diff --git a/train.py b/train.py
index 88ef61e8..b11ac89f 100644
--- a/train.py
+++ b/train.py
@@ -6,7 +6,7 @@ from utils.datasets import *
 from utils.utils import *
 
 parser = argparse.ArgumentParser()
-parser.add_argument('-epochs', type=int, default=160, help='number of epochs')
+parser.add_argument('-epochs', type=int, default=68, help='number of epochs')
 parser.add_argument('-batch_size', type=int, default=12, help='size of each image batch')
 parser.add_argument('-data_config_path', type=str, default='cfg/coco.data', help='data config file path')
 parser.add_argument('-cfg', type=str, default='cfg/yolov3.cfg', help='cfg file path')
@@ -86,7 +86,7 @@ def main(opt):
         optimizer = torch.optim.SGD(model.parameters(), lr=1e-3, momentum=.9, weight_decay=5e-4, nesterov=True)
 
     # Set scheduler
-    # scheduler = torch.optim.lr_scheduler.ExponentialLR(optimizer, gamma=0.99082, last_epoch=start_epoch - 1)
+    # scheduler = torch.optim.lr_scheduler.MultiStepLR(optimizer, milestones=[54, 61], gamma=0.1)
 
     modelinfo(model)
     t0, t1 = time.time(), time.time()
@@ -104,8 +104,14 @@ def main(opt):
         # scheduler.step()
 
         # Update scheduler (manual)
-        # for g in optimizer.param_groups:
-        #     g['lr'] = 1e-3 * (g ** epoch)  # 1/10th every [30, 50, 100, 250] epochs using g = [.926, .955, .977, .992]
+        if epoch < 54:
+            lr = 1e-3
+        elif epoch < 61:
+            lr = 1e-4
+        else:
+            lr = 1e-5
+        for g in optimizer.param_groups:
+            g['lr'] = lr
 
         ui = -1
         rloss = defaultdict(float)  # running loss