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Adding Evaluation Results (#1)
Browse files- Adding Evaluation Results (386351219b88e81dd49ecf108a4199bee66a1511)
Co-authored-by: Open LLM Leaderboard PR Bot <[email protected]>
README.md
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@@ -1,9 +1,112 @@
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---
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license: other
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license_name: internlm
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license_link: LICENSE
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datasets:
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- KnutJaegersberg/Deita-6k
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---
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@@ -17,4 +120,17 @@ You are an AI assistant. User will give you a task. Your goal is to complete the
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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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---
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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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### 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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