---
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