readme: ---
  language:
  - da
  license: cc-by-sa-4.0
  datasets:
  - DDSC/twitter-sent
  - DDSC/europarl
  widget:
  - text: Jeg tror alligvel, det bliver godt
  ---
  
  # Danish BERT Tone for the detection of subjectivity/objectivity
  
  The BERT Tone model detects whether a text (in Danish) is subjective or objective. 
  The model is based on the finetuning of the pretrained [Danish BERT](https://github.com/certainlyio/nordic_bert) model by BotXO. 
  
  See the [DaNLP documentation](https://danlp-alexandra.readthedocs.io/en/latest/docs/tasks/sentiment_analysis.html#bert-tone) for more details. 
  
  
  Here is how to use the model:
  
  ```python
  from transformers import BertTokenizer, BertForSequenceClassification
  
  model = BertForSequenceClassification.from_pretrained("alexandrainst/da-subjectivivity-classification-base")
  tokenizer = BertTokenizer.from_pretrained("alexandrainst/da-subjectivivity-classification-base")
  ```
  
  ## Training data
  
  The data used for training come from the [Twitter Sentiment](https://danlp-alexandra.readthedocs.io/en/latest/docs/datasets.html#twitsent) and [EuroParl sentiment 2](https://danlp-alexandra.readthedocs.io/en/latest/docs/datasets.html#europarl-sentiment2) datasets.