BERTweet-large-sexism-detector

This is a fine-tuned model of BERTweet-large on the Explainable Detection of Online Sexism (EDOS) dataset. It is intended to be used as a classification model for identifying tweets (0 - not sexist; 1 - sexist).

More information about the original pre-trained model can be found here

Classification examples:

Prediction	Tweet
sexist	Every woman wants to be a model. It's codeword for "I get everything for free and people want me"
not sexist	basically I placed more value on her than I should then?

More Details

For more details about the datasets and eval results, see (we will updated the page with our paper link)

How to use

from transformers import AutoModelForSequenceClassification, AutoTokenizer,pipeline
import torch
model = AutoModelForSequenceClassification.from_pretrained('sana-ngu/BERTweet-large-sexism-detector')
tokenizer = AutoTokenizer.from_pretrained('vinai/bertweet-large') 
classifier = pipeline("text-classification", model=model, tokenizer=tokenizer)
prediction=classifier("Every woman wants to be a model. It's codeword for 'I get everything for free and people want me' ")
label_pred = 'not sexist' if prediction == 0 else 'sexist' 

print(label_pred)