diff --git a/src/transformers/models/bert_generation/tokenization_bert_generation.py b/src/transformers/models/bert_generation/tokenization_bert_generation.py
index f8d49f86ac..3b6298fcbd 100644
--- a/src/transformers/models/bert_generation/tokenization_bert_generation.py
+++ b/src/transformers/models/bert_generation/tokenization_bert_generation.py
@@ -51,15 +51,19 @@ class BertGenerationTokenizer(PreTrainedTokenizer):
vocab_file (`str`):
[SentencePiece](https://github.com/google/sentencepiece) file (generally has a *.spm* extension) that
contains the vocabulary necessary to instantiate a tokenizer.
- eos_token (`str`, *optional*, defaults to `""`):
- The end of sequence token.
bos_token (`str`, *optional*, defaults to `""`):
The begin of sequence token.
+ eos_token (`str`, *optional*, defaults to `""`):
+ The end of sequence token.
unk_token (`str`, *optional*, defaults to `""`):
The unknown token. A token that is not in the vocabulary cannot be converted to an ID and is set to be this
token instead.
pad_token (`str`, *optional*, defaults to `""`):
The token used for padding, for example when batching sequences of different lengths.
+ sep_token (`str`, *optional*, defaults to `"<::::>"`):
+ The separator token, which is used when building a sequence from multiple sequences, e.g. two sequences for
+ sequence classification or for a text and a question for question answering. It is also used as the last
+ token of a sequence built with special tokens.
sp_model_kwargs (`dict`, *optional*):
Will be passed to the `SentencePieceProcessor.__init__()` method. The [Python wrapper for
SentencePiece](https://github.com/google/sentencepiece/tree/master/python) can be used, among other things,
diff --git a/utils/check_docstrings.py b/utils/check_docstrings.py
index 8a9aa1cf76..f46ad8995c 100644
--- a/utils/check_docstrings.py
+++ b/utils/check_docstrings.py
@@ -94,7 +94,6 @@ OBJECTS_TO_IGNORE = [
"BarthezTokenizerFast",
"BeitModel",
"BertConfig",
- "BertGenerationTokenizer",
"BertJapaneseTokenizer",
"BertModel",
"BertTokenizerFast",