
# 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.
{"language": ["da"], "license": "apache-2.0", "widget": [{"text": "Jeg ejer en r\u00f8d bil og det er en god bil."}]}
transformers pytorch tf bert text-classification da license:apache-2.0 autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #tf #bert #text-classification #da #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 


# 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:



## 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.
# 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: ## 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.
TAGS
#transformers #pytorch #tf #bert #text-classification #da #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 
 # 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: ## 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.
passage: TAGS
#transformers #pytorch #tf #bert #text-classification #da #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 
# 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:## 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.