diff --git a/deeppavlov/configs/faq/tfidf_logreg_autofaq.json b/deeppavlov/configs/faq/tfidf_logreg_autofaq.json
index 9e2516fceb..18f5067379 100644
--- a/deeppavlov/configs/faq/tfidf_logreg_autofaq.json
+++ b/deeppavlov/configs/faq/tfidf_logreg_autofaq.json
@@ -73,7 +73,7 @@
       },
       {
         "in": "y_pred_proba",
-        "out": "y_pred_ids",
+        "out": ["y_pred_ids", "y_pred_proba_max"],
         "class_name": "proba2labels",
         "max_proba": true
       },
@@ -85,7 +85,7 @@
     ],
     "out": [
       "y_pred_answers",
-      "y_pred_proba"
+      "y_pred_proba_max"
     ]
   },
   "train": {
diff --git a/deeppavlov/configs/faq/tfidf_logreg_en_faq.json b/deeppavlov/configs/faq/tfidf_logreg_en_faq.json
index 04ab1f34d4..ed7399a71b 100644
--- a/deeppavlov/configs/faq/tfidf_logreg_en_faq.json
+++ b/deeppavlov/configs/faq/tfidf_logreg_en_faq.json
@@ -72,7 +72,7 @@
       },
       {
         "in": "y_pred_proba",
-        "out": "y_pred_ids",
+        "out": ["y_pred_ids", "y_pred_proba_max"],
         "class_name": "proba2labels",
         "max_proba": true
       },
@@ -84,7 +84,7 @@
     ],
     "out": [
       "y_pred_answers",
-      "y_pred_proba"
+      "y_pred_proba_max"
     ]
   },
   "train": {
diff --git a/deeppavlov/models/classifiers/proba2labels.py b/deeppavlov/models/classifiers/proba2labels.py
index 29ab96ebc5..b7dffd5cfe 100644
--- a/deeppavlov/models/classifiers/proba2labels.py
+++ b/deeppavlov/models/classifiers/proba2labels.py
@@ -13,7 +13,7 @@
 # limitations under the License.
 
 from logging import getLogger
-from typing import List, Union
+from typing import List, Union, Tuple
 
 import numpy as np
 
@@ -54,7 +54,7 @@ def __init__(self,
         self.top_n = top_n
 
     def __call__(self, data: Union[np.ndarray, List[List[float]], List[List[int]]],
-                 *args, **kwargs) -> Union[List[List[int]], List[int]]:
+                 *args, **kwargs) -> Tuple[Union[List[List[int]], List[int]], Union[List[List[int]], List[int]]]:
         """
         Process probabilities to labels
 
@@ -63,14 +63,18 @@ def __call__(self, data: Union[np.ndarray, List[List[float]], List[List[int]]],
 
         Returns:
             list of labels (only label classification) or list of lists of labels (multi-label classification)
+            # add comment here
         """
         if self.confident_threshold:
-            return [list(np.where(np.array(d) > self.confident_threshold)[0])
+            labels = [list(np.where(np.array(d) > self.confident_threshold)[0])
                     for d in data]
+            return labels, [[d[l] for l in label] for d, label in zip(data, labels)]
         elif self.max_proba:
-            return [np.argmax(d) for d in data]
+            labels = [np.argmax(d) for d in data]
+            return labels, [[d[l] for l in label] for d, label in zip(data, labels)]
         elif self.top_n:
-            return [np.argsort(d)[::-1][:self.top_n] for d in data]
+            labels = [np.argsort(d)[::-1][:self.top_n] for d in data]
+            return labels, [[d[l] for l in label] for d, label in zip(data, labels)]
         else:
             raise ConfigError("Proba2Labels requires one of three arguments: bool `max_proba` or "
                               "float `confident_threshold` for multi-label classification or"