cd Cas_CLN&BTCAMS
Cas-CLN ==> mpn
BTCAMS ==> mhs
pretrained model：
|----chinese_roberta_wwm_large_ext_pytorch
(You should download by yourself from google. The folder is too large. https://huggingface.co/hfl/chinese-roberta-wwm-ext-large)
data:
CMeIE is also public available. Guan, T., Zan, H., Zhou, X., Xu, H., Zhang, K. (2020). CMeIE: Construction and Evaluation of Chinese Medical Information Extraction Dataset. In: Zhu, X., Zhang, M., Hong, Y., He, R. (eds) Natural Language Processing and Chinese Computing. NLPCC 2020. Lecture Notes in Computer Science(), vol 12430. Springer, Cham. https://doi.org/10.1007/978-3-030-60450-9_22
You can use your data by following the CMeIE's format or adjusting the code/spo_*/data_loader.py.
raw_data:
|----test_data.json
|----train_data.json
|----val_data.json
user_data:
|----split_data:
|----|----data_set1:
|----|----|----train_data.json
|----|----|----val_data.json
requirement:
----torch==1.2.0
----tqdm==4.35.0
----transformers==2.2.2
mkdir output_models
train: bash train_.sh
test: bash test_.sh