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This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the della merge method using unsloth/Meta-Llama-3.1-8B as a base.
Models Merged
The following models were included in the merge:
- DreadPoor/Spei_Meridiem-8B-model_stock
- DreadPoor/Aspire1.1-8B-model_stock
- DreadPoor/Heart_Stolen1.1-8B-Model_Stock
Configuration
The following YAML configuration was used to produce this model:
models:
- model: DreadPoor/Aspire1.1-8B-model_stock
parameters:
weight: 1.0
- model: DreadPoor/Spei_Meridiem-8B-model_stock
parameters:
weight: 1.0
- model: DreadPoor/Heart_Stolen1.1-8B-Model_Stock
parameters:
weight: 1.0
merge_method: della
base_model: unsloth/Meta-Llama-3.1-8B
parameters:
density: 1
lambda: 1.05
epsilon: 0.04
normalize: true
int8_mask: true
dtype: float32
out_dtype: bfloat16
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 29.18 |
| IFEval (0-Shot) | 72.35 |
| BBH (3-Shot) | 34.88 |
| MATH Lvl 5 (4-Shot) | 13.97 |
| GPQA (0-shot) | 8.61 |
| MuSR (0-shot) | 13.03 |
| MMLU-PRO (5-shot) | 32.26 |
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Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard72.350
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard34.880
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard13.970
- acc_norm on GPQA (0-shot)Open LLM Leaderboard8.610
- acc_norm on MuSR (0-shot)Open LLM Leaderboard13.030
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard32.260