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Hello,
I am running some tests with t5-small
, and t5-base
as pretrained model for Degree ED, but its behavior during generation is strange. More specifically, the generated text seems to be in a different language than English, and sometimes it is concatenated with the word "is" that is present in the template 'Event trigger is <Trigger>'
, for example: pred_texts = ['Event trigger isurmatoarele.', 'Event trigger is imobil.', 'Event trigger is betreut.', ... ]
.
Looking at the source files for Degree, I have noticed that with you've already experimented with t5 as encoder model. Do you have any suggestions as to how configure the generation/decoding steps for t5 to properly function?
Thanks!
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