Adapter salohnana2018/ABSA-SentencePair-corrected-domainAdapt-Stack-HARD50-Adapter-pfeiffer-run3 for CAMeL-Lab/bert-base-arabic-camelbert-msa

An adapter for the CAMeL-Lab/bert-base-arabic-camelbert-msa model that was trained on the [Arabic ABSA/SemEvalHotelReview](https://adapterhub.ml/explore/Arabic ABSA/SemEvalHotelReview/) dataset and includes a prediction head for classification.

This adapter was created for usage with the adapter-transformers library.

Usage

First, install adapter-transformers:

pip install -U adapter-transformers

Note: adapter-transformers is a fork of transformers that acts as a drop-in replacement with adapter support. More

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

from transformers import AutoAdapterModel

model = AutoAdapterModel.from_pretrained("CAMeL-Lab/bert-base-arabic-camelbert-msa")
adapter_name = model.load_adapter("salohnana2018/ABSA-SentencePair-corrected-domainAdapt-Stack-HARD50-Adapter-pfeiffer-run3", source="hf", set_active=True)

Architecture & Training

Evaluation results

Citation