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Adding Evaluation Results (#1)

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- Adding Evaluation Results (4f79ab536c9038cf61cf3791afe5d1726a42a78c)


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

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  1. README.md +117 -1
README.md CHANGED
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  license: llama2
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  datasets:
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  - 922-CA/MoCha_v1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  # monika-ddlc-7b-v1:
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  * LLaMA-2 7b chat fine-tuned for Monika character from DDLC (still somewhat experimental)
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  Finally, this model is not guaranteed to output aligned or safe outputs, use at your own risk.
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- Note: Ideally, would have liked to fine-tune on other models (specifically [Zephyr-7b-alpha](https://huggingface.co/HuggingFaceH4/zephyr-7b-alpha)). May try soon for later versions.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  license: llama2
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  datasets:
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  - 922-CA/MoCha_v1
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+ model-index:
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+ - name: monika-ddlc-7b-v1
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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: 54.95
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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=922-CA/monika-ddlc-7b-v1
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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: 76.78
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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=922-CA/monika-ddlc-7b-v1
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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: 45.61
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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=922-CA/monika-ddlc-7b-v1
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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: 43.94
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+ source:
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+ url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=922-CA/monika-ddlc-7b-v1
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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: 72.85
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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=922-CA/monika-ddlc-7b-v1
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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: 8.79
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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=922-CA/monika-ddlc-7b-v1
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+ name: Open LLM Leaderboard
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  ---
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  # monika-ddlc-7b-v1:
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  * LLaMA-2 7b chat fine-tuned for Monika character from DDLC (still somewhat experimental)
 
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  Finally, this model is not guaranteed to output aligned or safe outputs, use at your own risk.
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+ Note: Ideally, would have liked to fine-tune on other models (specifically [Zephyr-7b-alpha](https://huggingface.co/HuggingFaceH4/zephyr-7b-alpha)). May try soon for later versions.
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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_922-CA__monika-ddlc-7b-v1)
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+
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+ | Metric |Value|
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+ |---------------------------------|----:|
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+ |Avg. |50.49|
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+ |AI2 Reasoning Challenge (25-Shot)|54.95|
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+ |HellaSwag (10-Shot) |76.78|
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+ |MMLU (5-Shot) |45.61|
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+ |TruthfulQA (0-shot) |43.94|
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+ |Winogrande (5-shot) |72.85|
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+ |GSM8k (5-shot) | 8.79|
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+