DesivoMerge0.1 / README.md
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metadata
license: apache-2.0
tags:
  - merge
  - mergekit
model-index:
  - name: DesivoMerge0.1
    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: 65.87
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cris177/DesivoMerge0.1
          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: 85.39
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cris177/DesivoMerge0.1
          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: 64.35
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cris177/DesivoMerge0.1
          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: 55.36
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cris177/DesivoMerge0.1
          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: 78.53
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cris177/DesivoMerge0.1
          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: 58.53
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cris177/DesivoMerge0.1
          name: Open LLM Leaderboard

DesivoMerge0.1

DesivoMerge0.1 is a merge of a bunch of models using mergekit

The idea is to continuously merge models into a main model. The first merge is between open-orca-mistral-7B and open-hermes-7B, then I merged the resulting merge with the best performing 7B model on the open-llm leaderboard (TurdusBeagle-7B).

I will keep adding models to the merge until the average score of the models in the merge is lower than the score of the previous merge, in which case I will backtrack and find another model to merge.

I will try to avoid contaminated models by looking into each of the candidates before merging them.

🧩 Configuration

slices:
  - sources:
      - model: ./merge
        layer_range: [0, 32]
      - model: Azazelle/Argetsu
        layer_range: [0, 32]
merge_method: slerp
base_model: ./merge
tokenizer_source: base
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5
dtype: bfloat16

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric Value
Avg. 68.01
AI2 Reasoning Challenge (25-Shot) 65.87
HellaSwag (10-Shot) 85.39
MMLU (5-Shot) 64.35
TruthfulQA (0-shot) 55.36
Winogrande (5-shot) 78.53
GSM8k (5-shot) 58.53