Cs224n Squad2.0 Albert Base V2
ALBERT-base-v2 model provided for Stanford CS224n course students, used for SQuAD2.0 Q&A task benchmarking
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Release Time : 3/2/2022
Model Overview
This model is based on ALBERT-base-v2 architecture, fine-tuned on the SQuAD2.0 dataset, designed to help students quickly establish a benchmark model for Q&A systems
Model Features
Course-specific Optimization
Designed specifically for CS224n course, saving students' GPU time required to establish benchmark models
Subset Evaluation
Uses randomly selected half of the official development set samples (6,078 cases) for evaluation and model selection
Negative Sample Support
Supports handling negative samples without answers, complying with SQuAD2.0 task requirements
Model Capabilities
Reading Comprehension
Q&A System
Text Understanding
No-answer Detection
Use Cases
Education
Course Project Benchmark
Serves as a performance benchmark for CS224n course students' final projects
Provides 78.94% exact match rate and 81.77% F1 score
Research
Q&A System Research
Used as a baseline model for Q&A system-related research
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