Sign inGet started
Dataset · Hugging Face

tomaarsen/gooaq-hard-negatives

Dataset Card for GooAQ with mined hard negatives This dataset is a collection of question-answer-negative triplets and question-answer-negative_1...-negative_5 tuples from the GooAQ dataset. See GooAQ for additional information. This dataset can be used directly with Sentence Transformers to train embedding models. The negative samples have been automatically mined with all-MiniLM-L6-v2 and: range_min: 10, i.e. we skip the 10 most similar samples range_max: 100, i.e. we only… See the full description on the dataset page: https://huggingface.co/datasets/tomaarsen/gooaq-hard-negatives.

Author / organizationtomaarsen
Downloads135 (as reported by Hugging Face)
Likes11
Created19 June 2024
Last updated at source19 June 2024
sentence-transformers
Embed this entry
<iframe src="https://silytics.si/embed/item/67a6b105-2b4f-44d9-8978-b595d6b651da" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Free, no tracking. More about feeds and embeds.

Popularity, last 4 days

135 now (-37 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.

Connected in the knowledge graph

Explore this entry in the graph

Recent changes

  • 17 Oct 2026 Description: Dataset Card for GooAQ with mined hard negatives This dataset is a collection of question-answer-negative triplets and question-answer-negative_1...-negative_5 tuples from the GooAQ dataset. See GooAQ for additional information. This datase → Dataset Card for GooAQ with mined hard negatives This dataset is a collection of question-answer-negative triplets and question-answer-negative_1...-negative_5 tuples from the GooAQ dataset. See GooAQ for additional information. This datase

Changes detected by Silytics between refreshes of the source.

More from tomaarsen

Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 19 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.