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--- |
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license: apache-2.0 |
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datasets: |
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- gair-prox/RedPajama-pro |
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language: |
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- en |
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tags: |
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- llama |
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--- |
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# RedPJ-ProX-1.7B |
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<p align="center"> |
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<img src="prox-teaser.png"> |
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</p> |
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[ArXiv](http://arxiv.org/abs/2409.17115) | [Models](https://huggingface.co/gair-prox/RedPJ-ProX-1.7B) | [Data](https://huggingface.co/datasets/gair-prox/RedPajama-pro) | [Code](https://github.com/GAIR-NLP/program-every-example) |
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**RedPJ-ProX-1.7B** is a small language model. It was and trained on the [RedPajama-V2-pro](https://huggingface.co/datasets/gair-prox/RedPajama-pro) for 50B tokens. |
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## Evaluations |
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ProX models are evaluated over 10 language model benchmarks in zero-shot setting. |
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| | ArC-c | ARC-e | CSQA | HellaS | MMLU | OBQA | PiQA | SIQA | WinoG | SciQ | AVG | |
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|-----------------------|-------|-------|-------|-----------|-------|-------|-------|-------|-------|-------|------| |
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| raw | 26.9 | 51.4 | 32.4 | 47.3 | 29.3 | 32.2 | 69.7 | 39.6 | 52.1 | 79.1 | 46.0 | |
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| ours | 31.1 | 60.7 | 29.8 | 51.0 | 31.7 | 33.2 | 70.9 | 39.2 | 53.3 | 79.1 | 48.0 | |
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### Citation |
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``` |
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@article{zhou2024programming, |
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title={Programming Every Example: Lifting Pre-training Data Quality like Experts at Scale}, |
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author={Zhou, Fan and Wang, Zengzhi and Liu, Qian and Li, Junlong and Liu, Pengfei}, |
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journal={arXiv preprint arXiv:2409.17115}, |
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year={2024} |
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} |
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``` |
