A transformer-based model that performs multiple tasks on scholarly knowledge graphs.

In order to use exBERT you have two options.

Via docker

$ docker run <some fancy image> # coming soon

Or alternatively you can setup the python code locally and run it with the shown commands.

First you need to download all the required packages

$ pip install -r requirements.txt

To run the exBERT scripts, you need to run the following command

Changing the parameters determines what task to perform on which datasets and what hyperparameters.

An example how to run UMLS with Sci-BERT on link prediction task is:

python3 exBERT.py --task htp \
     --do_train \
     --do_eval \
     --do_predict \
     --data_dir ./data/UMLS \
     --bert_model allenai/scibert_scivocab_uncased \
     --max_seq_length 15 \
     --train_batch_size 32 \
     --learning_rate 5e-5 \
     --num_train_epochs 8.0 \
     --output_dir ./output_UMLS/ \
     --gradient_accumulation_steps 1 \
     --eval_batch_size 135 \
     --fp16