readme: ---
  language: protein
  tags:
  - protein language model
  datasets:
  - BFD
  - Custom Rosetta
  ---
  
  # ProtBert-BFD finetuned on Rosetta 20AA dataset
  
  This model is finetuned to predict Rosetta fold energy using a dataset of 100k 20AA sequences.
  
  Current model in this repo: `prot_bert_bfd-finetuned-032722_1752`
  
  ## Performance
  
  - 20AA sequences (1k eval set):\
  Metrics: 'mae': 0.090115, 'r2': 0.991208, 'mse': 0.013034, 'rmse': 0.114165
  
  - 40AA sequences (10k eval set):\
  Metrics: 'mae': 0.537456, 'r2': 0.659122, 'mse': 0.448607, 'rmse': 0.669781
  
  - 60AA sequences (10k eval set):\
  Metrics: 'mae': 0.629267, 'r2': 0.506747, 'mse': 0.622476, 'rmse': 0.788972
  
  
  ## `prot_bert_bfd` from ProtTrans
  The starting pretrained model is from ProtTrans, trained on 2.1 billion proteins from BFD.
  It was trained on protein sequences using a masked language modeling (MLM) objective. It was introduced in
  [this paper](https://doi.org/10.1101/2020.07.12.199554) and first released in
  [this repository](https://github.com/agemagician/ProtTrans).
  
  > Created by [Ladislav Rampasek](https://rampasek.github.io)
  