Comments (3)
lewtun
commented on June 11, 2024
5
Hey @mpangrazzi, yes SetFit works very well in multi-label scenarios and @fgbelidji has implemented a script here for that:
What's currently missing is a nice integration with the SetFitTrainer, so a PR for that would be very welcome (if I don't get to it first :))
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sanderland
commented on June 11, 2024
Also very interested in trying this on multi-label cases.
One question from reading the code: am I correct in understanding sentence_pairs_generation_multilabel gives a label "1" if any label overlaps and "0" on completely disjoint examples? If so, doesn't this give problems when e.g. one label is a strict subset of another, or one label is rather unbalanced.
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mpangrazzi
commented on June 11, 2024
Added in #69
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Related Issues (20)
- Can we use Setfit just for finetuning ST Embedding model to create embeddings HOT 2
- MultiGPU support or better intergration for loading models HOT 1
- i found a typo in docs HOT 1
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- Usage of deprecated `evaluation_strategy` in TrainingArguments HOT 1
- Data validation when using differentiable_head
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- exception:enum PyPreTokenizerTypeWrapper, while loading the fine-tuned model for evaluation HOT 7
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