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---
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]
<!-- Relevant interpretability work for the model goes here -->
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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]
- **Hours used:** [More Information Needed]
- **Cloud Provider:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
## 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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**BibTeX:**
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**APA:**
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## Glossary [optional]
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## More Information [optional]
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## Model Card Authors [optional]
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## Model Card Contact
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