A company is training a foundation model (FM). The company wants to increase the accuracy of the model up to a specific acceptance level. Which solution will meet these requirements?
B: Increase the epochs.
Explanation:
Increasing the epochs allows the model to go through the entire training dataset multiple times, improving its learning and optimizing its weights. This can help the model achieve a higher accuracy level, provided it does not lead to overfitting. For a foundation model (FM), increasing epochs is a common approach to refining accuracy to meet specific acceptance levels.
B. Increase the epochs.
Increasing the number of epochs, or training cycles, can help improve the accuracy of a foundation model. By exposing the model to the training data multiple times, it can learn more intricate patterns and relationships, leading to better performance.
B. Increase the epochs: Increasing the number of epochs allows the model to continue learning from the data, potentially improving its accuracy as it trains on more examples. However, there is a risk of overfitting if epochs are increased too much.
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