lr: 1e-05
sub_1:Test (Best Model) - Loss: 0.8048 - Accuracy: 0.2000 - F1: 0.1146
sub_1:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.1810 - F1: 0.1326
sub_1:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2190 - F1: 0.1230
sub_1:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1619 - F1: 0.1135
sub_1:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.1163
sub_1:Test (Best Model) - Loss: 0.8054 - Accuracy: 0.1143 - F1: 0.0826
sub_1:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 0.8053 - Accuracy: 0.0952 - F1: 0.0571
sub_1:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.1044
sub_1:Test (Best Model) - Loss: 0.8043 - Accuracy: 0.2476 - F1: 0.1784
sub_1:Test (Best Model) - Loss: 0.8036 - Accuracy: 0.2286 - F1: 0.1773
sub_1:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_1:Test (Best Model) - Loss: 0.8043 - Accuracy: 0.2381 - F1: 0.1329
sub_1:Test (Best Model) - Loss: 0.8045 - Accuracy: 0.2095 - F1: 0.1203
sub_2:Test (Best Model) - Loss: 0.7588 - Accuracy: 0.4000 - F1: 0.2786
sub_2:Test (Best Model) - Loss: 0.7974 - Accuracy: 0.3905 - F1: 0.3266
sub_2:Test (Best Model) - Loss: 0.8016 - Accuracy: 0.3619 - F1: 0.2778
sub_2:Test (Best Model) - Loss: 0.7984 - Accuracy: 0.4762 - F1: 0.4516
sub_2:Test (Best Model) - Loss: 0.7614 - Accuracy: 0.3619 - F1: 0.2308
sub_2:Test (Best Model) - Loss: 0.7962 - Accuracy: 0.3619 - F1: 0.2681
sub_2:Test (Best Model) - Loss: 0.7961 - Accuracy: 0.3905 - F1: 0.2645
sub_2:Test (Best Model) - Loss: 0.7870 - Accuracy: 0.4095 - F1: 0.2956
sub_2:Test (Best Model) - Loss: 0.7884 - Accuracy: 0.4000 - F1: 0.3460
sub_2:Test (Best Model) - Loss: 0.7853 - Accuracy: 0.4095 - F1: 0.2773
sub_2:Test (Best Model) - Loss: 0.7561 - Accuracy: 0.3905 - F1: 0.2615
sub_2:Test (Best Model) - Loss: 0.7775 - Accuracy: 0.3524 - F1: 0.2200
sub_2:Test (Best Model) - Loss: 0.8027 - Accuracy: 0.4095 - F1: 0.3527
sub_2:Test (Best Model) - Loss: 0.7963 - Accuracy: 0.3524 - F1: 0.2855
sub_2:Test (Best Model) - Loss: 0.7948 - Accuracy: 0.3333 - F1: 0.2140
sub_3:Test (Best Model) - Loss: 0.8024 - Accuracy: 0.1905 - F1: 0.1541
sub_3:Test (Best Model) - Loss: 0.8049 - Accuracy: 0.1810 - F1: 0.1265
sub_3:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 0.8048 - Accuracy: 0.2095 - F1: 0.1015
sub_3:Test (Best Model) - Loss: 0.8045 - Accuracy: 0.1905 - F1: 0.1536
sub_3:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 0.7969 - Accuracy: 0.2571 - F1: 0.2263
sub_3:Test (Best Model) - Loss: 0.8048 - Accuracy: 0.2000 - F1: 0.1317
sub_3:Test (Best Model) - Loss: 0.7960 - Accuracy: 0.2762 - F1: 0.2368
sub_3:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_3:Test (Best Model) - Loss: 0.8001 - Accuracy: 0.2667 - F1: 0.1648
sub_3:Test (Best Model) - Loss: 0.8049 - Accuracy: 0.1905 - F1: 0.1044
sub_3:Test (Best Model) - Loss: 0.7997 - Accuracy: 0.2571 - F1: 0.1955
sub_4:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2381 - F1: 0.1767
sub_4:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 0.8023 - Accuracy: 0.2571 - F1: 0.2180
sub_4:Test (Best Model) - Loss: 0.7848 - Accuracy: 0.2857 - F1: 0.1724
sub_4:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_4:Test (Best Model) - Loss: 0.8045 - Accuracy: 0.1810 - F1: 0.1104
sub_4:Test (Best Model) - Loss: 0.7854 - Accuracy: 0.2857 - F1: 0.1815
