Ph3della5-14B / README.md
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metadata
license: apache-2.0
library_name: transformers
tags:
  - mergekit
  - merge
base_model:
  - jpacifico/Chocolatine-14B-Instruct-DPO-v1.2
  - jpacifico/Chocolatine-14B-Instruct-DPO-v1.1
model-index:
  - name: Ph3della5-14B
    results:
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: IFEval (0-Shot)
          type: HuggingFaceH4/ifeval
          args:
            num_few_shot: 0
        metrics:
          - type: inst_level_strict_acc and prompt_level_strict_acc
            value: 47.99
            name: strict accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=allknowingroger/Ph3della5-14B
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: BBH (3-Shot)
          type: BBH
          args:
            num_few_shot: 3
        metrics:
          - type: acc_norm
            value: 48.41
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=allknowingroger/Ph3della5-14B
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MATH Lvl 5 (4-Shot)
          type: hendrycks/competition_math
          args:
            num_few_shot: 4
        metrics:
          - type: exact_match
            value: 14.35
            name: exact match
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=allknowingroger/Ph3della5-14B
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: GPQA (0-shot)
          type: Idavidrein/gpqa
          args:
            num_few_shot: 0
        metrics:
          - type: acc_norm
            value: 12.3
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=allknowingroger/Ph3della5-14B
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MuSR (0-shot)
          type: TAUR-Lab/MuSR
          args:
            num_few_shot: 0
        metrics:
          - type: acc_norm
            value: 14.36
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=allknowingroger/Ph3della5-14B
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MMLU-PRO (5-shot)
          type: TIGER-Lab/MMLU-Pro
          config: main
          split: test
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 42.08
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=allknowingroger/Ph3della5-14B
          name: Open LLM Leaderboard

merge

This is a merge of pre-trained language models created using mergekit.

Merge Details

Merge Method

This model was merged using the della_linear merge method using jpacifico/Chocolatine-14B-Instruct-DPO-v1.2 as a base.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: jpacifico/Chocolatine-14B-Instruct-DPO-v1.2
    parameters:
      weight: 0.5
      density: 0.8
  - model: jpacifico/Chocolatine-14B-Instruct-DPO-v1.1
    parameters:
      weight: 0.5
      density: 0.8
merge_method: della_linear
base_model: jpacifico/Chocolatine-14B-Instruct-DPO-v1.2
parameters:
  epsilon: 0.05
  lambda: 1
  int8_mask: true
dtype: float16
tokenzer_source: union

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric Value
Avg. 29.92
IFEval (0-Shot) 47.99
BBH (3-Shot) 48.41
MATH Lvl 5 (4-Shot) 14.35
GPQA (0-shot) 12.30
MuSR (0-shot) 14.36
MMLU-PRO (5-shot) 42.08