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Adding Evaluation Results (#2)
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---
library_name: transformers
tags:
- mergekit
- merge
base_model:
- nbeerbower/mistral-nemo-gutenberg-12B-v3
- nbeerbower/mistral-nemo-gutenberg-12B-v4
- nbeerbower/Lyra-Gutenberg-mistral-nemo-12B
- nbeerbower/mistral-nemo-gutenberg-12B
model-index:
- name: Gutensuppe-mistral-nemo-12B
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: IFEval (0-Shot)
type: HuggingFaceH4/ifeval
args:
num_few_shot: 0
metrics:
- type: inst_level_strict_acc and prompt_level_strict_acc
value: 29.16
name: strict accuracy
source:
url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=nbeerbower/Gutensuppe-mistral-nemo-12B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: BBH (3-Shot)
type: BBH
args:
num_few_shot: 3
metrics:
- type: acc_norm
value: 35.57
name: normalized accuracy
source:
url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=nbeerbower/Gutensuppe-mistral-nemo-12B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MATH Lvl 5 (4-Shot)
type: hendrycks/competition_math
args:
num_few_shot: 4
metrics:
- type: exact_match
value: 11.03
name: exact match
source:
url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=nbeerbower/Gutensuppe-mistral-nemo-12B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GPQA (0-shot)
type: Idavidrein/gpqa
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 11.63
name: acc_norm
source:
url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=nbeerbower/Gutensuppe-mistral-nemo-12B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MuSR (0-shot)
type: TAUR-Lab/MuSR
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 14.33
name: acc_norm
source:
url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=nbeerbower/Gutensuppe-mistral-nemo-12B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU-PRO (5-shot)
type: TIGER-Lab/MMLU-Pro
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 29.78
name: accuracy
source:
url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=nbeerbower/Gutensuppe-mistral-nemo-12B
name: Open LLM Leaderboard
---
# Gutensuppe-mistral-nemo-12B
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the [Model Stock](https://arxiv.org/abs/2403.19522) merge method using [nbeerbower/mistral-nemo-gutenberg-12B](https://huggingface.co./nbeerbower/mistral-nemo-gutenberg-12B) as a base.
### Models Merged
The following models were included in the merge:
* [nbeerbower/mistral-nemo-gutenberg-12B-v3](https://huggingface.co./nbeerbower/mistral-nemo-gutenberg-12B-v3)
* [nbeerbower/mistral-nemo-gutenberg-12B-v4](https://huggingface.co./nbeerbower/mistral-nemo-gutenberg-12B-v4)
* [nbeerbower/Lyra-Gutenberg-mistral-nemo-12B](https://huggingface.co./nbeerbower/Lyra-Gutenberg-mistral-nemo-12B)
### Configuration
The following YAML configuration was used to produce this model:
```yaml
models:
- model: nbeerbower/Lyra-Gutenberg-mistral-nemo-12B
- model: nbeerbower/mistral-nemo-gutenberg-12B-v4
- model: nbeerbower/mistral-nemo-gutenberg-12B-v3
- model: nbeerbower/mistral-nemo-gutenberg-12B
merge_method: model_stock
base_model: nbeerbower/mistral-nemo-gutenberg-12B
dtype: bfloat16
```
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co./datasets/open-llm-leaderboard/details_nbeerbower__Gutensuppe-mistral-nemo-12B)
| Metric |Value|
|-------------------|----:|
|Avg. |21.92|
|IFEval (0-Shot) |29.16|
|BBH (3-Shot) |35.57|
|MATH Lvl 5 (4-Shot)|11.03|
|GPQA (0-shot) |11.63|
|MuSR (0-shot) |14.33|
|MMLU-PRO (5-shot) |29.78|