transformers pytorch distilbert token-classification license:mit autotrain_compatible endpoints_compatible region:us
---
license: mit
widget:
- text: Monitored Natural Attenuation and, if necessary as a contingency, In Situ
    Chemical Oxidation to address the injection of a strong chemical oxidant to chemically
    treat the before the contingency can be implemented at the spill site.
  example_title: example 1
- text: Site was identified as a potential source of groundwater contamination after
    the City performed Assessments were investigated further for potential contamination.
  example_title: example 2
- text: Chromium releases from the UST is probably a major contributor to groundwater
    contamination in this area.
  example_title: example 3
---
## About the Model
An Environmental Named Entity Recognition model, trained on dataset from USEPA to recognize environmental due diligence (7 entities) from a given text corpus (remediation reports, record of decision, 5 year record etc). This model was built on top of distilbert-base-uncased

- Dataset: https://data.mendeley.com/datasets/tx6vmd4g9p/4
- Dataset Reasearch Paper: https://doi.org/10.1016/j.dib.2022.108579

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