lr: 0.0001
sub_1:Test (Best Model) - Loss: 1.6139 - Accuracy: 0.1714 - F1: 0.1088
sub_1:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.1714 - F1: 0.0798
sub_1:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2000 - F1: 0.1076
sub_1:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.2000 - F1: 0.1111
sub_1:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.2190 - F1: 0.1061
sub_1:Test (Best Model) - Loss: 1.6062 - Accuracy: 0.2048 - F1: 0.1215
sub_1:Test (Best Model) - Loss: 1.6155 - Accuracy: 0.1952 - F1: 0.0957
sub_1:Test (Best Model) - Loss: 1.6163 - Accuracy: 0.0952 - F1: 0.0657
sub_1:Test (Best Model) - Loss: 1.6123 - Accuracy: 0.2095 - F1: 0.1123
sub_1:Test (Best Model) - Loss: 1.6085 - Accuracy: 0.2095 - F1: 0.0852
sub_1:Test (Best Model) - Loss: 1.6069 - Accuracy: 0.2143 - F1: 0.1156
sub_1:Test (Best Model) - Loss: 1.6089 - Accuracy: 0.2048 - F1: 0.0831
sub_1:Test (Best Model) - Loss: 1.6081 - Accuracy: 0.2190 - F1: 0.1446
sub_1:Test (Best Model) - Loss: 1.6090 - Accuracy: 0.1952 - F1: 0.0653
sub_1:Test (Best Model) - Loss: 1.6087 - Accuracy: 0.2000 - F1: 0.1126
sub_2:Test (Best Model) - Loss: 1.5420 - Accuracy: 0.3762 - F1: 0.2841
sub_2:Test (Best Model) - Loss: 1.5711 - Accuracy: 0.4000 - F1: 0.3102
sub_2:Test (Best Model) - Loss: 1.5673 - Accuracy: 0.3524 - F1: 0.2088
sub_2:Test (Best Model) - Loss: 1.5820 - Accuracy: 0.3381 - F1: 0.2613
sub_2:Test (Best Model) - Loss: 1.5555 - Accuracy: 0.3810 - F1: 0.3014
sub_2:Test (Best Model) - Loss: 1.5790 - Accuracy: 0.3190 - F1: 0.2634
sub_2:Test (Best Model) - Loss: 1.5767 - Accuracy: 0.3619 - F1: 0.3120
sub_2:Test (Best Model) - Loss: 1.5787 - Accuracy: 0.3619 - F1: 0.2484
sub_2:Test (Best Model) - Loss: 1.5806 - Accuracy: 0.3238 - F1: 0.2035
sub_2:Test (Best Model) - Loss: 1.5799 - Accuracy: 0.3381 - F1: 0.2447
sub_2:Test (Best Model) - Loss: 1.5725 - Accuracy: 0.2571 - F1: 0.1935
sub_2:Test (Best Model) - Loss: 1.5656 - Accuracy: 0.2714 - F1: 0.2118
sub_2:Test (Best Model) - Loss: 1.5715 - Accuracy: 0.2714 - F1: 0.1925
sub_2:Test (Best Model) - Loss: 1.5738 - Accuracy: 0.2810 - F1: 0.1897
sub_2:Test (Best Model) - Loss: 1.5725 - Accuracy: 0.3048 - F1: 0.2367
sub_3:Test (Best Model) - Loss: 1.6046 - Accuracy: 0.2190 - F1: 0.1258
sub_3:Test (Best Model) - Loss: 1.6072 - Accuracy: 0.1952 - F1: 0.1004
sub_3:Test (Best Model) - Loss: 1.6081 - Accuracy: 0.2714 - F1: 0.1660
sub_3:Test (Best Model) - Loss: 1.6089 - Accuracy: 0.2000 - F1: 0.1707
sub_3:Test (Best Model) - Loss: 1.6067 - Accuracy: 0.2476 - F1: 0.1550
