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 avatar commented on June 27, 2024 2

Are you using the BERT-large or BERT-base model type? With BERT-base, you should get very good results with a seq len of 256 and batch size of 16 (I did, anyway...).

Google's recommended seq/batch combos are at https://github.com/google-research/bert#out-of-memory-issues .

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mrxiaohe avatar mrxiaohe commented on June 27, 2024

I am using BERT-large uncased. Did you get your results after only 4 epochs?

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mrxiaohe avatar mrxiaohe commented on June 27, 2024

@tombriles I changed the model from large to base (uncased), and now a max seq len of 256 doesn't cause the out of memory error (it did before when I used the large model). I will report back on the performance once training is done!

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