[BUG]: Gemini saved an additional portion of the weights while using tie_word_embeddings=True

[airlsyn]

Is there an existing issue for this bug?

• [X] I have searched the existing issues

🐛 Describe the bug

When fine-tuning a base model (Qwen2.5 3B Base) that uses tie_word_embeddings=True with GeminiPlugin and saving the checkpoint, I noticed an additional set of weights being saved:

    "lm_head.weight": "pytorch_model-00004.bin"

This leads to the following error when reloading the saved checkpoint:

[rank2]: RuntimeError: Error(s) in loading state_dict for GeminiDDP:
[rank2]:     Unexpected key(s) in state_dict: "lm_head.weight". 

Could you provide some advice on how to solve this issue and avoid saving the not needed weights?

Environment

Python: 3.11 colossalai: 0.4.6