shahrukhx01/bert-probe

BERT Probe: A python package for probing attention based robustness to character and word based adversarial evaluation. Also, with recipes of implicit and explicit defenses against character-level attacks.

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This package helps machine learning engineers and researchers assess how robust BERT models are to subtle changes in text, like typos or word substitutions, that adversaries might use. It takes a trained BERT model and a dataset, then exposes how the model's predictions change when presented with adversarial examples. The output provides insights into the model's vulnerabilities and suggests strategies to make it more resilient.

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Use this if you need to evaluate the resilience of your BERT-based text classification models against adversarial attacks and implement defenses to improve their robustness.

Not ideal if you are looking for a general-purpose BERT training framework or a tool to simply fine-tune BERT for standard tasks without a focus on adversarial robustness.

natural-language-processing model-security hate-speech-detection text-classification adversarial-machine-learning
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 16 / 25
Community 12 / 25

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18

Forks

3

Language

Jupyter Notebook

License

Apache-2.0

Last pushed

Jun 24, 2022

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