lr: 1e-05
sub_12:Test (Best Model) - Loss: 1.6139 - Accuracy: 0.2143 - F1: 0.2011
sub_3:Test (Best Model) - Loss: 1.5995 - Accuracy: 0.2190 - F1: 0.2097
sub_7:Test (Best Model) - Loss: 1.6040 - Accuracy: 0.2286 - F1: 0.1999
sub_11:Test (Best Model) - Loss: 1.5906 - Accuracy: 0.2524 - F1: 0.2503
sub_13:Test (Best Model) - Loss: 1.5889 - Accuracy: 0.2905 - F1: 0.2655
sub_12:Test (Best Model) - Loss: 1.6050 - Accuracy: 0.1762 - F1: 0.1750
sub_10:Test (Best Model) - Loss: 1.5817 - Accuracy: 0.3238 - F1: 0.3012
sub_7:Test (Best Model) - Loss: 1.5893 - Accuracy: 0.2857 - F1: 0.2658
sub_6:Test (Best Model) - Loss: 1.5808 - Accuracy: 0.3095 - F1: 0.2852
sub_2:Test (Best Model) - Loss: 1.5236 - Accuracy: 0.4000 - F1: 0.3429
sub_3:Test (Best Model) - Loss: 1.6083 - Accuracy: 0.1952 - F1: 0.1715
sub_8:Test (Best Model) - Loss: 1.5601 - Accuracy: 0.3286 - F1: 0.3189
sub_12:Test (Best Model) - Loss: 1.6216 - Accuracy: 0.1714 - F1: 0.1701
sub_14:Test (Best Model) - Loss: 1.5517 - Accuracy: 0.4048 - F1: 0.3864
sub_5:Test (Best Model) - Loss: 1.5632 - Accuracy: 0.3048 - F1: 0.2829
sub_9:Test (Best Model) - Loss: 1.5552 - Accuracy: 0.3571 - F1: 0.3039
sub_3:Test (Best Model) - Loss: 1.6190 - Accuracy: 0.2048 - F1: 0.1757
sub_10:Test (Best Model) - Loss: 1.5890 - Accuracy: 0.3000 - F1: 0.2829
sub_6:Test (Best Model) - Loss: 1.6000 - Accuracy: 0.2190 - F1: 0.2097
sub_12:Test (Best Model) - Loss: 1.6129 - Accuracy: 0.2000 - F1: 0.1858
sub_1:Test (Best Model) - Loss: 1.5385 - Accuracy: 0.4048 - F1: 0.3676
sub_13:Test (Best Model) - Loss: 1.6063 - Accuracy: 0.2190 - F1: 0.2171
sub_7:Test (Best Model) - Loss: 1.5937 - Accuracy: 0.2571 - F1: 0.2286
sub_3:Test (Best Model) - Loss: 1.6075 - Accuracy: 0.2095 - F1: 0.2047
sub_2:Test (Best Model) - Loss: 1.5536 - Accuracy: 0.3857 - F1: 0.3657
sub_6:Test (Best Model) - Loss: 1.6076 - Accuracy: 0.2429 - F1: 0.2292
sub_10:Test (Best Model) - Loss: 1.6003 - Accuracy: 0.2619 - F1: 0.2328
sub_5:Test (Best Model) - Loss: 1.5919 - Accuracy: 0.2619 - F1: 0.2509
sub_4:Test (Best Model) - Loss: 1.5580 - Accuracy: 0.3190 - F1: 0.3062
sub_11:Test (Best Model) - Loss: 1.5789 - Accuracy: 0.3143 - F1: 0.2878
sub_1:Test (Best Model) - Loss: 1.5918 - Accuracy: 0.2619 - F1: 0.2359
sub_3:Test (Best Model) - Loss: 1.5903 - Accuracy: 0.2524 - F1: 0.2036
sub_4:Test (Best Model) - Loss: 1.6034 - Accuracy: 0.2286 - F1: 0.2212
sub_13:Test (Best Model) - Loss: 1.5934 - Accuracy: 0.2714 - F1: 0.2618
sub_14:Test (Best Model) - Loss: 1.5767 - Accuracy: 0.2714 - F1: 0.2698
