Merge Models
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Models I merged using mergekit library
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3 items
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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 8B parameters and #5 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