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Roberta Base Nli
R
Roberta Base Nli
Developed by kwang123
This model is a natural language inference model based on the RoBERTa architecture, specifically fine-tuned for depression detection tasks.
Downloads 18
Release Time : 11/29/2023
Model Overview
The roberta-base-nli model is a natural language inference model based on the RoBERTa architecture, fine-tuned on the LT-EDI-ACL-2022 shared task 4 depression detection dataset, suitable for zero-shot classification tasks.
Model Features
Depression Detection
Specifically fine-tuned for depression detection tasks, capable of effectively identifying text content related to depression.
Zero-shot Classification
Supports zero-shot classification tasks, applicable to new classification tasks without additional training.
Natural Language Inference
Based on the RoBERTa architecture, it possesses strong natural language understanding and reasoning capabilities.
Model Capabilities
Text Classification
Natural Language Inference
Depression Detection
Use Cases
Mental Health
Depression Screening
Screens potential depression patients by analyzing users' text content.
Performs well on the LT-EDI-ACL-2022 dataset.
Academic Research
Mental Health Research
Used to study the relationship between depression and language expression.
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