Architecture: DINOv3 ViT-Small/16 (timm: vit_small_patch16_dinov3)
Classes: 8 vehicle body types
Source run: autolens-ai_checkpoints_dinov3_safe_weighted_aug_20260510_131319
Source checkpoint: checkpoints/autolens-ai_checkpoints_dinov3_safe_weighted_aug_20260510_131319/best-29-0.9491.ckpt
Export format: model.safetensors plus metadata.json, with ONNX for deployment
Calibration status: not applied yet; this repo is the pre-calibration package and will be updated later with temperature scaling

Classes

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

Preprocessing

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

Validation Results

Validation was used to select the checkpoint. The metrics below come from the best validation epoch in metrics.csv.

Best epoch: 29
Accuracy: 0.9576
F1-macro: 0.9491
F1-weighted: 0.9579
Precision-macro: 0.9504
Recall-macro: 0.9486
Loss: 0.7255

Internal Test Results

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

Accuracy: 0.9584
F1-macro: 0.9507
F1-weighted: 0.9584
Precision-macro: 0.9561
Recall-macro: 0.9456

Per-class Performance

Class	Precision	Recall	F1-score	Support
SUV	0.9576	0.9433	0.9504	670
VAN	0.9933	0.9780	0.9856	455
STATION WAGON	0.9524	0.9091	0.9302	66
MICRO	1.0000	0.9545	0.9767	22
OPEN WHEEL / F1	1.0000	0.9983	0.9991	586
SEDAN	0.9496	0.9689	0.9591	836
HATCHBACK	0.8667	0.8797	0.8731	266
PICK UP	0.9296	0.9331	0.9314	269

Training Curves

Internal Test Confusion Matrix

Artifact Sizes

model.safetensors: 82.373 MB
model.onnx: 82.572 MB

Files

model.safetensors — weights-only model artifact
metadata.json — architecture, classes, preprocessing, source run, and artifact metadata
model.onnx — ONNX Runtime inference artifact
metrics.csv — epoch-level training and validation history
per_class_metrics.txt — internal-test classification report
training_loss.png — training/validation loss curve
training_accuracy.png — training/validation accuracy curve
confusion_matrix.png — normalized internal-test confusion matrix
size_check.json / size_report.json — artifact size and ONNX smoke evidence
internal_test_results.json — structured internal-test summary

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. This repo is intentionally pre-calibration; probability calibration will be added in the next upload after temperature scaling is fitted.

morpeN1/autolens-dinov3-safe-weighted

AutoLens DINOv3 Safe Weighted

Model