sub_3:Test (Best Model) - Loss: 1.6046 - Accuracy: 0.2524 - F1: 0.2176
sub_3:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.1952 - F1: 0.0675
sub_3:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.2095 - F1: 0.1094
sub_3:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.1905 - F1: 0.1165
sub_3:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2190 - F1: 0.1518
sub_3:Test (Best Model) - Loss: 1.6090 - Accuracy: 0.2333 - F1: 0.1851
sub_3:Test (Best Model) - Loss: 1.6081 - Accuracy: 0.2095 - F1: 0.1623
sub_3:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.1952 - F1: 0.1477
sub_3:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.2048 - F1: 0.1628
sub_3:Test (Best Model) - Loss: 1.6089 - Accuracy: 0.1952 - F1: 0.1365
sub_4:Test (Best Model) - Loss: 1.6074 - Accuracy: 0.2571 - F1: 0.1510
sub_4:Test (Best Model) - Loss: 1.6086 - Accuracy: 0.2000 - F1: 0.0672
sub_4:Test (Best Model) - Loss: 1.6041 - Accuracy: 0.2524 - F1: 0.1531
sub_4:Test (Best Model) - Loss: 1.6058 - Accuracy: 0.2381 - F1: 0.1836
sub_4:Test (Best Model) - Loss: 1.6071 - Accuracy: 0.2381 - F1: 0.1315
sub_4:Test (Best Model) - Loss: 1.6080 - Accuracy: 0.2143 - F1: 0.1232
sub_4:Test (Best Model) - Loss: 1.6017 - Accuracy: 0.2524 - F1: 0.2238
sub_4:Test (Best Model) - Loss: 1.5836 - Accuracy: 0.3619 - F1: 0.2441
sub_4:Test (Best Model) - Loss: 1.6043 - Accuracy: 0.3048 - F1: 0.2444
sub_4:Test (Best Model) - Loss: 1.6076 - Accuracy: 0.2143 - F1: 0.1365
sub_4:Test (Best Model) - Loss: 1.6023 - Accuracy: 0.2952 - F1: 0.2449
sub_4:Test (Best Model) - Loss: 1.6081 - Accuracy: 0.2143 - F1: 0.1555
sub_4:Test (Best Model) - Loss: 1.6077 - Accuracy: 0.2143 - F1: 0.1427
sub_4:Test (Best Model) - Loss: 1.6083 - Accuracy: 0.1857 - F1: 0.1053
sub_4:Test (Best Model) - Loss: 1.6078 - Accuracy: 0.2000 - F1: 0.1522
sub_5:Test (Best Model) - Loss: 1.6073 - Accuracy: 0.2048 - F1: 0.1230
sub_5:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.1619 - F1: 0.1028
sub_5:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.1857 - F1: 0.1008
sub_5:Test (Best Model) - Loss: 1.6087 - Accuracy: 0.1524 - F1: 0.0812
sub_5:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.1952 - F1: 0.1254
sub_5:Test (Best Model) - Loss: 1.6069 - Accuracy: 0.2476 - F1: 0.1385
sub_5:Test (Best Model) - Loss: 1.6067 - Accuracy: 0.2238 - F1: 0.1817
sub_5:Test (Best Model) - Loss: 1.6079 - Accuracy: 0.2571 - F1: 0.1795
sub_5:Test (Best Model) - Loss: 1.6054 - Accuracy: 0.2286 - F1: 0.1658
sub_5:Test (Best Model) - Loss: 1.6083 - Accuracy: 0.1857 - F1: 0.1289
