diff --git a/train.py b/train.py
index 8cb68fc0748e..53dea89694ee 100644
--- a/train.py
+++ b/train.py
@@ -60,7 +60,7 @@ def train(hyp,  # path/to/hyp.yaml or hyp dictionary
           device,
           callbacks
           ):
-    save_dir, epochs, batch_size, weights, single_cls, evolve, data, cfg, resume, noval, nosave, workers, freeze, = \
+    save_dir, epochs, batch_size, weights, single_cls, evolve, data, cfg, resume, noval, nosave, workers, freeze = \
         Path(opt.save_dir), opt.epochs, opt.batch_size, opt.weights, opt.single_cls, opt.evolve, opt.data, opt.cfg, \
         opt.resume, opt.noval, opt.nosave, opt.workers, opt.freeze
 
@@ -124,7 +124,12 @@ def train(hyp,  # path/to/hyp.yaml or hyp dictionary
         model = Model(cfg, ch=3, nc=nc, anchors=hyp.get('anchors')).to(device)  # create
 
     # Freeze
-    freeze = [f'model.{x}.' for x in range(freeze)]  # layers to freeze
+    if len(freeze) >= 2:
+        freeze = freeze.split(',')
+        freeze = [x.replace(" ", "") for x in freeze]
+        freeze = [f'model.{x}.' for x in range(int(freeze[0]), int(freeze[1]) + 1)]  # layers to freeze
+    else:
+        freeze = [f'model.{x}.' for x in range(freeze)]
     for k, v in model.named_parameters():
         v.requires_grad = True  # train all layers
         if any(x in k for x in freeze):
@@ -469,7 +474,8 @@ def parse_opt(known=False):
     parser.add_argument('--linear-lr', action='store_true', help='linear LR')
     parser.add_argument('--label-smoothing', type=float, default=0.0, help='Label smoothing epsilon')
     parser.add_argument('--patience', type=int, default=100, help='EarlyStopping patience (epochs without improvement)')
-    parser.add_argument('--freeze', type=int, default=0, help='Number of layers to freeze. backbone=10, all=24')
+    parser.add_argument('--freeze', nargs='+', type=str, default='',
+                        help='Specify the layers that you want to freeze in training. (e.g. 10 represents freeze up to 10, or 1,2,4,6 represents freeze layers 1,2,4,6)')
     parser.add_argument('--save-period', type=int, default=-1, help='Save checkpoint every x epochs (disabled if < 1)')
     parser.add_argument('--local_rank', type=int, default=-1, help='DDP parameter, do not modify')