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--- |
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license: other |
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datasets: |
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- KnutJaegersberg/Deita-6k |
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license_name: internlm |
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license_link: LICENSE |
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model-index: |
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- name: Deita-20b |
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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: 63.91 |
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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=KnutJaegersberg/Deita-20b |
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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: 83.11 |
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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=KnutJaegersberg/Deita-20b |
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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: 67.4 |
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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=KnutJaegersberg/Deita-20b |
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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: 57.29 |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=KnutJaegersberg/Deita-20b |
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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: 84.61 |
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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=KnutJaegersberg/Deita-20b |
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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: 72.1 |
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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=KnutJaegersberg/Deita-20b |
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name: Open LLM Leaderboard |
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--- |
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Open Source License |
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The code is licensed under Apache-2.0, while model weights are fully open for academic research and also allow free commercial usage. To apply for a commercial license, please fill in the application form (English)/申请表（中文）. For other questions or collaborations, please contact internlm@pjlab.org.cn. |
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Prompt Example: |
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``` |
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### System: |
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You are an AI assistant. User will give you a task. Your goal is to complete the task as faithfully as you can. While performing the task think step-by-step and justify your steps. |
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### User: |
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How do you fine tune a large language model? |
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### Assistant: |
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``` |
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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_KnutJaegersberg__Deita-20b) |
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| Metric |Value| |
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|---------------------------------|----:| |
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|Avg. |71.40| |
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|AI2 Reasoning Challenge (25-Shot)|63.91| |
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|HellaSwag (10-Shot) |83.11| |
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|MMLU (5-Shot) |67.40| |
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|TruthfulQA (0-shot) |57.29| |
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|Winogrande (5-shot) |84.61| |
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|GSM8k (5-shot) |72.10| |
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