Resolving Interference When Merging Models
Paper • 2306.01708 • Published • 18
Meta-Llama-3.1-8B-Instruct-HalfAbliterated-TIES
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 meta-llama/Meta-Llama-3.1-8B 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: meta-llama/Meta-Llama-3.1-8B
chat_template: auto
dtype: float16
merge_method: ties
models:
- model: mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated
parameters:
density: 0.5
weight: 0.5
- model: meta-llama/Meta-Llama-3.1-8B-Instruct
parameters:
density: 0.5
weight: 0.5
parameters:
int8_mask: true
normalize: false
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 20.77 |
| IFEval (0-Shot) | 45.51 |
| BBH (3-Shot) | 28.91 |
| MATH Lvl 5 (4-Shot) | 11.63 |
| GPQA (0-shot) | 2.24 |
| MuSR (0-shot) | 6.59 |
| MMLU-PRO (5-shot) | 29.76 |
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Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard45.510
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard28.910
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard11.630
- acc_norm on GPQA (0-shot)Open LLM Leaderboard2.240
- acc_norm on MuSR (0-shot)Open LLM Leaderboard6.590
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard29.760