diff --git "a/AerialImageSegmentation/Task5\357\274\232\346\250\241\345\236\213\350\256\255\347\273\203\344\270\216\351\252\214\350\257\201.md" "b/AerialImageSegmentation/Task5\357\274\232\346\250\241\345\236\213\350\256\255\347\273\203\344\270\216\351\252\214\350\257\201.md"
index 9a8b8b9..82cc36a 100644
--- "a/AerialImageSegmentation/Task5\357\274\232\346\250\241\345\236\213\350\256\255\347\273\203\344\270\216\351\252\214\350\257\201.md"
+++ "b/AerialImageSegmentation/Task5\357\274\232\346\250\241\345\236\213\350\256\255\347\273\203\344\270\216\351\252\214\350\257\201.md"
@@ -80,15 +80,15 @@ criterion = nn.CrossEntropyLoss(size_average=False)
 optimizer = torch.optim.Adam(model.parameters(), 0.001)
 best_loss = 1000.0
 for epoch in range(20):
-print('Epoch: ', epoch)
+    print('Epoch: ', epoch)
 
-train(train_loader, model, criterion, optimizer, epoch)
-val_loss = validate(val_loader, model, criterion)
+    train(train_loader, model, criterion, optimizer, epoch)
+    val_loss = validate(val_loader, model, criterion)
 
-# 记录下验证集精度
-if val_loss < best_loss:
-    best_loss = val_loss
-    torch.save(model.state_dict(), './model.pt')
+    # 记录下验证集精度
+    if val_loss < best_loss:
+        best_loss = val_loss
+        torch.save(model.state_dict(), './model.pt')
 ```
 
 其中每个Epoch的训练代码如下：