lr: 1e-06
sub_1:Test (Best Model) - Loss: 1.5586 - Accuracy: 0.3190 - F1: 0.2897
sub_1:Test (Best Model) - Loss: 1.5498 - Accuracy: 0.2667 - F1: 0.2282
sub_1:Test (Best Model) - Loss: 1.5895 - Accuracy: 0.2524 - F1: 0.2325
sub_1:Test (Best Model) - Loss: 1.5801 - Accuracy: 0.2762 - F1: 0.2600
sub_1:Test (Best Model) - Loss: 1.5784 - Accuracy: 0.2714 - F1: 0.2429
sub_1:Test (Best Model) - Loss: 1.5359 - Accuracy: 0.3190 - F1: 0.3285
sub_1:Test (Best Model) - Loss: 1.5243 - Accuracy: 0.3048 - F1: 0.3111
sub_1:Test (Best Model) - Loss: 1.4828 - Accuracy: 0.3905 - F1: 0.3898
sub_1:Test (Best Model) - Loss: 1.5329 - Accuracy: 0.3000 - F1: 0.3118
sub_1:Test (Best Model) - Loss: 1.5406 - Accuracy: 0.3143 - F1: 0.3283
sub_1:Test (Best Model) - Loss: 1.5167 - Accuracy: 0.3143 - F1: 0.3211
sub_1:Test (Best Model) - Loss: 1.5076 - Accuracy: 0.3000 - F1: 0.2901
sub_1:Test (Best Model) - Loss: 1.5086 - Accuracy: 0.3381 - F1: 0.3311
sub_1:Test (Best Model) - Loss: 1.5279 - Accuracy: 0.3048 - F1: 0.2990
sub_1:Test (Best Model) - Loss: 1.5232 - Accuracy: 0.2571 - F1: 0.2555
sub_2:Test (Best Model) - Loss: 1.5145 - Accuracy: 0.3190 - F1: 0.2648
sub_2:Test (Best Model) - Loss: 1.5528 - Accuracy: 0.2619 - F1: 0.2225
sub_2:Test (Best Model) - Loss: 1.5502 - Accuracy: 0.2714 - F1: 0.2399
sub_2:Test (Best Model) - Loss: 1.5491 - Accuracy: 0.3000 - F1: 0.2720
sub_2:Test (Best Model) - Loss: 1.5537 - Accuracy: 0.2571 - F1: 0.2303
sub_2:Test (Best Model) - Loss: 1.5684 - Accuracy: 0.2238 - F1: 0.2104
sub_2:Test (Best Model) - Loss: 1.5218 - Accuracy: 0.2952 - F1: 0.2908
sub_2:Test (Best Model) - Loss: 1.5153 - Accuracy: 0.2571 - F1: 0.2458
sub_2:Test (Best Model) - Loss: 1.4973 - Accuracy: 0.2857 - F1: 0.2839
sub_2:Test (Best Model) - Loss: 1.5186 - Accuracy: 0.2762 - F1: 0.2792
sub_2:Test (Best Model) - Loss: 1.5147 - Accuracy: 0.2810 - F1: 0.2675
sub_2:Test (Best Model) - Loss: 1.5502 - Accuracy: 0.2810 - F1: 0.2627
sub_2:Test (Best Model) - Loss: 1.5246 - Accuracy: 0.2524 - F1: 0.2410
sub_2:Test (Best Model) - Loss: 1.5147 - Accuracy: 0.2619 - F1: 0.2539
sub_2:Test (Best Model) - Loss: 1.5694 - Accuracy: 0.2238 - F1: 0.2210
sub_3:Test (Best Model) - Loss: 1.5663 - Accuracy: 0.2571 - F1: 0.1942
sub_3:Test (Best Model) - Loss: 1.5902 - Accuracy: 0.2381 - F1: 0.1638
sub_3:Test (Best Model) - Loss: 1.5888 - Accuracy: 0.2524 - F1: 0.1975
sub_3:Test (Best Model) - Loss: 1.5768 - Accuracy: 0.2857 - F1: 0.2343
sub_3:Test (Best Model) - Loss: 1.5971 - Accuracy: 0.2571 - F1: 0.1782
