MeterMind: Industrial Gauge Reading with ERNIE-4.5-VL

Fine-tuned LoRA adapter for reading analog industrial gauges from images.

Model Description

MeterMind is a fine-tuned version of ERNIE-4.5-VL-28B-A3B that accurately reads analog gauge values from photographs. It was trained on synthetic industrial gauge images and achieves near-human accuracy.

Performance

Metric Baseline (Zero-Shot) MeterMind (Fine-Tuned) Improvement
MAE 2.82 0.60 79% better
RMSE 4.35 1.10 75% better
Within ±1 53% 87% +34 points
Exact Match 27% 60% +33 points

Supported Gauge Types

  • Standard pressure gauges (0-100 PSI)
  • Glycerin-filled pressure gauges (0-100 PSI)
  • Bimetal thermometers (0-220°F)

Training Details

Hyperparameters

  • LoRA rank (r): 8
  • LoRA alpha: 16
  • Learning rate: 2e-4
  • Training steps: 285 (1 epoch)
  • Batch size: 2 (effective)
  • Warmup steps: 10
  • Scheduler: Linear
  • Optimizer: AdamW 8-bit

Target Modules

q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj, fc1, fc2

Usage

from transformers import AutoProcessor, AutoModelForVision2Seq
from peft import PeftModel

# Load base model
base_model = AutoModelForVision2Seq.from_pretrained("unsloth/ERNIE-4.5-VL-28B-A3B-PT")
processor = AutoProcessor.from_pretrained("unsloth/ERNIE-4.5-VL-28B-A3B-PT")

# Load LoRA adapter
model = PeftModel.from_pretrained(base_model, "luliuzee/metermind-ernie-gauge-lora")

# Inference
prompt = "What is the reading on this gauge? Reply with only the numeric value."
# ... process image and generate

Intended Use

  • Industrial inspection automation
  • Digital rounds and operator logging
  • Equipment monitoring systems
  • Facility management applications

Limitations

  • Trained on synthetic data; real-world performance may vary
  • Best suited for circular analog gauges with clear markings
  • Requires clear, well-lit images for optimal accuracy

Citation

@misc{metermind2024,
  title={MeterMind: Industrial Gauge Reading with Fine-Tuned ERNIE-4.5-VL},
  author={luliuzee},
  year={2024},
  publisher={HuggingFace}
}

Links

Framework Versions

  • PEFT: 0.18.0
  • Transformers: 4.x
  • Unsloth: Latest
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