diff --git a/main.py b/main.py
index f561b16..35871ad 100644
--- a/main.py
+++ b/main.py
@@ -629,7 +629,6 @@ def main_beta():
             "hits_vt": hits_vt, "hits_trusted": hits_trusted,
         }
         if "server_pred" in res:
-            print(res["server_pred"].shape, server_val.value.shape)
             server = res["server_pred"] if len(res["server_pred"].shape) == 2 else res["server_pred"].max(axis=1)
             val = server_val.value.max(axis=1)
             data["server_pred"] = server.flatten()
@@ -679,8 +678,8 @@ def main_beta():
         client_user_preds.append(df_user.client_pred.as_matrix())
         if "server_val" in df.columns:
             server_user_preds.append(df_user.server_pred.as_matrix())
-    
-    logger.info("plot client curves")
+
+    logger.info("compute client curves")
     curves[model_prefix]["all"]["client_window_prc"] = visualize.calc_pr_mean(df.client_val.as_matrix(), client_preds)
     curves[model_prefix]["all"]["client_window_roc"] = visualize.calc_roc_mean(df.client_val.as_matrix(), client_preds)
     curves[model_prefix]["all"]["client_user_prc"] = visualize.calc_pr_mean(df_user.client_val.as_matrix(),
@@ -689,7 +688,7 @@ def main_beta():
                                                                              client_user_preds)
     
     if "server_val" in df.columns:
-        logger.info("plot server curves")
+        logger.info("compute server curves")
         curves[model_prefix]["all"]["server_window_prc"] = visualize.calc_pr_mean(df.server_val.as_matrix(),
                                                                                   server_preds)
         curves[model_prefix]["all"]["server_window_roc"] = visualize.calc_roc_mean(df.server_val.as_matrix(),
@@ -701,7 +700,7 @@ def main_beta():
                                                                                  server_user_preds)
     
     if df_server is not None:
-        logger.info("plot server flow curves")
+        logger.info("compute server flow curves")
         curves[model_prefix]["all"]["server_flow_prc"] = visualize.calc_pr_mean(df_server.server_val.as_matrix(),
                                                                                 server_flow_preds)
         curves[model_prefix]["all"]["server_flow_roc"] = visualize.calc_roc_mean(df_server.server_val.as_matrix(),
@@ -727,9 +726,11 @@ import matplotlib.pyplot as plt
 
 
 def plot_overall_result():
-    path, model_prefix = os.path.split(os.path.normpath(args.output_prefix))
+    path, model_prefix = os.path.split(os.path.normpath(args.model_path))
+    exists_or_make_path(f"{path}/figs/curves/")
     try:
         results = joblib.load(f"{path}/curves.joblib")
+        logger.info("curves successfully loaded")
     except Exception:
         results = {}