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llm-email-spam-detection's Issues

Code running GPU memory overflow

Hello, can you tell me the machine configuration parameters you use when running the code? After I ran the RoBERTa model training on the LING data set using the V100 graphics card on colab pro, I was prompted to run out of memory.

Error message:

OutOfMemoryError                          Traceback (most recent call last)

in ()

17

18     # Train LLMs

---> 19     train_llms(

20         list(range(5)),

21         ["ling", "sms", "spamassassin", "enron"],


19 frames

/ usr/local/lib/python3.10 / dist - packages/transformers/activations. Py in forward (self, input)

55

56     def forward(self, input: Tensor) -> Tensor:

---> 57         return self.act(input)

58

59



OutOfMemoryError: CUDA out of memory. Tried to allocate 72.00 MiB (GPU 0; 15.77 GiB total capacity; 14.60 GiB already allocated; 46.12 MiB free; 14.75 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid  fragmentation.  See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF

If it is convenient for you, can you disclose the output records generated by your training in the paper.
Thank you very much for your attention to this issue.

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