

TITLE
T5 supervised denoising task

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# 🚀 Feature request

Hi everyone!

I'm experimenting with T5 and I would like to fine-tune a specific pre-trained model of mine for tackling the 'filling the mask' task. To be clear, I have the following: I love \<mask> and Mario. Where \<mask> can be a single token or span.
At the moment I framed the problem in this way:
   - input: I love <extra_id_0> and Mario.
   - output/label: luca

The task I want to tackle is different from the canonical unsupervised one where I was able to perform it correctly. 
Do you think that the discussed framing presented above is enough?

From the result that I got,  it doesn't seem so.
