Comments (2)
It just looks like you retrieved top 100, not top 1000. So your recall@1000 is just recall@100.
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Yeah, indeed. I set it to be 100 in ranking = searcher.search_all(queries, k=100)
. I thought it was 200, but I didn't find the number 200 using Ctrl + F
. Haha, thanks for you prompt response and patience!
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Related Issues (20)
- Process stuck on Launcher while training using example code
- incremental training on colbert
- [incremental indexing] - IndexUpdater.update_searcher is successful but search result does not show newly indexed passage HOT 1
- ColBERTv1: Faiss_depth usage in retrieval
- [c++] Calling pop() on an empty stack causes "undefined behavior"
- Searcher.search intermittent bug after IndexUpdater.persist_to_disk HOT 2
- Trainer.train() should not take checkpoint as an argument and should use self.config.checkpoint HOT 1
- Clarification on PLAID retrieval HOT 6
- Multiprocessing takes forever after on .get() with mp.Queue() (Possible Deadlock) HOT 2
- How to use a designated GPU for training? HOT 2
- FileNotFoundError: [Errno 2] No such file or directory: '***/.venv/lib/python3.8/site-packages/colbert/modeling/segmented_maxsim.cpp' HOT 3
- Duplicate search results when `k` is a high value HOT 8
- Recall and MRR for checkpoint different from paper HOT 2
- Using GPU, ColBERT.try_load_torch_extensions from IndexUpdater reports "Error building extension 'segmented_lookup_cpp'" HOT 1
- How to see progress of Indexing HOT 2
- About training from scratch HOT 8
- about the ranking operation HOT 1
- FAILED: decompress_residuals.cuda.o, ninja: build stopped: subcommand failed (from: ColBERT/colbert/indexing/codecs/decompress_residuals.cu) HOT 7
- Fine tuning using colbert-ir/colbertv2.0 using training script now gives error HOT 6
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