diff --git a/main.py b/main.py
index cd8556e94654b87dc3fbba68d36479e7e4ff12a8..64578b75a7bfd3f703f1bf368dbde9ffbf6766a6 100644
--- a/main.py
+++ b/main.py
@@ -73,23 +73,23 @@ def run(args):
     loss_function = nn.CrossEntropyLoss()
     optimizer = optim.SGD(model.parameters(), lr=0.001, momentum=0.9)
 
-    for e in range(args.epoches):
-        loss, acc = train(model,data_train,optimizer,loss_function,e)
-        train_loss.append(loss)
-        train_acc.append(acc)
-        if e%args.eval_inter==0 :
-            loss, acc = test(model,data_test,loss_function,e)
-            val_loss.append(loss)
-            val_acc.append(acc)
-            if acc > best_acc :
-                save_model(model,args.save_path)
-                best_acc = acc
-    plt.plot(train_acc)
-    plt.plot(val_acc)
-    plt.plot(train_acc)
-    plt.plot(train_acc)
-    plt.show()
-    plt.savefig('output/training_plot.png')
+    # for e in range(args.epoches):
+    #     loss, acc = train(model,data_train,optimizer,loss_function,e)
+    #     train_loss.append(loss)
+    #     train_acc.append(acc)
+    #     if e%args.eval_inter==0 :
+    #         loss, acc = test(model,data_test,loss_function,e)
+    #         val_loss.append(loss)
+    #         val_acc.append(acc)
+    #         if acc > best_acc :
+    #             save_model(model,args.save_path)
+    #             best_acc = acc
+    # plt.plot(train_acc)
+    # plt.plot(val_acc)
+    # plt.plot(train_acc)
+    # plt.plot(train_acc)
+    # plt.show()
+    # plt.savefig('output/training_plot.png')
 
     load_model(model, args.save_path)
     make_prediction(model,data_test)