sub_5:Test (Best Model) - Loss: 1.6062 - Accuracy: 0.2286 - F1: 0.2093
sub_12:Test (Best Model) - Loss: 1.5881 - Accuracy: 0.2905 - F1: 0.2653
sub_8:Test (Best Model) - Loss: 1.5492 - Accuracy: 0.3571 - F1: 0.3311
sub_4:Test (Best Model) - Loss: 1.6064 - Accuracy: 0.2238 - F1: 0.2225
sub_10:Test (Best Model) - Loss: 1.5864 - Accuracy: 0.2810 - F1: 0.2726
sub_6:Test (Best Model) - Loss: 1.5921 - Accuracy: 0.2524 - F1: 0.2552
sub_13:Test (Best Model) - Loss: 1.5969 - Accuracy: 0.2381 - F1: 0.2243
sub_9:Test (Best Model) - Loss: 1.5497 - Accuracy: 0.3714 - F1: 0.3260
sub_11:Test (Best Model) - Loss: 1.6045 - Accuracy: 0.2238 - F1: 0.2244
sub_7:Test (Best Model) - Loss: 1.5981 - Accuracy: 0.2095 - F1: 0.2122
sub_1:Test (Best Model) - Loss: 1.6030 - Accuracy: 0.2190 - F1: 0.2125
sub_7:Test (Best Model) - Loss: 1.6157 - Accuracy: 0.1524 - F1: 0.1323
sub_6:Test (Best Model) - Loss: 1.5809 - Accuracy: 0.3286 - F1: 0.3075
sub_2:Test (Best Model) - Loss: 1.5277 - Accuracy: 0.3952 - F1: 0.3565
sub_12:Test (Best Model) - Loss: 1.6002 - Accuracy: 0.2714 - F1: 0.2681
sub_3:Test (Best Model) - Loss: 1.5920 - Accuracy: 0.2619 - F1: 0.2526
sub_14:Test (Best Model) - Loss: 1.5851 - Accuracy: 0.3048 - F1: 0.2868
sub_1:Test (Best Model) - Loss: 1.6221 - Accuracy: 0.1952 - F1: 0.1971
sub_5:Test (Best Model) - Loss: 1.5978 - Accuracy: 0.2714 - F1: 0.2538
sub_4:Test (Best Model) - Loss: 1.5857 - Accuracy: 0.2905 - F1: 0.2915
sub_13:Test (Best Model) - Loss: 1.5764 - Accuracy: 0.3048 - F1: 0.2869
sub_12:Test (Best Model) - Loss: 1.6091 - Accuracy: 0.2381 - F1: 0.2286
sub_3:Test (Best Model) - Loss: 1.6081 - Accuracy: 0.2286 - F1: 0.2219
sub_8:Test (Best Model) - Loss: 1.5879 - Accuracy: 0.3048 - F1: 0.3035
sub_6:Test (Best Model) - Loss: 1.5940 - Accuracy: 0.2619 - F1: 0.2626
sub_11:Test (Best Model) - Loss: 1.5915 - Accuracy: 0.2905 - F1: 0.2679
sub_7:Test (Best Model) - Loss: 1.5962 - Accuracy: 0.2905 - F1: 0.2606
sub_10:Test (Best Model) - Loss: 1.5607 - Accuracy: 0.3381 - F1: 0.2962
sub_1:Test (Best Model) - Loss: 1.5650 - Accuracy: 0.3286 - F1: 0.3076
sub_4:Test (Best Model) - Loss: 1.5824 - Accuracy: 0.2952 - F1: 0.2598
sub_2:Test (Best Model) - Loss: 1.5759 - Accuracy: 0.3048 - F1: 0.2823
sub_5:Test (Best Model) - Loss: 1.5658 - Accuracy: 0.3429 - F1: 0.3264
sub_3:Test (Best Model) - Loss: 1.5959 - Accuracy: 0.2238 - F1: 0.2244
sub_13:Test (Best Model) - Loss: 1.5932 - Accuracy: 0.3000 - F1: 0.2884
sub_6:Test (Best Model) - Loss: 1.6059 - Accuracy: 0.2714 - F1: 0.2793
