Comments (7)
Will need to use --batch_size=32
for 12GB. For 24GB GPU, works well.
f1b4520
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FYI, using ELMo with 12GB TitanXP (default batch_size = 64) works well :)
It takes up 9963MiB, and reaches 0.632 dev_f1 @ 5001.
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Weird.. which commit version did you use btw?
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I'm working on the forked repo (https://github.com/jhyuklee/piqa),
and the latest commit is 7dfb6fe.
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Worth pointing out that when I tried running the code on a 12GB GPU I also ran into a memory error with the default batch size of 64. Reducing the batch size to 32 solved the problem, and also gave a better F1 score of 63.5% (before applying the ELMO fix from 72c7623).
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@bdhingra thanks, 32 surely seems to work better (I got 63.7%).
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After updating to c6e8719, batch_size=64 makes OOM for me, too.
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Related Issues (11)
- About computation of Elmo HOT 2
- faiss does not provide pip installation
- leaderboard?
- Performance difference between evaluate.py vs piqa_evaluate.py HOT 2
- Error while running piqa_evaluate.py HOT 4
- TypeError: argument of type 'method' is not iterable HOT 4
- model.init(metadata) for test/embed HOT 1
- DataLoader with args.cache does not load elmo idx
- For the initial run, nltk download needed
- Allennlp does not support 3.7 yet
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