AutoLens EfficientNet-B2 Candidate

Current strongest CNN candidate for the AutoLens AI demo artifact lane.

Model

Architecture: EfficientNet-B2
Classes: 8 vehicle body types
Source run: baseline_0_efficientnet_b2_20260509_135313
Source checkpoint: checkpoints/baseline_0_efficientnet_b2_20260509_135313/best-04-0.8994.ckpt
Export format: model.safetensors plus metadata.json, with ONNX for deployment

Classes

SUV
VAN
STATION WAGON
MICRO
OPEN WHEEL / F1
SEDAN
HATCHBACK
PICK UP

Preprocessing

RGB input
Resize: 256
Center crop / model input: 224 x 224
Mean: [0.4429, 0.4354, 0.437]
Std: [0.2456, 0.2421, 0.2449]

Internal Test Results

Evaluated on held-out internal test set (3170 samples, no data leakage).

Accuracy: 0.9202
F1-macro: 0.8982
F1-weighted: 0.9201
Precision-macro: 0.9056
Recall-macro: 0.8923

Per-class Performance

Class	Precision	Recall	F1-score	Support
SUV	0.9213	0.9090	0.9151	670
VAN	0.9450	0.9824	0.9634	455
STATION WAGON	0.8033	0.7424	0.7717	66
MICRO	0.9545	0.9545	0.9545	22
OPEN WHEEL / F1	0.9948	0.9846	0.9897	586
SEDAN	0.9023	0.9282	0.9151	836
HATCHBACK	0.7662	0.8008	0.7831	266
PICK UP	0.9574	0.8364	0.8929	269

Temperature Scaling (Calibration)

Post-training calibration uses temperature scaling. Temperature was fit on the validation set only; the before/after values below are measured on the held-out internal test set.

Temperature: 1.7799
Internal test ECE before: 0.0393 → after: 0.0107
Internal test NLL before: 0.2745 → after: 0.2301
Internal test mean confidence before: 0.9595 → after: 0.9168
Internal test accuracy: 0.9202 (3170 samples)

Calibration parameters are stored in calibration.json. The ONNX model outputs raw logits; apply temperature scaling at inference time.

Artifact sizes

model.safetensors: 29.722 MB
model.onnx: 29.371 MB

Files

model.safetensors — weights-only model artifact
metadata.json — architecture, classes, preprocessing, source run, and artifact metadata
model.onnx — ONNX Runtime inference artifact
model.simplified.onnx — optional simplified ONNX graph when available
size_report.json / size_check.json — artifact size and ONNX smoke evidence

Intended use

Educational demo and report evidence for classifying uploaded vehicle images into the 8 AutoLens body-type classes.

Limitations

The dataset is assembled from public/open sources and may contain domain bias. Similar body styles such as hatchback, station wagon, and sedan can be ambiguous. The merged raw dataset is not redistributed in this model repository.

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