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Adding Evaluation Results (#1)

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- Adding Evaluation Results (a43f56f250321dcc3fec11920f22f1d6830fa4ec)


Co-authored-by: Open LLM Leaderboard PR Bot <leaderboard-pr-bot@users.noreply.huggingface.co>

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  1. README.md +119 -3
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  ---
 
 
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  license: apache-2.0
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  datasets:
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  - Intel/orca_dpo_pairs
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- language:
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- - en
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  Testing Mistral-Instruct model with Orca DPO dataset.
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  Trying to see the effects of DPO for own study.
@@ -61,4 +164,17 @@ Trying to see the effects of DPO for own study.
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  Used Mistral-7B-Instrcut-v0.2 model due to its good performance
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  Testing Mistral-Instruct model with Orca DPO dataset.
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  Trying to see the effects of DPO for own study.
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- Used Mistral-7B-Instrcut-v0.2 model due to its good performance
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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+ language:
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+ - en
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  license: apache-2.0
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  datasets:
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  - Intel/orca_dpo_pairs
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+ model-index:
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+ - name: DPO_mistral_7b_alpaca_0124_v1
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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: 63.4
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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=kwchoi/DPO_mistral_7b_alpaca_0124_v1
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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: 73.2
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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=kwchoi/DPO_mistral_7b_alpaca_0124_v1
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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: 60.51
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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=kwchoi/DPO_mistral_7b_alpaca_0124_v1
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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: 66.76
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+ source:
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+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kwchoi/DPO_mistral_7b_alpaca_0124_v1
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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: 77.19
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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=kwchoi/DPO_mistral_7b_alpaca_0124_v1
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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: 25.85
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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=kwchoi/DPO_mistral_7b_alpaca_0124_v1
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+ name: Open LLM Leaderboard
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  ---
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  Testing Mistral-Instruct model with Orca DPO dataset.
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  Trying to see the effects of DPO for own study.
 
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  Used Mistral-7B-Instrcut-v0.2 model due to its good performance
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  Testing Mistral-Instruct model with Orca DPO dataset.
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  Trying to see the effects of DPO for own study.
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+ Used Mistral-7B-Instrcut-v0.2 model due to its good performance
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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_kwchoi__DPO_mistral_7b_alpaca_0124_v1)
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+
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+ | Metric |Value|
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+ |---------------------------------|----:|
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+ |Avg. |61.15|
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+ |AI2 Reasoning Challenge (25-Shot)|63.40|
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+ |HellaSwag (10-Shot) |73.20|
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+ |MMLU (5-Shot) |60.51|
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+ |TruthfulQA (0-shot) |66.76|
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+ |Winogrande (5-shot) |77.19|
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+ |GSM8k (5-shot) |25.85|
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+