sub_9:Test (Best Model) - Loss: 1.5586 - Accuracy: 0.3714 - F1: 0.3298
sub_14:Test (Best Model) - Loss: 1.5727 - Accuracy: 0.3286 - F1: 0.3127
sub_12:Test (Best Model) - Loss: 1.6027 - Accuracy: 0.2286 - F1: 0.2201
sub_5:Test (Best Model) - Loss: 1.6030 - Accuracy: 0.2286 - F1: 0.2273
sub_8:Test (Best Model) - Loss: 1.5884 - Accuracy: 0.2905 - F1: 0.2830
sub_7:Test (Best Model) - Loss: 1.5895 - Accuracy: 0.2571 - F1: 0.2555
sub_2:Test (Best Model) - Loss: 1.5452 - Accuracy: 0.3762 - F1: 0.3554
sub_13:Test (Best Model) - Loss: 1.6227 - Accuracy: 0.1810 - F1: 0.1789
sub_1:Test (Best Model) - Loss: 1.5771 - Accuracy: 0.2667 - F1: 0.2654
sub_11:Test (Best Model) - Loss: 1.5799 - Accuracy: 0.3286 - F1: 0.3043
sub_3:Test (Best Model) - Loss: 1.5988 - Accuracy: 0.2381 - F1: 0.2216
sub_6:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2095 - F1: 0.1832
sub_7:Test (Best Model) - Loss: 1.6158 - Accuracy: 0.1762 - F1: 0.1655
sub_5:Test (Best Model) - Loss: 1.6011 - Accuracy: 0.2238 - F1: 0.2168
sub_14:Test (Best Model) - Loss: 1.5999 - Accuracy: 0.3000 - F1: 0.2922
sub_4:Test (Best Model) - Loss: 1.5843 - Accuracy: 0.3286 - F1: 0.3185
sub_7:Test (Best Model) - Loss: 1.6050 - Accuracy: 0.1857 - F1: 0.1820
sub_8:Test (Best Model) - Loss: 1.5618 - Accuracy: 0.3571 - F1: 0.3348
sub_14:Test (Best Model) - Loss: 1.5970 - Accuracy: 0.2143 - F1: 0.2140
sub_10:Test (Best Model) - Loss: 1.5820 - Accuracy: 0.3095 - F1: 0.2903
sub_6:Test (Best Model) - Loss: 1.5902 - Accuracy: 0.2571 - F1: 0.2380
sub_3:Test (Best Model) - Loss: 1.6156 - Accuracy: 0.2048 - F1: 0.1949
sub_12:Test (Best Model) - Loss: 1.5685 - Accuracy: 0.3000 - F1: 0.2944
sub_4:Test (Best Model) - Loss: 1.5934 - Accuracy: 0.2619 - F1: 0.2599
sub_2:Test (Best Model) - Loss: 1.5712 - Accuracy: 0.3429 - F1: 0.2831
sub_11:Test (Best Model) - Loss: 1.5968 - Accuracy: 0.2714 - F1: 0.2682
sub_9:Test (Best Model) - Loss: 1.5685 - Accuracy: 0.3000 - F1: 0.2234
sub_7:Test (Best Model) - Loss: 1.5939 - Accuracy: 0.1810 - F1: 0.1800
sub_6:Test (Best Model) - Loss: 1.5937 - Accuracy: 0.2810 - F1: 0.2541
sub_3:Test (Best Model) - Loss: 1.6238 - Accuracy: 0.1571 - F1: 0.1473
sub_13:Test (Best Model) - Loss: 1.5775 - Accuracy: 0.3143 - F1: 0.2775
sub_9:Test (Best Model) - Loss: 1.6020 - Accuracy: 0.1857 - F1: 0.1859
sub_5:Test (Best Model) - Loss: 1.5645 - Accuracy: 0.3429 - F1: 0.3202
sub_7:Test (Best Model) - Loss: 1.5976 - Accuracy: 0.2571 - F1: 0.2333
sub_4:Test (Best Model) - Loss: 1.6010 - Accuracy: 0.2333 - F1: 0.2403
sub_6:Test (Best Model) - Loss: 1.5970 - Accuracy: 0.2810 - F1: 0.2420
