metadata
license: apache-2.0
datasets:
- athirdpath/Merge_Glue
model-index:
- name: NEBULA-XB-v1.0_SFT_2_epoch
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: 63.05
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/NEBULA-XB-v1.0_SFT_2_epoch
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: 85.07
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/NEBULA-XB-v1.0_SFT_2_epoch
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: 65.41
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/NEBULA-XB-v1.0_SFT_2_epoch
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: 52.06
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/NEBULA-XB-v1.0_SFT_2_epoch
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: 82.24
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/NEBULA-XB-v1.0_SFT_2_epoch
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: 0.3
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/NEBULA-XB-v1.0_SFT_2_epoch
name: Open LLM Leaderboard
TeeZee/NEBULA-XB-v1.0_SFT_2_epoch
Experiment, can DUS be taken one or more steps further?
Technical notes:
- pretrained model NEBULA-XB-v1.0 finetuned on 30k entries from Merge_Glue 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
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 58.02 |
AI2 Reasoning Challenge (25-Shot) | 63.05 |
HellaSwag (10-Shot) | 85.07 |
MMLU (5-Shot) | 65.41 |
TruthfulQA (0-shot) | 52.06 |
Winogrande (5-shot) | 82.24 |
GSM8k (5-shot) | 0.30 |