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@@ -60,9 +60,9 @@ We evaluate the model indirectly, and only care about the positive class:
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  In this fashion we obtain the following metrics:
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- * Precision: 0.9423
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- * Recall: 0.7802
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- * F_1 score: 0.8538
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  ![A gif illustrating correspondance between true and predicted prosodic
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  units](output.gif)
 
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  In this fashion we obtain the following metrics:
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+ * Precision: 0.9464
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+ * Recall: 0.8260
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+ * F_1 score: 0.8821
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  ![A gif illustrating correspondance between true and predicted prosodic
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  units](output.gif)