--- language: - en license: apache-2.0 library_name: transformers tags: - mergekit - merge base_model: - chargoddard/prometheus-llama-3-8b-preference - chargoddard/prometheus-llama-3-8b-absolute datasets: - prometheus-eval/Preference-Collection - prometheus-eval/Feedback-Collection model-index: - name: prometheus-2-llama-3-8b results: - task: type: text-generation name: Text Generation dataset: name: IFEval (0-Shot) type: HuggingFaceH4/ifeval args: num_few_shot: 0 metrics: - type: inst_level_strict_acc and prompt_level_strict_acc value: 52.89 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=chargoddard/prometheus-2-llama-3-8b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: BBH (3-Shot) type: BBH args: num_few_shot: 3 metrics: - type: acc_norm value: 27.8 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=chargoddard/prometheus-2-llama-3-8b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MATH Lvl 5 (4-Shot) type: hendrycks/competition_math args: num_few_shot: 4 metrics: - type: exact_match value: 7.25 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=chargoddard/prometheus-2-llama-3-8b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GPQA (0-shot) type: Idavidrein/gpqa args: num_few_shot: 0 metrics: - type: acc_norm value: 3.02 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=chargoddard/prometheus-2-llama-3-8b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MuSR (0-shot) type: TAUR-Lab/MuSR args: num_few_shot: 0 metrics: - type: acc_norm value: 0.78 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=chargoddard/prometheus-2-llama-3-8b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MMLU-PRO (5-shot) type: TIGER-Lab/MMLU-Pro config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 23.19 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=chargoddard/prometheus-2-llama-3-8b name: Open LLM Leaderboard --- # prometheus-2-llama-3-8b Replication of [prometheus-7b-v2.0](https://huggingface.co/prometheus-eval/prometheus-7b-v2.0) using [Llama 3 8B Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) as a base model. As in their paper, two different models were trained on their preference and feedback datasets then linearly merged at equal weight. Training hyperparameters: * 1 epoch * Learning rate 1e-5 * Effective batch size 128 * Cosine annealing * ~5% warmup Uses Llama 3 Instruct prompt format and the same prompts as prometheus-7b-v2.0. See that readme for info. # Citations ```bibtex @misc{kim2023prometheus, title={Prometheus: Inducing Fine-grained Evaluation Capability in Language Models}, author={Seungone Kim and Jamin Shin and Yejin Cho and Joel Jang and Shayne Longpre and Hwaran Lee and Sangdoo Yun and Seongjin Shin and Sungdong Kim and James Thorne and Minjoon Seo}, year={2023}, eprint={2310.08491}, archivePrefix={arXiv}, primaryClass={cs.CL} } ``` ```bibtex @misc{kim2024prometheus, title={Prometheus 2: An Open Source Language Model Specialized in Evaluating Other Language Models}, author={Seungone Kim and Juyoung Suk and Shayne Longpre and Bill Yuchen Lin and Jamin Shin and Sean Welleck and Graham Neubig and Moontae Lee and Kyungjae Lee and Minjoon Seo}, year={2024}, eprint={2405.01535}, archivePrefix={arXiv}, primaryClass={cs.CL} } ``` # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_chargoddard__prometheus-2-llama-3-8b) | Metric |Value| |-------------------|----:| |Avg. |19.16| |IFEval (0-Shot) |52.89| |BBH (3-Shot) |27.80| |MATH Lvl 5 (4-Shot)| 7.25| |GPQA (0-shot) | 3.02| |MuSR (0-shot) | 0.78| |MMLU-PRO (5-shot) |23.19|