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First version of the da-bert-emotion-classification model and tokenizer
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metadata
language:
  - da
tags:
  - bert
  - pytorch
  - emotion
license: CC-BY_4.0
datasets:
  - social media
metrics:
  - f1
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 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.

See the DaNLP documentation for more details.

Here is how to use the model:

from transformers import BertTokenizer, BertForSequenceClassification

model = BertForSequenceClassification.from_pretrained("DaNLP/da-bert-emotion-classification")
tokenizer = BertTokenizer.from_pretrained("DaNLP/da-bert-emotion-classification")

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.