Update README.md

---
language: en
license: mit

---

# LayoutLM
**Multimodal (text + layout/format + image) pre-training for document AI**

[Microsoft Document AI](https://www.microsoft.com/en-us/research/project/document-ai/) | [GitHub](https://aka.ms/layoutlm)

## Model description

LayoutLM is a simple but effective pre-training method of text and layout for document image understanding and information extraction tasks, such as form understanding and receipt understanding. LayoutLM archives the SOTA results on multiple datasets. For more details, please refer to research paper:

[LayoutLM: Pre-training of Text and Layout for Document Image Understanding](https://arxiv.org/abs/1912.13318)
Yiheng Xu, Minghao Li, Lei Cui, Shaohan Huang, Furu Wei, Ming Zhou, [KDD 2020](https://www.kdd.org/kdd2020/accepted-papers)

## Training data

I fine tuned the LayoutLM-Base, Uncased (11M documents, 2 epochs): 12-layer, 768-hidden, 12-heads, 113M parameters
on RVL-CDIP Dataset(Total 3200 images : 1940 train, 640 test, 640 valid) for 50 epochs.

## Citation

``` latex
@misc {xu2019layoutlm,
title={LayoutLM: Pre-training of Text and Layout for Document Image Understanding},
author={Yiheng Xu and Minghao Li and Lei Cui and Shaohan Huang and Furu Wei and Ming Zhou},
year={2019},
eprint={1912.13318},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
```

README.md

@@ -1,3 +1,35 @@
----
-license: apache-2.0
----
+---
+language: en
+license: mit
+
+---
+
+# LayoutLM
+**Multimodal (text + layout/format + image) pre-training for document AI**
+
+[Microsoft Document AI](https://www.microsoft.com/en-us/research/project/document-ai/) | [GitHub](https://aka.ms/layoutlm)
+
+## Model description
+
+LayoutLM is a simple but effective pre-training method of text and layout for document image understanding and information extraction tasks, such as form understanding and receipt understanding. LayoutLM archives the SOTA results on multiple datasets. For more details, please refer to research paper: 
+
+[LayoutLM: Pre-training of Text and Layout for Document Image Understanding](https://arxiv.org/abs/1912.13318)
+Yiheng Xu, Minghao Li, Lei Cui, Shaohan Huang, Furu Wei, Ming Zhou, [KDD 2020](https://www.kdd.org/kdd2020/accepted-papers)
+
+## Training data
+
+I fine tuned the LayoutLM-Base, Uncased (11M documents, 2 epochs): 12-layer, 768-hidden, 12-heads, 113M parameters 
+on RVL-CDIP Dataset(Total 3200 images : 1940 train, 640 test, 640 valid) for 50 epochs.
+
+## Citation
+
+``` latex
+@misc{xu2019layoutlm,
+    title={LayoutLM: Pre-training of Text and Layout for Document Image Understanding},
+    author={Yiheng Xu and Minghao Li and Lei Cui and Shaohan Huang and Furu Wei and Ming Zhou},
+    year={2019},
+    eprint={1912.13318},
+    archivePrefix={arXiv},
+    primaryClass={cs.CL}
+}
+```