feat(experiment-logger): add standalone logging framework

Create reusable experiment logging package with:
- UnifiedLogger for multi-backend logging (WandB, disk, stdout)
- Automatic checkpoint and model saving with metadata
- WandB artifact upload support
- Graceful degradation when WandB unavailable
- Comprehensive API documentation

This is a standalone, project-agnostic library that can be reused
across different ML projects.

src/experiment_logger/wandb_utils.py

@@ -0,0 +1,69 @@
+"""Centralized WandB initialization utilities."""
+
+import logging
+from typing import Any, Dict, Optional
+
+logger = logging.getLogger(__name__)
+
+
+def init_wandb(
+    project: str,
+    config: Dict[str, Any],
+    name: Optional[str] = None,
+    entity: Optional[str] = None,
+    sync_tensorboard: bool = False,
+    save_code: bool = True,
+    resume: str = "allow",
+    **kwargs,
+):
+    """Initialize WandB with standardized settings.
+
+    This function provides a centralized way to initialize WandB across different
+    scripts, ensuring consistent configuration and error handling.
+
+    Args:
+        project: WandB project name
+        config: Configuration dictionary to log
+        name: Run name (auto-generated if None)
+        entity: WandB entity (team/user name)
+        sync_tensorboard: Whether to sync tensorboard logs
+        save_code: Whether to save code snapshots
+        resume: Resume strategy ("allow", "must", "never", "auto")
+        **kwargs: Additional arguments to pass to wandb.init()
+
+    Returns:
+        wandb.Run object if successful, None otherwise
+    """
+    try:
+        import wandb
+
+        run = wandb.init(
+            project=project,
+            entity=entity,
+            name=name,
+            config=config,
+            sync_tensorboard=sync_tensorboard,
+            save_code=save_code,
+            resume=resume,
+            **kwargs,
+        )
+        logger.info(f"WandB initialized successfully for project '{project}', run '{run.name}'")
+        return run
+    except ImportError:
+        logger.warning("WandB not installed. Skipping WandB initialization.")
+        return None
+    except Exception as e:
+        logger.error(f"Failed to initialize WandB: {e}")
+        return None
+
+
+def finish_wandb():
+    """Safely finish the current WandB run."""
+    try:
+        import wandb
+
+        if wandb.run is not None:
+            wandb.finish()
+            logger.info("WandB run finished successfully")
+    except Exception as e:
+        logger.warning(f"Error finishing WandB run: {e}")