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Demotest
D
Demotest
Developed by junzai
Text classification model fine-tuned on GLUE MRPC dataset based on bert-base-uncased
Downloads 17
Release Time : 3/2/2022
Model Overview
This model is a BERT model fine-tuned on the GLUE MRPC (Microsoft Research Paraphrase Corpus) dataset, primarily used for text classification tasks to determine whether two sentences are semantically equivalent (paraphrase identification).
Model Features
Efficient fine-tuning
Efficient fine-tuning based on pre-trained BERT model, suitable for specific text classification tasks
Semantic understanding
Capable of deep semantic understanding to determine if two sentences express the same meaning
Balanced performance
Achieves balanced performance in accuracy and F1 score (accuracy 82.84%, F1 score 88.18%)
Model Capabilities
Text classification
Semantic similarity judgment
Sentence pair analysis
Use Cases
Text analysis
Paraphrase detection
Determine whether two differently expressed sentences convey the same meaning
Achieved 82.84% accuracy on MRPC test set
Q&A systems
Determine semantic match between user questions and system answers
Content moderation
Duplicate content detection
Identify differently expressed but identical content
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