diff --git a/models.py b/models.py
index 136c314d..0df5930e 100755
--- a/models.py
+++ b/models.py
@@ -159,14 +159,16 @@ class YOLOLayer(nn.Module):
                 lh = 5 * MSELoss(h[mask], th[mask])
                 lconf = 1.5 * BCEWithLogitsLoss1(pred_conf[mask], mask[mask].float())
 
-                lcls = nM * CrossEntropyLoss(pred_cls[mask], torch.argmax(tcls, 1))
-                # lcls = nM * BCEWithLogitsLoss2(pred_cls[mask], tcls.float())
+                # lcls = nM * CrossEntropyLoss(pred_cls[mask], torch.argmax(tcls, 1))
+                lcls = nM * BCEWithLogitsLoss2(pred_cls[mask], tcls.float())
             else:
                 lx, ly, lw, lh, lcls, lconf = FT([0]), FT([0]), FT([0]), FT([0]), FT([0]), FT([0])
 
             lconf += nM * BCEWithLogitsLoss2(pred_conf[~mask], mask[~mask].float())
 
             loss = lx + ly + lw + lh + lconf + lcls
+
+            # Sum False Positives from unnasigned anchors
             i = torch.sigmoid(pred_conf[~mask]) > 0.99
             FPe = torch.zeros(self.nC)
             if i.sum() > 0: