distilbert-base-uncased-finetuned-squad Open-Source Q&A Model - Powering Question Answering in Reading Comprehension Tasks

Distilbert Base Uncased Finetuned Squad

Developed by shila

This model is a question-answering model fine-tuned on the SQuAD v2 dataset based on DistilBERT, suitable for reading comprehension tasks.

Question Answering System

Transformers

Open Source License:Apache-2.0 #Question Answering System #Reading Comprehension #Lightweight BERT

Downloads 15

Release Time : 7/20/2022

Model Overview

This is a fine-tuned DistilBERT model specifically designed for question-answering tasks, particularly trained on the SQuAD v2 dataset, capable of handling reading comprehension questions.

Model Features

Efficient and Lightweight

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

Question Answering Capability

Optimized specifically for question-answering tasks, capable of extracting answers from given text.

SQuAD v2 Adaptation

Fine-tuned on the SQuAD v2 dataset, capable of handling unanswerable questions.

Model Capabilities

Reading Comprehension

Answer Extraction

Text Understanding

Use Cases

Education

Automated Answering System

Helps students quickly find answers to questions from textbooks

Customer Service

FAQ Auto-Response

Extracts answers to questions from knowledge base documents

Training Loss	Epoch	Step	Validation Loss
No log	1.0	15	5.4661
No log	2.0	30	5.0915
No log	3.0	45	4.9348

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Distilbert Base Uncased Finetuned Squad

Model Overview

Model Features

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