distilbert-base-uncased-finetuned-squad Open-source Question Answering Model - Freely Assist in Efficiently Completing Question Answering Tasks

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Distilbert Base Uncased Finetuned Squad

Developed by kiana

This model is a fine-tuned version of DistilBERT on the SQuAD v2 question-answering dataset, designed for Q&A tasks.

Question Answering System

Transformers

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

Downloads 15

Release Time : 4/8/2022

Model Overview

A lightweight version of DistilBERT, fine-tuned on the SQuAD v2 dataset, specifically optimized for Q&A systems. It can understand questions and extract answers from given text.

Model Features

Lightweight and Efficient

40% fewer parameters than the original BERT model while maintaining 97% of its performance

Q&A Optimized

Fine-tuned specifically for Q&A tasks on the SQuAD v2 dataset

Uncased Processing

Case-insensitive text processing improves generalization capability

Model Capabilities

Text Understanding

Question Answering

Context Extraction

Use Cases

Smart Customer Service

Automated Q&A System

Automatically answers user questions based on knowledge base documents

Can accurately extract relevant answers from documents

Educational Technology

Learning Assistant Tool

Helps students quickly find answers to questions from textbooks

Training Loss	Epoch	Step	Validation Loss
1.2545	1.0	8235	1.2770
0.9861	2.0	16470	1.3071
0.8098	3.0	24705	1.4088

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Distilbert Base Uncased Finetuned Squad

Model Overview

Model Features

Model Capabilities

Use Cases

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