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hlm-micro-gesture-v2-uwave
qriton/hlm-micro-gesture-v2-uwave
hlm-micro-gesture-v2-uwave is a other model from qriton. Use it for the other task on the model card, and read the license before you ship it in a product. It is set up for pytorch. The card lists the license as apache-2.0.
HLM-Micro Gesture v2 is a small polynomial-Hopfield time-series classifier trained on the UWaveGestureLibrary real accelerometer gesture corpus.
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At a glance
- Task
- other
- Library
- pytorch
- License
- apache-2.0
- Access
- Public
- Created
- Jul 13, 2026
- Updated
- Jul 13, 2026
- SHA
- 1e7b17d4
Datasets
Model card
From the Hugging Face model README
HLM-Micro Gesture v2 - UWave
HLM-Micro Gesture v2 is a small polynomial-Hopfield time-series classifier trained on the UWaveGestureLibrary real accelerometer gesture corpus.
Results
| Field | Value |
|---|---|
| Parameters | 183,933 |
| Classes | 8 gestures |
| Reported test accuracy | 94.19% |
| Best checkpoint | epoch 18 of 30 |
| Input | 3-axis accelerometer, resampled to a 32-channel feature layout |
Reference points from common UWave time-series classifiers are in the high-80s to mid-90s depending on method and split. This checkpoint is a compact research model, not a production wearable system.
Files
| File | Purpose |
|---|---|
model.pt | Sanitized model-only PyTorch checkpoint |
config.json | Public architecture, task, classes, and metric metadata |
metrics.jsonl | Training/evaluation metrics from the local run |
Intended Use
- Research on compact polynomial-Hopfield classifiers.
- Edge/time-series gesture-recognition experiments.
- Baseline for replayable per-inference audit work.
Limitations
- Evaluated on UWaveGestureLibrary, not on arbitrary users or devices.
- No safety, medical, ergonomic, or production-use certification.
- Real deployments need sensor calibration, broader classes, and live-device validation.
- Task
- other
- Library
- pytorch
- License
- apache-2.0
- Created
- Jul 13, 2026
- Updated
- Jul 13, 2026