README.md

---
license: apache-2.0
tags:
- MetaModelv3
- merge
model-index:
- name: MetaModelv3
  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: 71.16
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=gagan3012/MetaModelv3
      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: 88.39
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=gagan3012/MetaModelv3
      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: 66.32
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=gagan3012/MetaModelv3
      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: 71.86
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=gagan3012/MetaModelv3
      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: 83.35
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=gagan3012/MetaModelv3
      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: 65.28
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=gagan3012/MetaModelv3
      name: Open LLM Leaderboard
---

# MetaModelv3

This model is a hybrid of the following models and is trained using the following configuration:
 * [jeonsworld/CarbonVillain-en-10.7B-v4](https://huggingface.co/jeonsworld/CarbonVillain-en-10.7B-v4)
 * [jeonsworld/CarbonVillain-en-10.7B-v2](https://huggingface.co/jeonsworld/CarbonVillain-en-10.7B-v2)
# [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_gagan3012__MetaModelv3)

| Metric                | Value                     |
|-----------------------|---------------------------|
| Avg.                  | 74.39   |
| ARC (25-shot)         | 71.16          |
| HellaSwag (10-shot)   | 88.39    |
| MMLU (5-shot)         | 66.32         |
| TruthfulQA (0-shot)   | 71.86   |
| Winogrande (5-shot)   | 83.35   |
| GSM8K (5-shot)        | 65.28        |

# [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_gagan3012__MetaModelv3)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |74.39|
|AI2 Reasoning Challenge (25-Shot)|71.16|
|HellaSwag (10-Shot)              |88.39|
|MMLU (5-Shot)                    |66.32|
|TruthfulQA (0-shot)              |71.86|
|Winogrande (5-shot)              |83.35|
|GSM8k (5-shot)                   |65.28|