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C4-ProX-1.7B

ArXiv | Models | Data | Code

C4-ProX-1.7B is a small language model. It was and trained on the C4-pro for 50B tokens.

Evaluations

ProX models are evaluated over 10 language model benchmarks in zero-shot setting.

ArC-c ARC-e CSQA HellaS MMLU OBQA PiQA SIQA WinoG SciQ AVG
raw 25.3 48.8 30.1 52.4 28.8 32.2 72.0 40.6 53.6 71.7 45.5
ours 31.1 56.0 28.4 55.2 31.1 36.2 74.0 41.0 54.1 76.8 48.4

Citation

@article{zhou2024programming,
  title={Programming Every Example: Lifting Pre-training Data Quality like Experts at Scale},
  author={Zhou, Fan and Wang, Zengzhi and Liu, Qian and Li, Junlong and Liu, Pengfei},
  journal={arXiv preprint arXiv:2409.17115},
  year={2024}
}
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Dataset used to train gair-prox/C4-ProX-1.7B

Collection including gair-prox/C4-ProX-1.7B