Model Stock: All we need is just a few fine-tuned models
Paper
• 2403.19522 • Published
• 13
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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 Model Stock merge method using meditsolutions/Llama-3.1-MedIT-SUN-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:
merge_method: model_stock
models:
- model: mlabonne/Hermes-3-Llama-3.1-8B-lorablated
parameters:
weight: 1.0
- model: huihui-ai/Dolphin3.0-Llama3.1-8B-abliterated
parameters:
weight: 1.0
base_model: meditsolutions/Llama-3.1-MedIT-SUN-8B
dtype: bfloat16
normalize: true
chat_template: auto
tokenizer:
source: union
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 11.98 |
| IFEval (0-Shot) | 18.85 |
| BBH (3-Shot) | 20.44 |
| MATH Lvl 5 (4-Shot) | 0.15 |
| GPQA (0-shot) | 3.69 |
| MuSR (0-shot) | 6.62 |
| MMLU-PRO (5-shot) | 22.15 |
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Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard18.850
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard20.440
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard0.150
- acc_norm on GPQA (0-shot)Open LLM Leaderboard3.690
- acc_norm on MuSR (0-shot)Open LLM Leaderboard6.620
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard22.150