README.md

metadata

language:
  - en
license: cc-by-nc-4.0
model-index:
  - name: Dionysus-Mistral-m3-v6
    results:
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: AI2 Reasoning Challenge (25-Shot)
          type: ai2_arc
          config: ARC-Challenge
          split: test
          args:
            num_few_shot: 25
        metrics:
          - type: acc_norm
            value: 63.14
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=decem/Dionysus-Mistral-m3-v6
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: HellaSwag (10-Shot)
          type: hellaswag
          split: validation
          args:
            num_few_shot: 10
        metrics:
          - type: acc_norm
            value: 84.51
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=decem/Dionysus-Mistral-m3-v6
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MMLU (5-Shot)
          type: cais/mmlu
          config: all
          split: test
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 62.82
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=decem/Dionysus-Mistral-m3-v6
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: TruthfulQA (0-shot)
          type: truthful_qa
          config: multiple_choice
          split: validation
          args:
            num_few_shot: 0
        metrics:
          - type: mc2
            value: 49.49
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=decem/Dionysus-Mistral-m3-v6
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: Winogrande (5-shot)
          type: winogrande
          config: winogrande_xl
          split: validation
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 78.45
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=decem/Dionysus-Mistral-m3-v6
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: GSM8k (5-shot)
          type: gsm8k
          config: main
          split: test
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 64.22
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=decem/Dionysus-Mistral-m3-v6
          name: Open LLM Leaderboard

Dionysus-Mistral-m3-v6 - A Fine-tuned Language Model

Overview

Dionysus-Mistral-m3-v6 is a language model fine-tuned on the AIDC-ai-business/Marcoroni-7B-v3 architecture. This model is mainly used for roleplay.

Model Details

• Developer: DECEM
• Base Model: AIDC-ai-business/Marcoroni-7B-v3
• Fine-tuning Method: SFT
• Language: English

Prompting

Prompt Template for alpaca style

{system prompt} (without the {})

### Instruction:
{user_name}: {prompt} (without the {})

### Response:
{character_name}: (without the {})

stop_words: </s>

Open LLM Leaderboard Evaluation Details

https://huggingface.co/datasets/open-llm-leaderboard/details_decem__Dionysus-Mistral-m3-v6

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	67.10
AI2 Reasoning Challenge (25-Shot)	63.14
HellaSwag (10-Shot)	84.51
MMLU (5-Shot)	62.82
TruthfulQA (0-shot)	49.49
Winogrande (5-shot)	78.45
GSM8k (5-shot)	64.22