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---
language: en
license: apache-2.0
datasets:
- ESGBERT/social_2k
tags:
- ESG
- social
---
# Model Card for SocRoBERTa-social
## Model Description
This is the SocRoBERTa-social language model. A language model that is trained to better classify social texts in the ESG domain.
Using the [SocRoBERTa-base](https://huggingface.co/ESGBERT/SocRoBERTa-base) model as a starting point, the SocRoBERTa-social Language Model is additionally fine-trained on a 2k social dataset to detect social text samples.
## How to Get Started With the Model
You can use the model with a pipeline for text classification:
```python
from transformers import AutoModelForSequenceClassification, AutoTokenizer, pipeline
from transformers.pipelines.pt_utils import KeyDataset
import datasets
from tqdm.auto import tqdm
tokenizer_name = "ESGBERT/SocRoBERTa-social"
model_name = "ESGBERT/SocRoBERTa-social"
model = AutoModelForSequenceClassification.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(tokenizer_name, max_len=512)
pipe = pipeline("text-classification", model=model, tokenizer=tokenizer, device=0)
# See https://huggingface.co/docs/transformers/main_classes/pipelines#transformers.pipeline
print(pipe("We follow rigorous supplier checks to prevent slavery and ensure workers' rights."))
```
## More details can be found in the paper
```bibtex
@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}
}
```
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