merge
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the task arithmetic merge method using DreadPoor/Aurora_faustus-8B-LINEAR + grimjim/Llama-3-Instruct-abliteration-LoRA-8B 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: DreadPoor/Aurora_faustus-8B-LINEAR+grimjim/Llama-3-Instruct-abliteration-LoRA-8B
dtype: bfloat16
merge_method: task_arithmetic
parameters:
normalize: false
slices:
- sources:
- layer_range: [0, 32]
model: DreadPoor/Aurora_faustus-8B-LINEAR+grimjim/Llama-3-Instruct-abliteration-LoRA-8B
parameters:
weight: 1.0
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 28.80 |
| IFEval (0-Shot) | 75.27 |
| BBH (3-Shot) | 34.20 |
| MATH Lvl 5 (4-Shot) | 12.92 |
| GPQA (0-shot) | 6.94 |
| MuSR (0-shot) | 13.78 |
| MMLU-PRO (5-shot) | 29.70 |
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Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard75.270
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard34.200
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard12.920
- acc_norm on GPQA (0-shot)Open LLM Leaderboard6.940
- acc_norm on MuSR (0-shot)Open LLM Leaderboard13.780
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard29.700