gitea_admin/sientia-dataops-model-manager
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

SIENTIAPDE-1645: Expose detailed model training information via a new Prometheus gauge. This gauge, sientia_training_info, records metadata such as dataset sizes, feature count, and evaluation metrics (MSE, MAE, R2) along with the training run's timestamp.

Browse Source
This commit is contained in:
vitor-aignosi
2026-06-18 09:56:30 -03:00
parent bc65ebb955
commit 2c63414770
3 changed files with 76 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

12
model_manager/activities/training.py
View File

@@ -262,6 +262,18 @@ class Training(SientiaMonitoring):
train_result.r2_val
)
mm_metrics.SIENTIA_TRAINING_INFO.labels(
pod_id=labels['pod_id'],
model_name=train_params.model_name,
model_type=train_params.model_type,
dataset_train_rows=str(len(train_result.train_data)),
dataset_val_rows=str(len(train_result.val_data)),
feature_count=str(len(train_params.variable_columns)),
mse=str(train_result.mse_val) if train_result.mse_val is not None else '',
mae=str(train_result.mae_val) if train_result.mae_val is not None else '',
r2=str(train_result.r2_val) if train_result.r2_val is not None else '',
).set(time.time() * 1000)
self.info(f'Starting MLflow run for {train_params.model_type}', metadata)
with self.mlflow_repository.start_run(
model_name=train_params.model_name,