| | --- |
| | 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 |
| |
|
| | | 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. |
| |
|
| | format is this: |
| |
|
| | ``` |
| | Instruction: <your instruction> |
| | Reasoning: // starting from here, the model will start to generate the resoning and output |
| | Output: |
| | ``` |
| |
|
| | # Uploaded model |
| |
|
| | - **Developed by:** appvoid |
| | - **License:** apache-2.0 |
| | - **Finetuned from model :** appvoid/arco |
| |
|
| | 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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