dardem/mdistilbert-base-cased-uk-toxicity

Binary toxicity classifier for Ukrainian.

This is the fine-tuned on the downstream task "distilbert-base-multilingual-cased" instance.

The evaluation metrics for binary toxicity classification are:

Precision: 0.9310 Recall: 0.9300 F1: 0.9300

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/mdistilbert-base-cased-uk-toxicity')
model = AutoModelForSequenceClassification.from_pretrained('dardem/mdistilbert-base-cased-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}
}