metadata
tags:
- generated_from_trainer
model-index:
- name: ROBERTA_SMILES_LARGE
results: []
widget:
- text: <mask>1CC[C@]23[C@@H]4[C@H]1CC5=C2C(=C(C=C5)O)O[C@H]3[C@H](C=C4)O
pipeline_tag: fill-mask
BERT_SMILES_LARGE
This model is a 83.5M parameter ROBERTA model fine tuned on a dataset of 1.1M SMILES (Simplified molecular-input line-entry system) for masked language modeling (MLM). This model builds on BERT_SMILES which was fine tuned on only 50k SMILES.
If you find this model useful, I would really appreciate you giving it a like!
Evaluation Loss: 0.482
Example:
Morphine
CN1CC[C@]23[C@@H]4[C@H]1CC5=C2C(=C(C=C5)O)O[C@H]3[C@H](C=C4)O
Intended uses & limitations
This model can now be used to predict physical or chemical properties with further training.
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Tokenizers 0.15.0