CarbonVillain-en-10.7B-v4/README.md

---
language:
- en
license: cc-by-nc-sa-4.0
tags:
- merge
- slerp
model-index:
- name: CarbonVillain-en-10.7B-v4
  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: 71.25
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=jeonsworld/CarbonVillain-en-10.7B-v4
      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: 88.48
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=jeonsworld/CarbonVillain-en-10.7B-v4
      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: 66.27
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=jeonsworld/CarbonVillain-en-10.7B-v4
      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: 71.95
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=jeonsworld/CarbonVillain-en-10.7B-v4
      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: 83.58
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=jeonsworld/CarbonVillain-en-10.7B-v4
      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: 65.58
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=jeonsworld/CarbonVillain-en-10.7B-v4
      name: Open LLM Leaderboard
---

# CarbonVillain
**This is a model created without learning to oppose indiscriminate carbon emissions.**  

This model is an experimental version created using [mergekit](https://github.com/cg123/mergekit).  
- merge models
  - [jeonsworld/CarbonVillain-en-10.7B-v1](https://huggingface.co/jeonsworld/CarbonVillain-en-10.7B-v1)
  - [jeonsworld/CarbonVillain-en-10.7B-v2](https://huggingface.co/jeonsworld/CarbonVillain-en-10.7B-v2)
- method: slerp

*Ranked 1st 2023.12.30*  


> thanks to [KyujinHan](https://huggingface.co/kyujinpy), [Yağız Çalık](https://huggingface.co/Weyaxi) and [VAGO solutions](https://huggingface.co/VAGOsolutions)  


# Prompt Template(s)

```
### User:
{user}

### Assistant:
{asistant}
```

# [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_jeonsworld__CarbonVillain-en-10.7B-v4)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |74.52|
|AI2 Reasoning Challenge (25-Shot)|71.25|
|HellaSwag (10-Shot)              |88.48|
|MMLU (5-Shot)                    |66.27|
|TruthfulQA (0-shot)              |71.95|
|Winogrande (5-shot)              |83.58|
|GSM8k (5-shot)                   |65.58|