---
library_name: transformers
license: mit
base_model: neuralmind/bert-base-portuguese-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
- precision
model-index:
- name: neuralmind/bert-base-portuguese-cased
  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. -->

# neuralmind/bert-base-portuguese-cased

This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0505
- Accuracy: 0.7211
- F1: 0.6737
- Recall: 0.7341
- Precision: 0.6706

## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 5151
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 120
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Recall | Precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
| 0.0685        | 1.0   | 18   | 0.0667          | 0.3571   | 0.3563 | 0.4877 | 0.4864    |
| 0.0642        | 2.0   | 36   | 0.0655          | 0.5268   | 0.5020 | 0.5461 | 0.5354    |
| 0.0629        | 3.0   | 54   | 0.0641          | 0.6607   | 0.6052 | 0.6253 | 0.6036    |
| 0.0614        | 4.0   | 72   | 0.0618          | 0.6964   | 0.6569 | 0.6942 | 0.6551    |
| 0.0583        | 5.0   | 90   | 0.0584          | 0.7054   | 0.6773 | 0.7339 | 0.6816    |
| 0.0549        | 6.0   | 108  | 0.0548          | 0.7321   | 0.6930 | 0.7295 | 0.6862    |
| 0.048         | 7.0   | 126  | 0.0553          | 0.7768   | 0.7124 | 0.7148 | 0.7102    |
| 0.0391        | 8.0   | 144  | 0.0521          | 0.7768   | 0.7460 | 0.7933 | 0.7360    |
| 0.032         | 9.0   | 162  | 0.0523          | 0.7679   | 0.7208 | 0.7424 | 0.7103    |
| 0.0222        | 10.0  | 180  | 0.0585          | 0.7946   | 0.7354 | 0.7381 | 0.7329    |
| 0.0181        | 11.0  | 198  | 0.0809          | 0.8036   | 0.7083 | 0.6880 | 0.7561    |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0