Bias Classification Using Bert

Overview:

This is a BERT based model designed to detect bias in text data enabling users to identify whether a given text is biased or non-biased.

Performance:

The model's performance on unseen data is:

Non-biased Precision: 0.93 Recall: 0.96

Biased Precision: 0.91 Recall: 0.88

Overall accuracy : 0.93

Usage

To use the model, you can utilize the transformers library from Hugging Face:

from transformers import AutoTokenizer, AutoModelForSequenceClassification

tokenizer = AutoTokenizer.from_pretrained("newsmediabias/UnBIAS-classification-bert")
model = AutoModelForSequenceClassification.from_pretrained("newsmediabias/UnBIAS-classification-bert")

classifier = pipeline("text-classification", model=model, tokenizer=tokenizer , device=0 if device.type == "cuda" else -1)


classifier("Anyone can excel at coding.")