sarahooker/adaption-hacker-news-article-prompts

This dataset is a remastered version of this dataset prepared using Adaption's Adaptive Data platform.

hackernewsarticle_prompts

This dataset contains text generation prompts derived from Hacker News article titles, instructing models to write full articles based on provided or self-generated headlines. The samples include specific tech and business topics from the Hacker News community, as well as instances where the model must invent a title from scratch. It is designed for training or evaluating systems on long-form content generation and headline expansion tasks.

Dataset size

There are 51 data points in this dataset. This is an instruction tuning dataset.

Quality of Remastered Dataset

The final quality is B, with a relative quality improvement of 58.0%.

Domain

• —Writing-editing-communication (64%)
• —Corporate-business (21%)
• —Marketing (7%)

Language

• —English (100%)

Tone

• —Creative (29%)
• —Informative (21%)
• —Humorous (14%)

Evaluation Results

• —Quality Gains: <img src="https://proteus-prod-public.s3.us-east-1.amazonaws.com/temp/bf26090e-ec53-40d6-bc95-0596e637e9b4.png" alt="QualityGains" style="max-width: 50%; display: block; margin-left: auto; margin-right: auto;" />

• —Grade Improvement: <img src="https://proteus-prod-public.s3.us-east-1.amazonaws.com/temp/d3c3ad76-ccd3-4373-bcaa-0908c4f15c55.png" alt="Grade" style="max-width: 50%; display: block; margin-left: auto; margin-right: auto;" />

• —Percentile Chart: <img src="https://proteus-prod-public.s3.us-east-1.amazonaws.com/temp/bcdc2dbb-8292-4604-9496-86e78e91e1f8.png" alt="Percentile Chart" style="max-width: 50%; display: block; margin-left: auto; margin-right: auto;" />