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--- |
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license: mit |
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dataset_info: |
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features: |
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- name: clean |
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dtype: string |
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- name: corrupted |
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dtype: string |
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- name: year |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 1234280 |
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num_examples: 10000 |
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download_size: 204638 |
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dataset_size: 1234280 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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language: |
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- en |
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--- |
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# Dataset Card for Dataset Name |
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<!-- Provide a quick summary of the dataset. --> |
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This is a dataset with examples from the Greater-Than circuit task. |
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## Dataset Details |
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### Dataset Description |
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<!-- Provide a longer summary of what this dataset is. --> |
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- **Curated by:** Michael Hanna |
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- **Language(s) (NLP):** English |
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- **License:** MIT |
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### Dataset Sources |
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<!-- Provide the basic links for the dataset. --> |
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- **Repository:** [https://github.com/hannamw/gpt2-greater-than](https://github.com/hannamw/gpt2-greater-than) |
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- **Paper:** [How does GPT-2 compute greater-than?: Interpreting mathematical abilities in a pre-trained language model](https://openreview.net/forum?id=p4PckNQR8k) |
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## Uses |
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This dataset is intended to be a model-agnostic version of the greater-than task. |
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The original task consisted of examples like `The war lasted from the year 1742 to the year 17`, based on the fact that GPT-2 small tokenizes 4-digit years into two, two-digit tokens. |
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One would then compute model performance as the probability assigned to years greater than 42, minus that assigned to years less-than or equal to 42. |
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New models now tokenize years differently; Llama tokenizes 1742 as `[174][2]`, and Gemma 2 tokenizes it as `[1][7][4][2]`. |
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You can still compute the probability assigned to good and bad decades; for example: |
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- For Llama 3, if the token at position [174] is y1, and the token at [2] is y1, you want to compute p(y1>174) + p(y1=174)* p(y2>2) - (p(y1<174) + p(y1=174)* p(y2<=2)) |
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- For Gemma 2, if the token at position [4] is y1, and the token at [2] is y1, you want to compute p(y1>4) + p(y1=4)* p(y2>2) - (p(y1<4) + p(y1=4)* p(y2<=2)) |
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For these purposes, it's easier to have the full string, i.e. `The war lasted from the year 1742 to the year 1743`, rather than the shortened version `The war lasted from the year 1742 to the year 17`. |
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## Dataset Structure |
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`clean`: The original greater-than example sentences |
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`corrupted`: The corrupted version of the corresponding sentence in `clean`, with the start-year decade set to `01`. |
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`year`: The start year from the corresponding sentence in `clean`. |
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## Dataset Creation |
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### Source Data |
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As described in the paper, this dataset was automatically created, using the template `The [event] lasted from the year [XX][YY] to the year [XX]`. |
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Michael Hanna and Ollie Liu developed the list of nouns used as `[event]`. |
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## Citation [optional] |
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<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> |
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[How does GPT-2 compute greater-than?: Interpreting mathematical abilities in a pre-trained language model](https://openreview.net/forum?id=p4PckNQR8k) |
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**BibTeX:** |
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``` |
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@inproceedings{ |
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hanna2023how, |
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title={How does {GPT}-2 compute greater-than?: Interpreting mathematical abilities in a pre-trained language model}, |
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author={Michael Hanna and Ollie Liu and Alexandre Variengien}, |
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booktitle={Thirty-seventh Conference on Neural Information Processing Systems}, |
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year={2023}, |
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url={https://openreview.net/forum?id=p4PckNQR8k} |
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} |
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``` |
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## Dataset Card Authors |
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Michael Hanna |
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## Dataset Card Contact |
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m.w.hanna@uva.nl |
