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mabera/
nigeria-wash-health-model

Name: nigeria-wash-health-model
Availability: InStock

meta-llama/Llama-3.3-70B-Instruct

finetune

apache-2.0

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Nigeria WASH Health Model

AutoScientist Challenge 2026 | Healthcare Category

Author: Hussein Adeiza (mabera)
Role: Licensed Environmental Health Officer, Abuja Nigeria
Base Model: Llama 3.3 70B
Fine-tuned with: AutoScientist by Adaption Labs

Model Description

This is a LoRA adapter fine-tuned on Nigeria DHS WASH health data (2003–2024). It predicts and explains child diarrhea risk from water, sanitation and hygiene indicators across Nigeria.

Training Data

Source: DHS Nigeria national surveys (2003–2024)
Dataset: 3,972 adapted rows (Hausa, Yoruba, French, English)
Quality improvement: 310% (Grade E → B)
Kaggle: https://www.kaggle.com/datasets/yunusahusseinadeiza/nigeria-wash-risk-model-diarrhea-prediction

Training Metrics

Win rate: ~70% adapted vs ~30% base model
Base model: meta-llama/Llama-3.3-70B-Instruct
Method: LoRA (r=16, alpha=32, all-linear)
Epochs: 1

Why This Matters

Most health AI is trained on Western clinical data. This model addresses the gap in African environmental health AI — built specifically for Nigerian and West African public health realities.

mabera/nigeria-wash-health-model