from_pretrained() - some model weights not initialized message
## Environment info
- `transformers` version: 4.0.1
- Platform: Linux-4.15.0-132-generic-x86_64-with-glibc2.10
- Python version: 3.8.5
- PyTorch version (GPU?): 1.7.1+cu110 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: <fill in>
- Using distributed or parallel set-up in script?: no

Note also: cookiecutter dependency is not included in pip install transformers so transformers-cli env initially fails

### Who can help
(T5) @patrickvonplaten, @patil-suraj, @sshleifer 

When using `T5ForConditionalGeneration.from_pretrained('t5-base')`, I get the following warning at load:
```
Some weights of the model checkpoint at t5-large were not used when initializing T5ForConditionalGeneration: ['decoder.block.0.layer.1.EncDecAttention.relative_attention_bias.weight']
- This IS expected if you are initializing T5ForConditionalGeneration from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining m
odel).                                                                                                                 
- This IS NOT expected if you are initializing T5ForConditionalGeneration from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification mode
l). 
```

If I load from a checkpoint that I create (i.e. local file), I get the same message.

But I think that all weights are, in fact, identical: 
- evaluation code on the model I finetune before saving AND
- evaluation code on the model I finetune, save, and then reload 
are identical.

This suggests that *all* weights are identical, since performance is identical. This contradicts the warning message.

Questions:
1) Are some weights actually not being loaded? If so, how could I observe identical behavior on metrics. Or is this warning wrong?
2) If this warning is correct, how can I force the model to fully load the model exactly as I saved it.
3) Is there any other difference (randomly initialized head, randomly initialized weights) between the t5 that is pretrained and the T5ForConditionalGeneration?

Duplicate of https://github.com/huggingface/transformers/issues/8933 . This wrong waring should have been fixed in newer versions, see: https://github.com/huggingface/transformers/blob/63c295ac05962b03701bdda87a90595b5f864075/src/transformers/models/t5/modeling_t5.py#L1188<|||||>Great! So *all* weights are in fact loaded from pretrained, or when loading from a checkpoint, then, right?