diff --git a/models/yolo.py b/models/yolo.py
index a9e1da43d913..a047fef397ee 100644
--- a/models/yolo.py
+++ b/models/yolo.py
@@ -62,7 +62,7 @@ def _make_grid(nx=20, ny=20):
 
 
 class Model(nn.Module):
-    def __init__(self, cfg='yolov5s.yaml', ch=3, nc=None):  # model, input channels, number of classes
+    def __init__(self, cfg='yolov5s.yaml', ch=3, nc=None, anchors=None):  # model, input channels, number of classes
         super(Model, self).__init__()
         if isinstance(cfg, dict):
             self.yaml = cfg  # model dict
@@ -75,8 +75,11 @@ def __init__(self, cfg='yolov5s.yaml', ch=3, nc=None):  # model, input channels,
         # Define model
         ch = self.yaml['ch'] = self.yaml.get('ch', ch)  # input channels
         if nc and nc != self.yaml['nc']:
-            logger.info('Overriding model.yaml nc=%g with nc=%g' % (self.yaml['nc'], nc))
+            logger.info(f"Overriding model.yaml nc={self.yaml['nc']} with nc={nc}")
             self.yaml['nc'] = nc  # override yaml value
+        if anchors:
+            logger.info(f'Overriding model.yaml anchors with anchors={anchors}')
+            self.yaml['anchors'] = round(anchors)  # override yaml value
         self.model, self.save = parse_model(deepcopy(self.yaml), ch=[ch])  # model, savelist
         self.names = [str(i) for i in range(self.yaml['nc'])]  # default names
         # print([x.shape for x in self.forward(torch.zeros(1, ch, 64, 64))])
diff --git a/train.py b/train.py
index e2c82339f7fe..1b8b315ce927 100644
--- a/train.py
+++ b/train.py
@@ -84,7 +84,7 @@ def train(hyp, opt, device, tb_writer=None, wandb=None):
         model.load_state_dict(state_dict, strict=False)  # load
         logger.info('Transferred %g/%g items from %s' % (len(state_dict), len(model.state_dict()), weights))  # report
     else:
-        model = Model(opt.cfg, ch=3, nc=nc).to(device)  # create
+        model = Model(opt.cfg, ch=3, nc=nc, anchors=hyp.get('anchors')).to(device)  # create
 
     # Freeze
     freeze = []  # parameter names to freeze (full or partial)