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I am trying to reproduce the results on MQUAKE-T and found the multihop results for "Base" are way less (16.22/22.59 for multihop and cot) than reported in Table 4. And I can not reproduce the FT results either.
Can you release your codes on evaluation and your own training hyperparameters for reproduction?
The text was updated successfully, but these errors were encountered:
Sorry for the evaluation issue! The bug is that the MQuAKE-T dataset we released before didn't contain the extended pre-edit gold answers (Appendix E in our updated version). This will cause a much lower performance of the base model due to the time mismatch of the training corpus and our Wikidata dump.
I have updated the dataset and MQuAKE-T includes a new field answer_extended which we used in our experiments. You should also use this filed for evaluating the base model before editing.
For FT results: we use the same hyperparameters as MEMIT did.
-----原始郵件-----
發件人:"Zexuan Zhong" ***@***.***>
發送時間:2023-11-27 05:53:06 (星期一)
收件人: princeton-nlp/MQuAKE ***@***.***>
抄送: "Shuo Zhang" ***@***.***>, Mention ***@***.***>
主題: Re: [princeton-nlp/MQuAKE] Can you release the codes for evaluation and training hyperparameters? (Issue #6)
Hi @ShuoZhangXJTU !
Sorry for the evaluation issue! The bug is that the MQuAKE-T dataset we released before didn't contain the extended pre-edit gold answers (Appendix E in our updated version). This will cause a much lower performance of the base model due to the time mismatch of the training corpus and our Wikidata dump.
I have updated the dataset and MQuAKE-T includes a new field answer_extended which we used in our experiments. You should also use this filed for evaluating the base model before editing.
For FT results: we use the same hyperparameters as MEMIT did.
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I am trying to reproduce the results on MQUAKE-T and found the multihop results for "Base" are way less (16.22/22.59 for multihop and cot) than reported in Table 4. And I can not reproduce the FT results either.
Can you release your codes on evaluation and your own training hyperparameters for reproduction?
The text was updated successfully, but these errors were encountered: