docs(pretrained_models): fix num parameters
Correct the number of parameters of BERT based models.

Sometimes the difference is important. For instance:
`bert-base-uncased` has **110M parameters** but `bert-base-multilingual-cased` has more than **178M parameters**, even if both models share the same architecture (12-layer, 768-hidden, 12-heads).

The difference is due to the vocabulary size:
`bert-base-uncased` uses a vocabulary of 30k entries while `bert-base-multilingual-cased` uses a vocabulary of 119k entries.
I created a new PR with the correct formatting: https://github.com/huggingface/transformers/pull/6043