diff --git a/.gitignore b/.gitignore
index 0478d6eb..44c1c23a 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,6 +1,5 @@
 *.pyc
 result.txt
 extracted_features*
-acc_results.txt
-auc_results.txt
+*results.txt
 .*
diff --git a/main.py b/main.py
index 8f469fd3..1adfbf22 100644
--- a/main.py
+++ b/main.py
@@ -177,11 +177,13 @@ def loop_dataset(g_list, classifier, sample_idxes, optimizer=None, bsize=cmd_arg
     
     # np.savetxt('test_scores.txt', all_scores)  # output test predictions
     
-    if not classifier.regression:
+    if not classifier.regression and cmd_args.printAUC:
         all_targets = np.array(all_targets)
         fpr, tpr, _ = metrics.roc_curve(all_targets, all_scores, pos_label=1)
         auc = metrics.auc(fpr, tpr)
         avg_loss = np.concatenate((avg_loss, [auc]))
+    else:
+        avg_loss = np.concatenate((avg_loss, [0.0]))
     
     return avg_loss
 
@@ -223,11 +225,11 @@ def loop_dataset(g_list, classifier, sample_idxes, optimizer=None, bsize=cmd_arg
             test_loss[2] = 0.0
         print('\033[93maverage test of epoch %d: loss %.5f acc %.5f auc %.5f\033[0m' % (epoch, test_loss[0], test_loss[1], test_loss[2]))
 
-    with open('acc_results.txt', 'a+') as f:
+    with open(cmd_args.data + '_acc_results.txt', 'a+') as f:
         f.write(str(test_loss[1]) + '\n')
 
     if cmd_args.printAUC:
-        with open('auc_results.txt', 'a+') as f:
+        with open(cmd_args.data + '_auc_results.txt', 'a+') as f:
             f.write(str(test_loss[2]) + '\n')
 
     if cmd_args.extract_features:
diff --git a/run_DGCNN.sh b/run_DGCNN.sh
index f38fc75f..f07babe2 100755
--- a/run_DGCNN.sh
+++ b/run_DGCNN.sh
@@ -91,9 +91,9 @@ if [ ${fold} == 0 ]; then
   echo "End of cross-validation"
   echo "The total running time is $[stop - start] seconds."
   echo "The accuracy results for ${DATA} are as follows:"
-  cat acc_results.txt
-  echo "Average accuracy is"
-  tail -10 acc_results.txt | awk '{ sum += $1; n++ } END { if (n > 0) print sum / n; }'
+  tail -10 ${DATA}_acc_results.txt
+  echo "Average accuracy and std are"
+  tail -10 ${DATA}_acc_results.txt | awk '{ sum += $1; sum2 += $1*$1; n++ } END { if (n > 0) print sum / n; print sqrt(sum2 / n - (sum/n) * (sum/n)); }'
 else
   CUDA_VISIBLE_DEVICES=${GPU} python main.py \
       -seed 1 \