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So I have at least a few times gone to the leaderboard and seen that it was restarted.
This takes quite a while, but once it is done the leaderboard is reasonably fast.
There are two solutions to this problem:
limit restarts (23 people can now rebuild and someone might rebuild the space if they see some oddities not knowing how long it takes)
reduce restart time, there are multiple ways to do this
speed up result loading (mteb.load_results())
reduce the results that are loaded by deleting unused files. E.g. if model 1 is run with ArxivClustering both with and without a revision, we might choose to keep only the one with a revision
another solution is the speed up the loading of the results.
Avoid recomputing the cache:
Once the cache is created loading the data is quite quick. However, the cache is recomputed on rebuilt. We could have the cache updated daily instead.
Edit: As mentioned in #1983 the leaderboard also takes up a decent amount of memory on at least Linux machines
@x-tabdeveloping has been the main person working on this. @x-tabdeveloping feel free to edit this issue if there are solutions you would like to add or remove.
The text was updated successfully, but these errors were encountered:
So I have at least a few times gone to the leaderboard and seen that it was restarted.
This takes quite a while, but once it is done the leaderboard is reasonably fast.
There are two solutions to this problem:
mteb.load_results()
)ArxivClustering
both with and without a revision, we might choose to keep only the one with a revisionEdit: As mentioned in #1983 the leaderboard also takes up a decent amount of memory on at least Linux machines
@x-tabdeveloping has been the main person working on this. @x-tabdeveloping feel free to edit this issue if there are solutions you would like to add or remove.
The text was updated successfully, but these errors were encountered: