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--- |
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library_name: transformers |
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tags: |
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- mergekit |
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- merge |
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base_model: |
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- RozGrov/NemoDori-v0.2.2-12B-MN-ties |
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- spow12/ChatWaifu_v1.4 |
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- Nohobby/MN-12B-Siskin-v0.2 |
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- GalrionSoftworks/Canidori-12B-v1 |
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- ArliAI/Mistral-Nemo-12B-ArliAI-RPMax-v1.1 |
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model-index: |
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- name: MN-Chinofun |
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results: |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: IFEval (0-Shot) |
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type: HuggingFaceH4/ifeval |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: inst_level_strict_acc and prompt_level_strict_acc |
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value: 61.1 |
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name: strict accuracy |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=djuna/MN-Chinofun |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: BBH (3-Shot) |
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type: BBH |
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args: |
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num_few_shot: 3 |
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metrics: |
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- type: acc_norm |
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value: 28.48 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=djuna/MN-Chinofun |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MATH Lvl 5 (4-Shot) |
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type: hendrycks/competition_math |
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args: |
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num_few_shot: 4 |
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metrics: |
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- type: exact_match |
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value: 10.5 |
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name: exact match |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=djuna/MN-Chinofun |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: GPQA (0-shot) |
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type: Idavidrein/gpqa |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: acc_norm |
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value: 6.15 |
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name: acc_norm |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=djuna/MN-Chinofun |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MuSR (0-shot) |
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type: TAUR-Lab/MuSR |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: acc_norm |
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value: 10.38 |
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name: acc_norm |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=djuna/MN-Chinofun |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MMLU-PRO (5-shot) |
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type: TIGER-Lab/MMLU-Pro |
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config: main |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 28.92 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=djuna/MN-Chinofun |
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name: Open LLM Leaderboard |
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--- |
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# merge |
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit). |
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## Merge Details |
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### Merge Method |
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This model was merged using the [Model Stock](https://arxiv.org/abs/2403.19522) merge method using [ArliAI/Mistral-Nemo-12B-ArliAI-RPMax-v1.1](https://huggingface.co/ArliAI/Mistral-Nemo-12B-ArliAI-RPMax-v1.1) as a base. |
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### Models Merged |
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The following models were included in the merge: |
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* [RozGrov/NemoDori-v0.2.2-12B-MN-ties](https://huggingface.co/RozGrov/NemoDori-v0.2.2-12B-MN-ties) |
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* [spow12/ChatWaifu_v1.4](https://huggingface.co/spow12/ChatWaifu_v1.4) |
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* [Nohobby/MN-12B-Siskin-v0.2](https://huggingface.co/Nohobby/MN-12B-Siskin-v0.2) |
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* [GalrionSoftworks/Canidori-12B-v1](https://huggingface.co/GalrionSoftworks/Canidori-12B-v1) |
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### Configuration |
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The following YAML configuration was used to produce this model: |
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```yaml |
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models: |
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- model: Nohobby/MN-12B-Siskin-v0.2 |
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- model: spow12/ChatWaifu_v1.4 |
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- model: RozGrov/NemoDori-v0.2.2-12B-MN-ties |
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- model: GalrionSoftworks/Canidori-12B-v1 |
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merge_method: model_stock |
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base_model: ArliAI/Mistral-Nemo-12B-ArliAI-RPMax-v1.1 |
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dtype: bfloat16 |
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``` |
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) |
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_djuna__MN-Chinofun) |
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| Metric |Value| |
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|-------------------|----:| |
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|Avg. |24.26| |
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|IFEval (0-Shot) |61.10| |
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|BBH (3-Shot) |28.48| |
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|MATH Lvl 5 (4-Shot)|10.50| |
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|GPQA (0-shot) | 6.15| |
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|MuSR (0-shot) |10.38| |
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|MMLU-PRO (5-shot) |28.92| |
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