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Distilbert Base Uncased Finetuned Squad
A question-answering model fine-tuned on the SQuAD dataset based on distilbert-base-uncased
Downloads 15
Release Time : 12/2/2022
Model Overview
This model is a lightweight version of DistilBERT, fine-tuned on the SQuAD question-answering dataset, specifically designed for QA tasks. It retains most of BERT's performance while reducing model size and computational resource requirements.
Model Features
Lightweight Architecture
Based on DistilBERT architecture, 40% smaller than standard BERT while retaining 97% of its language understanding capability
Efficient Fine-tuning
Specially fine-tuned on the SQuAD QA dataset to optimize performance for QA tasks
Low Resource Requirements
Significantly reduced computational resources needed for training and inference compared to original BERT
Model Capabilities
Reading Comprehension
Question Answering
Text Understanding
Use Cases
Education
Automated QA System
Used to build automated question-answering systems in education to answer student questions
Customer Service
Intelligent Customer Service
Deployed in customer service systems to automatically answer common questions
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