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Related Questions
- What are the key metrics used to monitor model performance during training, and how do they impact the choice of epoch size?
- How does monitoring loss and accuracy during training help in determining the optimal epoch size for a model?
- Can you explain the relationship between epoch size and model overfitting/underfitting, and how evaluation metrics influence this relationship?
- What are some common pitfalls to avoid when monitoring model performance during training, and how can they impact the choice of epoch size?
- How does the choice of evaluation metric (e.g. loss, accuracy, F1 score) influence the choice of epoch size?
- Can you provide examples of how monitoring model performance during training has influenced the choice of epoch size in real-world applications?
- How does the choice of epoch size impact the trade-off between model performance and training time, and how can evaluation metrics inform this trade-off?
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