Adding Evaluation Results
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leaderboard-pr-bot
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README.md
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---
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license: mit
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language:
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- en
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tags:
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- moe
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---
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# FusionNet_7Bx2_MoE_v0.1
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Fine-tuned model on English language using MoE method. The improved version from FusionNet_7Bx2_MoE_14B.
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## Model description
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The FusionNet_7Bx2_MoE_v0.1 is a model to experiment with the MoE method, which could significantly increase the performance of the original model. The FusionNet has 12.9B 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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tags:
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- moe
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pipeline_tag: text-generation
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model-index:
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- name: FusionNet_7Bx2_MoE_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: 74.06
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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_7Bx2_MoE_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: 88.9
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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_7Bx2_MoE_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: 65.0
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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_7Bx2_MoE_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: 71.2
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TomGrc/FusionNet_7Bx2_MoE_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: 87.53
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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_7Bx2_MoE_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: 70.28
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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_7Bx2_MoE_v0.1
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name: Open LLM Leaderboard
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---
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# FusionNet_7Bx2_MoE_v0.1
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Fine-tuned model on English language using MoE method. The improved version from FusionNet_7Bx2_MoE_14B.
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## Model description
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+
The FusionNet_7Bx2_MoE_v0.1 is a model to experiment with the MoE method, which could significantly increase the performance of the original model. The FusionNet has 12.9B 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_7Bx2_MoE_v0.1)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |76.16|
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|AI2 Reasoning Challenge (25-Shot)|74.06|
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|HellaSwag (10-Shot) |88.90|
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|MMLU (5-Shot) |65.00|
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|TruthfulQA (0-shot) |71.20|
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|Winogrande (5-shot) |87.53|
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|GSM8k (5-shot) |70.28|
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