Fix YosoConfig doc (#15353)

src/transformers/models/yoso/configuration_yoso.py

@@ -67,17 +67,17 @@ class YosoConfig(PretrainedConfig):
             The epsilon used by the layer normalization layers.
         position_embedding_type (`str`, *optional*, defaults to `"absolute"`):
             Type of position embedding. Choose one of `"absolute"`, `"relative_key"`, `"relative_key_query"`.
-        use_expectation (*bool*, *optional*, defaults to *True*):
+        use_expectation (`bool`, *optional*, defaults to `True`):
             Whether or not to use YOSO Expectation. Overrides any effect of num_hash.
         hash_code_len (`int`, *optional*, defaults to 9):
             The length of hashes generated by the hash functions.
         num_hash (`int`, *optional*, defaults to 64):
             Number of hash functions used in [`YosoSelfAttention`].
-        conv_window (`int`, *optional*, defaults to None):
+        conv_window (`int`, *optional*):
             Kernel size of depth-wise convolution.
-        use_fast_hash (*bool*, *optional*, defaults to *False*):
+        use_fast_hash (`bool`, *optional*, defaults to `False`):
             Whether or not to use custom cuda kernels which perform fast random projection via hadamard transform.
-        lsh_backward (*bool*, *optional*, defaults to *True*):
+        lsh_backward (`bool`, *optional*, defaults to `True`):
             Whether or not to perform backpropagation using Locality Sensitive Hashing.
 
     Example: