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README.md

@@ -1,181 +1,41 @@
----
-license: mit
-task_categories:
-- text-generation
-language:
-- en
-tags:
-- mathematics
-- group-theory
-- permutations
-- symbolic-reasoning
-pretty_name: Permutation Groups Dataset
-size_categories:
-- 100K<n<1M
-configs:
-- config_name: s3_data
-  data_files:
-    - split: train
-      path: data/s3_data/train/*
-    - split: test
-      path: data/s3_data/test/*
-- config_name: s4_data
-  data_files:
-    - split: train
-      path: data/s4_data/train/*
-    - split: test
-      path: data/s4_data/test/*
-- config_name: s5_data
-  data_files:
-    - split: train
-      path: data/s5_data/train/*
-    - split: test
-      path: data/s5_data/test/*
-- config_name: s6_data
-  data_files:
-    - split: train
-      path: data/s6_data/train/*
-    - split: test
-      path: data/s6_data/test/*
-- config_name: s7_data
-  data_files:
-    - split: train
-      path: data/s7_data/train/*
-    - split: test
-      path: data/s7_data/test/*
-- config_name: a3_data
-  data_files:
-    - split: train
-      path: data/a3_data/train/*
-    - split: test
-      path: data/a3_data/test/*
-- config_name: a4_data
-  data_files:
-    - split: train
-      path: data/a4_data/train/*
-    - split: test
-      path: data/a4_data/test/*
-- config_name: a5_data
-  data_files:
-    - split: train
-      path: data/a5_data/train/*
-    - split: test
-      path: data/a5_data/test/*
-- config_name: a6_data
-  data_files:
-    - split: train
-      path: data/a6_data/train/*
-    - split: test
-      path: data/a6_data/test/*
-- config_name: a7_data
-  data_files:
-    - split: train
-      path: data/a7_data/train/*
-    - split: test
-      path: data/a7_data/test/*
----
+# Permutation Groups Datasets
 
-# Permutation Groups Dataset
-
-A comprehensive collection of permutation composition datasets for symmetric and alternating groups, designed for training and evaluating models on group theory operations.
-
-## Dataset Description
-
-This dataset contains permutation composition problems for various mathematical groups:
-- **Symmetric Groups**: S3, S4, S5, S6, S7
-- **Alternating Groups**: A3, A4, A5, A6, A7
-
-Each dataset consists of sequences of permutations that need to be composed to produce a target permutation. This is useful for:
-- Training models on symbolic reasoning
-- Evaluating mathematical understanding
-- Testing compositional generalization
-- Studying group theory properties in neural networks
+This repository contains permutation composition datasets for various symmetric and alternating groups.
 
 ## Usage
 
+You can load individual datasets or all datasets combined:
+
 ```python
 from datasets import load_dataset
 
-# Load a specific group dataset
-s5_dataset = load_dataset("BeeGass/permutation-groups", name="s5_data", trust_remote_code=True)
-
-# Load alternating group A5
-a5_dataset = load_dataset("BeeGass/permutation-groups", name="a5_data", trust_remote_code=True)
+# Load a specific dataset
+s3_dataset = load_dataset("BeeGass/permutation-groups", name="s3_data", trust_remote_code=True)
+s7_dataset = load_dataset("BeeGass/permutation-groups", name="s7_data", trust_remote_code=True)
+a7_dataset = load_dataset("BeeGass/permutation-groups", name="a7_data", trust_remote_code=True)
 
 # Load all datasets combined
 all_datasets = load_dataset("BeeGass/permutation-groups", name="all", trust_remote_code=True)
-
-# Access the data
-train_data = s5_dataset["train"]
-test_data = s5_dataset["test"]
-
-# Example data point
-print(train_data[0])
-# {'input_sequence': '23 45 12', 'target': '67'}
 ```
 
-## Dataset Structure
-
-Each example contains:
-- `input_sequence`: A space-separated sequence of permutation IDs to be composed
-- `target`: The ID of the resulting permutation after composition
-
-The composition follows standard mathematical convention: for input `[p1, p2, p3]`, the result is `p3 ∘ p2 ∘ p1`.
-
 ## Available Configurations
 
-| Configuration | Group Type | Group Order | Elements | Train Samples | Test Samples |
-|--------------|------------|-------------|----------|---------------|--------------|
-| `s3_data` | Symmetric | S3 | 6 | 8,000 | 2,000 |
-| `s4_data` | Symmetric | S4 | 24 | 16,000 | 4,000 |
-| `s5_data` | Symmetric | S5 | 120 | 40,000 | 10,000 |
-| `s6_data` | Symmetric | S6 | 720 | 80,000 | 20,000 |
-| `s7_data` | Symmetric | S7 | 5,040 | 160,000 | 40,000 |
-| `a3_data` | Alternating | A3 | 3 | 4,000 | 1,000 |
-| `a4_data` | Alternating | A4 | 12 | 12,000 | 3,000 |
-| `a5_data` | Alternating | A5 | 60 | 24,000 | 6,000 |
-| `a6_data` | Alternating | A6 | 360 | 64,000 | 16,000 |
-| `a7_data` | Alternating | A7 | 2,520 | 120,000 | 30,000 |
-| `all` | Combined | - | - | 528,000 | 132,000 |
+- `s3_data`: Symmetric Group S3
+- `s4_data`: Symmetric Group S4
+- `s5_data`: Symmetric Group S5
+- `s6_data`: Symmetric Group S6
+- `s7_data`: Symmetric Group S7
+- `a5_data`: Alternating Group A5
+- `a6_data`: Alternating Group A6
+- `a7_data`: Alternating Group A7
+- `all`: All datasets combined
 
-## Dataset Features
-
-- **Variable sequence length**: Input sequences range from 3 to 512 permutations
-- **Consistent formatting**: All permutations use space-separated integer IDs
-- **Metadata included**: Each dataset includes a `metadata.json` file mapping IDs to permutation array forms
-- **Train/test split**: 80/20 split for all configurations
-
-## Understanding the Data
-
-Each permutation is represented by a unique integer ID. The `metadata.json` file in each dataset folder provides the mapping from IDs to permutation array forms.
-
-For example, in S3:
-- ID 0 might map to `[0, 1, 2]` (identity)
-- ID 1 might map to `[0, 2, 1]` (transpose elements 1 and 2)
-- etc.
-
-## Citation
-
-If you use this dataset in your research, please cite:
-
-```bibtex
-@software{permutation_groups_dataset,
-  author = {Bryan Gass},
-  title = {Permutation Groups Dataset},
-  year = {2024},
-  publisher = {Hugging Face},
-  url = {https://huggingface.co/datasets/BeeGass/permutation-groups}
-}
-```
-
-## Acknowledgments
+## Dataset Structure
 
-This dataset was inspired by the work of [William Merrill](https://github.com/viking-sudo-rm) and his paper ["The Illusion of State in State-Space Models"](https://arxiv.org/abs/2404.08819), which explores the computational properties of state-space models through group theory.
+Each dataset contains:
+- `input_sequence`: Space-separated sequence of permutation IDs
+- `target`: The ID of the composed permutation
 
 ## License
 
-This dataset is released under the MIT License.
-
-## Contact
-
-For questions or issues, please open an issue on the [GitHub repository](https://github.com/BeeGass/permutation-groups).
+MIT