Comments (2)
maxreciprocate
commented on September 13, 2024
Hello @nhanph!
No, the removal is not useless. If you check contents of python_model.bin immediately after this line:
trlx/trlx/trainer/accelerate_base_trainer.py
Line 309 in bcd237f
model.save_pretrained with heads_only=True, only value heads will be kept there.
>>> list(before_deletion_state_dict.keys())[:32]
['v_head.0.weight', 'v_head.0.bias', 'v_head.2.weight', 'v_head.2.bias', 'base_model.model.transformer.wte.weight', 'base_model.model.transformer.wpe.weight', 'base_model.model.transformer.h.0.ln_1.weight', 'base_model.model.transformer.h.0.ln_1.bias', 'base_model.model.transformer.h.0.attn.c_attn.weight', 'base_model.model.transformer.h.0.attn.c_attn.bias', 'base_model.model.transformer.h.0.attn.c_attn.lora_A.default.weight', 'base_model.model.transformer.h.0.attn.c_attn.lora_B.default.weight', 'base_model.model.transformer.h.0.attn.c_proj.weight', 'base_model.model.transformer.h.0.attn.c_proj.bias', 'base_model.model.transformer.h.0.ln_2.weight', 'base_model.model.transformer.h.0.ln_2.bias', 'base_model.model.transformer.h.0.mlp.c_fc.weight', 'base_model.model.transformer.h.0.mlp.c_fc.bias', 'base_model.model.transformer.h.0.mlp.c_proj.weight', 'base_model.model.transformer.h.0.mlp.c_proj.bias', 'base_model.model.transformer.h.1.ln_1.weight', 'base_model.model.transformer.h.1.ln_1.bias', 'base_model.model.transformer.h.1.attn.c_attn.weight', 'base_model.model.transformer.h.1.attn.c_attn.bias', 'base_model.model.transformer.h.1.attn.c_attn.lora_A.default.weight', 'base_model.model.transformer.h.1.attn.c_attn.lora_B.default.weight', 'base_model.model.transformer.h.1.attn.c_proj.weight', 'base_model.model.transformer.h.1.attn.c_proj.bias', 'base_model.model.transformer.h.1.ln_2.weight', 'base_model.model.transformer.h.1.ln_2.bias', 'base_model.model.transformer.h.1.mlp.c_fc.weight', 'base_model.model.transformer.h.1.mlp.c_fc.bias']
>>> list(after_save_pretrained_state_dict.keys())[:32]
['v_head.0.weight', 'v_head.0.bias', 'v_head.2.weight', 'v_head.2.bias']
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nhanph
commented on September 13, 2024
Thank you @maxreciprocate , I got the point about saving model's value head now.
My original question is from my observation when running ILQL training script that I see a pytorch_model.bin with the size comparable with the original model so I suspect that the base model is also saved. Is there somewhere that the heads_only flag is set to true during checkpointing when using peft_config as I cannot find it set anywhere?
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