README.md

metadata

language:
  - en
license: mit
datasets:
  - Sao10K/Claude-3-Opus-Instruct-15K
  - abacusai/SystemChat-1.1
  - Ba2han/DollyLlama-5k
model-index:
  - name: Llama-Phi-3_DoRA
    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: 62.29
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Ba2han/Llama-Phi-3_DoRA
          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: 79.08
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Ba2han/Llama-Phi-3_DoRA
          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: 69.44
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Ba2han/Llama-Phi-3_DoRA
          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: 54.08
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Ba2han/Llama-Phi-3_DoRA
          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: 73.4
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Ba2han/Llama-Phi-3_DoRA
          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: 68.01
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Ba2han/Llama-Phi-3_DoRA
          name: Open LLM Leaderboard

We have Llama-3 at home!

Highest PHI-3-Mini MMLU and Winogrande on the board!

The model has been trained on filtered versions of tagged datasets, as well as a few thousand more examples generated with llama-3-70B.

Use Zephyr template with any system message. Default system message should be:

You are a smart, friendly and helpful assistant.

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	67.72
AI2 Reasoning Challenge (25-Shot)	62.29
HellaSwag (10-Shot)	79.08
MMLU (5-Shot)	69.44
TruthfulQA (0-shot)	54.08
Winogrande (5-shot)	73.40
GSM8k (5-shot)	68.01