OpenMathInstruct-2 is a math instruction tuning dataset with 14M problem-solution pairs generated using the Llama3.1-405B-Instruct model.
Dataset Card
By NVIDIA, published under cc-by-4.0, revision 469216e3f46f.
OpenMathInstruct-2 is a math instruction tuning dataset with 14M problem-solution pairs generated using the Llama3.1-405B-Instruct model.
The training set problems of GSM8K and MATH are used for constructing the dataset in the following ways: - Solution augmentation: Generating chain-of-thought solutions for training set problems in GSM8K and MATH. - Problem-Solution augmentation: Generating new problems, followed by solutions for these new problems.
OpenMathInstruct-2 dataset contains the following fields:
- problem: Original problem from either the GSM8K or MATH training set or augmented problem from these training sets.
- generated_solution: Synthetically generated solution.
- expected_answer: For problems in the training set, it is the ground-truth answer provided in the datasets. For augmented problems, it is the majority-voting answer.
- problem_source: Whether the problem is taken directly from GSM8K or MATH or is an augmented version derived from either dataset.
Structure
default 21,972,791 rows
| Split | Rows | Size |
|---|---|---|
| train | 13,972,791 | 15.4 GB |
| train_1M | 1,000,000 | 1.3 GB |
| train_2M | 2,000,000 | 2.8 GB |
| train_5M | 5,000,000 | 6.5 GB |
Details
- Repository
- nvidia/OpenMathInstruct-2
- Publisher
- NVIDIA
- Task category
- Question answering
- Tags
- math, nvidia
- Size category
- 10M<n<100M
- Languages
- en
- Revision
- 469216e3f46f4dacf476b382e192485ea51a143e
- Last updated
- 2024-11-25
Files
59 files, 12.6 GB in total.
Every file
| File | Type | Size | SHA-256 |
|---|---|---|---|
| data/train-00000-of-00032.parquet | Data | 236.6 MB | 55bae5fa27c8 |
| data/train-00001-of-00032.parquet | Data | 236.9 MB | 4c1a2103a979 |
| data/train-00002-of-00032.parquet | Data | 236.6 MB | 29bd4017239b |
| data/train-00003-of-00032.parquet | Data | 236.8 MB | 619c696a8e43 |
| data/train-00004-of-00032.parquet | Data | 236.7 MB | e8d6d88a1cca |
| data/train-00005-of-00032.parquet | Data | 236.6 MB | 84781d52cab8 |
| data/train-00006-of-00032.parquet | Data | 236.8 MB | 85e196aac429 |
| data/train-00007-of-00032.parquet | Data | 236.8 MB | 279590a0ac58 |
| data/train-00008-of-00032.parquet | Data | 237.0 MB | bc6dbc7a97df |
| data/train-00009-of-00032.parquet | Data | 236.7 MB | fe38efc9a128 |
| data/train-00010-of-00032.parquet | Data | 237.0 MB | 574debcf9111 |
| data/train-00011-of-00032.parquet | Data | 237.0 MB | 750480cc24d2 |
| data/train-00012-of-00032.parquet | Data | 236.5 MB | 338117e09231 |
| data/train-00013-of-00032.parquet | Data | 236.7 MB | 363739df048e |
| data/train-00014-of-00032.parquet | Data | 236.7 MB | 9653648f9e65 |
| data/train-00015-of-00032.parquet | Data | 237.3 MB | 46aa107221b4 |
| data/train-00016-of-00032.parquet | Data | 236.8 MB | fc022c921698 |
| data/train-00017-of-00032.parquet | Data | 236.5 MB | 424a92182ed1 |
| data/train-00018-of-00032.parquet | Data | 236.7 MB | 57f3ce262c96 |
