training_config.json

{
  "model_name": "CBC Manufacturing RUL Regressor",
  "hf_repo": "careerbytecode/mlops-ref-manufacturing-rul",
  "task": "regression (turbofan Remaining Useful Life, in cycles)",
  "model_type": "single-layer LSTM (hidden 64) over a 30-cycle window of 15 normalized sensors",
  "framework": "pytorch",
  "serialization": "torch state_dict (.pt) + joblib meta",
  "loader": "see model.py: load_model() rebuilds LSTMReg + loads state_dict; predict_rul(model, meta, raw_window) normalizes + predicts",
  "is_torch_model": true,
  "requires_class_def": "model.py (LSTMReg)",
  "random_state": 42,
  "window": 30,
  "hidden": 64,
  "rul_cap": 125,
  "sensors": [
    "s2",
    "s3",
    "s4",
    "s6",
    "s7",
    "s8",
    "s9",
    "s11",
    "s12",
    "s13",
    "s14",
    "s15",
    "s17",
    "s20",
    "s21"
  ],
  "n_features": 15,
  "dataset": "NASA C-MAPSS FD001 turbofan degradation, NASA Open Data (public domain)",
  "python_version": "3.14.4",
  "library_versions": {
    "torch": "2.12.0+cpu",
    "xgboost": "3.2.0",
    "scikit-learn": "1.8.0",
    "numpy": "2.4.6",
    "pandas": "2.3.3",
    "joblib": "1.5.3"
  },
  "training_date": "2026-06-04T20:27:03.611734+00:00"
}