BigWeave-v20-110b / README.md
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Adding Evaluation Results (#1)
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metadata
language:
  - en
license: unknown
tags:
  - frankenmerge
  - 110b
pipeline_tag: conversational
model-index:
  - name: BigWeave-v20-110b
    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: 68.17
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=llmixer/BigWeave-v20-110b
          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: 88.54
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=llmixer/BigWeave-v20-110b
          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: 70.51
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=llmixer/BigWeave-v20-110b
          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: 62.47
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=llmixer/BigWeave-v20-110b
          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: 82.08
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=llmixer/BigWeave-v20-110b
          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: 36.39
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=llmixer/BigWeave-v20-110b
          name: Open LLM Leaderboard

BigWeave v20 110b

The BigWeave models aim to experimentally identify merge settings for increasing model performance. The version number merely tracks various attempts and is not a quality indicator. Only results demonstrating good performance are retained and shared.

Prompting Format

Mistral, Vicuna and Alpaca.

Merge process

This is a merge of 152334H/miqu-1-70b-sf and lizpreciatior/lzlv_70b_fp16_hf. By conducting exl2 measurements, we identify the least important layers of lzlv. These least important layers are extended with layers in-between to create longer series of consecutive layers. These slices are then inserted into miqu.

Merge configuration:

slices:
  - sources:
      - model: 152334H/miqu-1-70b-sf
        layer_range: [0, 1]
      - model: lizpreciatior/lzlv_70b_fp16_hf
        layer_range: [0, 1]
        parameters:
          weight: 0
  - sources:
    - model: 152334H/miqu-1-70b-sf
      layer_range: [1,26]
  - sources:
    - model: lizpreciatior/lzlv_70b_fp16_hf
      layer_range: [9,44]
  - sources:
    - model: 152334H/miqu-1-70b-sf
      layer_range: [27,52]
  - sources:
    - model: lizpreciatior/lzlv_70b_fp16_hf
      layer_range: [45,60]
  - sources:
    - model: 152334H/miqu-1-70b-sf
      layer_range: [53,79]
  - sources:
      - model: 152334H/miqu-1-70b-sf
        layer_range: [79, 80]
      - model: lizpreciatior/lzlv_70b_fp16_hf
        layer_range: [79, 80]
        parameters:
          weight: 0
merge_method: linear
parameters:
  weight: 1.0
dtype: float16
tokenizer_source: 152334H/miqu-1-70b-sf

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric Value
Avg. 68.03
AI2 Reasoning Challenge (25-Shot) 68.17
HellaSwag (10-Shot) 88.54
MMLU (5-Shot) 70.51
TruthfulQA (0-shot) 62.47
Winogrande (5-shot) 82.08
GSM8k (5-shot) 36.39