Checkpoint saving broken with the latest version of huggingface

[nepeee]

It generates a few bytes for the lora checkpoints with the latest version of hf but seems to be working with an older commit ex.: 50f82e12823ef8844b45a0dd864a78eea80de879

[johnsmith0031]

Do you mean transformers? or Peft?

[nepeee]

Ohh sry, its transformers.

[nepeee]

The issue is similar to this: https://github.com/huggingface/peft/issues/286

[johnsmith0031]

Thanks! I'll test it later to find out what's wrong with it

[johnsmith0031]

Fixed it inside pip branch.

[nepeee]

Well it seems to be working but when i try to resume it show a bunch of missing/unexpected keys. The training loss is about the same as before. Is this normal?

There were missing keys in the checkpoint model loaded: [
'base_model.model.model.embed_tokens.weight',
'base_model.model.model.layers.0.self_attn.q_proj.qzeros',
'base_model.model.model.layers.0.self_attn.q_proj.scales',
'base_model.model.model.layers.0.self_attn.q_proj.g_idx',
'base_model.model.model.layers.0.self_attn.q_proj.bias',
'base_model.model.model.layers.0.self_attn.q_proj.qweight',
'base_model.model.model.layers.0.self_attn.q_proj.lora_A.default.weight',
'base_model.model.model.layers.0.self_attn.q_proj.lora_B.default.weight',
'base_model.model.model.layers.0.self_attn.k_proj.qzeros',
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'base_model.model.model.layers.0.self_attn.v_proj.lora_B.default.weight',
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[johnsmith0031]

I think it's normal. The default implement in transformers cannot load the weight for lora models using peft as default. The weights are loaded by the extra 2 lines of code:

state_dict_peft = torch.load(os.path.join(ft_config.resume_checkpoint, 'adapter_model.bin'), map_location='cpu')
set_peft_model_state_dict(model, state_dict_peft)

[nepeee]

Thx seems to be working well now.