Omkar2118/datasets huggingface dataset:
NMF
Full name: Named Mathematical Formulas

Mathematical dataset based on 71 famous mathematical identities. Each entry consists of a name of the identity (*name*), a representation of that identity (*formula*), a label whether the representation belongs to the identity (*label*), and an id of the mathematical identity (*formula_name_id*). 
The false pairs are intentionally challenging, e.g., `a^2+2^b=c^2`as falsified version of the Pythagorean Theorem. All entries have been generated by using [data.json](data.json) as starting point and applying the randomizing and falsifying algorithms from [MathMutator (MAMUT)](https://github.com/aieng-lab/math-mutator). The formulas in the dataset are not just pure mathematical, but contain also textual descriptions of the mathematical identity. At most 400000 versions are generated per identity. There are ten times more falsified versions than true ones, such that the dataset can be used for a training with changing false examples every epoch.

This dataset might be used to train a language model based math-retrieval system with a NSP-like task.

See also see [ddrg/math_formula_retrieval](https://huggingface.co/datasets/ddrg/math_formula_retrieval) as a derived dataset which associates two formulas.

Introducing paper: MAMUT: A Novel Framework for Modifying Mathematical Formulas for the Generation of Specialized Datasets for Language Model Training
Mathematical Formula Retrieval
Full name: MFR (Mathematical Formula Retrieval)

Mathematical dataset based on 71 famous mathematical identities. Each entry consists of two identities (in formula or textual form), together with a label, whether the two versions describe the same mathematical identity. The false pairs are not randomly chosen, but intentionally hard by modifying equivalent representations (see [ddrg/named_math_formulas](https://huggingface.co/datasets/ddrg/named_math_formulas) for more information). At most 400000 versions are generated per identity. There are ten times more falsified versions than true ones, such that the dataset can be used for a training with changing false examples every epoch.

Introducing paper: MAMUT: A Novel Framework for Modifying Mathematical Formulas for the Generation of Specialized Datasets for Language Model Training