diff --git a/train.py b/train.py
index 0db2f89b..43388078 100644
--- a/train.py
+++ b/train.py
@@ -20,7 +20,7 @@ last = wdir + 'last.pt'
 best = wdir + 'best.pt'
 results_file = 'results.txt'
 
-# Hyperparameters (results68: 59.2 mAP@0.5 yolov3-spp-416) https://github.com/ultralytics/yolov3/issues/310
+# Hyperparameters (results68: 59.9 mAP@0.5 yolov3-spp-416) https://github.com/ultralytics/yolov3/issues/310
 
 hyp = {'giou': 3.54,  # giou loss gain
        'cls': 37.4,  # cls loss gain
@@ -28,7 +28,7 @@ hyp = {'giou': 3.54,  # giou loss gain
        'obj': 49.5,  # obj loss gain (*=img_size/320 if img_size != 320)
        'obj_pw': 1.0,  # obj BCELoss positive_weight
        'iou_t': 0.225,  # iou training threshold
-       'lr0': 0.00579,  # initial learning rate (SGD=1E-3, Adam=9E-5)
+       'lr0': 0.00579,  # initial learning rate (SGD=5E-3, Adam=5E-4)
        'lrf': -4.,  # final LambdaLR learning rate = lr0 * (10 ** lrf)
        'momentum': 0.937,  # SGD momentum
        'weight_decay': 0.000484,  # optimizer weight decay
@@ -94,6 +94,7 @@ def train():
             pg0 += [v]  # all else
 
     if opt.adam:
+        hyp['lr0'] *= 0.1  # reduce lr (i.e. SGD=5E-3, Adam=5E-4)
         optimizer = optim.Adam(pg0, lr=hyp['lr0'])
         # optimizer = AdaBound(pg0, lr=hyp['lr0'], final_lr=0.1)
     else: