diff --git a/train.py b/train.py
index 7548e4e1..fa5dead6 100644
--- a/train.py
+++ b/train.py
@@ -8,7 +8,7 @@ from utils.utils import *
 
 parser = argparse.ArgumentParser()
 parser.add_argument('-epochs', type=int, default=100, help='number of epochs')
-parser.add_argument('-batch_size', type=int, default=2, help='size of each image batch')
+parser.add_argument('-batch_size', type=int, default=16, 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')
 parser.add_argument('-multi_scale', default=False, help='random image sizes per batch 320 - 608')
diff --git a/utils/utils.py b/utils/utils.py
index dd261c7d..c4884f45 100755
--- a/utils/utils.py
+++ b/utils/utils.py
@@ -442,12 +442,13 @@ def plot_results():
     import matplotlib.pyplot as plt
     plt.figure(figsize=(16, 8))
     s = ['X', 'Y', 'Width', 'Height', 'Objectness', 'Classification', 'Total Loss', 'Precision', 'Recall', 'mAP']
-    for f in ('results.txt',
+    for f in ('results_64.txt','results_642.txt'
               ):
         results = np.loadtxt(f, usecols=[2, 3, 4, 5, 6, 7, 8, 17, 18, 16]).T  # column 16 is mAP
+        n = results.shape[1]
         for i in range(10):
             plt.subplot(2, 5, i + 1)
-            plt.plot(results[i, :250], marker='.', label=f)
+            plt.plot(range(1,n), results[i, 1:], marker='.', label=f)
             plt.title(s[i])
             if i == 0:
                 plt.legend()
@@ -466,4 +467,4 @@ def plot_results():
 #             plt.plot(results, marker='.', label=f)
 #             plt.title(s[i])
 #             if i == 0:
-#                 plt.legend()
\ No newline at end of file
+#                 plt.legend()