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base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
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library_name: peft
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---
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# Model Card for Model ID
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<!-- Provide a quick summary of what the model is/does. -->
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### Model Description
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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### Model Sources [optional]
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<!-- Provide the basic links for the model. -->
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- **Repository:** [More Information Needed]
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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## Uses
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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### Direct Use
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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[More Information Needed]
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### Downstream Use [optional]
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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[More Information Needed]
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### Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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[More Information Needed]
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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[More Information Needed]
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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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## How to Get Started with the Model
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Use the code below to get started with the model.
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[More Information Needed]
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## Training Details
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### Training Data
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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[More Information Needed]
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### Training Procedure
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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#### Speeds, Sizes, Times [optional]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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## Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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#### Testing Data
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<!-- This should link to a Dataset Card if possible. -->
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[More Information Needed]
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#### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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#### Metrics
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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[More Information Needed]
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### Results
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[More Information Needed]
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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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).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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[More Information Needed]
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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[More Information Needed]
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## More Information [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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[More Information Needed]
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## Model Card Contact
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[More Information Needed]
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### Framework versions
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- PEFT 0.15.1
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---
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base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
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library_name: peft
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license: llama3.1
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# Model Card for Model ID
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<!-- Provide a quick summary of what the model is/does. -->
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RoGuard is a lightweight, modular evaluation framework for assessing the safety of fine-tuned language models. It provides structured evaluation using configurable prompts, labeled datasets, and outputs comprehensive metrics.
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# 📊 Model Benchmark Results
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- **Prompt Metrics**: These evaluate how well the model classifies or responds to potentially harmful **user inputs**
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- **Response Metrics**: These measure how well the model handles or generates **responses**, ensuring its outputs are safe and aligned.
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| Model / Metric | Prompt | | | | | Response | | | |
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|---------------------------|--------:|------:|------:|-------:|-------:|---------:|----------:|-------:|-------:|
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| | ToxicC. | OAI | Aegis | XSTest | WildP. | BeaverT. | SaferRLHF | WildR. | HarmB. |
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| LlamaGuard2-8B | 42.7 | 77.6 | 73.8 | 88.6 | 70.9 | 71.8 | 51.6 | 65.2 | 78.5 |
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| LlamaGuard3-8B | 50.9 | 79.4 | 74.8 | 88.3 | 70.1 | 69.7 | 53.7 | 70.2 | 84.9 |
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| MD-Judge-7B | - | - | - | - | - | 86.7 | 64.8 | 76.8 | 81.2 |
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| WildGuard-7B | 70.8 | 72.1 | 89.4 | 94.4 | 88.9 | 84.4 | 64.2 | 75.4 | 86.2 |
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| ShieldGemma-7B | 70.2 | 82.1 | 88.7 | 92.5 | 88.1 | 84.8 | 66.6 | 77.8 | 84.8 |
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| GPT-4o | 68.1 | 70.4 | 83.2 | 90.2 | 87.9 | 83.8 | 67.9 | 73.1 | 83.5 |
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| BingoGuard-phi3-3B | 72.5 | 72.8 | 90.0 | 90.8 | 88.9 | 86.2 | 69.9 | 79.7 | 85.1 |
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| BingoGuard-llama3.1-8B | 75.7 | 77.9 | 90.4 | 94.9 | 88.9 | 86.4 | 68.7 | 80.1 | 86.4 |
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| 🛡️ RoGuard | 75.8 | 70.5 | 91.1 | 90.2 | 88.7 | 87.5 | 69.7 | 80.0 | 80.7 |
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## 🔗 GitHub Repository
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You can find the full source code and evaluation framework on GitHub:
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👉 [Roblox/RoGuard on GitHub](https://github.com/Roblox/RoGuard)
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