Danish BERT for hate speech classification
The BERT HateSpeech model classifies offensive Danish text into 4 categories:
Særlig opmærksomhed
(special attention, e.g. threat)Personangreb
(personal attack)Sprogbrug
(offensive language)Spam & indhold
(spam) This model is intended to be used after the BERT HateSpeech detection model.
It is based on the pretrained Danish BERT model by BotXO which has been fine-tuned on social media data.
See the DaNLP documentation for more details.
Here is how to use the model:
from transformers import BertTokenizer, BertForSequenceClassification
model = BertForSequenceClassification.from_pretrained("alexandrainst/da-hatespeech-classification-base")
tokenizer = BertTokenizer.from_pretrained("alexandrainst/da-hatespeech-classification-base")
Training data
The data used for training has not been made publicly available. It consists of social media data manually annotated in collaboration with Danmarks Radio.
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