QA Strategy

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>Here's an outline for a Quality Assurance (QA) strategy to test your GPT model against the Library of Congress MARC records:

  1. Data Validation:

  • Ensure the MARC 21 documentation used for training is accurate and comprehensive.
  • Verify the integrity of the actual Library of Congress MARC records you plan to use for testing.

    1. Model Training Assessment:

    • Check if the model has been trained effectively with the MARC 21 documentation.
    • Evaluate whether key concepts and details are correctly structured and understood by the model.

      1. Automated Testing:

      • Develop automated test scripts that feed MARC records to the model and assess its responses for accuracy.
      • Include a variety of records to cover different aspects of the MARC 21 format.

        1. Manual Review:

        • Conduct a manual review of the model's responses to ensure they align with the expected outputs based on the MARC records.
        • Involve subject matter experts who are familiar with MARC 21 and library cataloging practices.

          1. Performance Metrics:

          • Establish performance metrics like accuracy, response time, and relevance of the model's answers.
          • Use these metrics to quantitatively assess the model's performance.

            1. Feedback and Iteration:

            • Collect feedback from the tests and use it to refine the model.
            • Reiterate the training and testing process based on this feedback to continuously improve the model.

              1. Documentation and Reporting:

              • Keep thorough documentation of the testing process, methodologies, and results.
              • Report on the findings, highlighting areas of success and those needing improvement.

                1. Compliance and Ethical Considerations:

                • Ensure that the testing process adheres to any legal and ethical standards, particularly in handling and using MARC records from the Library of Congress.

                Remember, a robust QA strategy is iterative and should be adapted as you gather more insights from your testing phases. 

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