You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
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
The text was updated successfully, but these errors were encountered:
Is there an existing issue for this bug?
🐛 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:This leads to the following error when reloading the saved checkpoint:
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
The text was updated successfully, but these errors were encountered: