update: now checking the evaluations without chat templates
tempesthenno-nuslerp-0124
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-breadcrumbs
- /Users/sthenno/models/tempesthenno--converge-dtask
Configuration
The following YAML configuration was used to produce this model:
name: tempesthenno-nuslerp-0124
merge_method: nuslerp
tokenizer:
source: union
chat_template: "chatml"
dtype: float32
out_dtype: bfloat16
parameters:
int8_mask: true
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
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 40.97 |
IFEval (0-Shot) | 70.04 |
BBH (3-Shot) | 49.28 |
MATH Lvl 5 (4-Shot) | 39.27 |
GPQA (0-shot) | 18.68 |
MuSR (0-shot) | 20.21 |
MMLU-PRO (5-shot) | 48.36 |
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Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard70.040
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard49.280
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard39.270
- acc_norm on GPQA (0-shot)Open LLM Leaderboard18.680
- acc_norm on MuSR (0-shot)Open LLM Leaderboard20.210
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard48.360