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Yield Estimation Transformer

A Hugging Face custom pipeline using Transformers model for county-level corn yield estimation using multi-temporal weather observations and static soil properties.

The model combines weekly weather time-series with static soil features to estimate corn yield in bushels per acre (bu/acre). It is packaged for inference using Hugging Face Transformers and has been tested for deployment through FlexServ.

The Hugging Face text-classification task is used as the FlexServ-compatible serving interface. The underlying model performs regression, and the returned score represents predicted corn yield in bu/acre.

The training_code directory composes the source code for data preparation, model training, evaluation, and inference.

Hugging Face Model Card License: MIT

Model card

This component is distributed on Hugging Face — see the full model card at ICICLE-AI/yield-estimation.

License​

License This project is released under the MIT License. The full text is available in LICENSE.

References​

USA County Level Crop Yield Dataset​

This model uses the USA County Level Crop Yield Dataset.


@article{Khaki2020CNNRNN,
  author    = {Khaki, Saeed and Wang, Liang and Archontoulis, Sotirios V.},
  title     = {A CNN-RNN Framework for Crop Yield Prediction},
  journal   = {Frontiers in Plant Science},
  volume    = {10},
  pages     = {1750},
  year      = {2020},
  doi       = {10.3389/fpls.2019.01750},
  publisher = {Frontiers Media SA}
}

FlexServ​

The model is packaged and validated for deployment with FlexServ.

FlexServ documentation: https://zhangwei217245.github.io/FlexServ/

Acknowledgements​

This work was developed as part of the ICICLE AI Institute.

National Science Foundation (NSF) funded AI institute for Intelligent Cyberinfrastructure with Computational Learning in the Environment (ICICLE) (OAC 2112606)

Issue reporting​

Contact:

For questions or support:

Sarikaa Sridhar: sridhar.86@buckeyemail.osu.edu