feat: add experiment_name to TrainModelResult and update training logic

- Introduced experiment_name parameter in TrainModelResult to enhance tracking of training experiments.
- Updated the Training class to utilize run_name and experiment_name for improved MLflow run management.

model_manager/utils/models/train_model_result.py

@@ -44,6 +44,7 @@ class TrainModelResult:
     equation: dict | None = None
     equation_path: str | None = None
     run_name: str | None = None
+    experiment_name: str | None = None
     run_id: str | None = None
     report_path: str | None = None
     train_data_path: str | None = None