diff --git a/train.py b/train.py
index 0a1d5525..b34c2293 100644
--- a/train.py
+++ b/train.py
@@ -32,7 +32,7 @@ hyp = {'giou': 3.54,  # giou loss gain
        'lrf': -4.,  # final LambdaLR learning rate = lr0 * (10 ** lrf)
        'momentum': 0.937,  # SGD momentum
        'weight_decay': 0.000484,  # optimizer weight decay
-       'fl_gamma': 0.5,  # focal loss gamma
+       'fl_gamma': 1.5,  # focal loss gamma
        'hsv_h': 0.0138,  # image HSV-Hue augmentation (fraction)
        'hsv_s': 0.678,  # image HSV-Saturation augmentation (fraction)
        'hsv_v': 0.36,  # image HSV-Value augmentation (fraction)
diff --git a/utils/utils.py b/utils/utils.py
index 99e44665..788fd63d 100755
--- a/utils/utils.py
+++ b/utils/utils.py
@@ -340,7 +340,7 @@ def wh_iou(wh1, wh2):
 class FocalLoss(nn.Module):
     # Wraps focal loss around existing loss_fcn() https://arxiv.org/pdf/1708.02002.pdf
     # i.e. criteria = FocalLoss(nn.BCEWithLogitsLoss(), gamma=2.5)
-    def __init__(self, loss_fcn, gamma=0.5, alpha=1):
+    def __init__(self, loss_fcn, gamma=1.5, alpha=0.25):
         super(FocalLoss, self).__init__()
         self.loss_fcn = loss_fcn
         self.gamma = gamma