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--- |
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license: mit |
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language: |
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- en |
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--- |
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# LM Loss OPT RM |
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This is a fine tuned OPT 13b model for reward modelling. The finetuning has been done on top of the full [SLF5K](https://huggingface.co/datasets/JeremyAlain/SLF5K) dataset following the method presented in the paper [Training Language Models with Language Feedback at Scale](https://arxiv.org/abs/2303.16755). The main results can be seen in the following table: |
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| Model | # Params | Validation Accuracy (in %) | |
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|--------------------|-----------|-------------------| |
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| OPT LM Loss | 13B | **73.4 +/- 1.9** | |
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| OPT LM Loss | 1.3B | 69.6 +/- 2.0 | |
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| OPT RM Loss | 13B | 71.8 +/- 2.0 | |
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If using this model, please cite the following paper: |
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``` |
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@article{scheurer2023training, |
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title={Training Language Models with Language Feedback at Scale}, |
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author={Scheurer, J{\'e}r{\'e}my and Campos, Jon Ander and Korbak, Tomasz and Chan, Jun Shern and Chen, Angelica and Cho, Kyunghyun and Perez, Ethan}, |
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journal={arXiv preprint arXiv:2303.16755}, |
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year={2023} |
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} |
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``` |
