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Evaluating a Self-Instruct Filtering Strategy
Based on the provided scenario, evaluate the team's current filtering strategy. Explain why it is likely contributing to the observed performance issue and suggest a more effective filtering heuristic to improve the diversity of the generated instructions.
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Ch.4 Alignment - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
Evaluation in Bloom's Taxonomy
Cognitive Psychology
Psychology
Social Science
Empirical Science
Science
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A team uses an iterative process to automatically generate a large instruction-tuning dataset, starting from a small set of initial examples. After fine-tuning, the resulting model performs very well on tasks that are nearly identical to the initial examples but fails to generalize to new, unseen types of instructions. What is the most probable deficiency in the data generation pipeline that led to this outcome?
A team is using an iterative method to expand a small set of seed instructions into a large dataset for model training. Arrange the following steps of a single generation cycle in the correct chronological order.
Evaluating a Self-Instruct Filtering Strategy