ibm-granite/granite-embedding-small-english-r2
Model Summary: Granite-embedding-small-english-r2 is a 47M parameter dense biencoder embedding model from the Granite Embeddings collection that can be used to generate high quality text embeddings.
Overview
Benchmarks
CosQA
Code search with natural language queries
Corpus: 6,267 Queries: 500
Quality
map at 10 0.2733
mrr at 10 0.3107
ndcg at 10 0.3530
FiQA2018
Financial opinion mining and question answering
Corpus: 57,599 Queries: 648
Quality
map at 10 0.2614
mrr at 10 0.3941
ndcg at 10 0.3317
NFCorpus
Biomedical literature search from NutritionFacts.org
Corpus: 3,593 Queries: 323
Quality
ndcg at 10 0.3016
map at 10 0.1115
mrr at 10 0.5082
SCIDOCS
Citation prediction, document classification, and recommendation for scientific papers
Corpus: 25,656 Queries: 1,000
Quality
map at 10 0.0595
mrr at 10 0.1655
ndcg at 10 0.1026
SciFact
Scientific claim verification using research literature
Corpus: 5,183 Queries: 300
Quality
map at 10 0.6724
mrr at 10 0.6832
ndcg at 10 0.7157
StackOverflowQA
Programming question answering from Stack Overflow
Corpus: 19,931 Queries: 1,994
Quality
map at 10 0.8818
mrr at 10 0.8818
ndcg at 10 0.9005