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README.md
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### Model Description
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SMILES2IUPAC-canonical-
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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
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| SMILES2IUPAC-canonical-base |86.9
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| STOUT V2.0\* |
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| STOUT V2.0 (according to our tests) | |
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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
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