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Developed by junzai
Text classification model fine-tuned on GLUE MRPC dataset based on bert-base-uncased
Text Classification
Transformers
 EnglishOpen Source License:Apache-2.0#Text similarity analysis#High accuracy F1 score#GLUE fine-tuning
Downloads 15
Release Time : 3/2/2022

Model Overview

This model is a text classification model fine-tuned from the BERT base version on the GLUE MRPC (Microsoft Research Paraphrase Corpus) dataset, used to determine whether sentence pairs are semantically equivalent.

Model Features

High accuracy
Achieves 82.84% accuracy and 88.18% F1 score on the GLUE MRPC test set
Based on pre-trained model
Fine-tuned from the widely used bert-base-uncased model, with excellent language understanding capabilities
Lightweight fine-tuning
Requires only a small amount of training data to achieve good performance, with only 1 training epoch

Model Capabilities

Text classification
Semantic similarity judgment
Natural language understanding

Use Cases

Text processing
Paraphrase detection
Determine if two sentences express the same meaning
Accuracy 82.84%, F1 score 88.18%
Q&A systems
Determine if user questions and system answers are semantically matched
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