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update model card data

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  This model is designed to test the integration of a custom Dropout operator for the `Aidge platform` and to explore how predictive uncertainty varies between in-distribution (CIFAR-10) and out-of-distribution (GTSRB) samples. By analyzing the model’s predictive uncertainty across both datasets, we can evaluate how effectively the model distinguishes between familiar and unfamiliar inputs.
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  ## Model Details
 
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+ ---
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+ base_model:
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+ - resnet-18
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+ pipeline_tag: image-classification
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+ license: cc
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+ datasets:
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+ - cifar10
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+ language:
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+ - en
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+ metrics:
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+ - accuracy
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+ ---
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  This model is designed to test the integration of a custom Dropout operator for the `Aidge platform` and to explore how predictive uncertainty varies between in-distribution (CIFAR-10) and out-of-distribution (GTSRB) samples. By analyzing the model’s predictive uncertainty across both datasets, we can evaluate how effectively the model distinguishes between familiar and unfamiliar inputs.
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  ## Model Details