---
language:
- ja
- en
license: apache-2.0
datasets:
- augmxnt/ultra-orca-boros-en-ja-v1
model-index:
- name: shisa-gamma-7b-v1
  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: 53.16
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=augmxnt/shisa-gamma-7b-v1
      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: 77.3
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=augmxnt/shisa-gamma-7b-v1
      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: 55.23
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=augmxnt/shisa-gamma-7b-v1
      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: 50.73
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=augmxnt/shisa-gamma-7b-v1
      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: 73.88
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=augmxnt/shisa-gamma-7b-v1
      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: 22.74
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=augmxnt/shisa-gamma-7b-v1
      name: Open LLM Leaderboard
---
# shisa-gamma-7b-v1

For more information see our main [Shisa 7B](https://huggingface.co/augmxnt/shisa-gamma-7b-v1/resolve/main/shisa-comparison.png) model

We applied a version of our fine-tune data set onto [Japanese Stable LM Base Gamma 7B](https://huggingface.co/stabilityai/japanese-stablelm-base-gamma-7b) and it performed pretty well, just sharing since it might be of interest.

Check out our [JA MT-Bench results](https://github.com/AUGMXNT/shisa/wiki/Evals-%3A-JA-MT%E2%80%90Bench).

![Comparison vs shisa-7b-v1](https://huggingface.co/augmxnt/shisa-gamma-7b-v1/resolve/main/shisa-comparison.png)

![Comparison vs other recently released JA models](https://huggingface.co/augmxnt/shisa-gamma-7b-v1/resolve/main/ja-comparison.png)
# [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_augmxnt__shisa-gamma-7b-v1)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |55.50|
|AI2 Reasoning Challenge (25-Shot)|53.16|
|HellaSwag (10-Shot)              |77.30|
|MMLU (5-Shot)                    |55.23|
|TruthfulQA (0-shot)              |50.73|
|Winogrande (5-shot)              |73.88|
|GSM8k (5-shot)                   |22.74|