Code for NAACL 2022 paper Modeling Multi-Granularity Hierarchical Features for Relation Extraction.
transformers==3.0.2
python==3.7
pytorch==1.3.1
TACRED dataset is not open access, so we provide the cached file for the training and testing of our model. (If needed, you can get the raw data from https://catalog.ldc.upenn.edu/LDC2018T24. The TACRED Revisted dataset can be obtained by https://github.com/DFKI-NLP/tacrev.)
We use SpanBert from https://huggingface.co/SpanBERT/spanbert-large-cased.
TODO: We will released our trained model soon.
We provided log file of evaluation in logs.
You can evaluate our model by run:
chmod +x eval_tacred.sh; ./eval_tacred.sh
chmod +x eval_tacred_rev.sh; ./eval_tacred_rev.shWe train our model on single NVIDIA V100 GPU about 4 hours. You can train a new model by:
chmod +x run_spanbert.sh; ./run_spanbert.sh