sub_7:Test (Best Model) - Loss: 1.5982 - Accuracy: 0.2762 - F1: 0.2758
sub_1:Test (Best Model) - Loss: 1.5387 - Accuracy: 0.3286 - F1: 0.3292
sub_8:Test (Best Model) - Loss: 1.5928 - Accuracy: 0.2571 - F1: 0.2600
sub_12:Test (Best Model) - Loss: 1.5783 - Accuracy: 0.3095 - F1: 0.2962
sub_10:Test (Best Model) - Loss: 1.5913 - Accuracy: 0.2810 - F1: 0.2638
sub_2:Test (Best Model) - Loss: 1.5603 - Accuracy: 0.3619 - F1: 0.3586
sub_13:Test (Best Model) - Loss: 1.5913 - Accuracy: 0.2905 - F1: 0.2815
sub_11:Test (Best Model) - Loss: 1.5838 - Accuracy: 0.2952 - F1: 0.2936
sub_14:Test (Best Model) - Loss: 1.5433 - Accuracy: 0.4143 - F1: 0.3729
sub_3:Test (Best Model) - Loss: 1.6032 - Accuracy: 0.2238 - F1: 0.2236
sub_4:Test (Best Model) - Loss: 1.5846 - Accuracy: 0.3048 - F1: 0.2908
sub_13:Test (Best Model) - Loss: 1.6081 - Accuracy: 0.2476 - F1: 0.2381
sub_1:Test (Best Model) - Loss: 1.5880 - Accuracy: 0.2762 - F1: 0.2840
sub_14:Test (Best Model) - Loss: 1.5898 - Accuracy: 0.2952 - F1: 0.2918
sub_6:Test (Best Model) - Loss: 1.5899 - Accuracy: 0.1905 - F1: 0.1998
sub_10:Test (Best Model) - Loss: 1.5922 - Accuracy: 0.2810 - F1: 0.2850
sub_7:Test (Best Model) - Loss: 1.5842 - Accuracy: 0.2429 - F1: 0.2233
sub_9:Test (Best Model) - Loss: 1.5711 - Accuracy: 0.3762 - F1: 0.3445
sub_2:Test (Best Model) - Loss: 1.5674 - Accuracy: 0.3429 - F1: 0.3311
sub_8:Test (Best Model) - Loss: 1.5783 - Accuracy: 0.3000 - F1: 0.3007
sub_13:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2238 - F1: 0.2038
sub_3:Test (Best Model) - Loss: 1.6082 - Accuracy: 0.2048 - F1: 0.2035
sub_5:Test (Best Model) - Loss: 1.5382 - Accuracy: 0.3619 - F1: 0.3402
sub_4:Test (Best Model) - Loss: 1.5827 - Accuracy: 0.2714 - F1: 0.2688
sub_11:Test (Best Model) - Loss: 1.5909 - Accuracy: 0.3000 - F1: 0.2971
sub_14:Test (Best Model) - Loss: 1.5750 - Accuracy: 0.2571 - F1: 0.2595
sub_9:Test (Best Model) - Loss: 1.5781 - Accuracy: 0.2905 - F1: 0.2825
sub_6:Test (Best Model) - Loss: 1.5898 - Accuracy: 0.2619 - F1: 0.2561
sub_10:Test (Best Model) - Loss: 1.5860 - Accuracy: 0.2905 - F1: 0.2814
sub_11:Test (Best Model) - Loss: 1.5931 - Accuracy: 0.2524 - F1: 0.2287
sub_1:Test (Best Model) - Loss: 1.5612 - Accuracy: 0.3190 - F1: 0.3127
sub_2:Test (Best Model) - Loss: 1.5364 - Accuracy: 0.3667 - F1: 0.3231
sub_7:Test (Best Model) - Loss: 1.5861 - Accuracy: 0.2810 - F1: 0.2676
sub_8:Test (Best Model) - Loss: 1.5858 - Accuracy: 0.2571 - F1: 0.2555
sub_6:Test (Best Model) - Loss: 1.6073 - Accuracy: 0.2048 - F1: 0.1981
