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--- |
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license: cc-by-sa-4.0 |
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language: |
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- ts |
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- nr |
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- ve |
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- xh |
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- zu |
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- af |
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- en |
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- st |
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- ss |
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- nso |
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- tn |
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library_name: transformers |
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pipeline_tag: text-classification |
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datasets: |
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- dsfsi/vukuzenzele-monolingual |
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metrics: |
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- accuracy |
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tags: |
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- lid |
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- Language Identification |
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- African Languages |
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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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This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1). |
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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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- **Developed by:** Thapelo Sindane, Vukosi Marivate |
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- **Shared by [optional]:** DSFSI |
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- **Model type:** BERT |
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- **Language(s) (NLP):** Sepedi (nso), Sesotho(sot), Setswana(tsn), Xitsonga(tso), Isindebele(nr), Tshivenda(ven), IsiXhosa(xho), IsiZulu(zul), IsiSwati(ssw), Afrikaans(af), and English(en) |
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- **License:** CC-BY-SA |
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- **Finetuned from model [optional]:** N/A |
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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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Models must be used for language identification of the South African languages identified above |
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### Direct Use |
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LID for low-resourced languages |
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### Downstream Use [optional] |
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Language data filtering and identification |
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[More Information Needed] |
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### Out-of-Scope Use |
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Language detection in code-switched data. |
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[More Information Needed] |
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## Bias, Risks, and Limitations |
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Requires GPU to run fast |
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[More Information Needed] |
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### Recommendations |
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Do not use for sensitive tasks. Model at an infant stage. |
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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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## Training Details |
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### Training Data |
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The source data used to train the model came from the paper 'Preparing Vuk...' referenced below: |
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* Lastrucci, R., Dzingirai, I., Rajab, J., Madodonga, A., Shingange, M., Njini, D. and Marivate, V., 2023. Preparing the Vuk'uzenzele and ZA-gov-multilingual South African multilingual corpora. arXiv preprint arXiv:2303.03750. |
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Number of sentences in datasets: |
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'nso': 5007, |
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'tsn': 4851, |
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'sot': 5075, |
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'xho': 5219, |
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'zul': 5103, |
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'nbl': 5600, |
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'ssw': 5210, |
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'ven': 5119, |
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'tso': 5193, |
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'af': 5252, |
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'eng': 5552 |
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Train Test split: Train: 70% of minimum, 15% of minimum size, Dev: remaining sample |
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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] |
