diff --git a/train.py b/train.py
index 9551db3c..2099dd60 100644
--- a/train.py
+++ b/train.py
@@ -93,11 +93,11 @@ def train(
     scheduler = optim.lr_scheduler.LambdaLR(optimizer, lr_lambda=lf, last_epoch=start_epoch - 1)
     # scheduler = optim.lr_scheduler.MultiStepLR(optimizer, milestones=[218, 245], gamma=0.1, last_epoch=start_epoch - 1)
 
-    # y = []
-    # for epoch in range(epochs):
-    #     scheduler.step()
-    #     y.append(optimizer.param_groups[0]['lr'])
-    # plt.plot(y)
+    y = []
+    for _ in range(epochs):
+        scheduler.step()
+        y.append(optimizer.param_groups[0]['lr'])
+    plt.plot(y)
 
     # Dataset
     dataset = LoadImagesAndLabels(train_path, img_size=img_size, augment=True)
@@ -246,11 +246,11 @@ def train(
 def print_mutation(hyp, results):
     # Write mutation results
     a = '%11s' * len(hyp) % tuple(hyp.keys())  # hyperparam keys
-    b = '%11.3g' * len(results) % results  # results (P, R, mAP, F1, test_loss)
-    c = '%11.4g' * len(hyp) % tuple(hyp.values())  # hyperparam values
+    b = '%11.4g' * len(hyp) % tuple(hyp.values())  # hyperparam values
+    c = '%11.3g' * len(results) % results  # results (P, R, mAP, F1, test_loss)
     print('\n%s\n%s\nEvolved fitness: %s\n' % (a, b, c))
     with open('evolve.txt', 'a') as f:
-        f.write(a + b + '\n')
+        f.write(c + a + '\n')
 
 
 if __name__ == '__main__':