Iambe-20b-DARE-v2 / README.md
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metadata
language:
  - en
license: cc-by-nc-4.0
model-index:
  - name: Iambe-20b-DARE-v2
    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: 62.8
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=athirdpath/Iambe-20b-DARE-v2
          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: 84.53
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=athirdpath/Iambe-20b-DARE-v2
          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: 60.45
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=athirdpath/Iambe-20b-DARE-v2
          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: 53.85
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=athirdpath/Iambe-20b-DARE-v2
          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: 77.03
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=athirdpath/Iambe-20b-DARE-v2
          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: 33.28
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=athirdpath/Iambe-20b-DARE-v2
          name: Open LLM Leaderboard

Strange quirk: This model seems to need a context size of EXACTLY 4096 ONLY. I'm assuming this is a dares_ties effect?

Iambe-20b-DARE-v2

Alpaca prompt formatting

Description

Named after a charming daughter of Echo and Pan in Greek myth, Iambe-20b-DARE-v2 is an improved DARE merge building on my recent experiments.

Iambe is intended to have the best realistically possible understanding of anatomy and of a scene's state for a 20b merge, while remaining personable and authentic in "voice".

Update Methodology

Noromaid and the general "no-robots" vibe didn't come through like I'd hoped in v1. My hypothesis is that the "soul" MythoMax and Noromaid have is probably distributed widely over many low-value deltas, due to the "ephemeral" nature of such a thing.

My old base model was likely giving DARE conniption fits, so I replaced that with a truly vanilla 20b base model.

CleverGirl was updated to the DARE version, as Sir Hillary said, simply because it was there.

Without a large base of dare_ties models to compare to, I'm basically feeling my way through this intuitively, so here's to good results!

Recipe

merge_method: dare_ties

  • base_model: athirdpath/BigLlama-20b-v1.1

  • model: Noromaid-20b-v0.1.1

    weight: 0.38 / density: 0.60

  • model: athirdpath/athirdpath/Eileithyia-20b

    weight: 0.22 / density: 0.40

  • model: athirdpath/CleverGirl-20b-Blended-v1.1-DARE

    weight: 0.40 / density: 0.33

int8_mask: true

dtype: bfloat16

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric Value
Avg. 61.99
AI2 Reasoning Challenge (25-Shot) 62.80
HellaSwag (10-Shot) 84.53
MMLU (5-Shot) 60.45
TruthfulQA (0-shot) 53.85
Winogrande (5-shot) 77.03
GSM8k (5-shot) 33.28