README.md

metadata

language:
  - en
license: apache-2.0
datasets:
  - Open-Orca/OpenOrca
model-index:
  - name: llmdo-Mistral-7B-case-c-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: 62.03
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=juhwanlee/llmdo-Mistral-7B-case-c-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: 83.55
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=juhwanlee/llmdo-Mistral-7B-case-c-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: 62.69
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=juhwanlee/llmdo-Mistral-7B-case-c-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: 45.82
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=juhwanlee/llmdo-Mistral-7B-case-c-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: 79.08
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=juhwanlee/llmdo-Mistral-7B-case-c-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: 39.8
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=juhwanlee/llmdo-Mistral-7B-case-c-v1
          name: Open LLM Leaderboard

Model Details

• Model Description: This model is test for data ordering.
• Developed by: Juhwan Lee
• Model Type: Large Language Model

Model Architecture

This model is based on Mistral-7B-v0.1. We fine-tuning this model for data ordering task.

Mistral-7B-v0.1 is a transformer model, with the following architecture choices:

• Grouped-Query Attention
• Sliding-Window Attention
• Byte-fallback BPE tokenizer

Dataset

We random sample Open-Orca dataset. (We finetune the 100,000 dataset)

Guthub

https://github.com/trailerAI

License

Apache License 2.0

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	62.16
AI2 Reasoning Challenge (25-Shot)	62.03
HellaSwag (10-Shot)	83.55
MMLU (5-Shot)	62.69
TruthfulQA (0-shot)	45.82
Winogrande (5-shot)	79.08
GSM8k (5-shot)	39.80