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EnasAli/VitforEurosat
VitforEurosat is a machine learning model from EnasAli. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
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Updated Jul 12, 2023
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From the Hugging Face model README
Welcome to this end-to-end Image Classification example using Keras and Hugging Face Transformers. In this demo, we will use the Hugging Faces transformers and datasets library together with Tensorflow & Keras to fine-tune a pre-trained vision transformer for image classification.
We are going to use the EuroSAT dataset for land use and land cover classification. The dataset is based on Sentinel-2 satellite images covering 13 spectral bands and consisting out of 10 classes with in total 27,000 labeled and geo-referenced images.
More information for the dataset can be found at the repository.
We are going to use all of the great Feature from the Hugging Face ecosystem like model versioning and experiment tracking as well as all the great features of Keras like Early Stopping and Tensorboard.