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LENS D4000
L
LENS D4000
Developed by yibinlei
LENS-4000 is a transformer-based text embedding model focused on feature extraction and sentence similarity calculation, excelling in multiple text classification tasks.
Downloads 19
Release Time : 12/30/2024
Model Overview
This model is primarily used for text embedding and feature extraction, capable of efficiently calculating sentence similarity and suitable for various natural language processing tasks.
Model Features
High-performance text classification
Excels in multiple text classification tasks, such as achieving 97.05% accuracy in Amazon review classification.
Sentence similarity calculation
Capable of efficiently calculating similarity between sentences, suitable for information retrieval and matching tasks.
Multi-task support
Supports various natural language processing tasks, including classification and retrieval.
Model Capabilities
Text embedding
Feature extraction
Sentence similarity calculation
Text classification
Information retrieval
Use Cases
E-commerce
Amazon review classification
Performs sentiment classification (positive/negative) on Amazon product reviews.
Accuracy 97.05%, F1 score 97.05%
Counterfactual review detection
Identifies counterfactual reviews on the Amazon platform.
Accuracy 93.61%, F1 score 93.76%
Information retrieval
Argument retrieval
Retrieves relevant arguments in debate datasets.
NDCG@10 score 77.32
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