

TITLE
Unwanted left shift of target tokens in `get_nll`

COMMENTS
3

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## Environment info
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     Don't forget to fill out the missing fields in that output! -->
     
- `transformers` version: 3.4
- Platform: ubuntu
- Python version: 3.8
- PyTorch version (GPU?): 1.6
- Tensorflow version (GPU?):
- Using GPU in script?: yes
- Using distributed or parallel set-up in script?:no

### Who can help
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 RAG: @patrickvonplaten, @lhoestq
 -->

## Information

Model I am using (Bert, XLNet ...):

The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x ] my own modified scripts: (give details below)
I am training RAG on the FEVER dataset, trying to generate one token from `['[SUPPORTS]', '[REFUTES]', '[INCONCLUSIVE]'.  My loss function is always zero, I think because of the shift left that occurs in `RagTokenForGeneration.get_nll()`, which I think should only happen if special tokens are included.

The tasks I am working on is:
* [ ] an official GLUE/SQUaD task: (give the name)
* [x] my own task or dataset: (give details below)
Training RAG on FEVER dataset

## To reproduce

Steps to reproduce the behavior:

1. Simply train `RAGTokenForGeneration` on anything, using only one token with no special tokens.  Loss is zero

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## Expected behavior

<!-- A clear and concise description of what you would expect to happen. -->
