Resolving Interference When Merging Models
Paper
•
2306.01708
•
Published
•
15
This is a merge of pre-trained language models created using mergekit.
This model was merged using the TIES merge method using gz987/qwen2.5-7b-cabs-v0.3 as a base.
The following models were included in the merge:
The following YAML configuration was used to produce this model:
models:
- model: gz987/qwen2.5-7b-cabs-v0.3
#no parameters necessary for base model
- model: suayptalha/Clarus-7B-v0.1
parameters:
density: 0.2
weight: 0.2
- model: Xiaojian9992024/Qwen2.5-THREADRIPPER-Small
parameters:
density: 0.2
weight: 0.2
- model: rombodawg/Rombos-LLM-V2.5-Qwen-7b
parameters:
density: 0.2
weight: 0.2
- model: prithivMLmods/WebMind-7B-v0.1
parameters:
density: 0.2
weight: 0.2
- model: fblgit/cybertron-v4-qw7B-MGS
parameters:
density: 0.2
weight: 0.2
merge_method: ties
base_model: gz987/qwen2.5-7b-cabs-v0.3
parameters:
normalize: false
int8_mask: true
dtype: bfloat16
Detailed results can be found here! Summarized results can be found here!
| Metric | Value (%) |
|---|---|
| Average | 37.30 |
| IFEval (0-Shot) | 76.40 |
| BBH (3-Shot) | 36.62 |
| MATH Lvl 5 (4-Shot) | 48.79 |
| GPQA (0-shot) | 8.95 |
| MuSR (0-shot) | 15.51 |
| MMLU-PRO (5-shot) | 37.51 |