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If a dataset contains many label errors, what impact is most likely to occur on a machine learning model's training?
①Learning always speeds up.
②The model's generalization performance will always improve.
③The loss converges to zero more quickly.
④There will no longer be a need for data augmentation.
⑤The accuracy of the trained model decreases, making it vulnerable to noise.