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liserman/
xml-roberta-climate-change-narrow-v03

Name: xml-roberta-climate-change-narrow-v03
Availability: InStock

FacebookAI/xlm-roberta-base

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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 mentions of climate change or climate change policy.

Climate change	N	%
Yes	1902	26.76
No	5205	73.24

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.

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."

Non-examples

"We need to invest in renewable energy for a cleaner future." (Unless it explicitly mentions climate change or related policies)

Model Details

Finetuned from model: FacebookAI/xml-roberta-base
Learning rate: 2e-05
Epochs: 28
Warmup ratio: 0.1104518378674452

	Test set	Evaluation set
Loss	0.2814	0.2940
Accuracy	0.9691	0.9677
Accuracy balanced	0.9596	0.9619
F1 macro	0.9578	0.9597
F1 micro	0.9691	0.9677
Precision macro	0.9560	0.9576
Precision micro	0.9691	0.9677
Recall macro	0.9596	0.9619
Recall micro	0.9691	0.9677

liserman/xml-roberta-climate-change-narrow-v03