README.md

metadata

tags:
  - generated_from_trainer
model-index:
  - name: SMILES_BERT
    results: []
widget:
  - text: CC(=O)NC1<mask>CC=C(C=C1)O
pipeline_tag: fill-mask

SMILES_BERT

A BERT model trained on a list of 50,000 SMILES for MLM

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