V3 Large Mnli
MNLI task model fine-tuned on DeBERTa-v3-large, achieving 91.75% accuracy on the GLUE MNLI evaluation set
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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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