--- language: - en license: apache-2.0 tags: - not-for-all-audiences datasets: - Intel/orca_dpo_pairs - athirdpath/DPO_Pairs-Roleplay-Alpaca-NSFW - Open-Orca/SlimOrca - MinervaAI/Aesir-Preview - allenai/ultrafeedback_binarized_cleaned model-index: - name: NEBULA-23B-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: 66.72 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/NEBULA-23B-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: 86.98 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/NEBULA-23B-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: 65.4 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/NEBULA-23B-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: 57.6 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/NEBULA-23B-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: 82.95 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=TeeZee/NEBULA-23B-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-23B-v1.0 name: Open LLM Leaderboard --- # NEBULA-23.8B-v1.0 ![image/png](https://huggingface.co/TeeZee/NEBULA-23B-v1.0/resolve/main/NEBULA-23B-v1.0.jpg) ## Technical notes - 108 layers,DUS procedure, mistral(32)->SOLAR(48)->GALAXY(72)->NEBULA(108) - 23.8B parameters - model created as a extension of depth upscaling procedure used for SOLAR by upstage ## Results - model can and will produce NSFW content - GSM8k evaluation seems to be often broken, HellaSwag, Winograde and TQA show that its a smart model - RP and ERP work surprisingly good and I didn't encounter any GPTisms yet - lower memory footprint than 20B and 23B models - follows character card very well - NSFW output feels fresh comparing to existing models ## Finetuning for RP - SFT using MinervaAI/Aesir-Preview dataset, 10 epochs - DPO using athirdpath/DPO_Pairs-Roleplay-Alpaca-NSFW dataset, 1 epoch - SFT using 1xAda6000, 10h - DPO using 1x3090, 30h - jupyter notebooks or mergekit configs for anyone wanting to reproduce/reuse scripts - just drop me a message ## Prompt template - Alpaca - chat template is embedded in tokenizer config, should load automatically ## Context size - 4096 All comments are greatly appreciated, download, test and if you appreciate my work, consider buying me my fuel: Buy Me A Coffee # [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-23B-v1.0) | Metric |Value| |---------------------------------|----:| |Avg. |59.94| |AI2 Reasoning Challenge (25-Shot)|66.72| |HellaSwag (10-Shot) |86.98| |MMLU (5-Shot) |65.40| |TruthfulQA (0-shot) |57.60| |Winogrande (5-shot) |82.95| |GSM8k (5-shot) | 0.00|