sub_3:Test (Best Model) - Loss: 1.5708 - Accuracy: 0.3286 - F1: 0.3130
sub_3:Test (Best Model) - Loss: 1.5599 - Accuracy: 0.2714 - F1: 0.2602
sub_3:Test (Best Model) - Loss: 1.5665 - Accuracy: 0.3000 - F1: 0.2670
sub_3:Test (Best Model) - Loss: 1.5252 - Accuracy: 0.3095 - F1: 0.2972
sub_3:Test (Best Model) - Loss: 1.5300 - Accuracy: 0.3286 - F1: 0.3033
sub_3:Test (Best Model) - Loss: 1.5577 - Accuracy: 0.3286 - F1: 0.3348
sub_3:Test (Best Model) - Loss: 1.5831 - Accuracy: 0.2524 - F1: 0.2527
sub_3:Test (Best Model) - Loss: 1.5531 - Accuracy: 0.2571 - F1: 0.2645
sub_3:Test (Best Model) - Loss: 1.5476 - Accuracy: 0.2714 - F1: 0.2862
sub_3:Test (Best Model) - Loss: 1.5401 - Accuracy: 0.3333 - F1: 0.3338
sub_4:Test (Best Model) - Loss: 1.5713 - Accuracy: 0.2810 - F1: 0.2703
sub_4:Test (Best Model) - Loss: 1.5896 - Accuracy: 0.2190 - F1: 0.2016
sub_4:Test (Best Model) - Loss: 1.5928 - Accuracy: 0.2143 - F1: 0.1925
sub_4:Test (Best Model) - Loss: 1.5853 - Accuracy: 0.2286 - F1: 0.2117
sub_4:Test (Best Model) - Loss: 1.5543 - Accuracy: 0.3048 - F1: 0.2660
sub_4:Test (Best Model) - Loss: 1.5520 - Accuracy: 0.2952 - F1: 0.2824
sub_4:Test (Best Model) - Loss: 1.5484 - Accuracy: 0.2905 - F1: 0.2681
sub_4:Test (Best Model) - Loss: 1.5380 - Accuracy: 0.3333 - F1: 0.3337
sub_4:Test (Best Model) - Loss: 1.5509 - Accuracy: 0.3000 - F1: 0.2914
sub_4:Test (Best Model) - Loss: 1.5543 - Accuracy: 0.3429 - F1: 0.3434
sub_4:Test (Best Model) - Loss: 1.5624 - Accuracy: 0.2714 - F1: 0.2624
sub_4:Test (Best Model) - Loss: 1.5839 - Accuracy: 0.2381 - F1: 0.1995
sub_4:Test (Best Model) - Loss: 1.5913 - Accuracy: 0.2333 - F1: 0.1849
sub_4:Test (Best Model) - Loss: 1.5872 - Accuracy: 0.2429 - F1: 0.1855
sub_4:Test (Best Model) - Loss: 1.5824 - Accuracy: 0.2381 - F1: 0.2256
sub_5:Test (Best Model) - Loss: 1.5728 - Accuracy: 0.2905 - F1: 0.2737
sub_5:Test (Best Model) - Loss: 1.5641 - Accuracy: 0.2619 - F1: 0.2491
sub_5:Test (Best Model) - Loss: 1.5453 - Accuracy: 0.3000 - F1: 0.2764
sub_5:Test (Best Model) - Loss: 1.5401 - Accuracy: 0.2905 - F1: 0.2751
sub_5:Test (Best Model) - Loss: 1.5621 - Accuracy: 0.3000 - F1: 0.2670
sub_5:Test (Best Model) - Loss: 1.5525 - Accuracy: 0.2810 - F1: 0.2555
sub_5:Test (Best Model) - Loss: 1.5862 - Accuracy: 0.2667 - F1: 0.2113
sub_5:Test (Best Model) - Loss: 1.5302 - Accuracy: 0.3429 - F1: 0.3426
sub_5:Test (Best Model) - Loss: 1.5398 - Accuracy: 0.3048 - F1: 0.2714
sub_5:Test (Best Model) - Loss: 1.5704 - Accuracy: 0.2571 - F1: 0.2391
sub_5:Test (Best Model) - Loss: 1.5029 - Accuracy: 0.3381 - F1: 0.3512
