Finetuning BART on a  multi-input sequence to sequence task
I finetuned bart-base on a sequence to sequence task and I have the following questions:

a) Currently I structured the input and output for the bart model in "t5-style" by adding prefixes in front of each piece of input. For bart how should I give multiple inputs (or train it to return multiple outputs) to the model (is there special token to separate inputs, should I continue the t5-style prefixes, etc.)? Also, how would I do this for gpt-2/gpt-neo?

b) When finetuned with prefixes, the target data is formatted with "output: ......", however, the finetuned-bart returns "outputoutput: ......". Why is this repetiton occurring? Also, does the Bart tokenizer automatically add the eos token?

c) Also does the trainer api automaticallly handle ```adjust_logits_during_generation``` and ```decoder_start_token_id``` as discussed in this [post](https://discuss.huggingface.co/t/bart-base-rouge-scores/683)?

Could @patil-suraj or @patrickvonplaten help with this? This is my first project training an nlp model, and I would really appreciate any information you can offer regarding my questions.
Hi there! It would be better if you post this on the [forum](https://discuss.huggingface.co/) instead since this is much general question and not an issue. You can tag me on the forum using `@valhalla` :) 

Use issues to report bugs or for feature requests. Thanks!
<|||||>Thanks for your reply! I will close this issue and repost it on the forum.

EDIT:

@patil-suraj I have posted this on the huggingface forum [here](https://discuss.huggingface.co/t/finetuning-bart-on-a-multi-input-sequence-to-sequence-task/10201?u=nr1). Can you please take a look at it? Thank you!