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@NouamaneTazi NouamaneTazi commented Aug 12, 2023

You can try this PR using:

torchrun --nproc_per_node=2 examples/retrieval/evaluation/dense/evaluate_sbert_multi_gpu.py

Using e5-large model I got

  • MSMARCO (8.84M documents) took 1h03min to encode (on 16 GPUs) -> evaluation took 1h04min
  • NQ (2.68M documents) took 22min to encode (on 16 GPUs) -> evaluation took 25min

cc @thakur-nandan

Fixes #134

@NouamaneTazi NouamaneTazi marked this pull request as ready for review August 12, 2023 23:55
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LGTM.

@thakur-nandan thakur-nandan merged commit 1b38876 into beir-cellar:main Feb 4, 2025
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evaluate_sbert_multi_gpu - metrics.compute() unable to read cache file

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