

# DKbert-hatespeech-classification

Use this model to detect hatespeech in Danish. For details, guide and command line tool see [DK hate github](https://github.com/Guscode/DKbert-hatespeech-detection)

## Training data

Training data is from OffensEval2020 which can be found [here]( https://figshare.com/articles/dataset/Danish_Hate_Speech_Abusive_Language_data/12220805)

## Performance

The model achieves a macro F1-score of 0.78 

Precision hateful: 0.77

Recall hateful: 0.49

See more on [DK hate github](https://github.com/Guscode/DKbert-hatespeech-detection)

## Training procedure

- [BOTXO Nordic Bert](https://huggingface.co/DJSammy/bert-base-danish-uncased_BotXO,ai)
- Learning rate: 1e-5,
- Batch size: 16
- Max sequence length: 128

## Project information

This model was made in collaboration between [Johan Horsmans](https://github.com/JohanHorsmans) and [Gustav Aarup Lauridsen](https://github.com/Guscode) for their Cultural Data Science Exam.



{"language": ["da"], "license": "mit", "tags": ["Hatespeech", "Danish", "BERT"], "datasets": ["DKHate - OffensEval2020"], "Classes": ["Hateful", "Not Hateful"]}
transformers pytorch tf bert text-classification Hatespeech Danish BERT da license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tf #bert #text-classification #Hatespeech #Danish #BERT #da #license-mit #autotrain_compatible #endpoints_compatible #region-us 



# DKbert-hatespeech-classification

Use this model to detect hatespeech in Danish. For details, guide and command line tool see DK hate github

## Training data

Training data is from OffensEval2020 which can be found here

## Performance

The model achieves a macro F1-score of 0.78 

Precision hateful: 0.77

Recall hateful: 0.49

See more on DK hate github

## Training procedure

- BOTXO Nordic Bert
- Learning rate: 1e-5,
- Batch size: 16
- Max sequence length: 128

## Project information

This model was made in collaboration between Johan Horsmans and Gustav Aarup Lauridsen for their Cultural Data Science Exam.



# DKbert-hatespeech-classification

Use this model to detect hatespeech in Danish. For details, guide and command line tool see DK hate github ## Training data

Training data is from OffensEval2020 which can be found here ## Performance

The model achieves a macro F1-score of 0.78 

Precision hateful: 0.77

Recall hateful: 0.49

See more on DK hate github ## Training procedure

- BOTXO Nordic Bert
- Learning rate: 1e-5,
- Batch size: 16
- Max sequence length: 128 ## Project information

This model was made in collaboration between Johan Horsmans and Gustav Aarup Lauridsen for their Cultural Data Science Exam.
TAGS
#transformers #pytorch #tf #bert #text-classification #Hatespeech #Danish #BERT #da #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 # DKbert-hatespeech-classification

Use this model to detect hatespeech in Danish. For details, guide and command line tool see DK hate github ## Training data

Training data is from OffensEval2020 which can be found here ## Performance

The model achieves a macro F1-score of 0.78 

Precision hateful: 0.77

Recall hateful: 0.49

See more on DK hate github ## Training procedure

- BOTXO Nordic Bert
- Learning rate: 1e-5,
- Batch size: 16
- Max sequence length: 128 ## Project information

This model was made in collaboration between Johan Horsmans and Gustav Aarup Lauridsen for their Cultural Data Science Exam.
passage: TAGS
#transformers #pytorch #tf #bert #text-classification #Hatespeech #Danish #BERT #da #license-mit #autotrain_compatible #endpoints_compatible #region-us 
# DKbert-hatespeech-classification

Use this model to detect hatespeech in Danish. For details, guide and command line tool see DK hate github## Training data

Training data is from OffensEval2020 which can be found here## Performance

The model achieves a macro F1-score of 0.78 

Precision hateful: 0.77

Recall hateful: 0.49

See more on DK hate github## Training procedure

- BOTXO Nordic Bert
- Learning rate: 1e-5,
- Batch size: 16
- Max sequence length: 128## Project information

This model was made in collaboration between Johan Horsmans and Gustav Aarup Lauridsen for their Cultural Data Science Exam.