DistilBERT-base-uncased-finetuned-squad Open-source Q&A Model - Empowering Efficient Completion of Reading Comprehension Tasks

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Distilbert Base Uncased Finetuned Squad

Developed by ak987

A Q&A model based on DistilBERT, fine-tuned on the SQuAD dataset for reading comprehension tasks

Question Answering System

Transformers

Open Source License:Apache-2.0 #Q&A System #Reading Comprehension #Lightweight BERT

Downloads 15

Release Time : 5/22/2022

Model Overview

This model is a fine-tuned version of DistilBERT, specifically optimized for question-answering tasks, capable of answering questions based on given context.

Model Features

Lightweight BERT

Based on the DistilBERT architecture, it is 40% smaller than standard BERT while retaining 97% of its language understanding capabilities

Q&A Optimization

Specifically fine-tuned on the SQuAD Q&A dataset, excelling at extracting answers from text

Efficient Inference

Faster inference speed and lower resource consumption compared to the full BERT model

Model Capabilities

Reading Comprehension

Answer Extraction

Text Understanding

Use Cases

Educational Technology

Automated Answering System

Helps students quickly find answers to questions from textbooks

Customer Service

FAQ Auto-Response

Extracts relevant answers from knowledge base documents to respond to customer queries

Training Loss	Epoch	Step	Validation Loss
1.2253	1.0	5533	1.1728
0.9685	2.0	11066	1.1400
0.7604	3.0	16599	1.1576

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Distilbert Base Uncased Finetuned Squad

Model Overview

Model Features

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