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model = AutoAdapterModel.from_pretrained("roberta-base")
config = AdapterConfig.load("pfeiffer")
model.load_adapter("comsense/cosmosqa@ukp", config=config)

Description

Pfeiffer Adapter trained on Cosmos QA.

Properties

Pre-trained model
roberta-base
Adapter type
Task
Prediction Head
  No
Task
Common Sense Reasoning
Dataset
Cosmos QA

Architecture

Name
pfeiffer
Non-linearity
relu
Reduction factor
16
{
  "ln_after": false,
  "ln_before": false,
  "mh_adapter": false,
  "output_adapter": true,
  "adapter_residual_before_ln": false,
  "non_linearity": null,
  "original_ln_after": true,
  "original_ln_before": true,
  "reduction_factor": null,
  "residual_before_ln": true
}

Author

  Name
Jonas Pfeiffer
  E-Mail
pfeiffer@ukp.informatik.tu-darmstadt
  Web
https://pfeiffer.ai
  GitHub
JoPfeiff
  Twitter
@PfeiffJo

Versions

Identifier Comment Score Download
AdapterFusion DEFAULT

Citations

Adapter
@article{Pfeiffer2020AdapterFusion,
author = {Pfeiffer, Jonas and Kamath, Aishwarya and R{\"{u}}ckl{\'{e}}, Andreas and Cho, Kyunghyun and Gurevych, Iryna},
journal = {arXiv preprint},
title = {{AdapterFusion}:  Non-Destructive Task Composition for Transfer Learning},
 url       = {https://arxiv.org/pdf/2005.00247.pdf},
year = {2020}
}
Architecture
@misc{pfeiffer2020adapterfusion,
  title={AdapterFusion: Non-Destructive Task Composition for Transfer Learning},
  author={Jonas Pfeiffer and Aishwarya Kamath and Andreas Rücklé and Kyunghyun Cho and Iryna Gurevych},
  year={2020},
  eprint={2005.00247},
  archivePrefix={arXiv},
  primaryClass={cs.CL}
}
Task
@inproceedings{huang2019cosmos,
  title={Cosmos QA: Machine Reading Comprehension with Contextual Commonsense Reasoning},
  author={Huang, Lifu and Le Bras, Ronan and Bhagavatula, Chandra and Choi, Yejin},
  booktitle={Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)},
  pages={2391--2401},
  year={2019}
}