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ChemMRL

Sentence Similarity
sentence-transformers
Safetensors
modchembert
cheminformatics
smiles
molecular-similarity
feature-extraction
dense
Generated from Trainer
dataset_size:19381001
loss:Matryoshka2dLoss
loss:MatryoshkaLoss
loss:TanimotoSentLoss
custom_code
Eval Results (legacy)
Model card Files
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@@ -227,11 +227,11 @@ print(similarities)
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  | type | string | string | float |
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  | details | <ul><li>min: 17 tokens</li><li>mean: 42.36 tokens</li><li>max: 122 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 40.93 tokens</li><li>max: 122 tokens</li></ul> | <ul><li>min: 0.02</li><li>mean: 0.56</li><li>max: 1.0</li></ul> |
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  * Samples:
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- | smiles_a | smiles_b | label |
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- | :--------------------------------------------------------------------------------------------------- | :------------------------------------------------------------------------------------------------- | :------------------------------ |
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- | <code>COc1ccc(NC(=O)C2CC[NH+](C(C)C(=O)Nc3ccc(C(=O)Nc4ccc(F)c(F)c4)cc3C)CC2)cc1NC(=O)C1CCCCC1</code> | <code>Cc1cc(C(=O)Nc2ccc(F)c(F)c2)ccc1NC(=O)C(C)[NH+]1CCC(C(=O)Nc2cccc(NC(=O)C3CCCCC3)c2)CC1</code> | <code>0.8495575189590454</code> |
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- | <code>OCCN1CC[NH+](Cc2ccccc2OC2CC2)CC1</code> | <code>OCCN1CC[NH+](Cc2ccccc2On2cccn2)CC1</code> | <code>0.6615384817123413</code> |
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- | <code>CC1CN(C(=O)C2CC[NH+](Cc3cccc(C(N)=O)c3)CC2)CC(C)O1</code> | <code>CC1CN(C(=O)C2CC[NH+](Cc3ccccc3)CC2)CC(C)O1</code> | <code>0.7123287916183472</code> |
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  * Loss: [<code>Matryoshka2dLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#matryoshka2dloss) with these parameters:
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  ```json
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  {
 
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  | type | string | string | float |
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  | details | <ul><li>min: 17 tokens</li><li>mean: 42.36 tokens</li><li>max: 122 tokens</li></ul> | <ul><li>min: 11 tokens</li><li>mean: 40.93 tokens</li><li>max: 122 tokens</li></ul> | <ul><li>min: 0.02</li><li>mean: 0.56</li><li>max: 1.0</li></ul> |
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  * Samples:
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+ | smiles_a | smiles_b | label |
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+ | :----------------------------------------------------------------------------------------------------- | :--------------------------------------------------------------------------------------------------- | :------------------------------ |
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+ | <code>COc1ccc(NC(=O)C2CC\[NH+\](C(C)C(=O)Nc3ccc(C(=O)Nc4ccc(F)c(F)c4)cc3C)CC2)cc1NC(=O)C1CCCCC1</code> | <code>Cc1cc(C(=O)Nc2ccc(F)c(F)c2)ccc1NC(=O)C(C)\[NH+\]1CCC(C(=O)Nc2cccc(NC(=O)C3CCCCC3)c2)CC1</code> | <code>0.8495575189590454</code> |
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+ | <code>OCCN1CC\[NH+\](Cc2ccccc2OC2CC2)CC1</code> | <code>OCCN1CC\[NH+\](Cc2ccccc2On2cccn2)CC1</code> | <code>0.6615384817123413</code> |
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+ | <code>CC1CN(C(=O)C2CC\[NH+\](Cc3cccc(C(N)=O)c3)CC2)CC(C)O1</code> | <code>CC1CN(C(=O)C2CC\[NH+\](Cc3ccccc3)CC2)CC(C)O1</code> | <code>0.7123287916183472</code> |
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  * Loss: [<code>Matryoshka2dLoss</code>](https://sbert.net/docs/package_reference/sentence_transformer/losses.html#matryoshka2dloss) with these parameters:
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  ```json
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  {