sub_5:Test (Best Model) - Loss: 1.5430 - Accuracy: 0.2905 - F1: 0.2920
sub_5:Test (Best Model) - Loss: 1.5410 - Accuracy: 0.2905 - F1: 0.2862
sub_5:Test (Best Model) - Loss: 1.5558 - Accuracy: 0.2381 - F1: 0.2340
sub_5:Test (Best Model) - Loss: 1.5367 - Accuracy: 0.3476 - F1: 0.3621
sub_6:Test (Best Model) - Loss: 1.6038 - Accuracy: 0.2095 - F1: 0.2095
sub_6:Test (Best Model) - Loss: 1.6065 - Accuracy: 0.2143 - F1: 0.2105
sub_6:Test (Best Model) - Loss: 1.6137 - Accuracy: 0.1762 - F1: 0.1728
sub_6:Test (Best Model) - Loss: 1.5981 - Accuracy: 0.2095 - F1: 0.2085
sub_6:Test (Best Model) - Loss: 1.5944 - Accuracy: 0.2714 - F1: 0.2666
sub_6:Test (Best Model) - Loss: 1.6401 - Accuracy: 0.2000 - F1: 0.1913
sub_6:Test (Best Model) - Loss: 1.5972 - Accuracy: 0.2810 - F1: 0.2751
sub_6:Test (Best Model) - Loss: 1.6090 - Accuracy: 0.2286 - F1: 0.2201
sub_6:Test (Best Model) - Loss: 1.5931 - Accuracy: 0.2952 - F1: 0.2839
sub_6:Test (Best Model) - Loss: 1.5904 - Accuracy: 0.2476 - F1: 0.2460
sub_6:Test (Best Model) - Loss: 1.6186 - Accuracy: 0.2619 - F1: 0.2643
sub_6:Test (Best Model) - Loss: 1.6180 - Accuracy: 0.2571 - F1: 0.2492
sub_6:Test (Best Model) - Loss: 1.5918 - Accuracy: 0.2571 - F1: 0.2435
sub_6:Test (Best Model) - Loss: 1.6096 - Accuracy: 0.2857 - F1: 0.2806
sub_6:Test (Best Model) - Loss: 1.6057 - Accuracy: 0.2429 - F1: 0.2404
sub_7:Test (Best Model) - Loss: 1.6191 - Accuracy: 0.2048 - F1: 0.2027
sub_7:Test (Best Model) - Loss: 1.6384 - Accuracy: 0.2095 - F1: 0.2050
sub_7:Test (Best Model) - Loss: 1.6389 - Accuracy: 0.2238 - F1: 0.2152
sub_7:Test (Best Model) - Loss: 1.6283 - Accuracy: 0.2190 - F1: 0.2113
sub_7:Test (Best Model) - Loss: 1.6209 - Accuracy: 0.2190 - F1: 0.2137
sub_7:Test (Best Model) - Loss: 1.6225 - Accuracy: 0.2000 - F1: 0.1847
sub_7:Test (Best Model) - Loss: 1.6015 - Accuracy: 0.2143 - F1: 0.2120
sub_7:Test (Best Model) - Loss: 1.5996 - Accuracy: 0.2143 - F1: 0.2160
sub_7:Test (Best Model) - Loss: 1.6245 - Accuracy: 0.2190 - F1: 0.2082
sub_7:Test (Best Model) - Loss: 1.6156 - Accuracy: 0.2190 - F1: 0.1978
sub_7:Test (Best Model) - Loss: 1.5972 - Accuracy: 0.2429 - F1: 0.2359
sub_7:Test (Best Model) - Loss: 1.5988 - Accuracy: 0.2000 - F1: 0.1982
sub_7:Test (Best Model) - Loss: 1.6035 - Accuracy: 0.2524 - F1: 0.2545
sub_7:Test (Best Model) - Loss: 1.6263 - Accuracy: 0.1714 - F1: 0.1673
sub_7:Test (Best Model) - Loss: 1.6046 - Accuracy: 0.2333 - F1: 0.2142
sub_8:Test (Best Model) - Loss: 1.4700 - Accuracy: 0.3905 - F1: 0.3798
