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@@ -60,11 +60,11 @@ print(text2toxicity(['я люблю нигеров', 'я люблю африка
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  ## Training
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- The model has been trained on the joint dataset of [OK ML Cup](https://cups.mail.ru/ru/tasks/1048) and [Babakov et.al.](https://arxiv.org/abs/2103.05345) with `Adam` optimizer, learning rate of `1e-5`, and batch size of `128` for `5` epochs. The data was not filtered in any way. A text was considered inappropriate if its inappropritateness score was higher than 0.2. The per-label ROC AUC on the dev set is:
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  ```
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- non-toxic : 0.9909
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- insult : 0.9882
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- obscenity : 0.9824
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- threat : 0.9868
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- dangerous : 0.7758
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  ```
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  ## Training
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+ The model has been trained on the joint dataset of [OK ML Cup](https://cups.mail.ru/ru/tasks/1048) and [Babakov et.al.](https://arxiv.org/abs/2103.05345) with `Adam` optimizer, learning rate of `1e-5`, and batch size of `64` for `15` epochs. A text was considered inappropriate if its inappropritateness score was higher than 0.8, and appropriate - if it was lower than 0.2. The per-label ROC AUC on the dev set is:
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  ```
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+ non-toxic : 0.9937
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+ insult : 0.9912
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+ obscenity : 0.9881
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+ threat : 0.9910
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+ dangerous : 0.8295
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  ```