---
language:
  - en
library_name: pytorch
tags:
  - language-model
  - gpt2
  - transformer
  - wikitext-103

model-index:

- name: gpt2_wt103-40m_12-layer
  results:
  - task:
      type: language-modeling
    dataset:
      type: wikitext
      name: Wikitext-103
    metrics:
      - type: perplexity
        value: 40.3 
    
---

# Model description

paper: [Characterizing Verbatim Short-Term Memory in Neural Language Models](https://doi.org/10.48550/arXiv.2210.13569)

This is a gpt2-small-like decoder-only transformer model trained on a 40M token subset of the [wikitext-103 dataset](https://paperswithcode.com/dataset/wikitext-103).

# Intended uses

This checkpoint is intended for research purposes, for example those interested in studying the behavior of transformer language models trained on smaller datasets.