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Adding Evaluation Results (#2)
Browse files- Adding Evaluation Results (1f6a175585cc733d613a3b7b4c5f176a406299bb)
Co-authored-by: Open LLM Leaderboard PR Bot <leaderboard-pr-bot@users.noreply.huggingface.co>
README.md
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---
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license: apache-2.0
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language:
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- en
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- zh
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pipeline_tag: text-generation
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tags:
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- llama
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- latest
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-
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---
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![image/webp](https://cdn-uploads.huggingface.co/production/uploads/64ef2a96f2b8f40224d7b407/9wZAYV-keBPVtn6-cd17n.webp)
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The model output of llama 3 does not stop at eot, so it cannot be used out of the box. For the time being, we respect the official behavior and guide the model to output "end_of_text" directly at the end of fine-tuning, making it convenient for immediate fine-tuning in downstream fields.
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-
llama 3 模型输出 eot 时不会停止,无法开箱即用。我们暂时尊重官方的行为,精调时指导模型在最后直接输出 end_of_text,方便目前开箱即用地在下游领域精调。
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---
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language:
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- en
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- zh
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+
license: apache-2.0
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library_name: transformers
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tags:
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- llama
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- latest
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datasets:
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- teknium/OpenHermes-2.5
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pipeline_tag: text-generation
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model-index:
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- name: Gigi-Llama3-8B-Chinese-zh
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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: 59.64
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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=yaojialzc/Gigi-Llama3-8B-Chinese-zh
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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: 80.28
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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=yaojialzc/Gigi-Llama3-8B-Chinese-zh
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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: 66.91
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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=yaojialzc/Gigi-Llama3-8B-Chinese-zh
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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: 52.14
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=yaojialzc/Gigi-Llama3-8B-Chinese-zh
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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: 76.48
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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=yaojialzc/Gigi-Llama3-8B-Chinese-zh
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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: 66.79
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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=yaojialzc/Gigi-Llama3-8B-Chinese-zh
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name: Open LLM Leaderboard
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---
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![image/webp](https://cdn-uploads.huggingface.co/production/uploads/64ef2a96f2b8f40224d7b407/9wZAYV-keBPVtn6-cd17n.webp)
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The model output of llama 3 does not stop at eot, so it cannot be used out of the box. For the time being, we respect the official behavior and guide the model to output "end_of_text" directly at the end of fine-tuning, making it convenient for immediate fine-tuning in downstream fields.
|
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|
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+
llama 3 模型输出 eot 时不会停止,无法开箱即用。我们暂时尊重官方的行为,精调时指导模型在最后直接输出 end_of_text,方便目前开箱即用地在下游领域精调。
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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_yaojialzc__Gigi-Llama3-8B-Chinese-zh)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |67.04|
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|AI2 Reasoning Challenge (25-Shot)|59.64|
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|HellaSwag (10-Shot) |80.28|
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|MMLU (5-Shot) |66.91|
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|TruthfulQA (0-shot) |52.14|
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|Winogrande (5-shot) |76.48|
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|GSM8k (5-shot) |66.79|
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