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README.md
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metrics:
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- accuracy
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model-index:
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- name: ZINC-deberta
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results:
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- task:
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name: Masked Language Modeling
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## Model description
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## Intended uses & limitations
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## Training and evaluation data
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metrics:
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- accuracy
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model-index:
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- name: ZINC-deberta
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results:
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- task:
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name: Masked Language Modeling
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## Model description
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We trained deberta-base on SMILES from ZINC using the task of masked-language modeling (MLM). Its tokenizer is a character-level tokenizer trained on ZINC.
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## Intended uses & limitations
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This model can be used for the prediction of molecules' properties, reactions, or interactions with proteins by changing the way of finetuning.
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## Training and evaluation data
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