Because in a smaller dataset, your validation data is more likely to look like your training data.

Because there isn't enough data to activate all the convolutions or neurons.

Because with less data,the training will take place more quickly,and some features may be missed.

Because there's less likelihood of all possible features being ecountered in the training process.