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Bert Large Uncased Squadv1.1 Sparse 80 1x4 Block Pruneofa

Developed by Intel
This model is obtained by fine-tuning a pre-trained 80% 1x4 block sparse Prune OFA BERT-Large model through knowledge distillation, demonstrating excellent performance on the SQuADv1.1 Q&A task.
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Release Time : 3/27/2022

Model Overview

This model is a sparsified version based on the BERT-Large architecture, specifically optimized for Q&A tasks, achieving high accuracy on the SQuADv1.1 dataset.

Model Features

Efficient Sparse Structure
Adopts an 80% 1x4 block sparse structure, significantly reducing model parameters while maintaining performance.
Knowledge Distillation Optimization
Fine-tuned through knowledge distillation techniques to enhance performance on specific tasks.
High-Performance Q&A Capability
Achieves an F1 score of 91.174 on the SQuADv1.1 Q&A task.

Model Capabilities

Q&A System
Reading Comprehension
Text Understanding

Use Cases

EdTech
Automated Q&A System
Used for building intelligent Q&A systems in the education sector
Achieves an F1 score of 91.174 on standard Q&A datasets
Customer Service
Intelligent Customer Support
Used for handling common customer inquiries
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