batch size training

Batch size training is a way of training a computer model with a large dataset by splitting it into smaller groups of data. This helps a computer model to process the large dataset more quickly and accurately. Think of it like if you want to learn about a lot of different animals, like cats, dogs, and fish. Instead of trying to read about all of them at once, you could split them up into smaller groups and learn about one group at a time. That's what batch size training does - it splits up the data so the computer can deal with it more easily.