updates

train.py

@@ -134,6 +134,7 @@ def train():
     if opt.transfer or opt.prebias:  # transfer learning edge (yolo) layers
         nf = int(model.module_defs[model.yolo_layers[0] - 1]['filters'])  # yolo layer size (i.e. 255)
 
+        if opt.prebias:
             for p in optimizer.param_groups:
                 # lower param count allows more aggressive training settings: i.e. SGD ~0.1 lr0, ~0.9 momentum
                 p['lr'] *= 100  # lr gain