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

# LVI_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: 0.2393
- Accuracy: 0.9428
- F1: 0.9445
- Precision: 0.9182
- Recall: 0.9723

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.1736        | 1.0   | 3217  | 0.1532          | 0.9615   | 0.9618 | 0.955     | 0.9686 |
| 0.1105        | 2.0   | 6434  | 0.1464          | 0.9629   | 0.9630 | 0.9582    | 0.9679 |
| 0.0984        | 3.0   | 9651  | 0.2067          | 0.9525   | 0.9511 | 0.9786    | 0.9251 |
| 0.0996        | 4.0   | 12868 | 0.1873          | 0.9608   | 0.9610 | 0.9569    | 0.9651 |
| 0.17          | 5.0   | 16085 | 0.2393          | 0.9428   | 0.9445 | 0.9182    | 0.9723 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2