diff --git a/utils/utils.py b/utils/utils.py
index a28ed5b3..0202b8f5 100755
--- a/utils/utils.py
+++ b/utils/utils.py
@@ -674,7 +674,7 @@ def kmeans_targets(path='../coco/trainvalno5k.txt', n=9, img_size=416):  # from
 def print_mutation(hyp, results, bucket=''):
     # Print mutation results to evolve.txt (for use with train.py --evolve)
     a = '%10s' * len(hyp) % tuple(hyp.keys())  # hyperparam keys
-    b = '%10.5g' * len(hyp) % tuple(hyp.values())  # hyperparam values
+    b = '%10.3g' * len(hyp) % tuple(hyp.values())  # hyperparam values
     c = '%10.3g' * len(results) % results  # results (P, R, mAP, F1, test_loss)
     print('\n%s\n%s\nEvolved fitness: %s\n' % (a, b, c))
 
@@ -684,7 +684,7 @@ def print_mutation(hyp, results, bucket=''):
     with open('evolve.txt', 'a') as f:  # append result
         f.write(c + b + '\n')
     x = np.unique(np.loadtxt('evolve.txt', ndmin=2), axis=0)  # load unique rows
-    np.savetxt('evolve.txt', x[np.argsort(-fitness(x))], '%10.5g')  # save sort by fitness
+    np.savetxt('evolve.txt', x[np.argsort(-fitness(x))], '%10.3g')  # save sort by fitness
 
     if bucket:
         os.system('gsutil cp evolve.txt gs://%s' % bucket)  # upload evolve.txt