distilbert-base-uncased-finetuned-squad Open Source Question Answering Model

Distilbert Base Uncased Finetuned Squad

Developed by BillZou

This model is a question-answering model fine-tuned on the SQuAD dataset based on DistilBERT, designed for reading comprehension tasks.

Question Answering System

Transformers

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

Downloads 14

Release Time : 11/8/2022

Model Overview

A lightweight version of DistilBERT, fine-tuned on the SQuAD dataset, used to answer questions based on given text.

Model Features

Lightweight

Based on the DistilBERT architecture, it is smaller and faster than the standard BERT model while maintaining high performance.

Question Answering Capability

Fine-tuned on the SQuAD dataset, capable of answering questions based on given text.

Efficient Training

Uses linear learning rate scheduling and the Adam optimizer for efficient training.

Model Capabilities

Text Understanding

Question Answering

Reading Comprehension

Use Cases

Education

Reading Comprehension Assistance

Helps students understand article content and answer questions.

Customer Service

FAQ Auto-Response

Automatically answers common questions based on document content.

Training Loss	Epoch	Step	Validation Loss
No log	1.0	295	2.3734
3.0199	2.0	590	1.7638
3.0199	3.0	885	1.5867
1.582	4.0	1180	1.5535
1.582	5.0	1475	1.5281
1.2859	6.0	1770	1.5282

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Distilbert Base Uncased Finetuned Squad

Model Overview

Model Features

Model Capabilities

Use Cases

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🔧 Technical Details

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