6. TorchMetrics
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is a library that provides standardized metrics for evaluating PyTorch models. It
integrates seamlessly with PyTorch and PyTorch Lightning, offering a variety of metrics for tasks
like classification, regression, and segmentation.
WHEN TO USE
BinaryAccuracy: Measures accuracy for binary classification tasks.
BinaryF1Score: Computes the F1-score, a harmonic mean of precision and recall.
BinaryAUROC: Measures the Area Under the Receiver Operating Characteristic Curve,
which evaluates a model’s ability to distinguish between classes.
When you need standardized evaluation metrics for deep learning models.
If you're using PyTorch Lightning, since it integrates well with it.
To ensure that metric calculations are consistent and optimized across different devices
(CPU/GPU).
