đ Model Card for distilroberta-base-climate-detector
This is a fine - tuned language model designed to detect climate - related paragraphs. It offers a practical solution for quickly identifying climate - relevant text, which is valuable in the context of climate research and information processing.
đ Quick Start
You can use the model with a pipeline for text classification:
Basic Usage
from transformers import AutoModelForSequenceClassification, AutoTokenizer, pipeline
from transformers.pipelines.pt_utils import KeyDataset
import datasets
from tqdm.auto import tqdm
dataset_name = "climatebert/climate_detection"
model_name = "climatebert/distilroberta-base-climate-detector"
dataset = datasets.load_dataset(dataset_name, split="test")
model = AutoModelForSequenceClassification.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name, max_len=512)
pipe = pipeline("text-classification", model=model, tokenizer=tokenizer, device=0)
for out in tqdm(pipe(KeyDataset(dataset, "text"), padding=True, truncation=True)):
print(out)
⨠Features
- This is the fine - tuned ClimateBERT language model with a classification head for detecting climate - related paragraphs.
- Using the [climatebert/distilroberta - base - climate - f](https://huggingface.co/climatebert/distilroberta - base - climate - f) language model as starting point, the distilroberta - base - climate - detector model is fine - tuned on our climatebert/climate_detection dataset.
â ī¸ Important Note
This model is trained on paragraphs. It may not perform well on sentences.
đ Documentation
Model Description
This is the fine - tuned ClimateBERT language model with a classification head for detecting climate - related paragraphs.
Using the [climatebert/distilroberta - base - climate - f](https://huggingface.co/climatebert/distilroberta - base - climate - f) language model as starting point, the distilroberta - base - climate - detector model is fine - tuned on our climatebert/climate_detection dataset.
Citation Information
@techreport{bingler2023cheaptalk,
title={How Cheap Talk in Climate Disclosures Relates to Climate Initiatives, Corporate Emissions, and Reputation Risk},
author={Bingler, Julia and Kraus, Mathias and Leippold, Markus and Webersinke, Nicolas},
type={Working paper},
institution={Available at SSRN 3998435},
year={2023}
}
đ License
The model is licensed under the Apache - 2.0 license.
Property |
Details |
Model Type |
Fine - tuned ClimateBERT language model with a classification head |
Training Data |
climatebert/climate_detection |
Metrics |
accuracy |