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@@ -36,4 +36,23 @@ DistilProtBert model was pretrained on [Uniref50](https://www.uniprot.org/downlo
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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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+ |:-----:|:-----:|:-----:|:-----:|
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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