Gte Base
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Gte Base
Developed by thenlper
GTE-Base is a general-purpose text embedding model focused on sentence similarity and text retrieval tasks, performing well on multiple benchmarks.
Downloads 317.05k
Release Time : 7/27/2023
Model Overview
GTE-Base is a transformer-based sentence embedding model primarily used for generating high-quality sentence embeddings, suitable for tasks such as text similarity calculation, information retrieval, and text classification.
Model Features
Excellent Multi-task Performance
Performs consistently and excellently on various tasks including sentence similarity, text classification, clustering, and retrieval.
High-quality Sentence Embeddings
Capable of generating high-quality sentence-level embeddings suitable for various downstream NLP tasks.
Extensive Benchmark Validation
Comprehensively evaluated on multiple standard benchmark datasets such as MTEB.
Model Capabilities
Sentence similarity calculation
Text classification
Text clustering
Information retrieval
Semantic search
Text re-ranking
Use Cases
E-commerce
Product Review Classification
Sentiment polarity classification for Amazon product reviews
Achieved 91.77% accuracy on the AmazonPolarity dataset
Counterfactual Review Detection
Identifying counterfactual reviews on Amazon
Achieved 74.18% accuracy on the AmazonCounterfactual dataset
Customer Service
Banking Intent Classification
Intent classification for bank customer inquiries
Achieved 85.07% accuracy on the Banking77 dataset
Academic Research
Paper Clustering
Topic clustering for arXiv and biorxiv papers
Achieved 48.60% v_measure on the ArxivClusteringP2P dataset
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