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README.md

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+# 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](https://arxiv.org/abs/2109.15290), 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 are downloaded using from [ScienceDirect](https://www.sciencedirect.com/) using the [Elsevier API](https://dev.elsevier.com/). The detailed methodology is given in the paper.
+
+The codes for pretraining and finetuning on downstream tasks are shared on [GitHub](https://github.com/m3rg-repo/MatSciBERT).
+
+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}}
+}
+```