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README.md
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# Pretraining procedure
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Preprocessing was done using ProtBert's tokenizer.
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The details of the masking procedure for each sequence followed the original Bert (as mentioned in [ProtBert](https://huggingface.co/Rostlab/prot_bert)).
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# Pretraining procedure
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Preprocessing was done using ProtBert's tokenizer.
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The details of the masking procedure for each sequence followed the original Bert (as mentioned in [ProtBert](https://huggingface.co/Rostlab/prot_bert)).
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The model was pretrained on a single DGX cluster 3 epochs in total. local batch size was 16, the optimizer used was AdamW with a learning rate of 5e-5 and mixed precision settings.
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## Evaluation results
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When fine-tuned on downstream tasks, this model achieves the following results:
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Test results :
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| Task/Dataset | secondary structure (3-states) | Membrane |
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| CASP12 | 72 | |
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| TS115 | 81 | |
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| CB513 | 79 | |
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| DeepLoc | | 86 |
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Distinguish between:
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### BibTeX entry and citation info
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