metadata
license: mit
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- config_name: algebra__polynomial_roots
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- config_name: arithmetic__nearest_integer_root
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- config_name: numbers__base_conversion
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- config_name: probability__swr_p_level_set
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To run generation code within 'mathematics_dataset\mathematics_dataset':
- Activate python venv
.\.venv\Scripts\activate- Requirements defined in requires.txt
- Run
python generate_to_file.py --output_dir dsto generate dataset to directory \ds
Had to change enconding when opening files to utf-8 so that some characters are allowed (ã õ é)
To obtain dataset with the correct amount of rows:
- python
generate_to_file.py --output_dir ds --per_train_module 1999998 --per_test_module 10000
This dataset creates train set (train-easy,train-medium,train-hard) and the creates extrapolation ("measure generalization along various axes of difficulty to beyond that seen during training") and interpolation ("test questions are distinct from the train questions") tests. On HugginFace only interpolate tests are used as test set.
Some tests will not work, since they rely on english terms.