Mistral-test-case-4 / README.md
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metadata
language:
  - en
license: apache-2.0
datasets:
  - Open-Orca/OpenOrca
model-index:
  - name: Mistral-7B-attention-100000
    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: 52.99
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=NLUHOPOE/Mistral-7B-attention-100000
          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: 78.54
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=NLUHOPOE/Mistral-7B-attention-100000
          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: 54.79
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=NLUHOPOE/Mistral-7B-attention-100000
          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: 45.37
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=NLUHOPOE/Mistral-7B-attention-100000
          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: 75.61
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=NLUHOPOE/Mistral-7B-attention-100000
          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: 16.98
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=NLUHOPOE/Mistral-7B-attention-100000
          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. 54.05
AI2 Reasoning Challenge (25-Shot) 52.99
HellaSwag (10-Shot) 78.54
MMLU (5-Shot) 54.79
TruthfulQA (0-shot) 45.37
Winogrande (5-shot) 75.61
GSM8k (5-shot) 16.98