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README.md
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Training was implemented using the [**Lightly** self-supervised learning framework](https://docs.lightly.ai/self-supervised-learning/index.html). The training images were obtained from the [`clane9/imagenet-100`](https://huggingface.co/datasets/clane9/imagenet-100) dataset on Hugging Face.
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## Model Architecture
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The model uses a standard **ResNet-18** encoder with the classification head removed and a SimCLR projection head attached during self-supervised pretraining.
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Training was implemented using the [**Lightly** self-supervised learning framework](https://docs.lightly.ai/self-supervised-learning/index.html). The training images were obtained from the [`clane9/imagenet-100`](https://huggingface.co/datasets/clane9/imagenet-100) dataset on Hugging Face.
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**Code, preprocessing, analysis, and other related material associated with the paper are hosted on Github:** [DM-Diaz/eccentricity-constrained-simclr](https://github.com/DM-Diaz/eccentricity-constrained-simclr)
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## Model Architecture
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The model uses a standard **ResNet-18** encoder with the classification head removed and a SimCLR projection head attached during self-supervised pretraining.
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