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--- |
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license: mit |
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datasets: |
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- MuafiraThasni/DocLayNet-base_paragraphs_encoded_ml512 |
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language: |
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- en |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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- f1 |
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tags: |
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- document understanding |
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- document layout detection |
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- nlp |
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- doclaynet |
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- RoBERTa |
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--- |
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<!-- Provide a quick summary of what the model is/does. --> |
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This is a document layout classification model. This model is a fine-tuned version of nielsr/lilt-xlm-roberta-base with the DocLayNet base dataset. |
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## Model Details |
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### Model Description |
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- **Developed by:** Muafira Thasni |
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- **Language(s) (NLP):** English |
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- **License:** MIT |
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- **Finetuned from model:** nielsr/lilt-xlm-roberta-base |
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## Uses |
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### Training Procedure --> |
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#### Training Hyperparameters --> |
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#### Testing Data --> |
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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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## Environmental Impact |
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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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## 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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#### Hardware |
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#### Software |
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## Citation [optional] |
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