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Adding Evaluation Results (#2)

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- Adding Evaluation Results (6231aece0063e81b670097c90a56f55a73707c88)


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: mit
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  language:
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  - en
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- pipeline_tag: text-generation
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  tags:
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  - moe
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  # FusionNet_34Bx2_MoE
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  Fine-tuned model on English language using MoE method.
@@ -16,4 +119,17 @@ import torch
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  from transformers import AutoModelForCausalLM, AutoTokenizer
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  tokenizer = AutoTokenizer.from_pretrained("TomGrc/FusionNet_34Bx2_MoE")
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  model = AutoModelForCausalLM.from_pretrained("TomGrc/FusionNet_34Bx2_MoE")
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- ```
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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_34Bx2_MoE
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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: 72.95
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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_34Bx2_MoE
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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: 86.22
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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_34Bx2_MoE
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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: 77.05
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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_34Bx2_MoE
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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: 71.31
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+ source:
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+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TomGrc/FusionNet_34Bx2_MoE
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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: 83.98
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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_34Bx2_MoE
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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: 70.89
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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_34Bx2_MoE
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+ name: Open LLM Leaderboard
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  ---
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  # FusionNet_34Bx2_MoE
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  Fine-tuned model on English language using MoE method.
 
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  from transformers import AutoModelForCausalLM, AutoTokenizer
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  tokenizer = AutoTokenizer.from_pretrained("TomGrc/FusionNet_34Bx2_MoE")
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  model = AutoModelForCausalLM.from_pretrained("TomGrc/FusionNet_34Bx2_MoE")
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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_TomGrc__FusionNet_34Bx2_MoE)
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+
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+ | Metric |Value|
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+ |---------------------------------|----:|
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+ |Avg. |77.07|
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+ |AI2 Reasoning Challenge (25-Shot)|72.95|
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+ |HellaSwag (10-Shot) |86.22|
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+ |MMLU (5-Shot) |77.05|
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+ |TruthfulQA (0-shot) |71.31|
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+ |Winogrande (5-shot) |83.98|
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+ |GSM8k (5-shot) |70.89|
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+