The distilbert-base-uncased-finetuned-squad open-source Q&A model - Free deployment to empower reading comprehension

Distilbert Base Uncased Finetuned Squad

Developed by 21iridescent

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 #Q&A System #Reading Comprehension #SQuAD Fine-tuning

Downloads 19

Release Time : 3/28/2022

Model Overview

This is an optimized question-answering model based on the DistilBERT architecture, fine-tuned on the SQuAD v2 dataset, capable of answering questions based on given text.

Model Features

Efficient and Lightweight

Based on the DistilBERT architecture, it is smaller and faster than the original BERT model while maintaining good 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, supporting the handling of unanswerable questions.

Model Capabilities

Text Understanding

Question Answering

Context Analysis

Use Cases

Education

Reading Comprehension Assistance

Helps students understand article content and answer questions

Customer Service

FAQ Auto-Response

Automatically answers customer questions based on knowledge base documents

Training Loss	Epoch	Step	Validation Loss
1.2739	1.0	4118	1.2801
1.0001	2.0	8236	1.2823
0.8484	3.0	12354	1.3466

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Distilbert Base Uncased Finetuned Squad

Model Overview

Model Features

Model Capabilities

Use Cases

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