diff --git a/src/transformers/models/donut/processing_donut.py b/src/transformers/models/donut/processing_donut.py
index 1b00d894bd087..da9e89c1d8b63 100644
--- a/src/transformers/models/donut/processing_donut.py
+++ b/src/transformers/models/donut/processing_donut.py
@@ -108,10 +108,13 @@ def as_target_processor(self):
         self.current_processor = self.feature_extractor
         self._in_target_context_manager = False
 
-    def token2json(self, tokens, is_inner_value=False):
+    def token2json(self, tokens, is_inner_value=False, added_vocab=None):
         """
         Convert a (generated) token sequence into an ordered JSON format.
         """
+        if added_vocab is None:
+            added_vocab = self.tokenizer.get_added_vocab()
+
         output = dict()
 
         while tokens:
@@ -131,7 +134,7 @@ def token2json(self, tokens, is_inner_value=False):
                 if content is not None:
                     content = content.group(1).strip()
                     if r"<s_" in content and r"</s_" in content:  # non-leaf node
-                        value = self.token2json(content, is_inner_value=True)
+                        value = self.token2json(content, is_inner_value=True, added_vocab=added_vocab)
                         if value:
                             if len(value) == 1:
                                 value = value[0]
@@ -140,7 +143,7 @@ def token2json(self, tokens, is_inner_value=False):
                         output[key] = []
                         for leaf in content.split(r"<sep/>"):
                             leaf = leaf.strip()
-                            if leaf in self.tokenizer.get_added_vocab() and leaf[0] == "<" and leaf[-2:] == "/>":
+                            if leaf in added_vocab and leaf[0] == "<" and leaf[-2:] == "/>":
                                 leaf = leaf[1:-2]  # for categorical special tokens
                             output[key].append(leaf)
                         if len(output[key]) == 1:
@@ -148,7 +151,7 @@ def token2json(self, tokens, is_inner_value=False):
 
                 tokens = tokens[tokens.find(end_token) + len(end_token) :].strip()
                 if tokens[:6] == r"<sep/>":  # non-leaf nodes
-                    return [output] + self.token2json(tokens[6:], is_inner_value=True)
+                    return [output] + self.token2json(tokens[6:], is_inner_value=True, added_vocab=added_vocab)
 
         if len(output):
             return [output] if is_inner_value else output
diff --git a/tests/models/donut/test_processing_donut.py b/tests/models/donut/test_processing_donut.py
new file mode 100644
index 0000000000000..cad0e37bc5195
--- /dev/null
+++ b/tests/models/donut/test_processing_donut.py
@@ -0,0 +1,48 @@
+# coding=utf-8
+# Copyright 2022 HuggingFace Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+import unittest
+
+from transformers import DonutProcessor
+
+
+DONUT_PRETRAINED_MODEL_NAME = "naver-clova-ix/donut-base"
+
+
+class DonutProcessorTest(unittest.TestCase):
+    def setUp(self):
+        self.processor = DonutProcessor.from_pretrained(DONUT_PRETRAINED_MODEL_NAME)
+
+    def test_token2json(self):
+        expected_json = {
+            "name": "John Doe",
+            "age": "99",
+            "city": "Atlanta",
+            "state": "GA",
+            "zip": "30301",
+            "phone": "123-4567",
+            "nicknames": [{"nickname": "Johnny"}, {"nickname": "JD"}],
+        }
+
+        sequence = (
+            "<s_name>John Doe</s_name><s_age>99</s_age><s_city>Atlanta</s_city>"
+            "<s_state>GA</s_state><s_zip>30301</s_zip><s_phone>123-4567</s_phone>"
+            "<s_nicknames><s_nickname>Johnny</s_nickname>"
+            "<sep/><s_nickname>JD</s_nickname></s_nicknames>"
+        )
+        actual_json = self.processor.token2json(sequence)
+
+        self.assertDictEqual(actual_json, expected_json)