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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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widget: |
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- text: Jeg ejer en rød bil og det er en god bil. |
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--- |
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# Danish BERT for emotion classification |
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The BERT Emotion model classifies a Danish text in one of the following class: |
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* Glæde/Sindsro |
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* Tillid/Accept |
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* Forventning/Interrese |
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* Overasket/Målløs |
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* Vrede/Irritation |
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* Foragt/Modvilje |
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* Sorg/trist |
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* Frygt/Bekymret |
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It is based on the pretrained [Danish BERT](https://github.com/certainlyio/nordic_bert) model by BotXO which has been fine-tuned on social media data. |
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This model should be used after detecting whether the text contains emotion or not, using the binary [BERT Emotion model](https://huggingface.co/alexandrainst/da-binary-emotion-classification-base). |
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See the [DaNLP documentation](https://danlp-alexandra.readthedocs.io/en/latest/docs/tasks/sentiment_analysis.html#bert-emotion) 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-emotion-classification-base") |
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tokenizer = BertTokenizer.from_pretrained("alexandrainst/da-emotion-classification-base") |
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``` |
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## Training data |
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The data used for training has not been made publicly available. It consists of social media data manually annotated in collaboration with Danmarks Radio. |
