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Electra Large Discriminator Squad2 512
E

Electra Large Discriminator Squad2 512

Developed by ahotrod
This is a large-scale discriminator model based on the ELECTRA architecture, specifically fine-tuned for Q&A tasks on the SQuAD2.0 dataset, capable of handling both answerable and unanswerable question scenarios.
Question Answering System
Transformers
#High-precision Q&A System#No-answer Detection#ELECTRA Architecture
Downloads 8,925
Release Time : 3/2/2022

Model Overview

This model is a Q&A system based on the ELECTRA architecture, fine-tuned on the SQuAD2.0 dataset, with the ability to handle open-domain Q&A and determine whether a question is answerable.

Model Features

High-precision Q&A
Achieves 87.1% exact match rate and 90.0% F1 score on the SQuAD2.0 test set
No-answer Detection
Effectively identifies unanswerable questions, with an F1 score of 89.5% in no-answer scenarios
Efficient Training
Uses ELECTRA pre-training architecture, more efficient than traditional BERT

Model Capabilities

Open-domain Q&A
No-answer Detection
Text Understanding
Contextual Reasoning

Use Cases

Intelligent Customer Service
Automated Q&A System
Used to build customer service automated Q&A systems to answer common user questions
87.1% accuracy, significantly reducing the pressure on human customer service
Education
Learning Assistance Q&A
Helps students answer textbook-related questions
Can accurately answer over 90% of textbook-related questions
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