Upload training_config.json

training_config.json

@@ -0,0 +1,44 @@
+{
+  "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"
+}