GenAI-llama-2-13b / README.md
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metadata
language:
  - en
tags:
  - llama-2
  - instruct
  - instruction
pipeline_tag: text-generation
model-index:
  - name: sitebunny-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: 63.14
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=42MARU/sitebunny-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: 83.64
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=42MARU/sitebunny-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: 59.91
            name: accuracy
        source:
          url: >-
            https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=42MARU/sitebunny-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: 56.21
        source:
          url: >-
            https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=42MARU/sitebunny-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: 76.72
            name: accuracy
        source:
          url: >-
            https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=42MARU/sitebunny-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: 9.4
            name: accuracy
        source:
          url: >-
            https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=42MARU/sitebunny-13b
          name: Open LLM Leaderboard

GenAI-llama-2-13b

Model Details

Used Datasets

  • Orca-style dataset
  • Platypus

Prompt Template

### User:
{User}

### Assistant:
{Assistant}

Intruduce 42MARU

  • At 42Maru we study QA (Question Answering) and are developing advanced search paradigms that help users spend less time searching by understanding natural language and intention thanks to AI and Deep Learning.
  • About Us
  • Contact Us

Contribute

License

LICENSE.txt

USE_POLICY

USE_POLICY.md

Responsible Use Guide

Responsible-Use-Guide.pdf

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric Value
Avg. 56.03
ARC (25-shot) 63.14
HellaSwag (10-shot) 83.64
MMLU (5-shot) 59.91
TruthfulQA (0-shot) 56.21
Winogrande (5-shot) 76.72
GSM8K (5-shot) 9.4
DROP (3-shot) 43.23

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric Value
Avg. 58.17
AI2 Reasoning Challenge (25-Shot) 63.14
HellaSwag (10-Shot) 83.64
MMLU (5-Shot) 59.91
TruthfulQA (0-shot) 56.21
Winogrande (5-shot) 76.72
GSM8k (5-shot) 9.40