---
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.

<img src="./dionysus.jpg" alt="Dionysus" style="transform: scale(0.5);">

## Model Details

- **Developer:** DECEM
- **Base Model:** [AIDC-ai-business/Marcoroni-7B-v3](https://huggingface.co/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](https://huggingface.co/datasets/open-llm-leaderboard/details_decem__Dionysus-Mistral-m3-v6)
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_decem__Dionysus-Mistral-m3-v6)

|             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|