sub_8:Test (Best Model) - Loss: 1.5177 - Accuracy: 0.3333 - F1: 0.3422
sub_8:Test (Best Model) - Loss: 1.4482 - Accuracy: 0.3905 - F1: 0.3738
sub_8:Test (Best Model) - Loss: 1.5249 - Accuracy: 0.2714 - F1: 0.2777
sub_8:Test (Best Model) - Loss: 1.5014 - Accuracy: 0.3571 - F1: 0.3580
sub_8:Test (Best Model) - Loss: 1.4757 - Accuracy: 0.3429 - F1: 0.3598
sub_8:Test (Best Model) - Loss: 1.4867 - Accuracy: 0.3333 - F1: 0.3517
sub_8:Test (Best Model) - Loss: 1.4993 - Accuracy: 0.2952 - F1: 0.3118
sub_8:Test (Best Model) - Loss: 1.5189 - Accuracy: 0.2905 - F1: 0.3005
sub_8:Test (Best Model) - Loss: 1.5216 - Accuracy: 0.3000 - F1: 0.3141
sub_8:Test (Best Model) - Loss: 1.5376 - Accuracy: 0.2524 - F1: 0.2655
sub_8:Test (Best Model) - Loss: 1.5326 - Accuracy: 0.2667 - F1: 0.2871
sub_8:Test (Best Model) - Loss: 1.5430 - Accuracy: 0.2905 - F1: 0.2906
sub_8:Test (Best Model) - Loss: 1.5507 - Accuracy: 0.2619 - F1: 0.2517
sub_8:Test (Best Model) - Loss: 1.5349 - Accuracy: 0.2762 - F1: 0.2931
sub_9:Test (Best Model) - Loss: 1.5374 - Accuracy: 0.3000 - F1: 0.2671
sub_9:Test (Best Model) - Loss: 1.5750 - Accuracy: 0.2476 - F1: 0.2173
sub_9:Test (Best Model) - Loss: 1.5594 - Accuracy: 0.3238 - F1: 0.2893
sub_9:Test (Best Model) - Loss: 1.5674 - Accuracy: 0.2714 - F1: 0.2566
sub_9:Test (Best Model) - Loss: 1.5532 - Accuracy: 0.2571 - F1: 0.2398
sub_9:Test (Best Model) - Loss: 1.5835 - Accuracy: 0.2429 - F1: 0.2431
sub_9:Test (Best Model) - Loss: 1.5898 - Accuracy: 0.2429 - F1: 0.2519
sub_9:Test (Best Model) - Loss: 1.6028 - Accuracy: 0.2238 - F1: 0.2199
sub_9:Test (Best Model) - Loss: 1.5903 - Accuracy: 0.2333 - F1: 0.2315
sub_9:Test (Best Model) - Loss: 1.5543 - Accuracy: 0.2810 - F1: 0.2815
sub_9:Test (Best Model) - Loss: 1.6156 - Accuracy: 0.2190 - F1: 0.2129
sub_9:Test (Best Model) - Loss: 1.5648 - Accuracy: 0.2476 - F1: 0.2488
sub_9:Test (Best Model) - Loss: 1.5750 - Accuracy: 0.2333 - F1: 0.2362
sub_9:Test (Best Model) - Loss: 1.5863 - Accuracy: 0.2000 - F1: 0.1994
sub_9:Test (Best Model) - Loss: 1.5712 - Accuracy: 0.2429 - F1: 0.2472
sub_10:Test (Best Model) - Loss: 1.6209 - Accuracy: 0.2619 - F1: 0.2649
sub_10:Test (Best Model) - Loss: 1.5963 - Accuracy: 0.2619 - F1: 0.2544
sub_10:Test (Best Model) - Loss: 1.6212 - Accuracy: 0.2619 - F1: 0.2606
sub_10:Test (Best Model) - Loss: 1.6119 - Accuracy: 0.2095 - F1: 0.2066
sub_10:Test (Best Model) - Loss: 1.6162 - Accuracy: 0.2524 - F1: 0.2538
sub_10:Test (Best Model) - Loss: 1.6174 - Accuracy: 0.1905 - F1: 0.1895
sub_10:Test (Best Model) - Loss: 1.6213 - Accuracy: 0.2143 - F1: 0.2029
