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---
language:
- en
license: apache-2.0
datasets:
- Open-Orca/SlimOrca
model-index:
- name: NEBULA-XB-v1.0
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: 56.66
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/NEBULA-XB-v1.0
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: 81.78
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/NEBULA-XB-v1.0
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: 60.98
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/NEBULA-XB-v1.0
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: 44.03
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/NEBULA-XB-v1.0
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: 77.66
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/NEBULA-XB-v1.0
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: 0.0
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/NEBULA-XB-v1.0
name: Open LLM Leaderboard
---
### TeeZee/NEBULA-XB-v1.03 ###
Experiment, can DUS be taken one or more steps further?
### Technical notes:
- pretrained model v03 finetuned on 50k entries from SlimOrca dataset
- 18 layers removed from both models of finetuned GALAXY-XB-v03
- model has 108 layers (((48-12)*2)-18)*2 = 108
- second step in scaling DUS procedure
### To evaluate
- model performance after merge, should be a little lover that GALAXY finetuned on 50k of slimorca
# [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_TeeZee__NEBULA-XB-v1.0)
| Metric |Value|
|---------------------------------|----:|
|Avg. |53.52|
|AI2 Reasoning Challenge (25-Shot)|56.66|
|HellaSwag (10-Shot) |81.78|
|MMLU (5-Shot) |60.98|
|TruthfulQA (0-shot) |44.03|
|Winogrande (5-shot) |77.66|
|GSM8k (5-shot) | 0.00|
|