---
license: cc-by-nc-sa-4.0
language:
- en
metrics:
- f1
- accuracy
widget:
  - text: >-
      Girls like attention and they get desperate
tags:
- sexism
---

# BERTweet for sexism detection

This is a fine-tuned BERTweet large ([BERTweet: A pre-trained language model for English Tweets](https://aclanthology.org/2020.emnlp-demos.2/)) model for detecting sexism.
The training dataset is Explainable Detection of Online Sexism ([**EDOS**](https://github.com/rewire-online/edos)) consisting of 16000 entries in
English gathered from social media platforms: Twitter and Gab. It achieved a **Macro-F1** score of **0.85** and an **Accuracy** of **0.88** on the test set for the EDOS task.

## How to use

```python
from transformers import AutoModelForSequenceClassification, AutoTokenizer, pipeline

# Load model and tokenizer
tokenizer = AutoTokenizer.from_pretrained('tum-nlp/bertweet-sexism')
model = AutoModelForSequenceClassification.from_pretrained('tum-nlp/bertweet-sexism')

# Create the pipeline for classification
sexism_classifier = pipeline("text-classification", model=model, tokenizer=tokenizer)

# Predict
sexism_classifier("Girls like attention and they get desperate")
```

## Licensing Information

[Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License][cc-by-nc-sa].

[![CC BY-NC-SA 4.0][cc-by-nc-sa-image]][cc-by-nc-sa]

[cc-by-nc-sa]: http://creativecommons.org/licenses/by-nc-sa/4.0/
[cc-by-nc-sa-image]: https://i.creativecommons.org/l/by-nc-sa/4.0/88x31.png