sub_10:Test (Best Model) - Loss: 1.5829 - Accuracy: 0.2857 - F1: 0.2839
sub_10:Test (Best Model) - Loss: 1.5647 - Accuracy: 0.3048 - F1: 0.3107
sub_10:Test (Best Model) - Loss: 1.6050 - Accuracy: 0.1857 - F1: 0.1880
sub_10:Test (Best Model) - Loss: 1.6296 - Accuracy: 0.2190 - F1: 0.2184
sub_10:Test (Best Model) - Loss: 1.5855 - Accuracy: 0.2810 - F1: 0.2723
sub_10:Test (Best Model) - Loss: 1.5960 - Accuracy: 0.2476 - F1: 0.2393
sub_10:Test (Best Model) - Loss: 1.6051 - Accuracy: 0.2000 - F1: 0.1953
sub_10:Test (Best Model) - Loss: 1.6215 - Accuracy: 0.2143 - F1: 0.2103
sub_11:Test (Best Model) - Loss: 1.6132 - Accuracy: 0.1857 - F1: 0.1685
sub_11:Test (Best Model) - Loss: 1.6169 - Accuracy: 0.2286 - F1: 0.2222
sub_11:Test (Best Model) - Loss: 1.6114 - Accuracy: 0.2000 - F1: 0.1846
sub_11:Test (Best Model) - Loss: 1.6334 - Accuracy: 0.1952 - F1: 0.1851
sub_11:Test (Best Model) - Loss: 1.5941 - Accuracy: 0.2619 - F1: 0.2575
sub_11:Test (Best Model) - Loss: 1.5833 - Accuracy: 0.2381 - F1: 0.2315
sub_11:Test (Best Model) - Loss: 1.5838 - Accuracy: 0.2524 - F1: 0.2527
sub_11:Test (Best Model) - Loss: 1.5900 - Accuracy: 0.2429 - F1: 0.2264
sub_11:Test (Best Model) - Loss: 1.5798 - Accuracy: 0.2857 - F1: 0.2852
sub_11:Test (Best Model) - Loss: 1.5978 - Accuracy: 0.2286 - F1: 0.2107
sub_11:Test (Best Model) - Loss: 1.6125 - Accuracy: 0.2714 - F1: 0.2739
sub_11:Test (Best Model) - Loss: 1.5720 - Accuracy: 0.2857 - F1: 0.2763
sub_11:Test (Best Model) - Loss: 1.6033 - Accuracy: 0.2476 - F1: 0.2110
sub_11:Test (Best Model) - Loss: 1.6031 - Accuracy: 0.2429 - F1: 0.2390
sub_11:Test (Best Model) - Loss: 1.5889 - Accuracy: 0.2714 - F1: 0.2732
sub_12:Test (Best Model) - Loss: 1.5781 - Accuracy: 0.2571 - F1: 0.2550
sub_12:Test (Best Model) - Loss: 1.5742 - Accuracy: 0.2429 - F1: 0.2479
sub_12:Test (Best Model) - Loss: 1.5485 - Accuracy: 0.3381 - F1: 0.3233
sub_12:Test (Best Model) - Loss: 1.5545 - Accuracy: 0.3095 - F1: 0.3066
sub_12:Test (Best Model) - Loss: 1.5415 - Accuracy: 0.3095 - F1: 0.3154
sub_12:Test (Best Model) - Loss: 1.5606 - Accuracy: 0.2857 - F1: 0.2445
sub_12:Test (Best Model) - Loss: 1.5400 - Accuracy: 0.3000 - F1: 0.2496
sub_12:Test (Best Model) - Loss: 1.5910 - Accuracy: 0.2762 - F1: 0.2555
sub_12:Test (Best Model) - Loss: 1.5713 - Accuracy: 0.3095 - F1: 0.2871
sub_12:Test (Best Model) - Loss: 1.5750 - Accuracy: 0.2952 - F1: 0.2740
sub_12:Test (Best Model) - Loss: 1.6025 - Accuracy: 0.2190 - F1: 0.2241
