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Alibaba-NLP/gte-Qwen2-1.5B-instruct

gte-Qwen2-1.5B-instruct is the latest model in the gte (General Text Embedding) model family. The model is built on Qwen2-1.5B LLM model and use the same training data and strategies as the gte-Qwen2-7B-instruct model.

Overview

Architecture
Qwen2
Parameters
1.8B
Tasks
Encode
Outputs
Dense
Dimensions
Dense: 1,536
Max Sequence Length
32,768 tokens
License
apache-2.0

Benchmarks

CQADupstackPhysicsRetrieval

scientific retrieval en

Duplicate question retrieval from StackExchange Physics

Corpus: 38,314 Queries: 1,039
Quality
ndcg at 10 0.2961
map at 10 0.2488
mrr at 10 0.2904
Performance L4 b1 c16
Corpus 11.6K tok/s
Corpus p50 178.5ms
Query 2.2K tok/s
Query p50 69.6ms
Reference →

CosQA

technology retrieval en

Code search with natural language queries

Corpus: 6,267 Queries: 500
Quality
ndcg at 10 0.1225
map at 10 0.0886
mrr at 10 0.0951
Performance L4 b1 c16
Corpus 9.3K tok/s
Corpus p50 96.2ms
Query 1.2K tok/s
Query p50 66.8ms
Reference →

FiQA2018

finance retrieval en

Financial opinion mining and question answering

Corpus: 57,599 Queries: 648
Quality
ndcg at 10 0.2766
map at 10 0.2117
mrr at 10 0.3344
Performance L4 b1 c16
Corpus 11.8K tok/s
Corpus p50 222.9ms
Query 2.1K tok/s
Query p50 73.4ms
Reference →

LegalBenchConsumerContractsQA

legal retrieval en

Question answering on consumer contracts

Corpus: 153 Queries: 396
Quality
ndcg at 10 0.6897
map at 10 0.6244
mrr at 10 0.6268
Performance L4 b1 c16
Corpus 12.3K tok/s
Corpus p50 735.3ms
Query 3.1K tok/s
Query p50 71.9ms
Reference →

NFCorpus

medical retrieval en

Biomedical literature search from NutritionFacts.org

Corpus: 3,593 Queries: 323
Quality
ndcg at 10 0.2547
map at 10 0.0850
mrr at 10 0.4289
Performance L4 b1 c16
Corpus 12.7K tok/s
Corpus p50 384.4ms
Query 821 tok/s
Query p50 90.2ms
Reference →

NanoFiQA2018Retrieval

finance retrieval en

Smaller subset of the FiQA financial QA dataset

Quality
ndcg at 10 0.6524
map at 10 0.5848
mrr at 10 0.7032
Performance L4 b1 c16
Corpus 11.3K tok/s
Corpus p50 251.5ms
Query 1.9K tok/s
Query p50 88.7ms
Reference →

SCIDOCS

scientific retrieval en

Citation prediction, document classification, and recommendation for scientific papers

Corpus: 25,656 Queries: 1,000
Quality
ndcg at 10 0.0368
map at 10 0.0196
mrr at 10 0.0683
Performance L4 b1 c16
Corpus 12.4K tok/s
Corpus p50 261.1ms
Query 2.5K tok/s
Query p50 66.4ms
Reference →

SciFact

scientific retrieval en

Scientific claim verification using research literature

Corpus: 5,183 Queries: 300
Quality
ndcg at 10 0.6056
map at 10 0.5520
mrr at 10 0.5665
Performance L4 b1 c16
Corpus 12.6K tok/s
Corpus p50 370.4ms
Query 3.1K tok/s
Query p50 74.9ms
Reference →

StackOverflowQA

technology retrieval en

Programming question answering from Stack Overflow

Corpus: 19,931 Queries: 1,994
Quality
ndcg at 10 0.3744
map at 10 0.3466
mrr at 10 0.3466
Performance L4 b1 c16
Corpus 12.4K tok/s
Corpus p50 299.2ms
Query 11.4K tok/s
Query p50 421.4ms
Reference →

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