---
license: apache-2.0
language:
  - es
  - en
tags:
  - lora
  - openllama
  - agriculture
  - climate
  - potato
  - few-shot
  - classification
  - low-resource
  - causal-lm
datasets:
  - custom
base_model: openlm-research/open_llama_3b
model-index:
  - name: lora-lateblight-v5
    results: []
---


# lora-lateblight-v5 🌱 — OpenLLaMA-3B Fine-Tuned for Potato Late Blight Risk Prediction in Huancavelica, Peru

**Author**: Jorge Luis Alonso ([@jalonso24](https://huggingface.co/jalonso24))  
**Model Base**: [openlm-research/open_llama_3b](https://huggingface.co/openlm-research/open_llama_3b)  
**Adapter Format**: LoRA (PEFT)  
**Location**: Huancavelica, Andes, Peru  
**Languages**: Spanish, English  
**Task**: Multi-class classification (`Bajo`, `Moderado`, `Alto`) of late blight disease risk using natural language prompts

---

## 🔍 What is this?

`lora-lateblight-v5` is a lightweight, prompt-based classifier that predicts potato **late blight risk** levels using natural language inputs. It was fine-tuned with **LoRA adapters** on a curated dataset of expert-labelled and synthetic examples from Huancavelica, Peru.

It supports **bilingual prompts**, runs on **low-cost hardware**, and helps agronomists and rural farmers make better decisions using just weather and crop descriptions in plain language.

---

## 🧪 How was it trained?

- **Fine-Tuning Method**: LoRA (Low-Rank Adaptation)
  - `r=32`, `alpha=16`, `dropout=0.1`
- **Training Framework**: PEFT with `transformers`, Colab T4 GPU
- **Epochs**: 5, using mixed precision with float32 stabilization
- **Data Sources**:
  - Historical climate + crop risk data (SENAMHI, CIP)
  - Synthetic "Alto" risk cases for balancing
  - Distilled "Moderado" cases from GPT-4 + Gemini consensus
- **Prompt Style**:
  - Few-shot (3 labeled examples: `Bajo`, `Moderado`, `Alto`)
  - Natural, bilingual inputs (e.g., Spanish + English)
  - Example format:
    ```
    La variedad es INIA-302 Amarilis, sembrada en noviembre.
    La precipitación fue 18.4 mm, la temperatura máxima 17.2°C,
    la mínima 6.1°C y la humedad promedio 84.12%.

    ¿Cuál es el riesgo de tizón tardío?

    Riesgo:
    ```

---

## 📊 Evaluation Summary

| Metric             | Score     |
|--------------------|-----------|
| **Accuracy**        | 73%       |
| **Recall (Alto)**   | 100%      |
| **F1-score (Alto)** | 0.78      |
| **F1-score (Mod.)** | 0.25      |

- ✅ Model reliably detects all **high-risk (Alto)** cases
- ⚠️ Struggles with **moderate-risk (Moderado)** due to timing subtleties
- ⚖️ Prioritizes early warning over precision — suitable for advisory tools

---

## 📁 Files Included

- `adapter_model.safetensors` — LoRA adapter weights
- `tokenizer/` — Tokenizer from OpenLLaMA 3B
- `README.md` — This model card

---

## 🧠 Intended Use

- Forecast **potato late blight risk** in high-altitude Andean regions
- Run lightweight inference on devices like Beelink Mini PCs
- Support local extension workers, agronomists, or AI-powered alert tools
- Educate farmers using mobile-friendly prompts in Spanish or English

---

## 🚧 Known Limitations

- Overpredicts `Alto` in ambiguous cases — intended as a safety trade-off
- Struggles with unclear or borderline `Moderado` cases
- Not designed for **automated spraying systems** or **IoT-triggered actions**
- Needs expert validation before field-level decisions

---

## 🫷 Try It (Coming Soon)

We’re working on a [Gradio demo](https://huggingface.co/spaces) where you’ll be able to enter:
- Crop variety
- Planting month
- Weekly humidity, temperature, and rainfall

👉 and receive a natural-language **Riesgo** prediction.

---

## 📚 Citation

```
@misc{alonso2025lateblight,
  author = {Jorge Luis Alonso},
  title = {Predicting Potato Late Blight in Huancavelica, Peru, Using OpenLLaMA 3B + LoRA},
  year = {2025}, {\url{https://www.linkedin.com/pulse/improving-potato-late-blight-forecasting-huancavelica-alonso-5h1af}}
  note = {Fine-tuning based on expert-labelled and synthetic data with few-shot prompt classification},
  howpublished = {\url{https://huggingface.co/jalonso24/lora-lateblight-v5}}
}
```

Based on foundational studies by Gastelo et al. (2025), Giraldo et al. (2010), and Saffer et al. (2024).