--- 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.
