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Albert Base V2 Mrpc
A
Albert Base V2 Mrpc
Developed by Alireza1044
Text classification model fine-tuned on GLUE MRPC dataset based on albert-base-v2
Downloads 39
Release Time : 3/2/2022
Model Overview
This model is specifically designed for sentence pair semantic equivalence judgment tasks, excelling on the Microsoft Research Paraphrase Corpus (MRPC)
Model Features
High-precision Semantic Matching
Achieves 90.1% F1 score on MRPC test set, accurately determining whether sentence pairs express the same semantics
Lightweight Architecture
Parameter-efficient design based on ALBERT, more efficient than traditional BERT models
Model Capabilities
Text Similarity Judgment
Sentence Pair Classification
Semantic Equivalence Analysis
Use Cases
Text Processing
Q&A Systems
Judging semantic equivalence between user questions and knowledge base questions
Improves answer matching accuracy
Content Deduplication
Identifying differently phrased but semantically identical content in news or documents
Effectively reduces redundant information
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