BERT-Base-Uncased-Finetuned-SQuAD Open-Source Question-Answering Model

Bert Base Uncased Finetuned Squad

Developed by kaporter

A Q&A model fine-tuned on the SQuAD dataset based on the BERT base model

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Release Time : 3/2/2022

Model Overview

This model is a fine-tuned version of the BERT base architecture on the SQuAD Q&A dataset, specifically designed for question-answering tasks.

Optimized for Q&A Tasks

Specially fine-tuned for question-answering tasks, capable of extracting accurate answers from given texts

Based on BERT Architecture

Utilizes the BERT base architecture with strong contextual understanding capabilities

Fine-tuned on SQuAD Dataset

Trained on the SQuAD Q&A dataset, demonstrating excellent question-answering performance

Text Understanding

Answer Extraction

Contextual Analysis

Q&A Systems

Reading Comprehension Q&A

Answering questions based on given texts

Achieves good performance on the SQuAD evaluation set

Knowledge Base Q&A

Extracting answers from structured or unstructured texts

Property	Details
Model Name	bert - base - uncased - finetuned - squad
Task Type	Question Answering
Dataset	squad
Loss on Evaluation Set	1.0725

Training Loss	Epoch	Step	Validation Loss
1.0749	1.0	5533	1.0167
0.7851	2.0	11066	1.0299
0.6067	3.0	16599	1.0725

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