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--- |
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license: mit |
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dataset_info: |
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- config_name: algebra__polynomial_roots |
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- config_name: arithmetic__add_or_sub |
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- config_name: calculus__differentiate |
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- config_name: polynomials__add |
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num_bytes: 1275 |
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num_examples: 9 |
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- name: test |
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num_bytes: 1314 |
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num_examples: 10 |
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download_size: 98096 |
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dataset_size: 2589 |
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- config_name: polynomials__evaluate |
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features: |
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- name: question |
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dtype: string |
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- name: answer |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 625 |
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num_examples: 9 |
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- name: test |
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num_bytes: 706 |
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num_examples: 10 |
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download_size: 98096 |
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dataset_size: 1331 |
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- config_name: polynomials__evaluate_composed |
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features: |
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- name: question |
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dtype: string |
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- name: answer |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 1193 |
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num_examples: 9 |
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- name: test |
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num_bytes: 1492 |
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num_examples: 10 |
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download_size: 98096 |
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dataset_size: 2685 |
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- config_name: polynomials__expand |
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features: |
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- name: question |
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dtype: string |
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- name: answer |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 913 |
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num_examples: 9 |
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- name: test |
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num_bytes: 1014 |
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num_examples: 10 |
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download_size: 98096 |
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dataset_size: 1927 |
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- config_name: polynomials__simplify_power |
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features: |
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- name: question |
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dtype: string |
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- name: answer |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 1155 |
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num_examples: 9 |
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- name: test |
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num_bytes: 1481 |
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num_examples: 10 |
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download_size: 98096 |
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dataset_size: 2636 |
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- config_name: probability__swr_p_level_set |
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features: |
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- name: question |
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dtype: string |
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- name: answer |
|
dtype: string |
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splits: |
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- name: train |
|
num_bytes: 1541 |
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num_examples: 9 |
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- name: test |
|
num_bytes: 1766 |
|
num_examples: 10 |
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download_size: 98096 |
|
dataset_size: 3307 |
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- config_name: probability__swr_p_sequence |
|
features: |
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- name: question |
|
dtype: string |
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- name: answer |
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dtype: string |
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splits: |
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- name: train |
|
num_bytes: 1619 |
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num_examples: 9 |
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- name: test |
|
num_bytes: 1781 |
|
num_examples: 10 |
|
download_size: 98096 |
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dataset_size: 3400 |
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--- |
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|
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|
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To run generation code within 'mathematics_dataset\mathematics_dataset\': |
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- Activate python venv ``` .\.venv\Scripts\activate ``` |
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- Requirements defined in requires.txt |
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- Run ```python generate_to_file.py --output_dir ds``` to generate dataset to directory \ds |
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|
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Had to change enconding when opening files to utf-8 so that some characters are allowed (ã õ é) |
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|
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To obtain dataset with the correct amount of rows: |
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- python ```generate_to_file.py --output_dir ds --per_train_module 1999998 --per_test_module 10000``` |
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|
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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 |
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from the train questions") tests. |
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On HugginFace only interpolate tests are used as test set. |
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|
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Some tests will not work, since they rely on english terms. |
