language, license, datasets, model-index

language	license	datasets	model-index
en	apache-2.0	Open-Orca/SlimOrca	name results NEBULA-XB-v1.0 task dataset metrics source type name text-generation Text Generation name type config split args AI2 Reasoning Challenge (25-Shot) ai2_arc ARC-Challenge test num_few_shot 25 type value name acc_norm 56.66 normalized accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/NEBULA-XB-v1.0 Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type split args HellaSwag (10-Shot) hellaswag validation num_few_shot 10 type value name acc_norm 81.78 normalized accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/NEBULA-XB-v1.0 Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type config split args MMLU (5-Shot) cais/mmlu all test num_few_shot 5 type value name acc 60.98 accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/NEBULA-XB-v1.0 Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type config split args TruthfulQA (0-shot) truthful_qa multiple_choice validation num_few_shot 0 type value mc2 44.03 url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/NEBULA-XB-v1.0 Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type config split args Winogrande (5-shot) winogrande winogrande_xl validation num_few_shot 5 type value name acc 77.66 accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/NEBULA-XB-v1.0 Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type config split args GSM8k (5-shot) gsm8k main test num_few_shot 5 type value name acc 0.0 accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/NEBULA-XB-v1.0 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

Detailed results can be found here

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