Adding Evaluation Results
Browse filesThis is an automated PR created with [this space](https://huggingface.co/spaces/T145/open-llm-leaderboard-results-to-modelcard)!
The purpose of this PR is to add evaluation results from the Open LLM Leaderboard to your model card.
Please report any issues here: https://huggingface.co/spaces/T145/open-llm-leaderboard-results-to-modelcard/discussions
README.md
CHANGED
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@@ -11,6 +11,105 @@ tags:
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- text-generation-inference
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- coder
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- reasoner
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---
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@@ -77,4 +176,18 @@ print(response)
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2. **Language-Specific Variability**: Performance may vary across different programming languages.
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3. **Possible Error Propagation**: Extended text outputs might introduce logical inconsistencies.
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4. **Limited Real-World Awareness**: The model does not have access to real-time internet updates.
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-
5. **Prompt Sensitivity**: Performance depends on how well the prompt is structured.
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- text-generation-inference
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- coder
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- reasoner
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model-index:
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- name: Viper-Coder-Hybrid-v1.2
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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: wis-k/instruction-following-eval
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split: train
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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: 67.36
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name: averaged accuracy
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source:
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=prithivMLmods%2FViper-Coder-Hybrid-v1.2
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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: SaylorTwift/bbh
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split: test
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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: 48.29
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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#/?search=prithivMLmods%2FViper-Coder-Hybrid-v1.2
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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: lighteval/MATH-Hard
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split: test
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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: 33.31
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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#/?search=prithivMLmods%2FViper-Coder-Hybrid-v1.2
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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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split: train
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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: 16.55
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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#/?search=prithivMLmods%2FViper-Coder-Hybrid-v1.2
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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: 20.31
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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#/?search=prithivMLmods%2FViper-Coder-Hybrid-v1.2
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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: 47.14
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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#/?search=prithivMLmods%2FViper-Coder-Hybrid-v1.2
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name: Open LLM Leaderboard
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---
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2. **Language-Specific Variability**: Performance may vary across different programming languages.
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3. **Possible Error Propagation**: Extended text outputs might introduce logical inconsistencies.
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4. **Limited Real-World Awareness**: The model does not have access to real-time internet updates.
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5. **Prompt Sensitivity**: Performance depends on how well the prompt is structured.
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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/prithivMLmods__Viper-Coder-Hybrid-v1.2-details)!
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Summarized results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/contents/viewer/default/train?q=prithivMLmods%2FViper-Coder-Hybrid-v1.2&sort[column]=Average%20%E2%AC%86%EF%B8%8F&sort[direction]=desc)!
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| Metric |Value (%)|
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|-------------------|--------:|
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|**Average** | 38.83|
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|IFEval (0-Shot) | 67.36|
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|BBH (3-Shot) | 48.29|
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|MATH Lvl 5 (4-Shot)| 33.31|
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|GPQA (0-shot) | 16.55|
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|MuSR (0-shot) | 20.31|
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|MMLU-PRO (5-shot) | 47.14|
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