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README.md
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---
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license: apache-2.0
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---
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---
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language:
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- en
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license: apache-2.0
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tags:
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- not-for-all-audiences
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datasets:
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- Intel/orca_dpo_pairs
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- athirdpath/DPO_Pairs-Roleplay-Alpaca-NSFW
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- Open-Orca/SlimOrca
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- MinervaAI/Aesir-Preview
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- allenai/ultrafeedback_binarized_cleaned
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model-index:
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- name: NEBULA-23B-v1.0
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results:
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: AI2 Reasoning Challenge (25-Shot)
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type: ai2_arc
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config: ARC-Challenge
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split: test
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args:
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num_few_shot: 25
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metrics:
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- type: acc_norm
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value: 66.72
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/NEBULA-23B-v1.0
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: HellaSwag (10-Shot)
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type: hellaswag
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split: validation
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args:
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num_few_shot: 10
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metrics:
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- type: acc_norm
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value: 86.98
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/NEBULA-23B-v1.0
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MMLU (5-Shot)
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type: cais/mmlu
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config: all
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 65.4
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/NEBULA-23B-v1.0
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: TruthfulQA (0-shot)
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type: truthful_qa
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config: multiple_choice
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split: validation
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args:
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num_few_shot: 0
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metrics:
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- type: mc2
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value: 57.6
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/NEBULA-23B-v1.0
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: Winogrande (5-shot)
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type: winogrande
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config: winogrande_xl
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split: validation
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 82.95
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/NEBULA-23B-v1.0
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: GSM8k (5-shot)
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type: gsm8k
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config: main
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 0.0
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/NEBULA-23B-v1.0
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name: Open LLM Leaderboard
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---
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# NEBULA-23.8B-v1.0
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![image/png](https://huggingface.co/TeeZee/NEBULA-23B-v1.0/resolve/main/NEBULA-23B-v1.0.jpg)
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## Technical notes
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- 108 layers,DUS procedure, mistral(32)->SOLAR(48)->GALAXY(72)->NEBULA(108)
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- 23.8B parameters
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- model created as a extension of depth upscaling procedure used for SOLAR by upstage
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## Results
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- model can and will produce NSFW content
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- GSM8k evaluation seems to be often broken, HellaSwag, Winograde and TQA show that its a smart model
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- RP and ERP work surprisingly good and I didn't encounter any GPTisms yet
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- lower memory footprint than 20B and 23B models
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- follows character card very well
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- NSFW output feels fresh comparing to existing models
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## Finetuning for RP
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- SFT using MinervaAI/Aesir-Preview dataset, 10 epochs
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- DPO using athirdpath/DPO_Pairs-Roleplay-Alpaca-NSFW dataset, 1 epoch
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- SFT using 1xAda6000, 10h
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- DPO using 1x3090, 30h
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- jupyter notebooks or mergekit configs for anyone wanting to reproduce/reuse scripts - just drop me a message
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## Prompt template
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- Alpaca
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- chat template is embedded in tokenizer config, should load automatically
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All comments are greatly appreciated, download, test and if you appreciate my work, consider buying me my fuel:
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<a href="https://www.buymeacoffee.com/TeeZee" target="_blank"><img src="https://cdn.buymeacoffee.com/buttons/v2/default-yellow.png" alt="Buy Me A Coffee" style="height: 60px !important;width: 217px !important;" ></a>
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_TeeZee__NEBULA-23B-v1.0)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |59.94|
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|AI2 Reasoning Challenge (25-Shot)|66.72|
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|HellaSwag (10-Shot) |86.98|
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|MMLU (5-Shot) |65.40|
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|TruthfulQA (0-shot) |57.60|
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|Winogrande (5-shot) |82.95|
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|GSM8k (5-shot) | 0.00|
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