sthenno/tempesthenno-ppo-ckpt40

tempesthenno--nuslerp (BASE MODEL)

This is a merge of pre-trained language models created using mergekit.

Merge Details

Merge Method

This model was merged using the NuSLERP merge method.

Models Merged

The following models were included in the merge:

• /Users/sthenno/models/tempesthenno--converge-dtask
• /Users/sthenno/models/tempesthenno--converge-breadcrumbs

Configuration

The following YAML configuration was used to produce this model:

name: tempesthenno--nuslerp
merge_method: nuslerp
tokenizer:
  source: /Users/sthenno/models/tempesthenno--converge-dtask
chat_template: "chatml"
dtype: float32
out_dtype: bfloat16
parameters:
  int8_mask: false
  normalize: true
  rescale: false
slices:
  - sources:
      - model: /Users/sthenno/models/tempesthenno--converge-dtask
        layer_range: [0, 8]
        parameters:
          weight: 0.65
          nuslerp_flatten: false
          nuslerp_row_wise: true
      - model: /Users/sthenno/models/tempesthenno--converge-breadcrumbs
        layer_range: [0, 8]
        parameters:
          weight: 0.35
          nuslerp_flatten: false
          nuslerp_row_wise: true
  - sources:
      - model: /Users/sthenno/models/tempesthenno--converge-dtask
        layer_range: [8, 16]
        parameters:
          weight: 0.60
          nuslerp_flatten: false
          nuslerp_row_wise: true
      - model: /Users/sthenno/models/tempesthenno--converge-breadcrumbs
        layer_range: [8, 16]
        parameters:
          weight: 0.40
          nuslerp_flatten: false
          nuslerp_row_wise: true
  - sources:
      - model: /Users/sthenno/models/tempesthenno--converge-dtask
        layer_range: [16, 24]
        parameters:
          weight: 0.55
          nuslerp_flatten: false
          nuslerp_row_wise: false
      - model: /Users/sthenno/models/tempesthenno--converge-breadcrumbs
        layer_range: [16, 24]
        parameters:
          weight: 0.45
          nuslerp_flatten: false
          nuslerp_row_wise: false
  - sources:
      - model: /Users/sthenno/models/tempesthenno--converge-dtask
        layer_range: [24, 32]
        parameters:
          weight: 0.50
          nuslerp_flatten: false
          nuslerp_row_wise: false
      - model: /Users/sthenno/models/tempesthenno--converge-breadcrumbs
        layer_range: [24, 32]
        parameters:
          weight: 0.50
          nuslerp_flatten: false
          nuslerp_row_wise: false
  - sources:
      - model: /Users/sthenno/models/tempesthenno--converge-dtask
        layer_range: [32, 40]
        parameters:
          weight: 0.45
          nuslerp_flatten: true
      - model: /Users/sthenno/models/tempesthenno--converge-breadcrumbs
        layer_range: [32, 40]
        parameters:
          weight: 0.55
          nuslerp_flatten: true
  - sources:
      - model: /Users/sthenno/models/tempesthenno--converge-dtask
        layer_range: [40, 48]
        parameters:
          weight: 0.40
          nuslerp_flatten: true
      - model: /Users/sthenno/models/tempesthenno--converge-breadcrumbs
        layer_range: [40, 48]
        parameters:
          weight: 0.60
          nuslerp_flatten: true

Open LLM Leaderboard Evaluation Results

Metric	Value
Avg.	40.55
IFEval (0-Shot)	79.23
BBH (3-Shot)	50.57
MATH Lvl 5 (4-Shot)	34.21
GPQA (0-shot)	17.00
MuSR (0-shot)	14.56
MMLU-PRO (5-shot)	47.69

Refined:

Metric	Value
Avg.	42.74
IFEval (0-Shot)	79.23
BBH (3-Shot)	50.57
MATH Lvl 5 (4-Shot)	47.36
GPQA (0-shot)	17.00
MuSR (0-shot)	14.56
MMLU-PRO (5-shot)	47.69