sub_12:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2476 - F1: 0.2469
sub_12:Test (Best Model) - Loss: 1.5828 - Accuracy: 0.2238 - F1: 0.2399
sub_12:Test (Best Model) - Loss: 1.5637 - Accuracy: 0.2667 - F1: 0.2755
sub_12:Test (Best Model) - Loss: 1.5786 - Accuracy: 0.2381 - F1: 0.2518
sub_13:Test (Best Model) - Loss: 1.5791 - Accuracy: 0.2810 - F1: 0.2713
sub_13:Test (Best Model) - Loss: 1.5988 - Accuracy: 0.2286 - F1: 0.2160
sub_13:Test (Best Model) - Loss: 1.6009 - Accuracy: 0.2333 - F1: 0.2135
sub_13:Test (Best Model) - Loss: 1.5762 - Accuracy: 0.2333 - F1: 0.2282
sub_13:Test (Best Model) - Loss: 1.5952 - Accuracy: 0.2333 - F1: 0.2146
sub_13:Test (Best Model) - Loss: 1.6116 - Accuracy: 0.2095 - F1: 0.2093
sub_13:Test (Best Model) - Loss: 1.6039 - Accuracy: 0.2238 - F1: 0.2094
sub_13:Test (Best Model) - Loss: 1.5752 - Accuracy: 0.2381 - F1: 0.2175
sub_13:Test (Best Model) - Loss: 1.5722 - Accuracy: 0.2810 - F1: 0.2645
sub_13:Test (Best Model) - Loss: 1.5375 - Accuracy: 0.3238 - F1: 0.3022
sub_13:Test (Best Model) - Loss: 1.5739 - Accuracy: 0.2952 - F1: 0.2854
sub_13:Test (Best Model) - Loss: 1.5754 - Accuracy: 0.2333 - F1: 0.2137
sub_13:Test (Best Model) - Loss: 1.5837 - Accuracy: 0.2429 - F1: 0.2225
sub_13:Test (Best Model) - Loss: 1.5990 - Accuracy: 0.2524 - F1: 0.2434
sub_13:Test (Best Model) - Loss: 1.5870 - Accuracy: 0.2952 - F1: 0.2770
sub_14:Test (Best Model) - Loss: 1.5913 - Accuracy: 0.2762 - F1: 0.2637
sub_14:Test (Best Model) - Loss: 1.5684 - Accuracy: 0.2714 - F1: 0.2350
sub_14:Test (Best Model) - Loss: 1.5138 - Accuracy: 0.3238 - F1: 0.3200
sub_14:Test (Best Model) - Loss: 1.5575 - Accuracy: 0.2762 - F1: 0.2732
sub_14:Test (Best Model) - Loss: 1.5643 - Accuracy: 0.2667 - F1: 0.2607
sub_14:Test (Best Model) - Loss: 1.5279 - Accuracy: 0.3333 - F1: 0.2756
sub_14:Test (Best Model) - Loss: 1.5393 - Accuracy: 0.2619 - F1: 0.2078
sub_14:Test (Best Model) - Loss: 1.5320 - Accuracy: 0.3048 - F1: 0.2667
sub_14:Test (Best Model) - Loss: 1.5245 - Accuracy: 0.3190 - F1: 0.2769
sub_14:Test (Best Model) - Loss: 1.5564 - Accuracy: 0.2714 - F1: 0.2424
sub_14:Test (Best Model) - Loss: 1.5660 - Accuracy: 0.2810 - F1: 0.2662
sub_14:Test (Best Model) - Loss: 1.5700 - Accuracy: 0.2571 - F1: 0.2083
sub_14:Test (Best Model) - Loss: 1.5643 - Accuracy: 0.2619 - F1: 0.2325
sub_14:Test (Best Model) - Loss: 1.5730 - Accuracy: 0.2857 - F1: 0.2709
sub_14:Test (Best Model) - Loss: 1.5928 - Accuracy: 0.2381 - F1: 0.2177

=== Summary Results ===

acc: 26.65 ± 2.58
F1: 25.50 ± 2.65
acc-in: 30.15 ± 2.34
F1-in: 29.15 ± 2.65
