Merge Models
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Models I merged using mergekit library
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Merged Model
This is a merge of pre-trained language models created using mergekit.
This model is currently ranked #3 on the Open LLM Leaderboard among models up to 13B parameters!
Merge Details
Merge Method
This model was merged using the SLERP merge method.
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
base_model: ZeroXClem/Qwen2.5-7B-HomerCreative-Mix
dtype: bfloat16
merge_method: slerp
parameters:
t:
- filter: self_attn
value: [0.0, 0.5, 0.3, 0.7, 1.0]
- filter: mlp
value: [1.0, 0.5, 0.7, 0.3, 0.0]
- value: 0.5
slices:
- sources:
- layer_range: [0, 28]
model: ZeroXClem/Qwen2.5-7B-HomerCreative-Mix
- layer_range: [0, 28]
model: ZeroXClem/Qwen2.5-7B-HomerAnvita-NerdMix
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 34.62 |
| IFEval (0-Shot) | 78.08 |
| BBH (3-Shot) | 36.98 |
| MATH Lvl 5 (4-Shot) | 31.04 |
| GPQA (0-shot) | 8.61 |
| MuSR (0-shot) | 14.73 |
| MMLU-PRO (5-shot) | 38.28 |
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Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard78.080
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard36.980
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard31.040
- acc_norm on GPQA (0-shot)Open LLM Leaderboard8.610
- acc_norm on MuSR (0-shot)Open LLM Leaderboard14.730
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard38.280