---
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: 0.0500
- Accuracy: 0.7415
- F1: 0.6919
- Recall: 0.7472
- Precision: 0.6838

## 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: 150
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Recall | Precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
| 0.0667        | 1.0   | 18   | 0.0661          | 0.5536   | 0.4531 | 0.4520 | 0.4571    |
| 0.0624        | 2.0   | 36   | 0.0646          | 0.6696   | 0.5743 | 0.5752 | 0.5736    |
| 0.0625        | 3.0   | 54   | 0.0628          | 0.7321   | 0.6510 | 0.6510 | 0.6510    |
| 0.0612        | 4.0   | 72   | 0.0603          | 0.7411   | 0.6733 | 0.6795 | 0.6687    |
| 0.0566        | 5.0   | 90   | 0.0568          | 0.7768   | 0.7184 | 0.7260 | 0.7125    |
| 0.0544        | 6.0   | 108  | 0.0530          | 0.7589   | 0.7216 | 0.7588 | 0.7119    |
| 0.0488        | 7.0   | 126  | 0.0497          | 0.8214   | 0.7812 | 0.8010 | 0.7688    |
| 0.0398        | 8.0   | 144  | 0.0498          | 0.7946   | 0.7629 | 0.8054 | 0.75      |
| 0.0276        | 9.0   | 162  | 0.0540          | 0.8125   | 0.7681 | 0.7838 | 0.7575    |
| 0.0184        | 10.0  | 180  | 0.0674          | 0.7679   | 0.7156 | 0.7312 | 0.7065    |


### Framework versions

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