README.md

metadata

license: apache-2.0
base_model:
  - BAAI/Infinity-Instruct-7M-Gen-mistral-7B
  - SanjiWatsuki/Kunoichi-7B
  - uukuguy/speechless-instruct-mistral-7b-v0.2
base_model_relation: merge
model-index:
  - name: Inf-Silent-Kunoichi-v0.2-2x7B
    results:
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: IFEval (0-Shot)
          type: HuggingFaceH4/ifeval
          args:
            num_few_shot: 0
        metrics:
          - type: inst_level_strict_acc and prompt_level_strict_acc
            value: 36.36
            name: strict accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Jacoby746/Inf-Silent-Kunoichi-v0.2-2x7B
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: BBH (3-Shot)
          type: BBH
          args:
            num_few_shot: 3
        metrics:
          - type: acc_norm
            value: 32.26
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Jacoby746/Inf-Silent-Kunoichi-v0.2-2x7B
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MATH Lvl 5 (4-Shot)
          type: hendrycks/competition_math
          args:
            num_few_shot: 4
        metrics:
          - type: exact_match
            value: 5.66
            name: exact match
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Jacoby746/Inf-Silent-Kunoichi-v0.2-2x7B
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: GPQA (0-shot)
          type: Idavidrein/gpqa
          args:
            num_few_shot: 0
        metrics:
          - type: acc_norm
            value: 6.71
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Jacoby746/Inf-Silent-Kunoichi-v0.2-2x7B
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MuSR (0-shot)
          type: TAUR-Lab/MuSR
          args:
            num_few_shot: 0
        metrics:
          - type: acc_norm
            value: 13.26
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Jacoby746/Inf-Silent-Kunoichi-v0.2-2x7B
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MMLU-PRO (5-shot)
          type: TIGER-Lab/MMLU-Pro
          config: main
          split: test
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 25.25
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Jacoby746/Inf-Silent-Kunoichi-v0.2-2x7B
          name: Open LLM Leaderboard

Test merge of 7b models for learning purposees. v0.2 is mostly the same, with minor promting changes and consolidating shards from 1B to 4B to reduce number of files.

Description: This model is a merge of BAAI/Infinity-Instruct-7M-Gen-mistral-7B, SanjiWatsuki/Kunoichi-7B, and uukuguy/speechless-instruct-mistral-7b-v0.2 This is the first model I've ever uploaded and wanted to learn more about the process. Merged using mergekit-moe.

Works up to 8k context, 16k with 2.5 RoPe scaling

Prompt template: Custom format, or Alpaca

Alpaca: Below is an instruction that describes a task. Write a response that appropriately completes the request.

Instruction: {prompt}

Response:

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	19.92
IFEval (0-Shot)	36.36
BBH (3-Shot)	32.26
MATH Lvl 5 (4-Shot)	5.66
GPQA (0-shot)	6.71
MuSR (0-shot)	13.26
MMLU-PRO (5-shot)	25.25