{
  "fetched_at": "2026-10-19T09:10:26Z",
  "source_url": "https://www.kaggle.com/competitions/Imagenette-comp/data",
  "pages": [
    {
      "name": "data-description",
      "content": "<h2>File descriptions</h2>\n<ul>\n<li><strong>train</strong> - the training set</li>\n<li><strong>test</strong> - the test set</li>\n<li><strong>sample_submission.csv</strong> - a sample submission file in the correct format</li>\n</ul>",
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    {
      "name": "Description",
      "content": "# Imagenette Competition\nHi! It's the Imagenette competition, based on [imagenette](https://github.com/fastai/imagenette) dataset. This dataset is one of the main benchmark dataset for the image classification task, within ImageNet and CIFAR. Your goal here is creating and training a neural network model, that will identify an object on a photo.\n## Data Description\nDataset splits into train and test part. The training part consist of 10 folders with photos for each class. The test part has only photos without any distribution.\n## Baseline\nIn [github link](https://github.com/catalyst-team/dl-course/tree/master/homework-2/classification) you can find baseline notebook which will help you start your work.",
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    {
      "name": "Evaluation",
      "content": "## Evaluation\nThis competition is evaluated on the categorization accuracy of your predictions (the percentage of images you get correct).\n## Submission Format\nThe submission file should contain two column: /<Photo Id/>, /<Class Id/>\n```\n```",
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    {
      "name": "rules",
      "content": "This is a page where you can include rules that participants must accept before joining. You may wish to include rules like:\n\n - Don't cheat!\n - Apply yourself!\n - Have fun!",
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