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---
license: openrail
language:
- en
---
## 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")
pipe = pipeline("text-classification", model="newsmediabias/UnBIAS-classification-bert")
classifier("Anyone can excel at coding.")
```
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