[GGUF]

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: bamec66557/mergekit-slerp-xjlmywj
        layer_range: [0, 20]
      - model: bamec66557/MISCHIEVOUS-12B-Mix_0.3v
        layer_range: [0, 20]
    parameters:
      t:
        - value: 0.8

  - sources:
      - model: bamec66557/mergekit-slerp-xjlmywj
        layer_range: [20, 40]
      - model: bamec66557/MISCHIEVOUS-12B-Mix_0.3v
        layer_range: [20, 40]
    parameters:
      t:
        - value: 1.0
        - filter: self_attn
          value: [0.8, 0.9, 1.0, 1.1, 1.2]

merge_method: slerp  # Preserve merge method

base_model: bamec66557/mergekit-slerp-xjlmywj  # Base model

dtype: bfloat16  # Data types for fast merges

# Additional options
regularization:
  - method: weight_clipping
    clip_range: [-0.1, 0.1]

postprocessing:
  - operation: gaussian_smoothing
    sigma: 1.5  # Gaussian smoothing intensity
  - operation: smoothing
    parameters:
      adaptive: true
      range: [0.8, 1.2]  # Adaptively adjust
      kernel_size: 5  # Smoothing larger ranges with increased kernel size
  - operation: normalize  # Normalise after merge

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric Value
Avg. 26.31
IFEval (0-Shot) 65.08
BBH (3-Shot) 30.60
MATH Lvl 5 (4-Shot) 11.48
GPQA (0-shot) 8.95
MuSR (0-shot) 11.97
MMLU-PRO (5-shot) 29.81
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Dataset used to train bamec66557/MISCHIEVOUS-12B-Mix_0.4v

Collection including bamec66557/MISCHIEVOUS-12B-Mix_0.4v

Evaluation results