
sub_14:Test (Best Model) - Loss: 1.5339 - Accuracy: 0.2857 - F1: 0.2464
sub_14:Test (Best Model) - Loss: 1.5767 - Accuracy: 0.2619 - F1: 0.2429
sub_14:Test (Best Model) - Loss: 1.5458 - Accuracy: 0.3000 - F1: 0.2663
sub_14:Test (Best Model) - Loss: 1.5411 - Accuracy: 0.3048 - F1: 0.2827
sub_14:Test (Best Model) - Loss: 1.5859 - Accuracy: 0.2238 - F1: 0.2142
sub_14:Test (Best Model) - Loss: 1.5937 - Accuracy: 0.2381 - F1: 0.2121
sub_14:Test (Best Model) - Loss: 1.5805 - Accuracy: 0.2333 - F1: 0.1953
sub_14:Test (Best Model) - Loss: 1.5997 - Accuracy: 0.2238 - F1: 0.1783
sub_14:Test (Best Model) - Loss: 1.5819 - Accuracy: 0.2619 - F1: 0.2457
sub_14:Test (Best Model) - Loss: 1.5929 - Accuracy: 0.2667 - F1: 0.2400

=== Summary Results ===

acc: 24.49 ± 2.25
F1: 23.42 ± 2.33
acc-in: 27.94 ± 2.22
F1-in: 26.95 ± 2.34
