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---
license: mit
widget:
- text: "Demanda por fundos de <mask> para crianças cresce em 2022"
example_title: "Exemplo 1"
- text: "Havia uma <mask> no meio do caminho"
example_title: "Exemplo 2"
- text: "Na verdade, começar a <mask> cedo é ideal para ter um bom dinheiro no futuro"
example_title: "Exemplo 3"
- text: "Mitos e verdades sobre o <mask>. Doença que mais mata mulheres no Brasil."
example_title: "Exemplo 4"
tags:
- generated_from_trainer
model-index:
- name: tgf-xlm-roberta-base-pt-br
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# tgf-xlm-roberta-base-pt-br
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 64
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 2
- mixed_precision_training: Native AMP
### Training results
### Framework versions
- Transformers 4.23.1
- Pytorch 1.11.0a0+b6df043
- Datasets 2.6.1
- Tokenizers 0.13.1
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