sub_5:Test (Best Model) - Loss: 1.5994 - Accuracy: 0.3048 - F1: 0.2307
sub_5:Test (Best Model) - Loss: 1.5956 - Accuracy: 0.2286 - F1: 0.1831
sub_5:Test (Best Model) - Loss: 1.6006 - Accuracy: 0.2048 - F1: 0.1293
sub_5:Test (Best Model) - Loss: 1.5954 - Accuracy: 0.3238 - F1: 0.2690
sub_5:Test (Best Model) - Loss: 1.6002 - Accuracy: 0.2286 - F1: 0.1519
sub_6:Test (Best Model) - Loss: 1.5914 - Accuracy: 0.2905 - F1: 0.2495
sub_6:Test (Best Model) - Loss: 1.6065 - Accuracy: 0.2000 - F1: 0.1672
sub_6:Test (Best Model) - Loss: 1.6071 - Accuracy: 0.2762 - F1: 0.2179
sub_6:Test (Best Model) - Loss: 1.5943 - Accuracy: 0.2333 - F1: 0.1768
sub_6:Test (Best Model) - Loss: 1.6027 - Accuracy: 0.2429 - F1: 0.1967
sub_6:Test (Best Model) - Loss: 1.5865 - Accuracy: 0.2571 - F1: 0.1814
sub_6:Test (Best Model) - Loss: 1.6043 - Accuracy: 0.2286 - F1: 0.1825
sub_6:Test (Best Model) - Loss: 1.6027 - Accuracy: 0.2524 - F1: 0.1568
sub_6:Test (Best Model) - Loss: 1.5834 - Accuracy: 0.2381 - F1: 0.1484
sub_6:Test (Best Model) - Loss: 1.6068 - Accuracy: 0.2714 - F1: 0.1620
sub_6:Test (Best Model) - Loss: 1.6068 - Accuracy: 0.2429 - F1: 0.1851
sub_6:Test (Best Model) - Loss: 1.5931 - Accuracy: 0.2524 - F1: 0.1904
sub_6:Test (Best Model) - Loss: 1.6075 - Accuracy: 0.2048 - F1: 0.0839
sub_6:Test (Best Model) - Loss: 1.5964 - Accuracy: 0.2857 - F1: 0.2067
sub_6:Test (Best Model) - Loss: 1.6080 - Accuracy: 0.2571 - F1: 0.1821
sub_7:Test (Best Model) - Loss: 1.6442 - Accuracy: 0.1429 - F1: 0.0745
sub_7:Test (Best Model) - Loss: 1.6441 - Accuracy: 0.1190 - F1: 0.0654
sub_7:Test (Best Model) - Loss: 1.6498 - Accuracy: 0.1762 - F1: 0.0843
sub_7:Test (Best Model) - Loss: 1.6363 - Accuracy: 0.1381 - F1: 0.0948
sub_7:Test (Best Model) - Loss: 1.6253 - Accuracy: 0.1476 - F1: 0.0930
sub_7:Test (Best Model) - Loss: 1.6235 - Accuracy: 0.1857 - F1: 0.1336
sub_7:Test (Best Model) - Loss: 1.6190 - Accuracy: 0.2286 - F1: 0.1777
sub_7:Test (Best Model) - Loss: 1.6216 - Accuracy: 0.1905 - F1: 0.1088
sub_7:Test (Best Model) - Loss: 1.6133 - Accuracy: 0.1905 - F1: 0.1242
sub_7:Test (Best Model) - Loss: 1.6320 - Accuracy: 0.1619 - F1: 0.1556
sub_7:Test (Best Model) - Loss: 1.6119 - Accuracy: 0.1714 - F1: 0.0913
sub_7:Test (Best Model) - Loss: 1.6070 - Accuracy: 0.2190 - F1: 0.1594
sub_7:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.1762 - F1: 0.1150
sub_7:Test (Best Model) - Loss: 1.6043 - Accuracy: 0.2286 - F1: 0.1834
sub_7:Test (Best Model) - Loss: 1.6145 - Accuracy: 0.2190 - F1: 0.1447
