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--- |
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license: openrail++ |
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language: |
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- uk |
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widget: |
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- text: Ти неймовірна! |
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datasets: |
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- ukr-detect/ukr-toxicity-dataset |
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--- |
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## Binary toxicity classifier for Ukrainian. |
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This is the fine-tuned on the downstream task ["distilbert-base-multilingual-cased"](https://huggingface.co/distilbert-base-multilingual-cased) instance. |
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The evaluation metrics for binary toxicity classification are: |
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**Precision**: 0.9310 |
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**Recall**: 0.9300 |
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**F1**: 0.9300 |
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The training and evaluation data will be clarified later. |
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## How to use |
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```python |
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from transformers import AutoTokenizer, AutoModelForSequenceClassification |
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# load tokenizer and model weights |
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tokenizer = AutoTokenizer.from_pretrained('dardem/mdistilbert-base-cased-uk-toxicity') |
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model = AutoModelForSequenceClassification.from_pretrained('dardem/mdistilbert-base-cased-uk-toxicity') |
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# prepare the input |
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batch = tokenizer.encode('Ти неймовірна!', return_tensors='pt') |
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# inference |
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model(batch) |
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``` |
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## Citation |
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``` |
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@article{dementieva2024toxicity, |
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title={Toxicity Classification in Ukrainian}, |
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author={Dementieva, Daryna and Khylenko, Valeriia and Babakov, Nikolay and Groh, Georg}, |
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journal={arXiv preprint arXiv:2404.17841}, |
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year={2024} |
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} |
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``` |