sub_4:Test (Best Model) - Loss: 0.7984 - Accuracy: 0.2762 - F1: 0.2048
sub_4:Test (Best Model) - Loss: 0.8048 - Accuracy: 0.1905 - F1: 0.1486
sub_4:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2381 - F1: 0.1992
sub_4:Test (Best Model) - Loss: 0.7940 - Accuracy: 0.2762 - F1: 0.1930
sub_5:Test (Best Model) - Loss: 0.8042 - Accuracy: 0.1714 - F1: 0.1284
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0677
sub_5:Test (Best Model) - Loss: 0.8048 - Accuracy: 0.2000 - F1: 0.0672
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2286 - F1: 0.1286
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2476 - F1: 0.1538
sub_5:Test (Best Model) - Loss: 0.8033 - Accuracy: 0.2381 - F1: 0.2192
sub_5:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2476 - F1: 0.1618
sub_5:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1810 - F1: 0.0998
sub_5:Test (Best Model) - Loss: 0.8034 - Accuracy: 0.2095 - F1: 0.1613
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.1093
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.0851
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 0.8048 - Accuracy: 0.2095 - F1: 0.1425
sub_6:Test (Best Model) - Loss: 0.8049 - Accuracy: 0.1810 - F1: 0.1332
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.1076
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1905 - F1: 0.0937
sub_6:Test (Best Model) - Loss: 0.8045 - Accuracy: 0.2476 - F1: 0.1926
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2381 - F1: 0.1369
sub_6:Test (Best Model) - Loss: 0.8040 - Accuracy: 0.2095 - F1: 0.1325
sub_6:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1810 - F1: 0.0748
sub_7:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2190 - F1: 0.1330
sub_7:Test (Best Model) - Loss: 0.8036 - Accuracy: 0.2476 - F1: 0.2289
sub_7:Test (Best Model) - Loss: 0.8012 - Accuracy: 0.2381 - F1: 0.1522
sub_7:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2571 - F1: 0.2289
sub_7:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.1524 - F1: 0.1479
sub_7:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.0943
sub_7:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0672
sub_7:Test (Best Model) - Loss: 0.8045 - Accuracy: 0.2476 - F1: 0.1695
sub_7:Test (Best Model) - Loss: 0.8041 - Accuracy: 0.2857 - F1: 0.2779
sub_7:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_7:Test (Best Model) - Loss: 0.8028 - Accuracy: 0.2667 - F1: 0.2308
sub_7:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.0854
sub_7:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.0851
sub_8:Test (Best Model) - Loss: 0.7982 - Accuracy: 0.3810 - F1: 0.3039
sub_8:Test (Best Model) - Loss: 0.7967 - Accuracy: 0.2762 - F1: 0.1825
sub_8:Test (Best Model) - Loss: 0.7948 - Accuracy: 0.3143 - F1: 0.2112
sub_8:Test (Best Model) - Loss: 0.7799 - Accuracy: 0.3619 - F1: 0.2626
sub_8:Test (Best Model) - Loss: 0.7795 - Accuracy: 0.3048 - F1: 0.1899
sub_8:Test (Best Model) - Loss: 0.7773 - Accuracy: 0.3524 - F1: 0.2409
sub_8:Test (Best Model) - Loss: 0.7725 - Accuracy: 0.3238 - F1: 0.2351
sub_8:Test (Best Model) - Loss: 0.7983 - Accuracy: 0.3048 - F1: 0.2081
sub_8:Test (Best Model) - Loss: 0.8005 - Accuracy: 0.3048 - F1: 0.2420
sub_8:Test (Best Model) - Loss: 0.8044 - Accuracy: 0.2667 - F1: 0.1600
