Upgrading lightGBM API usage

🐛 Bug Description

The current usage of lightGBM API is deprecated.

  /home/xiaoyang/miniconda3/envs/kaggle/lib/python3.7/site-packages/lightgbm/engine.py:177: UserWarning: Found `n_estimators` in params. Will use it instead of argument
    _log_warning(f"Found `{alias}` in params. Will use it instead of argument")
  /home/xiaoyang/miniconda3/envs/kaggle/lib/python3.7/site-packages/lightgbm/engine.py:181: UserWarning: 'early_stopping_rounds' argument is deprecated and will be removed in a future release of LightGBM. Pass 'early_stopping()'
  callback via 'callbacks' argument instead.                                                                                                                                                                                             _log_warning("'early_stopping_rounds' argument is deprecated and will be removed in a future release of LightGBM. "
  /home/xiaoyang/miniconda3/envs/kaggle/lib/python3.7/site-packages/lightgbm/engine.py:239: UserWarning: 'verbose_eval' argument is deprecated and will be removed in a future release of LightGBM. Pass 'log_evaluation()' callback
  via 'callbacks' argument instead.
    _log_warning("'verbose_eval' argument is deprecated and will be removed in a future release of LightGBM. "
  /home/xiaoyang/miniconda3/envs/kaggle/lib/python3.7/site-packages/lightgbm/engine.py:260: UserWarning: 'evals_result' argument is deprecated and will be removed in a future release of LightGBM. Pass 'record_evaluation()' callba
  ck via 'callbacks' argument instead.
    _log_warning("'evals_result' argument is deprecated and will be removed in a future release of LightGBM. "

To Reproduce

Steps to reproduce the behavior:

1. train Qlib models based on lightGBM

Expected Behavior

Screenshot

Environment

Note: User could run cd scripts && python collect_info.py all under project directory to get system information
and paste them here directly.

• Qlib version:
• Python version:
• OS (Windows, Linux, MacOS):
• Commit number (optional, please provide it if you are using the dev version):

Additional Notes

Start by locating the Qlib model-training call sites that invoke LightGBM, then reproduce the warnings by following the issue's training steps. Check the available LightGBM usage and confirm that training no longer emits the listed deprecation warnings; scripts/collect_info.py all can provide environment details if needed.