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Hello, I used the scripts to prune the OPT-66B. (Unstructured, n_samples 128)
Upon with, I get a wikitext perplexity of 3404, which is way off the metric given in the paper.
I was wondering if the code output metric should be scaled by 0.01, (thus 3.404 perplexity)
Or if this is an outlier performance.
The text was updated successfully, but these errors were encountered:
This seems to be an outlier performance, which i get before from running on OPT-66B. I wasn't able to look into this (mainly because LLaMA and LLaMA2 is much more popular), but it would be interesting to study why this is the case from a scientific perspective.
Hello, I used the scripts to prune the OPT-66B. (Unstructured, n_samples 128)
Upon with, I get a wikitext perplexity of 3404, which is way off the metric given in the paper.
I was wondering if the code output metric should be scaled by 0.01, (thus 3.404 perplexity)
Or if this is an outlier performance.
The text was updated successfully, but these errors were encountered: