utahnlp / tevatron-elastic-bert-retriever-starbucks

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Total runs: 10
24-hour runs: 0
7-day runs: 4
30-day runs: 3
Model's Last Updated: July 11 2026
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Introduction of tevatron-elastic-bert-retriever-starbucks

Model Details of tevatron-elastic-bert-retriever-starbucks

tevatron-elastic-bert-retriever-starbucks

A retriever trained with Tevatron-Elastic , which trains one checkpoint to serve many operating points along the depth / width / token compression axes. This checkpoint is an elastic depth×width schedule (2D Matryoshka, Starbucks-style).

  • Base model: google-bert/bert-base-uncased
  • Task: retriever
  • Elastic axis: starbucks
  • Training data: rlhn/rlhn-680K , max length 512, query: / passage: prefixes.

Full-point BEIR-15 nDCG@10: 0.448 .

Load with the Tevatron-Elastic framework and select an operating point with prune_to / encode_at ; see the repository for usage. Part of a release of 20 checkpoints (3 backbones, retrieval and reranking, all compression axes) accompanying the Tevatron-Elastic paper. Reported as a reproducibility resource, not a state-of-the-art claim.

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10
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Updated:December 30 2025