diff --git a/test.py b/test.py
index 1461c714..8b9776fe 100644
--- a/test.py
+++ b/test.py
@@ -209,7 +209,7 @@ if __name__ == '__main__':
     parser.add_argument('--cfg', type=str, default='cfg/yolov3-spp.cfg', help='*.cfg path')
     parser.add_argument('--data', type=str, default='data/coco2014.data', help='*.data path')
     parser.add_argument('--weights', type=str, default='weights/yolov3-spp.weights', help='path to weights file')
-    parser.add_argument('--batch-size', type=int, default=16, help='size of each image batch')
+    parser.add_argument('--batch-size', type=int, default=32, help='size of each image batch')
     parser.add_argument('--img-size', type=int, default=416, help='inference size (pixels)')
     parser.add_argument('--conf-thres', type=float, default=0.001, help='object confidence threshold')
     parser.add_argument('--nms-thres', type=float, default=0.5, help='iou threshold for non-maximum suppression')
diff --git a/train.py b/train.py
index 5c939931..ee9caad2 100644
--- a/train.py
+++ b/train.py
@@ -213,7 +213,7 @@ def train():
                                                                      rect=True,
                                                                      cache_labels=True,
                                                                      cache_images=opt.cache_images),
-                                                 batch_size=batch_size,
+                                                 batch_size=batch_size * 2,
                                                  num_workers=nw,
                                                  pin_memory=True,
                                                  collate_fn=dataset.collate_fn)
@@ -326,7 +326,7 @@ def train():
             is_coco = any([x in data for x in ['coco.data', 'coco2014.data', 'coco2017.data']]) and model.nc == 80
             results, maps = test.test(cfg,
                                       data,
-                                      batch_size=batch_size,
+                                      batch_size=batch_size * 2,
                                       img_size=opt.img_size,
                                       model=model,
                                       conf_thres=0.001 if final_epoch else 0.1,  # 0.1 for speed