| --- |
| base_model: appvoid/arco |
| language: |
| - en |
| license: apache-2.0 |
| tags: |
| - text-generation-inference |
| - transformers |
| - unsloth |
| - llama |
| - trl |
| - sft |
| --- |
| |
| experimental model to expose arco to some reasoning |
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| after some research i notice i was finetuning models with super high lr, further models should be better since will maintain most of the power of arco |
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| | Task | Score | Metric | |
| |--------------|-------|-----------| |
| | ARC Challenge| 0.3473| acc_norm | |
| | HellaSwag | 0.5986| acc_norm | |
| | MMLU | 0.2489| acc | |
| | PIQA | 0.7318| acc_norm | |
| | Winogrande | 0.6259| acc | |
| |
| This table presents the extracted scores in a clear, tabular format. The "Task" column shows the name of each benchmark, the "Score" column displays the corresponding value, and the "Metric" column indicates whether the score is acc_norm or acc. |
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| format is this: |
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| ``` |
| Instruction: <your instruction> |
| Reasoning: // starting from here, the model will start to generate the resoning and output |
| Output: |
| ``` |
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| # Uploaded model |
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| - **Developed by:** appvoid |
| - **License:** apache-2.0 |
| - **Finetuned from model :** appvoid/arco |
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| This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. |
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| [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth) |
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