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We study the general trend in bias reduction as newer pre-trained models are released. Three recent models ( ELECTRA, DeBERTa and DistilBERT) are chosen and evaluated against two bias benchmarks, StereoSet and CrowS-Pairs. They are compared to the baseline of BERT using the associated metrics

License: Apache License 2.0

Python 82.56% Shell 8.33% Jupyter Notebook 9.11%
bias-detection

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bias-evaluation's Issues

Define a protocol for evaluating a model (read description)

  • We will be dealing with several models (BERT, RoBERTa, DistilBERT, etc).
  • So, it would be simpler if we can define a protocol that all the model implementations respect.
  • This enables us to evaluate all the models with a unified interface.

Other thoughts:

  • We may need different types of protocols for different evaluation benchmarks.

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