transformers pytorch roberta text-classification text classification fact checking en dataset:mwong/fever-evidence-related dataset:mwong/climate-evidence-related license:mit autotrain_compatible endpoints_compatible region:us
---
datasets:
- mwong/fever-evidence-related
- mwong/climate-evidence-related
language: en
license: mit
metrics: f1
tags:
- text classification
- fact checking
widget:
- text: Earth’s changing climate is a critical issue and poses the risk of significant
    environmental, social and economic disruptions around the globe.</s></s>Because
    of fears of climate change and adverse effects of drilling explosions and oil
    spills in the Gulf of Mexico, legislation has been considered, and governmental
    regulations and orders have been issued, which, combined with the local economic
    and employment conditions caused by both, could materially adversely impact the
    oil and gas industries and the economic health of areas in which a significant
    number of our stores are located.
  example_title: Evidence related to claim
---

# ClimateBert-related

ClimateBert-related is a classifier model that predicts if climate related evidence is related to query claim. The model achieved F1 score of 81.90% with test dataset "mwong/climate-evidence-related". Using pretrained ClimateBert-f model, the classifier head is trained on Fever dataset and adapted to climate domain using ClimateFever dataset.