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README.md

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+---
+language: en
+tags:
+- science
+- multi-displinary
+license: apache-2.0
+---
+
+# ScholarBERT_100_WB Model
+
+This is the **ScholarBERT_100_WB** variant of the ScholarBERT model family.
+
+The model is pretrained on a large collection of scientific research articles (**221B tokens**).
+Additionally, the pretraining data also includes the Wikipedia+BookCorpus, which are used to pretrain the [BERT-base](https://huggingface.co/bert-base-cased) and [BERT-large](https://huggingface.co/bert-large-cased) models.
+
+This is a **cased** (case-sensitive) model. The tokenizer will not convert all inputs to lower-case by default.
+
+The model is based on the same architecture as [BERT-large](https://huggingface.co/bert-large-cased) and has a total of 340M parameters.
+
+
+# Model Architecture
+
+| Hyperparameter  | Value |
+|-----------------|:-------:|
+| Layers     | 24    |
+| Hidden Size     | 1024  |
+| Attention Heads | 16    |
+| Total Parameters | 340M |
+
+
+# Training Dataset
+
+The vocab and the model are pertrained on **100% of the PRD** scientific literature dataset and the Wikipedia+BookCorpus.
+ 
+The PRD dataset is provided by Public.Resource.Org, Inc. (“Public Resource”), 
+a nonprofit organization based in California. This dataset was constructed from a corpus
+of journal article files, from which We successfully extracted text from 75,496,055 articles from 178,928 journals.
+The articles span across Arts & Humanities, Life Sciences & Biomedicine, Physical Sciences,
+Social Sciences, and Technology. The distribution of articles is shown below.
+
+![corpus pie chart](https://huggingface.co/globuslabs/ScholarBERT/resolve/main/corpus_pie_chart.png)
+
+
+# BibTeX entry and citation info
+If using this model, please cite this paper:
+
+[To be added]