sub_8:Test (Best Model) - Loss: 1.5983 - Accuracy: 0.2333 - F1: 0.1445
sub_8:Test (Best Model) - Loss: 1.6099 - Accuracy: 0.2095 - F1: 0.1478
sub_8:Test (Best Model) - Loss: 1.6023 - Accuracy: 0.2095 - F1: 0.0955
sub_8:Test (Best Model) - Loss: 1.6062 - Accuracy: 0.2095 - F1: 0.0914
sub_8:Test (Best Model) - Loss: 1.6024 - Accuracy: 0.2048 - F1: 0.0814
sub_8:Test (Best Model) - Loss: 1.6030 - Accuracy: 0.2429 - F1: 0.1513
sub_8:Test (Best Model) - Loss: 1.6073 - Accuracy: 0.2048 - F1: 0.1461
sub_8:Test (Best Model) - Loss: 1.5981 - Accuracy: 0.2571 - F1: 0.1969
sub_8:Test (Best Model) - Loss: 1.6063 - Accuracy: 0.2238 - F1: 0.1709
sub_8:Test (Best Model) - Loss: 1.6006 - Accuracy: 0.2857 - F1: 0.2143
sub_8:Test (Best Model) - Loss: 1.6016 - Accuracy: 0.2286 - F1: 0.1327
sub_8:Test (Best Model) - Loss: 1.5984 - Accuracy: 0.2810 - F1: 0.2419
sub_8:Test (Best Model) - Loss: 1.5975 - Accuracy: 0.2714 - F1: 0.1532
sub_8:Test (Best Model) - Loss: 1.5953 - Accuracy: 0.2952 - F1: 0.2223
sub_8:Test (Best Model) - Loss: 1.5982 - Accuracy: 0.2714 - F1: 0.1821
sub_9:Test (Best Model) - Loss: 1.6097 - Accuracy: 0.1905 - F1: 0.1076
sub_9:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6088 - Accuracy: 0.1810 - F1: 0.0984
sub_9:Test (Best Model) - Loss: 1.6101 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 1.6087 - Accuracy: 0.2143 - F1: 0.0921
sub_9:Test (Best Model) - Loss: 1.6114 - Accuracy: 0.1857 - F1: 0.1238
sub_9:Test (Best Model) - Loss: 1.6086 - Accuracy: 0.2476 - F1: 0.1997
sub_9:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.1810 - F1: 0.1371
sub_9:Test (Best Model) - Loss: 1.6110 - Accuracy: 0.2095 - F1: 0.1402
sub_9:Test (Best Model) - Loss: 1.6135 - Accuracy: 0.2048 - F1: 0.1681
sub_9:Test (Best Model) - Loss: 1.6098 - Accuracy: 0.1857 - F1: 0.1202
sub_9:Test (Best Model) - Loss: 1.6102 - Accuracy: 0.1714 - F1: 0.0679
sub_9:Test (Best Model) - Loss: 1.6103 - Accuracy: 0.2286 - F1: 0.2004
sub_9:Test (Best Model) - Loss: 1.6085 - Accuracy: 0.1952 - F1: 0.1091
sub_9:Test (Best Model) - Loss: 1.6087 - Accuracy: 0.2238 - F1: 0.1512
sub_10:Test (Best Model) - Loss: 1.6078 - Accuracy: 0.2476 - F1: 0.1509
sub_10:Test (Best Model) - Loss: 1.6090 - Accuracy: 0.1810 - F1: 0.1190
sub_10:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2476 - F1: 0.1541
sub_10:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.2190 - F1: 0.1623
sub_10:Test (Best Model) - Loss: 1.6108 - Accuracy: 0.2333 - F1: 0.1600
sub_10:Test (Best Model) - Loss: 1.6050 - Accuracy: 0.2857 - F1: 0.2055
