| | --- |
| | language: |
| | - da |
| | license: apache-2.0 |
| | widget: |
| | - text: Jeg ejer en rød bil og det er en god bil. |
| | --- |
| | |
| | # Danish BERT for emotion classification |
| |
|
| | The BERT Emotion model classifies a Danish text in one of the following class: |
| | * Glæde/Sindsro |
| | * Tillid/Accept |
| | * Forventning/Interrese |
| | * Overasket/Målløs |
| | * Vrede/Irritation |
| | * Foragt/Modvilje |
| | * Sorg/trist |
| | * Frygt/Bekymret |
| |
|
| | 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. |
| |
|
| | 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). |
| |
|
| | See the [DaNLP documentation](https://danlp-alexandra.readthedocs.io/en/latest/docs/tasks/sentiment_analysis.html#bert-emotion) for more details. |
| |
|
| | Here is how to use the model: |
| |
|
| | ```python |
| | from transformers import BertTokenizer, BertForSequenceClassification |
| | |
| | model = BertForSequenceClassification.from_pretrained("alexandrainst/da-emotion-classification-base") |
| | tokenizer = BertTokenizer.from_pretrained("alexandrainst/da-emotion-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. |
