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Dunzhang Stella En 400M V5

Developed by Marqo
Stella 400M is a medium-scale English text processing model focused on classification and information retrieval tasks.
Downloads 17.20k
Release Time : 9/25/2024

Model Overview

This model is primarily used for text classification and information retrieval tasks, demonstrating excellent performance on multiple standard datasets.

Model Features

High-performance classification
Achieved 97.19% accuracy on Amazon product review classification task
Multi-task capability
Supports various text processing tasks including classification and information retrieval
Medium-scale
Balanced 400M parameter design that balances performance and efficiency

Model Capabilities

Text classification
Sentiment analysis
Information retrieval
Text similarity calculation

Use Cases

E-commerce
Product review classification
Automatically classify sentiment tendencies of Amazon product reviews
Achieved 97.19% accuracy on Amazon polarity classification task
Multi-class review classification
Perform multi-star classification on Amazon reviews
Achieved 59.53% accuracy on Amazon multi-class review task
Information retrieval
Argument retrieval
Perform argument matching retrieval on ArguAna dataset
Achieved a main score of 64.24
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