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Bert Finetuned Squad

Developed by spasis
A BERT-based question answering model fine-tuned on the SQuAD dataset
Downloads 16
Release Time : 5/22/2022

Model Overview

This model is a BERT variant optimized for question answering tasks, excelling at extracting answers from given text.

Model Features

SQuAD Dataset Fine-tuning
Specially optimized on the Stanford Question Answering Dataset (SQuAD), with precise answer extraction capabilities
BERT Architecture Advantages
Based on the powerful BERT-base-cased architecture, featuring bidirectional Transformer contextual understanding
Efficient Training
Utilizes mixed-precision training (AMP) and Adam optimizer for high training efficiency

Model Capabilities

Reading Comprehension
Answer Extraction
Context Understanding

Use Cases

Education
Automated Answering System
Helps students quickly find answers to questions from textbooks
Customer Service
FAQ Auto-Response
Extracts precise answers from knowledge base documents to respond to customer inquiries
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