Open juhoinkinen opened 1 year ago
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This PR experiments with implementing batched suggest calls for the base projects in NN ensemble backend.
Unfortunately there is no notable performance gain in real use, at least with MLLM, fastText, and Omikuji base projects (as in YSO projects of Finto AI), but actually a performance regression. Performance gain is seen when using only Omikuji as the base project, which is the only one of the backends in Finto AI YSO base models having the batch suggest method implemented.
Below results are from for runs at kj-kk using 16 jobs training on
corpora/fulltext-train/fi/*/
.MLLM, fastText, and Omikuji base projects
1000 docs, 1 epoch
2000 docs, 10 epochs
Omikuji base project only
2000 docs, 1 epoch