sub_10:Test (Best Model) - Loss: 1.6039 - Accuracy: 0.2048 - F1: 0.0766
sub_10:Test (Best Model) - Loss: 1.6095 - Accuracy: 0.1810 - F1: 0.0755
sub_10:Test (Best Model) - Loss: 1.6060 - Accuracy: 0.2714 - F1: 0.1678
sub_10:Test (Best Model) - Loss: 1.6081 - Accuracy: 0.2048 - F1: 0.0768
sub_10:Test (Best Model) - Loss: 1.6050 - Accuracy: 0.2381 - F1: 0.1668
sub_10:Test (Best Model) - Loss: 1.6078 - Accuracy: 0.1952 - F1: 0.1117
sub_10:Test (Best Model) - Loss: 1.6071 - Accuracy: 0.2286 - F1: 0.1220
sub_10:Test (Best Model) - Loss: 1.6059 - Accuracy: 0.2286 - F1: 0.1280
sub_10:Test (Best Model) - Loss: 1.6071 - Accuracy: 0.2381 - F1: 0.1645
sub_11:Test (Best Model) - Loss: 1.6040 - Accuracy: 0.2667 - F1: 0.1665
sub_11:Test (Best Model) - Loss: 1.6011 - Accuracy: 0.2762 - F1: 0.2040
sub_11:Test (Best Model) - Loss: 1.6008 - Accuracy: 0.3238 - F1: 0.2569
sub_11:Test (Best Model) - Loss: 1.6066 - Accuracy: 0.2238 - F1: 0.1285
sub_11:Test (Best Model) - Loss: 1.5998 - Accuracy: 0.2381 - F1: 0.1649
sub_11:Test (Best Model) - Loss: 1.6147 - Accuracy: 0.2143 - F1: 0.1594
sub_11:Test (Best Model) - Loss: 1.6067 - Accuracy: 0.2000 - F1: 0.1666
sub_11:Test (Best Model) - Loss: 1.6093 - Accuracy: 0.1857 - F1: 0.1121
sub_11:Test (Best Model) - Loss: 1.6112 - Accuracy: 0.2143 - F1: 0.1822
sub_11:Test (Best Model) - Loss: 1.6132 - Accuracy: 0.1857 - F1: 0.1402
sub_11:Test (Best Model) - Loss: 1.6120 - Accuracy: 0.2000 - F1: 0.1358
sub_11:Test (Best Model) - Loss: 1.6153 - Accuracy: 0.2190 - F1: 0.1712
sub_11:Test (Best Model) - Loss: 1.6076 - Accuracy: 0.2476 - F1: 0.1814
sub_11:Test (Best Model) - Loss: 1.6132 - Accuracy: 0.2048 - F1: 0.1247
sub_11:Test (Best Model) - Loss: 1.6146 - Accuracy: 0.1905 - F1: 0.1302
sub_12:Test (Best Model) - Loss: 1.6085 - Accuracy: 0.2000 - F1: 0.1345
sub_12:Test (Best Model) - Loss: 1.6120 - Accuracy: 0.2000 - F1: 0.1288
sub_12:Test (Best Model) - Loss: 1.6161 - Accuracy: 0.2095 - F1: 0.1029
sub_12:Test (Best Model) - Loss: 1.6092 - Accuracy: 0.2429 - F1: 0.1387
sub_12:Test (Best Model) - Loss: 1.6104 - Accuracy: 0.2095 - F1: 0.1156
sub_12:Test (Best Model) - Loss: 1.6082 - Accuracy: 0.2524 - F1: 0.2123
sub_12:Test (Best Model) - Loss: 1.6110 - Accuracy: 0.2714 - F1: 0.2322
sub_12:Test (Best Model) - Loss: 1.6180 - Accuracy: 0.1905 - F1: 0.1262
sub_12:Test (Best Model) - Loss: 1.6142 - Accuracy: 0.2429 - F1: 0.1949
sub_12:Test (Best Model) - Loss: 1.6211 - Accuracy: 0.1952 - F1: 0.1659
sub_12:Test (Best Model) - Loss: 1.6100 - Accuracy: 0.2048 - F1: 0.1144
