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Bart Large Finetuned Squad2

Developed by phiyodr
A Q&A system model based on BART-large architecture, fine-tuned on the SQuAD2.0 dataset, excelling at extracting answers from given text
Downloads 83
Release Time : 3/2/2022

Model Overview

This model is specifically designed for Q&A tasks, capable of accurately answering user questions based on provided context, supporting scenarios where no answer is available

Model Features

SQuAD2.0 fine-tuning
Fine-tuned on the SQuAD2.0 dataset, supporting scenarios with no answer available
High-precision Q&A
Achieves 81.97% exact match rate and 85.94% F1 score on the development set
Context understanding
Can process contexts up to 384 tokens long, effectively comprehending complex texts

Model Capabilities

Text comprehension
Answer extraction
No-answer detection
Contextual Q&A

Use Cases

Education
Learning aid
Helps students quickly find answers from textbooks
Improves learning efficiency with accuracy exceeding 85%
Customer service
FAQ auto-response
Automatically answers common customer questions based on product documentation
Reduces workload of human customer service
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