Sure! Here are some common challenges I’ve faced when tuning hyperparameters:
Lots of Time Needed: Tuning can take a long time, especially when you’re working with big datasets and complicated models.
Overfitting: If you’re not careful, the model can focus too much on the validation set, making it less effective for new data.
Too Many Choices: When you consider more parameters, it gets super confusing. It becomes harder to find the best settings.
Getting Stuck: Sometimes, the process doesn’t move forward and just stays stuck in one spot, which is not ideal.
Dealing with these challenges can be tough, but it can also be very rewarding!
Sure! Here are some common challenges I’ve faced when tuning hyperparameters:
Lots of Time Needed: Tuning can take a long time, especially when you’re working with big datasets and complicated models.
Overfitting: If you’re not careful, the model can focus too much on the validation set, making it less effective for new data.
Too Many Choices: When you consider more parameters, it gets super confusing. It becomes harder to find the best settings.
Getting Stuck: Sometimes, the process doesn’t move forward and just stays stuck in one spot, which is not ideal.
Dealing with these challenges can be tough, but it can also be very rewarding!