README.md

metadata

language:
  - en
license: gemma
tags:
  - supernova
  - moth
  - gemma
  - gemma-2
  - gemma-2-it
  - gemma-2-9b-it
  - 9b
  - general
  - conversational
  - chat
  - instruct
base_model: google/gemma-2-9b-it
datasets:
  - sequelbox/Supernova
pipeline_tag: text-generation
model-index:
  - name: gemma-2-9B-MOTH
    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: 20.59
            name: strict accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sequelbox/gemma-2-9B-MOTH
          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: 3.21
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sequelbox/gemma-2-9B-MOTH
          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: 0
            name: exact match
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sequelbox/gemma-2-9B-MOTH
          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: 1.34
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sequelbox/gemma-2-9B-MOTH
          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: 0.62
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sequelbox/gemma-2-9B-MOTH
          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: 1.56
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sequelbox/gemma-2-9B-MOTH
          name: Open LLM Leaderboard

• MOTH is a general chat AI.
• MOTH is finetuned on high quality synthetic data.
• MOTH is trained on a variety of skills and specialties.
• This version of MOTH is trained on the Gemma 2 Instruct format.
• MOTH is also available for Llama 3.1; more MOTH finetunes for other models to follow.
• MOTH has not been manually tested and uses automatically generated datasets.
• Do as you will.

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	4.55
IFEval (0-Shot)	20.59
BBH (3-Shot)	3.21
MATH Lvl 5 (4-Shot)	0.00
GPQA (0-shot)	1.34
MuSR (0-shot)	0.62
MMLU-PRO (5-shot)	1.56