Adding Evaluation Results
#3
by
cc1emoon
- opened
README.md
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---
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base_model:
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- BioMistral/BioMistral-7B
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- mistralai/Mistral-7B-Instruct-v0.1
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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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- dare
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- medical
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- biology
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license: apache-2.0
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datasets:
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- pubmed
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language:
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- en
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- fr
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- pl
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- ro
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- de
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pipeline_tag: text-generation
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---
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# BioMistral-7B-mistral7instruct-dare
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@@ -147,3 +250,17 @@ Arxiv : [https://arxiv.org/abs/2402.10373](https://arxiv.org/abs/2402.10373)
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**CAUTION!** Both direct and downstream users need to be informed about the risks, biases, and constraints inherent in the model. While the model can produce natural language text, our exploration of its capabilities and limitations is just beginning. In fields such as medicine, comprehending these limitations is crucial. Hence, we strongly advise against deploying this model for natural language generation in production or for professional tasks in the realm of health and medicine.
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---
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language:
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- en
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- fr
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- pl
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- ro
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- de
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license: apache-2.0
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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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- dare
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- medical
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- biology
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base_model:
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- BioMistral/BioMistral-7B
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- mistralai/Mistral-7B-Instruct-v0.1
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datasets:
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- pubmed
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pipeline_tag: text-generation
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model-index:
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- name: BioMistral-7B-DARE
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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: 58.28
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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=BioMistral/BioMistral-7B-DARE
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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: 79.87
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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=BioMistral/BioMistral-7B-DARE
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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: 57.34
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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=BioMistral/BioMistral-7B-DARE
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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: 55.61
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=BioMistral/BioMistral-7B-DARE
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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: 76.09
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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=BioMistral/BioMistral-7B-DARE
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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: 15.01
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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=BioMistral/BioMistral-7B-DARE
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name: Open LLM Leaderboard
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---
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# BioMistral-7B-mistral7instruct-dare
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**CAUTION!** Both direct and downstream users need to be informed about the risks, biases, and constraints inherent in the model. While the model can produce natural language text, our exploration of its capabilities and limitations is just beginning. In fields such as medicine, comprehending these limitations is crucial. Hence, we strongly advise against deploying this model for natural language generation in production or for professional tasks in the realm of health and medicine.
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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_BioMistral__BioMistral-7B-DARE)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |57.03|
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|AI2 Reasoning Challenge (25-Shot)|58.28|
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|HellaSwag (10-Shot) |79.87|
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|MMLU (5-Shot) |57.34|
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|TruthfulQA (0-shot) |55.61|
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|Winogrande (5-shot) |76.09|
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|GSM8k (5-shot) |15.01|
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