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Roberta Base Few Shot K 128 Finetuned Squad Seed 42
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Roberta Base Few Shot K 128 Finetuned Squad Seed 42

Developed by anas-awadalla
A QA model fine-tuned on the SQuAD dataset using few-shot learning based on RoBERTa-base
Question Answering System
Transformers
Open Source License:MIT#QA System Fine-tuning#Few-shot Learning#Reading Comprehension Optimization
Downloads 19
Release Time : 3/2/2022

Model Overview

This model is based on the RoBERTa-base architecture and fine-tuned on the SQuAD QA dataset using a 128-sample few-shot learning strategy, suitable for question-answering tasks

Model Features

Few-shot Fine-tuning
Fine-tuned with only 128 samples, demonstrating few-shot learning capability
RoBERTa Architecture
Built upon the powerful RoBERTa-base pre-trained model
QA Optimization
Specifically optimized for QA tasks to extract answers from text

Model Capabilities

Reading Comprehension
Answer Extraction
Text Understanding

Use Cases

Education
Automated Answering System
Used in educational fields for automated QA systems to help students quickly acquire knowledge
Customer Service
FAQ Auto-Response
Automatically answers frequently asked questions to improve customer service efficiency
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