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--- |
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license: mit |
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datasets: |
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- CarrotAI/ko-instruction-dataset |
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- CarrotAI/Korean-sharegpt-dataset |
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- CarrotAI/qa-ko-dataset |
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language: |
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- ko |
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pipeline_tag: text-generation |
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--- |
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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl) |
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## Model Details |
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์์ฑํ ํ๊ตญ์ด ๋ฐ์ดํฐ์
์ผ๋ก axolotl์ ์ด์ฉํ์ฌ ํ์ธํ๋ํ์์ต๋๋ค. |
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### Model Description |
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Qwen/Qwen2-1.5B-Instruct ๋ชจ๋ธ์ ์ด์ฉํ์ฌ ์์ฑํ์์ต๋๋ค. |
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### LogicKor |
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default |
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| Category | Single turn | Multi turn | |
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|---|---|---| |
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| ์ถ๋ก (Reasoning) | 4.14 | 2.29 | |
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| ์ํ(Math) | 2.43 | 1.14 | |
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| ๊ธ์ฐ๊ธฐ(Writing) | 6.43 | 7.86 | |
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| ์ฝ๋ฉ(Coding) | 5.14 | 4.57 | |
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| ์ดํด(Understanding) | 5.29 | 4.57 | |
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| ๋ฌธ๋ฒ(Grammar) | 3.71 | 1.29 | |
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| Category | Score | |
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|---|---| |
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| Single turn | 4.52 | |
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| Multi turn | 3.62 | |
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| Overall | 4.07 | |
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1-shot |
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| Category | Single turn | Multi turn | |
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|---|---|---| |
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| ์ถ๋ก (Reasoning) | 4.14 | 1.43 | |
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| ์ํ(Math) | 2.86 | 1.00 | |
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| ๊ธ์ฐ๊ธฐ(Writing) | 5.00 | 4.57 | |
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| ์ฝ๋ฉ(Coding) | 3.14 | 3.43 | |
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| ์ดํด(Understanding) | 4.29 | 3.71 | |
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| ๋ฌธ๋ฒ(Grammar) | 2.71 | 1.43 | |
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| Category | Score | |
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| Single turn | 3.69 | |
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| Multi turn | 2.60 | |
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| Overall | 3.14 | |
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cot-1-shot |
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| Category | Single turn | Multi turn | |
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|---|---|---| |
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| ์ถ๋ก (Reasoning) | 3.00 | 2.86 | |
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| ์ํ(Math) | 1.57 | 1.00 | |
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| ๊ธ์ฐ๊ธฐ(Writing) | 5.86 | 6.00 | |
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| ์ฝ๋ฉ(Coding) | 4.29 | 4.14 | |
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| ์ดํด(Understanding) | 3.43 | 3.43 | |
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| ๋ฌธ๋ฒ(Grammar) | 3.00 | 1.14 | |
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| Category | Score | |
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|---|---| |
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| Single turn | 3.52 | |
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| Multi turn | 3.10 | |
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| Overall | 3.31 | |
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### Applications |
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This fine-tuned model is particularly suited for [mention applications, e.g., chatbots, question-answering systems, etc.]. Its enhanced capabilities ensure more accurate and contextually appropriate responses in these domains. |
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### Limitations and Considerations |
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While our fine-tuning process has optimized the model for specific tasks, it's important to acknowledge potential limitations. The model's performance can still vary based on the complexity of the task and the specificities of the input data. Users are encouraged to evaluate the model thoroughly in their specific context to ensure it meets their requirements. |
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``` |
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@article{Carrot-Ko-2.1B-Instruct, |
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title={CarrotAI/Carrot-Ko-2.1B-Instruct Card}, |
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author={CarrotAI (L, GEUN)}, |
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year={2024}, |
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url = {https://huggingface.co./CarrotAI/Carrot-2.1B-Instruct} |
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} |
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