sub_8:Test (Best Model) - Loss: 0.7993 - Accuracy: 0.4000 - F1: 0.3282
sub_8:Test (Best Model) - Loss: 0.7840 - Accuracy: 0.4190 - F1: 0.3407
sub_8:Test (Best Model) - Loss: 0.8008 - Accuracy: 0.3333 - F1: 0.2526
sub_8:Test (Best Model) - Loss: 0.7975 - Accuracy: 0.3810 - F1: 0.3257
sub_8:Test (Best Model) - Loss: 0.8040 - Accuracy: 0.3143 - F1: 0.2585
sub_9:Test (Best Model) - Loss: 0.8021 - Accuracy: 0.2571 - F1: 0.1978
sub_9:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 0.8036 - Accuracy: 0.1905 - F1: 0.1401
sub_9:Test (Best Model) - Loss: 0.8043 - Accuracy: 0.2286 - F1: 0.2027
sub_9:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2190 - F1: 0.1877
sub_9:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.1714 - F1: 0.1170
sub_9:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 0.7958 - Accuracy: 0.2667 - F1: 0.2354
sub_9:Test (Best Model) - Loss: 0.7947 - Accuracy: 0.2952 - F1: 0.2304
sub_9:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_9:Test (Best Model) - Loss: 0.8041 - Accuracy: 0.2476 - F1: 0.1959
sub_10:Test (Best Model) - Loss: 0.7981 - Accuracy: 0.2381 - F1: 0.1766
sub_10:Test (Best Model) - Loss: 0.7960 - Accuracy: 0.2667 - F1: 0.1640
sub_10:Test (Best Model) - Loss: 0.8040 - Accuracy: 0.2381 - F1: 0.1491
sub_10:Test (Best Model) - Loss: 0.7928 - Accuracy: 0.2571 - F1: 0.1935
sub_10:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2095 - F1: 0.1246
sub_10:Test (Best Model) - Loss: 0.8033 - Accuracy: 0.2381 - F1: 0.1993
sub_10:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0672
sub_10:Test (Best Model) - Loss: 0.8028 - Accuracy: 0.2286 - F1: 0.1331
sub_10:Test (Best Model) - Loss: 0.8054 - Accuracy: 0.2476 - F1: 0.2315
sub_10:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2095 - F1: 0.0992
sub_10:Test (Best Model) - Loss: 0.8022 - Accuracy: 0.2857 - F1: 0.1986
sub_10:Test (Best Model) - Loss: 0.7951 - Accuracy: 0.2667 - F1: 0.1952
sub_10:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2000 - F1: 0.0677
sub_10:Test (Best Model) - Loss: 0.8027 - Accuracy: 0.2381 - F1: 0.1956
sub_10:Test (Best Model) - Loss: 0.7967 - Accuracy: 0.1905 - F1: 0.1608
sub_11:Test (Best Model) - Loss: 0.8017 - Accuracy: 0.2952 - F1: 0.2800
sub_11:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0924
sub_11:Test (Best Model) - Loss: 0.7969 - Accuracy: 0.3524 - F1: 0.2831
sub_11:Test (Best Model) - Loss: 0.8020 - Accuracy: 0.3333 - F1: 0.2535
sub_11:Test (Best Model) - Loss: 0.8045 - Accuracy: 0.3238 - F1: 0.1972
sub_11:Test (Best Model) - Loss: 0.7786 - Accuracy: 0.3143 - F1: 0.2120
sub_11:Test (Best Model) - Loss: 0.7995 - Accuracy: 0.2952 - F1: 0.2096
sub_11:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.1441
sub_11:Test (Best Model) - Loss: 0.8008 - Accuracy: 0.2667 - F1: 0.2088
sub_11:Test (Best Model) - Loss: 0.8043 - Accuracy: 0.2381 - F1: 0.2334
sub_11:Test (Best Model) - Loss: 0.7683 - Accuracy: 0.3333 - F1: 0.1947
sub_11:Test (Best Model) - Loss: 0.7985 - Accuracy: 0.2952 - F1: 0.2470
sub_11:Test (Best Model) - Loss: 0.7869 - Accuracy: 0.2857 - F1: 0.2238
sub_11:Test (Best Model) - Loss: 0.7918 - Accuracy: 0.3238 - F1: 0.2894
sub_11:Test (Best Model) - Loss: 0.8045 - Accuracy: 0.2190 - F1: 0.1304
sub_12:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0909
