Adapter bert-base-multilingual-uncased-hinglish-sentiment for bert-base-multilingual-uncased

Note: This adapter was not trained by the AdapterHub team, but by these author(s): Meghana Bhange, Nirant K. See author details below.

Adapter for Hinglish Sentiment Analysis, based on SemEval 2020 Task 9

This adapter was created for usage with the Adapters library.

Usage

First, install adapters:

pip install -U adapters

Now, the adapter can be loaded and activated like this:

from adapters import AutoAdapterModel

model = AutoAdapterModel.from_pretrained("bert-base-multilingual-uncased")
adapter_name = model.load_adapter("AdapterHub/bert-base-multilingual-uncased-hinglish-sentiment")
model.set_active_adapters(adapter_name)

Architecture & Training

• Adapter architecture: pfeiffer
• Prediction head: classification
• Dataset: Hinglish Sentiment

Author Information

• Author name(s): Meghana Bhange, Nirant K
• Author email: hinglish@nirantk.com
• Author links: Website, GitHub, Twitter

Citation

@article{Hinglish,
    title={HinglishNLP: Fine-tuned Language Models for Hinglish Sentiment Detection},
    author={Meghana Bhange,
            Nirant Kasliwal,
    journal={ArXiv},
    year={2020}
}

This adapter has been auto-imported from https://github.com/Adapter-Hub/Hub/blob/master/adapters/nirantk/bert-base-multilingual-uncased-hinglish-sentiment.yaml.