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IFM/K2Datasets

K2 Dataset Card The following data mix was used to train K2 and achieve results in line with Llama 2 70B. Dataset Details K2 was trained on 1.4T tokens across two stages. The data sources and data mix for each stage are listed below. Dataset Description: Stage 1 Dataset Starting Tokens Multiplier Total Tokens % of Total dm-math 4.33B 3x 13B 1% pubmed-abstracts (from the Pile) 4.77B 3x 14.3B 1.1% uspto (from the Pile) 4.77B 3x… See the full description on the dataset page: https://huggingface.co/datasets/IFM/K2Datasets.

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Dataset Card

K2 Dataset Card

<!-- Provide a quick summary of the dataset. -->

The following data mix was used to train K2 and achieve results in line with Llama 2 70B.

Dataset Details

K2 was trained on 1.4T tokens across two stages. The data sources and data mix for each stage are listed below.

Dataset Description: Stage 1

<!-- Provide a longer summary of what this dataset is. -->

DatasetStarting TokensMultiplierTotal Tokens% of Total
dm-math4.33B3x13B1%
pubmed-abstracts (from the Pile)4.77B3x14.3B1.1%
uspto (from the Pile)4.77B3x14.3B1.1%
pubmed-central (from the Pile)26B1x26B2%
redpajama.arxiv27.3B1x27.3B2.1%
starcoder.spm67.6B0.5x33.8B2.6%
starcoder.fim67.6B0.5x33.8B2.6%
redpajama.stackexchange61.1B1x61.1B4.7%
starcoder132.6B0.5x66.3B5.1%
pile-of-law76.7B1x76.7B5.9%
redpajama.book80.6B1x80.6B6.2%
s2orc107.9B1x107.9B8.3%
redpajama.wikipedia22.1B6x132.6B10.2%
refinedweb612.3B1x612.3B47.1%
Totals--1.3T100%

Dataset Description: Stage 2

DatasetStarting TokensMultiplierTotal Tokens% of Total
open-web-math14.6B1x14.6B21%
redpajama.arxiv2B1x2B2.9%
simple-wiki4.3B1x4.3B6.2%
redpajama.book2B1x2B2.9%
algebraic-stack10.9B1x10.9B15.7%
pile-of-law2B0.5x33.8B2.9%
books5.8B1x5.8B8.3%
pes201.2B1x1.2B1.8%
pubmed-central (from the Pile)2B1x2B2.9%
redpajama.wikipedia2B1x2B2.9%
python20.5B1x20.5B29.6%
s2orc2B1x2B2.9%
Totals--69.4B*100%

*rounding

Data Collection and Processing

<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->

A step-by-step tutorial for reproducing the K2's data preperation can be found in the LLM360 Pretraining Suite here

Bias, Risks, and Limitations

<!-- This section is meant to convey both technical and sociotechnical limitations. -->

Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.

Citation

BibTeX:

bibtex
@misc{
      title={LLM360 K2-65B: Scaling Up Open and Transparent Language Models}, 
      author={The LLM360 Team},
      year={2024},
}