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# HateBERTimbau
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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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### Training Data
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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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## Evaluation
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### Testing Data, Factors & Metrics
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#### Testing Data
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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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## BibTeX Citation
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# HateBERTimbau
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HateBERTimbau is a transformer-based encoder model for identifying hate speech in Portuguese social media text. It is a fine-tuned version of the [BERTimbau](https://huggingface.co/neuralmind/bert-large-portuguese-cased) model, retrained on a dataset of 229,103 tweets specifically focused on potential hate speech.
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## Model Details
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### Training Data
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229,103 tweets associated with offensive content were used
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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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#### Training Hyperparameters
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- Batch Size: 4 samples
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- Epochs: 100
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- Learning Rate: 5e-5 with Adam optimizer
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- Maximum Sequence Length: 512 sentence pieces
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## Evaluation
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### Testing Data
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### Results
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## BibTeX Citation
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