ZEUS-8B-V27 / README.md
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Adding Evaluation Results (#1)
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---
base_model:
- Skywork/Skywork-o1-Open-Llama-3.1-8B
- FreedomIntelligence/HuatuoGPT-o1-8B
- unsloth/Meta-Llama-3.1-8B-Instruct
- arcee-ai/Llama-3.1-SuperNova-Lite
- VAGOsolutions/Llama-3.1-SauerkrautLM-8b-Instruct
- Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2
- unsloth/Llama-3.1-Storm-8B
library_name: transformers
tags:
- mergekit
- merge
model-index:
- name: ZEUS-8B-V27
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: IFEval (0-Shot)
type: wis-k/instruction-following-eval
split: train
args:
num_few_shot: 0
metrics:
- type: inst_level_strict_acc and prompt_level_strict_acc
value: 65.44
name: averaged accuracy
source:
url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=T145%2FZEUS-8B-V27
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: BBH (3-Shot)
type: SaylorTwift/bbh
split: test
args:
num_few_shot: 3
metrics:
- type: acc_norm
value: 32.22
name: normalized accuracy
source:
url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=T145%2FZEUS-8B-V27
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MATH Lvl 5 (4-Shot)
type: lighteval/MATH-Hard
split: test
args:
num_few_shot: 4
metrics:
- type: exact_match
value: 11.93
name: exact match
source:
url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=T145%2FZEUS-8B-V27
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GPQA (0-shot)
type: Idavidrein/gpqa
split: train
args:
num_few_shot: 0
metrics:
- type: acc_norm
value: 7.72
name: acc_norm
source:
url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=T145%2FZEUS-8B-V27
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: 9.84
name: acc_norm
source:
url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=T145%2FZEUS-8B-V27
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: 32.25
name: accuracy
source:
url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=T145%2FZEUS-8B-V27
name: Open LLM Leaderboard
---
# ZEUS 8B V27
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 [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) merge method using [unsloth/Meta-Llama-3.1-8B-Instruct](https://huggingface.co./unsloth/Meta-Llama-3.1-8B-Instruct) as a base.
### Models Merged
The following models were included in the merge:
* [Skywork/Skywork-o1-Open-Llama-3.1-8B](https://huggingface.co./Skywork/Skywork-o1-Open-Llama-3.1-8B)
* [FreedomIntelligence/HuatuoGPT-o1-8B](https://huggingface.co./FreedomIntelligence/HuatuoGPT-o1-8B)
* [arcee-ai/Llama-3.1-SuperNova-Lite](https://huggingface.co./arcee-ai/Llama-3.1-SuperNova-Lite)
* [VAGOsolutions/Llama-3.1-SauerkrautLM-8b-Instruct](https://huggingface.co./VAGOsolutions/Llama-3.1-SauerkrautLM-8b-Instruct)
* [Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2](https://huggingface.co./Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2)
* [unsloth/Llama-3.1-Storm-8B](https://huggingface.co./unsloth/Llama-3.1-Storm-8B)
### Configuration
The following YAML configuration was used to produce this model:
```yaml
base_model: Skywork/Skywork-o1-Open-Llama-3.1-8B
dtype: bfloat16
merge_method: slerp
name: strawberry-patch
parameters:
t:
- value: 0.5
slices:
- sources:
- layer_range: [0, 32]
model: Skywork/Skywork-o1-Open-Llama-3.1-8B
- layer_range: [0, 32]
model: FreedomIntelligence/HuatuoGPT-o1-8B
---
base_model: unsloth/Meta-Llama-3.1-8B-Instruct
dtype: bfloat16
merge_method: dare_ties
parameters:
int8_mask: 1.0
normalize: 1.0
random_seed: 145.0
slices:
- sources:
- layer_range: [0, 32]
model: unsloth/Llama-3.1-Storm-8B
parameters:
density: 0.94
weight: 0.35
- layer_range: [0, 32]
model: arcee-ai/Llama-3.1-SuperNova-Lite
parameters:
density: 0.92
weight: 0.26
- layer_range: [0, 32]
model: VAGOsolutions/Llama-3.1-SauerkrautLM-8b-Instruct
parameters:
density: 0.91
weight:
- filter: layers.20.
value: 0.0
- filter: layers.21.
value: 0.0
- filter: layers.22.
value: 0.0
- filter: layers.23.
value: 0.0
- filter: layers.24.
value: 0.0
- filter: layers.25.
value: 0.0
- filter: layers.26.
value: 0.0
- filter: layers.27.
value: 0.0
- value: 0.2
- layer_range: [0, 32]
model: strawberry-patch
parameters:
density: 0.92
weight:
- filter: layers.20.
value: 0.2
- filter: layers.21.
value: 0.2
- filter: layers.22.
value: 0.2
- filter: layers.23.
value: 0.2
- filter: layers.24.
value: 0.2
- filter: layers.25.
value: 0.2
- filter: layers.26.
value: 0.2
- filter: layers.27.
value: 0.2
- value: 0.0
- layer_range: [0, 32]
model: Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2
parameters:
density: 0.93
weight: 0.19
- layer_range: [0, 32]
model: unsloth/Meta-Llama-3.1-8B-Instruct
tokenizer:
tokens:
<|begin_of_text|>:
force: true
source: unsloth/Meta-Llama-3.1-8B-Instruct
<|eot_id|>:
force: true
source: unsloth/Meta-Llama-3.1-8B-Instruct
<|finetune_right_pad_id|>:
force: true
source: unsloth/Meta-Llama-3.1-8B-Instruct
```
# [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/T145__ZEUS-8B-V27-details)!
Summarized results can be found [here](https://huggingface.co./datasets/open-llm-leaderboard/contents/viewer/default/train?q=T145%2FZEUS-8B-V27&sort[column]=Average%20%E2%AC%86%EF%B8%8F&sort[direction]=desc)!
| Metric |Value (%)|
|-------------------|--------:|
|**Average** | 26.57|
|IFEval (0-Shot) | 65.44|
|BBH (3-Shot) | 32.22|
|MATH Lvl 5 (4-Shot)| 11.93|
|GPQA (0-shot) | 7.72|
|MuSR (0-shot) | 9.84|
|MMLU-PRO (5-shot) | 32.25|