Transformer models have revolutionized natural language processing, achieving state-of-the-art results on a variety of tasks. However, these powerful models are susceptible to inheriting and amplifying biases present in the training data. mitigating bias and promoting fairness in transformer models is crucial to prevent the perpetuation of harmful