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--- |
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language: |
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- da |
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license: apache-2.0 |
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datasets: |
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- DDSC/twitter-sent |
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- DDSC/europarl |
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widget: |
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- text: Jeg tror alligvel, det bliver godt |
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--- |
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# Danish BERT Tone for the detection of subjectivity/objectivity |
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The BERT Tone model detects whether a text (in Danish) is subjective or objective. |
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The model is based on the finetuning of the pretrained [Danish BERT](https://github.com/certainlyio/nordic_bert) model by BotXO. |
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See the [DaNLP documentation](https://danlp-alexandra.readthedocs.io/en/latest/docs/tasks/sentiment_analysis.html#bert-tone) for more details. |
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Here is how to use the model: |
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```python |
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from transformers import BertTokenizer, BertForSequenceClassification |
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model = BertForSequenceClassification.from_pretrained("alexandrainst/da-subjectivivity-classification-base") |
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tokenizer = BertTokenizer.from_pretrained("alexandrainst/da-subjectivivity-classification-base") |
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``` |
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## Training data |
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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. |
