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Stella En 400M V5

Developed by billatsectorflow
Stella 400M v5 is an English text embedding model that excels in multiple text classification and retrieval tasks.
Downloads 7,630
Release Time : 1/22/2025

Model Overview

This model is an English text embedding model primarily designed for text classification and retrieval tasks, demonstrating excellent performance across multiple standard datasets.

Model Features

High-performance Text Classification
Achieves 97.19% accuracy on Amazon product review classification tasks
Powerful Text Retrieval Capability
Scores 64.24 NDCG@10 on the ArguAna retrieval task
Multi-task Adaptability
Performs consistently across various text processing tasks, including classification and retrieval

Model Capabilities

Text Classification
Text Retrieval
Semantic Similarity Calculation
Text Embedding Generation

Use Cases

E-commerce
Product Review Classification
Classify Amazon product reviews as positive/negative
97.19% accuracy
Product Review Multi-classification
Classify Amazon product reviews by star rating
59.53% accuracy
Information Retrieval
Argument Retrieval
Perform argument retrieval on the ArguAna dataset
NDCG@10 64.24
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