metadata
library_name: transformers
tags:
- mergekit
- merge
base_model:
- Qwen/Qwen2.5-7B-Instruct
- bunnycore/Qwen-2.5-7B-R1-Stock
- Xiaojian9992024/Qwen2.5-Dyanka-7B-Preview
- suayptalha/Clarus-7B-v0.3
- bunnycore/Qwen-2.5-7b-s1k-lora_model
- Xiaojian9992024/Qwen2.5-Dyanka-7B-Preview
- bunnycore/Qwen-2.5-7b-s1k-lora_model
- bunnycore/QandoraExp-7B
model-index:
- name: Qwen2.5-7B-Instruct-Merge-Stock-v0.1
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: 75.09
name: strict accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Qwen2.5-7B-Instruct-Merge-Stock-v0.1
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: 36.4
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Qwen2.5-7B-Instruct-Merge-Stock-v0.1
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: 48.94
name: exact match
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Qwen2.5-7B-Instruct-Merge-Stock-v0.1
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: 7.16
name: acc_norm
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Qwen2.5-7B-Instruct-Merge-Stock-v0.1
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: 11.69
name: acc_norm
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Qwen2.5-7B-Instruct-Merge-Stock-v0.1
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: 37.59
name: accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=bunnycore/Qwen2.5-7B-Instruct-Merge-Stock-v0.1
name: Open LLM Leaderboard
Thinking Mode:
Think about the reasoning process in the mind first, then provide the answer.
The reasoning process should be wrapped within <think> </think> tags, then provide the answer after that, i.e., <think> reasoning process here </think> answer.
Merge Method
This model was merged using the Model Stock merge method using Qwen/Qwen2.5-7B-Instruct as a base.
Models Merged
The following models were included in the merge:
- bunnycore/Qwen-2.5-7B-R1-Stock
- Xiaojian9992024/Qwen2.5-Dyanka-7B-Preview
- suayptalha/Clarus-7B-v0.3 + bunnycore/Qwen-2.5-7b-s1k-lora_model
- Xiaojian9992024/Qwen2.5-Dyanka-7B-Preview + bunnycore/Qwen-2.5-7b-s1k-lora_model
- bunnycore/QandoraExp-7B
Configuration
The following YAML configuration was used to produce this model:
models:
- model: Xiaojian9992024/Qwen2.5-Dyanka-7B-Preview+bunnycore/Qwen-2.5-7b-s1k-lora_model
parameters:
weight: 0.5
- model: bunnycore/QandoraExp-7B
- model: bunnycore/Qwen-2.5-7B-R1-Stock
- model: Xiaojian9992024/Qwen2.5-Dyanka-7B-Preview
- model: suayptalha/Clarus-7B-v0.3+bunnycore/Qwen-2.5-7b-s1k-lora_model
base_model: Qwen/Qwen2.5-7B-Instruct
merge_method: model_stock
parameters:
dtype: bfloat16
tokenizer_source: Qwen/Qwen2.5-7B-Instruct
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 36.14 |
IFEval (0-Shot) | 75.09 |
BBH (3-Shot) | 36.40 |
MATH Lvl 5 (4-Shot) | 48.94 |
GPQA (0-shot) | 7.16 |
MuSR (0-shot) | 11.69 |
MMLU-PRO (5-shot) | 37.59 |