Adding Evaluation Results
#7
by
leaderboard-pr-bot
- opened
README.md
CHANGED
@@ -1,10 +1,9 @@
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---
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license: cc-by-nc-4.0
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language:
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- en
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- de
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library_name: transformers
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pipeline_tag: text-generation
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tags:
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- finetune
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- dpo
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- german
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datasets:
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- argilla/distilabel-math-preference-dpo
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---
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![SauerkrautLM](https://vago-solutions.ai/wp-content/uploads/2024/02/sauerkrautlm-solar-2.png "SauerkrautLM-SOLAR-Instruct")
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@@ -129,4 +232,17 @@ We are also keenly seeking support and investment for our startup, VAGO solution
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## Acknowledgement
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Many thanks to [argilla](https://huggingface.co/datasets/argilla) and [Huggingface](https://huggingface.co) for providing such valuable datasets to the Open-Source community. And of course a big thanks to [upstage](https://huggingface.co/upstage) for providing the open source community with their latest technology!
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-
Many thanks to [TheBloke](https://huggingface.co/TheBloke) for super fast quantifying all of our models.
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---
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language:
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- en
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- de
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+
license: cc-by-nc-4.0
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library_name: transformers
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tags:
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- finetune
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- dpo
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- german
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datasets:
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- argilla/distilabel-math-preference-dpo
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pipeline_tag: text-generation
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model-index:
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- name: SauerkrautLM-SOLAR-Instruct
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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: AI2 Reasoning Challenge (25-Shot)
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type: ai2_arc
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config: ARC-Challenge
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split: test
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args:
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num_few_shot: 25
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metrics:
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- type: acc_norm
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value: 70.82
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=VAGOsolutions/SauerkrautLM-SOLAR-Instruct
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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: HellaSwag (10-Shot)
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type: hellaswag
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split: validation
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args:
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num_few_shot: 10
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metrics:
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- type: acc_norm
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value: 88.63
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=VAGOsolutions/SauerkrautLM-SOLAR-Instruct
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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 (5-Shot)
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type: cais/mmlu
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config: all
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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: 66.2
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=VAGOsolutions/SauerkrautLM-SOLAR-Instruct
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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: TruthfulQA (0-shot)
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type: truthful_qa
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config: multiple_choice
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split: validation
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args:
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num_few_shot: 0
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metrics:
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- type: mc2
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value: 71.95
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=VAGOsolutions/SauerkrautLM-SOLAR-Instruct
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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: Winogrande (5-shot)
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type: winogrande
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config: winogrande_xl
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split: validation
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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: 83.5
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=VAGOsolutions/SauerkrautLM-SOLAR-Instruct
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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: GSM8k (5-shot)
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type: gsm8k
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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: 64.14
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=VAGOsolutions/SauerkrautLM-SOLAR-Instruct
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name: Open LLM Leaderboard
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---
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![SauerkrautLM](https://vago-solutions.ai/wp-content/uploads/2024/02/sauerkrautlm-solar-2.png "SauerkrautLM-SOLAR-Instruct")
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## Acknowledgement
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Many thanks to [argilla](https://huggingface.co/datasets/argilla) and [Huggingface](https://huggingface.co) for providing such valuable datasets to the Open-Source community. And of course a big thanks to [upstage](https://huggingface.co/upstage) for providing the open source community with their latest technology!
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+
Many thanks to [TheBloke](https://huggingface.co/TheBloke) for super fast quantifying all of our models.
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_VAGOsolutions__SauerkrautLM-SOLAR-Instruct)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |74.21|
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|AI2 Reasoning Challenge (25-Shot)|70.82|
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|HellaSwag (10-Shot) |88.63|
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|MMLU (5-Shot) |66.20|
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|TruthfulQA (0-shot) |71.95|
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|Winogrande (5-shot) |83.50|
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|GSM8k (5-shot) |64.14|
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