About the Model An English sequence classification model, trained on MBAD Dataset to detect bias and fairness in sentences (news articles). This model was built on top of distilbert base uncased model and trained for 30 epochs with a batch size of 16, a learning rate of 5e 5, and a maximum sequence length of 512. Dataset : MBAD Data Carbon emission 0.319355 Kg Train Accuracy Validation Accuracy Train loss Test loss : : : : 76.97 62.00 0.45 0.96 Usage The easiest way is to load the inference api from huggingface and second method is through the pipeline object offered by transformers library. Author This model is part of the Research topic "Bias and Fairness in AI" conducted by Deepak John Reji, Shaina Raza. If you use this work (code, model or dataset), please star at: Bias & Fairness in AI, (2022), GitHub repository,
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