Environmentalbert Environmental

🚀 EnvironmentalBERT-environmental模型卡片

本模型是一个专门用于ESG领域环境文本分类的语言模型，基于特定论文进行训练，能有效检测环境文本样本，为环境相关的文本分析提供了强大支持。

🚀 快速开始

可参考Medium上的这些教程，获取关于模型使用、大规模分析和微调的指南。

你可以使用管道进行文本分类：

基础用法

from transformers import AutoModelForSequenceClassification, AutoTokenizer, pipeline
 
tokenizer_name = "ESGBERT/EnvironmentalBERT-environmental"
model_name = "ESGBERT/EnvironmentalBERT-environmental"
 
model = AutoModelForSequenceClassification.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(tokenizer_name, max_len=512)
 
pipe = pipeline("text-classification", model=model, tokenizer=tokenizer) # set device=0 to use GPU
 
# See https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.pipeline
print(pipe("Scope 1 emissions are reported here on a like-for-like basis against the 2013 baseline and exclude emissions from additional vehicles used during repairs.", padding=True, truncation=True))

✨ 主要特性

基于这篇论文开发的EnvironmentalBERT-environmental语言模型，以EnvironmentalBERT-base模型为起点，在一个包含2000个样本的环境数据集上进行了额外的微调，能够更好地对ESG领域的环境文本进行分类。

📚 详细文档

更多详细信息可在论文中找到：

@article{Schimanski23ESGBERT,
    title={{Bridiging the Gap in ESG Measurement: Using NLP to Quantify Environmental, Social, and Governance Communication}},
    author={Tobias Schimanski and Andrin Reding and Nico Reding and Julia Bingler and Mathias Kraus and Markus Leippold},
    year={2023},
    journal={Available on SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4622514},
}

📄 许可证

本模型采用Apache-2.0许可证。

📦 数据集

• ESGBERT/environmental_2k

🏷️ 标签

• ESG
• environmental