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Unbiased model not returning identity labels #61

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SallyBean opened this issue Aug 23, 2022 · 6 comments
Open

Unbiased model not returning identity labels #61

SallyBean opened this issue Aug 23, 2022 · 6 comments

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@SallyBean
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Thanks for the great repo!

I'm running the 'Quick prediction' code using the unbiased model, but there are no identity labels being returned - even with severe toxicity. I only get the toxicity labels.

Am I missing something?

Thanks again!

@m13uz
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m13uz commented Aug 24, 2022

@SallyBean could you please provide a minimal reproducible example of the issue, e.g. a code snippet?

@SallyBean
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SallyBean commented Aug 24, 2022

@m13uz Sure, sorry about that! Thanks for your help in advance. :)

!pip install detoxify
from detoxify import Detoxify

input_text=["I hate women", "Men are idiots"]

results = Detoxify('unbiased').predict(input_text)

model = Detoxify('unbiased', device='cuda')

import pandas as pd

pd.DataFrame(results, index=input_text).round(5))

output (without the expected identity labels):
image

@jamt9000
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jamt9000 commented Sep 2, 2022

This is by design - the detoxify wrapper only returns the toxicity-related classes, since identity outputs are more intended for de-biasing during training. If you want them you could load the model checkpoint directly.

@Mario-RC
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Mario-RC commented Jan 3, 2023

This is by design - the detoxify wrapper only returns the toxicity-related classes, since identity outputs are more intended for de-biasing during training. If you want them you could load the model checkpoint directly.

Hello, how can I download and load the model checkpoint that returns identity labels? They would be very useful for my projects, thank you!

@lethal-mole
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Hello, is there any update over here? I couldn't find the checkpoints either
Thank you!!

@laurahanu
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Hello, that would be the unbiased model checkpoint, one way to get it to return the identity labels is to:

  • overwrite the class_names in the config that's saved inside the checkpoint with all the class names from here (combined as one list in the same order) and save the checkpoint with the updated class names
  • initialise the detoxify model from the newly saved checkpoint

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6 participants