Memorization Without Overfitting: Analyzing the Training Dynamics of Large Language Models

05/22/2022
by   Kushal Tirumala, et al.
9

Despite their wide adoption, the underlying training and memorization dynamics of very large language models is not well understood. We empirically study exact memorization in causal and masked language modeling, across model sizes and throughout the training process. We measure the effects of dataset size, learning rate, and model size on memorization, finding that larger language models memorize training data faster across all settings. Surprisingly, we show that larger models can memorize a larger portion of the data before over-fitting and tend to forget less throughout the training process. We also analyze the memorization dynamics of different parts of speech and find that models memorize nouns and numbers first; we hypothesize and provide empirical evidence that nouns and numbers act as a unique identifier for memorizing individual training examples. Together, these findings present another piece of the broader puzzle of trying to understand what actually improves as models get bigger.

READ FULL TEXT

page 1

page 2

page 3

page 4

12/14/2020

Extracting Training Data from Large Language Models

It has become common to publish large (billion parameter) language model...
05/04/2022

Provably Confidential Language Modelling

Large language models are shown to memorize privacy information such as ...
10/26/2020

Word Frequency Does Not Predict Grammatical Knowledge in Language Models

Neural language models learn, to varying degrees of accuracy, the gramma...
02/05/2020

Aligning the Pretraining and Finetuning Objectives of Language Models

We demonstrate that explicitly aligning the pretraining objectives to th...
04/13/2021

Large-Scale Contextualised Language Modelling for Norwegian

We present the ongoing NorLM initiative to support the creation and use ...
03/11/2019

Partially Shuffling the Training Data to Improve Language Models

Although SGD requires shuffling the training data between epochs, curren...
03/11/2022

Staged Training for Transformer Language Models

The current standard approach to scaling transformer language models tra...