Abraham Starosta
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Browse files- README.md +0 -5
- config.json +1 -1
README.md
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This model takes a tweet with the word "jew" in it, and determines if it's antisemitic.
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*Labels:*
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1 for antisemitic
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0 otherwise
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*Training data:*
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This model was trained on 4k tweets, where ~50% were labeled as antisemitic. I labeled them myself.
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This model takes a tweet with the word "jew" in it, and determines if it's antisemitic.
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*Training data:*
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This model was trained on 4k tweets, where ~50% were labeled as antisemitic. I labeled them myself.
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config.json
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"transformers_version": "4.2.2",
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"vocab_size": 28996,
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"id2label": {
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"0": "
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"1": "ANTISEMITIC"
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}
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}
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"transformers_version": "4.2.2",
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"vocab_size": 28996,
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"id2label": {
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"0": "NOT ANTISEMITIC",
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"1": "ANTISEMITIC"
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}
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}
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