README.md

metadata

language:
  - en
license: apache-2.0
library_name: transformers
tags:
  - mergekit
  - merge
base_model:
  - HumanLLMs/Human-Like-Qwen2.5-7B-Instruct
  - bunnycore/Qwen-2.5-7b-rp-lora
model-index:
  - name: Q2.5-Humane-RP
    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: 44.12
            name: strict accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Triangle104/Q2.5-Humane-RP
          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: 37.65
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Triangle104/Q2.5-Humane-RP
          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: 30.44
            name: exact match
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Triangle104/Q2.5-Humane-RP
          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: 9.17
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Triangle104/Q2.5-Humane-RP
          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: 15.33
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Triangle104/Q2.5-Humane-RP
          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: 38.8
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Triangle104/Q2.5-Humane-RP
          name: Open LLM Leaderboard

merge

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

Merge Details

Quant: https://huggingface.co/Triangle104/Q2.5-Humane-RP-Q4_K_M-GGUF

Merge Method

This model was merged using the passthrough merge method using HumanLLMs/Human-Like-Qwen2.5-7B-Instruct + bunnycore/Qwen-2.5-7b-rp-lora as a base.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

base_model: HumanLLMs/Human-Like-Qwen2.5-7B-Instruct+bunnycore/Qwen-2.5-7b-rp-lora
dtype: bfloat16
merge_method: passthrough
models:
  - model: HumanLLMs/Human-Like-Qwen2.5-7B-Instruct+bunnycore/Qwen-2.5-7b-rp-lora

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	29.25
IFEval (0-Shot)	44.12
BBH (3-Shot)	37.65
MATH Lvl 5 (4-Shot)	30.44
GPQA (0-shot)	9.17
MuSR (0-shot)	15.33
MMLU-PRO (5-shot)	38.80