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# Training
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*Skoltech/russian-inappropriate-messages* was finetuned on a multiclass data with four classes (*check the exact mapping between idx and label in* `model.config`).
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1) OK label
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2) Toxic label
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3) Severe toxic label
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4) Risks label
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The model was finetuned on a soon-to-be-posted
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# Evaluation results
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Model achieves the following results on the validation datasets (will be posted soon):
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| 0.896 | 0.348 | 0.490 | 0.591 |
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# Use in transformers
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# Training
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[*Skoltech/russian-inappropriate-messages*](https://huggingface.co/Skoltech/russian-inappropriate-messages) was finetuned on a multiclass data with four classes (*check the exact mapping between idx and label in* `model.config`).
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1) OK label — the message is OK in context and does not intent to offend or somehow harm the reputation of a speaker.
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2) Toxic label — the message might be seen as a offensive one in given context.
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3) Severe toxic label — the message is offencive, full of anger and was written to provoke a fight or any other discomfort
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4) Risks label — the message touches on sensitive topics and can harm the reputation of the speaker (i.e. religion, politics)
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The model was finetuned on a soon-to-be-posted dialogs datasets.
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# Evaluation results
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Model achieves the following results on the validation datasets (will be posted soon):
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|| OK - F1-score | TOXIC - F1-score | SEVERE TOXIC - F1-score | RISKS - F1-score |
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|---------|---------------|------------------|-------------------------|------------------|
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|twitter | 0.896 | 0.348 | 0.490 | 0.591 |
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|chats | 0.940 | 0.295 | 0.729 | 0.46 |
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# Use in transformers
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