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Roberta Base Mnli Bc

Developed by mujeensung
A text classification model fine-tuned on the GLUE MNLI dataset based on the RoBERTa-base model, excelling in natural language inference tasks
Text Classification
Transformers
 EnglishOpen Source License:MIT#High-precision text classification#Natural language inference#RoBERTa fine-tuning
Downloads 43
Release Time : 3/2/2022

Model Overview

This model is a fine-tuned version of RoBERTa-base for the MNLI (Multi-Genre Natural Language Inference) task, primarily used to determine the logical relationship between two sentences (entailment/contradiction/neutral)

Model Features

High accuracy
Achieves 95.8% accuracy on the MNLI evaluation set
Based on RoBERTa architecture
Utilizes the optimized RoBERTa-base pre-trained model as the foundation
Specialized fine-tuning
Specifically optimized for natural language inference tasks

Model Capabilities

Text classification
Natural language inference
Sentence relationship judgment

Use Cases

Natural language processing
Text entailment judgment
Determine whether an entailment relationship exists between two sentences
95.8% accuracy
Contradiction detection
Identify whether two sentences express contradictory viewpoints
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