diff --git "a/4.28 \354\213\244\355\227\230 \353\252\251\353\241\235.md" "b/4.28 \354\213\244\355\227\230 \353\252\251\353\241\235.md"
index c437bb0..adb9b75 100644
--- "a/4.28 \354\213\244\355\227\230 \353\252\251\353\241\235.md"	
+++ "b/4.28 \354\213\244\355\227\230 \353\252\251\353\241\235.md"	
@@ -22,9 +22,9 @@ CrossEntropyLoss 기준 대체적으로 train_loss < 0.1 부터 오버피팅되
 |모델|loss|배치|시드|time|epoch|loss|val_loss|val_mIoU|LB score|
 |------|---|---|---|---|---|---|---|---|---|
 |DLV3+, resnext50|CE|8|77|0.45s|12|0.103|0.343|0.434|0.5640|
-|"|(1-mIoU)*0.4|"|"|"|14|0.204|0.428|0.431|0.5653|
+|"|(1-mIoU)*0.4|"|"|"|11|0.204|0.428|0.431|0.5653|
 |"|(1-mIoU)*0.7|"|"|"|14||0.510|0.417|-|
-|"|(1-mIoU)*0.2|"|"|"||||||
+|"|(1-mIoU)*0.2|"|"|"|13||0.394|0.431|-|
 
 
 ## 기타 loss Function