sub_13:Test (Best Model) - Loss: 1.5977 - Accuracy: 0.2857 - F1: 0.2670
sub_4:Test (Best Model) - Loss: 1.6014 - Accuracy: 0.2476 - F1: 0.2432
sub_12:Test (Best Model) - Loss: 1.5727 - Accuracy: 0.2429 - F1: 0.2460
sub_3:Test (Best Model) - Loss: 1.5950 - Accuracy: 0.2857 - F1: 0.2746
sub_5:Test (Best Model) - Loss: 1.5635 - Accuracy: 0.3429 - F1: 0.3345
sub_10:Test (Best Model) - Loss: 1.6079 - Accuracy: 0.2429 - F1: 0.2364
sub_7:Test (Best Model) - Loss: 1.6029 - Accuracy: 0.2619 - F1: 0.2539
sub_14:Test (Best Model) - Loss: 1.5303 - Accuracy: 0.3952 - F1: 0.3639
sub_13:Test (Best Model) - Loss: 1.6152 - Accuracy: 0.2190 - F1: 0.2121
sub_6:Test (Best Model) - Loss: 1.6136 - Accuracy: 0.1857 - F1: 0.1787
sub_9:Test (Best Model) - Loss: 1.5826 - Accuracy: 0.2381 - F1: 0.2338
sub_4:Test (Best Model) - Loss: 1.6050 - Accuracy: 0.2000 - F1: 0.2034
sub_12:Test (Best Model) - Loss: 1.6157 - Accuracy: 0.2048 - F1: 0.1904
sub_3:Test (Best Model) - Loss: 1.6166 - Accuracy: 0.1667 - F1: 0.1566
sub_1:Test (Best Model) - Loss: 1.5737 - Accuracy: 0.3333 - F1: 0.3277
sub_8:Test (Best Model) - Loss: 1.5902 - Accuracy: 0.2762 - F1: 0.2739
sub_13:Test (Best Model) - Loss: 1.6202 - Accuracy: 0.2000 - F1: 0.1928
sub_2:Test (Best Model) - Loss: 1.5333 - Accuracy: 0.4000 - F1: 0.3899
sub_11:Test (Best Model) - Loss: 1.5582 - Accuracy: 0.3095 - F1: 0.3079
sub_5:Test (Best Model) - Loss: 1.5991 - Accuracy: 0.2952 - F1: 0.2833
sub_10:Test (Best Model) - Loss: 1.5989 - Accuracy: 0.2429 - F1: 0.2196
sub_13:Test (Best Model) - Loss: 1.6010 - Accuracy: 0.2476 - F1: 0.2290
sub_4:Test (Best Model) - Loss: 1.5803 - Accuracy: 0.3381 - F1: 0.3140
sub_12:Test (Best Model) - Loss: 1.5972 - Accuracy: 0.2857 - F1: 0.2849
sub_9:Test (Best Model) - Loss: 1.5398 - Accuracy: 0.4095 - F1: 0.3754
sub_5:Test (Best Model) - Loss: 1.5976 - Accuracy: 0.2714 - F1: 0.2591
sub_2:Test (Best Model) - Loss: 1.5732 - Accuracy: 0.3238 - F1: 0.2837
sub_14:Test (Best Model) - Loss: 1.5780 - Accuracy: 0.3238 - F1: 0.2992
sub_8:Test (Best Model) - Loss: 1.5726 - Accuracy: 0.3000 - F1: 0.3038
sub_5:Test (Best Model) - Loss: 1.6124 - Accuracy: 0.2381 - F1: 0.2266
sub_2:Test (Best Model) - Loss: 1.6033 - Accuracy: 0.2143 - F1: 0.2154
sub_1:Test (Best Model) - Loss: 1.5934 - Accuracy: 0.2667 - F1: 0.2633
sub_8:Test (Best Model) - Loss: 1.5955 - Accuracy: 0.3238 - F1: 0.3072
sub_10:Test (Best Model) - Loss: 1.6089 - Accuracy: 0.2048 - F1: 0.1915
sub_11:Test (Best Model) - Loss: 1.5998 - Accuracy: 0.2571 - F1: 0.2544
