Pythia: Interpreting Autoregressive Transformers Across Time and Scale

This repository is for EleutherAI's work-in-progress project Pythia which combines interpretability analysis and scaling laws to understand how knowledge develops and evolves during training in autoregressive transformers.

Models

Params	n_layers	d_model	n_heads	d_head	Batch Size	Learning Rate	Checkpoints	Evaluations
Pythia-19M	6	512	8	64	2M	1e-3	Ready	Ready
Pythia-19M-Deduped	6	512	8	64	2M	1e-3	Ready
Pythia-125M	12	768	12	64	4M	6e-4	Ready	In-Progress
Pythia-125M-Deduped	12	768	12	64	4M	6e-4	Ready	---------------
Pythia-350M	24	1024	16	64	4M	3e-4	Ready	---------------
Pythia-350M-Deduped	24	1024	16	64	4M	3e-4	Ready	---------------
Pythia-800M	16	2048	8	128	4M	3e-4	Ready	Ready
Pythia-800M-Deduped	16	2048	8	128	4M	3e-4	Ready	Ready
Pythia-1.3B	24	2048	16	128	4M	2e-4	Ready	Ready
Pythia-1.3B-Deduped	24	2048	16	128	4M	2e-4	Ready	Ready
Pythia-2.7B	32	2560	32	80	2M	1.6e-4	Ready	Ready
Pythia-2.7B-Deduped	32	2560	32	80	2M	1.6e-4	Ready	Ready
Pythia-6.7B	32	4096	32	128	2M	1.2e-4 ?	Ready	Ready
Pythia-6.7B-Deduped	32	4096	32	128	2M	1.2e-4 ?	Ready	Ready
Pythia-13B	36	5120	40	128	2M	1.2e-4	Ready	---------------
Pythia-13B-Deduped	36	5120	40	128	2M	1.2e-4	Ready	---------------

s3://pythia-hf/ contains the checkpoints that are converted to HF format.

TODO: add instructions for downloading a HF model from where they're hosted for very easy access to the intermediate ckpts

TODO: link to configs from table?

Experiments

Grammar Learning Trajectories of Language Models

Training Order and Memorization

A common explanation for language model training dynamics is that LMs have a mass of knowledge and when they come across new information they glom that knowledge on and slowly integrate it into the mass over time. One prediction that this mental model makes is that tokens encountered later in training will be more likely to be memorized than ones encountered earlier in training, as the model will not have time to adjust its representations to store the info without memorization. The primary goal of this experiment is to disprove this prediction.