Untitled Model (1)
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the TIES merge method using unsloth/Meta-Llama-3.1-8B-Instruct as a base.
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
base_model: unsloth/Meta-Llama-3.1-8B-Instruct
dtype: bfloat16
merge_method: ties
parameters:
density: 1.0
weight: 1.0
slices:
- sources:
- layer_range: [0, 32]
model: T145/KRONOS-8B-V1-P2
parameters:
density: 1.0
weight: 1.0
- layer_range: [0, 32]
model: T145/KRONOS-8B-V1-P3
parameters:
density: 1.0
weight: 1.0
- layer_range: [0, 32]
model: mukaj/Llama-3.1-Hawkish-8B
parameters:
density: 1.0
weight: 1.0
- layer_range: [0, 32]
model: unsloth/Meta-Llama-3.1-8B-Instruct
tokenizer_source: base
Open LLM Leaderboard Evaluation Results
Detailed results can be found here! Summarized results can be found here!
Metric | % Value |
---|---|
Avg. | 24.49 |
IFEval (0-Shot) | 70.22 |
BBH (3-Shot) | 29.66 |
MATH Lvl 5 (4-Shot) | 5.51 |
GPQA (0-shot) | 3.91 |
MuSR (0-shot) | 9.81 |
MMLU-PRO (5-shot) | 27.79 |
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Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard70.220
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard29.660
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard5.510
- acc_norm on GPQA (0-shot)Open LLM Leaderboard3.910
- acc_norm on MuSR (0-shot)Open LLM Leaderboard9.810
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard27.790