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What's the "best-practice" for configuring CachedMultipleNegativesRankingLoss when used for DDP. Say for example I have 3000 unique `positive` labels in my dataset, and I'm training using DDP on a sin…
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How should I modify the code if I only add positive examples and do not add negative examples for fine-tuning?
This is the error reported during fine-tuning training when I set neg in the fine-tuni…
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## Prelude / Prior Work
- https://github.com/kurtzace/complete-data-science-bootcamp-excercises
- [AI notes 2023](https://github.com/kurtzace/diary2023/issues/13)
- [Other data science steps taken …
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Hi,
I see that `edge_splitter_train.train_test_split()` samples the same number of positive and negative edges.
Currently, I don't see a way to control the ratio of positive and negative edges. I…
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```Optimizing for sigma. Current sigma: 1.0
New sigma: 1.0 (took 32.67 s)
Traceback (most recent call last):
File "/home/fbr/src/fp_bench/./rfr.py", line 273, in
r2 = mlkrr_train_test_UCAP(…
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I've been reading through some of the other issues here trying to learn what I can about how this works, and the most helpful comments I have seen so far is to simply adjust LR for bad generations, an…
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Hi,
This works looks extremely interesting for a small hobby 3D scanner project I'm working on, but I can't get it to work. From the paper and the project site, the results look more promising than…
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- [x] Migrate training API from older code
- [ ] Factual Data (Dataset) vs Model Training Dataset - Admin panel should transform
- [x] Difference in a dataset (like a git difference) (doesnt need t…
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I am trying to get some predictions of protein-protein complexes.
As "positive" control, I use prediction for a complex for which the cryoEM structure was solved and published in second half of 2022.…
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Hello! I'm experiencing an issue or unexpected behavior during the fine-tuning process where the training loss remains unchanged, despite varying the number of negative pairs in the dataset used for f…