llama-3-stinky-v2-8B
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 flammenai/Mahou-1.1-llama3-8B as a base.
Models Merged
The following models were included in the merge:
- mlabonne/ChimeraLlama-3-8B-v2
- grimjim/llama-3-merge-pp-instruct-8B
- grimjim/llama-3-merge-virt-req-8B
- uygarkurt/llama-3-merged-linear
- jeiku/Orthocopter_8B
- grimjim/llama-3-nvidia-ChatQA-1.5-8B
- openlynn/Llama-3-Soliloquy-8B-v2
- VAGOsolutions/Llama-3-SauerkrautLM-8b-Instruct
- nbeerbower/llama-3-stella-8B
- cloudyu/Meta-Llama-3-8B-Instruct-DPO
- NeverSleep/Llama-3-Lumimaid-8B-v0.1-OAS
- flammenai/Mahou-1.0-llama3-8B
Configuration
The following YAML configuration was used to produce this model:
models:
- model: mlabonne/ChimeraLlama-3-8B-v2
- model: cloudyu/Meta-Llama-3-8B-Instruct-DPO
- model: nbeerbower/llama-3-stella-8B
- model: VAGOsolutions/Llama-3-SauerkrautLM-8b-Instruct
- model: uygarkurt/llama-3-merged-linear
- model: openlynn/Llama-3-Soliloquy-8B-v2
- model: grimjim/llama-3-merge-pp-instruct-8B
- model: NeverSleep/Llama-3-Lumimaid-8B-v0.1-OAS
- model: grimjim/llama-3-merge-virt-req-8B
- model: jeiku/Orthocopter_8B
- model: grimjim/llama-3-nvidia-ChatQA-1.5-8B
- model: flammenai/Mahou-1.0-llama3-8B
merge_method: model_stock
base_model: flammenai/Mahou-1.1-llama3-8B
dtype: bfloat16
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 70.27 |
| AI2 Reasoning Challenge (25-Shot) | 66.98 |
| HellaSwag (10-Shot) | 83.20 |
| MMLU (5-Shot) | 68.33 |
| TruthfulQA (0-shot) | 55.83 |
| Winogrande (5-shot) | 77.51 |
| GSM8k (5-shot) | 69.75 |
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Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard66.980
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard83.200
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard68.330
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard55.830
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard77.510
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard69.750