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Adding Evaluation Results

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This is an automated PR created with https://huggingface.co/spaces/Weyaxi/open-llm-leaderboard-results-pr

The purpose of this PR is to add evaluation results from the Open LLM Leaderboard to your model card.

If you encounter any issues, please report them to https://huggingface.co/spaces/Weyaxi/open-llm-leaderboard-results-pr/discussions

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  ---
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  license: apache-2.0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  ### TeeZee/GALAXY-XB-v.01 ###
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@@ -9,4 +112,17 @@ Experiment, can DUS be taken one or more steps further?
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  - 8 layers removed from both models, as per original paper.
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  - base version of upstage/SOLAR-10.7B-v1.0 used for merge
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  - no finetuning done yet, this is just a merge, first step in DUS paper
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- - next step, if evaluation proves that its at least as 'smart' as base model, should be finetuning to 'recover' after merge
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  license: apache-2.0
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+ model-index:
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+ - name: GALAXY-XB-v.01
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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: 60.92
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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=TeeZee/GALAXY-XB-v.01
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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: 82.92
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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=TeeZee/GALAXY-XB-v.01
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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: 65.11
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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=TeeZee/GALAXY-XB-v.01
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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: 43.67
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+ source:
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+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/GALAXY-XB-v.01
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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: 81.14
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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=TeeZee/GALAXY-XB-v.01
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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: 43.44
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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=TeeZee/GALAXY-XB-v.01
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+ name: Open LLM Leaderboard
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  ---
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  ### TeeZee/GALAXY-XB-v.01 ###
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  - 8 layers removed from both models, as per original paper.
113
  - base version of upstage/SOLAR-10.7B-v1.0 used for merge
114
  - no finetuning done yet, this is just a merge, first step in DUS paper
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+ - next step, if evaluation proves that its at least as 'smart' as base model, should be finetuning to 'recover' after merge
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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_TeeZee__GALAXY-XB-v.01)
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+
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+ | Metric |Value|
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+ |---------------------------------|----:|
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+ |Avg. |62.87|
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+ |AI2 Reasoning Challenge (25-Shot)|60.92|
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+ |HellaSwag (10-Shot) |82.92|
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+ |MMLU (5-Shot) |65.11|
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+ |TruthfulQA (0-shot) |43.67|
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+ |Winogrande (5-shot) |81.14|
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+ |GSM8k (5-shot) |43.44|
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+