
Frederik Gaasdal Jensen • Henry Stoll • Sippo Rossi • Raghava Rao Mukkamala

# UNHCR Hate Speech Detection Model
This is a transformer model that can detect hate and offensive speech for English text. The primary use-case of this model is to detect hate speech targeted at refugees.  The model is based on *roberta-uncased* and was fine-tuned on 12 abusive language datasets.

The model has been developed as a collaboration between UNHCR, the UN Refugee Agency, and Copenhagen Business School.

- F1-score on test set (10% of the overall dataset): 81%
- Hatecheck score: 90.3% 

## Labels

```python
{
  0: "Normal",
  1: "Offensive",
  2: "Hate speech",
}
```

{"language": "en", "tags": ["text classification", "hate speech", "offensive language", "hatecheck"], "datasets": ["unhcr-hatespeech"], "metrics": ["f1", "hatecheck"]}
transformers pytorch roberta text-classification text classification hate speech offensive language hatecheck en dataset:unhcr-hatespeech autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #text-classification #text classification #hate speech #offensive language #hatecheck #en #dataset-unhcr-hatespeech #autotrain_compatible #endpoints_compatible #region-us 


Frederik Gaasdal Jensen • Henry Stoll • Sippo Rossi • Raghava Rao Mukkamala

# UNHCR Hate Speech Detection Model
This is a transformer model that can detect hate and offensive speech for English text. The primary use-case of this model is to detect hate speech targeted at refugees.  The model is based on *roberta-uncased* and was fine-tuned on 12 abusive language datasets.

The model has been developed as a collaboration between UNHCR, the UN Refugee Agency, and Copenhagen Business School.

- F1-score on test set (10% of the overall dataset): 81%
- Hatecheck score: 90.3% 

## Labels



# UNHCR Hate Speech Detection Model
This is a transformer model that can detect hate and offensive speech for English text. The primary use-case of this model is to detect hate speech targeted at refugees.  The model is based on *roberta-uncased* and was fine-tuned on 12 abusive language datasets.

The model has been developed as a collaboration between UNHCR, the UN Refugee Agency, and Copenhagen Business School.

- F1-score on test set (10% of the overall dataset): 81%
- Hatecheck score: 90.3% ## Labels
TAGS
#transformers #pytorch #roberta #text-classification #text classification #hate speech #offensive language #hatecheck #en #dataset-unhcr-hatespeech #autotrain_compatible #endpoints_compatible #region-us 
 # UNHCR Hate Speech Detection Model
This is a transformer model that can detect hate and offensive speech for English text. The primary use-case of this model is to detect hate speech targeted at refugees.  The model is based on *roberta-uncased* and was fine-tuned on 12 abusive language datasets.

The model has been developed as a collaboration between UNHCR, the UN Refugee Agency, and Copenhagen Business School.

- F1-score on test set (10% of the overall dataset): 81%
- Hatecheck score: 90.3% ## Labels
passage: TAGS
#transformers #pytorch #roberta #text-classification #text classification #hate speech #offensive language #hatecheck #en #dataset-unhcr-hatespeech #autotrain_compatible #endpoints_compatible #region-us 
# UNHCR Hate Speech Detection Model
This is a transformer model that can detect hate and offensive speech for English text. The primary use-case of this model is to detect hate speech targeted at refugees.  The model is based on *roberta-uncased* and was fine-tuned on 12 abusive language datasets.

The model has been developed as a collaboration between UNHCR, the UN Refugee Agency, and Copenhagen Business School.

- F1-score on test set (10% of the overall dataset): 81%
- Hatecheck score: 90.3%## Labels