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.
Runs of utahnlp tevatron-elastic-bert-retriever-starbucks on huggingface.co
10
Total runs
0
24-hour runs
3
3-day runs
4
7-day runs
3
30-day runs
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