Problem while initializing custom model with added tokens 
Hi, I'm trying to train my model with new special token 'name', but it keeps throwing size mismatch error. 
I think the problem is that my model has pretrained models inside initialization.

Model Structure
```
class MaskedLM(RobertaPreTrainedModel):
    def __init__(self, config):
        super().__init__(config=config)
        self.roberta = RobertaModel(config)
        self.lm_head = RobertaLMHead(config)
        self.refinement_num = 5
        self.mask_id = 50264
        self.init_weights()

    def forward(...):

```

After resizing my model, embedding size changed from 50265 to 50266. 

```
MaskedLM(
  (roberta): RobertaModel(
    (embeddings): RobertaEmbeddings(
      (word_embeddings): Embedding(50266, 768)
      (position_embeddings): Embedding(514, 768, padding_idx=1)
      (token_type_embeddings): Embedding(1, 768)
      (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
      (dropout): Dropout(p=0.1, inplace=False)

```

But the problem is out_features size in lm_head remains the same. (50265)

```
  (lm_head): RobertaLMHead(
    (dense): Linear(in_features=768, out_features=768, bias=True)
    (layer_norm): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
    (decoder): Linear(in_features=768, out_features=50265, bias=True)
  )

```

Is there any way that I can both load the pretrained weights and add one new token? 

-------------

Setting Tokenizer 
```
tokenizer = RobertaTokenizer.from_pretrained('roberta-base')
tokenizer.add_tokens('<name>')
```

Setting Model
```
model = MaskedLM.from_pretrained('roberta-base')
model.resize_token_embeddings(len(tokenizer))
```
