---
license: apache-2.0
language:
- nl
pipeline_tag: text-classification
---

Fine-tuned model for detecting instances of abusive language in Ducth tweets. The model has been trained with [DALC v2.0 ](https://github.com/tommasoc80/DALC).

Abusive language is defined as "Impolite, harsh, or hurtful language (that may contain profanities or vulgar language) that result in a debasement, harassment,
threat, or aggression of an individual or a (social) group, but not necessarily of an entity, an institution, an organisations, or a concept." ([Ruitenbeek et al., 2022](https://aclanthology.org/2022.woah-1.5/))

The model achieve the following results on multiple test data:

- DALC held-out test set: macro F1: 72.23; F1 Abusive: 51.60
- HateCheck-NL (functional benchmark for hate speech): Accuracy: 60.19;  Accuracy non-hateful tests: 57.38 ; Accuracy hateful tests: 59.58
- OP-NL (dynamyc benchmark for offensive language): macro F1: 57.57

More details on the training settings and pre-processind are available [here](https://github.com/tommasoc80/DALC)