diff --git a/examples/pytorch/multiple-choice/run_swag.py b/examples/pytorch/multiple-choice/run_swag.py
index 50e42b7997f..cbd7e90d884 100755
--- a/examples/pytorch/multiple-choice/run_swag.py
+++ b/examples/pytorch/multiple-choice/run_swag.py
@@ -152,21 +152,21 @@ class DataCollatorForMultipleChoice:
     Data collator that will dynamically pad the inputs for multiple choice received.
 
     Args:
-        tokenizer (:class:`~transformers.PreTrainedTokenizer` or :class:`~transformers.PreTrainedTokenizerFast`):
+        tokenizer ([`PreTrainedTokenizer`] or [`PreTrainedTokenizerFast`]):
             The tokenizer used for encoding the data.
-        padding (:obj:`bool`, :obj:`str` or :class:`~transformers.file_utils.PaddingStrategy`, `optional`, defaults to :obj:`True`):
+        padding (`bool`, `str` or [`~file_utils.PaddingStrategy`], *optional*, defaults to `True`):
             Select a strategy to pad the returned sequences (according to the model's padding side and padding index)
             among:
 
-            * :obj:`True` or :obj:`'longest'`: Pad to the longest sequence in the batch (or no padding if only a single
-              sequence if provided).
-            * :obj:`'max_length'`: Pad to a maximum length specified with the argument :obj:`max_length` or to the
-              maximum acceptable input length for the model if that argument is not provided.
-            * :obj:`False` or :obj:`'do_not_pad'` (default): No padding (i.e., can output a batch with sequences of
-              different lengths).
-        max_length (:obj:`int`, `optional`):
+            - `True` or `'longest'`: Pad to the longest sequence in the batch (or no padding if only a single sequence
+              if provided).
+            - `'max_length'`: Pad to a maximum length specified with the argument `max_length` or to the maximum
+              acceptable input length for the model if that argument is not provided.
+            - `False` or `'do_not_pad'` (default): No padding (i.e., can output a batch with sequences of different
+              lengths).
+        max_length (`int`, *optional*):
             Maximum length of the returned list and optionally padding length (see above).
-        pad_to_multiple_of (:obj:`int`, `optional`):
+        pad_to_multiple_of (`int`, *optional*):
             If set will pad the sequence to a multiple of the provided value.
 
             This is especially useful to enable the use of Tensor Cores on NVIDIA hardware with compute capability >=
diff --git a/examples/pytorch/multiple-choice/run_swag_no_trainer.py b/examples/pytorch/multiple-choice/run_swag_no_trainer.py
index 6f0f38a8318..7daad8f3853 100755
--- a/examples/pytorch/multiple-choice/run_swag_no_trainer.py
+++ b/examples/pytorch/multiple-choice/run_swag_no_trainer.py
@@ -191,21 +191,21 @@ class DataCollatorForMultipleChoice:
     Data collator that will dynamically pad the inputs for multiple choice received.
 
     Args:
-        tokenizer (:class:`~transformers.PreTrainedTokenizer` or :class:`~transformers.PreTrainedTokenizerFast`):
+        tokenizer ([`PreTrainedTokenizer`] or [`PreTrainedTokenizerFast`]):
             The tokenizer used for encoding the data.
-        padding (:obj:`bool`, :obj:`str` or :class:`~transformers.file_utils.PaddingStrategy`, `optional`, defaults to :obj:`True`):
+        padding (`bool`, `str` or [`~file_utils.PaddingStrategy`], *optional*, defaults to `True`):
             Select a strategy to pad the returned sequences (according to the model's padding side and padding index)
             among:
 
-            * :obj:`True` or :obj:`'longest'`: Pad to the longest sequence in the batch (or no padding if only a single
-            sequence if provided).
-            * :obj:`'max_length'`: Pad to a maximum length specified with the argument :obj:`max_length` or to the
-            maximum acceptable input length for the model if that argument is not provided.
-            * :obj:`False` or :obj:`'do_not_pad'` (default): No padding (i.e., can output a batch with sequences of
-            different lengths).
-        max_length (:obj:`int`, `optional`):
+            - `True` or `'longest'`: Pad to the longest sequence in the batch (or no padding if only a single sequence
+              if provided).
+            - `'max_length'`: Pad to a maximum length specified with the argument `max_length` or to the maximum
+              acceptable input length for the model if that argument is not provided.
+            - `False` or `'do_not_pad'` (default): No padding (i.e., can output a batch with sequences of different
+              lengths).
+        max_length (`int`, *optional*):
             Maximum length of the returned list and optionally padding length (see above).
-        pad_to_multiple_of (:obj:`int`, `optional`):
+        pad_to_multiple_of (`int`, *optional*):
             If set will pad the sequence to a multiple of the provided value.
 
             This is especially useful to enable the use of Tensor Cores on NVIDIA hardware with compute capability >=
diff --git a/examples/tensorflow/multiple-choice/run_swag.py b/examples/tensorflow/multiple-choice/run_swag.py
index 536626a0f94..69c75b21234 100644
--- a/examples/tensorflow/multiple-choice/run_swag.py
+++ b/examples/tensorflow/multiple-choice/run_swag.py
@@ -73,21 +73,21 @@ class DataCollatorForMultipleChoice:
     Data collator that will dynamically pad the inputs for multiple choice received.
 
     Args:
-        tokenizer (:class:`~transformers.PreTrainedTokenizer` or :class:`~transformers.PreTrainedTokenizerFast`):
+        tokenizer ([`PreTrainedTokenizer`] or [`PreTrainedTokenizerFast`]):
             The tokenizer used for encoding the data.
-        padding (:obj:`bool`, :obj:`str` or :class:`~transformers.file_utils.PaddingStrategy`, `optional`, defaults to :obj:`True`):
+        padding (`bool`, `str` or [`~file_utils.PaddingStrategy`], *optional*, defaults to `True`):
             Select a strategy to pad the returned sequences (according to the model's padding side and padding index)
             among:
 
-            * :obj:`True` or :obj:`'longest'`: Pad to the longest sequence in the batch (or no padding if only a single
-              sequence if provided).
-            * :obj:`'max_length'`: Pad to a maximum length specified with the argument :obj:`max_length` or to the
-              maximum acceptable input length for the model if that argument is not provided.
-            * :obj:`False` or :obj:`'do_not_pad'` (default): No padding (i.e., can output a batch with sequences of
-              different lengths).
-        max_length (:obj:`int`, `optional`):
+            - `True` or `'longest'`: Pad to the longest sequence in the batch (or no padding if only a single sequence
+              if provided).
+            - `'max_length'`: Pad to a maximum length specified with the argument `max_length` or to the maximum
+              acceptable input length for the model if that argument is not provided.
+            - `False` or `'do_not_pad'` (default): No padding (i.e., can output a batch with sequences of different
+              lengths).
+        max_length (`int`, *optional*):
             Maximum length of the returned list and optionally padding length (see above).
-        pad_to_multiple_of (:obj:`int`, `optional`):
+        pad_to_multiple_of (`int`, *optional*):
             If set will pad the sequence to a multiple of the provided value.
 
             This is especially useful to enable the use of Tensor Cores on NVIDIA hardware with compute capability >=