C

Cs224n Squad2.0 Albert Base V2

Developed by elgeish
ALBERT-base-v2 model provided for Stanford CS224n course students, used for SQuAD2.0 Q&A task benchmarking
Downloads 169
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
Featured Recommended AI Models
AIbase
Empowering the Future, Your AI Solution Knowledge Base
© 2025AIbase