metadata

language:
  - en
tags:
  - JobBERT
  - job postings

JobBERT

This is the JobBERT 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 continuously pre-trained from a bert-base-cased checkpoint on ~3.2M sentences from job postings. 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}
}