Mirrored mergekit-ready models
Collection
Mirrored models tweaked to be more friendly for mergekit. No pickles allowed.
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lemon07r/Gemma-2-Ataraxy-v4c-9B, fixed
This is a merge of pre-trained language models created using mergekit.
Excess lm_head.weight tensor weights have been trimmed away from the weights at lemon07r/Gemma-2-Ataraxy-v4c-9B.
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: zelk12/recoilme-gemma-2-Ataraxy-9B-v0.1-t0.25
dtype: bfloat16
merge_method: slerp
parameters:
t: 0.25
slices:
- sources:
- layer_range: [0, 42]
model: zelk12/recoilme-gemma-2-Ataraxy-9B-v0.1-t0.25
- layer_range: [0, 42]
model: lemon07r/Gemma-2-Ataraxy-v3b-9B
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 32.63 |
| IFEval (0-Shot) | 69.45 |
| BBH (3-Shot) | 44.13 |
| MATH Lvl 5 (4-Shot) | 17.98 |
| GPQA (0-shot) | 11.19 |
| MuSR (0-shot) | 15.30 |
| MMLU-PRO (5-shot) | 37.72 |
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Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard69.450
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard44.130
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard17.980
- acc_norm on GPQA (0-shot)Open LLM Leaderboard11.190
- acc_norm on MuSR (0-shot)Open LLM Leaderboard15.300
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard37.720