|
--- |
|
language: |
|
- en |
|
tags: |
|
- retrained |
|
- SpanBERT |
|
--- |
|
|
|
|
|
SpanBERT |
|
|
|
This is the SpanBERT model from: |
|
|
|
Mike Zhang, Kristian Nørgaard Jensen, Sif Dam Sonniks, and Barbara Plank. __SkillSpan: Hard and Soft Skill Extraction from Job Postings__. To appear at the 2022 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL). 2022. |
|
|
|
This model is pre-trained from scratch on the BookCorpus and WikiData. To pre-train from scratch we use the code from Splinter: https://github.com/oriram/splinter. |
|
On our job posting dataset, we found that our `spanbert-base-cased` model works better than the original. |
|
|
|
More information can be found in the paper (which should be released when the NAACL proceedings are online). |
|
|
|
If you use this model, please cite the following paper: |
|
|
|
``` |
|
@misc{https://doi.org/10.48550/arxiv.2204.12811, |
|
doi = {10.48550/ARXIV.2204.12811}, |
|
url = {https://arxiv.org/abs/2204.12811}, |
|
author = {Zhang, Mike and Jensen, Kristian Nørgaard and Sonniks, Sif Dam and Plank, Barbara}, |
|
keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences}, |
|
title = {SkillSpan: Hard and Soft Skill Extraction from English Job Postings}, |
|
publisher = {arXiv}, |
|
year = {2022}, |
|
copyright = {arXiv.org perpetual, non-exclusive license} |
|
} |
|
``` |
