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liserman/climaparl-xlm-roberta-climate-change-broad-v03

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face
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Climate classification model

This model is trained to classify climate change statements from parliamentary speeches. We finetuned a multilingual xml-roberta-base model on 7107 sentences from parliamentary speeches from 27 countries (EU + UK) to detect explicit and implicit mentions of climate change or climate change policy.

**Climate change****N****%**
Yes214230.14
No496569.86

Code Book

We define sentences as climate related if they directly references climate change, climate policy, or consequences of climate change (e.g., excessive temperature rises, sea level rise). This includes explicit mentions of climate change, global warming, greenhouse gases, carbon emissions, and specific climate change policies or targets.

Furthermore, we define a sentence as climate related if it does not explicitly mention climate change or policies exclusively targeting climate change, but has a clear relation to emission reduction/decarbonization or climate change adaptation. We consider statements about green electricity/sustainable energy/energy transition etc. as CO2 emission reduction/decarbonization efforts. Note that adaptation policies such as flood protection are only regarded as climate statements if there is also a reference to an increasing trend, severity, or frequency of floods due to changing climate. Sentences are only to be coded as implicit climate change, provided they do not explicitly relate to a different goal than combating climate change such as energy security or economic growth. In addition, statements that only refer to a reduction of pollutants or demands that polluters need to pay are too unspecific and are therefore not coded as climate change.

Examples

  • —"We must reduce our greenhouse gas emissions by 40% by 2030 to combat climate change."
  • —"We oppose the new carbon tax proposed by the government."
  • —"Climate change is the defining issue of our time, and we must act now to prevent catastrophic impacts."
  • —"The new legislation focuses on cutting carbon emissions."
  • —"We are committed to the Paris Agreement."
  • —"We need to invest in renewable energy for a cleaner future."
  • —"Renewable energy projects are vital for our environmental goals." (implicit emission reduction)

Non-examples

  • —"Renewable energy will enhance our energy security." (Mentions a goal other than climate change)
  • —"Economic growth can be supported by clean energy technologies." (Focuses on economic growth)
  • —"Sustainable development is key to our future prosperity." (Too broad, does not clearly relate to climate change)
  • —"We need to develop sustainable farming practices." (Too broad, does not clearly relate to climate change)

Model Details

  • —Finetuned from model: FacebookAI/xml-roberta-base
  • —Learning rate: 2e-05
  • —Epochs: 24
  • —Warmup ratio: 0.20865917769646153
**Test set****Evaluation set**
Loss0.56890.5971
Accuracy0.93110.9339
Accuracy balanced0.92800.9270
F1 macro0.92140.9218
F1 micro0.93110.9339
Precision macro0.91560.9170
Precision micro0.93110.9339
Recall macro0.92800.9270
Recall micro0.93110.9339