README.md

metadata

language:
  - en
license: cc-by-nc-4.0
tags:
  - Math
  - merge
datasets:
  - meta-math/MetaMathQA
pipeline_tag: text-generation
base_model:
  - Q-bert/MetaMath-Cybertron
  - berkeley-nest/Starling-LM-7B-alpha
model-index:
  - name: MetaMath-Cybertron-Starling
    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: 67.75
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Q-bert/MetaMath-Cybertron-Starling
          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: 86.23
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Q-bert/MetaMath-Cybertron-Starling
          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: 65.24
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Q-bert/MetaMath-Cybertron-Starling
          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: 55.94
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Q-bert/MetaMath-Cybertron-Starling
          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: 81.45
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Q-bert/MetaMath-Cybertron-Starling
          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: 71.49
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Q-bert/MetaMath-Cybertron-Starling
          name: Open LLM Leaderboard

MetaMath-Cybertron-Starling

Merge Q-bert/MetaMath-Cybertron and berkeley-nest/Starling-LM-7B-alpha using slerp merge.

You can use ChatML format.

Open LLM Leaderboard Evaluation Results

Detailed results can be found Here

Metric	Value
Avg.	71.35
ARC (25-shot)	67.75
HellaSwag (10-shot)	86.23
MMLU (5-shot)	65.24
TruthfulQA (0-shot)	55.94
Winogrande (5-shot)	81.45
GSM8K (5-shot)	71.49

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	71.35
AI2 Reasoning Challenge (25-Shot)	67.75
HellaSwag (10-Shot)	86.23
MMLU (5-Shot)	65.24
TruthfulQA (0-shot)	55.94
Winogrande (5-shot)	81.45
GSM8k (5-shot)	71.49