Nli Deberta V3 Base
A cross-encoder model based on microsoft/deberta-v3-base, trained for natural language inference tasks, capable of determining the relationship between sentence pairs (contradiction, entailment, or neutral).
Downloads 65.55k
Release Time : 3/2/2022
Model Overview
This model is a natural language inference (NLI) cross-encoder specifically designed to determine the relationship between two sentences, outputting probability scores for three labels: contradiction, entailment, or neutral.
Model Features
High Accuracy
Achieves 92.38% and 90.04% accuracy on SNLI and MultiNLI datasets respectively
Multilingual Support
Although primarily trained for English, it can handle natural language inference tasks for Chinese text
Zero-shot Classification Capability
Can be used in zero-shot classification scenarios without domain-specific training data
Model Capabilities
Natural Language Inference
Textual Relationship Judgment
Zero-shot Classification
Use Cases
Text Analysis
QA System Validation
Validate the logical consistency between answers and questions in QA systems
Accurately determines whether answers entail the required information from questions
Content Moderation
Detect contradictory statements in user-generated content
Identifies inconsistencies or contradictions in text
Information Retrieval
Search Result Relevance Evaluation
Assess the relevance of search results to query intent
Determines whether search results entail the query intent
Featured Recommended AI Models
Š 2025AIbase