Galal123/rasd-laya-track-classifier
AI model by Galal123
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Model card & documentation
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Classifies a radar/sensor track described in plain English as drone, bird, aircraft or unknown (clutter), with a calibrated probability. It replaces the hand-written rule-based classifier in RASD (Qatar Airspace Guardian), a hackathon simulation of airspace monitoring around three Qatari sites. It only classifies: it has no actions, flight control or engagement outputs. laya library's own finetune (soft-ce loss, then temperature calibration on a held-out slice of the training rows). (2000 rows from validation runs; the test split was not used for selection): validation accuracy 0.960, macro-F1 0.960. simulation. 10814 class-balanced training rows, 2 epochs, 6.4 min on one NVIDIA A100-SXM4-80GB. natural class mix. The rule-based classifier answers unknown whenever its evidence is thin; that counts as wrong for a real object. Its confidence is a heuristic score, not a probability. Fine-tuned model per class Confusion matrix (rows = truth, columns = prediction) Hard cases (accuracy;…
Read the full model card ↗ · Preview checked 2026-11-07T07:39:32.859Z
Inside the original model card — Document outline
- RASD Laya track classifier
- Results on the held-out test split (measured)
- Use
- Training sweep (selection on validation only)
- Limitations
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Model overview
Galal123/rasd-laya-track-classifier is a task-unspecified model repository published by Galal123 on Hugging Face. A library was not reported.
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- Created
- 2026-11-07T06:45:52.000Z
- Last modified
- 2026-11-07T06:45:52.000Z
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