V

V3 Large Mnli

Developed by NDugar
MNLI task model fine-tuned on DeBERTa-v3-large, achieving 91.75% accuracy on the GLUE MNLI evaluation set
Downloads 61
Release Time : 3/2/2022

Model Overview

This model is a fine-tuned version of DeBERTa-v3-large on the GLUE MNLI dataset, specifically designed for natural language inference tasks.

Model Features

High accuracy
Achieves 91.75% accuracy on the MNLI evaluation set
Zero-shot classification capability
Supports zero-shot classification tasks
Optimized training parameters
Fine-tuned using linear learning rate scheduler and Adam optimizer

Model Capabilities

Natural language inference
Zero-shot classification
Text classification

Use Cases

Text analysis
Text entailment judgment
Determine whether entailment, contradiction, or neutral relationship exists between two sentences
91.75% accuracy
Zero-shot classification
Can perform classification tasks without domain-specific training data
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