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Adding Evaluation Results (#1)

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- Adding Evaluation Results (65947a3d64c4ea3fd9dd9c3c3d058bf94198075c)


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

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  1. README.md +120 -4
README.md CHANGED
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  ---
 
 
 
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  library_name: transformers
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  tags:
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  - peft
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- license: mit
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  datasets:
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  - HuggingFaceH4/ultrachat_200k
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- language:
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- - en
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  LoRA adapter for kaitchup/Maixtchup-4x7b briefly fine-tuned on UltraChat.
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@@ -29,4 +132,17 @@ model = AutoModelForCausalLM.from_pretrained(
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  model.config.use_cache = True
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  model = PeftModel.from_pretrained(model, "kaitchup/Maixtchup-4x7b-QLoRA-SFT-UltraChat")
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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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  library_name: transformers
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  tags:
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  - peft
 
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  datasets:
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  - HuggingFaceH4/ultrachat_200k
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+ model-index:
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+ - name: Maixtchup-4x7b-QLoRA-SFT-UltraChat
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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=kaitchup/Maixtchup-4x7b-QLoRA-SFT-UltraChat
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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: 83.23
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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=kaitchup/Maixtchup-4x7b-QLoRA-SFT-UltraChat
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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: 60.78
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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=kaitchup/Maixtchup-4x7b-QLoRA-SFT-UltraChat
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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: 53.33
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+ source:
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+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=kaitchup/Maixtchup-4x7b-QLoRA-SFT-UltraChat
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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=kaitchup/Maixtchup-4x7b-QLoRA-SFT-UltraChat
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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: 43.21
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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=kaitchup/Maixtchup-4x7b-QLoRA-SFT-UltraChat
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+ name: Open LLM Leaderboard
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  ---
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  LoRA adapter for kaitchup/Maixtchup-4x7b briefly fine-tuned on UltraChat.
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  model.config.use_cache = True
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  model = PeftModel.from_pretrained(model, "kaitchup/Maixtchup-4x7b-QLoRA-SFT-UltraChat")
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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_kaitchup__Maixtchup-4x7b-QLoRA-SFT-UltraChat)
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+
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+ | Metric |Value|
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+ |---------------------------------|----:|
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+ |Avg. |63.11|
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+ |AI2 Reasoning Challenge (25-Shot)|60.92|
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+ |HellaSwag (10-Shot) |83.23|
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+ |MMLU (5-Shot) |60.78|
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+ |TruthfulQA (0-shot) |53.33|
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+ |Winogrande (5-shot) |77.19|
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+ |GSM8k (5-shot) |43.21|
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+