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mabera/nigeria-fertilizer-access-model
nigeria-fertilizer-access-model is a machine learning model from mabera. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
Author: Hussein Adeiza (mabera) Role: Licensed Environmental Health Officer, Abuja Nigeria Base Model: Llama 3.3 70B Fine-tuned with: AutoScientist by Adaption Labs
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Updated Jul 11, 2026
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From the Hugging Face model README
Author: Hussein Adeiza (mabera) Role: Licensed Environmental Health Officer, Abuja Nigeria Base Model: Llama 3.3 70B Fine-tuned with: AutoScientist by Adaption Labs
A LoRA adapter fine-tuned to interpret raw Nigerian fertilizer market statistics, price data, subsidy structure, yield gaps, and import dependency, and produce structured economic analytical reasoning. Raw statistics go in, expert interpretation comes out, grounded strictly in cited source data.
This submission's Adaptive Data quality score did not improve during adaptation (8.0 to 8.0, Grade B held steady), the first time in this portfolio this has happened. The win rates remain solid (62% training, 75% General Win Rate), so the model itself performs well, but the quality metric specifically did not move. A plausible contributing factor: this run used a smaller datapoint expansion (1,011 rows) than prior submissions (20,000+ rows on Oil Spill and Desertification), though this has not been confirmed as the cause. Disclosed transparently rather than only reporting the stronger win-rate figures.
Powered by Adaptive Data — Adaption Labs AutoScientist Challenge 2026, Part 2 — Agriculture Category