README.md

MatSciBERT

A Materials Domain Language Model for Text Mining and Information Extraction

This is the pretrained model presented in MatSciBERT: A Materials Domain Language Model for Text Mining and Information Extraction, which is a BERT model trained on material science research papers.

The training corpus comprises papers related to the broad category of materials: alloys, glasses, metallic glasses, cement and concrete. We have utilised the abstracts and full length of papers(when available). All the research papers have been downloaded using from ScienceDirect using the Elsevier API. The detailed methodology is given in the paper.

The codes for pretraining and finetuning on downstream tasks are shared on GitHub.

If you find this useful in your research, please consider citing:

@article{gupta_matscibert_2021,
  title = {{{MatSciBERT}}: A {{Materials Domain Language Model}} for {{Text Mining}} and {{Information Extraction}}},
  shorttitle = {{{MatSciBERT}}},
  author = {Gupta, Tanishq and Zaki, Mohd and Krishnan, N. M. Anoop and Mausam},
  year = {2021},
  month = sep,
  journal = {arXiv:2109.15290 [cond-mat]},
  eprint = {2109.15290},
  eprinttype = {arxiv},
  primaryclass = {cond-mat},
  archiveprefix = {arXiv},
  keywords = {Computer Science - Computation and Language,Condensed Matter - Materials Science}}
}