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Adding Evaluation Results (#1)

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- Adding Evaluation Results (02526ad8902c6d0b67522140a5f7dbdb2afcb970)


Co-authored-by: Open LLM Leaderboard PR Bot <[email protected]>

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  ---
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- license: mit
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  language:
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  - en
 
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  pipeline_tag: text-generation
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  # FusionNet
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  Fine-tuned model on English language using single passthrough Fusion method.
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  ## Model description
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- The FusionNet is a model to experiment with the single passthrough Fusion method, which could significantly increase the performance of the original model. The FusionNet has 21.2B parameters, and this model is fine-tuned. Enjoy!
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
 
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  language:
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  - en
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+ license: mit
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  pipeline_tag: text-generation
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+ model-index:
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+ - name: FusionNet_passthrough_v0.1
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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: 69.45
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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=TomGrc/FusionNet_passthrough_v0.1
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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: 87.79
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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=TomGrc/FusionNet_passthrough_v0.1
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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: 65.2
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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=TomGrc/FusionNet_passthrough_v0.1
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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: 67.67
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+ source:
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+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TomGrc/FusionNet_passthrough_v0.1
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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: 81.53
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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=TomGrc/FusionNet_passthrough_v0.1
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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: 22.82
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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=TomGrc/FusionNet_passthrough_v0.1
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+ name: Open LLM Leaderboard
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  ---
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  # FusionNet
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  Fine-tuned model on English language using single passthrough Fusion method.
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  ## Model description
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+ The FusionNet is a model to experiment with the single passthrough Fusion method, which could significantly increase the performance of the original model. The FusionNet has 21.2B parameters, and this model is fine-tuned. Enjoy!
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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_TomGrc__FusionNet_passthrough_v0.1)
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+
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+ | Metric |Value|
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+ |---------------------------------|----:|
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+ |Avg. |65.74|
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+ |AI2 Reasoning Challenge (25-Shot)|69.45|
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+ |HellaSwag (10-Shot) |87.79|
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+ |MMLU (5-Shot) |65.20|
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+ |TruthfulQA (0-shot) |67.67|
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+ |Winogrande (5-shot) |81.53|
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+ |GSM8k (5-shot) |22.82|
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+