Cs224n Squad2.0 Distilbert Base Uncased
This model was established as a benchmark for the CS224n student project, based on the DistilBERT architecture and fine-tuned on the SQuAD2.0 dataset for question-answering tasks.
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Release Time : 3/2/2022
Model Overview
This model is a lightweight question-answering model based on the DistilBERT architecture, specifically optimized for the SQuAD2.0 dataset, capable of handling question-answering tasks that include unanswerable questions.
Model Features
Lightweight Architecture
Based on DistilBERT, smaller and faster than standard BERT models while maintaining high performance.
Handling Unanswerable Questions
Supports scenarios with unanswerable questions in SQuAD2.0.
Efficient Training
Optimized training parameters, suitable for student projects.
Model Capabilities
Reading Comprehension
Question-Answering System
Text Understanding
Use Cases
Education
CS224n Student Project
Serves as a benchmark model for student projects, helping students quickly start developing question-answering systems.
Provides an exact match score of 65.17 and an F1 score of 67.87.
Question-Answering System
Document-Based Question Answering
Answers user questions from given text.
Performs well on the SQuAD2.0 dataset.
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