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Transformer Example Update - AutoModelforSequenceClassification #2190
Transformer Example Update - AutoModelforSequenceClassification #2190
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Tried on Colab and it seems this does not work fine... @Ishan-Kumar2 could you check please ? Thanks !! |
Thanks for investigating @sdesrozis. Thanks for the PR @Ishan-Kumar2, please make sure your code works before pushing your updates, thanks! |
Hi @sdesrozis, I tested on my machine and on colab just now, its seems to be working for me. Could you share the notebook you running or please have a look at this one(I stopped the run after 1 epoch)? |
@Ishan-Kumar2 I confirm it does not work using GPU which is not enabled in your notebook. Anyway, it would be great that your branch works fine (version 0.5 instead of 0.4.6)
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@sdesrozis thanks for the review, I realized there was a slight mistake in the transfer of the input to GPU. I have fixed it now and tested on Colab, it works fine. Please take a look thanks! |
Thanks for the updates @Ishan-Kumar2, the first issue has been solved, but there is another issue related to GPU memory in Colab with the default |
Hey @Ishan-Kumar2, any updates of this? |
@KickItLikeShika, added the commit. Sorry for the delay, I was stuck on why there was a sudden increase in GPU memory usage when going from Epoch 0 to Epoch 1. |
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Very nice work, Ishan! thanks a lot for the updates!
@KickItLikeShika I have made a minor change reverting the validation dataloader batch_size to 2 * train_loader batch_size. This wasn't the reason for the out of memory earlier. |
Hey @Ishan-Kumar2 and @KickItLikeShika , thank you for working on this PR. Just wanted to let you know that we are in the process of shifting ignite/examples to https://github.com/pytorch-ignite/examples. While this PR is a great improvement, this might not be relevant and can be removed once we make tutorials out of this, one of which is already in the process: pytorch-ignite/examples#32 which uses |
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@Ishan-Kumar2 Thanks ! LGTM !
Fixes #2189
Description:
Changes the model from
AutoModel
toAutoModelforSequenceClassification
so that any model which supports Sequence Classification list can be used without the need to make changes to the code.Check list: