Editing Models with Task Arithmetic
Paper
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2212.04089
•
Published
•
7
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 jpacifico/Chocolatine-14B-Instruct-DPO-v1.2 as a base.
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
models:
- model: jpacifico/Chocolatine-14B-Instruct-DPO-v1.2
parameters:
weight: 1.0
- model: failspy/Phi-3-medium-4k-instruct-abliterated-v3
parameters:
weight: 1.0
- model: jpacifico/Chocolatine-14B-Instruct-4k-DPO
parameters:
weight: 1.0
merge_method: task_arithmetic
base_model: jpacifico/Chocolatine-14B-Instruct-DPO-v1.2
parameters:
normalize: true
dtype: float16
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 30.08 |
| IFEval (0-Shot) | 46.95 |
| BBH (3-Shot) | 47.93 |
| MATH Lvl 5 (4-Shot) | 13.90 |
| GPQA (0-shot) | 13.42 |
| MuSR (0-shot) | 16.81 |
| MMLU-PRO (5-shot) | 41.49 |
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Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard46.950
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard47.930
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard13.900
- acc_norm on GPQA (0-shot)Open LLM Leaderboard13.420
- acc_norm on MuSR (0-shot)Open LLM Leaderboard16.810
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard41.490