deberta-base-finetuned-aqa-squad1 open-source model - Free deployment to achieve automatic question-answering function

Deberta Base Finetuned Aqa Squad1

Developed by stevemobs

This model is a fine-tuned version of DeBERTa-base on the SQuAD question answering dataset, designed for automatic question answering tasks

Question Answering System

Transformers

Open Source License:MIT #Question Answering System #Reading Comprehension #SQuAD Fine-tuning

Downloads 14

Release Time : 5/24/2022

Model Overview

This is a question answering model based on the DeBERTa architecture, specifically fine-tuned for the SQuAD dataset, suitable for reading comprehension-style question answering tasks.

Model Features

SQuAD Dataset Fine-tuning

Optimized specifically for the SQuAD question answering dataset

DeBERTa Architecture

Based on the advanced DeBERTa architecture with powerful contextual understanding capabilities

Low Training Loss

Achieved a training loss of 0.5586 after 2 epochs of training

Model Capabilities

Reading Comprehension

Question Answering System

Text Understanding

Use Cases

Education

Automatic Answering System

Answer related questions based on given text content

Information Retrieval

Document Question Answering

Extract information from documents to answer user questions

Training Loss	Epoch	Step	Validation Loss
0.7662	1.0	7380	0.7575
0.5586	2.0	14760	0.7790

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Deberta Base Finetuned Aqa Squad1

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 DeBERTa-Base Finetuned AQA SQuAD1

🚀 Quick Start

📚 Documentation

Model description

Intended uses & limitations

Training and evaluation data

🔧 Technical Details

Training procedure

Training hyperparameters

Training results

Framework versions

📄 License