diff --git a/data/coco.data b/data/coco2017.data
similarity index 100%
rename from data/coco.data
rename to data/coco2017.data
diff --git a/detect.py b/detect.py
index 6da45c3b..21ce7716 100644
--- a/detect.py
+++ b/detect.py
@@ -155,7 +155,7 @@ def detect(save_txt=False, save_img=False):
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
     parser.add_argument('--cfg', type=str, default='cfg/yolov3-spp.cfg', help='cfg file path')
-    parser.add_argument('--data', type=str, default='data/coco.data', help='coco.data file path')
+    parser.add_argument('--data', type=str, default='data/coco2017.data', help='*.data file path')
     parser.add_argument('--weights', type=str, default='weights/yolov3-spp.weights', help='path to weights file')
     parser.add_argument('--source', type=str, default='data/samples', help='source')  # input file/folder, 0 for webcam
     parser.add_argument('--output', type=str, default='output', help='output folder')  # output folder
diff --git a/test.py b/test.py
index caffb552..3cc52dd7 100644
--- a/test.py
+++ b/test.py
@@ -204,7 +204,7 @@ def test(cfg,
 if __name__ == '__main__':
     parser = argparse.ArgumentParser(prog='test.py')
     parser.add_argument('--cfg', type=str, default='cfg/yolov3-spp.cfg', help='cfg file path')
-    parser.add_argument('--data', type=str, default='data/coco.data', help='coco.data file path')
+    parser.add_argument('--data', type=str, default='data/coco2017.data', help='*.data file 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('--img-size', type=int, default=416, help='inference size (pixels)')
@@ -225,4 +225,4 @@ if __name__ == '__main__':
              opt.iou_thres,
              opt.conf_thres,
              opt.nms_thres,
-             opt.save_json or (opt.data == 'data/coco.data'))
+             opt.save_json or any([x in opt.data for x in ['coco.data', 'coco2014.data', 'coco2017.data']]))
diff --git a/train.py b/train.py
index 4c1eaeeb..329d9443 100644
--- a/train.py
+++ b/train.py
@@ -324,13 +324,14 @@ def train():
             print_model_biases(model)
         elif not opt.notest or final_epoch:  # Calculate mAP
             with torch.no_grad():
+                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,
                                           img_size=opt.img_size,
                                           model=model,
                                           conf_thres=0.001 if final_epoch else 0.1,  # 0.1 for speed
-                                          save_json=final_epoch and 'coco.data' in data and model.nc == 80,
+                                          save_json=final_epoch and is_coco,
                                           dataloader=testloader)
 
         # Write epoch results
@@ -419,7 +420,7 @@ if __name__ == '__main__':
     parser.add_argument('--batch-size', type=int, default=16)  # effective bs = batch_size * accumulate = 16 * 4 = 64
     parser.add_argument('--accumulate', type=int, default=4, help='batches to accumulate before optimizing')
     parser.add_argument('--cfg', type=str, default='cfg/yolov3-spp.cfg', help='cfg file path')
-    parser.add_argument('--data', type=str, default='data/coco.data', help='*.data file path')
+    parser.add_argument('--data', type=str, default='data/coco2017.data', help='*.data file path')
     parser.add_argument('--multi-scale', action='store_true', help='adjust (67% - 150%) img_size every 10 batches')
     parser.add_argument('--img-size', type=int, default=416, help='inference size (pixels)')
     parser.add_argument('--rect', action='store_true', help='rectangular training')