merge
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the DARE TIES merge method using NousResearch/Meta-Llama-3-8B as a base.
Models Merged
The following models were included in the merge:
- Locutusque/Llama-3-NeuralHercules-5.0-8B
- NousResearch/Hermes-2-Theta-Llama-3-8B
- Locutusque/llama-3-neural-chat-v2.2-8b
Configuration
The following YAML configuration was used to produce this model:
models:
- model: NousResearch/Meta-Llama-3-8B
# No parameters necessary for base model
- model: NousResearch/Hermes-2-Theta-Llama-3-8B
parameters:
density: 0.6
weight: 0.55
- model: Locutusque/llama-3-neural-chat-v2.2-8b
parameters:
density: 0.55
weight: 0.4
- model: Locutusque/Llama-3-NeuralHercules-5.0-8B
parameters:
density: 0.65
weight: 0.6
merge_method: dare_ties
base_model: NousResearch/Meta-Llama-3-8B
parameters:
int8_mask: true
dtype: bfloat16
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 20.22 |
IFEval (0-Shot) | 53.71 |
BBH (3-Shot) | 26.92 |
MATH Lvl 5 (4-Shot) | 6.87 |
GPQA (0-shot) | 1.68 |
MuSR (0-shot) | 8.07 |
MMLU-PRO (5-shot) | 24.07 |
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Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard53.710
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard26.920
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard6.870
- acc_norm on GPQA (0-shot)Open LLM Leaderboard1.680
- acc_norm on MuSR (0-shot)Open LLM Leaderboard8.070
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard24.070