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@@ -23,7 +23,7 @@ SMILES2IUPAC-canonical-base was designed to accurately translate SMILES chemical
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  ### Model Description
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- SMILES2IUPAC-canonical-small is based on the MT5 model with optimizations in implementing different tokenizers for the encoder and decoder.
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  - **Developed by:** Knowladgator Engineering
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  - **Model type:** Encoder-Decoder with attention mechanism
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  - **Language(s) (NLP):** SMILES, IUPAC (English)
@@ -111,10 +111,10 @@ The model was trained on 100M examples of SMILES-IUPAC pairs with lr=0.0003, bat
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  | Model | Accuracy | BLEU-4 score | Size(MB) |
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  |-------------------------------------|---------|------------------|----------|
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- | SMILES2IUPAC-canonical-small |75%| 0.93 | 23 |
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- | SMILES2IUPAC-canonical-base |86.9%|0.964|180|
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- | STOUT V2.0\* | 66.65% | 0.92 | 128 |
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- | STOUT V2.0 (according to our tests) | | 0.89 | 128 |
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  *According to the original paper https://jcheminf.biomedcentral.com/articles/10.1186/s13321-021-00512-4
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  ## Citation
 
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  ### Model Description
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+ SMILES2IUPAC-canonical-base is based on the MT5 model with optimizations in implementing different tokenizers for the encoder and decoder.
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  - **Developed by:** Knowladgator Engineering
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  - **Model type:** Encoder-Decoder with attention mechanism
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  - **Language(s) (NLP):** SMILES, IUPAC (English)
 
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  | Model | Accuracy | BLEU-4 score | Size(MB) |
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  |-------------------------------------|---------|------------------|----------|
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+ | SMILES2IUPAC-canonical-small |75% |0.93 |23 |
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+ | SMILES2IUPAC-canonical-base |86.9% |0.964 |180 |
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+ | STOUT V2.0\* |66.65% |0.92 |128 |
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+ | STOUT V2.0 (according to our tests) | |0.89 |128 |
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  *According to the original paper https://jcheminf.biomedcentral.com/articles/10.1186/s13321-021-00512-4
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  ## Citation