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README.md
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It's 48% accurate at guessing male, female, and non-binary. (random guessing is 33.33% accurate)
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But I am aware it is biased towards males because of a data diversity issue.
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The diversity issues being I collected different post amounts based on each user's account gender.
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I plan to fix this in v5.
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---
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datasets:
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- breadlicker45/gender-bluesky-classification-v4
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base_model:
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- Lajavaness/bilingual-embedding-base
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---
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It's 48% accurate at guessing male, female, and non-binary. (random guessing is 33.33% accurate)
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But I am aware it is biased towards males because of a data diversity issue.
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The diversity issues being I collected different post amounts based on each user's account gender.
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I plan to fix this in v5.
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