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Commit 7a76696e authored by haileyschoelkopf's avatar haileyschoelkopf
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push unscramble

parent d93a96b4
# Unscramble
### Paper
Language Models are Few-Shot Learners
https://arxiv.org/pdf/2005.14165.pdf
Unscramble is a small battery of 5 “character manipulation” tasks. Each task
involves giving the model a word distorted by some combination of scrambling,
addition, or deletion of characters, and asking it to recover the original word.
Homepage: https://github.com/openai/gpt-3/tree/master/data
### Citation
```
@inproceedings{NEURIPS2020_1457c0d6,
author = {Brown, Tom and Mann, Benjamin and Ryder, Nick and Subbiah, Melanie and Kaplan, Jared D and Dhariwal, Prafulla and Neelakantan, Arvind and Shyam, Pranav and Sastry, Girish and Askell, Amanda and Agarwal, Sandhini and Herbert-Voss, Ariel and Krueger, Gretchen and Henighan, Tom and Child, Rewon and Ramesh, Aditya and Ziegler, Daniel and Wu, Jeffrey and Winter, Clemens and Hesse, Chris and Chen, Mark and Sigler, Eric and Litwin, Mateusz and Gray, Scott and Chess, Benjamin and Clark, Jack and Berner, Christopher and McCandlish, Sam and Radford, Alec and Sutskever, Ilya and Amodei, Dario},
booktitle = {Advances in Neural Information Processing Systems},
editor = {H. Larochelle and M. Ranzato and R. Hadsell and M. F. Balcan and H. Lin},
pages = {1877--1901},
publisher = {Curran Associates, Inc.},
title = {Language Models are Few-Shot Learners},
url = {https://proceedings.neurips.cc/paper/2020/file/1457c0d6bfcb4967418bfb8ac142f64a-Paper.pdf},
volume = {33},
year = {2020}
}
```
### Subtasks
* `anagrams1` - Anagrams of all but the first and last letter.
* `anagrams2` - Anagrams of all but the first and last 2 letters.
* `cycle_letters` - Cycle letters in a word.
* `random_insertion` - Random insertions in the word that must be removed.
* `reversed_words` - Words spelled backwards that must be reversed.
### Checklist
For adding novel benchmarks/datasets to the library:
* [x] Is the task an existing benchmark in the literature?
* [x] Have you referenced the original paper that introduced the task?
* [x] If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test?
If other tasks on this dataset are already supported:
* [x] Is the "Main" variant of this task clearly denoted?
* [x] Have you provided a short sentence in a README on what each new variant adds / evaluates?
* [x] Have you noted which, if any, published evaluation setups are matched by this variant?
* [x] Checked for equivalence with v0.3.0 LM Evaluation Harness
group:
- greedy_until
task: anagrams1
dataset_path: EleutherAI/unscramble
dataset_name: mid_word_1_anagrams
output_type: greedy_until
test_split: validation
doc_to_text: "{{context}}"
doc_to_target: "{{completion}}"
generation_kwargs:
until:
- "\n"
metric_list:
- metric: exact_match
aggregation: mean
higher_is_better: true
ignore_case: false
ignore_punctuation: false
group:
- greedy_until
task: anagrams2
dataset_path: EleutherAI/unscramble
dataset_name: mid_word_2_anagrams
output_type: greedy_until
test_split: validation
doc_to_text: "{{context}}"
doc_to_target: "{{completion}}"
generation_kwargs:
until:
- "\n"
metric_list:
- metric: exact_match
aggregation: mean
higher_is_better: true
ignore_case: false
ignore_punctuation: false
group:
- greedy_until
task: cycle_letters
dataset_path: EleutherAI/unscramble
dataset_name: cycle_letters_in_word
output_type: greedy_until
test_split: validation
doc_to_text: "{{context}}"
doc_to_target: "{{completion}}"
generation_kwargs:
until:
- "\n"
metric_list:
- metric: exact_match
aggregation: mean
higher_is_better: true
ignore_case: false
ignore_punctuation: false
group:
- greedy_until
task: random_insertion
dataset_path: EleutherAI/unscramble
dataset_name: random_insertion_in_word
output_type: greedy_until
test_split: validation
doc_to_text: "{{context}}"
doc_to_target: "{{completion}}"
generation_kwargs:
until:
- "\n"
metric_list:
- metric: exact_match
aggregation: mean
higher_is_better: true
ignore_case: false
ignore_punctuation: false
group:
- greedy_until
task: reversed_words
dataset_path: EleutherAI/unscramble
dataset_name: reversed_words
output_type: greedy_until
test_split: validation
doc_to_text: "{{context}}"
doc_to_target: "{{completion}}"
generation_kwargs:
until:
- "\n"
metric_list:
- metric: exact_match
aggregation: mean
higher_is_better: true
ignore_case: false
ignore_punctuation: false
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