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- ### Dataset summary
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  This dataset is a DeepL -based machine translated version of the Jigsaw toxicity dataset for Finnish. The dataset is originally from a Kaggle competition https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge/data.
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- The dataset poses a multi-label text classification problem and includes the labels `identity_attack, insult, obscene, severe_toxicity, threat and toxicity`.
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  #### Example data
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  }
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  ```
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- ### Data fields
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  Fields marked as `label_` have either `0` to convey *not* having that category of toxicity in the text and `1` to convey having that category of toxicity present in the text.
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  - `text`: a `string` feature.
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- ### Data splits
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  The splits are the same as in the original English data.
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@@ -59,6 +59,18 @@ The splits are the same as in the original English data.
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  | -------- | -----: | ---------: |
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  | Jigsaw toxicity data | 159571 | 63978 |
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  ### Considerations for Using the Data
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  Due to DeepL terms and conditions, this dataset **must not be used for any machine translation work**, namely machine translation
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  system development and evaluation of any kind. In general, we wish you do not pair the original English data with the translations
 
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+ ### Dataset Summary
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  This dataset is a DeepL -based machine translated version of the Jigsaw toxicity dataset for Finnish. The dataset is originally from a Kaggle competition https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge/data.
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+ The dataset poses a multi-label text classification problem and includes the labels `identity_attack`, `insult`, `obscene`, `severe_toxicity`, `threat` and `toxicity`.
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  #### Example data
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  }
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  ```
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+ ### Data Fields
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  Fields marked as `label_` have either `0` to convey *not* having that category of toxicity in the text and `1` to convey having that category of toxicity present in the text.
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  - `text`: a `string` feature.
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+ ### Data Splits
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  The splits are the same as in the original English data.
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  | -------- | -----: | ---------: |
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  | Jigsaw toxicity data | 159571 | 63978 |
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+ ### Evaluation Results
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+
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+ Results from fine-tuning [TurkuNLP/bert-large-finnish-cased-v1](https://huggingface.co/TurkuNLP/bert-large-finnish-cased-v1) for multi-label toxicity detection.
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+ | dataset | F1-micro | Precision | Recall |
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+ | -------------------- | ----: | ---: | ----: |
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+ | TurkuNLP/wikipedia-toxicity-data-fi | 0.66 | 0.58 | 0.76 |
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+
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+ <!--- Base results from fine-tuning [bert-large-cased](https://huggingface.co/bert-large-cased) on the original English data for multi-label toxicity detection.
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+ | dataset | F1-micro | Precision | Recall |
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+ | -------------------- | ----: | ---: | ----: |
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+ | jigsaw_toxicity_pred | 0.69 | 0.59 | 0.81 | --->
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+
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  ### Considerations for Using the Data
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  Due to DeepL terms and conditions, this dataset **must not be used for any machine translation work**, namely machine translation
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  system development and evaluation of any kind. In general, we wish you do not pair the original English data with the translations