merge
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the breadcrumbs_ties merge method using lemon07r/Gemma-2-Ataraxy-9B as a base.
Models Merged
The following models were included in the merge:
- wzhouad/gemma-2-9b-it-WPO-HB
- rtzr/ko-gemma-2-9b-it + ghost613/gemma9_on_korean_summary_events
- rtzr/ko-gemma-2-9b-it
Configuration
The following YAML configuration was used to produce this model:
slices:
- sources:
- model: lemon07r/Gemma-2-Ataraxy-9B
layer_range: [0, 42]
parameters:
weight: 1
density: 0.7
gamma: 0.03
- model: wzhouad/gemma-2-9b-it-WPO-HB
layer_range: [0, 42]
parameters:
weight: 1
density: 0.42
gamma: 0.03
- model: rtzr/ko-gemma-2-9b-it
layer_range: [0, 42]
parameters:
weight: 1
density: 0.42
gamma: 0.03
- model: rtzr/ko-gemma-2-9b-it+ghost613/gemma9_on_korean_summary_events # lora model loading
layer_range: [0, 42]
parameters:
weight: 1
density: 0.42
gamma: 0.03
merge_method: breadcrumbs_ties
base_model: lemon07r/Gemma-2-Ataraxy-9B
dtype: bfloat16
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 25.94 |
IFEval (0-Shot) | 64.16 |
BBH (3-Shot) | 38.79 |
MATH Lvl 5 (4-Shot) | 0.15 |
GPQA (0-shot) | 11.41 |
MuSR (0-shot) | 9.12 |
MMLU-PRO (5-shot) | 31.99 |
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Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard64.160
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard38.790
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard0.150
- acc_norm on GPQA (0-shot)Open LLM Leaderboard11.410
- acc_norm on MuSR (0-shot)Open LLM Leaderboard9.120
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard31.990