File size: 1,737 Bytes
ccfc23a 2ebcd8f 6fa5406 7e39cfd 2ebcd8f 7a02c9a ccfc23a b4673eb 88ed6b5 4fc19b0 88ed6b5 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 |
---
language: en
tags:
- science
- multi-displinary
license: apache-2.0
---
# ScholarBERT_100 Model
This is the **ScholarBERT_100** variant of the ScholarBERT model family.
The model is pretrained on a large collection of scientific research articles (**221B tokens**).
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.
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.
# BibTeX entry and citation info
If using this model, please cite this paper:
```
@misc{hong2023diminishing,
title={The Diminishing Returns of Masked Language Models to Science},
author={Zhi Hong and Aswathy Ajith and Gregory Pauloski and Eamon Duede and Kyle Chard and Ian Foster},
year={2023},
eprint={2205.11342},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
```
|