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Version
pyabsa==2.3.1
torch==1.13.0
transformers==4.29.0
Describe the bug
I used to load my custom state_dict from my windows system and the loading procedure worked.
However, I am training now on a linux server for resource reasons. I trained a sample model and copied the whole folder containing the model files to my windows system (.args, config, .state_dict, .tokenizer).
Now I tried to load that model in the same way as always but I get errors: (refer to Screenshot for details).
RuntimeError: Error(s) in loading state_dict for FAST_LCF_ATEPC:
Missing key(s) in state_dict: "bert4global.embeddings.position_ids".
if not hasattr(ATEPCModelList, self.model.class.name):
raise KeyError(
"The checkpoint you are loading is not from any ATEPC model."
)
Code To Reproduce
aspect_extractor = ATEPC.AspectExtractor('fast_lcf_atepc_custom_dataset_cdw_apcacc_75.0_apcf1_74.31_atef1_40.45',
auto_device=True, # False means load model on CPU
cal_perplexity=True,
)
Expected behavior
I expect the program to load my custom checkpoint/saved_state_dict.
Screenshots
The text was updated successfully, but these errors were encountered:
I now have an idea why it does not work. I had a different version of tranformers on linux where i trained (4.35.2), in contrast in windows i have transformers==4.29 which might be the problem when loading the state_dict.
Version
pyabsa==2.3.1
torch==1.13.0
transformers==4.29.0
Describe the bug
I used to load my custom state_dict from my windows system and the loading procedure worked.
However, I am training now on a linux server for resource reasons. I trained a sample model and copied the whole folder containing the model files to my windows system (.args, config, .state_dict, .tokenizer).
Now I tried to load that model in the same way as always but I get errors: (refer to Screenshot for details).
RuntimeError: Error(s) in loading state_dict for FAST_LCF_ATEPC:
Missing key(s) in state_dict: "bert4global.embeddings.position_ids".
if not hasattr(ATEPCModelList, self.model.class.name):
raise KeyError(
"The checkpoint you are loading is not from any ATEPC model."
)
Code To Reproduce
aspect_extractor = ATEPC.AspectExtractor('fast_lcf_atepc_custom_dataset_cdw_apcacc_75.0_apcf1_74.31_atef1_40.45',
auto_device=True, # False means load model on CPU
cal_perplexity=True,
)
Expected behavior
I expect the program to load my custom checkpoint/saved_state_dict.
Screenshots
The text was updated successfully, but these errors were encountered: