Z-2-A.TEST-TEMP-MODEL
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:
- D:\VICIOUS_MESH-12B-OMEGA
- D:\jetreessence
Configuration
The following YAML configuration was used to produce this model:
models:
- model: "D:\\VICIOUS_MESH-12B-OMEGA"
- model: "D:\\jetreessence"
merge_method: slerp
base_model: "D:\\VICIOUS_MESH-12B-OMEGA"
dtype: bfloat16
parameters:
t: [0, 0.5, 1, 0.5, 0]
regularization:
- method: gradient_penalty
scale: 0.05
- method: weight_clipping
clip_range: [-0.15, 0.15]
- method: random_noise
scale: 0.01
- method: attention_dropout
scale: 0.02
postprocessing:
- operation: entropy_regularization
scale: 0.05
- operation: non_linear_scaling
parameters:
function: relu
- operation: sharpening
intensity: 0.6
- operation: gaussian_smoothing
sigma: 0.3
- operation: normalize
- operation: dynamic_scaling
scale_range: [0.98, 1.02]
- operation: smoothing
parameters:
adaptive: true
range: [0.98, 1.02]
kernel_size: 3
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 26.94 |
IFEval (0-Shot) | 66.02 |
BBH (3-Shot) | 31.36 |
MATH Lvl 5 (4-Shot) | 11.10 |
GPQA (0-shot) | 8.61 |
MuSR (0-shot) | 14.70 |
MMLU-PRO (5-shot) | 29.83 |
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Model tree for bamec66557/NameLess-12B-prob
Dataset used to train bamec66557/NameLess-12B-prob
Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard66.020
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard31.360
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard11.100
- acc_norm on GPQA (0-shot)Open LLM Leaderboard8.610
- acc_norm on MuSR (0-shot)Open LLM Leaderboard14.700
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard29.830