---
library_name: transformers
tags: []
---

# Model Card for Model ID

<!-- Provide a quick summary of what the model is/does. -->



## Model Details



## Evaluation



<!-- These are the evaluation metrics being used, ideally with a description of why. -->

|            | Qwen2.5-0.5B-Instruct | finetuning-model       |
|:-----------|----------------------:|-----------------------:|
| mmlu       |  0.4592               | 0.4614                 |



| llm-jp-eval| Qwen2.5-0.5B-Instruct | finetuning-model       |
|:-----------|----------------------:|-----------------------:|
| AVG        |  0.3037               | 0.3176                 |
| CG         |  0                    | 0                      |
| EL         |  0.2637               | 0.3146                 |
| FA         |  0.0386               | 0.0419                 |
| HE         |  0.2700               | 0.3250                 |
| MC         |  0.4033               | 0.3733                 |
| MR         |  0.0900               | 0.2700                 |
| MT         |  0.6148               | 0.6691                 |
| NLI        |  0.5460               | 0.3180                 |
| QA         |  0.2608               | 0.2791                 |
| RC         |  0.5495               | 0.5847                 |
### Results

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#### Summary



## Model Examination [optional]

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## Environmental Impact

<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->

Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).

- **Hardware Type:** [More Information Needed]
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## Technical Specifications [optional]

### Model Architecture and Objective

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### Compute Infrastructure

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#### Hardware

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#### Software

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## Citation [optional]

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## Glossary [optional]

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