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Albert Xlarge V2 Finetuned Wnli
This model is a text classification model fine-tuned on the WNLI task of GLUE based on ALBERT-xlarge-v2
Downloads 31
Release Time : 3/2/2022
Model Overview
This model is a variant of the ALBERT-xlarge-v2 architecture, specifically fine-tuned for the WNLI (Winograd Schema Challenge) task to address textual entailment problems
Model Features
Efficient Parameter Sharing
Based on the ALBERT architecture, it employs a cross-layer parameter sharing mechanism, significantly reducing the number of model parameters
WNLI Task Optimization
Specifically fine-tuned for the Winograd Schema Challenge task
Lightweight Architecture
Compared to the original BERT model, the ALBERT architecture greatly reduces the number of parameters while maintaining performance
Model Capabilities
Text Classification
Natural Language Inference
Textual Entailment Judgment
Use Cases
Natural Language Processing
Textual Entailment Judgment
Determine whether one sentence entails the meaning of another sentence
Achieved 56.34% accuracy on the WNLI test set
Semantic Similarity Analysis
Analyze the semantic relationship between two sentences
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