---
language:
- en
license: mit
tags:
- process-control
- industrial-automation
- qlora
- llama
- fine-tuned
- mpc
---

# Experiment A — Baseline Fine-Tuning (No Predictive Context)

**Paper**: LLMs as Autonomous Controllers for Multivariable Industrial Fluid Processes
**Author**: Vidyashree Rayar — BTU Cottbus-Senftenberg

Baseline: Llama 3.2-3B-Instruct fine-tuned with QLoRA on 11,975 records. Full cumulative prompt (SP+CoT+FS), no predictive horizon. Achieves 60.0% overall accuracy with 0% format and content hallucination — strongest safety performance across all experiments.

## Base Model

[meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct) fine-tuned with QLoRA (4-bit NF4, LoRA r=16, alpha=32, rsLoRA enabled).

## Code & Results

[github.com/vidyashreerayar/festo-llm-process-control](https://github.com/vidyashreerayar/festo-llm-process-control)