sub_4:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.2333 - F1: 0.2303
sub_12:Test (Best Model) - Loss: 1.5894 - Accuracy: 0.2524 - F1: 0.2338
sub_9:Test (Best Model) - Loss: 1.5661 - Accuracy: 0.3429 - F1: 0.3275
sub_10:Test (Best Model) - Loss: 1.6063 - Accuracy: 0.1952 - F1: 0.1896
sub_8:Test (Best Model) - Loss: 1.6007 - Accuracy: 0.2714 - F1: 0.2516
sub_1:Test (Best Model) - Loss: 1.6076 - Accuracy: 0.2381 - F1: 0.2256
sub_5:Test (Best Model) - Loss: 1.5836 - Accuracy: 0.2905 - F1: 0.2778
sub_2:Test (Best Model) - Loss: 1.5559 - Accuracy: 0.3714 - F1: 0.3190
sub_14:Test (Best Model) - Loss: 1.5803 - Accuracy: 0.3619 - F1: 0.3315
sub_4:Test (Best Model) - Loss: 1.6025 - Accuracy: 0.2524 - F1: 0.2489
sub_10:Test (Best Model) - Loss: 1.6011 - Accuracy: 0.2286 - F1: 0.2029
sub_12:Test (Best Model) - Loss: 1.5820 - Accuracy: 0.2857 - F1: 0.2936
sub_11:Test (Best Model) - Loss: 1.5704 - Accuracy: 0.3238 - F1: 0.3203
sub_10:Test (Best Model) - Loss: 1.6058 - Accuracy: 0.2333 - F1: 0.2193
sub_5:Test (Best Model) - Loss: 1.5983 - Accuracy: 0.2333 - F1: 0.2235
sub_9:Test (Best Model) - Loss: 1.5748 - Accuracy: 0.2857 - F1: 0.2668
sub_2:Test (Best Model) - Loss: 1.5334 - Accuracy: 0.3714 - F1: 0.3205
sub_1:Test (Best Model) - Loss: 1.5643 - Accuracy: 0.3286 - F1: 0.3217
sub_8:Test (Best Model) - Loss: 1.5783 - Accuracy: 0.3190 - F1: 0.2761
sub_9:Test (Best Model) - Loss: 1.5823 - Accuracy: 0.3095 - F1: 0.2889
sub_11:Test (Best Model) - Loss: 1.5908 - Accuracy: 0.3000 - F1: 0.2809
sub_14:Test (Best Model) - Loss: 1.5623 - Accuracy: 0.3571 - F1: 0.3214
sub_8:Test (Best Model) - Loss: 1.5912 - Accuracy: 0.2667 - F1: 0.2550
sub_11:Test (Best Model) - Loss: 1.5959 - Accuracy: 0.2524 - F1: 0.2401
sub_1:Test (Best Model) - Loss: 1.5739 - Accuracy: 0.3000 - F1: 0.2869
sub_2:Test (Best Model) - Loss: 1.5479 - Accuracy: 0.3524 - F1: 0.3359
sub_9:Test (Best Model) - Loss: 1.5858 - Accuracy: 0.2571 - F1: 0.2437
sub_14:Test (Best Model) - Loss: 1.5479 - Accuracy: 0.4190 - F1: 0.3803
sub_1:Test (Best Model) - Loss: 1.6021 - Accuracy: 0.2429 - F1: 0.2308
sub_11:Test (Best Model) - Loss: 1.6130 - Accuracy: 0.1952 - F1: 0.1926
sub_8:Test (Best Model) - Loss: 1.5817 - Accuracy: 0.3333 - F1: 0.3023
sub_9:Test (Best Model) - Loss: 1.5904 - Accuracy: 0.2952 - F1: 0.2679
sub_14:Test (Best Model) - Loss: 1.5787 - Accuracy: 0.3571 - F1: 0.3409
sub_9:Test (Best Model) - Loss: 1.5817 - Accuracy: 0.2905 - F1: 0.2527

=== Summary Results ===

acc: 27.80 ± 3.65
F1: 26.32 ± 3.24
acc-in: 30.53 ± 3.81
F1-in: 29.52 ± 3.76
