Comments (3)
Just to make sure I understand the context of your question, you are essentially writing your own code for pretraining the model on your own dataset, right? If so, I think this short thread will be useful for you.
Overall these inputs seem reasonable (assuming you don't have GO annotations), but that would of course depend on how exactly you use them to pretrain the model.
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@nadavbra thank you for your answer.
Yes I am changing your code a bit. I saw this thread and I also changed the DatasetHandler object to this one -
BTW, what exactly did you mean by "how exactly you use them to pretrain your model?", are you talking about the GO annotations? I dont want to use any at all
Thanks
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I just meant the overall flow of your code. Everything you do seems reasonable, but it just depends on your overall implementation.
I'd be curious to know whether it ended up working in the end.
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Related Issues (20)
- Failing to get the weights from the dedicated github repo HOT 5
- Use ProteinBERT with Own Dataset HOT 3
- Original h5 file HOT 5
- loss plot during pretraining HOT 1
- signal peptide detection HOT 1
- KeyError: "Unable to open object (object 'test_set_mask' doesn't exist)" HOT 6
- How to extract the embedding of an amino acid? HOT 10
- Graph execution error HOT 6
- Extract local and global representation using finetune model HOT 1
- Running Benchmarks HOT 4
- Evaluation on larger data set HOT 6
- Using vector representations in the "weights" parameter in the "embedding" section of an LSTM model after fine-tuning my own data HOT 1
- Failing to extract global embedding (1,15599) -> (1,512) HOT 1
- What do the settings mean? HOT 3
- Error when trying to run the finetuning code given in the jupyter notebook HOT 2
- ValueError, set_weights error
- model_generation.py list is not callable error HOT 2
- GO annotations during fine tuning HOT 1
- Missing MajorPTMs train CSV file HOT 1
- Can't get proteinBERT to run on GPU HOT 1
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