PeroVazPT-BR Classifier
Model Description
The PeroVazPT-BR Classifier is designed to classify text between European Portuguese (PT) and Brazilian Portuguese (BR).
This model is a fine-tuned version of prajjwal1/bert-tiny on the VeraCruz Dataset. The model was trained on the VeraCruz Dataset, a collection of text samples from both languages. The model was trained on a total of 500,000 examples, a evenly split between European Portuguese and Brazilian Portuguese, ensuring a balanced representation of both language variants.
It achieves the following results on an evaluation set of 50,000 examples:
- Loss: 0.1791
- Accuracy: 0.9461
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 256
- eval_batch_size: 256
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- steps: 2500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.4772 | 0.06 | 500 | 0.2501 | 0.9080 |
| 0.3412 | 0.13 | 1000 | 0.2275 | 0.9135 |
| 0.3122 | 0.19 | 1500 | 0.2578 | 0.9014 |
| 0.2975 | 0.25 | 2000 | 0.1992 | 0.9396 |
| 0.2877 | 0.31 | 2500 | 0.1791 | 0.9461 |
Framework versions
- Transformers 4.40.0.dev0
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.2
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