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Update README.md

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@@ -47,5 +47,10 @@ results = model.predict(
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  Clearly describes the performance metrics used to assess the model, includes at least one performance-related graph (e.g., training/validation loss, accuracy, or clustering context figure), and provides a detailed explanation of its significance. For unsupervised learning (e.g., KMeans), a context figure showing cluster distribution and meaning is required.
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  Clearly describes an example study that could be conducted using the model, including a specific hypothesis and a well-justified explanation of why the model is an effective tool for the study. For unsupervised projects, includes clear instructions for submitting a markdown document with a context figure explaining cluster meanings.
 
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  Clearly describes the performance metrics used to assess the model, includes at least one performance-related graph (e.g., training/validation loss, accuracy, or clustering context figure), and provides a detailed explanation of its significance. For unsupervised learning (e.g., KMeans), a context figure showing cluster distribution and meaning is required.
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+ # Metrics and Graphs:
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+ Below is the F1 confidence curve for this model:
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+ ![Confidence Curve](/F1_curve (1).png)
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  Clearly describes an example study that could be conducted using the model, including a specific hypothesis and a well-justified explanation of why the model is an effective tool for the study. For unsupervised projects, includes clear instructions for submitting a markdown document with a context figure explaining cluster meanings.