---
language:
- en
license: agpl-3.0
model-index:
- name: Michel-13B
  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: 61.26
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=PotatoOff/Michel-13B
      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: 83.21
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=PotatoOff/Michel-13B
      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: 55.05
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=PotatoOff/Michel-13B
      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: 50.43
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=PotatoOff/Michel-13B
      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: 75.22
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=PotatoOff/Michel-13B
      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: 20.17
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=PotatoOff/Michel-13B
      name: Open LLM Leaderboard
---

# Michel - 13B

**A Uncensored fine tune model general tasks focused of [NousHermes-Llama2-13B](https://huggingface.co/NousResearch/Nous-Hermes-Llama2-13b).**  
With the help of [my team](https://huggingface.co/ConvexAI).

#### Quants

[Michel Exl2 Quant](https://huggingface.co/bartowski/Michel-13B-exl2)  
[Michel GGUF Quant](https://huggingface.co/Kquant03/Michel-13B-GGUF)  

### Useful

- **Uses Llama2 prompt template.**  
- Next one will be more interesting :}
  
### I had good results with this parameters:
  - temperature: 0.8
  - top_p: 0.75
  - min_p: 0
  - top_k: 0
  - repetition_penalty: 1.05
    
### General Usecase Test  


### BenchMarks on OpenLLM Leaderboard
More details: [Michel-13B OpenLLM BenchMarks](https://huggingface.co/datasets/open-llm-leaderboard/details_PotatoOff__Michel-13B)  
![image/png](https://cdn-uploads.huggingface.co/production/uploads/64e7616c7df33432812e3c57/kDGDa1nzXJAJJ9yZdwIBz.png)  


### Thank you h2m for the compute

### Have Fun :)

# [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_PotatoOff__Michel-13B)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |57.56|
|AI2 Reasoning Challenge (25-Shot)|61.26|
|HellaSwag (10-Shot)              |83.21|
|MMLU (5-Shot)                    |55.05|
|TruthfulQA (0-shot)              |50.43|
|Winogrande (5-shot)              |75.22|
|GSM8k (5-shot)                   |20.17|