Deberta V3 Large Mnli
DeBERTa-v3-large model trained on MultiNLI dataset for textual entailment relationship judgment
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Release Time : 3/2/2022
Model Overview
This model is based on Microsoft's DeBERTa-v3-large architecture and trained on the Multi-genre Natural Language Inference (MultiNLI) dataset, specifically designed to determine the entailment relationship (entailment/neutral/contradiction) between two texts.
Model Features
Disentangled Attention Mechanism
Utilizes an innovative disentangled attention mechanism to enhance the model's understanding of textual relationships.
Enhanced Mask Decoder
Employs an enhanced mask decoder to improve performance in NLU tasks.
Multi-genre Training
Trained on the MultiNLI dataset containing 433,000 sample pairs, covering various text genres.
Model Capabilities
Textual Entailment Judgment
Zero-shot Classification
Natural Language Inference
Use Cases
Sentiment Analysis
Movie Review Sentiment Judgment
Analyze sentiment tendencies in movie reviews
Can accurately determine whether a review supports the movie
Content Moderation
Contradictory Content Detection
Identify contradictory statements in user-generated content
Can be used to detect false or misleading information
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