ArcheeS/vitals-interpreter-model

Vitals Interpreter Model (Fine-Tuned LLM)

Project Overview

This project implements a fine-tuned transformer model that interprets basic human vital signs and generates structured health guidance.

The model takes numerical vitals as input and produces a concise, human-readable output consisting of:

• Health status classification
• Suggested action/advice

---

Objective

To build a lightweight, efficient AI system that:

• Understands structured vital inputs
• Classifies health condition into categories
• Generates consistent and controlled responses

---

Model Details

• Base Model: t5-small
• Architecture: Encoder-Decoder Transformer
• Fine-Tuning Type: Supervised Fine-Tuning (SFT)
• Framework: Hugging Face Transformers

---

Input Format

interpret vitals -> heart rate X, blood pressure Y/Z, temperature T

Example:

interpret vitals -> heart rate 125, blood pressure 150/95, temperature 100

---

Output Format

Status: <Normal | High | Low | Critical> | Advice:

Example Output:

Status: High | Advice: Monitor and consult doctor

---

Dataset

• Type: Synthetic dataset
• Size: ~30–50 samples
• Design Approach:
  • Based on medically accepted ranges of vital signs
  • Balanced across categories:
    • Normal
    • High
    • Low
    • Critical

Why Synthetic Data?

Due to lack of publicly available labeled text datasets for this task, a controlled dataset was generated to:

• Ensure consistency in output format
• Improve learning efficiency
• Avoid noisy or unstructured data

---

Training Configuration

• Epochs: 20–30
• Batch Size: 2–4
• Learning Rate: 5e-5
• Max Sequence Length: 64
• Tokenizer: AutoTokenizer (T5)

---

Evaluation

Method:

• Manual testing with unseen inputs
• Verification of:
  • Correct classification (Normal / High / Low / Critical)
  • Proper output structure
  • Relevance of advice

Sample Predictions:

Input	Output
HR: 125, BP: 150/95, Temp: 100	Status: High | Advice: Monitor and consult doctor
HR: 72, BP: 120/80, Temp: 98.6	Status: Normal | Advice: No action needed
HR: 140, BP: 170/110, Temp: 103	Status: Critical | Advice: Emergency care required

---

How to Use

Installation

from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

Author:
Archee Sinha
B.Tech CSE (AI)
ABES Institute of Technology