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| library_name: transformers |
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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 Details |
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| ### Model Description |
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| <!-- Provide a longer summary of what this model is. --> |
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| This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. |
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| - **Developed by:** The [NERT Lab](http://nert.georgetown.edu/) + Lauren Levine at Georgetown University. |
| - **Primary Maintainer:** Wesley Scivetti |
| - **Model type:** Fine-tuned XLM-R for SNACS token/span classification. |
| - **Language(s):** Trained on Chinese, English, Gujarati, Hindi, and Japanese. Potentially some zero-shot capabilities in other languages. |
| - **License:** [More Information Needed] |
| - **Finetuned from model:** XLM-R Large |
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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] |
| - **Paper:** [Multilingual Supervision Improves Semantic Disambiguation of Adpositions (LREC-COLING 2024)](https://aclanthology.org/2025.coling-main.247/) |
| - **Demo:** [Running on Huggingface Spaces!](https://huggingface.co/spaces/WesScivetti/SNACS_English_Demo) |
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| ## Uses |
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| SNACS Classification tasks, which assign semantic labels to adpositions and case markers across languages. |
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| ## Bias, Risks, and Limitations |
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| Training was limited to the five languages listed above. Additional multilingual zero-shot capabilities are not empirically verified. |
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| ## How 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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| Fine-tuning for token classification with robust hyperparameter search. See paper for details. |
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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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| #### 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] |
| - **Hours used:** [More Information Needed] |
| - **Cloud Provider:** [More Information Needed] |
| - **Compute Region:** [More Information Needed] |
| - **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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| ## 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] |
