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Reproducing SERAC and MEND results #447
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Previously, some users did not have the necessary resource to complete the training of SERAC and MEND on CounterFact. |
Sorry, due to limited computing and storage resources, we will run it as soon as possible and upload the complete checkpoint to help you. Thank you for using EasyEdit! |
I actually did manage to run SERAC training on ZsRE, but only with data/zsre/zsre_mend_train_10000.json rather than the entire ZsRE training set. My portability results are different from what was reported in the README - 'portability': {'one_hop_acc': 0.3953153117763729} as opposed to 57.82 that was listed here. I see that similar results were reported here that you discuss match expectations for a smaller model, but I do not understand why that does not match the reported values. I did have a similar issue to #123 and switched over to the https://huggingface.co/Cheng98/llama-160m model as you suggest, but I would not expect this change to lead to such different final values. |
Sorry, we will try to handle this ASAP. Recently, computing resources have been extremely tight, making it very difficult to have machines available for debugging. |
I understand from #442 that you provided the checkpoints for SERAC and MEND trained on the CounterFact dataset, but I am not seeing CounterFact results for Llama in any of your papers. Do you happen to have those results or the checkpoints trained on ZsRE so I can ensure I have reproduced your solution? I am getting the following results for ZsRE with the provided SERAC checkpoint:
The rephrase_acc is low.
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