More Data Cannot Repair a Model That Still Underfits
If a model is still unable to reach the desired error level on its current training set, simply collecting additional labeled examples will not by itself push development error down to that target. As the training set grows, training error does not improve from the extra data alone and may remain unchanged or become slightly worse. In typical cases, development error is also above training error.
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