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---
license: mit
library_name: transformers
tags:
- mergekit
- merge
- math
- llama3
- physics
- chemistry
- biology
- dolphin
base_model:
- cognitivecomputations/dolphin-2.9-llama3-8b
- Weyaxi/Einstein-v6.1-Llama3-8B
- Locutusque/llama-3-neural-chat-v1-8b
model-index:
- name: CosmicBun-8B
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: AI2 Reasoning Challenge (25-Shot)
type: ai2_arc
config: ARC-Challenge
split: test
args:
num_few_shot: 25
metrics:
- type: acc_norm
value: 61.86
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aloobun/CosmicBun-8B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: HellaSwag (10-Shot)
type: hellaswag
split: validation
args:
num_few_shot: 10
metrics:
- type: acc_norm
value: 84.29
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aloobun/CosmicBun-8B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU (5-Shot)
type: cais/mmlu
config: all
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 65.53
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aloobun/CosmicBun-8B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: TruthfulQA (0-shot)
type: truthful_qa
config: multiple_choice
split: validation
args:
num_few_shot: 0
metrics:
- type: mc2
value: 54.08
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aloobun/CosmicBun-8B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: Winogrande (5-shot)
type: winogrande
config: winogrande_xl
split: validation
args:
num_few_shot: 5
metrics:
- type: acc
value: 78.85
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aloobun/CosmicBun-8B
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GSM8k (5-shot)
type: gsm8k
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 68.23
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=aloobun/CosmicBun-8B
name: Open LLM Leaderboard
---
# model
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
### 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 [Locutusque/llama-3-neural-chat-v1-8b](https://huggingface.co/Locutusque/llama-3-neural-chat-v1-8b) as a base.
### Models Merged
The following models were included in the merge:
* [cognitivecomputations/dolphin-2.9-llama3-8b](https://huggingface.co/cognitivecomputations/dolphin-2.9-llama3-8b)
* [Weyaxi/Einstein-v6.1-Llama3-8B](https://huggingface.co/Weyaxi/Einstein-v6.1-Llama3-8B)
### Configuration
The following YAML configuration was used to produce this model:
```yaml
base_model: Locutusque/llama-3-neural-chat-v1-8b
dtype: bfloat16
merge_method: dare_ties
parameters:
int8_mask: 1.0
normalize: 0.0
slices:
- sources:
- layer_range: [0, 4]
model: cognitivecomputations/dolphin-2.9-llama3-8b
parameters:
density: 1.0
weight: 0.6
- layer_range: [0, 4]
model: Weyaxi/Einstein-v6.1-Llama3-8B
parameters:
density: 0.6
weight: 0.5
- layer_range: [0, 4]
model: Locutusque/llama-3-neural-chat-v1-8b
parameters:
density: 1.0
weight: 0.5
- sources:
- layer_range: [4, 8]
model: cognitivecomputations/dolphin-2.9-llama3-8b
parameters:
density: 0.8
weight: 0.1
- layer_range: [4, 8]
model: Weyaxi/Einstein-v6.1-Llama3-8B
parameters:
density: 1.0
weight: 0.2
- layer_range: [4, 8]
model: Locutusque/llama-3-neural-chat-v1-8b
parameters:
density: 1.0
weight: 0.7
- sources:
- layer_range: [8, 12]
model: cognitivecomputations/dolphin-2.9-llama3-8b
parameters:
density: 0.7
weight: 0.1
- layer_range: [8, 12]
model: Weyaxi/Einstein-v6.1-Llama3-8B
parameters:
density: 0.7
weight: 0.2
- layer_range: [8, 12]
model: Locutusque/llama-3-neural-chat-v1-8b
parameters:
density: 0.7
weight: 0.6
- sources:
- layer_range: [12, 16]
model: cognitivecomputations/dolphin-2.9-llama3-8b
parameters:
density: 0.9
weight: 0.2
- layer_range: [12, 16]
model: Weyaxi/Einstein-v6.1-Llama3-8B
parameters:
density: 0.6
weight: 0.6
- layer_range: [12, 16]
model: Locutusque/llama-3-neural-chat-v1-8b
parameters:
density: 0.7
weight: 0.3
- sources:
- layer_range: [16, 20]
model: cognitivecomputations/dolphin-2.9-llama3-8b
parameters:
density: 1.0
weight: 0.2
- layer_range: [16, 20]
model: Weyaxi/Einstein-v6.1-Llama3-8B
parameters:
density: 1.0
weight: 0.2
- layer_range: [16, 20]
model: Locutusque/llama-3-neural-chat-v1-8b
parameters:
density: 0.9
weight: 0.4
- sources:
- layer_range: [20, 24]
model: cognitivecomputations/dolphin-2.9-llama3-8b
parameters:
density: 0.7
weight: 0.2
- layer_range: [20, 24]
model: Weyaxi/Einstein-v6.1-Llama3-8B
parameters:
density: 0.9
weight: 0.3
- layer_range: [20, 24]
model: Locutusque/llama-3-neural-chat-v1-8b
parameters:
density: 1.0
weight: 0.4
- sources:
- layer_range: [24, 28]
model: cognitivecomputations/dolphin-2.9-llama3-8b
parameters:
density: 1.0
weight: 0.4
- layer_range: [24, 28]
model: Weyaxi/Einstein-v6.1-Llama3-8B
parameters:
density: 0.8
weight: 0.2
- layer_range: [24, 28]
model: Locutusque/llama-3-neural-chat-v1-8b
parameters:
density: 0.9
weight: 0.4
- sources:
- layer_range: [28, 32]
model: cognitivecomputations/dolphin-2.9-llama3-8b
parameters:
density: 1.0
weight: 0.3
- layer_range: [28, 32]
model: Weyaxi/Einstein-v6.1-Llama3-8B
parameters:
density: 0.9
weight: 0.2
- layer_range: [28, 32]
model: Locutusque/llama-3-neural-chat-v1-8b
parameters:
density: 1.0
weight: 0.3
```
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_aloobun__CosmicBun-8B)
| Metric |Value|
|---------------------------------|----:|
|Avg. |68.81|
|AI2 Reasoning Challenge (25-Shot)|61.86|
|HellaSwag (10-Shot) |84.29|
|MMLU (5-Shot) |65.53|
|TruthfulQA (0-shot) |54.08|
|Winogrande (5-shot) |78.85|
|GSM8k (5-shot) |68.23|
|