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---
license: mit
language:
- en
library_name: transformers
pipeline_tag: text-classification
tags:
- ethics
- research
- deberta
- classification
datasets:
- custom
metrics:
- accuracy
- f1
base_model: microsoft/deberta-v3-base
model-index:
- name: ethics-review-deberta
results: []
---
# Ethics Review DeBERTa Model
A fine-tuned DeBERTa-v3-base model for classifying research ethics guideline compliance.
## Model Description
This model classifies text segments from research proposals to determine if they adequately address specific ethics review guidelines.
## Labels
- **LABEL_0 / ADDRESSED**: The text adequately addresses the ethics guideline
- **LABEL_1 / NEEDS_REVISION**: The text needs revision or doesn't address the guideline
## Usage
```python
from transformers import pipeline
classifier = pipeline("text-classification", model="JohnLicode/ethics-review-deberta")
# Example
text = "Guideline 1.1 Objectives: The general objective is to develop an AI ethics review system."
result = classifier(text)
print(result)
# [{'label': 'LABEL_0', 'score': 0.95}] # ADDRESSED
```
## Training
- Base model: `microsoft/deberta-v3-base`
- Task: Binary text classification
- Training data: Custom ethics review dataset with 30 guideline categories
## Intended Use
This model is designed to assist ethics review committees by providing preliminary assessments of research proposals against institutional guidelines.
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