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metadata
license: apache-2.0
language:
  - en
pipeline_tag: text-generation
library_name: transformers
tags:
  - nlp
  - llm

K2: a Fully Transparent OSS Reproduction of Llama 2 Performance Using 35% Less Data

LLM360 demystifies the data recipe used for Llama 2 - 70B with K2. While K2’s performance deviates slightly from Llama’s, the scores share enough similarities to provide insight into the potential characteristics of training datasets used for Llama 2.

Evaluations

eval table

Datasets and Mix

The following data mix was used to train K2 and achieve results in line with Llama 2 70B. The full data sequence will be available soon.

Dataset Starting Tokens Multiplier Total Tokens % of Total
dm-math 4.33B 3x 13B 1%
pubmed-abstracts 4.77B 3x 14.3B 1.1%
uspto 4.77B 3x 14.3B 1.1%
pubmed-central 26B 1x 26B 2%
redpajama.arxiv 27.3B 1x 27.3B 2.1%
starcoder.spm 67.6B 0.5x 33.8B 2.6%
starcoder.fim 67.6B 0.5x 33.8B 2.6%
redpajama.stackexchange 61.1B 1x 61.1B 4.7%
starcoder 132.6B 0.5x 66.3B 5.1%
pile-of-law 76.7B 1x 76.7B 5.9%
redpajama.book 80.6B 1x 80.6B 6.2%
s2orc 107.9B 1x 107.9B 8.3%
redpajama.wikipedia 22.1B 6x 132.6B 10.2%
refinedweb 612.3B 1x 612.3B 47.1%
Totals - - 1.3T 100%

First 10 Checkpoints

Additional Artifacts

We are working on release caliber artifacts for the dataset, code, and analysis which will be released over the next few weeks.

Model Description

  • Model type: 65 billion parameter language model with the same architecture as LLaMA.
  • Language(s) (NLP): English
  • License: Apache 2.0
  • Resources for more information:
    • Training Code: TBD
    • Data Preparation: TBD
    • Metrics: TBD
    • Fully processed K2 pretraining dataset: TBD

About LLM360

LLM360 is an initiative for comprehensive and fully open-sourced LLMs, where all training details, model checkpoints, intermediate results, and additional analyses are made available to the community. Our goal is to advance the field by inviting the community to deepen the understanding of LLMs together. As the first step of the project LLM360, we release all intermediate model checkpoints, our fully-prepared pre-training dataset, all source code and configurations, and training details. We are committed to continually pushing the boundaries of LLMs through this open-source effort.

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