SMILES_BERT / README.md
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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