dataset_info:
features:
- name: instruction
dtype: string
- name: output
dtype: string
splits:
- name: train
num_bytes: 15268888.05
num_examples: 487500
- name: test
num_bytes: 391509.95
num_examples: 12500
download_size: 12160789
dataset_size: 15660398
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
tags:
- math
Simple Math
Just like my teacher gave me homework, i thought maybe we can also add some of these basics on the trainings of our models.
It was created with very simple code that is in the repo, if you add more complex operations and so.. please share the code :D thank you
Note to contributors: thank you to those contributing on the experiment with beautiful commits and good spirit
The model needs some splits
The complexity has to be gradual as show in experiments
Feel free to contribute on the readme Evaluation tests.
Lets aim to build an ablation & paper together. All contributors will be cited.
Add your log entry on the version so we can keep a track, thanks.
Versions
24.01.24 Added gradual complexity on a separate script 20-23.01.24 Multiple contributions with operations and increased complexity on the main generator script.
If you use Simple Math o train your model, please cite on the modelcard or the paper. Thank you