merge
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the della merge method using Qwen/Qwen2.5-7B as a base.
Models Merged
The following models were included in the merge:
- Etherll/Qwen2.5-7B-della-test
- jeffmeloy/Qwen2.5-7B-nerd-uncensored-v1.0
- fblgit/cybertron-v4-qw7B-MGS
Configuration
The following YAML configuration was used to produce this model:
models:
- model: Etherll/Qwen2.5-7B-della-test
parameters:
weight: 1
density: 1
lambda: 0.9
- model: jeffmeloy/Qwen2.5-7B-nerd-uncensored-v1.0
parameters:
weight: 1
density: 1
lambda: 0.9
- model: fblgit/cybertron-v4-qw7B-MGS
parameters:
weight: 1
density: 1
lambda: 0.9
merge_method: della
base_model: Qwen/Qwen2.5-7B
parameters:
weight: 1
density: 1
lambda: 0.9
int8_mask: true
dtype: bfloat16
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 28.51 |
| IFEval (0-Shot) | 75.09 |
| BBH (3-Shot) | 35.92 |
| MATH Lvl 5 (4-Shot) | 0.91 |
| GPQA (0-shot) | 8.05 |
| MuSR (0-shot) | 13.20 |
| MMLU-PRO (5-shot) | 37.89 |
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Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard75.090
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard35.920
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard0.910
- acc_norm on GPQA (0-shot)Open LLM Leaderboard8.050
- acc_norm on MuSR (0-shot)Open LLM Leaderboard13.200
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard37.890