Learn Before
Example of SFT Dataset Samples
A Supervised Fine-Tuning (SFT) dataset is composed of samples, where each sample includes an input x and an output y. The input x typically combines an instruction with user-provided context (e.g., an article to summarize, a report to analyze). The output y is the desired response that correctly follows the instruction. For instance, tasks can range from summarization and financial data extraction to email classification and technical troubleshooting.
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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
Related
Example of SFT Dataset Samples
Key Attributes of Effective SFT Datasets and Their Impact on LLM Performance
Input and Output Sequences in SFT
A team is preparing a dataset to fine-tune a pre-trained language model to follow specific instructions. Which of the following data entries best exemplifies the fundamental structure of a single sample in a Supervised Fine-Tuning (SFT) dataset?
Evaluating a Potential Fine-Tuning Dataset
Characteristics of SFT Datasets
Analyzing Data Samples for Instruction-Following
Learn After
A machine learning engineer is preparing data to teach a language model how to summarize news articles. Which of the following examples represents a single, well-formed data sample that correctly combines an instruction, context, and a desired response for this task?
Evaluating SFT Data Sample Quality
Constructing an SFT Data Sample for Email Classification