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: jpacifico/Chocolatine-3B-Instruct-DPO-Revised
layer_range: [0, 32]
- model: microsoft/Phi-3.5-mini-instruct
layer_range: [0, 32]
merge_method: slerp
base_model: jpacifico/Chocolatine-3B-Instruct-DPO-Revised
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. | 21.88 |
IFEval (0-Shot) | 27.22 |
BBH (3-Shot) | 35.70 |
MATH Lvl 5 (4-Shot) | 8.91 |
GPQA (0-shot) | 9.28 |
MuSR (0-shot) | 18.22 |
MMLU-PRO (5-shot) | 31.96 |
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Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard27.220
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard35.700
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard8.910
- acc_norm on GPQA (0-shot)Open LLM Leaderboard9.280
- acc_norm on MuSR (0-shot)Open LLM Leaderboard18.220
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard31.960