SMILES_BERT
A BERT model trained on a list of 50,000 SMILES for MLM.
If you find this model useful, I would really appreciate you giving it a like!
Example:
Acetaminophen
CC(=O)NC1=CC=C(C=C1)O
Model description
This model is a BERT model that was trained on a list of 50k SMILES. The SMILES were sourced from BindingDB and the compounds bind to certain proteins with some affinity. The purpose of this model was to provide a model that understands SMILES which can then be fine-tuned for other tasks in which SMILES data can be useful e.g. bind affinity prediction, classification, etc.
Intended uses & limitations
This model was trained in order to provide a model which can then be fine-tuned for other tasks in which SMILES data can be useful such as predicting physical properties, chemical activity, or biological activity.
Training results
Training Loss: 0.9446000
Further evaluation is needed
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Tokenizers 0.15.0