--- license: apache-2.0 datasets: - ClimatePolicyRadar/national-climate-targets language: - en pipeline_tag: text-classification tags: - climate widget: - text: "The Net Zero Strategy, published in October 2021, was the first document of its kind for a major economy. It set out the government’s vision for a market-led, technology-driven transition to decarbonise the UK economy and reach net zero by 2050." inference: parameters: function_to_apply: "sigmoid" --- ## National Climate Targets Classifier - Climate Policy Radar A multi-label text-classifier trained on the National Climate Targets dataset by Climate Policy Radar. Using the [climatebert/distilroberta-base-climate-f](https://huggingface.co/climatebert/distilroberta-base-climate-f) model as a starting point, this classifier is trained on the [ClimatePolicyRadar/national-climate-targets](https://huggingface.co/datasets/ClimatePolicyRadar/national-climate-targets) dataset to predict Net Zero ("NZT") , "Reduction" and "Other" targets in a multi-label setting. The training data is an expert annotated subset of national laws, policies and UNFCCC submissions. For more information on the annotation methodology and classifier training [see our paper](https://arxiv.org/abs/2404.02822). ## Getting started ```python from transformers import AutoModelForSequenceClassification, AutoTokenizer model_name = "ClimatePolicyRadar/national-climate-targets" example = "The Net Zero Strategy, published in October 2021, was the first "\ "document of its kind for a major economy. It set out the government’s "\ "vision for a market-led, technology-driven transition to decarbonise "\ "the UK economy and reach net zero by 2050." model = AutoModelForSequenceClassification.from_pretrained(model_name) tokenizer = AutoTokenizer.from_pretrained(model_name) # using sigmoid because the model is multi-label pipe = pipeline("text-classification", model=model, tokenizer=tokenizer, function_to_apply="sigmoid") pipe(example, padding=True, truncation=True) >>> [{'label': 'NZT', 'score': 0.9142044186592102}] ``` ## Licence Our classifier is licensed as [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0). Please read our [Terms of Use](https://app.climatepolicyradar.org/terms-of-use), including any specific terms relevant to commercial use. Contact partners@climatepolicyradar.org with any questions. ## Links - __Repository__: [coming soon] - __Paper__: [coming soon] ## Citation [coming soon] ## Authors & Contact Climate Policy Radar team: Matyas Juhasz, Tina Marchand, Roshan Melwani, Kalyan Dutia, Sarah Goodenough, Harrison Pim, and Henry Franks. dsci@climatepolicyradar.org https://climatepolicyradar.org