---
language:
- en
license: mit
datasets:
- Open-Orca/SlimOrca
- beaugogh/openorca-multiplechoice-10k
metrics:
- accuracy
model-index:
- name: llama2_7b_merge_orcafamily
  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: 56.91
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=yeen214/llama2_7b_merge_orcafamily
      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: 81.17
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=yeen214/llama2_7b_merge_orcafamily
      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: 51.49
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=yeen214/llama2_7b_merge_orcafamily
      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: 49.68
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=yeen214/llama2_7b_merge_orcafamily
      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: 75.93
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=yeen214/llama2_7b_merge_orcafamily
      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: 23.12
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=yeen214/llama2_7b_merge_orcafamily
      name: Open LLM Leaderboard
---


This model is based on the LLama 7b model as a backbone, and datasets from various Orcas have been fine-tuned and merged.


The three models were combined, and the model with the best ARC and MMLU performance was given the highest weight.


First: fine-tuning beaugogh/openorca-multiplechoice-10k on llama2 7b, but using the NEFTune method.


Second: model fine-tuned with the SlimOrca dataset on llama2 7b.

Third : Model with beaugogh/openorca-multiplechoice-10k fine-tuned on llama2 7b.



We'll add the results once we have the official results
# [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_yeen214__llama2_7b_merge_orcafamily)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |56.38|
|AI2 Reasoning Challenge (25-Shot)|56.91|
|HellaSwag (10-Shot)              |81.17|
|MMLU (5-Shot)                    |51.49|
|TruthfulQA (0-shot)              |49.68|
|Winogrande (5-shot)              |75.93|
|GSM8k (5-shot)                   |23.12|