my-output
This is a merge of pre-trained language models created using mergekit.
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:
slices:
- sources:
- model: Qwen/Qwen2.5-1.5B
layer_range: [0, 28]
- model: Qwen/Qwen2.5-1.5B-Instruct
layer_range: [0, 28]
merge_method: slerp
base_model: Qwen/Qwen2.5-1.5B-Instruct
parameters:
t:
- filter: self_attn
value: [0, 0.25, 0.5, 0.75, 1]
- filter: mlp
value: [1, 0.75, 0.5, 0.25, 0]
- value: 0.5
dtype: bfloat16
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 14.67 |
| IFEval (0-Shot) | 27.95 |
| BBH (3-Shot) | 19.02 |
| MATH Lvl 5 (4-Shot) | 8.91 |
| GPQA (0-shot) | 4.25 |
| MuSR (0-shot) | 6.51 |
| MMLU-PRO (5-shot) | 21.36 |
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Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard27.950
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard19.020
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard8.910
- acc_norm on GPQA (0-shot)Open LLM Leaderboard4.250
- acc_norm on MuSR (0-shot)Open LLM Leaderboard6.510
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard21.360