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Early stopping: Difference between revisions
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==How does early stopping work?== | ==How does early stopping work?== | ||
Early stopping occurs by comparing the performance of a model on both the [[training set]] and validation set during training. The validation set is an omitted portion of data from the training set that allows us to assess its suitability for unseen data. As the model learns on this set, its performance on the validation set is monitored at regular intervals; if | Early stopping occurs by comparing the performance of a model on both the [[training set]] and validation set during training. The validation set is an omitted portion of data from the training set that allows us to assess its suitability for unseen data. As the model learns on this set, its performance on the validation set is monitored at regular intervals; if [[validation loss]] starts to increase, then training is stopped and the model with the best [[validation]] performance is selected as the final model. | ||
Early stopping can be implemented using various criteria, such as monitoring validation loss or [[accuracy]]. The criteria used to terminate training can be set based on domain knowledge or determined empirically through experimentation. One popular approach involves using a [[patience]] [[parameter]] which controls how many [[epoch]]s of training may continue without improvement in validation performance. If after these specified number of epochs have passed without improvement in validation performance, training is then terminated. | Early stopping can be implemented using various criteria, such as monitoring validation loss or [[accuracy]]. The criteria used to terminate training can be set based on domain knowledge or determined empirically through experimentation. One popular approach involves using a [[patience]] [[parameter]] which controls how many [[epoch]]s of training may continue without improvement in validation performance. If after these specified number of epochs have passed without improvement in validation performance, training is then terminated. | ||