Assessing the Quality of Synthetic Data with Data-Centric AI(cleanlab.ai)

Assessing the Quality of Synthetic Data with Data-Centric AI

https://cleanlab.ai/blog/studio-synthetic-data/

2 comments

Many folks using LLMs to generate data nowadays, but how do you know which synthetic data is good?

Introducing synthetic data quality assessment! Without writing ANY code, you can quickly identify which synthetic data is unrealistic (ie. low-quality) and which real data is underrepresented in the synthetic samples. This tool works seamlessly across synthetic text, image, and tabular datasets.

In this blogpost we demonstrate how to automatically detect issues in synthetic customer reviews data generated from the [Gretel.ai](http://Gretel.ai) LLM synthetic data generator.

seaEngineering3 anni fa

Data Quality is key for all applications and models, and LLMs are no exception :) I've been working on a small community project with synthetic data (https://github.com/ydataai/ydata-synthetic) using ydata-synthetic, and it really shows! Underrepresentation (category imbalance) and missing data are two of the main issues!