merge
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the DARE TIES merge method using NousResearch/Meta-Llama-3-8B as a base.
Models Merged
The following models were included in the merge:
Configuration
The following YAML configuration was used to produce this model:
models:
- model: NousResearch/Meta-Llama-3-8B-Instruct
parameters:
density: 1
weight: 1
- model: Dampfinchen/Llama-3-8B-Ultra-Instruct
parameters:
density: 0.5
weight: 0.2
merge_method: dare_ties
base_model: NousResearch/Meta-Llama-3-8B
dtype: bfloat16
Test of salt sprinkle methode. The goal is to retain all of L3 Instruct's capabilities while adding better RP, RAG, German and story writing capabilities in the form of Ultra Instruct. Model may generate harmful responses, I'm not responsible for what you do with this model.
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 67.61 |
| AI2 Reasoning Challenge (25-Shot) | 61.35 |
| HellaSwag (10-Shot) | 77.76 |
| MMLU (5-Shot) | 67.88 |
| TruthfulQA (0-shot) | 52.82 |
| Winogrande (5-shot) | 74.98 |
| GSM8k (5-shot) | 70.89 |
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Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard61.350
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard77.760
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard67.880
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard52.820
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard74.980
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard70.890