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qriton/hlm-micro-har-v1-uci-har

sourceHugging Faceapache-2.0updated 2mo agoView on Hugging Face
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Model Card

HLM-Micro HAR v1 - UCI HAR

HLM-Micro HAR v1 is a compact polynomial-Hopfield classifier trained on the UCI Human Activity Recognition dataset.

Results

FieldValue
Parameters277,760
Classes6 activities
Reported test accuracy93.52%
Test windows2,947 held-out UCI HAR windows
DataSmartphone IMU activity windows from 30 subjects

Per-class summary from the source evaluation:

ClassAccuracy
Walking99.60%
Upstairs98.09%
Downstairs93.10%
Sitting90.84%
Standing95.30%
Laying84.92%

Files

FilePurpose
model.ptSanitized model-only PyTorch checkpoint
config.jsonPublic architecture, task, classes, and metric metadata
metrics.jsonlTraining/evaluation metrics from the local run

Intended Use

  • —Research on compact human-activity-recognition models.
  • —TinyML and edge-sensor experiments.
  • —Baseline for HLM-Micro architecture comparisons.

Limitations

  • —UCI HAR is a fixed benchmark, not a complete wearable deployment test.
  • —Not a medical, fall-detection, gait-analysis, or safety-critical model.
  • —Production use would require new data collection, calibration, and deployment testing.