sub_12:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2286 - F1: 0.1361
sub_12:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.1810 - F1: 0.0613
sub_12:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2095 - F1: 0.1058
sub_12:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0815
sub_12:Test (Best Model) - Loss: 0.8037 - Accuracy: 0.2381 - F1: 0.1626
sub_12:Test (Best Model) - Loss: 0.8068 - Accuracy: 0.1524 - F1: 0.1254
sub_12:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_12:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2190 - F1: 0.1104
sub_12:Test (Best Model) - Loss: 0.8050 - Accuracy: 0.2286 - F1: 0.1466
sub_12:Test (Best Model) - Loss: 0.7975 - Accuracy: 0.2286 - F1: 0.1628
sub_12:Test (Best Model) - Loss: 0.8039 - Accuracy: 0.1714 - F1: 0.1393
sub_12:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2667 - F1: 0.1551
sub_12:Test (Best Model) - Loss: 0.8045 - Accuracy: 0.1905 - F1: 0.1258
sub_12:Test (Best Model) - Loss: 0.8044 - Accuracy: 0.2476 - F1: 0.1441
sub_13:Test (Best Model) - Loss: 0.8021 - Accuracy: 0.2476 - F1: 0.1400
sub_13:Test (Best Model) - Loss: 0.8017 - Accuracy: 0.2571 - F1: 0.1417
sub_13:Test (Best Model) - Loss: 0.8040 - Accuracy: 0.2476 - F1: 0.1341
sub_13:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2286 - F1: 0.1206
sub_13:Test (Best Model) - Loss: 0.8035 - Accuracy: 0.1714 - F1: 0.1306
sub_13:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2667 - F1: 0.1706
sub_13:Test (Best Model) - Loss: 0.7985 - Accuracy: 0.3143 - F1: 0.1907
sub_13:Test (Best Model) - Loss: 0.8043 - Accuracy: 0.3143 - F1: 0.1819
sub_13:Test (Best Model) - Loss: 0.8047 - Accuracy: 0.2000 - F1: 0.0667
sub_13:Test (Best Model) - Loss: 0.8042 - Accuracy: 0.2762 - F1: 0.1739
sub_13:Test (Best Model) - Loss: 0.8012 - Accuracy: 0.3143 - F1: 0.2064
sub_13:Test (Best Model) - Loss: 0.8033 - Accuracy: 0.3048 - F1: 0.2108
sub_13:Test (Best Model) - Loss: 0.8044 - Accuracy: 0.2952 - F1: 0.1677
sub_13:Test (Best Model) - Loss: 0.8024 - Accuracy: 0.3048 - F1: 0.2382
sub_13:Test (Best Model) - Loss: 0.8010 - Accuracy: 0.3048 - F1: 0.1932
sub_14:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2095 - F1: 0.1235
sub_14:Test (Best Model) - Loss: 0.8025 - Accuracy: 0.2381 - F1: 0.1523
sub_14:Test (Best Model) - Loss: 0.7944 - Accuracy: 0.2667 - F1: 0.1624
sub_14:Test (Best Model) - Loss: 0.8034 - Accuracy: 0.1905 - F1: 0.1076
sub_14:Test (Best Model) - Loss: 0.7958 - Accuracy: 0.3048 - F1: 0.1959
sub_14:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2476 - F1: 0.1508
sub_14:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2571 - F1: 0.1574
sub_14:Test (Best Model) - Loss: 0.7906 - Accuracy: 0.3238 - F1: 0.2031
sub_14:Test (Best Model) - Loss: 0.7900 - Accuracy: 0.3333 - F1: 0.1953
sub_14:Test (Best Model) - Loss: 0.8046 - Accuracy: 0.2095 - F1: 0.1433
sub_14:Test (Best Model) - Loss: 0.8040 - Accuracy: 0.2190 - F1: 0.1726
sub_14:Test (Best Model) - Loss: 0.8003 - Accuracy: 0.2667 - F1: 0.1548
sub_14:Test (Best Model) - Loss: 0.8005 - Accuracy: 0.2476 - F1: 0.1765
sub_14:Test (Best Model) - Loss: 0.7740 - Accuracy: 0.3810 - F1: 0.3091
sub_14:Test (Best Model) - Loss: 0.7906 - Accuracy: 0.3905 - F1: 0.2687

=== Summary Results ===

acc:   24.90 ± 5.37
F1:    15.90 ± 5.42
acc-in:30.08 ± 5.47
F1-in: 20.97 ± 5.85
