{
  "fetched_at": "2026-10-24T12:23:25Z",
  "source_url": "https://www.kaggle.com/competitions/HW1NLP/data",
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    {
      "name": "data-description",
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    {
      "name": "Evaluation",
      "content": "# Evaluation Metrics</h2>\n## The evaluation metric for this competition is  Macro F-Score.\n\nThe F1 score, commonly used in information retrieval, measures accuracy using the statistics precision p and recall r. Precision is the ratio of true positives (tp) to all predicted positives (tp + fp). Recall is the ratio of true positives to all actual positives (tp + fn). The F1 score is given by:\n$$ F1 = 2\\frac{p \\cdot r}{p+r}\\ \\ \\mathrm{where}\\ \\ p = \\frac{tp}{tp+fp},\\ \\ r = \\frac{tp}{tp+fn} $$\n\nMacro F score calculate f1 score for each label, and find their unweighted mean\n## Submission Format</h2>\nSubmission files should contain two columns: id  and Target.</p>\n<p>The file should contain a header and have the following format:</p>\n<pre>id ,Target <br>7789, -1<br>7790,  1 <br> ",
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