Generating Diverse Instructions for a Summarization Task
You are preparing a dataset to fine-tune a language model for a single-sentence summarization task. To make the model more robust and flexible, you need to create varied instructions for this same task. Provide three distinct instructions you would use in your dataset. Each instruction should prompt the model to summarize a given text into one sentence, but be phrased differently.
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Ch.2 Generative Models - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
Creation in Bloom's Taxonomy
Cognitive Psychology
Psychology
Social Science
Empirical Science
Science
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A team is fine-tuning a language model for a single, specific task: extracting the main sentiment (positive, negative, or neutral) from customer reviews. To ensure the final model is robust and can handle the varied ways users might phrase this request, which of the following training data strategies is the most effective?
Diagnosing a Fine-Tuning Data Issue
Generating Diverse Instructions for a Summarization Task
Example of a Sentence-First Prompt for Grammaticality Judgment with Answer Options
Example of a Constraint-First Prompt for Grammaticality Judgment