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--- |
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base_model: |
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- prithivMLmods/Llama-3.1-8B-Open-SFT |
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tags: |
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- text-generation-inference |
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- transformers |
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- unsloth |
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- Llama3 |
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- trl |
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- COT |
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- Reasoning |
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license: apache-2.0 |
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language: |
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- en |
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datasets: |
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- Daemontatox/LongCOT-Reason |
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metrics: |
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- accuracy |
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- character |
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- competition_math |
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- code_eval |
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library_name: transformers |
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pipeline_tag: text-generation |
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model-index: |
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- name: AetherDrake-SFT |
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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: IFEval (0-Shot) |
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type: HuggingFaceH4/ifeval |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: inst_level_strict_acc and prompt_level_strict_acc |
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value: 48.13 |
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name: strict accuracy |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Daemontatox/AetherDrake-SFT |
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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: BBH (3-Shot) |
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type: BBH |
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args: |
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num_few_shot: 3 |
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metrics: |
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- type: acc_norm |
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value: 27.14 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Daemontatox/AetherDrake-SFT |
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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: MATH Lvl 5 (4-Shot) |
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type: hendrycks/competition_math |
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args: |
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num_few_shot: 4 |
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metrics: |
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- type: exact_match |
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value: 14.65 |
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name: exact match |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Daemontatox/AetherDrake-SFT |
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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: GPQA (0-shot) |
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type: Idavidrein/gpqa |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: acc_norm |
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value: 9.4 |
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name: acc_norm |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Daemontatox/AetherDrake-SFT |
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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: MuSR (0-shot) |
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type: TAUR-Lab/MuSR |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: acc_norm |
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value: 9.97 |
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name: acc_norm |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Daemontatox/AetherDrake-SFT |
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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-PRO (5-shot) |
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type: TIGER-Lab/MMLU-Pro |
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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: 27.77 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Daemontatox/AetherDrake-SFT |
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name: Open LLM Leaderboard |
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--- |
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# AetherDrake-SFT |
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- **Developed by:** Daemontatox |
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- **License:** Apache 2.0 |
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- **Finetuned Using:** [Unsloth](https://github.com/unslothai/unsloth), Hugging Face Transformers, and TRL Library |
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## Model Overview |
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The **AetherDrake-SFT Model** is an advanced AI system optimized for logical reasoning, multi-step problem-solving, and decision-making tasks. Designed with efficiency and accuracy in mind, it employs a structured system prompt to ensure high-quality answers through a transparent and iterative thought process. |
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### System Prompt and Workflow |
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This model operates using an innovative reasoning framework structured around the following steps: |
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1. **Initial Thought:** |
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The model uses `<Thinking>` tags to reason step-by-step and craft its best possible response. |
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Example: |
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2. **Self-Critique:** |
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It evaluates its initial response within `<Critique>` tags, focusing on: |
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- **Accuracy:** Is it factually correct and verifiable? |
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- **Clarity:** Is it clear and free of ambiguity? |
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- **Completeness:** Does it fully address the request? |
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- **Improvement:** What can be enhanced? |
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Example: |
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3. **Revision:** |
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Based on the critique, the model refines its response within `<Revising>` tags. |
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Example: |
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4. **Final Response:** |
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The revised response is presented clearly within `<Final>` tags. |
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Example: |
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5. **Tag Innovation:** |
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When needed, the model creates and defines new tags for better structuring or clarity, ensuring consistent usage. |
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Example: |
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### Key Features |
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- **Structured Reasoning:** Transparent, multi-step approach for generating and refining answers. |
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- **Self-Improvement:** Built-in critique and revision ensure continuous response enhancement. |
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- **Clarity and Adaptability:** Tagging system provides organized, adaptable responses tailored to user needs. |
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- **Creative Flexibility:** Supports dynamic problem-solving with the ability to introduce new tags and concepts. |
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--- |
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## Use Cases |
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The model is designed for various domains, including: |
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1. **Research and Analysis:** Extracting insights and providing structured explanations. |
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2. **Education:** Assisting with tutoring by breaking down complex problems step-by-step. |
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3. **Problem-Solving:** Offering logical and actionable solutions for multi-step challenges. |
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4. **Content Generation:** Producing clear, well-organized creative or professional content. |
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--- |
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## Training Details |
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- **Frameworks:** |
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- [Unsloth](https://github.com/unslothai/unsloth) for accelerated training. |
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- Hugging Face Transformers and the TRL library for reinforcement learning with human feedback (RLHF). |
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- **Dataset:** Finetuned on diverse reasoning-focused tasks, including logical puzzles, mathematical problems, and commonsense reasoning scenarios. |
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- **Hardware Efficiency:** |
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- Trained with bnb-4bit precision for reduced memory usage. |
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- Optimized training pipeline achieving 2x faster development cycles. |
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--- |
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## Limitations |
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- **Arithmetic Equations** Model might hallucinate in the middle of thinking and using Arithmetic Equations as it wasn't trained on latex equations. |
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- **Very Complex problems** Model has a tendency to get side tracked when asked long and complex problems and might answer with uncertainty. |
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## Ethical Considerations |
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- **Transparency:** Responses are structured for verifiability through tagging. |
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- **Bias Mitigation:** Includes self-critique to minimize biases and ensure fairness. |
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- **Safe Deployment:** Users are encouraged to evaluate outputs to prevent harm or misinformation. |
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--- |
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## License |
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This model is distributed under the Apache 2.0 license, allowing users to use, modify, and share it in compliance with the license terms. |
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--- |
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## Acknowledgments |
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Special thanks to: |
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- [Unsloth](https://github.com/unslothai/unsloth) for accelerated training workflows. |
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- Hugging Face for their powerful tools and libraries. |
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--- |
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Experience the **AetherDrake-SFT**, leveraging its structured reasoning and self-improvement capabilities for any task requiring advanced AI reasoning. |
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) |
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/Daemontatox__AetherDrake-SFT-details)! |
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Summarized results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/contents/viewer/default/train?q=Daemontatox/AetherDrake-SFT)! |
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| Metric |% Value| |
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|-------------------|------:| |
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|Avg. | 22.84| |
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|IFEval (0-Shot) | 48.13| |
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|BBH (3-Shot) | 27.14| |
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|MATH Lvl 5 (4-Shot)| 14.65| |
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|GPQA (0-shot) | 9.40| |
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|MuSR (0-shot) | 9.97| |
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|MMLU-PRO (5-shot) | 27.77| |
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