diff --git a/map_nav_src/reverie/env.py b/map_nav_src/reverie/env.py
index 65e9848..7234ebc 100644
--- a/map_nav_src/reverie/env.py
+++ b/map_nav_src/reverie/env.py
@@ -370,7 +370,11 @@ class ReverieObjectNavBatch(object):
         assert len(goal_viewpoints) > 0, '%s_%s'%(scan, str(gt_objid))
 
         scores['success'] = float(path[-1] in goal_viewpoints)
-        scores['found_success'] = float(pred_found == gt_found)
+        if scores['success'] == 1.0:
+            scores['found_success'] = float(pred_found == gt_found) 
+        else:
+            scores['found_success'] = 0.0
+
         scores['oracle_success'] = float(any(x in goal_viewpoints for x in path))
         scores['spl'] = scores['success'] * gt_lengths / max(scores['trajectory_lengths'], gt_lengths, 0.01)
         scores['sspl'] = scores['spl'] * scores['found_success']
@@ -385,6 +389,7 @@ class ReverieObjectNavBatch(object):
         print('eval %d predictions' % (len(preds)))
         print(preds[0])
 
+
         metrics = defaultdict(list)
         for item in preds:
             instr_id = item['instr_id']
@@ -393,7 +398,14 @@ class ReverieObjectNavBatch(object):
             scan, gt_traj, gt_objid = self.gt_trajs[instr_id]
             pred_found = item['found']
             gt_found = item['gt_found']
+
+
             traj_scores = self._eval_item(scan, traj, pred_objid, gt_traj, gt_objid, pred_found, gt_found)
+
+            # record "success" in the result file
+            # let the visualization tool can get the success status 
+            item['success'] = traj_scores['success']
+
             for k, v in traj_scores.items():
                 metrics[k].append(v)
             metrics['instr_id'].append(instr_id)
diff --git a/map_nav_src/scripts/run_reverie.sh b/map_nav_src/scripts/run_reverie.sh
index 34f84bc..56b5f01 100644
--- a/map_nav_src/scripts/run_reverie.sh
+++ b/map_nav_src/scripts/run_reverie.sh
@@ -10,7 +10,7 @@ obj_ft_dim=768
 ngpus=1
 seed=0
 
-name=${train_alg}-${features}
+name=${train_alg}-${features}-advanced-adversarial
 name=${name}-seed.${seed} #-${ngpus}gpus
 
 outdir=${DATA_ROOT}/REVERIE/exprs_map/finetune/${name}
@@ -63,8 +63,10 @@ flag="--root_dir ${DATA_ROOT}
 #       --tokenizer bert \
 #       --bert_ckpt_file '../datasets/REVERIE/exprs_map/pretrain/cmt-vitbase-mlm.mrc.sap.og-init.lxmert-aug.speaker/ckpts/model_step_100000.pt' \
 #       --eval_first
+
 # test
+echo /root/mount/Matterport3DSimulator/VLN-DUET/datasets/REVERIE/exprs_map/finetune/${name}/ckpts/best_val_unseen
 CUDA_VISIBLE_DEVICES='0' python3 reverie/main_nav_obj.py $flag  \
       --tokenizer bert \
-      --resume_file /root/mount/Matterport3DSimulator/VLN-DUET/datasets/REVERIE/exprs_map/finetune/dagger-vitbase-seed.0/ckpts/best_val_unseen \
+      --resume_file /root/mount/Matterport3DSimulator/VLN-DUET/datasets/REVERIE/exprs_map/finetune/${name}/ckpts/best_val_unseen \
       --test --submit