metadata
license: openrail++
language:
- uk
widget:
- text: Ти неймовірна!
datasets:
- ukr-detect/ukr-toxicity-dataset
base_model:
- FacebookAI/xlm-roberta-base
Binary toxicity classifier for Ukrainian
This is the fine-tuned on the downstream task "xlm-roberta-base" instance.
The evaluation metrics for binary toxicity classification are:
Precision: 0.9130 Recall: 0.9065 F1: 0.9061
The training and evaluation data will be clarified later.
How to use
from transformers import AutoTokenizer, AutoModelForSequenceClassification
# load tokenizer and model weights
tokenizer = AutoTokenizer.from_pretrained('dardem/xlm-roberta-base-uk-toxicity')
model = AutoModelForSequenceClassification.from_pretrained('dardem/xlm-roberta-base-uk-toxicity')
# prepare the input
batch = tokenizer.encode('Ти неймовірна!', return_tensors='pt')
# inference
model(batch)
Citation
@article{dementieva2024toxicity,
title={Toxicity Classification in Ukrainian},
author={Dementieva, Daryna and Khylenko, Valeriia and Babakov, Nikolay and Groh, Georg},
journal={arXiv preprint arXiv:2404.17841},
year={2024}
}