| data/train-00019-of-00032.parquet | Data | 236.5 MB | 9ff9798ed581 |
| data/train-00020-of-00032.parquet | Data | 236.8 MB | a9cbd3619965 |
| data/train-00021-of-00032.parquet | Data | 236.8 MB | 5f644f9d77b1 |
| data/train-00022-of-00032.parquet | Data | 236.8 MB | b546f1f094d8 |
| data/train-00023-of-00032.parquet | Data | 236.7 MB | 4ba1d104be88 |
| data/train-00024-of-00032.parquet | Data | 236.7 MB | dfbce7391b52 |
| data/train-00025-of-00032.parquet | Data | 236.9 MB | 08e7ebce1ecc |
| data/train-00026-of-00032.parquet | Data | 236.7 MB | 3e6545137ea2 |
| data/train-00027-of-00032.parquet | Data | 236.3 MB | 6d46ac4f285f |
| data/train-00028-of-00032.parquet | Data | 236.8 MB | b9378a52c74b |
| data/train-00029-of-00032.parquet | Data | 236.8 MB | 93aee9bae8fe |
| data/train-00030-of-00032.parquet | Data | 236.6 MB | 2191af67a930 |
| data/train-00031-of-00032.parquet | Data | 236.8 MB | b7fc689fb28a |
| data/train_1M-00000-of-00003.parquet | Data | 212.9 MB | 93700f39cdc8 |
| data/train_1M-00001-of-00003.parquet | Data | 213.2 MB | c208b3cda829 |
| data/train_1M-00002-of-00003.parquet | Data | 212.9 MB | 1a42cf7139b6 |
| data/train_2M-00000-of-00006.parquet | Data | 217.1 MB | 0e5070d547da |
| data/train_2M-00001-of-00006.parquet | Data | 217.0 MB | f535f5868188 |
| data/train_2M-00002-of-00006.parquet | Data | 216.9 MB | 3b9e9306db9e |
| data/train_2M-00003-of-00006.parquet | Data | 217.2 MB | 0b758d1e798f |
| data/train_2M-00004-of-00006.parquet | Data | 217.2 MB | 478feb390152 |
| data/train_2M-00005-of-00006.parquet | Data | 217.4 MB | cbec946a2d11 |
| data/train_5M-00000-of-00014.parquet | Data | 222.4 MB | b6c45a7eb504 |
| data/train_5M-00001-of-00014.parquet | Data | 222.1 MB | 73b9d40ac366 |
| data/train_5M-00002-of-00014.parquet | Data | 221.8 MB | 8313fde2b1cf |
| data/train_5M-00003-of-00014.parquet | Data | 221.9 MB | 2a5183be98b8 |
| data/train_5M-00004-of-00014.parquet | Data | 222.1 MB | 1e22f77711e0 |
| data/train_5M-00005-of-00014.parquet | Data | 222.0 MB | 69c9ea15ac79 |
| data/train_5M-00006-of-00014.parquet | Data | 222.3 MB | a293ab952250 |
| data/train_5M-00007-of-00014.parquet | Data | 222.6 MB | 5a4c2b9fe337 |
| data/train_5M-00008-of-00014.parquet | Data | 222.1 MB | 0b2d598714a1 |
| data/train_5M-00009-of-00014.parquet | Data | 222.4 MB | 7d07b4847af4 |
| data/train_5M-00010-of-00014.parquet | Data | 221.9 MB | 34168a7b268c |
| data/train_5M-00011-of-00014.parquet | Data | 222.3 MB | 7dc69d30990e |
| data/train_5M-00012-of-00014.parquet | Data | 222.4 MB | 3518f76d3d95 |
| data/train_5M-00013-of-00014.parquet | Data | 221.8 MB | 5c15c5617b51 |
| README.md | Documentation | 6.4 KB | — |
| SFT Data Diagram 1.jpg | Other | 269.0 KB | d9fa9ade48cb |
| scaling_plot.jpg | Other | 172.0 KB | dfccb18ebb30 |
| .gitattributes | Repository | 3.3 KB | — |
License and Download
- License
- cc-by-4.0
- Access
- No access gate
Released by NVIDIA through its official repository on Hugging Face. Read the license.
Models Trained on This Dataset
- Trained on (disclosed)FinAI