merge
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-14B-Instruct-4k-DPO
layer_range: [0, 39]
- model: dnhkng/RYS-Phi-3-medium-4k-instruct
layer_range: [0, 39]
merge_method: slerp
base_model: jpacifico/Chocolatine-14B-Instruct-4k-DPO
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5
dtype: bfloat16
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 7.85 |
| IFEval (0-Shot) | 16.97 |
| BBH (3-Shot) | 10.64 |
| MATH Lvl 5 (4-Shot) | 0.00 |
| GPQA (0-shot) | 5.82 |
| MuSR (0-shot) | 5.59 |
| MMLU-PRO (5-shot) | 8.08 |
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Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard16.970
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard10.640
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard0.000
- acc_norm on GPQA (0-shot)Open LLM Leaderboard5.820
- acc_norm on MuSR (0-shot)Open LLM Leaderboard5.590
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard8.080