---
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