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---
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 |