sub_12:Test (Best Model) - Loss: 1.6226 - Accuracy: 0.1905 - F1: 0.1236
sub_12:Test (Best Model) - Loss: 1.6158 - Accuracy: 0.1857 - F1: 0.1254
sub_12:Test (Best Model) - Loss: 1.6203 - Accuracy: 0.2429 - F1: 0.2354
sub_12:Test (Best Model) - Loss: 1.6124 - Accuracy: 0.2190 - F1: 0.1319
sub_13:Test (Best Model) - Loss: 1.6001 - Accuracy: 0.2857 - F1: 0.2579
sub_13:Test (Best Model) - Loss: 1.5983 - Accuracy: 0.2714 - F1: 0.2298
sub_13:Test (Best Model) - Loss: 1.5967 - Accuracy: 0.2667 - F1: 0.1866
sub_13:Test (Best Model) - Loss: 1.6014 - Accuracy: 0.2524 - F1: 0.2224
sub_13:Test (Best Model) - Loss: 1.5983 - Accuracy: 0.2238 - F1: 0.1805
sub_13:Test (Best Model) - Loss: 1.5901 - Accuracy: 0.2857 - F1: 0.2591
sub_13:Test (Best Model) - Loss: 1.5996 - Accuracy: 0.2857 - F1: 0.2574
sub_13:Test (Best Model) - Loss: 1.5920 - Accuracy: 0.2524 - F1: 0.1851
sub_13:Test (Best Model) - Loss: 1.6038 - Accuracy: 0.2524 - F1: 0.1453
sub_13:Test (Best Model) - Loss: 1.6000 - Accuracy: 0.2381 - F1: 0.1496
sub_13:Test (Best Model) - Loss: 1.5934 - Accuracy: 0.2571 - F1: 0.1812
sub_13:Test (Best Model) - Loss: 1.5920 - Accuracy: 0.2905 - F1: 0.2013
sub_13:Test (Best Model) - Loss: 1.5915 - Accuracy: 0.2857 - F1: 0.1668
sub_13:Test (Best Model) - Loss: 1.5817 - Accuracy: 0.3000 - F1: 0.2285
sub_13:Test (Best Model) - Loss: 1.5933 - Accuracy: 0.2667 - F1: 0.1886
sub_14:Test (Best Model) - Loss: 1.6075 - Accuracy: 0.1905 - F1: 0.1348
sub_14:Test (Best Model) - Loss: 1.6080 - Accuracy: 0.2143 - F1: 0.1472
sub_14:Test (Best Model) - Loss: 1.6083 - Accuracy: 0.2190 - F1: 0.1674
sub_14:Test (Best Model) - Loss: 1.6065 - Accuracy: 0.2143 - F1: 0.1529
sub_14:Test (Best Model) - Loss: 1.6094 - Accuracy: 0.2048 - F1: 0.1087
sub_14:Test (Best Model) - Loss: 1.6039 - Accuracy: 0.2429 - F1: 0.1785
sub_14:Test (Best Model) - Loss: 1.6056 - Accuracy: 0.2095 - F1: 0.1445
sub_14:Test (Best Model) - Loss: 1.6068 - Accuracy: 0.2190 - F1: 0.1058
sub_14:Test (Best Model) - Loss: 1.6077 - Accuracy: 0.2238 - F1: 0.1758
sub_14:Test (Best Model) - Loss: 1.6079 - Accuracy: 0.2286 - F1: 0.1746
sub_14:Test (Best Model) - Loss: 1.6105 - Accuracy: 0.1571 - F1: 0.1126
sub_14:Test (Best Model) - Loss: 1.6121 - Accuracy: 0.2048 - F1: 0.1588
sub_14:Test (Best Model) - Loss: 1.6113 - Accuracy: 0.1619 - F1: 0.1166
sub_14:Test (Best Model) - Loss: 1.6089 - Accuracy: 0.1905 - F1: 0.1373
sub_14:Test (Best Model) - Loss: 1.6086 - Accuracy: 0.2000 - F1: 0.1831

=== Summary Results ===

acc: 22.99 ± 3.55
F1: 15.62 ± 3.44
acc-in: 27.11 ± 3.74
F1-in: 18.34 ± 4.16
