--- language: - da tags: - bert - pytorch - subjectivity - objectivity license: CC-BY_4.0 datasets: - Twitter Sentiment - Europarl Sentiment widget: - text: "Jeg tror alligvel, det bliver godt" metrics: - f1 --- # 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("DaNLP/da-bert-tone-subjective-objective") tokenizer = BertTokenizer.from_pretrained("DaNLP/da-bert-tone-subjective-objective") ``` ## 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.