Finetuning/reports/resnet50-finetunned.csv

1	accuracy	macro_precision	macro_recall	macro_f1	weighted_precision	weighted_recall	weighted_f1
2	0.9333	0.9500	0.9333	0.9264	0.9500	0.9333	0.9264
3	0.9167	0.9425	0.9167	0.9111	0.9425	0.9167	0.9111
4	0.9333	0.9500	0.9333	0.9264	0.9500	0.9333	0.9264
5	0.8667	0.9050	0.8667	0.8625	0.9050	0.8667	0.8625
6	0.9000	0.9208	0.9000	0.8976	0.9208	0.9000	0.8976
7	0.9000	0.9208	0.9000	0.8926	0.9208	0.9000	0.8926
8	0.9667	0.9750	0.9667	0.9657	0.9750	0.9667	0.9657
9	0.9000	0.9308	0.9000	0.9012	0.9308	0.9000	0.9012
10	0.9833	0.9875	0.9833	0.9829	0.9875	0.9833	0.9829
11	0.9500	0.9625	0.9500	0.9486	0.9625	0.9500	0.9486
12	0.8667	0.9008	0.8667	0.8551	0.9008	0.8667	0.8551
13	0.9167	0.9375	0.9167	0.9093	0.9375	0.9167	0.9093
14	0.9000	0.9250	0.9000	0.8921	0.9250	0.9000	0.8921
15	0.9000	0.9333	0.9000	0.9024	0.9333	0.9000	0.9024
16	0.9500	0.9625	0.9500	0.9486	0.9625	0.9500	0.9486
17	0.9167	0.9333	0.9167	0.9148	0.9333	0.9167	0.9148
18	0.9167	0.9375	0.9167	0.9143	0.9375	0.9167	0.9143
19	0.9667	0.9750	0.9667	0.9657	0.9750	0.9667	0.9657
20	0.9333	0.9500	0.9333	0.9314	0.9500	0.9333	0.9314
21	0.9000	0.9350	0.9000	0.8957	0.9350	0.9000	0.8957
22	0.9000	0.9350	0.9000	0.9007	0.9350	0.9000	0.9007