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---
tags:
- topic-modeling
- bertopic
- university
- admissions
- mmr
- keybert
---
# 🧠 bertopic-admissions-mmr-keybert
This model is a fine-tuned BERTopic model for clustering university admissions-related questions and documents using Maximal Marginal Relevance (MMR) and KeyBERT-based keyword generation.
## 🏗️ Model Details
**Base Model:** BERTopic (HuggingFace Transformers + UMAP + HDBSCAN)
**Embedding Model:** `all-MiniLM-L6-v2`
**Keyword Method:** MMR + KeyBERT
**Training Data:** 50-question CSV dataset on university admissions topics
**Date Trained:** April 2025
## 📊 Intended Use
- Question clustering for FAQ and chatbot systems
- Identifying user intent for university-related inquiries
## 🧯 Limitations
- Small training dataset (50 rows)
- English-only
- May group distinct topics if vocabulary overlaps
## 📁 How to Use
```python
from bertopic import BERTopic
# Load model
topic_model = BERTopic.load("your-local-folder-or-hf-repo-name")
# Transform new docs
topics, probs = topic_model.transform(docs)
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