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@@ -7,7 +7,7 @@ datasets:
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  metrics:
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  - accuracy
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  model-index:
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- - name: ZINC-deberta-base-output
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  results:
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  - task:
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  name: Masked Language Modeling
@@ -33,11 +33,11 @@ It achieves the following results on the evaluation set:
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  ## Model description
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- More information needed
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  ## Intended uses & limitations
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- More information needed
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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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