Cryptocurrency Q&A
Is 100 epochs too many?
Is 100 epochs too many?
SamsungShineBrightnessRadiance
Thu Dec 26 2024
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5 answers
667
I'm training a machine learning model and wondering if setting the number of epochs to 100 is excessive. I'm concerned about overfitting and want to ensure optimal performance.
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5 answers
Nicola
Sat Dec 28 2024
Early stopping not only prevents overfitting but also saves valuable time and computational power. It is an essential technique in model training, especially when dealing with large datasets and complex models.
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Giulia
Sat Dec 28 2024
For more intricate models, such as those used in deep learning on extensive datasets like CIFAR-10, the optimal number of epochs often lies between 60 and 70. This range provides a good compromise between training thoroughly and avoiding overfitting.
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mia_clark_teacher
Sat Dec 28 2024
When training various models, a common starting point for the number of epochs is within the range of 50 to 100. This provides a good balance between training sufficiently and not wasting computational resources.
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Bianca
Sat Dec 28 2024
After reaching this point, the risk of overfitting increases significantly. Therefore, it is important to be vigilant and use early stopping to prevent the model from deteriorating in performance on unseen data.
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henry_rose_scientist
Sat Dec 28 2024
However, it is crucial to employ early stopping techniques during the training process. By monitoring the validation performance, one can determine when the model begins to overfit and stop training accordingly.
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